Abstract:

This paper investigates retirement patterns of married couples in Belgium. We use social security administrative data over the years 2003-2017 and employ a discrete choice model to predict retirement behavior. In particular, we focus on the spousal bonus of pension benefits in order to understand how financial incentives coming from the structure of the social security system influence both spouses' retirement decisions. Our results show that there is a considerably small impact of the hypothetical policy change of removing the spousal bonus. The share of women who retires before the earliest eligibility age drops from 23% to 21% when the spousal bonus is removed. More than half of women, who would be eligible to benefit from the spousal bonus initially, switch to alternative retirement routes. Surprisingly, we do not observe a significant change in men’s retirement behavior.

Abstract

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Attracting more contributors to Free and Open Source Software (FOSS) involves the following trade-off. On the one hand, the overall quality of the software increases with the number and diversity of contributions – a positive vertical differentiation effect. On the other hand, including more contributors may drive the characteristics of the software closer to those of existing products, thereby intensifying the competition with these products – a negative horizontal differentiation effect. This explains how retaining excessive control over an FOSS can be a major source of hindrance its development and growth. When taking into account how firms may choose to monetise an open source product, I show that horizontal differentiation: (i) lowers the barrier to entry of firms; (ii) encourages firms to exert larger effort in development. I show all this in a minimal working environment with costless effort and linear transportation cost.

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This session will take place, as usual, in room c.035 at CORE.

Abstract

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An observer wants to understand a decision-maker's preferences from her choice. She believes that decision-maker takes decisions under limited attention; i.e., does not consider all alternatives. In this paper, we make the point that given the nature of established experimental evidence, the existing models of limited attention are not quite helpful in fulfilling the observer's goal. Addressing this challenge, we propose a "minimal" adjustment to the theory of choice under limited attention by assuming that the decision-maker makes at least one comparison in her decision process. We illustrate that, as minimal as this adjustment is, it enriches the model with significant welfare relevance. We further apply our model to experimental data and establish that this significant increase in welfare relevance comes with negligible costs in explanatory power.

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This session will take place, as usual, in room c.035 at CORE.

Title: Should we care about ECB inflation expectations?

Abstract:

We use optimal combination of forecasts to introduce a novel forecast encompassing test to evaluate time-series and institutional inflation projections in the euro area. Combination weights reveal which forecasts are the most informative. Although, ECB is the most informative forecaster on average, it does not encompass its competitors and its weight varies over time. Macro-financial conditions and monetary policy actions explain this variability. The greater the uncertainty surrounding inflation and the difference between current and the 2% inflation target, the less informative ECB’s forecasts are. The more contractionary the monetary policy, the more informative they are. ECB’s declining weight and the relation with its determinants raise a warning flag: the potential loss of informativeness damages ECB’s leading role at anchoring inflation expectations and questions whether the goal of preserving financial stability is compatible with the inflation targeting objective.
 

The next session of the CORE Brown Bag is scheduled for Wednesday, October 19th at 12:50.

Amma Panin (CORE) will present her latest research project, entitled "Religious Organizations as Competing Platforms". We will provide the abstract of the work next week.

This session will take place, as usual, in room c.035 at CORE.

Brett Hollenbeck
(UCLA Anderson School of Management)

Detecting fake review buyers using network structure: Direct evidence from Amazon

Author: Rodolphe Vanderveken

Title : On the optimal combination of naive and mean-variance portfolio strategies

Abstract : In an influential paper, Tu and Zhou (2011, RFS) reaffirm the added value of mean-variance portfolio theory by proposing a methodology to combine the sample mean-variance portfolio with the naive equally weighted portfolio. We show that the seemingly natural convexity constraint they impose that the two combination coefficients must sum to one is unnecessary in theory and has several undesirable consequences relative to the unconstrained portfolio combination. In particular, it leads to an overinvestment in the sample mean-variance portfolio, and a worse performance than the risk-free asset for sufficiently risk-averse investors. However, although wrong in theory, we demonstrate that the convexity constraint acts as a bound constraint on combination coefficients and thus can help improve performance when these are estimated. Empirically, we find that the constrained combination outperforms the optimal combination for investors with small risk aversion, but quickly deteriorates and delivers negative utilities as risk aversion increases. In contrast, the optimal combination performs consistently well for any degree of risk aversion. Therefore, we introduce a mixed strategy that succeeds in taking the best of the optimal and constrained combination.

Mathematical Formulations for Consistent Travelling Salesman Problems

Abstract: The consistent travelling salesman problem looks for a minimum-cost set of Hamiltonian routes, one for every day of a given time period. When a customer requires service in several days, the service times at different days must differ in no more than a given threshold (for example, one hour). We analyze two variants of the problem, depending whether the vehicle is allowed to wait or not at a customer location before its service starts. There are three mathematical models in the literature for the problem without waiting times, and this paper describes a new one appropriated to be solved with a branch-and-cut algorithm. There were no mathematical models in the literature for the other variant, and this paper adapts the four mathematical models to it. We analyze computational results of the formulations on instances from the literature.

Christoph Carnehl (Bocconi University)

Pricing for the Stars
Dynamic Pricing in the Presence of Rating Systems

Maintaining good ratings increases the profits of sellers on online platforms. We analyze the role of strategic pricing for ratings management in a setting where a monopolist sells a good of unknown quality. Higher prices reduce the value for money, which on average worsens reviews. However, higher prices also induce only those consumers with a strong taste for the product to purchase, which on average improves reviews. Our model flexibly parametrizes the two effects. This parametrization can rationalize the observed heterogeneity in the relationship between reviews and prices and highlights the dependence of outcomes on the dominant effect. We analytically characterize a seller’s optimal dynamic pricing strategy, long-run profits and consumer surplus, as well as consumers’ speed of learning. Knowledge of the relative strength of price and selection effect is essential for managing ratings with prices. Our results have important implications for the design of rating systems.

• ZOOM

Simon Schulten (DICE) will present an empirical work on the interplay between consumer mistakes and firm's behavior in online auctions, entitled "Managing Bidder Learning in Retail Auctions".

Abstract

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When firms exploit behavioral biases, it is natural to think that, eventually, consumers will learn to avoid their mistakes, which limits their exploitation. Profit maximizing firms, however, have an incentive to undermine such learning. We study these learning dynamics in a multi-unit descending price auction with a simultaneous fixed price offer. In our panel of 8 million bids by 280.000 bidders, consumers frequently bid more than the fixed price. Depending on other bidders’ bids, an overbid sometimes leads to paying more than the fixed price (overpaying). We argue overpaying increases the saliency of the consumers’ mistake by making it payoff-relevant and thereby may affect consumer learning. Indeed, bidders who overpay subsequently overbid less often and are more likely to leave the market compared to bidders who similarly overbid but did not overpay. We document a structural break in overpaying and the firm actions that caused it. Methodologically, we discuss identification of our treatment effects using causal graphs and show how these treatment effects identify a three-type structural model of bidder behavior with learning dynamics.

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This session will take place in a hybrid format: in room c.035 at CORE, and on Teams, at the following link.

will give a presentation on

Integration Vs Cultural Persistence: Fertility and Working Time among Second Generation Migrants in France

Abstract

We study how cultural norms in the origin country, measured at different times, affect fertility and labor force participation of second-generation migrant women in France. We apply the so-called epidemiological approach to test that the culture of origin affects people’s behavior and decisions, by using the dataset TeO (Trajectoires et Origines) on population diversity in France in 2008. We find that: 1) cultural norms affect people’s decisions, confirming the results of Fernandez and Fogli (2009) also for the French context, 2) the timing of the norm is crucial. Cultural norms that matter the most are those prevailing at the time of the interview, much more than those prevailing at the time of the end of their education or when the second-generation migrants were born. The later the norm is measured in time, the most powerful its effect, suggesting that the socialization of peers is more important than that of parents. The explanatory power of norms holds also when controlling for socio-economic characteristics such as age, siblings, education for both the respondent, spouse, and parents 3) the feeling of being French moderates the persistence of cultural norms differently for fertility and labor force participation, while the perceived feeling of being discriminated does not alter the persistence of the cultural norms.

UAntwerpen, UCLouvain, UGent, ULB, ULiège, UNamur and VUB).

by

Jean-Baptiste Michau (Ecole Polytechnique, France)
on
The Trilemma for Low Interest Rate Macroeconomics

Abstract

Three desirable goals of macroeconomic policy are: full employment, low inflation, and a low debt level with no Ponzi scheme. This paper shows that, when the natural real interest rate is persistently depressed, at most two of these three goals can be simultaneously achieved. Depending of the parameters of the economy, each of the three possibilities can be the preferred option, resulting in a non-trivial policy trilemma.

The seminar will take place on Thursday, November 17th from 16:30 until 18:00 in Conference Room Lamfalussy, entrance: rue de Berlaimont 14, 1000 Brussels and will also be able to be followed via a Microsoft Teams meeting.

Please reply by email to nbbmacro.seminar@nbb.be if you wish to participate to this seminar or if you want to have an appointment with the speaker.

Please let us know if you will be physically present or will follow online. After registration and if you have indicated that you want to join online you will receive a confirmation email with the link to the seminar.

In case you want to access the NBB Parking (rue Montagne aux Herbes potagères 41), please also provide us with your name and the license plate of your car.

and will also be able to be followed via a Microsoft Teams meeting.

Bhaskar Dutta

will give a presentation on

Attack and Interception in Networks

Abstract:
This paper studies a game of attack and interception in a network, where a single attacker chooses a target and a path, and each node chooses a level of protection. We show that the Nash equilibrium of the game exists and is unique. It involves a mixed strategy of the attacker except when one target has a very high value relative to others. We characterize equilibrium attack paths and attack distributions as a function of the underlying network and target values. We also show that adding a link or increasing the value of a target may harm the attacker - a comparative statics e ect which is reminiscent of Braess's paradox in transportation economics. Finally, we contrast the Nash equilibrium with the equilibria of two variations of the model : one where nodes make sequential protection decisions upon observing the arrival of a suspicious object, and one where all nodes cooperate in defense

will give a presentation on 

Measuring Complementarities in Vertical Markets: Evidence from the Digital Advertising Industry

Abstract
The digital advertising industry is characterized by a proliferation of specialized intermediaries helping advertisers in their purchases of online ad space. This study contributes to the analysis of the vertical complementarities in this market by posing and estimating a structural econometric model of how advertisers match to intermediaries. Exploiting novel data and some recent methods in the estimation of many-to-many matching games for large markets, we quantify the value created by the matches, their driving forces and, counterfactually, evaluate the likely effects of the growing concentration among intermediaries. The estimates clearly show that competing advertisers benefit from dealing with a common intermediary and, moreover, offer a precise quantification of various forces including industry specialization, exclusive contracting and diversification.

Le lien Zoom: https://telecom-paris.zoom.us/j/95474902964?pwd=NDgxM1hEK2FMbVhITGZ1RWptL3RRdz09

Niranjana Prasad, CORE

will give a presentation on

Institutional trust and women's healthcare utilization: Evidence from India

Abstract:

Despite the reduction in global maternal mortality rates, there persists a significant proportion of women who continue to not access institutional care. 25% of women surveyed by the National Family Health Surveys in India, report giving birth at home, 20% receive ante-natal care at home and only 36 % received post-natal care. India also continues to report one of the highest estimated numbers of maternal deaths. This study focuses on the role of non-economic determinants of institutional services for delivery among pregnant women in India. I specifically aim to answer the question of how trust in institutions affects women's healthcare utilization. However, there is difficulty in linking mistrust in institutions to healthcare utilization, due to endogeneity concerns. If this is indeed the case, coefficients of trust in a simple health regression would be biased. I use percentage change in voter turnout as an instrument for district-level trust. To study health outcomes in conjunction with trust and electoral data, I employ the Indian National Family Health Survey (NFHS) (2015-16), the two waves of the Indian Human Development Survey - II (IHDS-II) and electoral data from the Election Commission of India. This study finds that an increase in regional trust in politicians reduces home and private hospital births by 0.202 and 0.348 standard deviations respectively and increases skilled delivery in public hospitals by 0.459 standard deviations. Similar results are found when testing the role of trust in local governments. Results remain robust to additional controls and instrumenting close elections in addition to electoral turnout

will give a presentation on:

Epictetusian Rationality

Abstract:

According to Epictetus, mental freedom and happiness can be achieved by distinguishing between, on the one hand, things that are upon our control (our acts, opinions and desires), and, on the other hand, things that are not upon our control (our body, property, offices and reputation), and by wishing for nothing that is outside our control. This article proposes two accounts of Epictetus’s precept: the I account of Epictetus’s precept requires indifference between outcomes differing only on circumstances, whereas the IB account requires indifference between outcomes involving the best replies to circumstances. We study the implications of these precepts on the preference relation and on the existence of Epictetusian rationality. The I account implies that the preference relation satisfies independence of circumstances, whereas the IB account implies robustness to dominated alternatives. Unlike the IB account, the I account rules ou(counter)adaptive preferences. Finally, when examining game-theoretical implications of Epictetusian rationality, we show that the two accounts of Epictetus’s precept exclude the existence of prisoner’s dilemmas.

will give a presentation on

Unite and Conquer: Seller Collusion in Multi-Sided Markets

Abstract:

While online marketplaces gained economic relevance in recent years, the academic debate on how the design of multi-sided markets shapes competition on such platform has been quite limited. In this paper, I investigate how platforms’ marketplace design choices (especially pricing strategies) affect the likelihood of seller collusion and whether platforms have incentives to break or sustain cartels. Building on a game-theoretic model, I analyze how marketplace design choices may affect competition between sellers in a multi-sided market and how platforms can exploit this. My results suggest that high transaction fees limit competition between sellers by increasing their incentives to collude. In that, platforms can manipulate the degree of product variety in each product category on the platform. The outlined theoretical framework also enables the exploration of additional non-pricing-related marketplace design features, such as information disclosure and the number of products.

will give a presentation on 

"Chance-constrained problems with integer second-stage recourse decisions”

Abstract:

We study a class of chance-constrained two-stage stochastic optimization problems where the second-stage recourse decisions belong to mixed-integer convex sets.

Due to the nonconvexity of the second-stage feasible sets, standard decomposition approaches cannot be applied. We develop a provably convergent branch-and-cut scheme that

iteratively generates valid inequalities for the convex hull of the second-stage feasible sets, resorting to spatial branching when cutting no longer suffices. We show that this algorithm

attains an approximate notion of convergence, whereby the feasible sets are relaxed by some positive tolerance. Computational results on chance-constrained resource planning problems

indicate that our implementation of the proposed algorithm is highly effective in solving this class of problems, compared to a naive reformulation tackled with a state-of-the-art MIP solver.

For logistic reasons, please note that the seminar will hold at 14h instead of the usual 16h.

"Bidding and Investment in Wholesale Electricity Markets:
Pay-as-Bid versus Uniform-Price"
CORE contact person: Paul Belleflamme

"Rethinking the Integrated Economic Impacts of Energy Transition on Environment, Investment, and Geopolitics: The Case of Clean Hydrogen as Bottleneck-breaker of Climate Change Mitigation Dilemmas"

CORE contact person: Paul Belleflamme

"The Cost of Air Pollution for Workers and Firms"

CORE contact person: Paul Belleflamme

"A Global Survey of Scientific Consensus and Controversy on Climate Policy"

CORE contact person: Paul Belleflamme

The Strategic Value of Data Sharing

ZOOM link

Abstract

In this paper, we consider competition across two markets where data collected in each market adds value in the other market. A multiproduct firm (1) is a monopolist in market A, and is also active in a second market B where it competes with an established (specialist) firm 2. Firm 1 leverages its presence in both markets to gain a data advantage. In such a market structure, we study the incentive of the specialist firm to share data with its dominant competitor and its implications on profitability, competition and consumer welfare. Our main contribution is to show that the smaller firm has incentives to share data with the dominant firm even for free. This data altruism acts as a strategic device employed by the small firm to lower the intensity of competition by transforming a competitor into a co-opetitor by creating "co-dependence". Specifically, by sharing value-enhancing data, the specialist firm makes the dominant firm a stakeholder in the valuable data collected by the specialist and hence also in its market share. This lowers the competitive intensity of the dominant firm in the competitive market B which enhances (demand and hence also) data collection by the smaller firm. This value creation arising from data altruism substitutes value addition through costly investments made by the dominant firm. A direct managerial implication of this result is that data altruism by the specialist firm can be a win-win outcome for both firms. While data altruism increases market share of the smaller firm, it is not consumer welfare enhancing as it lowers competition (in the secondary market). This result has clear policy implications.

will give a presentation on

Smiles In Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces

Abstract

Online platforms often face challenges being both fair (i.e., non-discriminatory) and efficient (i.e., maximizing revenue). Using computer vision algorithms and observational data from a microlending marketplace, we find that choices made by borrowers creating online profiles impact both of these objectives. We further support this conclusion with a web-based randomized survey experiment. In the experiment, we create profile images using Generative Adversarial Networks that differ in a specific feature and estimate it’s impact on lender demand. We then counterfactually evaluate alternative platform policies and identify particular approaches to influencing the changeable profile photo features that can ameliorate the fairness-efficiency tension.

ZOOM link

will give a presentation on

Estimating Demand with Multi-Homing in Two-Sided Markets

Abstract

We empirically investigate the relevance of multi-homing in two-sided markets. We build a structural econometric model that allows for multihoming. We then estimate readers’ and advertisers’ demand using an original dataset on the Italian daily newspaper market that includes information on double-homing by readers. The results show that a model that does not allow for multi-homing produces biased estimates on both sides of the market. On the reader side, accounting for multi-homing helps to recognize complementarity between products; on the advertising side, it allows to measure to what extent advertising demand depends on the shares of exclusive and overlapping readers.

ZOOM link

will give a presentation on 

Thumbs Up, Thumbs Down: Dislike Attacks and Content Creator Productivity on YouTube

Abstract

Harassment can be harmful to mental health and reduce creativity and productivity. This paper provides evidence on the productivity effects of online harassment by examining a sudden and unanticipated change on YouTube where dislike counts were hidden from public view. Using detailed channel-level data, I show that this design change had several effects on content creators. First, harassment in form of “dislike attacks”, where users drive up dislike counts unrelated to video quality, decreases following this platform design change. Prior to this design change, women seem to have been more affected by this type of harassment. Second, this design change leads to a persistent increase in productivity for female, relative to male, content creators. Third, there is some evidence of redistribution of demand among content creators.

ZOOM link

will give a presentation on

Blockchains, Tokens, and Platforms.

Abstract

The development of blockchains technologies, including smart contracts and cryptographic tokens, have a potential to change the competition between platforms. In this presentation, based on a couple of projects, I will discuss how utility tokens can help new platforms enter the market, and how governance tokens can help platforms to increase social welfare. I will also discuss limitations of these technologies in improving platform strategy and competition.

ZOOM link

!!! Séminaire reporté au 8 mars

« Du chiffre au discours »

14h30 Sébastien Van Bellegem (CORE). Introduction

14h45 Jean-Noël Ferrié (CNRS, UIR Rabat). Ni la nature ni les chiffres ne parlent d’eux-mêmes : sur l’insertion des données scientifiques dans le discours politique

15h15 Ernesto San Martín (PUC Chili). Le consentement éclairé induit-il un biais dans la recherche ?

15h45 Discussion

entitled "Social identity, downward comparisons and the just-world fallacy: A note on the social-psychological origins of economic inequality"

Abstract:

We study how inequality can stem from interactions that are neither economic (trade, production) nor political. We propose two models in which, prior to any interaction, individuals are identical, but the only stable equilibria involve inequality. Our key assumptions are inspired by well-established social-psychological theories. The driving force to inequality in the first model is individuals' need of building their social identity, and the resulting utility they derive from downward social comparisons. The driving force to inequality in the second model is the mental burden of being poor, which is augmented by the stigma emerging from interacting with the rich. This stigma emerges from this interaction as the response of the rich to the threat to their belief in the just-world hypothesis.

will give a presentation on

Market Equilibria in Cross-Border Balancing Platforms

Abstract:

The next phase of electricity markets integration in Europe will see the introduction of pan-European balancing platforms, MARI and PICASSO, for the trading of manual and automatic frequency restoration reserve. This paper provides an analytical framework for the study of pricing asymmetries between European member states in this context. The pricing asymmetries are due to balancing incentive components and consist of the unilateral introduction by a member state of either (i) an adder on the imbalance price and balancing price, (ii) an adder on the imbalance price solely, or (iii) the introduction of a real-time price for the trading of real-time balancing capacity. The analytical framework allows us to characterize the optimal bidding strategy of flexible assets under the different designs and to derive the resulting equilibria. Our analysis demonstrates that adders without the trading of balancing capacity create inefficiencies by distorting the merit order and tend to be detrimental to the member state introducing it.

The Environmental Implications of Renting the Runway

Abstract:

I study the impact on clothing production of subscription-based leasing arrangements: I adopt a stylized setup that features two competitive fringes of retailers and an Access Based Service Provider (ABSP) that offers a two-period rental contract; each fringe supplies a horizontally differentiated good, and the subscription to the ABSP gives access to both products. Consumers display a taste for variety: their gross surplus from the purchase of both products is superadditive. The green credential of the ABSP stems from its efficiency in serving the fraction of users that buys both items; with only one piece per subscriber, the ABSP can provide two distinct outfits, swapping items among its clients between periods. I show that the entrance of the ABSP reduces total production if and only if users exhibit a sufficiently strong preference for variety and if the unit production costs are low enough. Subsequently, I analyze the competitive interaction between the ABSP and the retail side in a Stackelberg game: a retailer that sells both products holds a first-mover advantage against an ABSP. In this set-up, if the demand side is characterized by very low acceptance of rental vis-à-vis ownership, then entrance necessarily implies a larger production volume.

Oil Price Shocks and Bond Risk Premia: Evidence from a Panel of 15 Countries

Abstract:

We study the effect of oil price shocks on bond risk premia. Based on Baumeister and Hamilton (2019), we identify the different sources of oil price shocks using a structural vector autoregressive (SVAR) model of the global market for crude oil. These structural factors are then used as unspanned factors in an affine term structure model based on the representation of Joslin et al. (2014). This is done for a total of 15 countries. Bond risk premia of net oil-exporting countries show a reaction to the structural shocks which is often statistically significant and in line with the expectation. For oil-importing developed countries, mainly the reaction to economic activity shocks is statistically significant and with the expected sign. The results for oil-importing developing countries are most of the time not statistically significant or run counter what one would expect. Among the unspanned factors, global economic activity explains most of the variability in bond risk premia. Finally, a historical decomposition around the outbreak of the COVID-19 crisis shows a variety of patterns in the evolution of bond risk premia.

Who Should Get the Money? Estimating Welfare Weights in the US

Abstract:

Welfare weights measure the value of providing an additional dollar of consump- tion to individuals in society. We identify the welfare weights assigned by the general population of the U.S. to individuals in society using a large-scale real stakes experi- ment. In our experiment, participants in the role of “Social Architects" assign welfare weights to seven real “Recipients" with disposable incomes that span the income distribution of the U.S. The welfare weights obtained from our experiment are suffi- cient statistics that can incorporate various ideals and can be directly used to evaluate reforms. We find that the welfare weights of the general population of the U.S. (i) exhibit, on average, a low to moderate degree of progressivity, (ii) predict their policy preferences, (iii) are slightly more progressive than the welfare weights implied by the existing policies in the U.S., and (iv) are much less progressive than the welfare weights commonly used in the literature.

will give a presentation on

Hysteresis for the Young: Search Capital and Unemployment

Abstract:

This paper argues that search ability should be considered a distinct type of human capital. Workers are endowed with a search ability that determines their effectiveness of search, or their intrinsic job arrival rate. Workers build up their job search capital by interacting with the labour market, finding and moving on to different jobs. Long, stable employment spells without search erode their search capital over time. This channel has notable implications for modelling and policy in all labour markets, but it is particularly relevant in dual labour markets.

In the presence of large, persistent negative shocks like the Great Recession, the inability of young workers to accumulate search capital can explain why they suffer larger increases in unemployment and long-term unemployment, something traditional hysteresis models struggle to explain. Using administrative data, I show that search capital, as proxied by the number of jobs a worker has had, is negatively correlated with unemployment duration. I build a heterogeneous agent search model with both productive and search human capital to show the effect that dynamic search capital has on workers' lifetime utility. The calibrated model shows that despite the protective effects of accumulating search capital against aggregate shocks, the cost in terms of uncertainty outweighs the benefits. The model favours active labour market policies over employment incentives to tackle long-term unemployment among young workers.

Mark Tremblay (Miami University)

Will give a presentation on

Multi-homing vs. Single-homing in Two-Sided Markets: A Cautionary Tale of Participation vs. Transaction.

Abstract

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The pioneering work on platforms and two-sided markets introduced the importance of distinguishing between single-homing and multi-homing. Instead of considering the relationship between homing decisions and participation prices, we contribute to this literature by considering how homing participation impacts transaction prices. Motivated by the example of ride-sharing where a consumer that downloads (participates on) both Lyft and Uber will choose which ever platform offers them the best option (in terms of price and wait times), we develop a model that considers how platform competition and agent homing decisions impact transaction prices across platforms. We find the development of a transaction market generates positive indirect network effects (benefits across sides) and negative direct network effects (competition within side), and that multi-homers do at least as well as single-homers. In addition, greater multi-homing on either side of the market reduces the volatility of transaction prices. In terms of types of platform fees, we find that greater multi-homing occurs when platforms utilize transaction fees instead of membership fees.

Camille Hainnaux (AMSE)

Will give a presentatio on

"Taxing incognito: optimal climate taxation and inequality"

Abstract

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This paper explores optimal alternatives to carbon taxation using already existing taxes in the economy and its impact on inequality. I build a two-sector Ramsey model with heterogeneous agents, in which the carbon stock harms the final good sector’s productivity and individual utility. I find that there exist several alternatives to the standard carbon tax, both in a first- and second-best setting. Under these alternatives, the carbon tax on energy production is replaced by either taxes on energy consumption or taxes on inputs. In first-best, taxes on inputs act as substitutes to income taxes: the government can choose between making households bear the environmental tax burden or to indirectly tax the energy producer. In the latter case, the final good sector is partly subsidized to compensate for the distortion created by the alternative fiscal policy. Studying the optimal Ramsey fiscal policy, a consumption tax is needed along the carbon tax as long as the social and private gains of increasing energy consumption relatively to final good consumption are unequal. Alternatives to carbon taxation are similar to the first-best ones. Income taxes are now always non-zero and vary with the alternatives chosen. Due to the general equilibrium impact of alternatives to carbon taxation, second-best alternatives affect inequality through several channels."

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will give a presentation on

 "Alliances and Technological Partnerships in Contests".

Abstract

" This paper analyses the formation of alliances and technological partnerships in contests. Alliances enhance the probability of winning at the cost of sharing the prize if won, while technological partnerships reduce the marginal cost of the effort invested in the contest by the members. When the players cannot form technological partnerships, no alliances is stable in the long run.

I extend the concept of contractual stability by allowing technological partners to prevent the formation of new alliances. It is found that the pair of grand coalitions, where all the players form one unique alliance and technological partnership, is stable. However, it is restrictive to enable some players that are not directly involved in the formations of new coalitions to cancel these formations. To circumvent this limitation, I proposed a stability notion where the non-deviating players can issue a veto regarding the formation of new alliances. If the vetoes are ignored, the deviating players can be excluded from their technological coalition. The pairs of grand coalitions remain stable, provided that the technological partnerships are sufficiently intense. These findings suggest that the formation of technological partnerships facilitates the formation of alliances in contests. In particular, the formation of the grand alliance, where there is no more contest between the players, can be stable in the long run. "

will give a presentation on

Additive regression with general imperfect variables

will give a presentation on

Bayesian Bi-level Sparse Group Regressions for Macroeconomic Forecasting

will give a presentation on

Identification and inference in high dimensional econometric models
 

will give a presentation on

Direction Identification and Minimax Estimation by Generalized Eigenvalue Problem in High Dimensional Sparse Regression

Abstract:

“In high dimensional sparse linear regression, a selection and an estimation of the parameters are studied based on an $l_0-$constraint on the direction of the vector of parameters. We first establish a general result for the direction of the vector of parameters, that is identified through the leading generalized eigenspace of measurable matrices. Based on this result we suggest addressing the Best Subset Selection problem in a new perspective by solving an empirical generalized eigenvalue problem to estimate the direction of the high-dimensional parameter. We then study a new estimator founded on the RIFLE algorithm and show a non-asymptotic bound of the $L^2$ risk, the minimax convergence of the estimator and a Central Limit Theorem. Simulations show the superiority of the proposed inference over some known $l_0$ constrained estimators.”

will give a presentation on

A Single Relation Theory of Welfarist Social Evaluation

Abstract: 

Despite its central importance, the analysis of social welfare still faces conceptual issues related to well-being measurement. To overcome this problem, the paper offers a new theory of Welfarist social evaluation over states of the world where a single relation captures incomplete comparisons of qualitative well-being differences and levels. It closes the gap between public discourse and theoretical analysis and clarifies the role of numerical well-being representations. The analysis is based on a new anonymity condition for fixed well-being levels at states. It provides a unified rationale for existing two-person conditions (including Hammond Equity, Pigou-Dalton) and identifies deep connections between seemingly distinct approaches to social evaluation. Dependent on the extent of interpersonal well-being comparability, Strong Pareto and the new condition characterize Simple Majority Relation, a level-based Borda Relation, Utilitarianism, Leximin, and a new class of Additive Welfarist Relations. The relational analysis does not employ problematic independence or neutrality conditions from the literature on Social Welfare Functionals. Allowing for an infinite set of individuals, it applies to fixed and variable population contexts. It also connects the social evaluation of states and acts in choice under uncertainty.

will give a presentation on

 "Job uncertainty, wage growth, and cyclical reallocation".

Abstract

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This paper studies the role of the frictional labor market in the transmission of aggregate shocks in an economy with on-job search. To this end, I incorporate the dynamic job ladder in a Heterogeneous-Agent New Keynesian model with Search and Matching frictions. I show that the job ladder impacts the earnings risk wedge over the business cycle through the change in job-to-job transition rates, as well as through the change in relative wages. Both channels produce quantitatively significant amplification of the aggregate shocks."

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Research in econometrics at UCLouvain has suffered in previous years, not the least due to the Covid crisis. The emergence of data science as a new discipline inspires us to rethink and perhaps redefine the position of econometrics and econometricians in teaching and research.

The main part of the program includes twelve scientific presentations of invited speakers. The workshop is open to everyone, but registration is mandatory.

If you want to register to this event please send a mail to severine.devisscher@uclouvain.be before 25 May 2023

Programme

Friday, June 2, 2023

Room: UCLouvain, CORE B.-135

9:00-9:30: Gilles Mordant
Center-Outward Multiple-Output Lorenz Curves and Gini Indices: a measure transportation approach

9:30-10:00: Jozef Barunik
The Dynamic Persistence of Economic Shocks

10:00-10:30: Geert Dhaene
Approximate Functional Differencing

coffee break

11:00-11:30: Nikolaus Hautsch
Estimation risk for systemic risk measures driven by semi-parametric models

11:30-12:00: Edoardo Otranto
Realized Covariance Models with Time-varying Parameters and Spillover Effects

lunch break

14:00-14:30: Roman Liesenfeld
A TVP Model with Bayesian Shrinkage for Global Minimum Variance Portfolio Prediction

14:30-15:00: Arnaud Dufays
Linking Frequentist and Bayesian Change-Point Methods

15:00-15:30: Jeroen Rombouts
Factor Dynamics, Risk Premia, and Higher Moments in Multi-Factor Option Pricing Models

coffee break

16:00-16:30: Ines Wilms
Monitoring Machine Learning Forecasts for Platform Data Streams

16:30-17:00: Frantisek Cech
Quantile Treasury Futures Pricing

17:00 - 17:30: Piet Sercu
Efficient Y-indices for Regressions with an Application of Covid's Impact on Stock-market Liquidity

Vous pouvez vous inscrire via ce lien: 

https://forms.office.com/e/eEXJ6RRzbR

Vous trouverez le programme sur la page web :

https://uclouvain.be/en/research-institutes/lidam/core/conferences-en-memoire-du-professeur-jacques-dreze.html

will give a presentation on

Well-being measurement with reference consumption

Abstract:

We axiomatically study how to measure well-being when individuals have heterogeneous preferences and consumption bundles are evaluated by comparison with some reference bundle (a poverty line bundle, an index of needs, the average consumption in a reference group, etc.). Our key requirement is that well-being remains constant if the reference bundle changes towards a bundle that the individual deems equivalent. Accounting for preferences may lead two individuals with identical consumption and reference bundles to have unequal well-being levels. To limit this inequality, we study four axioms based on the lattice structure of the set of indifference contours. We define and characterize three measures. One prominent measure corresponds to the ratio between equivalent income at consumption and at reference, where prices are chosen to maximize well-being

will give a presentation on

Fraud Detection under Limited State Capacity: Experimental Evidence from Senegal

Abstract:

Information on taxpayers is essential to efficiently allocate tax administrations’ scarce resources in low income countries, yet collecting it can prove both intricate and costly. In the context of Senegal, this paper shows that a randomized low-cost communication campaign can induce some of the largest firms to submit more complete third-party reports about their service suppliers. The intervention increases the prevalence of suppliers' numerical ID in third-party reports by 52% on average. This improves identification information for about 18,546 client-suppliers pairs in total, thereby facilitating the tracking of $1.6 billion, i.e the equivalent of 6 % of GDP. Matching suppliers' ID to the tax registry and the universe of tax declarations, we show that the new information increases the probability to detect payments going to under-reporting formal suppliers by 44%. A simulation exercise shows that exploiting the newly available information to strategically audit the largest under-reporting formal suppliers could increase audit returns by 115%.

Bert Willems

will give a presentation on

Multi-product Supply Function Equilibria

Abstract:

We solve for Nash equilibria in a procurement auction with two heterogeneous divisible goods. There are (dis)economies of scope in production and goods could be substitutes or complements for the procurer. Before demand is realized, each firm offers a vector of supply functions where supply of a good depends on the prices of both goods. This is related to the organisation of the product-mix auction and electricity markets with complex bids. We show that outcomes are not influenced by bundling of the goods. For quadartic costs and linear demand, we can use this property to transform the multi-product problem into an equivalent set of separated single-good markets, which can be analysed independently. We show that Lerner and pass-through tensors can be used to characterise mark-ups and welfare losses in a multi-product market. Eigenvalues of the tensors are fundamental properties of the multi-product market, as they do not depend on bundling.

will give a presentation on 

Algorithms for latency routing and location routing problems

Abstract:

The latency location routing problem (LLRP) is a relatively new variant of the well-known location routing problem. Given a set of customers to be served and a set of potential uncapacitated depots, the problem consists of determining the subset of at most p depots to open, the customers and the vehicles to be assigned to each open depot and the routes to be constructed to fulfill the demand of the customers by taking into account the capacity of the vehicles. The objective is to minimize the sum of the arrival times at the customers, i.e., the latency. The multi-depot cumulative capacitated vehicle routing problem (MDCCVRP) is a particular case of LLRP in which all the available depots can be opened. The multi-depot k-traveling repairman problem (MDk-TRP) is a particular case of MDCCVRP in which there are no capacity constraints for the vehicles. A novel iterated-local-search-based metaheuristic algorithm called M-ILS is proposed for the solution of the LLRP, the MDCCVRP, and the MDk-TRP. Extensive computational experiments indicate that M-ILS outperforms the currently published algorithms in terms of solution quality, requiring competitive computing times. The LLRP assumes that all the parameters involved are deterministic. In real-life situations it may be not true, and uncertainty must be taken into account. In this talk, we also consider an LLRP with stochastic travel times (LLRP-STT). Since latency routing problems have been mainly motivated by applications in disaster operations management (e.g. humanitarian logistics problems) a risk-averse decision maker is assumed. A two-stage stochastic programming model and a variable neighborhood search (VNS) heuristic are proposed for solving the LLRP-STT. Furthermore, for solving instances with continuous probability distributions, i.e., an infinite number of scenarios, a sampling method and a simheuristic algorithm are developed. The effectiveness of the proposed methods is studied through extensive computational experiments. Moreover, several insights are presented.

will give a presentation on

Deep Reinforcement Learning for Inventory Optimisation with Non-Stationary Uncertain Demand

Abstract:

We consider here a single-item lot sizing problem with fixed costs, lead time, and both backorders and lost sales, and we show that, after an appropriate training in randomly generated environments, Deep Reinforcement Learning (DRL) agents can interpolate in real-time near-optimal dynamic policies on instances with a rolling-horizon, provided a previously unseen demand forecast and without the need to periodically resolve the problem. Extensive computational experiments show that the policies provided by these agents compete, and in some circumstances even outperform by several percentage points of gap, those provided by heuristics based on dynamic programming. These results confirm the importance of DRL in the context of inventory control problems and support its use in solving practical instances featuring realistic assumptions.

Dr. Allan Sapucaia - CORE

will give a presentation on

Optimizing over path-length matrices of unrooted binary trees

Abstract:

We characterize the set Θn of the path-length matrices induced by unrooted binary trees with n leaves, based in part on a strengthening of results on the tree realization problem. In addition, we present several new valid inequalities and polyhedral results for the convex hull of Θn. We then focus on the Balanced Minimum Evolution Problem (BMEP), a NP-hard nonlinear optimization problem over Θn much studied in the literature on molecular phylogenetics. Working in an extended space, our characterization leads to a first integer linear programming formulation for the BMEP. Modifying this formulation and strengthening the valid inequalities derived earlier by lifting leads to a second formulation which constitutes the core of a branch-and-cut algorithm. Including a new primal heuristic and several separation oracles, this algorithm significantly outperforms the best available exact algorithm for BMEP, based on a dedicated massively parallel branch-and-bound algorithm.

will give a presentation on

Applying High-Performance Computing to the European Resource Adequacy Assessment

Abstract:

This work considers the European Resource Adequacy Assessment, which is a pan-European resource adequacy process that is being developed by the European Networks of Transmission System Operators for Electricity (ENTSO-E). A critical part of this process is the so-called Economic Viability Assessment model, which aims at determining future expansion and retirement capacity opportunities for the entire European network. As such, the problem is stochastic. Nevertheless, due to computational constraints, simplified approaches have been

followed by ENTSO-E. Our work formulates the problem as a two-stage stochastic problem and proposes two decomposition algorithms for solving the problem which are implemented in a high-performance computing infrastructure. The first is a subgradient-based algorithm, and the second uses a relaxation

of the second stage (the economic dispatch) in order to speed up the subgradient calculation thus achieving a considerable reduction in solution time. We compare our schemes against the commonly used Bender’s decomposition. We compare the obtained stochastic solution against the deterministic solution proposed by ENTSO-E for their 2021 study and analyze the impact of the stochastic solution on various adequacy indicators.

will give a presentation on 

Exact Mixed-Integer Programming Approach for Chance-Constrained Multi-Area Reserve Sizing

Abstract:

An exact algorithm is developed for the chance-constrained multi-area reserve sizing problem in the presence of transmission network constraints. The problem can be cast as a two-stage stochastic mixed integer linear program using sample approximation. Due to the complicated structure of the problem, existing methods attempt to find a feasible solution based on heuristics. Existing mixed-integer algorithms that can be applied directly to a two-stage stochastic program can only address small-scale problems that are not practical. We have found the minimal description of the projection of our problem onto the space of the first-stage variables. This enables us to directly apply more general Integer Programming techniques for mixing sets, that arise in chance-constrained problems. Combining the advantages of the minimal projection and the strengthening reformulation from IP techniques, our method can tackle real-world problems. We specifically consider a case study of the 10-zone Nordic network with 100,000 scenarios where the optimal solution can be found in approximately 5 minutes.

Nicolas Stevens - CORE

will give a presentation on

The Many Advantages of Convex Hull Pricing for the European Electricity Auction

Abstract:

Since the liberalization of the power sector and the creation of wholesale electricity markets, the question of how to price the non-convexities present in the market has attracted the interest of both academics and practitioners. Over the years, US markets have studied and adopted different and evolving pricing rules. Since the “Trilateral Market Coupling” (2006), the European day-ahead market has opted for notably different pricing rule. Recently, the EU stakeholders have undertaken research to reform it, picking interest for some approaches discussed on the other side of the Atlantic. Our paper aims at contributing to the debate. We analyse six different pricing methods. We establish several mathematical properties to enable their accurate comparison. Our findings are illustrated on stylized examples and numerical simulations performed on realistic datasets. Both theoretical and numerical evidences gathered in our paper point towards the many advantages of convex hull pricing.

Dr. Quentin Lété - ETH Zürich

will give a presentation on

Power Generation Investment under Zonal Electricity Pricing with Market-Based Re-dispatch

Abstract:

There is currently an intense debate in Europe on the allocation transmission capacity in the internal electricity market. In this context, the concept of market-based re-dispatch has regained considerable attention, as a candidate design to re-conciliate the zonal organization of the market with a pricing system that supports the efficient real-time dispatch. In this paper, we study the problem of capacity expansion under zonal pricing with market-based re-dispatch. We propose a formulation of the problem as a mixed linear complementarity problem and analyze the existence and efficiency of solutions, both from a theoretical and empirical perspective. We find that zonal pricing with market-based re-dispatch leads to large efficiency losses. Moreover, although there exist theoretical conditions under which the efficiency of the design could be improved by means of regulatory interventions, the strictness of these conditions renders their practical implementation difficult and, therefore, a full recovery of the efficiency unlikely.

will give a presentation on

Manipulating Perceived Product Differentiation (joint with Fabrizio Ciotti).

Abstract:

A digital platform operates a marketplace that two competing firms use to offer a product to consumers. Consumers perceive the products of the two firms as horizontally differentiated. The platform can manipulate the perceived product differentiation by making one product relatively more accessible than the other for all consumers. We show that this manipulation creates a net value for the firms, insofar as the profit gain of the advantaged firm is larger than the profit loss of the disadvantaged one. We compare two monetisation strategies for the platform. In exchange for the advantage conferred by the manipulation of consumers’ perceptions, the platform asks firms to pay either a lump-sum fee or a per-unit royalty. We show that the platform finds the royalty more profitable. Under this scheme, the manipulation is neutral for both firms but makes the consumers worse off. In contrast, compared to the absence of manipulation, the lump-sum scheme would make the advantaged firm indifferent, the disadvantaged firm worse off, and consumers better off.

 Seminar postponed to a later date.

More info coming soon ...

! ! ! ! ! 

Paul Belleflamme (CORE)

will give a presentation on

Strategically free

Abstract

--------------------------------

On many two-sided platforms, one group of users can access the platform services for free. The usual economic explanation behind this observation is that price choices are constrained. Either the best conduct is to subsidize a group of users but negative prices are prohibited or unfeasible. Or, the profit-maximizing price is slightly above zero but micropayments are too costly to implement. We propose an alternative strategic explanation. We consider two two-sided platforms that compete to attract single-homing users of two distinct groups. Extending the model of Armstrong (2006), we allow platforms to commit, in the first stage, to set their membership fee equal to zero for one group of users. In the second stage, platforms choose whichever membership fee that was not committed to beforehand. We show that both platforms may give free access to the same group of users at the subgame-perfect equilibrium of this game, although they would have charged positive fees absent the possibility of commitment. The intuition is as follows. Positive cross-group network effects lead platforms to use each group of users as “bait” to attract the other group. If the price for one group (say A) is zero, there is no revenue to be made from that group. So, by committing to give free access to Group A users, the platform credibly indicates that it will not compete too aggressively to attract users from Group B, which leads the rival platform to act likewise. Such a commitment is optimal if the additional profit resulting from the relaxed competition for Group B users makes up for the lost profit from Group A users.

Will give a presentation on:

The Bright Side of the GDPR: Welfare-improving Privacy Management

Abstract:

We study the GDPR's opt-in requirement in a model with a firm that provides a digital service and consumers who are heterogeneous in their valuations of the firm's service as well as the privacy costs incurred when sharing personal data with the firm. We show that the GDPR boosts demand for the service by allowing consumers with high privacy costs to buy the service without sharing data. The increased demand leads to a higher price but a smaller quantity of shared data. If the firm's revenue is largely usage-based rather than data-based, then both the firm's profit and consumer surplus increase after the GDPR, implying that the GDPR can be welfare-improving. But if the firm's revenue is largely from data monetization, then the GDPR can reduce the firm's profit and consumer surplus.

will give a presentatio on:

Who is AI replacing? The impact of ChatGPT on online freelancing platforms.

ZOOM link

Abstract:

This paper studies the impact of generative AI technologies on the demand for online freelancers, using a large dataset from a leading global freelancing platform. We focus on how the demand effect of the release of ChatGPT differs across various jobs that require different skills or software. Our findings indicate a 14 percent decrease following the ChatGPT introduction in the number of job posts in jobs associated with writing, statistical analysis, engineering, accounting research, and web development when compared to jobs associated with data entry, video services, and audio services, which require more manual tasks. Furthermore, we utilize prior evidence on AI exposure to different occupations and Google Trends to demonstrate that the more pronounced decline in freelancer demand within those specific occupations is linked with their heightened exposure to AI technology, as well as higher general public awareness of ChatGPT's substitutability.

will give a presentation on

Competition in Peer-To-Peer Markets

Abstract:

Peer-to-peer (P2P) markets, such as Uber and AirBnB, allow consumers to find suitable small and independent service providers. In doing so, platforms that manage P2P markets indirectly compete with established traditional providers.

Building on Einav et al. (2016), I develop a model of competition between a platform and a traditional firm and look for the equilibrium prices and level of investment by the vertically integrated traditional incumbent. Specifically, firms compete à la Hotelling for consumers but, while the platform just needs to attract sufficient peer suppliers to match the number of customers, the standard firm relies on a fixed supply that it accumulated by investing in a previous stage of the game.

I show that when the traditional firm faces a supply constraint, it charges a higher price, and the platform can exploit this to charge in turn a higher price too and make a higher margin.

will give a presentation on

Competition through Recommendations

Abstract:

This paper explores if and how platforms should design informative recommendation systems. I show that monopolist platforms prefer recommendation systems that are more informative than value-for-money. When facing competition, platforms reduce the informativeness of their recommendations as their rivals provide more informative recommendations, but never prefer recommendations that are worse than value-for-money. I also show that naive consumers result in more informative recommendations because it is more difficult for the platform to attract consumers.
 

(NUCB Business School, Nagoya University of Commerce and Business, Nagoya, Japan)

will give a presentation on:

Crafting Narratives, Fostering Insight: Case Studies in Platform Strategy

In the realm of business education, case studies emerge as crucial tools, bridging the gap between theory and real-world intricacies. This session aims to uncover the vital role played by case studies in cultivating a deep understanding of complex business frameworks, providing students with invaluable insights. Our discussion will revolve around the practical application of case studies in unraveling the intricacies of platform strategy. By delving into real-world case studies in the classroom, students not only grasp the nuances of ecosystem development, user engagement, and scalability but also gain a commendable understanding of platforms. As we delve into the topic, we'll closely examine the process of creating case studies and tailored teaching notes to align with the dynamic nature of platforms. Our focus will be on crafting narratives that capture the unique aspects of specific platforms, encouraging students to engage in strategic analysis using a theoretical lens. In addition, we'll explore the process of publishing and disseminating these cases, expanding their reach and impact.

• M. Mohsin Hakeem : https://mba.nucba.ac.jp/en/faculty/mohsin_hakeem.html

(MIT Sloan School of Management)

will give a presentation on:

Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?

Newly-developed large language models (LLM)—because of how they are trained and designed—are implicit computational models of humans—a homo silicus. LLMs can be used like economists use homo economicus: they can be given endowments, information, preferences, and so on, and then their behavior can be explored in scenarios via simulation. Experiments using this approach, derived from Charness and Rabin (2002), Kahneman, Knetsch and Thaler (1986), and Samuelson and Zeckhauser (1988) show qualitatively similar results to the original, but it is also easy to try variations for fresh insights. LLMs could allow researchers to pilot studies via simulation first, searching for novel social science insights to test in the real world.

• John Horton : https://john-joseph-horton.com

(University of Padova)

will give a presentation on :

Design and governance of quality on a digital platform

This paper studies the incentives of a platform to curate quality of third-party products it hosts. There are two types of sellers. "Normal sellers'' have heterogeneous intrinsic quality and can enhance their quality through effort. "Bad sellers" have zero quality and never exert effort.  Quality is unobserved to consumers who rely on a rating system to form beliefs on product quality. We show that the platform  may intentionally host bad sellers to induce more effort by normal sellers, even if it can identify and block bad sellers at zero cost. We determine the conditions on the distribution of normal sellers' quality and effort cost function under which the platform has these incentives. We also show that a social planner might also want to have some bad sellers on board. Moreover, tolerating bad sellers can also be a more effective tool to induce more effort than making the rating system more stringent.

• Leonardo Madio : https://sites.google.com/view/leonardomadio/

(Collegio Carlo Alberto)

will give a presentation on :

Self-Regulation and the Evolution of Content: A Cross-Platform Analysis

Is platform self-regulation of social media effective in moderating online content? Or does it shift abusive posts to darker corners of the internet? This paper addresses these questions by analyzing the effect of social media regulation from a cross-platform perspective. I exploit a policy of Twitter against racist hate speech and investigate whether regulation is effective in curbing this harmful content or whether it shifts abusive content to unregulated platforms. I exploit synthetic difference-in-differences and regression discontinuity in time to assess the effects of Twitter's policy. I find that hate speech and racist hate speech content decrease on Twitter after the policy, but there is no apparent increase in hate speech and racist hate speech on Parler for users that have accounts on both platforms. I finally exploit word embedding to analyze whether the language used for abusive content changes after the policy.

• Marina Rizzi : https://www.phdpareto.carloalberto.org/marina-rizzi/

(AMSE)

will give a presentation on

Nation building in post-conflict settings: Evidence from South Africa

Abstract : 
How do states rebuild nations after a major conflict? Truth and Reconciliation Commissions (TRCs) have emerged as one of the most common interventions to achieve this objective. Despite their popularity, little is known about their efficacy to foster reconciliation and nation building. We fill this gap by studying the seminal TRC established in South Africa after the end of the Apartheid. To measure exposure to TRC across South African municipalities, we leverage quasi-random variation in media coverage of the TRC message. South African municipalities with higher historical exposure to TRC on media have lower levels of violence today. This effect is driven by improved nation building and higher trust towards post-Apartheid institutions. Exploiting daily variation in TRC hearings and mediatic exposure in the short run, we bolster our interpretation that our long-run results are forged in the years of TRC activity. The same evidence suggests that our results are driven by the coverage of TRC on media as opposed to generic media exposure.

• Daniela Horta Saenz : https://daniela-horta-saenz.github.io

(EDHEC Business School) 

will give a presentation on :

Binary public decisions with a status quo: undominated mechanisms without coercion.

Abstract :

We discuss the problem of choosing between two public alternatives under the assumption that preferences are quasi-linear and that one of the two alternatives represents the status quo. We characterize the class of strategy-proof and feasible mechanisms satisfying Voluntary Participation, that are not dominated by another strategy-proof and feasible mechanism. These mechanisms form a n-parameter infinite family, the Unanimity mechanism is the only anonymous mechanism within this class.

• Giacomo Valletta https://www.linkedin.com/in/giacomo-valletta-020166b2/

(CORE) 

will give a presentation on :

Interactions of Imbalance Settlement with Energy and Reserve Markets in Multi-Product European Balancing Markets.

Abstract :

This paper provides a framework for analyzing the interaction of imbalance settlement with the clearing of real-time energy and reserve markets. We characterize the optimal strategies of price-taking flexibility providers that can participate in sequential capacity auctions for automatic and manual frequency restoration reserves, followed by an auction that is conducted by the system operator for activating balancing energy. We establish equilibria based on three market features: (i) reserve demand curves, (ii) the activation strategy implemented by the system operator, and (iii) the imbalance settlement scheme. The optimal activation strategy is derived and the effect of the imbalance pricing scheme on bidding incentives, cost efficiency, and reserve prices is discussed.

(Paris School of Economics)

invited by Paul Belleflamme

will give a presentation on :

Procurement with rationing of capacity constrained suppliers

Abstract :

Large-scale procurement auctions with capacity constrained bidders have multiple winners with a split award. The split percentage is usually pre-specified. However, there are auctions, like renewable energy capacity creation auctions in India and Brazil, where the auctioneer does not specify the split, but asks the bidders to report their capacity before the auction. Thereafter, in an English auction, bidders compete on price, and the lowest price loser is given a residual quantity to clear the market, thereby splitting the award ex-post. The non-trivial BNE of the English auction under IPV assumption, for given quantity bids, is characterized by lesser competitiveness and a strictly positive probability of bidding the reserve by the bidder with the highest quantity. Such a BNE is unique with 2 players, but may not always exist with more players. The data from renewable energy auctions in India further provides some preliminary empirical evidence of bunching.

  Manpreet Singh

Conference on Technological Change -- April 29, 2024

List of speakers :

• Oliver Schlenker (University of Konstanz)
• Ulrich Zierahn-Weilage (Utrecht University)
• Max Brès (Swedish Central Bank)
• Joonas Tuhkuri (Stockholm University)
• Zsofia Barany (Central European University)
• Fabrizio Colella (University of Lugano)
• Cristina Lafuente (University of Bath and European University Institute)
• Elisa Keller (University of Exeter)
• Pascual Restrepo (Boston University, keynote)
• Philipp Kircher (Cornell and UCLouvain)

  Program  

(UNamur)

invited by Paul Belleflamme

will give a presentation on :

Recurrent backers in crowdfunding

Abstract :

Crowdfunding platforms(CFPs) constitute a peculiar kind of 2-sided platformswhere multiple network effects are at work. A greater mass of project entrepreneurs looking for funds tends to attractmore backers, thereby increasing the pie, but as more project creators become visible, the number of competitors to share it with increases too. On the other hand, a greater number of funders, entices even further creators to join the platform. Among users of CFPs, recurrent backers, that is backers contributing more than once, have so far received comparatively modest attention. Yet, it has been suggested that their presence is actually a key driver in success of a CFPs as they are a stable presence on the platform, thereby attracting creators, and they contribute to create cascades of contributions. In this project I aim to empirically test whether these backers behave differently fromthe others (such as single-pledge backers and friends and family of the entrepreneurs) and whether they really contribute to stimulate contributions from other backers.

(CORE)

invited by ...

will give a presentation on :

Consumer fairness concerns for personalized pricing by two-sided platforms

Abstract :

Online platforms can track consumers’ behaviors to infer their willingness-to-pay and extract profits by offering personalized prices. Ideally, consumers’ fairness concern may restrict online platforms’ incentives to exert such price discrimination. However, in practice, online platforms have distinct attitudes toward consumers’ fairness concerns. To understand the mechanism underlying the phenomenon, I set up a configuration for a two-sided monopolistic platform between suppliers and two types of consumers with fairness concerns. Based on this configuration, I characterize the condition under which the platform exerts price discrimination according to consumers’ willingness-to-pay and specify how consumers’ fairness concerns interact with the platform’s discriminatory pricing given the two-sided structure. The results suggest that: (i) a monopolistic platform will exert price discrimination according to consumers’ willingness-to-pay if consumers’ aversion to being unfairly treated by the platform in terms of pricing is not strong enough in relation to their stickiness to the platform; and (ii) a monopolistic platform faces a fairness concerns-contingent trade-off between extracting more profits from consumers whose willingness-to-pay is stronger than other consumers and extracting more profits from the supplier side.

Richard O’Neill

(Federal Energy Regulatory Commission)

invited by Nicolas Stevens

will give a presentation on :

Average Incremental Cost (AIC) Pricing for a Surplus-Maximizing Two-Sided Multi-Period Non-Convex ISO Auction Market

Abstract :

General equilibrium theory is an elegant presentation of the properties of convex and certain non-convex markets. Convex auction markets have a ‘single-price’ Walrasian market clearing. If the bids and offers are at marginal costs and values (truth telling), the markets are Pareto efficient. Prices are revenue neutral and sustainable. In the absence of market power, the market is incentive compatible. In a sense they achieve perfection by assuming away problems. With the exception of certain financial markets, the reality is that markets are not convex. For non-convex markets, these properties can be approximated using the convex hull and limit arguments such as ‘as the number of market participants approaches infinity’. If the convex hull is not close to the feasible constraint set, the presentation may not be very elegant and a single-price Walrasian equilibrium may not exist. Specifically, markets with units that have declining average costs, e.g. fossil-fuel generators, or increasing average value, e.g., batch product runs with startup costs, may need discriminatory pricing to efficiently clear the markets and retain some of the important properties of market design. In this presentation, we focus the analysis on ISO electric energy auction markets with energy (private goods) and reserves (public goods), and introduce average incremental cost pricing. We show that AIC pricing has properties that are superior to the properties of other pricing methods including LMP+ (LMP +make-whole payments) , ELMP+ (ELMP +make-whole payments) and Convex Hull Pricing (CHP+uplift). AIC pricing is similar to LMP+, ELMP+ and CHP, but eliminates two troubling issues: make-whole payments and uplift, and letting a non-dispatched unit set the market price. Other properties include transparency, that is, free of uplift or make-whole payments, entry and exit signaling, revenue neutrality, incentive compatibility. Prices may need to be discriminatory or split each node and time period into two separate but related markets: an upper market and a lower market. Each is priced separately but can interact symbiotically. In bilateral markets with an empty core, negotiations are in an indefinite loop. The auction also solves this problem: first by finding the optimal surplus and then pricing the optimal solution. In addition, AIC pricing lowers capacity market prices. With bid-in demand and AIC pricing, the market is more efficient, more reliable, more sustainable, and may eliminate the need for a capacity market.

 Richard O’Neill

 In case you are planning to attend the seminar, please feel free to register here in order for us to estimate attendance:

https://forms.office.com/Pages/ResponsePage.aspx?id=1JCwei76z068fEEntNWC7MX5K5dMfJdNn-PCy8ZKBiFUMFpaNjBJM0JOSjg5TktQU1VHR1FKSUw2Sy4u

François Maniquet

(CORE)

will give a presentation on :

The welfare cost of social pressure

Abstract :

A basic assumption in welfare economics is that rational and well-informed choices reveal what a person considers is good for them. Social pressure, however, can be a source of discrepancy between choices and welfare. We have collected data from a sample of more than one thousand German mothers of young children about their preferred labor time under different scenarios. Based on a vignette survey, we find evidence that some women (especially wives of highly educated men, and West-German wives) have a lower labor time whereas even more women have a larger labor time than if women were not criticized by people around them based on their labor time. We then estimate a discrete labor choice model based on which we compute the welfare cost of this social pressure. We find that the effect of the social pressure to stay home on revealed preference for leisure is four times larger than that of having an additional child, whereas social pressure is on average equivalent to an additional tax of 2.5% on household disposable income.

Optimization methods are fundamental to data science and AI, enabling critical tasks such as sparse data recovery, clustering, dimensionality reduction, and data completion. They are also essential for training machine learning models, including neural networks.
However, existing optimization methods are being constantly challenged by the particular features of modern applications. For example, emerging problems related to data science and AI often involve a huge number of variables, complex data structure, and may require distributed data support.
Consequently, there is a rising demand for the development of new optimization methods customized for specific applications and ideally supported by provable efficiency guarantees. This workshop aims to bring together experts interested in the theory, design, and application of optimization methods. It will serve as a platform for sharing the latest advancements in Algorithmic Optimization, promoting idea exchange and scientific collaborations.

Confirmed Speakers :

Masoud Ahookhosh (University of Antwerp, Belgium)
Francis Bach (INRIA, France)
Nicolas Boumal (EPFL, Switzerland)
Coralia Cartis (University of Oxford, UK)
Etienne de Klerk (Tilburg University, Netherlands)
Nikita Doikov (EPFL, Switzerland)
Radu Dragomir (Télécom Paris, France) 
Pavel Dvurechensky (WIAS, Germany)
Mihai Florea (Université catholique de Louvain, Belgium)
Robert Freund (MIT, USA)
Michel Gevers (Université catholique de Louvain, Belgium)
François Glineur (Université catholique de Louvain, Belgium)
Geovani Nunes Grapiglia (Université catholique de Louvain, Belgium)
Niao He (ETH Zürich, Switzerland) 
Tibor Illés (Corvinus University of Budapest, Hungary) 
Anatoli Juditsky (Université Grenoble Alpes, France)
George Lan (Georgia Institute of Technology, USA)
Goran Lesaja (Georgia Southern University, USA) 
Boris Mordukhovich (Wayne State University, USA)
Ion Necoara (University Politehnica Bucharest, Romania)
Arkadi Nemirovski (Georgia Institute of Technology, USA)
Yurii Nesterov (Université catholique de Louvain, Belgium)
Panos Patrinos (KU Leuven, Belgium)
Peter Richtárik (KAUST, Saudi Arabia)
Anton Rodomanov (CISPA Helmholtz Center for Information Security, Germany)
Kees Roos (Delft University of Technology, Netherlands)
Katya Scheinberg (Cornell University, USA) 
Damien Scieur (Samsung - SAIL Montréal, Canada) 
Vladimir Shikhman (Chemnitz University of Technology, Germany)
Vladimir Spokoiny (WIAS, Germany)
Tamás Terlaky (Lehigh University, USA) 
Philippe Toint (Université de Namur, Belgium)
Levent Tunçel (University of Waterloo, Canada)
Paul Van Dooren (Université catholique de Louvain)
Luis Nunes Vicente (Lehigh University, USA) 
Stephen Wright (University of Wisconsin, USA)
Yinyu Ye (Stanford University, USA)

Poster Presentation :

Zohreh Aminifard
Alexander Bodard
Nizar Bousselmi
Dânâ Davar
Zhicheng Deng
Brecht Evens
Mohammad Hamed Firouzehtarash
Nicolas Gillis
Susan Guaderi
Alireza Kabgani
Yassine Kamri
Aleksandr Lobanov
Elaheh Lotfian
Estelle Massart
Konstantinos Oikonomidi
Morteza Rahimi
Marcos Medeiros Raimundo
Teodor Rotaru
Anne Rubbens 
Seyed Amjad Seyedi
Bas Symoens
Timothé Taminiau
Sofiane Tanji
Guanchun Tong
Manu Upadhyaya
Charlotte Vermeylen
Nico Vervliet
Hongjin Wu
Moslem Zamani

Other participants :

Pierre-Antoine Absil
Michel Baes
Vincent Blondel
Lieven De Lathauwer
Olivier Devolder
Yves Genin
Osman Guler
Yvan Hachez
Julien Hendrickx
Miloica Jaćimović
Raphaël Jungers
Etienne Loute
Stefan Richter
Annick Sartenaer
Laurence Wolsey

Program committe :

Yurii Nesterov
François Glineur
Geovani Grapiglia

Organizing Committee :

François Glineur
Geovani Grapiglia
Nancy Guillaume
Séverine De Visscher

For more details about the event and the latest information, please visit the workshop website at: https://sites.uclouvain.be/algopt2024/

 

Hassan Nosratabadi (ULB. ECARES)

On the Welfare (Ir)Relevance of Two-Stage Models

This paper investigates the welfare relevance of two-stage models of choice. That is, we ask to what extent these models may be used to identify preferences. We show that a large class of the two-stage models can only be identified through direct choice reversals. This class includes the models of limited attention, choice overload, rational shortlist method, among others. Moreover, we provide characterization results for some of these models to find the exact nature of direct reversals needed to learn about preferences. Finally, applying our result on experimental data, we show that almost no preference are identified via these models. On the other hand, the data seems to suggest that welfare relevance, almost entirety, responds to ad-hoc assumptions about the mechanics of the first stage (e.g., the size of the filter) rather than its nature, where the focus of the literature has been so far.

  Hassan Nosratabadi

Leïla Van Keirsbilck (LIDAM. CORE)

The transmission of shocks across sectors and the dynamics of sectoral prices

This paper explores the dynamics of U.S. sectoral producer prices in a large Bayesian vector autoregressive (BVAR) model that uses the Input-Output matrix and the Investment Flow matrix to inform the prior. We first validate our model by comparing its performance in terms of forecasting headline inflation. We then analyze the effects of sectoral and aggregate shocks, identified via external instruments, on different sectoral prices and on aggregate variables. Our contribute to a deeper understanding of sectoral price dynamics, offering insights for monetary and fiscal policy decisions in the face of inflationary pressures.

  Leïla Van Keirsbilck

Mathieu Van Vyve (LIDAM. CORE)

Identifying when thresholds from the Paris Agreement are breached: the minmax average, a novel smoothing approach

Identifying when a given threshold has been breached in the global temperature record has become of crucial importance since the Paris Agreement. However there is no formally agreed methodology for this. In this work we show why local smoothing methodologies like the moving average and other climate modeling based approaches are fundamentally ill-suited for this specific purpose, and propose a better one, that we call the minmax average. It has strong links with the isotonic regression, is conceptually simple and is arguably closer to the intuitive meaning of “breaching the threshold” in the climate discourse, all favorable features for acceptability. When applied to the global mean surface temperature anomaly (GMSTA) record from Berkeley Earth, we obtain the following conclusions. First, the rate of increase has been ∼+0.25°C per decade since 1995. Second, based on this new estimate alone, we should plausibly expect the GMSTA to reach 1.49°C in 2023 and not go below that on average in the medium-term future. When taking into account the record temperatures of the second half of 2023, not having breached the 1.5°C threshold already in July 2023 is only possible with record long and/or deep La Niña in the following years.

  Mathieu Van Vyve​​​​

Michael McMahon

(University of Oxford)

will give a presentation on

Tough Talk: The Fed and the Risk Premium

Abstract: We study how monetary policy affects financial risk premia. Unlike existing studies, we focus on the Federal Open Market Committee’s (FOMC’s) forward-looking policy stance, beyond the current announcement and macroeconomic forecasts, which we derive from the policymakers’private deliberations. A more hawkish policymakers’ stance in the FOMC meeting predicts lower risk premia during the intermeeting period. This effect is not explained by the content of the FOMC statement and unfolds gradually after the announcement. We document the importance of intermeeting communication via speeches and minutes to show how communicating forward-looking stance is vital in managing policy-induced risk perceptions.

Joint with Anna Cieslak.

PROGRAM  •  REGISTRATION  •  ABOUT CHAIRE FRANCQUI

• Program

Map to the event

• Registration 
   

 

About Chaire Francqui

The prestigious Chair promotes inter-university collaboration, expanding scientific partnerships with international institutions and broadening our academic community's global outlook. Visiting scholars contribute fresh ideas to ongoing research and inspire intellectual exchange, fostering vibrant academic dialogue across disciplines.

Promotors

	Sébastien Van Bellegem
	Gentiane Haesbroeck
	Francis Tuerlinckx
	Yves Rosseel

Laureen de Barsy (Université de Liège)
Invited by Paul Belleflamme

will give a presentation on :

The Role of Talent Acquisition in Technology Leadership and Diversification

Abstract : 

This paper aims to track innovation activities around Big Tech acquisitions. To do so, we make use of patent data. Unlike products, which often change names, patented technologies can be tracked as they move across firms. We use this feature of the patent data to assess the impact of Big Tech acquisitions on the development of acquired technologies. But patents expire and technologies evolve. In contrast, the talent of the people who generated the knowledge is an asset that can produce a continuous flow of future knowledge. Therefore, we examine Big Tech's strategy of acquiring not just technologies, but also the talent behind these technologies. We track inventors from firms acquired by Big Tech platforms, and we identify those who continue to innovate for their acquirer post-acquisition. We find that inventors working pre-acquisition on technologies that are closer to their acquirer’s “core” fields are more likely to keep innovating for their acquirer. We extend our analysis by investigating hypothetical explanations for this finding. First, we find that inventors specialising in core technologies are easier for the acquirer to assess, which could partly explain that they are more likely to stay active after acquisition. In a next step [work in progress], we will also test a second potential explanation for this result; namely that Big Tech would be hiring inventors skilled in its core technologies in order to bolster its in-house expertise in these areas.

  Laureen de Barsy

Bernard Sinclair-Desgagné
(SKEMA Business School)

Internal Carbon Pricing in the Multidivisional Firm

In response to environmental concerns, big corporations, which largely allocate resources through so-called ‘internal markets’, often seek to have the associated internal (or transfer) prices incorporate their social cost of pollution. We develop a theoretical rationale and framework to analyze this phenomenon. Our model involves two vertically related subsidiaries located in different j urisdictions. We examine how transfer prices would convey the mandatory carbon fares holding in each jurisdiction, consider the impact on each subsidiary’s production and emissions abatement, and point out the ramifications for the organization of the firm and public p olicy. T hereby, we also capture how the fi rm’s internal carbon pricing interacts with fiscal c ompliance. Through transfer pricing, finally, a carbon fare in one jurisdiction can have an incidence on the other jurisdiction’s subsidiary; implications for environmental governance are briefly discussed.

  Bernard Sinclair-Desgagné 

Samuel Fiorini (ULB)
Invited by Daniele Catanzaro

will give a presentation on :

Integer programs with nearly totally unimodular matrices: the cographic case

Abstract : 

It is a notorious open question whether integer programs (IPs), with an integer coefficient matrix M whose subdeterminants are all bounded by a constant Δ in absolute value, can be solved in polynomial time. We answer this question in the affirmative if we further require that, by removing a constant number of rows and columns from M, one obtains a submatrix A that is the transpose of a network matrix.
Our approach focuses on the case where A arises from M after removing k rows only, where k is a constant. We achieve our result in two main steps, the first related to the theory of IPs and the second related to graph minor theory.

First, we derive a strong proximity result for the case where A is a general totally unimodular matrix: Given an optimal solution of the linear programming relaxation, an optimal solution to the IP can be obtained by finding a constant number of augmentations by circuits of [A I].

Second, for the case where A is transpose of a network matrix, we reformulate the problem as a maximum constrained integer potential problem on a graph G. We observe that if G is 2-connected, then it has no rooted K_{2,t}-minor for t=Ω(kΔ). We leverage this to obtain a tree-decomposition of G into highly structured graphs for which we can solve the problem locally. This allows us to solve the global problem via dynamic programming.

This is joint work with Manuel Aprile (U Padova), Gwenaël Joret (ULB), Stefan Kober (ULB), Michał T. Seweryn (ULB / Charles U Prague), Stefan Weltge (TU Munich), Yelena Yuditsky (ULB).

  Samuel Fiorini

Quentin Lété (CORE)

will give a presentation on :

Forward electricity market with nonconvexities

Abstract : 

Thermal generators must decide whether to produce electricity well in advance, as starting up or shutting down operations require lead time. By participating in forward auctions, like day-ahead or intraday auctions, they can lock in prices, ensuring that they will not make a loss when committing to produce power in the future. Their participation leads to the auction turning nonconvex as thermal generators must communicate indivisible fixed costs associated with start-up and shut-down operations. How to price electricity in such a nonconvex auction is a long-standing debate, but a consensus seems to be emerging towards convex hull pricing. However, most existing literature studies the nonconvex forward market in isolation, ignoring the relationship with the convex real-time market. In this talk, we propose a model to study nonconvex pricing in two-settlement markets, accounting for both day-ahead and real-time markets with financial participants. We show on an illustrative example that, in this case, most of the theoretical properties of convex hull pricing (efficiency and loss opportunity costs minimization) cease to hold. We then present simulation results on a case study calibrated on the PJM market.

  Quentin Lété

Dimitri Watel (SAMOVAR).
Invited by Daniele Catanzaro

will give a presentation on :

Optimization of electrical network configuration : complexity and approximability

Abstract : 

In an electric network, the electric flow is not freely chosen by the operator. It results from the power demands made by consumers and the network's topology. By knowing these two parameters, one can deduce the value of the flow in each cable of the network. We assume a simplified model where the demand at each node is equally distributed in each input arc. The operator can influence the network using two parameters: by disabling one or more nodes or by forcing the direction of the electric current. Once these actions are decided, the operator can estimate the flow value throughout the network. The operator's goal is to avoid overloading the electric sources, as this could lead to their failure and consequently overload other sources. With this snowball effect, the operator risks a total blackout. One way to prevent this phenomenon is to optimize the load reserve. The load of a source is the percentage of its production capacity that is being utilized, which must remain well below 100% to avoid overload. The load reserve is the difference between the maximum load and the minimum load of all sources combined. Therefore, a balanced network is one where all sources are utilized at the same percentage. This type of optimization also ensures equitable revenue when the energy-producing entities do not all have the same production capacity. Our problem can be described as follows: given an electric network and the load calls from consumers, what are the deactivation and orientation actions that the operator should take to minimize the load reserve? In this problem, we are interested in the complexity and approximability of this issue. We demonstrate that this problem is NP-Hard and inapproximable in general. It remains NP-Hard even in the case where the electric network is a tree; however, in this case, there exists an approximation scheme with an absolute approximation ratio. The end of the presentation will address the challenges of generating realistic instances and evaluating these algorithms.

  Dimitri Watel

Hugo Gilbert (Université Paris Dauphine).
Invited by Daniele Catanzaro

will give a presentation on :

On the Computation of Strategyproof and Fair Picking Sequences

Abstract : 

When allocating indivisible items to agents, it is known that the only strategyproof mechanisms that satisfy a set of rather mild conditions are constrained serial dictatorships (also known as non-interleaving picking sequences): given a fixed order over agents, at each step the designated agent chooses a given number of items (depending on her position in the sequence). With these rules, agents who come earlier in the sequence have a larger choice of items. However, this advantage can be compensated by a higher number of items received by those who come later. How to balance priority in the sequence and number of items received is a nontrivial question. 
In this presentation, we use a model parameterized by a mapping from ranks to scores, a social welfare functional, and a distribution over preference profiles. For several meaningful choices of parameters, we show that an optimal sequence can be computed exactly in polynomial time or approximated by resorting to sampling.  

Joint work with Sylvain Bouveret, Jérôme Lang, and Guillaume Méroué.

  Hugo Gilbert

Emiliano Lancini (Université Paris Dauphine).
Invited by Daniele Catanzaro

will give a presentation on :

Sequential picking games against greedy on Matroids

Abstract : 

Given a hypergraph on a set of n ordered vertices, we define an independent set X to be feasible, if X is a possible outcome for a player in a sequential picking game, against a greedyadversary, where no hyperedge can be contained in the union of both outcomes. We prove that testing feasibilty is NP-complete, even if the hypergaph is a graph, but it becomes polynomial for matroid hypergraphs, that is, when the hyperedges are the circuits of some matroid. We prove that optimizing a linear function over feasible sets is NP-hard for matroid hypergraphs, even for graphic matroids, but it becomes polynomial for laminar matroids.

  Emiliano Lancini

Ibrahim Abada (Grenoble Ecole de Management).
Invited by Daniele Catanzaro

will give a presentation on :

Risk-sharing in Energy Communities

Abstract : 

Energy communities are considered one of the pillars of the energy transition, owing to the rapid development of digital smart appliances and metering. They benefit from strong political support to accommodate their penetration in Europe. Nevertheless, the pace at which they have developed has been very slow compared with what was expected a decade ago. Many articles have revealed some of the underlying reasons, among which are social heterogeneity among participants, unfavorable local regulations, and inadequate governance. Most recently, a nascent body of research has highlighted the need to find adequate sharing rules for the benefits of community projects. Because of the complexity of these rules, the appointment of a community manager or coordinator may be necessary. This paper follows suit by providing guidance to policy makers or community managers about optimal risk-sharing schemes among members of an energy community. By modeling and simulating energy communities that invest in a rooftop photo-voltaic project and face some degree of production and remuneration risk, we find that a high level of risk aversion makes it impossible to allocate the risk in a stable way. Furthermore, we show that some communities whose members' risk aversion is too heterogeneous cannot form successfully. Besides, even when risk can be allocated in a stable manner, we show that fair allocations are so complex that they require the intervention of a coordinator or a community manager. Finally, we analyze the advantages of developing judicious risk-sharing instruments between communities and a central entity for providing stability.

  Ibrahim Abada

Luca Neri (CORE)

will give a presentation on :

Uncovering attention heterogeneity

Abstract : 

Individuals vary in their attention to news. Building on theories of imperfect information, we propose a novel method to uncover the distribution of attention in surveys of consumers and professional forecasters. We develop a finite mixture model to cluster forecasts according to their attention, which is robust to forecast rounding and non-adjustment. Our results reveal substantial attention heterogeneity in survey data, showing that ignoring this heterogeneity can underestimate average inattention. By constructing a panel of individual attention measures, we provide new insights into the drivers of attention from within-individual variations. Finally, we discuss the theoretical implications of our findings.

  Luca Neri

Antoine Germain (CORE)

will give a presentation on :

Job Market Talk​​​​​​​

  Antoine Germain

Paul Belleflamme (CORE)

will give a presentation on :

Competition for Prominence

Abstract : 

We examine prominence allocation in digital marketplaces, analyzing how default retailer selection affects competition and consumer welfare. We investigate the impact of different fee structures (unit vs. ad valorem) on prominence allocation and market dynamics. Our findings reveal that prominence significantly influences retailer competition, with both positive and negative implications for consumers. The choice of fee structure profoundly affects allocation strategies and competitive landscapes. This research contributes to digital marketplace economics, offering valuable insights to policymakers, marketplace operators, and retailers.

(joint work with Fabrizio Ciotti and Leonardo Madio)

  Paul Belleflamme

Michele Modugno (Federal Reserve Bank)
Invited by Prof. Leonardo Iania

will give a presentation on :

Decoding Equity Market Reactions to Macroeconomic News

Abstract : 

We show that the reaction of the equity market to macroeconomic news is rationalized by their propagation into the real economy. We embody all the macro news in an activity and a price news indexes that together explain 34% of the quarterly stock price returns variation. When those indexes capture a stream of favorable macroeconomic surprises, publicly traded firms experience increases in revenues, profitability, financing, and investment activities. This firm-level result culminates in an expansion of the real side of the whole US economy. These results, taken together, show that the expectation of the realization of firms growth is the main driver of the stock prices reaction to macro news.

  Michele Modugno

Matteo Bulgarelli (CORE)

will give a presentation on :

Leasing, Bundling and Aggregate Output: Are Rental Subscriptions Sustainable?

Abstract : 

We study the potential of rental subscriptions as a tool to abate the production impact. We build an oligopoly model where two single-product retailers and a multi-product rental provider compete on prices: products in our model are horizontally differentiated, while leasing is qualitatively inferior to owning an item. The rental provider, or Access Based Service Provider (ABSP) offers a bundle of two products, and its user base receives one product per period. We compare the equilibrium outcomes with a setup where the multi-product firm sells the two products, rather than renting them out. We show that leasing is greener than selling for goods characterized by small unit cost: moreover, a marginal improvement on the ability of the ABSP to serve multiple consumers with the same item does not necessarily result in a lower production impact, due to the strategic response of the competitors. Finally, we find that as leasing and selling become closer substitutes, leasing is more likely to result in higher production impact, in that the cost savings implied by better asset utilisation translate into a very large user base for the multi-product firm.

  Matteo Bulgarelli

Cette année, la conférence sera donnée par Jean Drèze, avec pour thème
L'emploi garanti en action : l'expérience indienne

Jean Drèze, économiste du développement, est actuellement professeur invité à l'université de Ranchi en Inde et professeur honoraire à la Delhi School of Economics.
Il a apporté de nombreuses contributions à l'économie du développement et aux politiques publiques, en particulier concernant l'Inde. Parmi ses ouvrages récents, citons An Uncertain Glory :
India and Its Contradictions (avec Amartya Sen) et Sense and Solidarity : Jholawala Economics for Everyone. Jean Drèze est également actif dans diverses campagnes en faveur des droits économiques et sociaux.
Son travail a contribué à l'élaboration de plusieurs législations sociales importantes en Inde, notamment la loi nationale sur la garantie de l'emploi rural (National Rural Employment Guarantee Act).

La conférence aura lieu le jeudi 19 décembre 2024 à Louvain-la-Neuve, au Foyer royal (Aula Magna) à 18 heures.
Deux membres de l'UCLouvain interviendront dans la foulée de sa présentation:

• Bruno van der Linden de l'IRES, UCLouvain
• Philippe van Parijs de la Chaire Hoover d'éthique économique et sociale, UCLouvain

Un drink sera proposé à 20h.

Etant donné que le nombre de personnes qui peuvent assister à la conférence est limité, l'inscription est gratuite mais obligatoire.
Pour vous inscire à cette conférence et/ou au drink, merci de compléter le lien suivant avant le 6 décembre 2024:

https://forms.office.com/e/SpmeKKmTk2

Daniele Catanzaro, Président du CORE,
William Pariente, Président de l'ESL,
Bernard Fierens Gevaert, Président de l'ADEL.

Lors de cette conférence, des photos et vidéos seront prises et utilisées sur le site internet. Si vous ne souhaitez pas apparaitre sur ces photos; merci d'envoyer un message à lidam.com@uclouvain.be

Federico Michelotto (University of Bologna)
Invited by Daniele Catanzaro

will give a presentation on :

A parallel metaheuristic framework for the Capacitated Vehicle Routing Problem

Abstract : 

The Capacitated Vehicle Routing Problem (CVRP) is one of the most studied combinatorial optimization problems which can be described as follows. Given a set of customers, each of which with a known location and demand, and a fleet of homogeneous vehicles with fixed capacity, the goal of the CVRP is to find the minimum cost set of routes, so that each customer is served by exactly one vehicle and the capacity constraints for the vehicles are satisfied. Given the inherent computational difficulty and practical relevance of the problem, several successful heuristics and metaheuristics have been proposed for its solution. However, almost all methods proposed in the literature for solving the CVRP are sequential algorithms. Despite the impressive results achieved by recent metaheuristic methods on large-scale instances, the sequential nature of these algorithms becomes a fundamental limitation when the goal is to efficiently solve instances with thousands or more customers. Therefore, this work aims to propose an effective and paradigmatic parallel metaheuristic framework for large-scale instances of the CVRP. We show that it is possible to obtain equivalent solutions’ quality with an approximately linear speed-up with respect to one of the most efficient state-of-the-art metaheuristic for the CVRP.

Francesco Pisanu (CORE)

will give a presentation on :

Hard problems on box-totally dual integral polyhedra

Abstract : 

A rational linear system is Totally Dual Integral (TDI) if for every integer linear function for which the optimum is finite the associated dual problem has an integer optimal solution. A TDI system is box-TDI if adding any rational bounds on the variables preserves its TDIness. Box-TDI systems are systems that yield strong min-max relations such as the one involved in the Max Flow-Min Cut Theorem of Ford and Fulkerson.  Cook proved that box-TDIness is a polyhedral property, therefore polyhedra that can be described by box-TDI systems are called box-TDI polyhedra. 

Box-TDI polyhedra characterize the following generalization of the well-known totally unimodular matrices. A matrix is totally equimodular (TE) if for each subset of linearly independent rows, the corresponding nonzero maximal minors have the same absolute value. A matrix A is TE if and only if any polyhedron described by A is box-TDI for each rational RHS.

In this work, we prove that the problem of deciding whether a given polyhedron is box-TDI is co-NP-complete. We also prove that the edge-vertex incidence matrix of any graph is TE. As a consequence of Karp's hardness result on the maximum stable set problem, this implies that integer programming over box-TDI polyhedra is NP-hard.

This is a joint work with Patrick Chervet, Roland Grappe, Mathieu Lacroix, and Roberto Wolfler Calvo.

As the energy transition continues, the electricity system will look fundamentally different in the years to come. With increasing generation from renewable energy sources and greater consumer participation, significant challenges arise for the design and operation of liberalized electricity systems. This workshop aims to bring together researchers in economics and operations research to discuss these challenges and explore innovative solutions.

Highlights:

10 Talks by International Guest Speakers

Date: 27 January 2025

Venue: Building Ommegang, Rue de l'Ommegang 6, 1000 Bruxelles. Directions and access instructions.

Organizers: Quentin Lété, Bert Willems

Confirmed Speakers:

• Lesia Mitridati (DTU, Denmark)
• Anthony Papavasiliou (NTUA, Greece)
• Pär Holmberg (IFN Stockholm, Sweden)
• Silvester van Kooten (UJEP, Czech Republic)
• Marion Ott (ZEW, Germany)
• Estelle Cantillon (ULB, Belgium)
• David Wozabal (VU Amsterdam, Netherlands)
• Han La Poutré (CWI/TU Delft, Netherlands)
• Nicolas Astier (PSE, France)

Register for Attendance: Click here

Also, don't miss our Interdisciplinary PhD Workshop on Energy Systems on January 28, 2025!

Benedetto Manca (University of Cagliari) 

will give a presentation on : 

Random Projections for Mathematical Programming. 

Abstract : 

Random projections are random linear maps which approximately preserve geometrical quantities. The Johson-Lindenstrauss Lemma states that there exist random projections with a relatively small number of rows which preserve the pairwise Euclidean distances among a set of points. 
In the past years several results on the application of random projections to Mathematical Programming instances are being obtained, showing that it is possible to obtain an approximate formulation with less decision variables and constraints and therefore easier to solve. 
In this talk I will introduce the generic framework of random projections for Mathematical Programming formulations and I will present more in details some results in the case of Linear Programming, Quadratic Programming and the Minimum Sum of Squares problem. 

will give a presentation on : 

Network dual reoptimization policies and bounds for managing energy real options. 

Abstract : 

Energy operations and investments are managed with real option models that embed timing and/or switching decisions, where the former and latter types of decisions change irreversibly and reversibly, respectively, the status of the real asset. Optimizing the flexibility in these models requires solving a finite-horizon Markov decision process with finite endogenous states but a high-dimensional and continuous exogenous state space, which is typically intractable and requires heuristic approaches. Least squares Monte Carlo (LSM) is a popular approximate dynamic programming method for this purpose while a known forecast-based reoptimization heuristic (FRH) is not well suited to handle timing decisions. We develop a network dual reoptimization framework that leverages network flow algorithms and employs a novel class of partial information relaxations to overcome this shortcoming. Our framework provides both a new policy and a dual bound and we establish that: (i) the decisions taken by our policy are equivalent to solving a scenario-based two-stage stochastic program but computationally more efficient since scenarios are solved independently; and (ii) our dual bound is provably tighter than the known penalized perfect information bound. Numerical experiments on two energy real options dealing with commodity production and vehicle fleet upgrade show that our policy outperforms FRH by 10-20% and LSM by to 2-5%, while our dual bound improves by less than 1%.

will give a presentation on : 

Comparative approaches for economic modeling in healthcare markets, relevance of random price generators. 

Abstract : 

OBJECTIVES: this communication aims to discuss how and in which context a random price generator for health care markets can be useful in comparison with other approaches for economic modeling and pricing of medical products and services 
METHODS: a comparison of the different approaches used will be discussed with their statistical limitations: nested logit models, cumulative logit models, latent model of choices , shrinkable estimators with Hierarchical Bayesian approach, combination of robust pricing optimization with multinomial logit choice models and choice models with random price generators; an application in progress of the BLP model on NGS sequencing will also be presented. 
RESULTS: random generators prove to be useful but do not fit any kind of structural conditions to adjust supply and demand of health care markets, especially in more regulated health and economic systems. An approach by sets of alternatives for choice models allows to adjust for heterogeneity of demand but lack of price data in some markets makes it useful to rely on shrinkable estimators with HB approaches. In duopoly cases, the BLP model currently tested, may help investigation of antitrust policies. 
CONCLUSIONS: the complexity of health care markets lead to consider various combinations of models and even participatory modeling to reach growing consensus with various layers of decision makers both on the payer side and economic actors often switching to data driven models for both drug and vaccines supplies.

To register please fill in this form

Programme

Chair : Mathieu Sauvenier

• 9:00 Introduction (Van Bellegem-San Martin): “Is statistical modeling Galilean ?”
• 9:30 A view from physics:
  Nicolas Gisin (Université de Genève) : “Intuitionism, a physicist’s point of view”
• 10:30 Break
• 10:45 A view from scholastic:
  Rudolf Schüßler (Universität Bayreuth) : ”Scholastic probability: rational assertibility and expert opinion”
• 11:45 A view from logic :
  Peter Verdée (UCLouvain) : « Interpretation and logic of probabilities. Distinguishing uncertainty, modality, vagueness and indeterminacy”
• 12:45 Break
• 2:00PM A view from psychology :
  Ernesto San Martin (PUC, Chile): “Modern Probability Theory and Psychometrics: What are the consequences of platonistic statistics versus Kolmogorov constructive approach ?”
• 3:00PM A view from economics : 
  Sébastien Van Bellegem (UCLouvain) : “Economic models and data : between idealization and reality”
• 3:30PM Questions
• 4PM stop

Chair: Mathis Dartevelle

Chair : Martial Toniotti

will give a presentation on : 

Tax Reform on Monopoly Platformer in Borderless Economy: The Incidence on Prices and Efficiency Consequences. 

Abstract : 

As development of online market brings ongoing concerns that foreign app suppliers avoid value-added tax (VAT) in a domestic country, some countries design a tax reform which makes platform pay VAT instead of app suppliers (platform taxation). In the market where the monopoly platformer determines the prices of the network good and the commission fee of the platform services (with online apps as a representative example), this study investigates whether the prevention of tax leaks by platform tax improves the welfare of the host country, as well as the extent of the cross-market incidence of the two-sided market. We find that the tax reform reduces foreign app suppliers and consumption of a network good such as smartphones, with substantial extent of cross-market pass-through. The effect of the tax reform on home app suppliers crucially depends on the responsiveness of the app supplies from the number of users, which we call entry elasticity. Platform tax also increases the tax burden laid on the network product, but the monopoly seller let the increase of the tax burden born entirely by consumers. We also show that digitalization reduces the loss of welfare as well as tax planning by the platformer.

Miguel Anjos (University of Edinburgh) 

will give a presentation on : 

Optimizing the Present and Future of Smart Electric Power Grids. 

Abstract : 

A smart grid is the combination of a traditional electrical power system with information and energy both flowing back and forth between suppliers and consumers. This new paradigm introduces major challenges such as the integration of decentralized energy generation, the increase of electric transportation, and the need for electricity consumers to play an active role in the operations of the grid. This presentation will overview the changes in progress in several countries, present some recent research on mathematical optimization models to support these changes, and conclude with a summary of the opportunities for optimization to contribute to the future success of smart grids.

   Joint Seminar with ICTEAM

   Bâtiment Euleur, salle A.002

Cécile Rottner (EDF) 

will give a presentation on : 

Structured-symmetry-breaking techniques in Integer Linear Programming, case study on the Unit Commitment Problem. 

Abstract : 

Symmetries arising in integer linear programs (ILP) can impair the solution process, in particular when symmetric solutions lead to an excessively large Branch and Bound search tree. Various techniques, so called symmetry-breaking techniques, are available to handle symmetries in ILP. A symmetry is defined as a permutation of the variables such that for any solution, the image of the permutation is also solution, with same cost. The symmetry group is the set of all such permutations. In this presentation, we focus on structured symmetries, defined when symmetry groups contain all sub-column permutations of given solution submatrices. These symmetry groups are assumed to be known or previously detected. Such general symmetry structure arise in various combinatorial problem structures (bin packing, graph coloring, etc) and is present in particular in the Unit Commitment Problem (UCP), when some production units are identical. We review and classify methods to handle structured symmetries in ILP, and propose a numerical analysis of the performance on various UCP instances.

   CORE B.-135

Axel Parmentier  (Ecole Nationale des Ponts et Chaussées) 

will give a presentation on : 

Recent trends in Combinatorial Optimization Augmented Machine Learning. 

Abstract : 

Combinatorial optimization augmented machine learning (COAML) is a novel and rapidly growing field that integrates methods from machine learning and operations research to tackle data-driven problems that involve both uncertainty and combinatorics. These problems arise frequently in industrial processes, where firms seek to leverage large and noisy data sets to better optimize their operations. COAML typically involves embedding combinatorial optimization layers into neural networks and training them with decision-aware learning techniques. This talk provides an overview of the field, covering its main applications, algorithms, and theoretical foundations. We will notably emphasize recent contributions on empirical risk minimization and the resulting theoretical guarantees. We also demonstrate the effectiveness of COAML on contextual and dynamic stochastic optimization problems, as evidenced by its winning performance on the 2022 EURO-NeurIPS challenge on dynamic vehicle routing.
 

   Joint Seminar with ICTEAM

   Bâtiment Euleur, salle A.002

Yelena Yuditski (ULB) 

will give a presentation on : 

Total Matching and Subdeterminants. 

Abstract : 

In the total matching problem, one is given a graph G with weights on the vertices and edges. The goal is to find a maximum weight set of vertices and edges that is the non-incident union of a stable set and a matching. We consider the natural formulation of the problem as an integer program (IP), with variables corresponding to vertices and edges. Let M = M(G) denote the constraint matrix of this IP. We define Delta(G) as the maximum absolute value of the determinant of a square submatrix of M. We show that the total matching problem can be solved in strongly polynomial time provided Delta(G) <= Delta for some constant Delta is an element of Z(>= 1). We also show that the problem of computing Delta(G) admits an FPT algorithm. We also establish further results on Delta(G) when G is a forest. 

   CORE B.-135

Carla Michini (University of Winsconsin-Madison) 

will give a presentation on : 

Pure Nash equilibria in structured congestion games. 

Abstract : 

Congestion games are a class of non-cooperative games that can be used to model resource sharing among selfish players. A prominent solution concept for these games is that of pure Nash equilibrium (PNE), a strategy profile where no player has incentive to unilaterally deviate. In this talk I will address two central questions. The first question is: which structures allow us to design a polynomial-time algorithm for the computation of a PNE? The second question is: which structures can limit the inefficiency of pure Nash equilibria? To answer the first question, I will present a polyhedral approach that can be leveraged to design a strongly polynomial-time algorithm to compute a PNE in symmetric totally unimodular (TU) congestion games, where the players’ strategies are binary vectors inside polyhedra defined by TU constraint matrices. In relation to the second question, I will consider different measures of social cost and quantify equilibria inefficiency through the notion of pure Price of Anarchy (PoA). I will present bounds on the PoA for two main structured congestion games: congestion games defined over series-parallel networks and congestion games defined over paving matroids. 

This is a joint work with Bainian Hao. 

   CORE B.-135

Diego Delle Donne  (ESSEC Business School) 

will give a presentation on : 

Freight-on-Transit for urban last-mile deliveries: Strategic and operational planning by means of integer programming. 

Abstract : 

We study a delivery strategy for last-mile deliveries in urban areas which combines freight transportation with mass mobility systems with the goal of creating synergies contrasting negative externalities caused by transportation. The idea is to use the residual capacity on public transport means for moving freight within the city. In particular, the system is such that parcels are first transported from origins (central distribution centers) to drop-in stations, which are stop locations on public vehicle itineraries. Then, they are transported on public vehicles to drop-out stations, from where they are delivered to destination by green vehicles (such as bikes, drones, porters, etc.). The system is known as Freight-On-Transit (FOT). In this work, we focus on strategic and operational decisions related to FOT. We propose different formulations for the problems and effective heuristic solution approaches based on column generation techniques. 

Sophie Huiberts (LIMOS) 

will give a presentation on : 

Open problems about the simplex method. 

Abstract : 

The simplex method is a very efficient algorithm. In this talk we see a few of the state-of-the-art theories for explaining this observation. We will discuss what it takes for a mathematical model to explain an algorithm’s qualities, and whether existing theories meet this bar. Following this, we will question what the simplex method is and if the theoretician's simplex method is the same algorithm as the practitioner's simplex method. Along the way I will share some anecdotes about linear programming history. 
 

   Joint Seminar with ICTEAM

   Bâtiment Euleur, salle A.002

Matteo Bulgarelli (CORE) 

will give a presentation on : 

TBA ... 

Abstract : 

TBA ... 
 

   CORE C.035

Leonardo Madio (University of Padova) 

will give a presentation on : 

Transparency of Add-On Fees on Peer-to-Peer Platforms: Evidence from Airbnb. 

Abstract : 

This paper investigates the impact of price transparency on equilibrium prices and fees by considering a policy change implemented by Airbnb that affected the transparency of cleaning fees for IP addresses from the European Union (EU). Using a difference-in-differences approach, we find a reduction in cleaning fees of 2-4%. Consistent with our theoretical framework, we also find that listings without a cleaning fee, something that is common on Airbnb, appear more affordable after the policy change and react by increasing their nightly price by 5-6%. We argue that this result is driven by some hosts learning about the full prices of their rivals due to the transparency policy, finding themselves more affordable. This analysis uncovers a new mechanism through which greater price transparency can lead to price increases. 
 

   CORE C.035

Paul Belleflamme (CORE) 

will give a presentation on : 

Strategically free. 

Abstract : 

We present a novel rationale for two-sided platforms to offer free access to a specific group of users: platforms may find it advantageous to commit to providing free access on one side in order to alleviate price competition on the other. To illustrate this point, we extend Armstrong's (2006) platform competition model with singlehoming for both user groups. Our model expands the strategy sets by allowing platforms to commit to offering free access to one of the two user groups. (Assuming that platforms incur no marginal costs when onboarding users, providing free access effectively equates to pricing at marginal cost).

To clarify our argument (and without loss of generality), we assume unilateral cross-side network effects, where Group B users benefit as more Group A users join their platform, while Group A users remain indifferent to the participation of Group B users. We also posit that, in the absence of a commitment to free access, platforms would charge both user groups a positive fee at equilibrium. In this context, reducing the fee to zero for side B can enable a platform to enhance its profits on side A, even though this decision does not directly influence the participation of Group A users (who do not perceive value in Group B users’ participation).

The rationale is as follows: when a platform commits to offering free access on side B, its profits become independent of the number of users attracted on that side. Consequently, the platform no longer needs to leverage side A users to attract Group B users, allowing it to credibly signal to its rival platform its intent to maintain a high fee on side A, thereby easing price competition. We outline the conditions under which the gains on side A surpass the losses on side B, leading both platforms to commit to free access for side B at equilibrium.

Joined with Eric Toulemonde (UNamur).

Sumit Shrivastav (CORE) 

will give a presentation on : 

Platform Diversification. 

Abstract : 

Recent trends show that many two-sided platforms are diversifying into additional businesses. This raises an important question: how does a platform’s diversification affect its existing market? We examine a framework in which a platform that diversifies must allocate its limited resources on one side of the market—specifically,  sellers—across its two businesses. In doing so, both the diversifying platform and its competitor behave as constrained monopolists on the seller side. We analyze how diversification influences platform pricing, relative profitability, and overall welfare. Our findings offer insights into the strategic and welfare implications of platform diversification in two-sided markets. 

In the context of the new course "Using Economic Tools to Solve Global Challenges", Guilhem Cassan and Amma Panin are pleased to invite you to a special lecture by Professor Jan Eeckhout on his book, The Profit Paradox, which explores the rise of market power in the modern economy and its consequences for wages, inequality, and economic growth.

In The Profit Paradox, Professor Eeckhout examines how large firms' increasing dominance has led to soaring profits but stagnant wages, widening inequality, and lower economic dynamism. His analysis provides insights into the paradox that while corporate success should benefit the broader economy, excessive market power is eroding competition and worker prosperity.

   The lecture will take place on Monday 5 May from 12:45 to 14:00 in SOCR 40. 

Join us  for what promises to be an engaging and thought-provoking discussion. We look forward to seeing you there.

   More info

Antoine Germain (CORE) 

will give a presentation on : 

Consumer welfare and equality of opportunity. 

Abstract : 

Hicksian compensating and equivalent variations are widely used by cost-benefit analysts but criticized by theorists for their intransitivity and lack of inequality aversion. In a general consumption environment allowing for price dispersion in addition to income and preference heterogeneity, this paper builds an axiomatic theory of consumer welfare based on the ethics of equality of opportunity: unequal budgets create welfare-relevant inequalities but heterogeneous preferences do not. When combined with a separability condition, these ethics single out a welfare measure that is transitive, inequality-averse and based on a particular money-metric utility function. I discuss implications for equivalence scales and cost of living indices. 
 

   CORE C.035

Carla Michini (University of Winsconsin-Madison) 

will give a presentation on : 

A polyhedral study of multivariate decision trees. 

Abstract : 

Decision trees are a widely used tool for interpretable machine learning. Multivariate decision trees employ hyperplanes at the branch nodes to route datapoints throughout the tree and yield more compact models than univariate trees. Recently, mixed-integer programming (MIP) has been applied to formulate the optimal decision tree problem. A key component of most MIP formulations is a specification of how to route datapoints in the tree from the root to the leaves. Our goal is to provide polyhedral characterizations of realizable routings, i.e., routings that can be realized using multivariate branching rules. We first focus on shattering inequalities, a class of valid inequalities that can be used to strengthen almost any MIP formulation and that have been shown to be computationally effective. We prove that if all the feature vectors are in general position, then the shattering inequalities defined for the root of the tree are facet-defining for the convex hull of the realizable routings. We then show that every facet-defining inequality of a depth one tree involving at least two variables is also facet-defining for trees of arbitrary depth. Finally, we show that facet-defining inequalities characterizing realizable routings are also facet-defining for a complete MIP formulation. We validate our theoretical results by performing numerical experiments that specifically exploit shattering inequalities defined at the root node and we observe an improvement in performance for both numerical and categorical datasets, especially for decision trees of intermediate size. 

This is a joint work with Zachary Zhou. 

   CORE B.-135

• Session 1 : 

Riccardo Paba (CORE) 

will give a presentation on : 

Retailing with demand prediction. 

Abstract : 

The surge of AI-driven demand-forecasting services prompts a central question: how does forecast access reshape a retailer’s core decisions? We model a monopolistic seller that chooses output before demand is realised, sets prices ex post, and can discard unsold units at a cost. We derive optimal production, pricing, profits, and disposal both with and without a binary prediction signal, showing how forecast accuracy shifts each decision. The analysis highlights the economic and environmental consequences of adopting demand-prediction tools in retailing.

• Session 2 : 

Jing Su (CORE) 

will give a presentation on : 

Consumer Fairness Concerns and Third-Degree Price Discrimination of Two-Sided Platforms. 

Abstract : 

This paper studies how consumers’ fairness concerns influence the third-degree price discrimination of a monopoly two-sided platform. We show that the presence of fair ness concerns creates a negative demand externality from low-willingness-to-pay to high-willingness-to-pay consumers, namely, charging less to the former reduces the latter’s demand. With this new externality, a platform can earn more profits from consumers by strengthening price discrimination on the consumer side, but this lowers profits from the seller side. Hence, a platform whose profit potential from sellers is larger would take consumers’ fairness concerns more seriously and price-discriminate less. Our results can explain why some online platforms shy away from adopting price discrimination in response to consumers’ fairness concerns, while others always price-discriminate among consumers.

Robin Ng (University of Mannheim) 

will give a presentation on : 

Enabling Communication Through Content Moderation. 

Abstract : 

This paper investigates how moderation can facilitate effective communication on online platforms where users have strategic incentives to mislead. In a model where a sender communicates information to a receiver and may exert costly effort to make their message more persuasive, communication fails without moderation due to either cheap talk dynamics or excessive sender costs that deter participation. When combined with sender effort, moderation discourages misleading messages, enabling truthful communication without requiring excessive sender effort. Full information transmission can often be sustained with minimal moderation, as even limited inspection deters deception. However, excessive moderation reduces sender effort, diminishing the quality of high-effort messages that benefit receivers. An optimal moderation policy often strikes a balance: just enough intervention to sustain truthful communication while preserving sender incentives to provide high-quality messages.

Amma Panin (CORE) 

will give a presentation on : 

Invisible Hands of Gods: How Religion Improves Economic Decision-Making and Outcomes. 

Abstract : 

Religion is big business in Africa. Religion is also poorly understood business. Almost 96% of Ghanaians agree with the statement “religion is important to my daily life”. They put their money where their mouths are. Expenditure surveys show that households spend 15-20% of their budgets on religious activities—more than is spent on clothes, school, or entertainment. What are they paying for? I hypothesize that individuals use religion as a tool to relax psychological constraints. Religion makes it easier for individuals to produce useful, if not necessarily correct, beliefs about themselves or their actions. For example, they may take out a loan to expand a business because they overestimate the returns to effort. Religious organizations also put members in touch with one another and these interactions may make the beliefs true. For example, co-religionists may patronize their fellow member’s newly expanded business, increasing the chances that the business will be a success. In this way, religion relaxes psychological constraints (low confidence in the example) and improves economic outcomes (business profits). I test this hypothesis across three work packages measuring whether the demand for religious messages responds to their psychological usefulness; using text analysis on 10 years of sermons and geo-coded data on church branches to test whether churches compete with one another by attracting members for secular interactions; and conducting a randomized control trial to understand how receiving a prophecy affects business owner’s profits.

Johannes Johnen (CORE) 

will give a presentation on : 

Harvesting Ratings. 

Abstract : 

Evidence suggests lower prices lead to better ratings, but better ratings induce firms to charge higher prices in the future. We model that consumers are only willing to make the effort to rate a seller if this seller provides a sufficient value-for-money. Using this model, we explore how firms use prices to impact their own ratings. We show that firms harvest ratings: they offer lower prices in early periods to trigger consumers to leave a good rating in order to earn larger profits in the future. Because especially low-quality firms harvest ratings, harvesting makes ratings less-informative about quality. Based on this mechanism, (i) we argue that rating harvesting causes rating inflation; (ii) we show that a marketplace that facilitates ratings (e.g. through reminders, one-click ratings etc.) may get more ratings, but also less-informative ratings; (iii) a marketplace that screens the quality of sellers makes ratings less-informative if the screening is insufficient. Counter to the conventional wisdom that consumers benefit from ratings via the information they transmit, we show that consumers prefer somewhat, but never fully informative ratings. Nonetheless consumers prefer more-informative ratings than average sellers. We apply these results to characterise when a two-sided platform wants to facilitate ratings. Our results suggest that efforts of major platforms to facilitate ratings may have lead to less-informative ratings, and possibly also shifted surplus from consumers to sellers.

Sougata Poddar (The University of Iowa) 

will give a presentation on : 

Does Strategic Shelving of Patents Lead to Market Dominance?

Abstract : 

In many markets, we observe scenarios where a firm sometimes pays to acquire new technologies (patents), however, does not use them for its use, i.e., shelves them. By shelving the technology, the technology-acquiring firm can prevent its competitor from using it and thus maintain its strategic advantage in the market. This may create market dominance. We show that this happens often when an outside innovator uses exclusive licensing to transfer technology where potential licensees have different efficiency levels of production and have asymmetric absorptive capacities of the transferred technology. However, we also show when this will not happen in the same environment. We find that under fixed fee licensing, when the size of the innovation is not big, technology is shelved, whereas if the innovation is large, it is not shelved. With per-unit royalty licensing, we find interesting non-monotonicity with respect to shelving and no shelving as the size of the innovation increases. We also find out the optimal licensing contract of the innovator in this environment and potential welfare loss due to shelving on the society.

Emiliano Lancini (Université Paris-Dauphine) 
will give a presentation on : 

Matroids: optimization and polyhedra. 

Abstract : 

In this lecture, I will present a key optimization result concerning matroids. We will begin by recalling the standard definition of a greedy algorithm and then demonstrate that greedy algorithms yield optimal solutions for every linear maximization or minimization problem over a combinatorial structure if and only if that structure is a matroid. This result will be illustrated through a classical example: Kruskal's algorithm. We will then introduce a related polyhedral object, the polymatroid, and discuss some of its fundamental properties, including box-total dual integrality.
 

• Session 1 : 

Henri Dehaybe (CORE) 

will give a presentation on : 

New Heuristics for Phylogeny Estimation under the Balanced Minimum Evolution Criterion. 

Abstract : 

Recent advances in the combinatorics of the Balanced Minimum Evolution Problem (BMEP) enabled the characterization of the mathematical properties that a symmetric integer matrix of order  must satisfy to encode the Path-Length Matrix (PLM) of an Unrooted Binary Tree (UBT). This result, together with the identification of fundamental facet-defining inequalities for the convex hull of BMEP solutions, has led to an integer linear programming formulation that currently serves as the reference exact solution algorithm. Here, we show how to exploit these advances to improve the approximation algorithms for the problem. We first leverage the tight linear programming relaxation of this formulation to develop an enhanced Neighbor Joining–like heuristic. Next, we embed this heuristic into a Beam Search framework to further improve the quality of the solutions. Computational experiments show that the proposed algorithms outperform existing heuristics, making their use highly desirable in practice.

• Session 2 : 

Thomas De Munck (CORE) 

will give a presentation on : 

A rolling horizon approach to coordinating ride-hailing platforms and public transit systems. 

Abstract : 

The integration of ride-hailing platforms with public transit systems can bring many benefits, including improved utilization of public transit, and affordable and accessible customer services. In this work, we consider the online problem of a ride-hailing platform that dispatches drivers to customers while coordinating with public transit. Customer requests arrive dynamically over time. For each request, the platform must decide (i) whether to provide door-to-door, first-mile, or last-mile service, and (ii) which driver to dispatch to the resulting service. To address this problem, we develop a rolling horizon approach based on stochastic optimization. The approach is enhanced by a route selection procedure and a Benders decomposition. In numerical experiments, we evaluate the benefits of a coordinated system under various parameter configurations and objective functions. Our results suggest that the platform and the customers can significantly benefit from coordination.

Maria Paola Priola (University of Cagliari) 

will give a presentation on : 

From Data Streams to User Screens: a Multimodal hEalth Datawarehouse for ITAly (MEDITA). 

Abstract : 

Public health data are essential for understanding population health, monitoring trends, and informing evidence-based decision-making. Data Warehouses (DWs) play a critical role in standard­ izing, integrating, and analyzing large-scale datasets. However, existing solutions often encounter challenges such as data fragmentation, structural complexity, and limited user interactivity. This paper presents MEDITA (Multimodal hEalth Datawarehouse for ITAiy), a prototype platform de­ signed to unify and analyze both textual and tabular data from Italian public health sources through an Extract-Transform-Load-Model-Deploy (ETLMD) pipeline. MEDITA includes interactive visu­ alization tools, statistical modeling for time series analysis, and a Retrieval-Augmented Generation (RAG) chatbot that enables real-time querying in Italian. As a centralized and user-friendly reposi­ tory, MEDITA enhances accessibility for both healthcare researchers, who require structured data for analysis, and the general public, who can explore public health insights without technical expertise. Future development may include support for video, audio, and electronic health records, expanding the role of multimodal analytics in public health research.

“Conflict and the roots of gender norms in India”

Amma Panin will lead a discussion on the paper titled “Conflict and the roots of gender norms in India” by Mark Dincecco, James Fenske, Bishnupriya Gupta, Anil Menon. We meet at least once a month at LLN or Namur to discuss recent working papers in the broad areas of political economy, culture, and development economics. 

Program of the day

2025 Belgo-Japan Public Economics conference 

Friday November 14, 2025

08.45 : welcome coffee/tea

SESSION 1 : Taxing household and multinationals

09.00-09.50 : Pierre Pestieau (University of Liège)
                         Taxing inter vivos transfers and bequests

09.50-10.40 :  Jean Hindriks (UCLouvain)
                         Taxing Multinationals: Revenue-production efficiency tradeoff 

10.45-11.15 :  coffee/tea break

SESSION 2: Multinationals architecture and profit shifting 

11.15-12.05 :   Kozo Kiyota (Keio University)
                        Keep Your Enemies Closer: International Joint Ventures in the Global Network 
                        of Japanese Multinational Companies

12.05-12-55:  Mohammed Mardan (Norwegian School of Economics, Norway) 
                      The ART of profit shifting

13.00-14.00 : Lunch 

SESSION 3: International taxation and global minimum tax

14.00-14.50:   Hirofumi Okoshi (Okayama University)
                       Reallocating Taxing Rights and Online Trade: 
                       Pillar One as a Partial Formula Apportionment                                  

14.50-15.40:  Andreas Haufler (LMU Munich University, Germany)
                      Will the Global Minimum Tax Hurt Developing Countries?

18.00: diner at the Martin’s Hotel (restaurant B’Comm)

Saturday November 15, 2025

08.45 : welcome coffee/tea

SESSION 4 : Climate and aging

09.00-09.50 : Keisaku Higashida (Kwansei Gakuin University)
                         Move Together or Drop Out? 
                         The Impact of “Going Further Ahead” by Front-runners of Climate Action 

09.50-10.40 : Yukihiro Nishimura (Osaka University) 
                         Public pensions and LTC insurance with family solidarity 

10.45-11.15 : coffee/tea break

SESSION 5 : Optimal taxation and altruism subsidy

11.15-12.05 : Shigeo Morita (Fukuoka University)
                      How should love for children be subsidized?: 
                      Optimal non-linear subsidy on parents' expenditure for children? 

12.05-12-55 : Laurence Jacquet (Cergy Paris University, France)
                       Generalized Production Efficiency

An exact algorithm for robust influence maximization

Abstract: We propose a Branch-and-Cut algorithm for the robust influence maximization problem. The influence maximization problem aims to identify, in a social network, a set of given cardinality comprising actors that are able to influence the maximum number of other actors. We assume that the social network is given in the form of a graph with node thresholds to indicate the resistance of an actor to influence, and arc weights to represent the strength of the influence between two actors. In the robust version of the problem that we study, the node thresholds and arc weights are affected by uncertainty and we optimize over a worst-case scenario within given robustness budgets. We study properties of the robust solution and show that even computing the worst-case scenario for given robustness budgets is NP-hard. We implement an exact Branch-and-Cut as well as a heuristic Branch-Cut-and-Price. Numerical experiments show that we are able to solve to optimality instances of size comparable to other exact approaches in the literature for the non-robust problem, and we can tackle the robust version with similar performance. On larger instances (>= 2000 nodes), our heuristic Branch-Cut-and-Price significantly outperforms a 2-opt heuristic.

This is a joint work with Giacomo Nannicini, Giorgio Sartor, and  Emiliano Traversi.

Totally equimodular matrices: decomposition and triangulation.

Abstract: 

One way of obtaining strong combinatorial min-max theorems is to study if a system of linear inequalities Ax≤b is totally dual integral (TDI). The MaxFlow-MinCut theorem of Ford and Fulkerson is one fine example. In that specific case, the matrix A involved is totally unimodular (TU), meaning all its nonzero subdeterminants are ±1, and that implies that the system is TDI. In fact, since the matrix is TU, the system satisfies an even stronger property: it is box-TDI, that is, it remains TDI when we impose any bounds to the variables. Totally equimodular matrices appear in this context, as a generalization of totally unimodular matrices.

A full row rank matrix is equimodular when all its nonzero subdeterminants of maximal size have the same absolute value, this value is called the equideterminant of the matrix.
A matrix is totally equimodular (TE) if for all its row induced matrices are equimodular when they are of full row rank. When a matrix is TU, it is TE, and all the involved equideterminants equal to 1.
More generally, systems of linear inequalities defined by TE matrices are box-TDI.

We identify a matrix with the set of vectors composed of its rows.A set of vectors is TE if the associated matrix is TE.
After giving several examples of TE matrices, I will give a first result: a decomposition theorem for TE matrices with full row rank.
Incidentally, we obtain that systems defined by TE matrices with 0,±1 entries are totally dual dyadic.
We will then leverage this decomposition theorem to analyze the cones generated by linearly independent TE sets of vectors, such cones are called te-cones.
We first provide their Hilbert basis, which is the minimal set of integer vectors of the cone that generate all its integer points with nonnegative combinations.
Finally, we will find a unimodular regular Hilbert triangulation for te-cones in (almost) all cases of the decomposition.

This is a joint work with Patrick Chervet and Roland Grappe (arXiv:2504:05930).

An Introduction to Modelling with GAMSPy

This workshop offers a hands-on introduction to GAMSPy. GAMSPy combines the high-performance GAMS execution system with the flexible Python language, creating a powerful mathematical optimization package. It acts as a bridge between the expressive Python language and the robust GAMS system, allowing you to create complex mathematical models effortlessly.

Join us to explore GAMSPy’s fundamental functionalities through practical, interactive exercises. We’ll cover everything from defining sets, parameters, variables, and equations to solving models and retrieving results, all within a familiar Python environment. Beyond the basics, we’ll also provide a glimpse into more advanced features, demonstrating how GAMSPy can streamline complex modeling workflows and enhance your analytical capabilities.

In addition, we will discuss how GAMSPy can support benchmarking projects for integer programming (IP) solving, help evaluate the impact of different modeling choices, and illustrate how it can complement or extend direct solver-based approaches such as CPLEX or Gurobi within C++ environments.

Whether you’re a seasoned GAMS user looking to integrate with Python or a Python user curious about optimization, this workshop will equip you with the essential skills to get started with GAMSPy.
 

Silvia Di Gregorio, Maitresse de Conference, Université Sorbonne Paris Nord
 

A Knowledge Compilation Take on Binary Polynomial Optimization

Abstract:
The Binary Polynomial Optimization (BPO) problem is defined as the problem of maximizing a given polynomial function over all binary points. The main contribution of this paper is to draw a novel connection between BPO and the field of Knowledge Compilation. This connection allows us to unify and significantly extend the state-of-the-art for BPO, both in terms of tractable classes, and in terms of existence of extended formulations. In particular, for instances of BPO with hypergraphs that are either β-acyclic or with bounded incidence treewidth, we obtain strongly polynomial algorithms for BPO, and extended formulations of polynomial size for the corresponding multilinear polytopes. The generality of our technique allows us to obtain the same type of results for extensions of BPO, where we enforce extended cardinality constraints on the set of binary points, and where variables are replaced by literals. We also obtain strongly polynomial algorithms for the variant of the above problems where we seek k best feasible solutions, instead of only one optimal solution. Computational results show that the resulting algorithms can be significantly faster than current state-of-the-art.
This is a joint work with Florent Capelli and Alberto Del Pia.
 

Francesca Demelas

(University of Pisa)

Machine Learning for Lagrangian Relaxation

Abstract: 

I present two machine-learning approaches to enhance Lagrangian relaxation methods. Lagrangian relaxation dualizes a subset of constraints using penalization weights, called Lagrangian multipliers, to obtain bounds on the optimal value, typically optimized via iterative schemes such as the Bundle method.
The first approach is an amortized optimization model that directly predicts Lagrangian multipliers. A probabilistic graph neural network encodes each instance, represented as a bipartite graph, and a deterministic decoder outputs a multiplier per constraint. The model is trained in an unsupervised way by maximizing the resulting Lagrangian bound, and its predictions can effectively initialize, or even replace, the Bundle method.
The second approach learns to improve the Bundle method itself. At each iteration, it adapts the algorithm’s regularization parameter and replaces the quadratic subproblem with a learned surrogate based on a recurrent attention architecture that produces a convex combination of stored subgradients. By smoothing the stabilization-point updates, the full pipeline becomes differentiable and trainable end-to-end. This yields a trainable optimization algorithm that extends classical Lagrangian relaxation and enables meta-learning and broader learning-to-optimize applications.

Laszlo Végh

University of Bonn

Matroids are equitable

Abstract :

We show that if the ground set of a matroid can be partitioned into k≥2 bases, then for any given subset S of the ground set, there is a partition into k bases such that the sizes of the intersections of the bases with S may differ by at most one, settling a conjecture by Fekete and Szabó from 2011. 

In the talk, I will present the surprisingly simple proof, as well as some extensions and applicaitons in fair division. I will also give an overview of related questions on matroid basis exchanges. This is based on joint work with Hannaneh Akrami, Roshan Raj, and Siyue Liu.

Mercredi 17 décembre 2025, de 13h00 à 14h00 (sandwichs offerts). 
Louvain-la-Neuve, Place Montesquieu, 1 > LECL 93. 

L’économie est partout — dans les politiques publiques, sur les marchés, dans les inégalités, dans l’actualité. Mais à quoi sert-elle vraiment ? Est-ce une science qui améliore la société, une boîte à outils pour la prise de décision, ou une discipline qui doit être repensée ?

Lors de ce débat public, trois économistes de premier plan — André Sapir (ULB), Jean-Philippe Platteau (UNamur) et Michel De Vroey (UCLouvain) — confronteront leurs perspectives autour d’une question centrale : que devrait faire l’économie, et pour qui ?

Des politiques européennes au développement et aux institutions, des normes sociales qui influencent les comportements à l’histoire des idées macroéconomiques, les intervenants remettront en question les idées reçues sur ce que font les économistes — et sur ce qu’ils devraient faire.

Que vous soyez étudiant·e en économie, curieux ou curieuse de l’impact réel de votre discipline, ou simplement intéressé·e par la façon dont la pensée économique façonne notre monde, ce débat vous offrira des éclairages nouveaux, des perspectives critiques et l’occasion de repenser la finalité de l’économie aujourd’hui.

Venez interroger votre discipline — et peut-être la redécouvrir.

Debate Summary — What Is Economics Good For? Economics is everywhere — in public policy, in markets, in inequality, in the headlines.

But what is it actually good for? Is it a science that shapes society for the better, a toolbox for decision-making, or a discipline in need of rethinking? In this public debate, three leading economists — André Sapir, Jean-Philippe Platteau, and Michel De Vroey — bring their contrasting perspectives to one big question: What should economics be doing, and for whom?

From European policy to development and institutions, from the social norms that shape behaviour to the history of macroeconomic ideas, the speakers will challenge assumptions about what economists do — and what they should do.

Whether you're a student in economics, curious about the real-world impact of your field, or simply interested in how economic thinking shapes our world, this debate will offer fresh insights, critical perspectives, and a chance to rethink the purpose of economics today.

Come question your discipline — and maybe rediscover it.

André Sapir est un économiste belge et Professeur à l’Université libre de Bruxelles (ULB). Senior Fellow au think tank Bruegel et Research Fellow au CEPR, il est reconnu pour ses travaux sur l’intégration européenne, le commerce et la gouvernance économique. Il a été conseiller économique du président de la Commission européenne Romano Prodi et a dirigé le Rapport Sapir sur la stratégie de croissance de l’UE. Son parcours illustre le lien entre recherche académique et décision politique à haut niveau.

André Sapir is a Belgian economist and University Professor at the Université libre de Bruxelles (ULB). A Senior Fellow at the Bruegel think tank and Research Fellow at CEPR, he is known for his influential work on European integration, trade, and economic governance. Sapir served as economic adviser to European Commission President Romano Prodi and coordinated the landmark Sapir Report on Europe’s growth strategy. His career bridges academic research and high-level policy, making him a leading voice on the role economics can play in shaping European institutions.

Jean-Philippe Platteau est Professeur émérite à l’Université de Namur, où il a cofondé le Centre de recherche en économie du développement. Ses travaux étudient comment les normes sociales, les institutions et les pratiques informelles influencent le développement, notamment en matière de droits fonciers, d’action collective et de culture économique. Auteur de plusieurs ouvrages majeurs, il souligne l’importance de comprendre les réalités sociales — et pas seulement les marchés — pour penser l’économie.

Jean-Philippe Platteau is Emeritus Professor of Economics at the University of Namur, where he co-founded the Centre for Research in Economic Development. His research explores how social norms, institutions, and informal practices shape development outcomes, with influential work on land rights, collective action, and the role of culture in economic life. Author of several key books on institutions and development, Platteau’s work highlights the importance of understanding real societies — not just markets — when thinking about economics.

Michel De Vroey est Professeur émérite de l’UCLouvain et spécialiste de l’histoire de la pensée macroéconomique. Ses recherches retracent l’évolution de la macroéconomie, de Keynes aux modèles contemporains, en montrant comment les idées et les débats ont façonné la discipline. Son ouvrage A History of Macroeconomics from Keynes to Lucas and Beyond a marqué le domaine et rappelle combien comprendre l’histoire de l’économie éclaire son rôle et ses limites actuelles.

Michel De Vroey is Professor Emeritus at UCLouvain and a specialist in the history of macroeconomic thought. His research traces the evolution of macroeconomics from Keynes to modern models, examining how ideas and debates have shaped the discipline. His widely praised book A History of Macroeconomics from Keynes to Lucas and Beyond illustrates his central contribution: showing how understanding the past of economics helps clarify its role and limitations today.

Bryan David Galarza Montenegro

(University of Antwerpen)

will give a presentation on:

An application of advanced optimization methods in Non-Emergency Medical Transportation

Abstract:

Non-Emergency Medical Transportation (NEMT) is becoming increasingly important as healthcare systems shift toward outpatient care and aging populations require more frequent medical appointments. However, current NEMT operations face significant operational challenges and are often manually planned in practice. This work presents the design, implementation, and deployment of an advanced optimization engine developed to automate NEMT planning operations. This work is part of a VLAIO development project for a leading software platform in the sector. The optimization engine addresses the complex problem of assigning patient trips to a heterogeneous fleet of vehicles and staff shifts while respecting numerous constraints, including time windows, vehicle capabilities, mobility requirements, and case-specific restrictions. A parallelized Large Neighborhood Search (LNS) metaheuristic, combined with Simulated Annealing and local search refinements, forms the core of the algorithm. The engine is implemented in C++ and integrated directly with the company's web platform. It supports both static full-day planning and real-time dynamic scheduling. Results are validated with real operational data from transport providers in Belgium and Germany. The system has been successfully deployed in production, demonstrating significant improvements in planning efficiency, dispatcher workload reduction, and service quality.

More info about the speaker

Roberto Ronco

(National Research Council of Italy)

will give a presentation on:

On the Path-Length Matrices of Unrooted Binary Trees

Abstract:

The Path-Length Matrix (PLM) of an Unrooted Binary Tree (UBT) is a symmetric integer matrix of order n ≥ 3 that uniquely encodes a tree with n leaves and internal vertices of degree 3. PLMs have applications in clustering and in computational biology, among others. One notable example is the Balanced Minimum Evolution Problem (BMEP), a NP-hard problem that is central in phylogeny estimation. In this talk, we extend the results in [1, 2] on necessary and sufficient conditions for a matrix to encode the PLM of a UBT with n leaves [3]. In particular, we show a reduced set of conditions for n ≤ 11 that, interestingly, does not include the so-called Buneman’s four-point conditions [4]. 1. Catanzaro, D., Labb´e, M., Pesenti, R., and Salazar-Gonz´ales, J. J., The balanced minimum evolution problem, INFORMS Journal on Computing 24(2), 276–294 (2012). 2. Catanzaro, D., Pesenti, R., Sapucaia, A., and Wolsey, L. A., Optimizing over path-length matrices of unrooted binary trees, Mathematical Programming A (2025). 3. Catanzaro, D., Pesenti, R., and Ronco, R., Characterizing path-length matrices of unrooted binary trees (LIDAM Discussion Paper CORE 2024/28), UCLouvain, LIDAM/CORE (2024). 4. Buneman, P., A note on the metric properties of trees, Journal of combinatorial theory 17(B), 48–50 (1974). 

More info about the speaker

Frédéric Meunier

(Ecole nationale des ponts et chaussée) 

Will give a presentation on : 

Envy-free divisions of cakes: recent results and open questions

Abstract: 

The envy-free cake-cutting problem asks for a way to divide a cake (identified with the interval [0,1]) among players with different tastes so that each receives a connected piece and no one envies another’s share. The Stromquist–Woodall theorem from 1980 guarantees the existence of such an envy-free division under mild assumptions. Recently, there has been a surge of interest in this problem from various perspectives — computer science, social choice theory, economics, and topological combinatorics. In this talk, we present several extensions, from these perspectives: the cake may be “poisoned,” there may be multiple cakes with joint preferences, or the cake may be discrete (as in the necklace-splitting problem). We will also discuss several challenging open questions. This talk is based on joint work with Ayumi Igarashi, Francis Su, and Shira Zerbib.

More information about the speaker

Diederik Coppiters

(UCLouvain - Institute of Mechanics, Materials and Civil Engineering) 

Will give a presentation on:

When the optimum is not enough: designing energy systems for an unpredictable world

Abstract: 

Computer models have transformed how we analyze and optimize energy systems. However, the designs they produce are only as reliable as the assumptions they make about future operating conditions—conditions that are dynamic, complex, and deeply uncertain.
This talk examines how to place uncertainty at the center of energy system design. I first present methods to characterize uncertainty under data scarcity and to propagate it through computationally demanding models using surrogate-based approaches. I then show how these methods can be used to study the sensitivity of optimal designs in linear programming models, and how they can be embedded in metaheuristic optimization frameworks for nonlinear system models to target expected performance, robustness, and, for the first time, antifragility—systems that benefit from variability rather than merely withstand it.
Finally, I address structural uncertainty: factors such as stakeholder preferences, implementation constraints, and social acceptance that are difficult to formalize, but often decisive in practice. Rather than focusing on a single optimum, I show how Modeling to Generate Alternatives can identify structurally different near-optimal designs, and how interpretable machine learning can turn the large solution sets into actionable design rules and policy-relevant archetypes.
The methods are illustrated with applications ranging from detailed process engineering models to national-scale energy system analyses. Taken together, they shift the focus from optimizing for a single predicted scenario to designing systems that remain effective in an unpredictable future.

More info about the speaker

We will host a special Brownbag Lunch series, "CORE 6 from 60" where current junior researchers will present 1 paper from each decade of CORE's history.

• 1970s: Wednesday, 15 April 2026

Claude d'Aspremont, Jean J. Gabszewicz and Jacques-François Thisse
On Hotelling's "Stability in competition"
In : Econometrica, 1979, vol. 47(5), p. 1145-1150

      presented by: Sumit Shrivastav

Research Conference (May 7-8): 

A two-day research conference on “The Past, the Present, and the Future of DSGE Models”, featuring presentations and discussions by leading scholars in macroeconomics.

Program

You will find all informations on the dedicated Website:

Summer School Brussels

This two-day workshop brings together leading economists to present and discuss cutting-edge research on consumer protection. The program covers a broad range of topics at the intersection of industrial organization, behavioral economics, and public policy, including hidden fees and shrouded pricing, data privacy and consent design, gambling and addiction, price discrimination, behavioral nudges and targeted interventions, and the welfare effects of regulation.

The workshop features two keynote presentations — by Chiara Farronato (Harvard Business School) on consumer welfare in data sharing, and by Paul Heidhues (ESMT Berlin) on procrastination markets — alongside seven additional paper presentations by researchers from leading institutions.

The event will take place at the Foyer Royal (entry of Louvain House). Participation is free, but registration is required. Please register using this link.

May 19^th