Research
1. Digital Economics
Price Discrimination and Big Data: Evidence from a Mobile Puzzle Game, with Christian Helmers, Alessandro Iaria, Julian Runge, and Stefan Wagner (Revise and Resubmit, International Journal of Industrial Organization)
Abstract: We use a unique dataset from a mobile puzzle game to investigate the welfare consequences of price discrimination. We rely on experimental variation to characterize player behavior and estimate a model of demand for game content. Our counterfactual simulations show that optimal uniform pricing would increase profit by +340% with respect to the game developer’s observed pricing. This is almost the same as the increase in profit associated with first-degree price discrimination (+347%). All pricing strategies considered—including optimal uniform pricing—would induce a transfer of surplus from players to game developer without, however, generating sizeable dead-weight losses.
How to improve both the pay and quality of microtasking platforms ? (Working Paper Arriving Soon with Chiara Belletti)
Abstract : Micro-tasking platforms enable the collection of data used to train machine learning algorithms and artificial intelligence. However, a classical Principal-Agent problem may limit the quality of the data produced. As firms do not always monitor the quality of the work done with sufficient frequency, a moral hazard problem may arise. We develop a structural model of equilibrium demand and supply of effort to measure quality and monitoring behavior. We estimate the parameters of this model using proprietary data from a leading micro-tasking platform. We find that metrics relying on observed task rejection underestimate quality. We discuss several mitigation strategies. We suggest a more accurate back-of-the-envelope correction based on a firm’s own monitoring rate to increase the employers awareness about the potential data quality. Finally, we discuss incentive schemes to induce higher quality work. Using counter-factual simulations, we show that charging penalties for workers with a rejected task could induce higher effort and require less monitoring from the firms.
Study of Deemed Suppliers on VAT Tax Fraud on French Digital Platforms (Paquet TVA, DAC 7) (joint work with French Ministry of Public Finances (DGFIP, Matthieu Chtioui, Christophe Bellego).
2. Antitrust Policy and Labor Markets
Wages, Hires, and Labor Market Concentration, with Ioana Marinescu and Ivan Ouss (2021, Journal of Economic Behavior and Organization)
Abstract: How does employer market power affect workers? We compute the concentration of new hires by occupation and commuting zone in France using linked employer-employee data. Using instrumental variables, we find that a 10% increase in labor market concentration decreases hires by 3.2% and their hourly wage by nearly 0.5%, as hypothesized by monopsony theory. Based on a simple merger simulation, we find that a merger between the top two employers in the retail industry would be most damaging, with about 30 million euros in annual loss to the wage bill of new hires, and a 3000 decrease in annual hires.
Media : Libération , Concurrences , Resolution Foundation, Groupe d'Experts sur le SMIC
When, and by How Much, Can Salary Arbitration Raise Wages ? (Revise & Resubmit, Oxford Journal of Economics and Statistics)
Abstract: In a typical labor market, a small number of firms set wages below the worker's marginal productivity. Few instruments are available to the policy maker: encouraging entry of new competitors is costly and firms are seldom broken up for the purpose of creating additional competition. This article clarifies the conditions under which Salary Arbitration can be a relevant policy instrument, capable of setting wages to the levels of a more competitive labor market. Under this policy, both the firm and worker can unilaterally threaten to call an arbitrator which has the final say over the wage. This threat potentially increases the worker's outside-option which can then result in higher wages. As evidence, this paper relies on a quasi-random discontinuity in the rule determining eligibility for Final-Offer Arbitration within Major League Baseball to study its effects on compensation and inequality. It finds that following eligibility for arbitration, wages increased, on average, by at least 50% in comparison to a group of similar workers who faced a monopsony. Upon joining an imperfectly competitive market, the post-arbitration wages do not markedly change, suggesting they were already set to their market level. A simple theoretical model is used to understand this market-mimicking behavior: it shows that to copy market outcomes, the arbitrator must be able to benchmark her assessment using wages actually resulting from a comparable but more competitive market. Therefore, the relevancy of Salary Arbitration as a policy is context-dependent on the existence of such a market.
How to Detect and Measure Labor Market Collusion? (Job Market Paper)
Abstract: With the aim of expanding the set of tools available to antitrust practitioners, this paper develops two new econometric methods to detect and measure the effects of labor market cartels. The first method is reduced form and aims to estimate wage loss. It exploits the inter-percentile difference between high earners and low earners within a difference-in-differences framework. This approach is simple to implement, can easily be explained to non-economists, measures heterogeneous effects, and requires no additional data compared to that necessary for a before-after analysis. The method is illustrated by revisiting the 1986-8 case of collusion in Major League Baseball, measuring an average yearly income loss of 26%. Second, this paper develops a structural model of labor market competition for the purpose of detecting collusive behavior. Applied to the data, it reveals that at the beginning of the cartel, there were heightened barriers to mobility across firms, rising profits, and a decreasing labor share of income. Surprisingly, these patterns sustain past the end date of the cartel, suggesting important and underestimated long-run effects. Finally, the structural model is used to simulate counter-factual wages, revealing that the yearly average wage should have been at least 30% higher.
3. Applied Econometrics
Abstract: Log-linear models are prevalent in empirical research. Yet, how to handle zeros in the dependent variable remains an unsettled issue. This article clarifies it and addresses the "log of zero'' by developing a new family of estimators called iterated Ordinary Least Squares (iOLS). This family nests standard approaches such as log-linear and Poisson regressions, offers several computational advantages, and corresponds to the correct way to perform the popular log(Y+1) transformation. We extend it to the endogenous regressor setting (i2SLS) and overcome other common issues with Poisson models, such as controlling for many fixed-effects. We also develop specification tests to help researchers select between alternative estimators. Finally, our methods are illustrated through numerical simulations and replications of landmark publications.
Among the Top 525 most downloaded papers of SSRN.
Stata Software available from : https://github.com/ldpape/iOLS_delta
Media : Empirical Legal Studies, Eviews, David Giles' Blog.