567 research outputs found
Urban-biased structural change
Using firm-level data from France, we document that the shift of economic activity from manufacturing to services over the last few decades has been urban-biased: structural change has been more pronounced in areas with higher population density. This bias can be accounted for by the location choices of large services firms that sort into big cities and large manufacturing firms that increasingly locate in suburban and rural areas. Motivated by these findings, we estimate a structural model of city formation with heterogeneous firms and international trade. We find that agglomeration economies have strengthened for services but weakened for manufacturing. This divergence is a key driver of the urban bias, but it dampens aggregate structural change. Rising manufacturing productivity and falling international trade costs further contribute to the growth of large services firms in the densest urban areas, boosting services productivity and services exports, but also land prices
On linear, fractional, and submodular optimization
In this thesis, we study four fundamental problems in the theory of optimization. 1. In fractional optimization, we are interested in minimizing a ratio of two functions over some domain. A well-known technique for solving this problem is the Newton– Dinkelbach method. We propose an accelerated version of this classical method and give a new analysis using the Bregman divergence. We show how it leads to improved or simplified results in three application areas. 2. The diameter of a polyhedron is the maximum length of a shortest path between any two vertices. The circuit diameter is a relaxation of this notion, whereby shortest paths are not restricted to edges of the polyhedron. For a polyhedron in standard equality form with constraint matrix A, we prove an upper bound on the circuit diameter that is quadratic in the rank of A and logarithmic in the circuit imbalance measure of A. We also give circuit augmentation algorithms for linear programming with similar iteration complexity. 3. The correlation gap of a set function is the ratio between its multilinear and concave extensions. We present improved lower bounds on the correlation gap of a matroid rank function, parametrized by the rank and girth of the matroid. We also prove that for a weighted matroid rank function, the worst correlation gap is achieved with uniform weights. Such improved lower bounds have direct applications in submodular maximization and mechanism design. 4. The last part of this thesis concerns parity games, a problem intimately related to linear programming. A parity game is an infinite-duration game between two players on a graph. The problem of deciding the winner lies in NP and co-NP, with no known polynomial algorithm to date. Many of the fastest (quasi-polynomial) algorithms have been unified via the concept of a universal tree. We propose a strategy iteration framework which can be applied on any universal tree
Essays in game theory
This dissertation studies the nature and the role of strategic uncertainty, which is uncertainty about the strategy choice of the other players. This uncertainty is typically represented by the player's probabilistic belief about the other players. In these models, analysts rely on the expected utility hypothesis to predict players' behavior. However, the expected utility model is often criticized since it excludes much interesting behavior. In the first chapter of the dissertation, I analyze a very general class of games and study a notion of rationalizability, showing it captures rationality and common knowledge of rationality in this framework. The framework is general enough to accommodate many non-expected utility models. I show that any rationalizable action profile can be made uniquely so by perturbing higher order uncertainty slightly. This result implies that the set of the rationalizable action profiles is generically a singleton. When there are multiple rationalizable action profiles, any refinement is not stable because there is another model with slightly different higher order beliefs where another action profile is uniquely rationalizable. This result also suggests that relaxing the expected utility axioms such as independence does not change behavior of the rational agents very much in strategic settings. In particular, if an action profile is uniquely rationalizable in the expected utility model, this action profile is still uniquely rationalizable even if the agents' risk attitude or ambiguity attitude changes slightly.
In the second chapter, I propose a new framework to study the role of strategic uncertainty in the information design problem while maintaining the expected utility hypothesis about the players' behavior. In the information design problem, a designer chooses an information structure, which is a probability distribution over signals she discloses to the player about the state. The designer's goal is to affect the players' decisions and implement her preferred outcome. After receiving information, the players update their belief about the other players. I characterize what is implementable when the designer takes into account potential misunderstandings of information and misspecification of beliefs of the players. In particular, I require that an outcome close to the desired one is implementable in every nearby information structure. I show that under a richness condition, an outcome is robustly implementable if and only if it is strictly dominant for all realizations of the signal. As a result, the designer's ability to affect the outcome is severely restricted and she cannot gain by disclosing information in many interesting cases. Another main result suggests that the designer has to send a more informative signal to implement a particular outcome compared to the standard case
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Dynamic Price Competition: Theory and Evidence from Airline Markets
We introduce a model of dynamic pricing in perishable goods markets with competition and provide conditions for equilibrium uniqueness. Pricing dynamics are rich because both own and competitor scarcity affect future profits. We identify new competitive forces that can lead to misallocation due to selling units too quickly: the Bertrand scarcity trap. We empirically estimate our model using daily prices and bookings for competing U.S. airlines. We compare competitive equilibrium outcomes to those where firms use pricing heuristics based on observed internal pricing rules at a large airline. We find that pricing heuristics increase revenues (4-5%) and consumer surplus (3%)
Team production and firm dynamics with search and matching models
Defence date: 10 October 2023Examining board: Prof. Philipp Kircher, (Cornell University, supervisor); Prof. Russell W. Cooper, (European University Institute, co-supervisor); Prof. Pieter Gautier, (Vrije Universiteit Amsterdam); Prof. Leo Kaas, (Goethe University Frankfurt)This thesis investigates various aspects of the effects of technological change, capital subsidies, and firm dynamics on labor reallocation, wage inequality, the gender pay gap and, coworker learning in Italy. The first chapter uses a matching model that partitions the workforce into white and blue-collar workers, and firms hire both types while optimizing their labor composition based on a quality-quantity trade-off. Technological change leads to increased capital investment, affecting labor composition and wage distribution. Results from simulation modeling on Italian data show that worker-capital complementarities drive inequality changes within firms, while worker-capital complementarities, worker-teammates complementarity, and compositional effects account for shifts in the between-firms component. The second chapter further investigates the impact of capital subsidies on the gender pay gap, highlighting the distribution of the pay gap between and within firms over time. A theoretical model explains the connection between pay gap distribution, capital intensity and skill pay gap. Reducing capital rental prices can decrease gender pay gap by allowing female workers to sort into better-matched jobs at the expense of an increased skill gap. The last chapter explores coworker learning opportunities, acknowledging firms as the ultimate arrangers of a worker’s group of colleagues. A firm dynamics general equilibrium model with human capital spillovers among colleagues is used. The model human capital allocation is efficient, as it balances learning and production complementarities based on firm productivity level. Using employer-employee data, the study reveals stylized facts on coworker spillovers conditional on firm growth and size, emphasizing the importance of a large pool of small growing firms to generate coworker learning opportunities.1. Firm Wage Inequality: Capital-Skill Complementarity and Labor Reallocation --
2. The Gender Pay Gap Between and Within Firms: Implications from Capital-Skill Complementarity and Sorting --
3. Coworker Learning with Firm Dynamics --
A. Appendix to chapter 1 --
B. Appendix to chapter 2 --
C. Appendix to chapter
Individualized Treatment Allocation in Sequential Network Games
Designing individualized allocation of treatments so as to maximize the
equilibrium welfare of interacting agents has many policy-relevant
applications. Focusing on sequential decision games of interacting agents, this
paper develops a method to obtain optimal treatment assignment rules that
maximize a social welfare criterion by evaluating stationary distributions of
outcomes. Stationary distributions in sequential decision games are given by
Gibbs distributions, which are difficult to optimize with respect to a
treatment allocation due to analytical and computational complexity. We apply a
variational approximation to the stationary distribution and optimize the
approximated equilibrium welfare with respect to treatment allocation using a
greedy optimization algorithm. We characterize the performance of the
variational approximation, deriving a performance guarantee for the greedy
optimization algorithm via a welfare regret bound. We establish the convergence
rate of this bound. We demonstrate the performance of our proposed method in
simulation exercises
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