This paper examines how regulation can push an oligopoly from one pricing regime to another. It uses rich data from Chilean pharmacy chains to study a ban on comparative price advertising. Before the ban, ads created demand spillovers across products, making aggressive loss-leader pricing profitable. Once these spillovers were removed, selling below cost became unattractive for any firm, and prices quickly shifted to a coordinated, higher level. A structural demand model shows that the ban reduced both price elasticity and cross-product spillovers, and counterfactuals indicate that the loss of spillovers, rather than just lower elasticity, mainly explains the move to the new coordinated pricing regime. The results show how well-intentioned regulation can unintentionally promote price coordination by weakening the mechanisms that support competitive outcomes.
Estimating the Number of Components in Panel Data Finite Mixture Regression Models with an Application to Production Function Heterogeneity
This paper develops the likelihood ratio-based test of the null hypothesis of a M0-component model against an alternative of (M0 + 1)-component model in the normal mixture panel regression by extending the Expectation-Maximization (EM) test of Chen and Li (2009a) and Kasahara and Shimotsu (2015) to the case of panel data. We show that, unlike the cross-sectional normal mixture, the first-order derivative of the density function for the variance parameter in the panel normal mixture is linearly independent of its second-order derivatives for the mean parameter. On the other hand, like the cross-sectional normal mixture, the likelihood ratio test statistic of the panel normal mixture is unbounded. We consider the Penalized Maximum Likelihood Estimator to deal with the unboundedness, where we obtain the data-driven penalty function via computational experiments. We derive the asymptotic distribution of the Penalized Likelihood Ratio Test (PLRT) and EM test statistics by expanding the log-likelihood function up to five times for the reparameterized parameters. The simulation experiment indicates good finite sample performance of the proposed EM test. We apply our EM test to estimate the number of production technology types for the finite mixture Cobb-Douglas production function model studied by Kasahara et al. (2022) using the panel data of the Japanese and Chilean manufacturing firms. We find the evidence of heterogeneity in elasticities of output for intermediate goods, suggesting that production function is heterogeneous across firms beyond their Hicks-neutral productivity terms.
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
This paper investigates how the discount factor and payoff functions can be identified in stationary infinite-horizon dynamic discrete choice models. In single-agent models, we show that common nonparametric assumptions on per-period payoffs -- such as homogeneity of degree one, monotonicity, concavity, zero cross-differences, and complementarity -- provide identifying restrictions on the discount factor. These restrictions take the form of polynomial equalities and inequalities with degrees bounded by the cardinality of the state space. These restrictions also identify payoff functions under standard normalization at one action. In dynamic game models, we show that firm-specific discount factors can be identified using assumptions such as irrelevance of other firms' lagged actions, exchangeability, and the independence of adjustment costs from other firms' actions. Our results demonstrate that widely used nonparametric assumptions in economic analysis can provide substantial identifying power in dynamic structural models.
Heterogeneous Diffusion of Electric Vehicles in China: Demand, Learning, Product Entry, and the Incidence of Industrial Policy
China's electric-vehicle (EV) sales share rose from about 1% of passenger-vehicle sales in 2015 to roughly 45% in 2024. This paper studies this rapid technology diffusion using an equilibrium differentiated-products model of the automobile market and a Shapley decomposition of the model-implied 2015–2024 change in national EV share. The decomposition separates six complementary channels: Quality, Variety, Battery, Subsidy, Residual, and Market. Product improvement is the dominant force, with Quality contributing 45.47% in EV-share units, followed by Variety expansion at 14.82% and Battery-related cost decline at 8.19%. The Subsidy block contributes −13.63% because direct purchase subsidies were phased down relative to the 2015 regime, but a separate no-subsidy counterfactual shows that subsidies still increased adoption and private surplus by supporting demand, battery-cost learning, and product availability. The diffusion path is also heterogeneous across cities, firms, and consumers: Tier 1 cities reached double-digit EV penetration years before lower-tier cities, EV-native firms retain a substantially larger share of their 2024 EV business under subsidy removal than legacy OEMs do, and per-capita consumer-surplus loss from subsidy removal is roughly five times larger in Tier 1 than in the residual “Rest” tier.
A Generalized Finite Dependence Framework for Dynamic Discrete Choice Models
This paper extends the finite dependence framework of Arcidiacono and Miller (2011, 2020) for dynamic discrete choice models. For dependence horizons ρ ≥ 2, the joint weight over a future path is a product of per-step decision weights, making the search for valid weighting schemes a nonlinear problem. We introduce a flow parameterization that linearizes this product structure, reducing the problem to a linear optimization with linear constraints—a convex quadratic program solvable via a single sparse linear system. This linearization enables algorithmic discovery of finite dependence representations, extending the framework beyond models with renewal actions to environments with persistent state variables, including capital accumulation, dynamic games, and models with high-order state dependence.
Regulating the Traffic Economy: Salary Caps, Superstar Rents, and Platform Production
This paper studies how the 2018 actor salary-cap regulation reshaped competition in the Chinese long-form video streaming industry. We model the pre-regulation equilibrium as a prisoner's dilemma in which platforms bid aggressively for a small set of traffic-generating stars, driving up costs and eroding profits. We interpret the salary cap as a public and enforceable constraint that limited bidding competition and shifted the market toward a lower-cost equilibrium. To quantify these effects, we develop and estimate a unified structural model of consumer demand, actors' dynamic career choices, and platform sourcing decisions. The model implies a shift away from advertising-driven traffic acquisition and toward subscription-oriented competition based more heavily on content quality, with implications for production incentives, vertical integration, and bargaining outcomes. The model also matches key post-regulation patterns in the data, including changes in actors' career choices and in the relationship between quality and viewership. More broadly, our results show how a targeted wage constraint in a key upstream input market can reshape business models, bargaining outcomes, and the basis of competition in a digital media industry.
This paper empirically examines the evolution of product space choices in the Chinese automobile market, focusing on the strategic entry decisions of firms into the electric vehicle (EV) segment. We investigate how the prior production of plug-in hybrid electric vehicles (PHEVs) or hybrid electric vehicles (HEVs) by firms reduces their entry costs into the battery electric vehicle (BEV) market. Our findings suggest that firms can adopt a stepwise approach to product development, gradually moving from conventional vehicles to PHEVs, then to HEVs, and finally to BEVs, to ease the adoption costs associated with the transition to fully electric models. We analyze the impact of this strategic behavior on the broader automotive market and explore the implications for policy design, particularly in the context of subsidies aimed at promoting EV adoption. By understanding the dynamics of firms' product space choices and their response to policy incentives, this study contributes to the ongoing debate on how to effectively accelerate the transition to sustainable transportation solutions.
Dual Network Effects in the EV Transition: Rise of Charging, Decline of Gas Stations
The transition from internal combustion engine vehicles (ICEs) to electric vehicles (EVs) is shaped by dual network effects: positive feedback between EV adoption and charging-station deployment, and opposing feedback between ICE ownership and gas-station viability. We develop a theoretical and empirical framework in which the two networks co-evolve and compete, generating tipping dynamics in which a market converges to an EV- or ICE-dominated equilibrium according to whether adoption crosses a critical threshold. Using city-level data from China, 2015–2024, we estimate a structural model with random-coefficient demand, dynamic charging-station entry, and Bertrand-Nash pricing on the supply side. Estimated tipping thresholds vary widely across cities and are linked through cross-market spillovers from national pricing, product variety, and battery-cost learning. Counterfactuals show that uniform subsidies are dominated by spatially targeted policies that prioritize low-threshold markets, lowering the cumulative subsidy needed to ignite a self-sustaining transition and informing the optimal timing of policy withdrawal.
Dynamic Decision Models with Continuous-Discrete Mix Choices
This paper develops a framework for estimating dynamic decision models in which agents simultaneously make continuous and discrete choices. We derive identification conditions and propose an estimation strategy that accommodates mixed choice sets in a unified dynamic programming framework.
Older Working Papers
Using Euler equation to estimate non-finite-dependent dynamic discrete choice model with unobserved heterogeneity (with Hiro Kasahara) — Slides, Draft Paper
Building up Trust in a Dynamic Game: A Study on Collusive Price-fixing in the Chilean Pharmaceutical Retail Industry (Original version of the Job Market Paper, December 2020 preliminary draft) — Draft Paper
Losing Market Share in a Growing Industry: BYD Company and Electric Vehicles in China (with Victor Aguirregabiria and Yiran Hao) — Draft Paper
Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with 2-period Finite Dependence (with Hiro Kasahara and Katsumi Shimotsu) — New Version Coming Soon, Slides, Paper