Equilibrium Transition from Loss-Leader Competition: How Advertising Restrictions Facilitate Price Coordination in Chilean Pharmaceutical Retail
Job Market Paper | Resubmitted to The RAND Journal of Economics
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.
Testing the number of components in finite mixture model with normal panel regression
with Hiro Kasahara
Resubmitted to Quantitative Economics
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
with Hiro Kasahara and Katsumi Shimotsu
Submitted
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 a New Technology: Subsidies, Reallocation, and the Rise of China's Electric-Vehicle Market, 2015–2024
China's electric-vehicle share of new passenger-vehicle registrations rose from under one percent to 44% between 2015 and 2024, concentrating first in lower-income, lower-tier, budget segments before propagating up the income and quality distributions. I decompose this transition using a BLP demand system on a 79-market panel, a Shapley value over 2⁸ counterfactual equilibria, and an Olley–Pakes split of the Lerner change. The mean Lerner rose by +0.138 points: within-firm growth accounts for 112%, reallocation −12%, while the Herfindahl index fell from 1,374 to 887 — the inverse of the U.S. superstar pattern. Battery learning (+27.3 pp) and an EV-specific unobserved trend (+15.1 pp) drive most of the +44.3 pp adoption rise; the wealth-effect channel under 73% income growth pulls −22.9 pp. Direct subsidies contribute only −2.7 pp statically, but a never-existed-subsidy forward simulation gives 2024 EV share counterfactually −21.7 to −40.6 pp lower: subsidies were constitutive of the bootstrap, not a marginal price wedge.
A Generalized Finite Dependence Framework for Dynamic Discrete Choice Models
with Hiro Kasahara and Katsumi Shimotsu
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.