Semiparametric Estimation of a Dynamic Game of Incomplete Information

Recently, empirical industrial organization economists have proposed estimators for dynamic games of incomplete information. In these models, agents choose from a finite number actions and maximize expected discounted utility in a Markov perfect equilibrium. Previous econometric methods estimate the probability distribution of agents%u2019 actions in a first stage. In a second step, a finite vector of parameters of the period return function are estimated. In this paper, we develop semiparametric estimators for dynamic games allowing for continuous state variables and a nonparametric first stage. The estimates of the structural parameters are T1/2 consistent (where T is the sample size) and asymptotically normal even though the first stage is estimated nonparametrically. We also propose sufficient conditions for identification of the model.

Identification and Estimation of Discrete Games of Complete Information

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation-based estimators for static, discrete games. With appropriate exclusion restrictions about how covariates enter into payoffs and influence equilibrium selection, the model is identified with only weak parametric assumptions. Monte Carlo evidence demonstrates that the estimator can perform well in moderately-sized samples. As an application, we study the strategic decision of firms in spatially-separated markets to establish a presence on the Internet.

Moral Hazard, Adverse Selection and Health Expenditures: A Semiparametric Analysis

Theoretical models predict asymmetric information in health insurance markets may generate inefficient outcomes due to adverse selection and moral hazard. However, previous empirical research has found it difficult to disentangle adverse selection from moral hazard in health care. We empirically study this question by using data from the Health and Retirement Study to estimate a structural model of the demand for health insurance and medical care. Using a two-step semi-parametric estimation strategy we find significant evidence of moral hazard, but not of adverse selection.

Identification and Estimation of Discrete Games of Complete Information

We discuss the identification and estimation of discrete games with complete information. Following Bresnahan and Reiss, a discrete game is defined to be a generalization of a standard discrete choice model in which utility depends on the actions of other players. Using recent algorithms that compute the complete set of the Nash equilibria, we propose simulation-based estimators for static, discrete games. With appropriate exclusion restrictions about how covariates enter into payoffs and influence equilibrium selection, the model is identified with only weak parametric assumptions. Monte Carlo evidence demonstrates that the estimator can perform well in moderately-sized samples. As an illustration, we study the strategic decisions of firms in spatially-separated markets in establishing a presence on the InternetEmpirical Industrial Organization, Simulation Based Estimation, Homotopies

The Perceptions of Macao Undergraduates Regarding Help Websites for Problem Gambling

This study conducted a web-surfing exercise and a questionnaire survey among a group of Macao undergraduate students regarding the websites that offered help with problem gambling. The results of this study found that most help websites in Macao and Hong Kong provided basic information-sharing service. The students indicated that they would choose their preferred help organization based on factors such as trust, familiarity, and the characteristics of the websites. They also gave comments/suggestions related to the publicity, design, contents, and focus of the websites. This study discussed the results and their implications for future research and practice

Product Construction of Affine Codes

Binary matrix codes with restricted row and column weights are a desirable method of coded modulation for power line communication. In this work, we construct such matrix codes that are obtained as products of affine codes - cosets of binary linear codes. Additionally, the constructions have the property that they are systematic. Subsequently, we generalize our construction to irregular product of affine codes, where the component codes are affine codes of different rates.Comment: 13 pages, to appear in SIAM Journal on Discrete Mathematic