A maximum entropy approach to estimation and inference in dynamic models

Article Abstract:

Two estimation problems constructed from dynamic discrete time models are examined. One problem concerns noisy state observations in a case where there is nonlinearity between the observation and state equations. In this problem, the goal is to estimate the observation and state equation parameters and the unknown values of the state variable. The other problem concerns a case of linear-quadratic control where the objective is to estimate state equation and objective function parameters. In both cases, a nonlinear inversion procedure is proposed for estimating unknown parameters.

Models, Dynamic programming, Mathematical optimization, Optimization theory, Time-series analysis, Time series analysis

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Estimating the size distribution of firms using government summary statistics

Article Abstract:

The maximum entropy method can be used to compute the market shares of firms in an industry even if the information available from government summary statistics is limited in scope. This estimation method is shown to be applicable to information such as the Herfindahl-Hirschmenn Index and the four-firm concentration ratio. The use of the maximum entropy method is also illustrated through the estimation of market shares in 20 industries.

Industrial organization, Market share, Corporate size

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Dynamic taxes and quotas with learning

Article Abstract:

A comparative study is conducted on taxes and quotas when non-strategic firms and the regulator have information about abatement costs. The optimal quota policy is characterized and results identify the informational advantage of taxes.

United States, Forecasts, trends, outlooks, Analysis, Forecasts and trends, Corporate taxes, Market trend/market analysis, Tax policy, Corporations

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