Parametric and Nonparametric Approaches to Price and Tax Reform
价格与税制改革的参数和非参数方法AI 解读 ↓
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价格与税制改革的参数和非参数方法AI 解读 ↓
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In many public policy problems, we need to estimate the way in which policy changes affect people's behavior. In the analysis of tax and subsidy reform—the topic of this article—we need to know how tax-induced price changes affect the amounts that people buy of the taxed goods. We present various economic and statistical approaches to obtaining the required estimates. We consider the standard structural methods in economics, where the behavior and welfare of individual agents are captured simultaneously by the specification of utility functions whose parameters are to be estimated. We argue that these methods are less useful than alternatives that directly consider the derivatives of the regression function of average behavior. We consider both parametric and nonparametric estimators of these derivatives in the context of price reform for foods in Pakistan, focussing on the advantages and disadvantages of “average derivative estimation” (ADE). ADE is attractive in principle, because it directly estimates the statistics required for policy analysis. In the practical case considered here, neither technique is a clear winner; each has strengths and weaknesses.
未观测竞争下的第一价格拍卖非参数识别:密度断点框架
We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be nonparametrically identified in a second step. This extends, under testable…
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未观测竞争下的第一价格拍卖非参数识别:密度不连续框架
We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be nonparametrically identified in a second step. This extends, under testable…
BLP 模型中的条件矩估计与推断
The random-coefficient demand model of Berry, Levinsohn, and Pakes (1995) is commonly estimated by the generalized method of moments (GMM), using an unconditional moment restriction with a fixed set of instruments. Identification of the model, however, rests on a conditional moment restriction. The two are not equivalent: the unconditional restriction may admit additional parameter values. We construct a counterexample in which the model is identified by the conditional…