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误差可预测时的反事实结果插补AI 解读

A crucial input into causal inference is the imputed counterfactual outcome. Imputation error can arise because of sampling uncertainty from estimating the prediction model using the untreated observations, or from out-of-sample information not captured by the model. While the literature has focused on sampling uncertainty, it vanishes with the sample size. Often overlooked is the possibility that the out-of-sample error can be informative about the missing counterfactual…

高维面板数据缺失值与协方差的因子插补AI 解读

Economists are blessed with a wealth of data for analysis, but more often than not, values in some entries of the data matrix are missing. Various methods have been proposed to handle missing observations in a few variables. We exploit the factor structure in panel data of large dimensions. Our tall-project algorithm first estimates the factors from a tall block in which data for all rows are observed, and projections of unit specific sample size are then used to estimate…

分类调查回答的潜在狄利克雷分析AI 解读

Beliefs are important determinants of an individual’s choices and economic outcomes, so understanding how they comove and differ across individuals is of considerable interest. Researchers often rely on surveys that report individual beliefs as qualitative data. We propose using a Bayesian hierarchical latent class model to analyze the comovements and observed heterogeneity in categorical survey responses. We show that the statistical model corresponds to an economic…

矩阵补全、反事实与缺失数据的因子分析AI 解读

This paper proposes an imputation procedure that uses the factors estimated from a tall block along with the re-rotated loadings estimated from a wide block to impute missing values in a panel of data. Assuming that a strong factor structure holds for the full panel of data and its sub-blocks, it is shown that the common component can be consistently estimated at four different rates of convergence without requiring regularization or iteration. An asymptotic analysis of the…

基于辅助统计量的模拟估计：ABC与模拟最小距离的联系AI 解读

The frequentist method of simulated minimum distance (SMD) is widely used in economics to estimate complex models with an intractable likelihood. In other disciplines, a Bayesian approach known as Approximate Bayesian Computation (ABC) is far more popular. This paper connects these two seemingly related approaches to likelihood-free estimation by means of a Reverse Sampler that uses both optimization and importance weighting to target the posterior distribution. Its hybrid…

动态模型中的测量误差AI 解读

Static models that are not identifiable in the presence of white noise measurement errors are known to be potentially identifiable when the model has dynamics. However, few results are available for the plausible case of serially correlated measurement errors. This paper provides order and rank conditions for “limited information” identification of parameters in dynamic models with measurement errors where some aspects of the probability model are not fully specified or…

数据丰富环境中的工具变量估计AI 解读

We consider estimation of parameters in a regression model with endogenous regressors. The endogenous regressors along with a large number of other endogenous variables are driven by a small number of unobservable exogenous common factors. We show that the estimated common factors can be used as instrumental variables and they are more efficient than the observed variables in our framework. Whereas standard optimal generalized method of moments estimator using a large number…

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found to be highly persistent, further complicating estimation and inference. We propose a variant of the translog demand system, the NTLOG, and an associated estimator that can be applied…

价格与税制改革的参数和非参数分析方法AI 解读

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…

价格与税制改革的参数和非参数方法AI 解读

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…

解释变量非平稳时需求系统的齐次性检验AI 解读

Abstract An implication of optimizing theory is that demand functions are homogeneous of degree zero in prices and nominal income. Evidence based on estimations of demand systems has repeatedly found this restriction to be rejected by the data. However, the hypothesis is often formulated in terms of regressors that are non‐stationary. This paper re‐examines the evidence for homogeneity in light of recent developments in time‐series econometrics with special emphasis on the…