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双重差分平均处理效应推断：固定 b 方法AI 解读

This paper provides an analysis of the standard errors proposed by Driscoll and Kraay (1998) (DK) in linear Difference-in-Differences (DD) models with fixed effects and individual-specific time trends. The analysis is accomplished within the fixed-b asymptotic framework developed by Kiefer and Vogelsang (2005) for heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimator based tests. For both the fixed-N, large-T, and large-N, large-T cases, it is…

不可观测异质性与内生支出下反事实需求的界限AI 解读

We propose a method to predict rational counterfactual demand responses from repeated cross-sections. We derive bounds on the distribution of counterfactual demands that are consistent with the Weak Axiom of Revealed Preferences, without putting any restriction on the preference heterogeneity across consumers. In contrast to existing methods, we also allow for endogeneity of total expenditures. In addition, the method can readily incorporate restrictions on the income…

使用高频数据检验因子数量的秩检验AI 解读

In the literature, consistency of the estimates of the number of factors for large-dimensional factor models had been extensively studied recently. But the second-order property of the estimator has long been unsolved due to lack of limiting distribution of the estimators. In this paper, we propose a rank test of the number of factors using large panel high-frequency data contaminated with microstructure noise. The rank test is realized by forming a fixed number of…

第一价格拍卖中基于 GPV 估计量的推断AI 解读

We consider inference on the probability density of valuations in the first-price sealed-bid auctions model within the independent private value paradigm. We show the asymptotic normality of the two-step nonparametric estimator of Guerre et al. (2000) (GPV), and propose an easily implementable and consistent estimator of the asymptotic variance. We prove the validity of the pointwise percentile bootstrap confidence intervals based on the GPV estimator. Lastly, we use the…

使用排序选择数据半参数估计随机效用模型AI 解读

We propose semiparametric methods for estimating random utility models using rank-ordered choice data. Our primary method is the generalized maximum score (GMS) estimator. With partially rank-ordered data, the GMS estimator allows for arbitrary forms of interpersonal heteroskedasticity. With fully rank-ordered data, the GMS estimator becomes considerably more flexible, allowing for random coefficients and alternative-specific heteroskedasticity and correlations. The GMS…

收入区间数据下离散选择的应用福利分析AI 解读

This paper concerns empirical measurement of Hicksian consumer welfare under interval-reported income. Bhattacharya (2015, 2018a) has shown that for discrete choice, welfare distributions resulting from a hypothetical price-change can be expressed as closed-form transformations of choice probabilities. However, when income is interval-reported, as is the case in many surveys, the choice probabilities, and hence welfare distributions are not point-identified. We derive bounds…

组合 p 值检验协整回归中的多重结构突变AI 解读

We propose a multiple hypothesis testing approach to assess structural stability in cointegrating regressions. Underlying tests are constructed via a Vector Error Correction Model and generalize the reduced rank regression procedures of Hansen (2003). We generalize the likelihood ratio test proposed in Hansen (2003) to accommodate unknown break dates through the specification of several scenarios regarding the number and the location of the breaks. We define a combined…

部分识别光滑凸模型的贝叶斯推断AI 解读

This paper proposes novel Bayesian procedures for partially identified models when the identified set is convex with a smooth boundary, whose support function is locally smooth with respect to the data distribution. Using the posterior of the identified set, we construct Bayesian credible sets for the identified set, the partially identified parameter and their scalar transformations. These constructions, based on the support function, benefit from several computationally…

预期短缺与风险价值的动态半参数模型AI 解读

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to overcome the problem of “elicitability” for ES by jointly modeling ES and VaR, and…

双重自回归模型的严格平稳性检验与 GLAD 估计AI 解读

In this article we develop a tractable procedure for testing strict stationarity in a double autoregressive model and formulate the problem as testing if the top Lyapunov exponent is negative. Without strict stationarity assumption, we construct a consistent estimator of the associated top Lyapunov exponent and employ a random weighting approach for its variance estimation, which in turn are used in a t-type test. We also propose a GLAD estimation for parameters of interest,…

大数据流失偏误的面板分位数方法：随机实验背景下的证据AI 解读

This paper introduces a quantile regression estimator for panel data models with individual heterogeneity and attrition. The method is motivated by the fact that attrition bias is often encountered in Big Data applications. For example, many users sign-up for the latest program but few remain active users several months later, making the evaluation of such interventions inherently very challenging. Building on earlier work by Hausman and Wise (1979), we provide a simple…

三阶段半参数推断：控制变量与可微性AI 解读

We show the usefulness of the path-derivative calculations that were introduced in econometrics by Newey (1994) for multi-step semi-parametric estimators. These estimators estimate a finite-dimensional parameter using moment conditions that depend on nonparametric regressions on observed and estimated regressors that are estimated in the second and first step of the estimation procedure, respectively. Our earlier paper showed that Newey’s calculations can be extended to…

允许内生性的回归结构变化无模型一致检验AI 解读

Structural instability leads to misleading inference and imprecise prediction of time series models that assume stationarity. We propose a model-free consistent test for structural change in regression by testing the instability of the Fourier transform of data. This novel approach avoids smoothed nonparametric estimation of the unknown regression function and so is free of the “curse of dimensionality” problem. Unlike the existing literature, we allow for endogenous and…

若干非可分离散选择模型的构造性识别AI 解读

This paper introduces new results on the nonparametric identification of separable and nonseparable discrete choice models. It presents constructive methods for recovering the derivatives of the utility functions of the alternatives in a set, when these utility functions are nonparametric and nonseparable in unobservable random terms. When the utility functions are separable, the constructive methods require fewer assumptions. It is assumed that only the probability of…

无需独立性的卷积AI 解读

Widely used convolution and deconvolution techniques traditionally rely on independence assumptions, often criticized as being strong. We observe that the convolution theorem actually holds under a weaker assumption, known as subindependence. We show that this notion is arguably as weak as a conditional mean assumption. We report various simple characterizations of subindependence and devise constructive methods to generate subindependent random variables. We extend…

提高模型设定检验的功效AI 解读

This paper shows how to increase the power of Hausman’s (1978) specification test as well as the difference test in a large class of models. The idea is to impose the restrictions of the null and the alternative hypotheses when estimating the covariance matrix. If the null hypothesis is true then the proposed test has the same distribution as the existing ones in large samples. If the hypothesis is false then the proposed test statistic is larger with probability approaching…

横截面与面板数据中的非可分多项选择模型AI 解读

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimensional unobserved heterogeneity with cross-section and panel data. We show that derivatives of choice probabilities with respect to continuous attributes are weighted averages of utility derivatives in cross-section…

固定效应模型中的因变量缺失AI 解读

This paper considers estimation of linear fixed-effects models in which the dependent variable may be missing. For cross-sectional units with dependent variables missing, use of covariate information from all time periods can provide efficiency gains relative to complete-data methods. A classical minimum distance (CMD) estimator based upon Chamberlain (1982, 1984), which is consistent under a missing-at-random (MAR) type assumption, is proposed for the static fixed-effects…

以Besov函数类为索引的依赖过程不变原理及线性Hausman检验应用AI 解读

This paper considers functional central limit theorems for stationary absolutely regular mixing processes. Bounds for the entropy with bracketing are derived using recent results in Nickl and Pötscher (2007). More specifically, their bracketing metric entropy bounds are extended to a norm defined in Doukhan, Massart and Rio (1995, henceforth DMR) that depends both on the marginal distribution of the process and on the mixing coefficients. Using these bounds, and based on a…

高频数据中市场微观结构噪声的Hausman检验AI 解读

We develop tests that help assess whether a high frequency data sample can be treated as reasonably free of market microstructure noise at a given sampling frequency for the purpose of implementing high frequency volatility and other estimators. The tests are based on the Hausman principle of comparing two estimators, one that is efficient but not robust to the deviation being tested, and one that is robust but not as efficient. We investigate the asymptotic properties of…

杰里·豪斯曼AI 解读

This paper is in two parts. The first part includes some reminiscences of my life with Jerry since we both arrived at MIT in 1972. The second part discusses what I view as Jerry’s most important and long-lasting contribution to energy economics. Jerry has been an amazing friend and colleague for 45 years. His paper analyzing consumer choice of energy using durable equipment and the estimate of consumer discount rates continues to be the gold standard from an analytical…

工具变量估计目标的结构AI 解读

When the overidentifying restrictions of the constant-effect linear instrumental variables model fail, common IV estimators converge to different probability limits. I characterize the estimands of two stage least squares, two step GMM, and limited information maximum likelihood as functions of the single-instrument estimands from the just-identified IV regressions which consider each instrument separately. The limited information maximum likelihood estimand is found to be…

非平衡面板中的相关随机效应模型AI 解读

I propose some strategies for allowing unobserved heterogeneity to be correlated withobserved covariates and sample selection for unbalanced panels. The methods are extensions of the Chamberlain–Mundlak approach for balanced panels when explanatory variables are strictly exogenous conditional on unobserved effects. A byproduct is fully robust Hausman tests for unbalanced panels. Even for nonlinear models, in many cases the estimators can be implemented using standard…

选择受限下的劳动供给与税收AI 解读

A model of labour supply and taxation is developed in which observed hours reflect both the distribution of preferences and restrictions on choices. Hours restrictions are placed in a constrained rational choice setting in which the set of alternative hours on offer is restricted. Choices are made on a random subset of possible hours. We focus on the case where the choice set contains at most two offers. We show that when the choice set distribution is known, preferences can…