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DIRECTIONALLY DIFFERENTIABLE ECONOMETRIC MODELS

方向可微的计量经济模型

The current article examines the limit distribution of the quasi-maximum likelihood estimator obtained from a directionally differentiable quasi-likelihood function and represents its limit distribution as a functional of a Gaussian stochastic process indexed by direction. In this way, the standard analysis that assumes a differentiable quasi-likelihood function is treated as a special case of our analysis. We also examine and redefine the standard quasi-likelihood ratio,…

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GRANGER CAUSALITY AND STRUCTURAL CAUSALITY IN CROSS-SECTION AND PANEL DATA

截面与面板数据中的格兰杰因果和结构因果

Granger noncausality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger ( G –) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well…

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A FLEXIBLE NONPARAMETRIC TEST FOR CONDITIONAL INDEPENDENCE

灵活的非参数条件独立检验

This paper proposes a nonparametric test for conditional independence that is easy to implement, yet powerful in the sense that it is consistent and achieves n −1/2 local power. The test statistic is based on an estimator of the topological “distance” between restricted and unrestricted probability measures corresponding to conditional independence or its absence. The distance is evaluated using a family of Generically Comprehensively Revealing (GCR) functions, such as the…

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Testing for monotonicity in unobservables under unconfoundedness

无混杂条件下不可观测因素单调性的检验

Monotonicity in a scalar unobservable is a common assumption when modeling heterogeneity in structural models. Among other things, it allows one to recover the underlying structural function from certain conditional quantiles of observables. Nevertheless, monotonicity is a strong assumption and in some economic applications unlikely to hold, e.g., random coefficient models. Its failure can have substantive adverse consequences, in particular inconsistency of any estimator…

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Estimating nonseparable models with mismeasured endogenous variables

含测量误差内生变量的非可分模型估计

We study the identification and estimation of covariate-conditioned average marginal effects of endogenous regressors in nonseparable structural systems when the regressors are mismeasured. We control for the endogeneity by making use of covariates as control variables; this ensures conditional independence between the endogenous causes of interest and other unobservable drivers of the dependent variable. Moreover, we recover distributions of the underlying true causes from…

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VAR for VaR: Measuring tail dependence using multivariate regression quantiles

用于 VaR 的 VAR:以多元回归分位数衡量尾部依赖

This paper proposes methods for estimation and inference in multivariate, multi-quantile models. The theory can simultaneously accommodate models with multiple random variables, multiple confidence levels, and multiple lags of the associated quantiles. The proposed framework can be conveniently thought of as a vector autoregressive (VAR) extension to quantile models. We estimate a simple version of the model using market equity returns data to analyze spillovers in the…

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Testing for separability in structural equations

结构方程可分性的检验

Separability is an important feature of structural equations, as it implies the absence of unobservable heterogeneity of effects and has significant implications for identification and efficiency of estimation. This paper provides a nonparametric test for separability in structural equations. The test is based on a conditional independence test recently developed by Huang et al. (2013), building on consistent procedures of Bierens (1982, 1990) and Stinchcombe and White…

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Testing conditional independence via empirical likelihood

基于经验似然的条件独立检验

We construct two classes of smoothed empirical likelihood ratio tests for the conditional independence hypothesis by writing the null hypothesis as an infinite collection of conditional moment restrictions indexed by a nuisance parameter. One class is based on the CDF; another is based on smoother functions. We show that the test statistics are asymptotically normal under the null hypothesis and a sequence of Pitman local alternatives. We also show that the tests possess an…

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A two-stage procedure for partially identified models

部分识别模型的两阶段程序

This paper studies a two-stage procedure for estimating partially identified models, based on Chernozhukov, Hong, and Tamer’s (2007) theory of set estimation and inference. We consider the case where a sub-vector of parameters or their identified set can be estimated separately from the rest, possibly subject to a priori restrictions. Our procedure constructs the second-stage set estimator and confidence set by taking appropriate level sets of a criterion function, using a…

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Granger causality, exogeneity, cointegration, and economic policy analysis

格兰杰因果、外生性、协整与经济政策分析

Policy analysis had long been a main interest of Clive Granger’s. Here, we present a framework for economic policy analysis that provides a novel integration of several fundamental concepts at the heart of Granger’s contributions to time-series analysis. We work with a dynamic structural system analyzed by White and Lu (2010) with well defined causal meaning; under suitable conditional exogeneity restrictions, Granger causality coincides with this structural notion. The…

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Robustness checks and robustness tests in applied economics

应用经济学中的稳健性检查与稳健性检验

A common exercise in empirical studies is a “robustness check”, where the researcher examines how certain “core” regression coefficient estimates behave when the regression specification is modified by adding or removing regressors. If the coefficients are plausible and robust, this is commonly interpreted as evidence of structural validity. Here, we study when and how one can infer structural validity from coefficient robustness and plausibility. As we show, there are…

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A WARP-SPEED METHOD FOR CONDUCTING MONTE CARLO EXPERIMENTS INVOLVING BOOTSTRAP ESTIMATORS

含自助法估计量的蒙特卡洛实验:Warp-speed 加速方法

We analyze fast procedures for conducting Monte Carlo experiments involving bootstrap estimators, providing formal results establishing the properties of these methods under general conditions.

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SOME EXTENSIONS OF A LEMMA OF KOTLARSKI

Kotlarski 引理的若干扩展

This note demonstrates that the conditions of Kotlarski’s (1967, Pacific Journal of Mathematics 20(1), 69–76) lemma can be substantially relaxed. In particular, the condition that the characteristic functions of M , U 1 , and U 2 are nonvanishing can be replaced with much weaker conditions: The characteristic function of U 1 can be allowed to have real zeros, as long as the derivative of its characteristic function at those points is not also zero; that of U 2 can have an…

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Nonparametric identification in nonseparable panel data models with generalized fixed effects

具有广义固定效应的非可分面板模型的非参数识别

This paper extends the familiar notion of fixed effects to nonlinear structures with infinite-dimensional unobservables, like preferences. The main result is that a generalized version of differencing identifies local average responses (LARs) in nonseparable structures. In contrast to existing results, this does not require either substantial restrictions on functional form or independence between the persistent unobservables and the explanatory variables of interest, and it…

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Local indirect least squares and average marginal effects in nonseparable structural systems

不可分结构系统中的局部间接最小二乘与平均边际效应

We study the scope of local indirect least squares (LILS) methods for nonparametrically estimating average marginal effects of an endogenous cause X on a response Y in triangular structural systems that need not exhibit linearity, separability, or monotonicity in scalar unobservables. One main finding is negative: in the fully nonseparable case, LILS methods cannot recover the average marginal effect. LILS methods can nevertheless test the hypothesis of no effect in the…

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Generalized runs tests for the IID hypothesis

独立同分布假设的广义游程检验

We provide a family of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to tests designed for specific alternatives, such as serial correlation, GARCH, or structural breaks. Our tests have appealing computational simplicity in that they do not require kernel density estimation, with the associated challenge of bandwidth selection. Simulations show levels close to nominal asymptotic levels. Our…

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TESTING STRUCTURAL CHANGE IN PARTIALLY LINEAR MODELS

部分线性模型的结构变化检验

We consider two tests of structural change for partially linear time-series models. The first tests for structural change in the parametric component, based on the cumulative sums of gradients from a single semiparametric regression. The second tests for structural change in the parametric and nonparametric components simultaneously, based on the cumulative sums of weighted residuals from the same semiparametric regression. We derive the limiting distributions of both tests…

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Testing for unobserved heterogeneity in exponential and Weibull duration models

指数与威布尔持续时间模型中的不可观测异质性检验

We examine the use of the likelihood ratio (LR) statistic to test for unobserved heterogeneity in duration models, based on mixtures of exponential or Weibull distributions. We consider both the uncensored and censored duration cases. The asymptotic null distribution of the LR test statistic is not the standard chi-square, as the standard regularity conditions do not hold. Instead, there is a nuisance parameter identified only under the alternative, and a null parameter…

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The construction of empirical credit scoring rules based on maximization principles

基于最大化原则构建经验信用评分规则

We examine the econometric implications of the decision problem faced by a profit/utility-maximizing lender operating in a simple "double-binary" environment, where the two actions available are "approve" or "reject", and the two states of the world are "pay back" or "default". In practice, such decisions are often made by applying a fixed cutoff to the maximum likelihood estimate of a parametric model of the default probability. Following (Elliott and Lieli, 2007), we argue…

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A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE

基于 Hellinger 距离的非参数条件独立检验

We propose a nonparametric test of conditional independence based on the weighted Hellinger distance between the two conditional densities, f ( y | x , z ) and f ( y | x ), which is identically zero under the null. We use the functional delta method to expand the test statistic around the population value and establish asymptotic normality under β-mixing conditions. We show that the test is consistent and has power against alternatives at distance n −1/2 h − d /4 . The cases…

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Mixtures of t-distributions for finance and forecasting

用于金融与预测的 t 分布混合

We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. Particularly desirable for econometric applications are closed-form expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-of-sample, than…

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Testing for Regime Switching

状态切换检验

We analyze use of a quasi-likelihood ratio statistic for a mixture model to test the null hypothesis of one regime versus the alternative of two regimes in a Markov regime-switching context. This test exploits mixture properties implied by the regime-switching process, but ignores certain implied serial correlation properties. When formulated in the natural way, the setting is nonstandard, involving nuisance parameters on the boundary of the parameter space, nuisance…

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