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随机极限自助概率测度下的推断AI 解读

Asymptotic bootstrap validity is usually understood as consistency of the distribution of a bootstrap statistic, conditional on the data, for the unconditional limit distribution of a statistic of interest. From this perspective, randomness of the limit bootstrap measure is regarded as a failure of the bootstrap. We show that such limiting randomness does not necessarily invalidate bootstrap inference if validity is understood as control over the frequency of correct…

边疆文化：美国“强烈个人主义”的根源与延续AI 解读

The presence of a westward‐moving frontier of settlement shaped early U.S. history. In 1893, the historian Frederick Jackson Turner famously argued that the American frontier fostered individualism. We investigate the “frontier thesis” and identify its long‐run implications for culture and politics. We track the frontier throughout the 1790–1890 period and construct a novel, county‐level measure of total frontier experience (TFE). Historically, frontier locations had…

This paper proposes a valid bootstrap‐based distributional approximation for M ‐estimators exhibiting a Chernoff (1964)‐type limiting distribution. For estimators of this kind, the standard nonparametric bootstrap is inconsistent. The method proposed herein is based on the nonparametric bootstrap, but restores consistency by altering the shape of the criterion function defining the estimator whose distribution we seek to approximate. This modification leads to a generic and…

We propose leave‐out estimators of quadratic forms designed for the study of linear models with unrestricted heteroscedasticity. Applications include analysis of variance and tests of linear restrictions in models with many regressors. An approximation algorithm is provided that enables accurate computation of the estimator in very large data sets. We study the large sample properties of our estimator allowing the number of regressors to grow in proportion to the number of…

This paper analyzes a procedure called Testing‐Based Forward Model Selection (TBFMS) in linear regression problems. This procedure inductively selects covariates that add predictive power into a working statistical model before estimating a final regression. The criterion for deciding which covariate to include next and when to stop including covariates is derived from a profile of traditional statistical hypothesis tests. This paper proves probabilistic bounds, which depend…

This paper considers a class of generalized methods of moments (GMM) estimators for general dynamic panel models, allowing for weakly exogenous covariates and cross‐sectional dependence due to spatial lags, unspecified common shocks, and time‐varying interactive effects. We significantly expand the scope of the existing literature by allowing for endogenous time‐varying spatial weight matrices without imposing explicit structural assumptions on how the weights are formed. An…

The objective of this paper is to identify and estimate network formation models using observed data on network structure. We characterize network formation as a simultaneous‐move game, where the utility from forming a link depends on the structure of the network, thereby generating strategic interactions between links. With the prevalence of multiple equilibria, the parameters are not necessarily point identified. We leave the equilibrium selection unrestricted and propose…

对《英国住房市场中的理性泡沫》的回应AI 解读

In Giglio, Maggiori, and Stroebel (2016), we propose and implement a new test for classic rational bubbles. Such bubbles derive their value from each agent's rational expectation of being able to resell the bubble claims to the next agent. Backward induction ensures that classic rational bubbles can only exist on infinite‐maturity assets. Our empirical exercise shows that infinite‐maturity claims and 999‐year claims for otherwise identical housing assets trade at the same…

We investigate claims made in Giacomini and White (2006) and Diebold (2015) regarding the asymptotic normality of a test of equal predictive ability. A counterexample is provided in which, instead, the test statistic diverges with probability 1 under the null.

We consider statistical inference in games. Each player obtains a small random sample of other players' actions, uses statistical inference to estimate their actions, and chooses an optimal action based on the estimate. In a sampling equilibrium with statistical inference (SESI), the sample is drawn from the distribution of players' actions based on this process. We characterize the set of SESIs in large two‐action games, and compare their predictions to those of Nash…

We propose a decomposition of the realized covariance matrix into components based on the signs of the underlying high‐frequency returns, and we derive the asymptotic properties of the resulting realized semicovariance measures as the sampling interval goes to zero. The first‐order asymptotic results highlight how the same‐sign and mixed‐sign components load differently on economic information related to stochastic correlation and jumps. The second‐order asymptotic results…

Oversubscribed treatments are often allocated using randomized waiting lists. Applicants are ranked randomly, and treatment offers are made following that ranking until all seats are filled. To estimate causal effects, researchers often compare applicants getting and not getting an offer. We show that those two groups are not statistically comparable. Therefore, the estimator arising from that comparison is inconsistent when the number of waitlists goes to infinity. We…

It is well understood that classical sample selection models are not semiparametrically identified without exclusion restrictions. Lee (2009) developed bounds for the parameters in a model that nests the semiparametric sample selection model. These bounds can be wide. In this paper, we investigate bounds that impose the full structure of a sample selection model with errors that are independent of the explanatory variables but have unknown distribution. The additional…

劳动力市场中Roy模型、搜寻与补偿性工资差异的综合模型估计AI 解读

In this paper, we develop a model that captures key components of the Roy model, a search model, compensating differentials, and human capital accumulation on‐the‐job. We establish which components of the model can be non‐parametrically identified and which ones cannot. We estimate the model and use it to assess the relative contribution of the different factors for overall wage inequality. We find that variation in premarket skills (the key feature of the Roy model) is the…

This paper considers the problem of forecasting a collection of short time series using cross‐sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coefficients under a correlated random effects distribution. This formula utilizes cross‐sectional information to transform the unit‐specific (quasi) maximum likelihood estimator into an approximation of the posterior mean under a prior distribution that…

回归分析中基于抽样与基于设计的不确定性AI 解读

Consider a researcher estimating the parameters of a regression function based on data for all 50 states in the United States or on data for all visits to a website. What is the interpretation of the estimated parameters and the standard errors? In practice, researchers typically assume that the sample is randomly drawn from a large population of interest and report standard errors that are designed to capture sampling variation. This is common even in applications where it…

动态随机效用AI 解读

We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice behavior of agents who solve dynamic decision problems by maximizing some stochastic process ( U t ) of utilities. We show first that even when ( U t ) is arbitrary, dynamic random utility imposes new testable across‐period restrictions on behavior, over and above period‐by‐period analogs of the static random utility axioms. An important feature of dynamic random utility is that…

理性行为的动态分位数模型AI 解读

This paper develops a dynamic model of rational behavior under uncertainty, in which the agent maximizes the stream of future τ ‐quantile utilities, for τ ∈ (0,1). That is, the agent has a quantile utility preference instead of the standard expected utility. Quantile preferences have useful advantages, including the ability to capture heterogeneity and allowing the separation between risk aversion and elasticity of intertemporal substitution. Although quantiles do not share…

动态二元选择面板模型中的排除限制：评《无严格外生回归变量的半参数二元选择面板模型》AI 解读

In this note we revisit the use of exclusion restrictions in the semiparametric binary choice panel data model introduced in Honore and Lewbel (2002). We show that in a dynamic panel data setting (where one of the pre-determined explanatory variables is the lagged dependent variable), the exclusion restriction in Honore and Lewbel (2002) implicitly re- quires serial independence condition on an observed regressor, that if violated in the data will result in their procedure…

网络数据的固定效应回归AI 解读

This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two‐way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer–employee or student–teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network…

失业状态依赖的非参数推断AI 解读

This paper is about measuring state dependence in dynamic discrete outcomes. I develop a nonparametric dynamic potential outcomes (DPO) model and propose an array of parameters and identifying assumptions that can be considered in this model. I show how to construct sharp identified sets under combinations of identifying assumptions by using a flexible linear programming procedure. I apply the analysis to study state dependence in unemployment for working age high school…

状态依赖效用的非贝叶斯理论AI 解读

Many decision situations involve two or more of the following divergences from subjective expected utility: imprecision of beliefs (or ambiguity), imprecision of tastes (or multi‐utility), and state dependence of utility. This paper proposes and characterizes a model of uncertainty averse preferences that can simultaneously incorporate all three phenomena. The representation supports a principled separation of (imprecise) beliefs and (potentially state‐dependent, imprecise)…

退休融资：一种最优改革方法AI 解读

We study Pareto optimal policy reforms aimed at overhauling retirement financing as an integral part of the tax and transfer system. Our framework for policy analysis is a heterogeneous‐agent overlapping‐generations model that performs well in matching the aggregate and distributional features of the U.S. economy. We present a test of Pareto optimality that identifies the main source of inefficiency in the status quo policies. Our test suggests that lack of asset subsidies…

高维选择中的群体差异测度：方法及国会演讲应用AI 解读

We study the problem of measuring group differences in choices when the dimensionality of the choice set is large. We show that standard approaches suffer from a severe finite‐sample bias, and we propose an estimator that applies recent advances in machine learning to address this bias. We apply this method to measure trends in the partisanship of congressional speech from 1873 to 2016, defining partisanship to be the ease with which an observer could infer a…