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多元广义分位数回归的置信带AI 解读

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest, which follow after a series of approximation steps including a Bahadur representation, a new strong approximation theorem, and exponential tail inequalities for Gaussian random fields. As a byproduct…

收入动态中的未观测异质性：经验贝叶斯视角AI 解读

Empirical Bayes methods for Gaussian compound decision problems involving longitudinal data are considered. The new convex optimization formulation of the nonparametric (Kiefer–Wolfowitz) maximum likelihood estimator for mixture models is employed to construct nonparametric Bayes rules for compound decisions. The methods are first illustrated with some simulation examples and then with an application to models of income dynamics. Using panel data, we estimate a simple…

Summary Simulation from the truncated multivariate normal distribution in high dimensions is a recurrent problem in statistical computing and is typically only feasible by using approximate Markov chain Monte Carlo sampling. We propose a minimax tilting method for exact independently and identically distributed data simulation from the truncated multivariate normal distribution. The new methodology provides both a method for simulation and an efficient estimator to hitherto…

部分识别半参数条件矩模型的统计推断AI 解读

This paper develops inference methods for conditional moment models in which the unknown parameter is possibly partially identified and may contain infinite-dimensional components. For a conjectured restriction on the parameter, we consider testing the hypothesis that the restriction is satisfied by at least one element of the identified set. We propose using the sieve minimum of a Kolmogorov–Smirnov type statistic as the test statistic, derive its asymptotic distribution,…

多元与联立方程空间自回归模型的识别及拟最大似然估计AI 解读

This paper investigates a simultaneous equations spatial autoregressive model which incorporates simultaneity effects, own-variable spatial lags and cross-variable spatial lags as explanatory variables, and allows for correlation between disturbances across equations. In exposition, we also discuss a multivariate spatial autoregressive model that can be treated as a reduced form of the simultaneous equations model. We study parameter spaces, parameter identification,…

含固定效应的变系数面板模型：理论与美国商业银行应用AI 解读

In this paper, we propose a semiparametric varying-coefficient categorical panel data model in which covariates (variables affecting the coefficients) are purely categorical. This model has two features: first, fixed effects are included to allow for correlation between individual unobserved heterogeneity and the regressors; second, it allows for cross-sectional dependence through a general spatial error dependence structure. We derive a semiparametric estimator for our…

跨国债务执行、企业投资与风险承担AI 解读

We argue that the prospect of an imperfect enforcement of debt contracts in default reduces shareholder–debtholder conflicts and induces leveraged firms to invest more and take on less risk as they approach financial distress. To test these predictions, we use a large panel of firms in 41 countries with heterogeneous debt enforcement characteristics. Consistent with our model, we find that the relation between debt enforcement and firms’ investment and risk depends on the…

含噪数据下贫困转移矩阵的估计AI 解读

Summary This paper investigates measurement error biases in estimated poverty transition matrices. We compare transition matrices based on survey expenditure data to transition matrices based on measurement‐error‐free simulated expenditure. The simulation model uses estimates that correct for measurement error in expenditure. We find that time‐varying measurement error in expenditure data magnifies economic mobility. Roughly 45 % of households initially in poverty at time t…

竞争企业数量未知时在线价格竞争模型的识别与估计AI 解读

Summary This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement errors. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened…

Firpo、Fortin 与 Lemieux（2009）无条件分位数回归的复现AI 解读

Summary This paper is a narrow replication of Firpo, Fortin and Lemieux (Unconditional quantile regressions. Econometrica 2009; 77(3): 953–973), who propose a new estimation method, called ‘unconditional quantile regressions’. Using their empirical example, we confirm their results for the effects of unionization on US wage inequality during the period 1983–1985 for both conditional and unconditional quantile regressions. In addition, this paper applies the proposed…

内生性与不依从下已处理者及其他群体平均处理效应的尖锐工具变量界限AI 解读

Summary In the presence of an endogenous binary treatment and a valid binary instrument, causal effects are point identified only for the subpopulation of compliers, given that the treatment is monotone in the instrument. With the exception of the entire population, causal inference for further subpopulations has been widely ignored in econometrics. We invoke treatment monotonicity and/or dominance assumptions to derive sharp bounds on the average treatment effects on the…

非参数工具变量模型中的完备性与一致性AI 解读

This paper provides positive testability results for the identification condition in a nonparametric instrumental variable model, known as completeness, and it links the outcome of the test to properties of an estimator of the structural function. In particular, I show that the data can provide empirical evidence in favor of both an arbitrarily small identified set as well as an arbitrarily small asymptotic bias of the estimator. This is the case for a large class of…

单调性约束下的非参数工具变量估计AI 解读

The ill-posedness of the inverse problem of recovering a regression function in a nonparametric instrumental variable (NPIV) model leads to estimators that may suffer from poor statistical performance.In this paper, we explore the possibility of imposing shape restrictions to improve the performance of the NPIV estimators.We assume that the regression function is monotone and consider sieve estimators that enforce the monotonicity constraint.We define a restricted measure of…

从资产需求识别信念AI 解读

The demand for assets as prices and initial wealth vary identifies beliefs and attitudes towards risk. We derive conditions that guarantee identification with no knowledge either of the cardinal utility index or of the distribution of future endowments or payoffs of assets; the argument applies even if the asset market is incomplete and demand is observed only locally.

具有度异质性的网络形成计量模型AI 解读

I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent‐level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution of observed and unobserved agent‐level characteristics is left unrestricted. Two estimators for the (common) homophily parameter, β0, are developed and their properties studied under…

近似对称性假设下的随机化检验AI 解读

This paper develops a theory of randomization tests under an approximate symmetry as-sumption. Randomization tests provide a general means of constructing tests that control size in finite samples whenever the distribution of the observed data exhibits symmetry under the null hypothesis. Here, by exhibits symmetry we mean that the distribution remains invariant under a group of transformations. In this paper, we provide conditions under which the same construction can be…

广义工具变量模型AI 解读

This paper develops characterizations of identified sets of structures and structural features for complete and incomplete models involving continuous or discrete variables.Multiple values of unobserved variables can be associated with particular combinations of observed variables.This can arise when there are multiple sources of heterogeneity, censored or discrete endogenous variables, or inequality restrictions on functions of observed and unobserved variables.The models…

劳动收入与消费动态：非线性面板数据框架AI 解读

We develop a new quantile-based panel data framework to study the nature of income persistence and the transmission of income shocks to consumption.Log-earnings are the sum of a general Markovian persistent component and a transitory innovation.The persistence of past shocks to earnings is allowed to vary according to the size and sign of the current shock.Consumption is modeled as an age-dependent nonlinear function of assets and the two earnings components.We establish the…

密集网络形成的结构模型AI 解读

This paper proposes an empirical model of network formation, combining strategic and random networks features. Payoffs depend on direct links, but also link externalities. Players meet sequentially at random, myopically updating their links. Under mild assumptions, the network formation process is a potential game and converges to an exponential random graph model (ERGM), generating directed dense networks. I provide new identification results for ERGMs in large networks: if…

单交叉随机效用模型AI 解读

We propose a novel model of stochastic choice: the single-crossing random utility model (SCRUM). This is a random utility model in which the collection of utility functions satisfies the single-crossing property. We offer a characterization of SCRUMs based on three easy-to-check properties: Positivity, Monotonicity and Centrality. The identified collection of utility functions and associated probabilities is basically unique. We establish a stochastic monotone comparative…

重叠不足下平均处理效应的稳健置信区间AI 解读

Robust Confidence Intervals for Average Treatment Effects under Limited Overlap *Estimators of average treatment effects under unconfounded treatment assignment are known to become rather imprecise if there is limited overlap in the covariate distributions between the treatment groups.But such limited overlap can also have a detrimental effect on inference, and lead for example to highly distorted confidence intervals.This paper shows that this is because the coverage error…

不对称信息下的议价：认罪协商的实证研究AI 解读

This paper empirically investigates how sentences to be assigned at trial impact plea bargaining. The analysis is based on the model of bargaining with asymmetric information by Bebchuk, 1984. I provide conditions for the nonparametric identification of the model, propose a consistent nonparametric estimator, and implement it using data on criminal cases from North Carolina. Employing the estimated model, I evaluate how different sentencing reforms affect the outcome of…

分位数选择模型及其在工资不平等变化研究中的应用AI 解读

We propose a method to correct for sample selection in quantile regression models.Selection is modelled via the cumulative distribution function, or copula, of the percentile error in the outcome equation and the error in the participation decision.Copula parameters are estimated by minimizing a method-of-moments criterion.Given these parameter estimates, the percentile levels of the outcome are re-adjusted to correct for selection, and quantile parameters are estimated by…

高维数据下的项目评估与因果推断AI 解读

The accepted manuscript version (last revised 5 Jan 2018 (v8)) has 118 pages, 3 tables, 11 figures, and includes supplementary appendix. This version corrects some typos in Example 2 of the published version. This supplement contains 11 appendices with additional results and some omitted proofs. Appendices F-J include additional results for Sections 2-7, respectively. Appendix K gathers auxiliary results on algebra of covering entropies. Appendices L and M contain the proofs…