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效率前沿的非参数工具变量估计AI 解读

The paper investigates endogeneity issues in nonparametric frontier models. It considers a nonseparable model for a cost function C=φ(Y,U) where C and Y are the cost and the output, U is uniform in [0,1] and φ is increasing with respect to U. The cost frontier corresponds to U=0 and U can be interpreted as a normalized level of inefficiency. The endogeneity issue arises when Y is dependent of U. For identification and estimation, we use a nonparametric instrumental variables…

好产出、坏产出与技术：环境生产模型中的内生性AI 解读

In this paper we consider an environmental production process in which firms intend to produce outputs (which we label as desirable/good) but the production process is such that it automatically produces some other unintentional but inevitable undesirable (bad) outputs as by-products (emission of pollutants). Like stochastic production frontier, by-production technology specifies that there is a minimal amount of the by-product that is produced, given the quantities of…

非参数前沿估计中的不可观测异质性与内生性AI 解读

In production theory, firm efficiencies are measured by their distances to a production frontier. In the presence of heterogeneous conditions (like environmental factors) that may influence the shape and the position of the frontier, traditional measures of efficiency obtained in the space of inputs/outputs are difficult to interpret, since they mix managerial inefficiency and shift of the frontier. This can be corrected by using nonparametric conditional efficiencies. In…

利用技术、市场与企业行为信息分解满足公理的生产率指数AI 解读

This paper uses distance functions to define new output and input quantity indexes that satisfy important axioms from index number theory (e.g., identity, transitivity, proportionality and time-space reversal). Dividing the output index by the input index yields a new productivity index that can be decomposed into a measure of technical change, a measure of environmental change, and several measures of efficiency change. A problem with this new index is that it cannot be…

内生解释变量与内生状态切换回归的控制函数估计AI 解读

We derive simple, multi-step estimation methods for a linear model with heterogeneous coefficients when there are both continuous and discrete endogenous explanatory variables. We consider both cross-sectional and panel data settings. When we extend our model to panel data, we use the Chamberlain–Mundlak device to allow heterogeneity to be correlated with time-varying explanatory variables. We apply the panel data methods we propose to estimation of a housing budget share…

随机前沿模型中的内生性AI 解读

Stochastic frontier models are typically estimated by maximum likelihood (MLE) or corrected ordinary least squares. The consistency of either estimator depends on exogeneity of the explanatory variables (inputs, in the production frontier setting). We will investigate the case that one or more of the inputs is endogenous, in the simultaneous equation sense of endogeneity. That is, we worry that there is correlation between the inputs and statistical noise or inefficiency.

存在内生选择与固定效应的变系数面板模型AI 解读

This paper considers a flexible panel data sample selection model in which (i) the outcome equation is permitted to take a semiparametric, varying coefficient form to capture potential parameter heterogeneity in the relationship of interest, (ii) both the outcome and (parametric) selection equations contain unobserved fixed effects and (iii) selection is generalized to a polychotomous case. We propose a two-stage estimator. Given consistent parameter estimates from the…

In many statistical applications of one-sided tests of multiple hypotheses researchers are often concerned not only with global tests of the intersection of individual hypotheses, but also with multiple tests of individual hypotheses. For example, in clinical trial studies researchers often need to find out the efficacy of a treatment, as well as the significance of each outcome measurement (endpoint) of the treatment. This article proposes MaxT type tests aiming at…

计数过程的广义分位数回归及其重复事件应用AI 解读

In survival analysis, quantile regression has become a useful approach to account for covariate effects on the distribution of an event time of interest. In this paper, we discuss how quantile regression can be extended to model counting processes, and thus lead to a broader regression framework for survival data. We specifically investigate the proposed modeling of counting processes for recurrent events data. We show that the new recurrent events model retains the…

Multiple testing of correlations arises in many applications including gene coexpression network analysis and brain connectivity analysis. In this paper, we consider large scale simultaneous testing for correlations in both the one-sample and two-sample settings. New multiple testing procedures are proposed and a bootstrap method is introduced for estimating the proportion of the nulls falsely rejected among all the true nulls. The properties of the proposed procedures are…

分位数回归中变系数的估计与检验AI 解读

In this article, we establish a novel connection between the null hypothesis H0 on the coefficients and a rank-reducible form of the varying coefficient model in quantile regression. We use B-splines to approximate the varying coefficients in the rank-reducible model, and make use of the fact that the null hypothesis H0 implies a unidimensional structure of a transformed coefficient matrix for the B-spline basis functions. By evaluating the unidimensional structure, we…

病例对照数据二次分析中的分位数回归AI 解读

Case-control design is widely used in epidemiology and other fields to identify factors associated with a disease. Data collected from existing case-control studies can also provide a cost-effective way to investigate the association of risk factors with secondary outcomes. When the secondary outcome is a continuous random variable, most of the existing methods focus on the statistical inference on the mean of the secondary outcome. In this paper, we propose a quantile-based…

多层纵向数据嵌套隐马尔可夫链模型的成对似然推断AI 解读

In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and between clusters. For this aim, we propose an approach based on nested hidden (latent) Markov chains, which are associated with every sample unit and with every cluster. The approach allows us to account for the previously mentioned forms of unobserved heterogeneity in a dynamic…

部分工具变量无效时的工具变量估计及孟德尔随机化应用AI 解读

Instrumental variables have been widely used for estimating the causal effect between exposure and outcome. Conventional estimation methods require complete knowledge about all the instruments’ validity; a valid instrument must not have a direct effect on the outcome and not be related to unmeasured confounders. Often, this is impractical as highlighted by Mendelian randomization studies where genetic markers are used as instruments and complete knowledge about instruments’…

Causal inference in completely randomized treatment-control studies with binary outcomes is discussed from Fisherian, Neymanian, and Bayesian perspectives, using the potential outcomes model. A randomization-based justification of Fisher’s exact test is provided. Arguing that the crucial assumption of constant causal effect is often unrealistic, and holds only for extreme cases, some new asymptotic and Bayesian inferential procedures are proposed. The proposed procedures…

序贯条件独立下中介效应估计量的有限样本表现AI 解读

Using a comprehensive simulation study based on empirical data, this article investigates the finite sample properties of different classes of parametric and semiparametric estimators of (natural) direct and indirect causal effects used in mediation analysis under sequential conditional independence assumptions. The estimators are based on regression, inverse probability weighting, and combinations thereof. Our simulation design uses a large population of Swiss jobseekers…

医疗支出价格弹性的删失分位数工具变量估计AI 解读

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to…

有序响应模型中的单变量阈值效应：收入与幸福感梯度估计的应用AI 解读

This short article extends well-known threshold models to the ordered response setting. We consider the case where the sample is endogenously split to estimate regime-dependent coefficients for one variable of interest, while keeping the other coefficients and auxiliary parameters constant across the threshold. We use Monte Carlo methods to examine the behavior of the model. In addition, we derive the formulae for the partial effects associated with the model. We apply our…

用于网络自动社群发现的假设检验AI 解读

Summary Community detection in networks is a key exploratory tool with applications in a diverse set of areas, ranging from finding communities in social and biological networks to identifying link farms in the World Wide Web. The problem of finding communities or clusters in a network has received much attention from statistics, physics and computer science. However, most clustering algorithms assume knowledge of the number of clusters k. We propose to determine k…

死亡截断问题中利用结局测量后的信息AI 解读

Summary Many clinical studies on non-mortality outcomes such as quality of life suffer from the problem that the non-mortality outcome can be censored by death, i.e. the non-mortality outcome cannot be measured if the subject dies before the time of measurement. To address the problem that this censoring by death is informative, it is of interest to consider the average effect of the treatment on the non-mortality outcome among subjects whose measurement would not be…

存在内生性时的单调性检验AI 解读

This paper develops a test for monotonicity of nonparametric regression models under endogeneity, which in its generality is novel in the literature. The test statistic, which is built upon a second order U-process, introduces ‘correction terms’ based on control functions that purge the endogeneity. The test has a non-standard asymptotic distribution from which asymptotic critical values can directly be derived. Furthermore, the test statistic is extended to accommodate…

固定效应模型中的分组效应估计量AI 解读

We consider estimation of nonlinear panel data models with common and individual specific parameters. Fixed effects estimators are known to suffer from the incidental parameters problem, which can lead to large biases in estimates of common parameters. Pooled estimators, which ignore heterogeneity across individuals, are also generally inconsistent. We assume that individuals in the data are grouped on multiple levels where groups are defined by some observable external…

股票回购的实体经济效应AI 解读

We employ a regression discontinuity design to identify the real effects of share repurchases on other firm outcomes. The probability of share repurchases that increase earnings per share (EPS) is sharply higher for firms that would have just missed the EPS forecast in the absence of the repurchase, when compared with firms that “just beat” the EPS forecast. We use this discontinuity to show that EPS-motivated repurchases are associated with reductions in employment and…

股票回购与流动性AI 解读

We analyze the impact of share repurchases on liquidity based on a new comprehensive data set of realized share repurchases in the US, which covers 50,204 repurchase months between 2004 and 2010. Using instrumental variable analysis, we show that repurchases unequivocally improve liquidity and suggest that endogenous controls have confounded results in earlier studies. Liquidity also influences how firms execute repurchase programs. Repurchases provide liquidity when other…