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先后调整还是同时调整：相互关联的要素需求AI 解读

Firms may adjust capital and labor sequentially or simultaneously. In this paper, we develop a structural model of interrelated factor demand subject to nonconvex adjustment costs and estimated by simulated method of moments. Based on Norwegian manufacturing industry plant-level data, parameter estimates reveal cost advantages for adjusting capital and making net changes in labor simultaneously. Factor demand models with fully specified interrelated adjustment costs…

通过最优组合分位数信息实现高效回归估计AI 解读

We develop a generally applicable framework for constructing efficient estimators of regression models via quantile regressions. The proposed method is based on optimally combining information over multiple quantiles and can be applied to a broad range of parametric and nonparametric settings. When combining information over a fixed number of quantiles, we derive an upper bound on the distance between the efficiency of the proposed estimator and the Fisher information. As…

固定效应动态面板模型的非参数估计AI 解读

This paper considers nonparametric estimation of autoregressive panel data models with fixed effects. A within-group type series estimator is developed and its convergence rate and asymptotic normality are derived. It is found that the series estimator is asymptotically biased and the bias could reduce the mean-square convergence rate compared with the cross-section cases. A bias corrected nonparametric estimator is developed.

条件平均处理效应的估计AI 解读

We consider a functional parameter called the conditional average treatment effect (CATE), designed to capture heterogeneity of a treatment effect across subpopulations when the unconfoundedness assumption applies. In contrast to quantile regressions, the subpopulations of interest are defined in terms of the possible values of a set of continuous covariates rather than the quantiles of the potential outcome distributions. We show that the CATE parameter is nonparametrically…

基于面板数据与风险承担理论评估金融机构的消费和投资影响AI 解读

The theory of the optimal allocation of risk and the Townsend Thai panel data on financial transactions are used to assess the impact of the major formal and informal financial institutions of an emerging market economy. We link financial institution assessment to the actual impact on clients, rather than ratios and non-performing loans. We derive both consumption and investment equations from a common core theory with both risk and productive activities. The empirical…

利用分数多项式逼近正规经济函数的似然推断AI 解读

This paper shows that regular fractional polynomials can approximate regular cost, production and utility functions and their first two derivatives on closed compact subsets of the strictly positive orthant of Euclidean space arbitrarily well. These functions therefore can provide reliable approximations to demand functions and other economically relevant characteristics of tastes and technology. Using canonical cost function data, it shows that full Bayesian inference for…

断点回归设计的稳健非参数置信区间AI 解读

In the regression-discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may be seriously hampered by their sensitivity to the specific bandwidth employed. Available bandwidth selectors typically…

家庭是否通过住房所有权自我保险？美国城市间的证据AI 解读

Are households more likely to be homeowners when “housing risk” is higher? We show that home-ownership rates and loan-to-value (LTV) ratios at the city level are strongly negatively correlated with local house price volatility. However, causal inference is confounded by house price levels, which are systematically correlated with housing risk in an intuitive way: in cities where the land value is larger relative to the local cost of structures, house prices are higher and…

兼有离散与连续选择的动态决策过程的非参数识别AI 解读

This paper establishes conditions for nonparametric identification of dynamic optimization models in which agents make both discrete and continuous choices. We consider identification of both the payoff function and the distribution of unobservables. Models of this kind are prevalent in applied microeconomics and many of the required conditions are standard assumptions currently used in empirical work. We focus on conditions on the model that can be implied by economic…

用混合模型倾向得分估计道路扩容对交通量与密度的因果效应AI 解读

Road network capacity expansions are frequently proposed as solutions to urban traffic congestion but are controversial because it is thought that they can directly “induce” growth in traffic volumes. This article quantifies causal effects of road network capacity expansions on aggregate urban traffic volume and density in U.S. cities using a mixed model propensity score (PS) estimator. The motivation for this approach is that we seek to estimate a dose-response relationship…

估计处理与大量协变量交互作用的简便方法AI 解读

We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure,…

内生性与样本流失下的多期处理效应评估AI 解读

This article develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pretreatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment effect on the outcomes of compliers (the subpopulation whose treatment reacts on the instrument) in multiple periods based on inverse probability weighting. Treatment selection and…

存在内生回归变量时的加性非参数回归AI 解读

In this article we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient, and free from the curse of dimensionality. Monte Carlo simulations support the asymptotic developments. We employ a partially linear extension of our model to study the relationship between child care and cognitive outcomes. Some of…

联立方程网络模型的识别与有效估计AI 解读

This article considers identification and estimation of social network models in a system of simultaneous equations. We show that, with or without row-normalization of the social adjacency matrix, the network model has different equilibrium implications, needs different identification conditions, and requires different estimation strategies. When the adjacency matrix is not row-normalized, the variation in the Bonacich centrality across nodes in a network can be used as an…

超高维纵向数据的非参数独立筛选与结构识别AI 解读

Ultra-high dimensional longitudinal data are increasingly common and the analysis is challenging both theoretically and methodologically. We offer a new automatic procedure for finding a sparse semivarying coefficient model, which is widely accepted for longitudinal data analysis. Our proposed method first reduces the number of covariates to a moderate order by employing a screening procedure, and then identifies both the varying and constant coefficients using a group SCAD…

私人信号相关的不完全信息二元决策博弈的半参数识别AI 解读

This paper studies the identification and estimation of a static binary decision game of incomplete information. We make no parametric assumptions on the joint distribution of private signals and allow them to be correlated. We show that the parameters of interest can be point-identified subject to a scale normalization under mild support requirements for the regressors (publicly observed state variables) and errors (private signals). Following Manski and Tamer (2002), we…

照料年迈父母与欧洲成熟女性的就业状态AI 解读

We study the prevalence of informal caregiving to elderly parents by their mature daughters in Europe and the links between parental health, intense (daily) caregiving, and the employment status of daughters. We group data from SHARE into three country pools (North, Central, and South), which differ in the availability of public formal care services and female labor market attachment. There is a strong North-South gradient in the (positive) effect of parental ill health on…

股票流动性促进还是阻碍企业创新？AI 解读

ABSTRACT We aim to tackle the longstanding debate on whether stock liquidity enhances or impedes firm innovation. This topic is of interest because innovation is crucial for firm‐ and national‐level competitiveness and stock liquidity can be altered by financial market regulations. Using a difference‐in‐differences approach that relies on the exogenous variation in liquidity generated by regulatory changes, we find that an increase in liquidity causes a reduction in future…

含共同因子的大型动态面板模型的估计效率AI 解读

This paper deals with asymptotically efficient estimation in exchangeable nonlinear dynamic panel models with common unobservable factors. These models are relevant for applications to large portfolios of credits, corporate bonds, or life insurance contracts. For instance, the Asymptotic Risk Factor (ARF) model is recommended in the current regulation in Finance (Basel II and Basel III) and Insurance (Solvency II) for risk prediction and computation of the required capital.…

低层次条件下筛极大似然估计量的一致性与渐近正态性AI 解读

This paper considers sieve maximum likelihood estimation of seminonparametric (SNP) models with an unknown density function as non-Euclidean parameter, next to a finite-dimensional parameter vector. The density function involved is modeled via an infinite series expansion, so that the actual parameter space is infinite-dimensional. It will be shown that under low-level conditions the sieve estimators of these parameters are consistent, and the estimators of the Euclidean…

含非参数生成回归变量的最大得分估计AI 解读

The estimation problem in this paper is motivated by the maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages. We estimate conditional expectations nonparametrically in the first stage. Then, in the second stage, we estimate the preference parameters based on the maximum score estimator of Manski, using the choice…

含附带函数的面板数据模型中的一阶差分AI 解读

This note discusses a class of models for panel data that accommodate between‐group heterogeneity that is allowed to exhibit positive within‐group variance. Such a set‐up generalizes the traditional fixed‐effect paradigm in which between‐group heterogeneity is limited to univariate factors that act like constants within groups. Notable members of the class of models considered are non‐linear regression models with additive heterogeneity and multiplicative‐error models…

含极端次序统计量的社会互动模型AI 解读

In this paper, we introduce a social interaction econometric model with an extreme order statistic to model peer effects. We show that the model is a well‐defined system of equations and that it is a static game with complete information. The social interaction model can include exogenous regressors and group effects. Instrumental variables estimators are proposed for the general model that includes exogenous regressors. We also consider distribution‐free methods that use…

基于得分的间接推断AI 解读

The efficient method of moments (EMM) estimator is an indirect inference estimator based on the simulated auxiliary score evaluated at the sample estimate of the auxiliary parameters. We study an alternative estimator that uses the sample auxiliary score evaluated at the simulated binding function, which maps the structural parameters of interest to the auxiliary parameters. We show that the alternative estimator has the same asymptotic properties as the EMM estimator but in…