论文检索

基于剖面优化的单指标分位数回归推断AI 解读

Single index models offer greater flexibility in data analysis than linear models but retain some of the desirable properties such as the interpretability of the coefficients. We consider a pseudo-profile likelihood approach to estimation and testing for single-index quantile regression models. We establish the asymptotic normality of the index coefficient estimator as well as the optimal convergence rate of the nonparametric function estimation. Moreover, we propose a score…

面板数据分析中的结构识别AI 解读

Panel data analysis is an important topic in statistics and econometrics. In such analysis, it is very common to assume the impact of a covariate on the response variable remains constant across all individuals. While the modelling based on this assumption is reasonable when only the global effect is of interest, in general, it may overlook some individual/subgroup attributes of the true covariate impact. In this paper, we propose a data driven approach to identify the…

向量分位数回归：最优传输方法AI 解读

We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector $Y$, taking values in $\mathbb{R}^{d}$ given covariates $Z=z$, taking values in $\mathbb{R}^{k}$, is a map $u\longmapsto Q_{Y|Z}(u,z)$, which is monotone, in the sense of being a gradient of a convex function, and such that given that vector $U$ follows a reference non-atomic distribution $F_{U}$, for instance uniform…

使用回归不连续设计评估GED证书的劳动力市场回报AI 解读

We evaluate returns to General Educational Development (GED) certification for high school dropouts using state administrative data. We apply a fuzzy regression discontinuity method to account for test takers retaking the test. For women we find that GED certification has no statistically significant effect on either employment or earnings. For men we find a significant increase in earnings in the second year after taking the test but no impact in subsequent years. GED…

良好信用声誉的价值：来自信用卡债务重谈的证据AI 解读

I exploit a natural experiment to estimate borrowers’ willingness to pay for a good credit reputation. A lender in Chile offered lower installments to borrowers who were in default. Those who owed more than a fixed arbitrary cutoff were additionally offered a clean public repayment record. Using the cutoff in a fuzzy regression discontinuity design, I show that borrowers are willing to pay the equivalent of 11% of their monthly income for a good reputation. Borrowers use…

未测中介—结局混杂下中介效应的锐敏感性界限AI 解读

It is often of interest to decompose the total effect of an exposure into a component that acts on the outcome through some mediator and a component that acts independently through other pathways. Said another way, we are interested in the direct and indirect effects of the exposure on the outcome. Even if the exposure is randomly assigned, it is often infeasible to randomize the mediator, leaving the mediator-outcome confounding not fully controlled. We develop a…

网络数据的回归分析AI 解读

This paper concerns regression methodology for assessing relationships between multi-dimensional response variables and covariates that are correlated within a network. To address analytical challenges associated with the integration of network topology into the regression analysis, we propose a hybrid quadratic inference method that uses both prior and data-driven correlations among network nodes. A Godambe information-based tuning strategy is developed to allocate weights…

非参数工具变量回归中泛函的自适应估计AI 解读

We consider the problem of estimating the value ℓ ( ϕ ) of a linear functional, where the structural function ϕ models a nonparametric relationship in presence of instrumental variables. We propose a plug-in estimator which is based on a dimension reduction technique and additional thresholding. It is shown that this estimator is consistent and can attain the minimax optimal rate of convergence under additional regularity conditions. This, however, requires an optimal choice…

弱依赖下非线性分位数回归的渐近理论AI 解读

This paper studies the asymptotic properties of the nonlinear quantile regression model under general assumptions on the error process, which is allowed to be heterogeneous and mixing. We derive the consistency and asymptotic normality of regression quantiles under mild assumptions. First-order asymptotic theory is completed by a discussion of consistent covariance estimation.

含内生解释变量的空间半参数模型AI 解读

This paper proposes a semiparametric generalized method of moments estimator (GMM) estimator for a partially parametric spatial model with endogenous spatially dependent regressors. The finite-dimensional estimator is shown to be consistent and root-n asymptotically normal under some reasonable conditions. A spatial heteroscedasticity and autocorrelation consistent covariance estimator is constructed for the GMM estimator. The leading application is nonlinear spatial…

控制点与数据合并：因子结构模型的识别和推断AI 解读

Factor structure models are widely used in economics to extract latent variables, such as personality traits, and to measure their impact on outcomes of interest. The identification and inference of these models, however, highly depend on the availability of rich longitudinal data. To overcome the common problem of data scarcity, this paper proposes to combine datasets that each identify some part of the likelihood, thereby recovering the identification of the complete…

异质专业能力下的贝叶斯决策问题估计AI 解读

We consider the recent novel two-step estimator of Iaryczower and Shum (American Economic Review 2012; 102: 202–237), who analyze voting decisions of US Supreme Court justices. Motivated by the underlying theoretical voting model, we suggest that where the data under consideration display variation in the common prior, estimates of the structural parameters based on their methodology should generally benefit from including interaction terms between individual and time…

电力市场放松管制影响的平滑转换 Logit 模型AI 解读

This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The…

含二元内生解释变量的非参数三角模型估计AI 解读

We consider identification and estimation in a nonparametric triangular system with a binary endogenous regressor and nonseparable errors. For identification, we take a control function approach utilizing the Dynkin system idea. We articulate various trade‐offs, including continuity, monotonicity and differentiability. For estimation, we use the idea of local instruments under smoothness assumptions, but we do not assume additive separability in latent variables. Our…

面板数据模型中斜率同质性的拉格朗日乘数型检验AI 解读

In this paper, we employ the Lagrange multiplier (LM) principle to test parameter homogeneity across cross‐section units in panel data models. The test can be seen as a generalization of the Breusch–Pagan test against random individual effects to all regression coefficients. While the original test procedure assumes a likelihood framework under normality, several useful variants of the LM test are presented to allow for non‐normality, heteroscedasticity and serially…

朋友与邻居：局部经济发展与犯罪活动AI 解读

Abstract We exploit a sudden shock to demand for a subset of low-wage workers generated by the 2005 Base Realignment and Closure (BRAC) program in San Antonio, Texas, to identify the effects of localized economic development on crime. We use a difference-in-differences methodology that takes advantage of variation in BRAC’s impact over time and across neighborhoods. We find that appropriative criminal behavior increases in neighborhoods where a fraction of residents…

大 N、大 T 非线性面板模型中的个体与时间效应AI 解读

We derive fixed effects estimators of parameters and average partial effects in (possibly dynamic) nonlinear panel data models with individual and time effects. They cover logit, probit, ordered probit, Poisson and Tobit models that are important for many empirical applications in micro and macroeconomics. Our estimators use analytical and jackknife bias corrections to deal with the incidental parameter problem, and are asymptotically unbiased under asymptotic sequences…

状态密度时间序列的非平稳性AI 解读

This paper proposes a new framework to analyze the nonstationarity in the time series of state densities, representing either cross-sectional or intra-period distributions of some underlying economic variables. We regard each state density as a realization of Hilbertian random variable, and use a functional time series model to fit a given time series of state densities. This allows us to explore various sources of the nonstationarity of such time series. The potential unit…

持续协变量下的预测分位数回归：IVX-QR 方法AI 解读

This paper develops econometric methods for inference and prediction in quantile regression (QR) allowing for persistent predictors. Conventional QR econometric techniques lose their validity when predictors are highly persistent. I adopt and extend a methodology called IVX filtering (Magdalinos and Phillips, 2009) that is designed to handle predictor variables with various degrees of persistence. The proposed IVX-QR methods correct the distortion arising from persistent…

基于留一受试者交叉验证的模型平均AI 解读

This paper develops a frequentist model averaging method based on the leave-subject-out cross-validation. This method is applicable not only to averaging longitudinal data models, but also to averaging time series models which can have heteroscedastic errors. The resulting model averaging estimators are proved to be asymptotically optimal in the sense of achieving the lowest possible squared errors. Both simulation study and empirical example show the superiority of the…

GEL 估计量的模型误设稳健自助法与高阶渐近改进AI 解读

I propose a nonparametric iid bootstrap procedure for the empirical likelihood, the exponential tilting, and the exponentially tilted empirical likelihood estimators that achieves asymptotic refinements for t tests and confidence intervals, and Wald tests and confidence regions based on such estimators. Furthermore, the proposed bootstrap is robust to model misspecification, i.e., it achieves asymptotic refinements regardless of whether the assumed moment condition model is…

银行的地理扩张能否降低风险？AI 解读

We develop a new identification strategy to evaluate the impact of the geographic expansion of a bank holding company (BHC) across US metropolitan statistical areas (MSAs) on BHC risk. For the average BHC, the instrumental variable results suggest that geographic expansion materially reduces risk. Geographic diversification does not affect loan quality. The results are consistent with arguments that geographic expansion lowers risk by reducing exposure to idiosyncratic local…

华尔街的旋转门AI 解读

Credit analysts often leave rating agencies to work at firms they rate. We use benchmark rating agencies as counterfactuals to measure rating inflation in a difference-in-differences framework and find that transitioning analysts award inflated ratings to their future employers before switching jobs. We find no evidence that analysts inflate ratings of other firms they rate. Market based measures of hiring firms' credit quality further indicate that transitioning analysts'…

司机请注意，附近有儿童：交通、污染与婴儿健康AI 解读

We investigate the effects of automobile congestion on ambient air pollution and local infant mortality rates using data from California spanning 2002 to 2007. Constructing instrumental variables (IV) using the relationship of traffic, weather conditions, and pollutants, we show that particulate matter, even at modern levels, has large marginal effects on weekly infant mortality rates, especially for premature or low birthweight infants. We also find suggestive evidence of…