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固定效应动态面板模型：一种因子分析方法AI 解读

We consider the estimation of dynamic panel data models in the presence of incidental parameters in both dimensions: individual fixed-effects and time fixed-effects, as well as incidental parameters in the variances. We adopt the factor analytical approach by estimating the sample variance of individual effects rather than the effects themselves. In the presence of cross-sectional heteroskedasticity, the factor method estimates the average of the cross-sectional variances…

动态面板数据模型不同估计方法的有限样本比较AI 解读

SUMMARY The Wooldridge method is based on a simple and novel strategy to deal with the initial values problem in nonlinear dynamic random‐effects panel data models. The characteristic of the method makes it very attractive in empirical applications. However, its finite sample performance and robustness are not fully known as of yet. In this paper we investigate the performance and robustness of this method in comparison with an ideal case in which the initial values are…

内生性与公司内部治理的动态关系AI 解读

We use a well-developed dynamic panel generalized method of moments (GMM) estimator to alleviate endogeneity concerns in two aspects of corporate governance research: the effect of board structure on firm performance and the determinants of board structure. The estimator incorporates the dynamic nature of internal governance choices to provide valid and powerful instruments that address unobserved heterogeneity and simultaneity. We re-examine the relation between board…

时间序列设定错误下动态面板模型的偏差AI 解读

We consider within-group estimation of higher-order autoregressive panel models with exogenous regressors and fixed effects, where the lag order is possibly misspecified. Even when disregarding the misspecification bias, the fixed-effect bias formula is quite different from the correctly specified case though its asymptotic order remains the same under the stationarity. We suggest bias reduction methods under the possible time series misspecification.

固定效应空间动态面板的估计：空间协整情形AI 解读

Yu et al. (2008) establish asymptotic properties of quasi-maximum likelihood estimators for a stable spatial dynamic panel model with fixed effects when both the number of individuals n and the number of time periods T are large. This paper investigates unstable cases where there are unit roots generated by temporal and spatial correlations. We focus on the spatial cointegration model where some eigenvalues of the data generating process are equal to 1 and the outcomes of…

动态面板结构方程中 LIML 估计量的若干性质AI 解读

We investigate the finite sample and asymptotic properties of the within-groups (WG), the random-effects quasi-maximum likelihood (RQML), the generalized method of moment (GMM) and the limited information maximum likelihood (LIML) estimators for a panel autoregressive structural equation model with random effects when both T (time-dimension) and N (cross-section dimension) are large. When we use the forward-filtering due to Alvarez and Arellano (2003), the WG, the RQML and…

动态非线性固定效应面板模型的偏差减少AI 解读

The fixed effects estimator of panel models can be severely biased because of well-known incidental parameter problems. It is shown that this bias can be reduced in nonlinear dynamic panel models. We consider asymptotics where n and T grow at the same rate as an approximation that facilitates comparison of bias properties. Under these asymptotics, the bias-corrected estimators we propose are centered at the truth, whereas fixed effects estimators are not. We discuss several…

带固定效应的动态面板分位数回归AI 解读

This paper studies a quantile regression dynamic panel model with fixed effects. Panel data fixed effects estimators are typically biased in the presence of lagged dependent variables as regressors. To reduce the dynamic bias, we suggest the use of the instrumental variables quantile regression method of Chernozhukov and Hansen (2006) along with lagged regressors as instruments. In addition, we describe how to employ the estimated models for prediction. Monte Carlo…

短面板向量自回归中脉冲响应函数的渐近分布AI 解读

This paper establishes the asymptotic distributions of the impulse response functions in panel vector autoregressions with a fixed time dimension. It also proves the asymptotic validity of a bootstrap approximation to their sampling distributions. The autoregressive parameters are estimated using the GMM estimators based on the first differenced equations and the error variance is estimated using an extended analysis-of-variance type estimator. Contrary to the time series…

双层动态面板 Tobit 模型的模拟估计：已婚女性劳动供给AI 解读

In this paper a computationally practical simulation estimator is proposed for the two-tiered dynamic panel Tobit model originally developed by Cragg (1971). The log-likelihood function simulated through procedures based on a recursive algorithm formulated by the Geweke–Hajivassiliou–Keane simulator is maximized. The simulation estimators are then applied to study the labor supply of married women. The rich dynamic structure of the labor force participation decision as well…

衡量房价在空间与时间上的扩散AI 解读

How fast and how long (and to what magnitude) does a change in housing prices in one region affect its neighbors? In this paper, I apply a time series technique for measuring impulse response functions from local projections to a spatial autoregressive model of housing prices. For a dynamic panel of California counties, the data reveal that the diffusion of regional housing prices across space lasts up to two and half years. This result, and the econometric techniques…

动态反馈对面板模型 LS 与 MM 估计精度的影响：补充结果AI 解读

In this paper, we show that the order of magnitude of the finite sample bias of the estimator of Bun and Kiviet (2006) reduces from O(T/N) to O(1/N) if the original level model is transformed by the upper triangular Cholesky factorization of the inverse of the pseudo variance matrix of error component ui wherein true values of the variances of individual effects and disturbances may not be used. Some variants of the system GMM estimator that are associated with the…

美国专利的知识溢出：含隐秘共同创新因子的动态专利强度模型AI 解读

During the past two decades, innovations protected by patents have played a key role in business strategies. This fact enhanced studies of the determinants of patents and the impact of patents on innovation and competitive advantage. Sustaining competitive advantages is as important as creating them. Patents help sustaining competitive advantages by increasing the production cost of competitors, by signaling a better quality of products and by serving as barriers to entry.…

单位根空间动态面板数据模型的估计AI 解读

This paper examines the asymptotics of the QMLE for unit root dynamic panel data models with spatial effect and fixed effects. We consider a unit root dynamic panel data model with spatially correlated disturbances and a unit root spatial dynamic panel data model. For both models the estimate of the dynamic coefficient is $\root \of {nT^3 }$ consistent and the estimates of other parameters are $\root \of {nT}$ consistent, and all of them are asymptotically normal. For the…

动态面板模型的间接推断AI 解读

Maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size and large cross section sample size asymptotics. This paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference, shows unbiasedness and analyzes efficiency. Monte Carlo studies show that our procedure achieves substantial bias reductions with only mild…

增广动态面板模型的迭代可行广义最小二乘估计AI 解读

This article provides the large sample distribution of the iterated feasible generalized least-squares (IFGLS) estimator of an augmented dynamic panel data model. The regressors in the model include lagged values of the dependent variable and may include other explanatory variables that, while exogenous with respect to the time-varying error component, may be correlated with an unobserved time-invariant component. The article compares the finite sample properties of the…

同时含时间与个体固定效应的空间动态面板模型AI 解读

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with both time and individual fixed effects when the number of individuals n and the number of time periods T can be large. We propose a data transformation approach to eliminate the time effects. When n / T → 0, the estimators are $\root \of {nT}$ consistent and asymptotically centered normal; when n is asymptotically proportional to T , they are $\root \of {nT}$…

电视观看对儿童认知发展的动态处理效应分析AI 解读

Abstract We investigate whether TV watching at ages 6–7 and 8–9 affects cognitive development measured by math and reading scores at ages 8–9, using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child‐specific factor, endogeneity of TV watching, and dynamic nature of the causal relation . A special emphasis is placed on the last aspect, where TV watching affects cognitive development, which in turn affects…

动态面板模型中系统GMM估计量的弱工具变量问题AI 解读

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error. However, we show in this paper that in the covariance stationary panel data AR(1) model the expected values of the concentration parameters in the differenced and levels equations for the…

固定效应动态面板中在单位根处保持强工具的 GMM 估计AI 解读

This paper develops new estimation and inference procedures for dynamic panel data models with fixed effects and incidental trends. A simple consistent GMM estimation method is proposed that avoids the weak moment condition problem that is known to affect conventional GMM estimation when the autoregressive coefficient ( ρ ) is near unity. In both panel and time series cases, the estimator has standard Gaussian asymptotics for all values of ρ ∈ (−1, 1] irrespective of how the…

内部与外部习惯形成面板模型的估计AI 解读

A new bias-corrected estimator is developed for dynamic panel model with both fixed and spatial effects. The estimator is asymptotically unbiased, normally distributed, and it has good finite sample properties (low finite sample bias and root mean squared error). Applying the estimator to annual consumption data for the continental U.S. states shows that state consumption growth is not significantly affected by its own (lagged) consumption growth. However, it is affected by…

处理附带参数问题的极大似然方法AI 解读

This paper uses the invariance principle to solve the incidental parameter problem of [Econometrica 16 (1948) 1–32]. We seek group actions that preserve the structural parameter and yield a maximal invariant in the parameter space with fixed dimension. M-estimation from the likelihood of the maximal invariant statistic yields the maximum invariant likelihood estimator (MILE). Consistency of MILE for cases in which the likelihood of the maximal invariant is the product of…

动态面板数据模型中均值非平稳性的影响AI 解读

In this paper, we investigate the effect of mean-nonstationarity on the first-difference generalized method of moments (FD-GMM) estimator in dynamic panel data models. We find that when data is mean-nonstationary and the variance of individual effects is significantly larger than that of disturbances, the FD-GMM estimator performs quite well. We demonstrate that this is because the correlation between the lagged dependent variable and instruments gets larger owing to the…

持久数据下动态面板模型的 GMM 估计与推断AI 解读

In this paper we consider generalized method of moments–based (GMM-based) estimation and inference for the panel AR(1) model when the data are persistent and the time dimension of the panel is fixed. We find that the nature of the weak instruments problem of the Arellano–Bond (Arellano and Bond, 1991, Review of Economic Studies 58, 277–297) estimator depends on the distributional properties of the initial observations. Subsequently, we derive local asymptotic approximations…