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空间自回归模型的稳健估计AI 解读

This article proposes and studies two Huber-type estimation approaches, namely, the Huber instrumental variable (IV) estimation and the Huber generalized method of moments (GMM) estimation, for a spatial autoregressive model. We establish the consistency, asymptotic distributions, finite sample breakdown points, and influence functions of these estimators. Simulation studies show that compared to the corresponding traditional estimators (the two-stage least squares…

起讫点流量空间自回归模型的极大似然估计AI 解读

We introduce a spatial autoregressive hurdle model for nonnegative origin–destination flows yN,ij. The model incorporates a hurdle formulation to elucidate the different data-generating processes for zero and positive flows. Our model specifies three types of spatial influences on flow yN,ij that quantify the impact of third-party characteristics on the flow yN,ij: (i) the effect of outflows from origin j, (ii) the effect of inflows to destination i, and (iii) the effect of…

具有主导单元的空间自回归模型的 QML 与有效 GMM 估计AI 解读

This article investigates QML and GMM estimation of spatial autoregressive (SAR) models in which the column sums of the spatial weights matrix might not be uniformly bounded. We develop a central limit theorem in which the number of columns with unbounded sums can be finite or infinite and the magnitude of their column sums can be O(nδ) if δ<1. Asymptotic distributions of QML and GMM estimators are derived under this setting, including the GMM estimators with the best linear…

空间计量模型贝叶斯估计的大样本性质AI 解读

This paper studies asymptotic properties of a posterior probability density and Bayesian estimators of spatial econometric models in the classical statistical framework. We focus on the high-order spatial autoregressive model with spatial autoregressive disturbance terms, due to a computational advantage of Bayesian estimation. We also study the asymptotic properties of Bayesian estimation of the spatial autoregressive Tobit model, as an example of nonlinear spatial models.…

谁是关键参与者？青少年违法行为的网络分析AI 解读

This article presents a methodology for empirically identifying the key player, whose removal from the network leads to the optimal change in aggregate activity level in equilibrium [Ballester, C., Calvó-Armengol, A., and Zenou, Y. (2006), “Who’s Who in Networks. Wanted: The Key Player,” Econometrica, 74: 1403–1417], allowing the network links to rewire after the removal of the key player. First, we propose an IV-based estimation strategy for the social-interaction effect,…

鞅差下有效的两步广义经验似然估计与检验AI 解读

This paper considers two-step generalized empirical likelihood (GEL) estimation and tests with martingale differences when there is a computationally simple $\sqrt n$ -consistent estimator of nuisance parameters or the nuisance parameters can be eliminated with an estimating function of parameters of interest. As an initial estimate might have asymptotic impact on final estimates, we propose general $C(\alpha )$ -type transformed moments to eliminate the impact, and use them…

动态面板空间向量自回归估计：稳定性与空间多变量协整AI 解读

This paper introduces dynamic panel spatial vector autoregressive models. We study features of dynamics and spatial interactions that an SVAR model can generate and classify the model into stable or unstable cases by partitioning parameter spaces. For stable, spatial cointegration, and mixed cointegration cases, we investigate identification and QML estimation of the models to take into account simultaneity and correlated relationships. Asymptotic properties and…

由双边变量构造内生空间权重的 SAR 模型估计AI 解读

This paper studies the estimation of a cross-sectional spatial autoregressive (SAR) model with spatial weights constructed by bilateral variables like the trade or investment between regions. We model the possible endogeneity in spatial weights due to the correlation between the error term in the SAR model and unobserved interactive fixed effects in bilateral variables. Using a control function approach, we propose two-stage estimation methods and establish their consistency…

具有跨期优化的空间动态模型：设定与估计AI 解读

In this paper, we introduce a dynamic spatial interaction econometric model. There are n forward-looking agents of whom each has a parametric linear-quadratic payoff, and they interact with their neighbors through a spatial network. Considering a Markov perfect equilibrium (MPE), we derive a unique Nash equilibrium equation and construct a new spatial dynamic panel data (SDPD) model. For estimation, we suggest mainly the quasi-maximum likelihood (QML) method. Asymptotic…

动态面板模型的初始条件：组内方程与组间方程AI 解读

Summary This paper investigates the quasi-maximum likelihood estimation of short dynamic panel data models. We consider their estimation on both fixed effects and random effects specifications and propose a Hausman test when exogenous variables are present. For a dynamic panel model, initial conditions play important roles in model structure and estimation, and they give rise to a between equation under the random effects framework. With the between equation properly…

采用指数概率分布的网络形成与互动模型：设定与估计AI 解读

We model network formation and interactions under a unified framework by considering that individuals anticipate the effect of network structure on the utility of network interactions when choosing links. There are two advantages of this modeling approach: first, we can evaluate whether network interactions drive friendship formation or not. Second, we can control for the friendship selection bias on estimated interaction effects. We provide microfoundations of this…

空间模型选择的似然比检验AI 解读

This paper develops a nondegenerate likelihood-ratio test for model selection between two competitive spatial econometrics models. It generalizes the test of Vuong (1989) to models with spatial near-epoch dependent (NED) data. We do not make any structural assumption on the true model specification and allow for the cases where both or one of the two competing models are mis-specified. The test is valid whether two models are nested or non-nested. As a prerequisite of the…

空间自回归模型的广义经验似然估计与检验AI 解读

This paper considers the generalized empirical likelihood (GEL) estimation and tests of high order spatial autoregressive (SAR) models by exploring an inherent martingale structure. The GEL estimator has the same asymptotic distribution as the generalized method of moments estimator explored with same moment conditions for estimation, but circumvents a first step estimation of the optimal weighting matrix with a preliminary estimator, and thus can be robust to unknown…

矩阵指数空间模型的非正规 N2SLS 与 LASSO 估计AI 解读

In this paper, we consider estimation of the matrix exponential spatial specification model with the Durbin and endogenous regressors. We find that the nonlinear two-stage least squares (N2SLS) estimator is in general consistent and asymptotically normal. However, when the Durbin and endogenous regressors are irrelevant, the gradient vector of the N2SLS criterion function has a singular covariance matrix with probability approaching one (w.p.a.1.). Some components of the…

空间自回归 Tobit 模型的筛最大似然估计AI 解读

This paper extends the ML estimation of a spatial autoregressive Tobit model under normal disturbances in Xu and Lee (2015b, Journal of Econometrics) to distribution-free estimation. We examine the sieve MLE of the model, where the disturbances are i.i.d.with an unknown distribution. We show that the spatial autoregressive process with Tobit censoring and related variables are spatial near-epoch dependent (NED). A related contribution is that we develop some exponential…

具有交互固定效应的空间动态面板模型AI 解读

This paper studies the estimation of a dynamic spatial panel data model with interactive individual and time effects with large n and T. The model has a rich spatial structure including contemporaneous spatial interaction and spatial heterogeneity. Dynamic features include individual time lag and spatial diffusion. The interactive effects capture heterogeneous impacts of time effects on cross sectional units. The interactive effects are treated as parameters, so as to allow…

内生时变空间权重下空间动态面板模型的拟极大似然估计AI 解读

In spatial panel data models, when a spatial weights matrix is constructed from economic or social distance, spatial weights could be endogenous and also time varying. This paper presents model specification and proposes QMLE estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices. Asymptotic properties of the proposed QMLE are rigorously established. We extend the notion of spatial near-epoch dependence to allow time dependence.…

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,…

含时变内生空间权重、共同因子与随机系数的空间面板自回归模型：贝叶斯分析AI 解读

This article examines spatial panel autoregressive (SAR) models with dynamic, time-varying endogenous spatial weights matrices, common factors, and random coefficients. An empirical application is on the spillover effects of state Medicaid spending. Endogeneity of spatial weights matrices comes from the correlation of “economic distance” and the disturbances in the SAR equation. Common factors control for common shocks to all states and random coefficients may capture…

空间自回归Tobit模型的最大似然估计AI 解读

This paper examines a Tobit model with spatial autoregressive interactions. We consider the maximum likelihood estimation for this model and analyze asymptotic properties of the estimator based on the spatial near-epoch dependence of the dependent variable process generated from the model structure. We show that the maximum likelihood estimator is consistent and asymptotically normally distributed. Monte Carlo experiments are performed to verify finite sample properties of…

矩阵指数空间模型的大样本性质及其外国直接投资应用AI 解读

This paper studies large sample properties of the matrix exponential spatial specification (MESS). We find that the quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the QMLE of the SAR model. For the general model that has MESS in both the dependent variable and disturbances, labeled MESS(1,1), the QMLE can be consistent under unknown heteroskedasticity when the spatial weights matrices in the two MESS…

因变量非线性变换的空间自回归模型AI 解读

This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a statistical test to compare the nonlinear transformation against alternatives. Monte Carlo experiments are designed…

空间依赖 Moran’s I 检验的自助法AI 解读

This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the test statistic for Moran’s I test for spatial dependence. We show that, for many statistics in spatial econometric models, the bootstrap can be studied based on linear–quadratic (LQ) forms of disturbances. By proving the uniform convergence of the cumulative distribution function for LQ forms to that of a normal distribution, we show that the bootstrap is…

空间权重矩阵内生时的空间自回归模型估计AI 解读

The spatial autoregressive (SAR) model is a standard tool for analyzing data with spatial correlation. Conventional estimation methods rely on the key assumption that the spatial weight matrix is strictly exogenous, which would likely be violated in some empirical applications where spatial weights are determined by economic factors. This paper presents model specification and estimation of the SAR model with an endogenous spatial weight matrix. We provide three estimation…