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Full-Text Articles in Social and Behavioral Sciences
Joint Tests For Dynamic And Spatial Effects In Short Dynamic Panel Data Models With Fixed Effects And Heteroskedasticity, Zhenlin Yang
Joint Tests For Dynamic And Spatial Effects In Short Dynamic Panel Data Models With Fixed Effects And Heteroskedasticity, Zhenlin Yang
Research Collection School Of Economics
Simple and reliable tests are proposed for testing the existence of dynamic and/or spatial effects in fixed-effects panel data models with small T and possibly heteroskedastic errors. The tests are constructed based on the adjusted quasi scores (AQS), which correct the conditional quasi scores given the initial differences to account for the effect of initial values. To improve the finite sample performance, standardized AQS tests are also derived, which are shown to have much improved finite sample properties. All the proposed tests are robust against nonnormality, but some are not robust against cross-sectional heteroskedasticity (CH). A different type of adjustments …
Diagnostic Tests For Homoskedasticity In Spatial Cross-Sectional Or Panel Models, Badi K. Baltagi, Alain Pirotte, Zhenlin Yang
Diagnostic Tests For Homoskedasticity In Spatial Cross-Sectional Or Panel Models, Badi K. Baltagi, Alain Pirotte, Zhenlin Yang
Research Collection School Of Economics
We propose an Adjusted Quasi-Score (AQS) method for constructing tests for homoskedasticity in spatial econometric models. We first obtain an AQS function by adjusting the score-type function from the given model to achieve unbiasedness, and then develop an Outer-Product-of-Martingale-Difference (OPMD) estimate of its variance. In standard problems where a genuine (quasi) score vector is available, the AQS-OPMD method leads to finite sample improved tests over the usual methods. More importantly in non-standard problems where a genuine (quasi) score is not available and the usual methods fail, the proposed AQS-OPMD method provides feasible solutions. The AQS tests are formally derived and …
Spatial Panel Data Models With Temporal Heterogeneity, Yuhong Xu
Spatial Panel Data Models With Temporal Heterogeneity, Yuhong Xu
Dissertations and Theses Collection (Open Access)
This dissertation studies the fixed effects (FE) spatial panel data (SPD) models with temporal heterogeneity (TH), where the regression coefficients and spatial coefficients are allowed to change with time. The FE-SPD model with time-varying coefficients renders the usual transformation method in dealing with the fixed effects inapplicable, and an adjusted quasi score (AQS) method is proposed, which adjusts the concentrated quasi score function with the fixed effects being concentrated out. AQS tests for the lack of temporal heterogeneity (TH) in slope and spatial parameters are first proposed. Then, a set of AQS estimation and inference methods for the FE-SPD model …
Robust Estimation And Inference Of Spatial Panel Data Models With Fixed Effects, Shew Fan Liu, Zhenlin Yang
Robust Estimation And Inference Of Spatial Panel Data Models With Fixed Effects, Shew Fan Liu, Zhenlin Yang
Research Collection School Of Economics
It is well established that the quasi maximum likelihood (QML) estimation of the spatial regression models is generally inconsistent under unknown cross-sectional heteroskedasticity (CH) and the CH-robust methods have been developed. The same issue remains for the spatial panel data (SPD) models but the similar studies based on QML approach do not seem to have been carried out. This paper focuses on the SPD model with fixed effects (FE). We argue that under unknown CH the QML estimator for the SPD-FE model is inconsistent in general, but there are ‘special cases’ where it may remain consistent although the exact conditions …
Estimation Of Fixed Effects Spatial Dynamic Panel Data Models With Small T And Unknown Heteroskedasticity, Liyao Li, Zhenlin Yang
Estimation Of Fixed Effects Spatial Dynamic Panel Data Models With Small T And Unknown Heteroskedasticity, Liyao Li, Zhenlin Yang
Research Collection School Of Economics
We consider the estimation and inference of fixed effects (FE) spatial dynamic panel data (SDPD) models under small T and unknown heteroskedasticity by extending the M-estimation strategy for homoskedastic FE-SDPD model of Yang (2018, Journal of Econometrics). Unbiased estimating equations are obtained by adjusting the conditional quasi-score functions given the initial observations, leading to M-estimators that are free from the initial conditions and robust against unknown cross-sectional heteroskedasticity. Consistency and asymptotic normality of the proposed M-estimator are established. The standard errors are obtained by representing the estimating equations as sums of martingale differences. Monte Carlo results show that the proposed …
Specification Tests For Temporal Heterogeneity In Spatial Panel Data Models With Fixed Effects, Yuhong Xu, Zhenlin Yang
Specification Tests For Temporal Heterogeneity In Spatial Panel Data Models With Fixed Effects, Yuhong Xu, Zhenlin Yang
Research Collection School Of Economics
We propose adjusted quasi score (AQS) tests for testing the existence of temporal heterogeneity in slope and spatial parameters in spatial panel data (SPD) models, allowing for the presence of individual-specific and/or time-specific fixed effects (or in general intercept heterogeneity). The SPD model with spatial lag is treated in detail by first considering the model with individual fixed effects only, and then extending it to the model with both individual and time fixed effects. Two types of AQS tests (naïve and robust) are proposed, and their asymptotic properties are presented. These tests are then fully extended to SPD models with …
Specification Tests For Temporal Heterogeneity In Spatial Panel Models With Fixed Effects, Yuhong Xu, Zhenlin Yang
Specification Tests For Temporal Heterogeneity In Spatial Panel Models With Fixed Effects, Yuhong Xu, Zhenlin Yang
Research Collection School Of Economics
We propose score type tests for testing the existence of temporal heterogeneity in slope and spatial parameters in spatial panel data (SPD) models, allowing for the presence of individual-specific and/or time-specific fixed effects (or in general intercept heterogeneity). The SPD model with spatial lag effect is treated in detail by first considering the model with individual-specific effects only, and then extending it to the model with both individual and time specific effects. Two types of tests (naive and robust) are proposed, and their asymptotic properties are presented. These tests are then fully extended to an SPD model with both spatial …
Unified M-Estimation Of Fixed-Effects Spatial Dynamic Models With Short Panels, Zhenlin Yang
Unified M-Estimation Of Fixed-Effects Spatial Dynamic Models With Short Panels, Zhenlin Yang
Research Collection School Of Economics
It is well known that quasi maximum likelihood (QML) estimation of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values, and a wrong treatment of them will result in inconsistency and serious bias. The same issues apply to spatial DPD (SDPD) models with short panels. In this paper, a unified Mestimation method is proposed for estimating the fixed-effects SDPD models containing three major types of spatial effects, namely spatial lag, spatial error and space-time lag. The method is free from the specification of the distribution of the initial observations and robust against nonnormality …
Diagnostic Tests For Homoskedasticity In Spatial Cross-Sectional Or Panel Models, Badi H. Baltagi, Alain Pirotte, Zhenlin Yang
Diagnostic Tests For Homoskedasticity In Spatial Cross-Sectional Or Panel Models, Badi H. Baltagi, Alain Pirotte, Zhenlin Yang
Research Collection School Of Economics
We propose tests for homoskedasticity in spatial econometric models, based on joint or concentrated score functions and an Outer-Product-of-Martingale-Difference (OPMD) estimate of the variance of the joint or concentrated score functions. Versions of these tests robust against non-normality are also given. Asymptotic properties of the proposed tests are formally examined using a cross-section model and a panel model with fixed effects. Monte Carlo results show that the proposed tests based on the concentrated score function have good finite sample properties. Finally, the generality of the proposed approach in constructing tests for homoskedasticity is further demonstrated using a spatial dynamic panel …
Bias Correction And Refined Inferences For Fixed Effects Spatial Panel Data Models, Zhenlin Yang, Jihai Yu, Shew Fan Liu
Bias Correction And Refined Inferences For Fixed Effects Spatial Panel Data Models, Zhenlin Yang, Jihai Yu, Shew Fan Liu
Research Collection School Of Economics
This paper first presents simple methods for conducting up to third-order bias and variance corrections for the quasi maximum likelihood (QML) estimators of the spatial parameter(s) in the fixed effects spatial panel data (FE-SPD) models. Then, it shows how the bias and variance corrections lead to refined t-ratios for spatial effects and for covariate effects. The implementation of these corrections depends on the proposed bootstrap methods of which validity is established. Monte Carlo results reveal that (i) the QML estimators of the spatial parameters can be quite biased, (ii) a second-order bias correction effectively removes the bias, and (iii) the …
A Practical Test For Strict Exogeneity In Linear Panel Data Models With Fixed Effects, Liangjun Su, Yonghui Zhang, Jie Wei
A Practical Test For Strict Exogeneity In Linear Panel Data Models With Fixed Effects, Liangjun Su, Yonghui Zhang, Jie Wei
Research Collection School Of Economics
This paper provides a practical test for strict exogeneity in linear panel data models with fixed effects when the number of individuals N goes to infinity while the number of time periods T is fixed. The test is based on the supremum of a sequence of Wald test statistics. Under suitable conditions, we establish the asymptotic distribution of the test statistic and consistency of the test. A bootstrap procedure is proposed to improve the finite sample performance and the validity of the procedure is justified. We investigate the finite sample performance of the test via a small set of Monte …
Unified M-Estimation Of Fixed-Effects Spatial Dynamic Models With Short Panels, Zhenlin Yang
Unified M-Estimation Of Fixed-Effects Spatial Dynamic Models With Short Panels, Zhenlin Yang
Research Collection School Of Economics
It is well known that quasi maximum likelihood (QML) estimation of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values, and a wrong treatment of them will result in inconsistency and serious bias. The same issues apply to spatial DPD (SDPD) models with short panels. In this paper, a unified Mestimation method is proposed for estimating the fixed-effects SDPD models containing three major types of spatial effects, namely spatial lag, spatial error and space-time lag. The method is free from the specification of the distribution of the initial observations and robust against nonnormality …
Model Selection In The Presence Of Incidental Parameters, Yeonseok Lee, Peter C. B. Phillips
Model Selection In The Presence Of Incidental Parameters, Yeonseok Lee, Peter C. B. Phillips
Research Collection School Of Economics
This paper considers model selection in panels where incidental parameters are present. Primary interest centers on selecting a model that best approximates the underlying structure involving parameters that are common within the panel. It is well known that conventional model selection procedures are often inconsistent in panel models and this can be so even without nuisance parameters. Modifications are then needed to achieve consistency. New model selection information criteria are developed here that use either the Kullback-Leibler information criterion based on the profile likelihood or the Bayes factor based on the integrated likelihood with a bias-reducing prior. These model selection …
Initial-Condition Free Estimation Of Fixed Effects Dynamic Panel Data Models, Zhenlin Yang
Initial-Condition Free Estimation Of Fixed Effects Dynamic Panel Data Models, Zhenlin Yang
Research Collection School Of Economics
It is well known that (quasi) MLE of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values; ignoring them or a wrong treatment of them will result in inconsistency or serious bias. This paper introduces a initial-condition free method for estimating the fixed-effects DPD models, through as simple modification of the quasi-score. An outer-product-of-gradients (OPG) method is also proposed for robust inference. The MLE of Hsiao, Pesaran and Tahmiscioglu (2002, Journal of Econometrics), where the initial observations are modeled, is extended to quasi MLE and an OPG method is proposed for robust inference. …
Quasi-Maximum Likelihood Estimation For Spatial Panel Data Regressions, Zhenlin Yang
Quasi-Maximum Likelihood Estimation For Spatial Panel Data Regressions, Zhenlin Yang
Research Collection School Of Economics
This article considers quasi-maximum likelihood estimations (QMLE) for two spatial panel data regression models: mixed effects model with spatial errors and transformed mixed effects model (where response and covariates are transformed) with spatial errors. One aim of transformation is to normalize the data, thus the transformed models are more robust with respect to the normality assumption compared with the standard ones. QMLE method provides additional protection against violation of normality assumption. Asymptotic properties of the QMLEs are investigated. Numerical illustrations are provided.
Discrete Choice Modeling With Nonstationary Panels Applied To Exchange Rate Regime Choice, Sainan Jin
Discrete Choice Modeling With Nonstationary Panels Applied To Exchange Rate Regime Choice, Sainan Jin
Research Collection School Of Economics
This paper develops a regression limit theory for discrete choice nonstationary panels with large cross section (N) and time series (T) dimensions. Some results emerging from this theory are directly applicable in the wider context of M-estimation. This includes an extension of work by Wooldridge [Wooldridge, J.M., 1994. Estimation and Inference for Dependent Processes. In: Engle, R.F., McFadden, D.L. (Eds.). Handbook of Econometrics, vol. 4, North-Holland, Amsterdam] on the limit theory of local extremum estimators to multi-indexed processes in nonlinear nonstationary panel data models. It is shown that the maximum likelihood (ML) estimator is consistent without an incidental parameters problem …
Nonparametric Structural Estimation Via Continuous Location Shifts In An Endogenous Regressor, Peter C. B. Phillips, Liangjun Su
Nonparametric Structural Estimation Via Continuous Location Shifts In An Endogenous Regressor, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
Recent work by Wang and Phillips (2009b, c) has shown that ill posed inverse problems do not arise in nonstationary nonparametric regression and there is no need for nonparametric instrumental variable estimation. Instead, simple Nadaraya Watson nonparametric estimation of a (possibly nonlinear) cointegrating regression equation is consistent with a limiting (mixed) normal distribution irrespective of the endogeneity in the regressor, near integration as well as integration in the regressor, and serial dependence in the regression equation. The present paper shows that some closely related results apply in the case of structural nonparametric regression with independent data when there are continuous …
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
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 increases in variance, thereby substantially reducing root mean square errors. The method is compared with certain consistent estimators and is shown to have superior finite sample properties to the generalized method of …
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Indirect Inference For Dynamic Panel Models, Christian Gourieroux, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
It is well-known that 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 (T) and large cross section sample size (N) asymptotics. The estimation bias is particularly relevant in practical applications when T is small and the autoregressive parameter is close to unity. The present paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference (Gouriéroux et al., 1993), shows unbiasedness and analyzes efficiency. The method is implemented in a simple linear dynamic panel model, but has wider …
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We consider consistent estimation of partially linear panel data models with fixed effects. We propose profile-likelihood-based estimators for both the parametric and nonparametric components in the models and establish convergence rates and asymptotic normality for both estimators.