The effects of cross-section dimension n in panel co-integration test

Hu, Yi; Xia, Xiaohua; Wang, Meijin; Zhanming, Chen

doi:10.1016/j.cnsns.2009.05.001

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Panel cointegration tests can also be divided into two generations. The tests proposed by Kao [42] and Pedroni [43] are two famous representatives of the first generation [44]. Both tests are based on residuals of regression, which can be regarded as an extension of the traditional Engle-Granger two steps cointegration method [45].…”

Section: Panel Cointegration Testsmentioning

confidence: 99%

The Relationship between Energy Consumption and Economic Growth: Evidence from China’s Industrial Sectors

Guo

Wang

et al. 2015

Energies

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Abstract:In this article, the relationship between energy consumption and economic growth is examined from the viewpoint of China's industrial sectors. Panel data from 37 industrial sectors in China covering the period from 1998 to 2010 was used in this study. Not only first generation panel unit root tests and panel cointegration tests, but also second generation tests that account for dependence between cross-sectional units were employed. The empirical results reveal that both energy consumption and economic growth are integrated as order one, and they are cointegrated. Panel fully modified ordinary least squares estimators show that a 1% increase in energy consumption increases the real value added of industrial sectors by 0.871%, and a 1% increase in real value added of industrial sectors increases energy consumption by 1.103%. The panel vector error correction models for causality tests are estimated by a system generalized moment method. We find a unidirectional causal relation running from economic growth to energy consumption in the shortrun. In the long run, however, there is evidence of a unidirectional causality running from energy consumption to economic growth. OPEN ACCESSEnergies 2015, 8 9393

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Section: Panel Cointegration Testsmentioning

confidence: 99%

The Relationship between Energy Consumption and Economic Growth: Evidence from China’s Industrial Sectors

Guo

Wang

et al. 2015

Energies

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“…In this section, panel data of relevant index in 2003-2012 will be based to take empirical analysis of influence of tax arrangements to upgrading and rationalization of industrial structure in China. We check the stationarity of the variables using nonstationary panel data methods [22][23][24][25][26][27]; in particular, according to [22,24], stationarity tests for series should be conducted before performing the panel regression; otherwise the regression may be spurious and this will result in misleading conclusions. And according to the Monte Carlo comparisons by [25,26], the second-generation panel unit root tests proposed by Bai and Ng [24] and Pesaran [28] are robust relatively, so we choose them in our empirical study.…”

Section: Analysis Of Empirical Study Resultsmentioning

confidence: 99%

Tax Arrangement and Regional Industrial Restructuring: Evidence from Panel Data in China

Zhang

Tao

et al. 2016

Mathematical Problems in Engineering

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Regional industrial restructuring has been one of the major items in the transformation of economic development mode. An exploration was made into the influence of tax arrangement on the regional industrial structure by setting up a panel data econometric model based on the evaluation and analysis of the regional industrial structure in China. It was shown that tax arrangement influenced the regional industrial restructuring in terms of three aspects. Microlevel: the turnover tax and income tax appeared with a U-path of influence on upgrading of the industrial structure while appearing with an inverted U-path of influence on rationalization of the industrial structure. In addition, the levy of resource tax had a negative impact on both upgrading and rationalization of the industrial structure. Mesolevel: taxation in the secondary and tertiary industries appeared with a U-path of influence on upgrading of the industrial structure. An increase of taxation in the secondary industry had a negative impact on rationalization of the industrial structure. The taxation in the tertiary industry appeared with an inverted U-path of influence on rationalization of the industrial structure. Macrolevel: the macrotax burden had a U-path of influence on both upgrading and rationalization of the industrial structure.

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“…It is a stylized fact that plenty of relationships are dynamic and nonlinear in nature and society, especially in economic and financial systems [1][2][3][4][5][6][7][8]. These relationships are usually depicted by nonlinear models.…”

Section: Introductionmentioning

confidence: 99%

Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models

Xia

Deng

et al. 2014

Discrete Dynamics in Nature and Society

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Generalized method of moments (GMM) has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample performance is not very well. In order to improve the finite sample performance of generalized method of moments estimators, this paper studies higher-order mean squared error of two-step efficient generalized method of moments estimators for nonlinear models. Specially, we consider a general nonlinear regression model with endogeneity and derive the higher-order asymptotic mean square error for two-step efficient generalized method of moments estimator for this model using iterative techniques and higher-order asymptotic theories. Our theoretical results allow the number of moments to grow with sample size, and are suitable for general moment restriction models, which contains conditional moment restriction models as special cases. The higher-order mean square error can be used to compare different estimators and to construct the selection criteria for improving estimator’s finite sample performance.

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The effects of cross-section dimension n in panel co-integration test

Cited by 6 publications

References 22 publications

The Relationship between Energy Consumption and Economic Growth: Evidence from China’s Industrial Sectors

The Relationship between Energy Consumption and Economic Growth: Evidence from China’s Industrial Sectors

Tax Arrangement and Regional Industrial Restructuring: Evidence from Panel Data in China

Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models

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