Testing for slope heterogeneity in Stata

2021 ◽  
Vol 21 (1) ◽  
pp. 51-80
Author(s):  
Tore Bersvendsen ◽  
Jan Ditzen
Keyword(s):  
Economic Growth ◽  
Monte Carlo Simulation ◽  
Cross Sectional ◽  
Robust Test ◽  
Economic Growth Model ◽  
Robust Version ◽  
Cross Sectional Dimension ◽  
Cross Sectional Dependence ◽  
Time Periods ◽  
New Community

In this article, we introduce a new community-contributed command, xthst, to test for slope heterogeneity in panels with many observations over cross-sectional units and time periods. The command implements such a test, the delta test (Pesaran and Yamagata, 2008, Journal of Econometrics 142: 50–93). Under its null, slope coefficients are homogeneous across cross-sectional units. Under the alternative, slope coefficients are heterogeneous in the cross-sectional dimension. xthst also includes two extensions. The first is a heteroskedasticity- and autocorrelation-consistent robust test along the lines of Blomquist and Westerlund (2013, Economics Letters 121: 374–378). The second extension is a cross-sectional-dependence robust version. We discuss all tests and present examples using an economic growth model. A Monte Carlo simulation shows that the size and the power behave as expected.

Health Infrastructure and Economic Growth in Sub-Saharan Africa

2017 ◽  
pp. 82-98
Author(s):  
Samuel Adams ◽  
Edem Kwame Mensah Klobodu ◽  
Richmond Odartey Lamptey
Keyword(s):  
Economic Growth ◽  
Labor Force ◽  
Capital Investment ◽  
Sub Saharan Africa ◽  
Sufficient Evidence ◽  
Cross Sectional ◽  
Health Infrastructure ◽  
Fixed Capital Formation ◽  
Cross Sectional Dependence ◽  
Sub Saharan

In this study, we examine the effect of health infrastructure on economic growth in 30 Sub-Saharan Africa (SSA) countries over the period 1990-2014. Using modern econometric techniques that account for cross-sectional dependence in panel data, we find that health infrastructure (measured by mortality rate) does not have robust impact on economic growth. Gross fixed capital formation, however, is positively associated with economic growth while labor force and polity variables exhibit significant association with economic growth. The results provide sufficient evidence that although capital investment is adequate, the labor force and political environment have not facilitated the health infrastructure in increasing the GDP per capita level in SSA.

Health Infrastructure and Economic Growth in Sub-Saharan Africa

2018 ◽  
pp. 146-163
Author(s):  
Samuel Adams ◽  
Edem Kwame Mensah Klobodu ◽  
Richmond Odartey Lamptey
Keyword(s):  
Economic Growth ◽  
Labor Force ◽  
Capital Investment ◽  
Sub Saharan Africa ◽  
Sufficient Evidence ◽  
Cross Sectional ◽  
Health Infrastructure ◽  
Fixed Capital Formation ◽  
Cross Sectional Dependence ◽  
Sub Saharan

In this study, we examine the effect of health infrastructure on economic growth in 30 Sub-Saharan Africa (SSA) countries over the period 1990-2014. Using modern econometric techniques that account for cross-sectional dependence in panel data, we find that health infrastructure (measured by mortality rate) does not have robust impact on economic growth. Gross fixed capital formation, however, is positively associated with economic growth while labor force and polity variables exhibit significant association with economic growth. The results provide sufficient evidence that although capital investment is adequate, the labor force and political environment have not facilitated the health infrastructure in increasing the GDP per capita level in SSA.

Nexus of Renewable Energy Consumption, Economic Growth, Population Growth, FDI, and Environmental Degradation in South Asian Countries: New Evidence from Driscoll-Kraay Standard Error Approach

2021 ◽  
Vol 3 (2) ◽  
pp. 200-211
Author(s):  
Ansar Abbas Shah ◽  
Muhammad Sajjad Hussain ◽  
Muhammad Atif Nawaz ◽  
Mazhar Iqbal
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Population Growth ◽  
South Asian ◽  
Environmental Degradation ◽  
Asian Countries ◽  
Renewable Energy Consumption ◽  
Cross Sectional ◽  
Cross Sectional Dependence

Environmental degradation is the most prominent area nowadays, especially in developing counties where high renewable energy consumption and population growth deteriorate the atmosphere of the country. Thus, the current study investigates the nexus among renewable energy consumption, economic growth (EG), population growth, foreign direct investment (FDI), and environmental degradation in South Asian countries. The covariance matrix estimators that are developed by “Driscoll and Kraay” are used in this study. The primary property of this estimator is that it does not account for the cross-sectional dependence; thus, it provides substantial, robust outcomes among the cross-sectional units while in the presence of cross-sectional dependence. The data was collected from the World Development Indicators (WDI) from 2001 to 2019. The findings exposed that positive nexus among the population growth, FDI, and environmental degradation while renewable energy consumption and EG has negative nexus with environmental degradation and also not supported the EKC hypothesis in South Asian countries. These findings suggested that the regulators should develop policies that reduce environmental degradation in the presence of high EG, energy consumption, FDI, and population growth.

ELECTRICITY CONSUMPTION, TRADE OPENNESS AND ECONOMIC GROWTH IN DEVELOPING COUNTRIES: A DISAGGREGATED APPROACH

2021 ◽  
pp. 1-28
Author(s):  
KIZITO UYI EHIGIAMUSOE ◽  
SIKIRU JIMOH BABALOLA
Keyword(s):  
Economic Growth ◽  
Trade Openness ◽  
Electricity Consumption ◽  
Impulse Response Functions ◽  
African Countries ◽  
Cross Sectional ◽  
Long Run ◽  
Short Run ◽  
Cross Sectional Dependence ◽  
Trade And Growth

This study examines the relationship between electricity consumption, trade openness and economic growth in 25 African countries during 1980–2016. It disaggregates electricity into renewable and non-renewable and disaggregates trade into exports and imports. It employs cointegration and Granger causality techniques that enable us to determine both joint and individual causality, as well as account for individual heterogeneity and cross-sectional dependence. It also uses the variance decompositions (VDs) and impulse response functions (IRFs). This study shows a short-run and long-run joint causality from electricity and trade to growth, as well as a short-run and long-run joint causality from trade and growth to electricity. Besides, the Dumitrescu–Hurlin Granger non-causality technique shows a bidirectional causality between electricity and growth and between trade and growth but a unidirectional causality from electricity to trade. It also reveals the causal relationships from exports, imports, renewable and non-renewable electricity to growth. This study implies that electricity consumption and trade openness stimulate growth, while the latter also determines electricity consumption and trade openness. Based on the findings, we recommend some policy options.

scholarly journals Dynamic Panel Analysis under Cross-Sectional Dependence

2014 ◽  
Vol 22 (2) ◽  
pp. 258-273 ◽  
Author(s):  
Khusrav Gaibulloev ◽  
Todd Sandler ◽  
Donggyu Sul
Keyword(s):  
Economic Growth ◽  
International Political Economy ◽  
Panel Analysis ◽  
Dynamic Panel ◽  
Cross Sectional ◽  
Dynamic Panels ◽  
Cross Sectional Dependence ◽  
Dynamic Panel Regression ◽  
Dynamic Panel Analysis ◽  
The Impact

This article investigates inconsistency and invalid statistical inference that often characterize dynamic panel analysis in international political economy. These econometric concerns are tied to Nickell bias and cross-sectional dependence. First, we discuss how to avoid Nickell bias in dynamic panels. Second, we put forward factor-augmented dynamic panel regression as a means for addressing cross-sectional dependence. As a specific application, we use our methods for an analysis of the impact of terrorism on economic growth. Different terrorism variables are shown to have no influence on economic growth for five regional samples when Nickell bias and cross-dependence are taken into account. Our finding about terrorism and growth is contrary to the extant literature.

Oil exports and non-oil exports

2017 ◽  
Vol 44 (4) ◽  
pp. 540-551 ◽  
Author(s):  
Huseyin Karamelikli ◽  
Guray Akalin ◽  
Unal Arslan
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Dynamic Panel Data ◽  
Cross Sectional ◽  
Content Type ◽  
Oil Exports ◽  
Cross Sectional Dependence ◽  
The Cross ◽  
Opec Member ◽  
The Impact

Purpose The purpose of this paper is to examine the dynamic relationship between oil exports, non-oil exports, imports and economic growth in the Organization of Petroleum Exporting Countries (OPEC), covering the period 1972-2013 by using panel data analysis. Design/methodology/approach The results from the dynamic panel data methods are as follows: there exists the cross-sectional dependence on each variable. According to the cross-sectionally augmented panel unit root tests, all variables are stationary at the first difference. Westerlund and Edgerton (2007) LM Bootstrap cointegration test shows that there is a long-term relationship between variables. Findings The results obtained by the Common Correlated Effects (CCE) estimator indicate that the increase in oil exports has a positive impact on the GDP of all countries, while the increase in oil exports has a negative impact on the non-oil exports of some countries. Originality/value In this study, the relationship between oil exports, economic growth, imports and non-oil exports of the 12 OPEC member countries is tested by considering the cross-sectional dependence between 1972 and 2013. In the study, the authors found a positive relationship as a result of researching the impact of oil exports on economic growth in the frame of CCE panel estimations results.

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