How Does Trade Openness Affect Regional Demographic Transitions? Evidence from China's Provincial Panel Data

2017 ◽  
Vol 25 (3) ◽  
pp. 112-130
Author(s):  
Shujin Zhu ◽  
Renyu Li ◽  
Tenglong Zhong
Keyword(s):  
Panel Data ◽  
Trade Openness ◽  
Demographic Transitions

Determinants of Industrial Development

2021 ◽  
pp. 378-406
Author(s):  
Fiona Tregenna ◽  
Kevin Nell ◽  
Chris Callaghan
Keyword(s):  
Developing Countries ◽  
Human Capital ◽  
Exchange Rate ◽  
Panel Data ◽  
Industrial Development ◽  
Trade Openness ◽  
Developed Countries ◽  
Government Consumption ◽  
Capital Account Liberalization ◽  
Exchange Rate Depreciation

Global evidence suggests that, for many countries, manufacturing typically has an inverted U-shaped relationship with development. But unlike the historical experience of most developed countries, for most developing countries the turning point of this relationship is occurring sooner in the development process, and at substantially lower levels of income. This is termed ‘premature deindustrialization’. The consequences of this may be particularly important if such countries can no longer rely on manufacturing-led development. Why are some countries more industrialized, or more deindustrialized, than other comparable countries? To explore these issues, this chapter uses panel-data econometric techniques to analyse the determinants of the share of manufacturing in GDP, across countries and across time. Domestic determinants include investment, government consumption, population size, human capital, democracy, and natural resource endowments. External determinants include trade openness, capital account liberalization, and exchange rate depreciation.

Determinants of FDI in developed and developing countries: a quantitative analysis using GMM

2018 ◽  
Vol 45 (2) ◽  
pp. 348-382 ◽  
Author(s):  
Neha Saini ◽  
Monica Singhania
Keyword(s):  
Developing Countries ◽  
Panel Data ◽  
Multinational Corporations ◽  
Management Practices ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Trade Openness ◽  
Content Type ◽  
Generalized Moments ◽  
Determinants Of Fdi

PurposeThe purpose of this paper is to investigate the potential determinants of FDI, in developed and developing countries.Design/methodology/approachThis paper investigates FDI determinants based on panel data analysis using static and dynamic modeling for 20 countries (11 developed and 9 developing), over the period 2004-2013. For static model estimations, Hausman (1978) test indicates the applicability of fixed effect/random effect, while generalized moments of methods (GMM) (dynamic model) is used to capture endogeneity and unobserved heterogeneity.FindingsThe outcome across different countries depicts diverse results. In developed countries, FDI seeks policy-related determinants (GDP growth, trade openness, and freedom index), and in developing country FDI showed positive association for economic determinants (gross fixed capital formulation (GFCF), trade openness, and efficiency variables).Research limitations/implicationsThe destination of FDI is limited to 20 countries in the present paper. The indicator of the institutional environment, namely economic freedom index, used in this paper has received some criticism in calculations.Practical implicationsThe paper enlists recommendations for future FDI policies and may assist government in providing a tactical framework for skill development, thereby increasing manufacturing growth rate. The paper also throws light on vertical and horizontal capital inflows considering resource, strategy, and market-seeking FDI.Social implicationsFDI may bring significant benefits by creating high-quality jobs, introducing modern production and management practices. It highlights how multinational corporations and government contribute to better working conditions in host countries.Originality/valueThe paper uncovers important features like macroeconomic variables, especially country-wise efficiency scores, policy variables, GFCF, and freedom index, for determining FDI inflows in 20 countries using panel data methods and provides a roadmap for developed and developing countries. The study highlights endogeneity and unobserved heteroscedasticity by applying GMM one- and two-step procedure.

scholarly journals Worldwide Tax Revenue Collection: Lessons from Pre-Pandemic Era

2020 ◽  
Vol 4 (3) ◽  
pp. 183-194
Author(s):  
Ahmad Zaky Zamani
Keyword(s):  
Panel Data ◽  
Trade Openness ◽  
Fixed Effect ◽  
Institutional Factors ◽  
Tax Revenue ◽  
Key Factors ◽  
Tax Collection ◽  
System Gmm ◽  
Revenue Collection ◽  
The World

Despite the fact that majority of countries in the world rely heavily on tax revenue, there is a vast difference in terms of tax collection performance. This study reassessed several structural, economic, demographic and institutional factors that potentially explain the variation. We employ pooled OLS, fixed effect and system GMM estimations to analyze a panel data of 161 countries for 15 years spanning from 2002 to 2017. Our findings confirmed that level of development and investment are among key factors that leads to revenue improvement. It is very likely that such a relationship has two-way directions. Other factors such as trade openness, inflation, share of agriculture and national resources in the economy, population, and governance, cannot be downplayed despite its mixed inferences.

scholarly journals ANALISIS INVESTASI ASING LANGSUNG (FDI) DI NEGARA ASEAN TAHUN 2000-2017

2019 ◽  
Vol 3 (3) ◽  
pp. 397-409
Author(s):  
Futuhatul Barorah ◽  
Nazaruddin Malik ◽  
Zainal Arifin
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Interest Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Direct Investment ◽  
Trade Openness ◽  
Analytical Tool ◽  
Gdp Growth ◽  
Testing Hypotheses

The aim of this research is nalyze foreign direct investment (FDI) from 2000 to 2017. The analytical tool used was multiple linear regression with panel data method by testing hypotheses namely F test, t-test, and Determination Coefficient R2. The software used in the analysis of this study was Eviews 9. The finding of the study denotes that all of influence of GDP growth, Trade Openness, Interest Rate and Inflation gave influence toward on Foreign Direct Invesment with a probability value of 0,0000. While individually, The country of Myanmar has the highest intercept inversely proportional to Malaysia which has the smallest intercept. While individually GDP growth and Trade Openness has a positive and significant effect on Foreugn Direct Invesment, Interest Rate and inflation has a negative and significant effect on Forign Direct Invesment.

Sign in / Sign up

Export Citation Format

Share Document