scholarly journals Generalized Moments Estimation for Panel Data

10.3386/t0291 ◽  
2003 ◽  
Author(s):  
Viliam Druska ◽  
William Horrace
2018 ◽  
Vol 45 (2) ◽  
pp. 348-382 ◽  
Author(s):  
Neha Saini ◽  
Monica Singhania

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.


2019 ◽  
pp. 46-64 ◽  
Author(s):  
Vladimir V. Klimanov ◽  
Sofiya М. Kazakova ◽  
Anna A. Mikhaylova

The article examines the impact of various socio-economic and financial indicators on the resilience of Russian regions. For each region, the integral index of resilience is calculated, and its correlation dependence with the selected indicators is revealed. The study confirms the relationship between fiscal resilience and socio-economic resilience of the regions. The analysis of panel data for 75 regions from 2007 to 2016 shows that there are significant differences in the dynamics of indicators in different periods. In particular, the degree of exposure to the negative effects of the crises of 2008—2009 and 2014—2015 in non-resilient regions is higher than in resilient ones.


Author(s):  
Hoi Le Quoc ◽  
Hoi Chu Minh

Financial development could exert various effects on income distribution of a country. By employing Generalized Method of Moment, this paper aims at examining the impacts of credit market depth, one of most used financial development barometers, on income inequality in Vietnam. The empirical findings show that expanding credit market in the country could lead to higher income inequality. We have not found evidence that supports the hypothesis of an inverted U-shaped relation ever introduced by Greenwood and Jovanovich, although this hypothesis may still hold in a sense that Vietnam has not reached to the inflection point to generate such a curve alike.


2018 ◽  
Vol 18 (5) ◽  

This study examines whether board diversity affects firm performance. We investigate this study using panel data of a sample of S&P 500 firms during a 12 year period. After controlling for industry, firm size, and other board composition variables, we find that all three board diversity variables of interest – gender, ethnicity, and age have a significant influence on firm performance. While ethnicity and age have a positive influence on firm performance, it was found that gender has a negative influence. Implications for future research are discussed.


Sign in / Sign up

Export Citation Format

Share Document