scholarly journals Research on Interaction Mechanism Between China’s Manufacture NVC and “Belt & Road Initiative “ RVC – Based on Simultaneous Equation Model

2020 ◽  
Author(s):  
Nina Zhu ◽  
Yingqiao Qin
Keyword(s):  
Interaction Mechanism ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Simultaneous Equation Model

Remittances, Economic Growth and Poverty: A Case of African OIC Member Countries

2018 ◽  
Vol 57 (2) ◽  
pp. 121-143
Author(s):  
Nasim Shah Shirazi ◽  
Sajid Amin Javed ◽  
Dawood Ashraf
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Poverty Reduction ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Annual Data ◽  
Simultaneous Equation Model ◽  
African Countries ◽  
Alternative Source ◽  
The Impact

This paper investigates the impact of remittance inflows on economic growth and poverty reduction for seven African countries using annual data from 1992-2010. By using the depth of hunger as a proxy for poverty in a Simultaneous Equation Model (SEM), we find that remittances have statistically significant growth enhancing and poverty reducing impact. Drawing on our estimates, we conclude that financial development level significantly increases the remittances inflows and strengthens poverty alleviating impact of remittances. Results of our study further show a signficant interactive imapct of remittances and finacial develpment on economic growth, suggesting the substitutability between remittance inflows and financial development. We further find that 3 percentage point increase in credit provision to the private sector (financial development) can help eliminate the severe depth of hunger in the region. Remittances, serving an alternative source of private credit, can be effective in this regard. Keywords: Remittance Inflow, Poverty Alleviation, Financial Development, Simultaneous Equation Model

Estimation of Cointegration Vectors with Linear Restrictions

1993 ◽  
Vol 9 (1) ◽  
pp. 19-35 ◽  
Author(s):  
Pentti Saikkonen
Keyword(s):  
Generalized Least Squares ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Asymptotic Distributions ◽  
Reduced Form ◽  
Simultaneous Equation Model ◽  
Test Procedures ◽  
Rank Condition ◽  
Efficient System ◽  
Linear Restrictions

A general approach for the estimation of cointegration vectors with linear restrictions is described. In the special case of zero restrictions, the cointegration relations of the paper are formally similar to the structural form of a traditional simultaneous equation model. The proposed estimation procedures require a conventional rank condition of identification but no exogeneity assumption. In place of exogenous variables there are series that are not cointegrated and can therefore describe the common trends in the system. The estimators of the paper are flexible and simple to use. They can be combined with several recent estimators developed for cointegration regressions which in the present context are formally similar to the reduced form of a simultaneous equation model. After the coefficient matrix of a cointegration regression has been estimated, the estimators of the paper can be obtained by simple generalized least squares. Both single equation estimators and more efficient system estimators are developed. The asymptotic distributions of the estimators are shown to be mixed normal so that Wald tests with asymptotic chi-square distributions under the null hypothesis can be obtained in the usual way. Convenient test procedures for checking the validity of overidentification restrictions are also provided.

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