Identifying reduced-form relations with panel data: The case of pollution and income

2009 ◽  
Vol 58 (1) ◽  
pp. 27-42 ◽  
Author(s):  
Herman R.J. Vollebergh ◽  
Bertrand Melenberg ◽  
Elbert Dijkgraaf
Keyword(s):  
2021 ◽  
Author(s):  
Ekaterina Dmitrievna Myagotina ◽  
Ilona Vladimirovna Tregub

Nowadays analysis of various econometric models is used to study a significant amount of updated statistical information and find out relationships between statistical economic indicators, that were not investigated earlier. Main idea of investigation in this research work — to find out whether factors influence on the GRP, Consumption, Profit of the organizations and Investments or the model is outdated and non-applicable nowadays. The results obtained in the framework of this research will give us understanding changing which factors (exogeneous variables) — for example, increasing or decreasing credit and deposit rates, tax rates will rise national income, consumer expenditure, investment and operating surplus and, as a result, will accelerate economic development of the Russian Federation. The purpose is to evaluate whether the Menges model which includes all the indicators mentioned as dependent variables is applicable in the modern conditions of the Central Federal District in Russia or not and to find out whether there are other factors which also have an impact on endogenous variables. The object — a set of the panel data of economic statistical information of the Central Federal District in Russia (2008–2013). The subject — the reduced form of Menges model including GRP, Consumption, Profit of the organizations and Net Investments. According to our research, it is reasonable enough to increase the volume of industrial production in order to increase GRP both economically and with the help of the Menges econometric model. Besides that, it is also reasonable to increase the volume of industrial production in order to get a higher cost of investment.


Author(s):  
Herman R.J. Vollebergh ◽  
Elbert Dijkgraaf ◽  
Bertrand Melenberg
Keyword(s):  

2018 ◽  
Vol 11 (2) ◽  
pp. 79-91
Author(s):  
Arya Fendha Ibnu Shina

Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data.  Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations


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.


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