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Spatial Effects' Robustness for Key Macroeconomic Indicators of Russian Federation

Student: Shibneva Ekaterina

Supervisor: Olga Demidova

Faculty: Faculty of Economic Sciences

Educational Programme: Master

Year of Graduation: 2014

<p>The purpose of this study is to examine the features of the influence of Moscow and the Moscow region on other regions of the Russian Federation. Several econometric models with the inclusion of spatial effects (with the inclusion of Moscow and Moscow Region and without inclusion) were conducted for this evaluation for the main macroeconomic indicators of the Russian regions (the unemployment rate, the real wage index GRP). The study was conducted on panel data for Russian regions for the 2000-2012. unemployment rates, real wage index and GRP were estimated using different spatial models and two weighting matrices. A special spatial influence of Moscow and the Moscow region on neighboring regions was found out by considering the coefficient estimates of indirect effects of spatial models for Durbin static and dynamic cases. A comparison of three cases: in one of them, the model includes data for Moscow and the Moscow region and it was used for the evaluation with the help of weight matrix that takes into account the neighborhood of Moscow with other regions. In the second case, &nbsp;a new evaluation matrix was proposed, which assumed no &quot;neighborhood&quot; of Moscow and Moscow Region with other regions. In the third case Moscow and Moscow Region are completely excluded from the evaluation. Then, the comparison of coefficients was conducted using ratios of direct and indirect effects for separation regions&#39; influence on each other. The estimation results of the coefficients for all three models are consistent with previous studies. The special influence of Moscow and Moscow Region on the spatial effects and its significance in the evaluation of the main macroeconomic parameters was reviewed in this study. In evaluating spatial models consistency in the signs and significance of the coefficient estimates is often observed. However, for some factors (the proportion of specialists with higher education, population density, urban population, the level of air pollution) inclusion and exclusion of Moscow and Moscow region affected the significance of the coefficients. The most considerable differences can be observed in estimating real wages. Thus, the inclusion and exclusion of Moscow and Moscow region affects the estimation of the models with the inclusion of spatial effects for macroeconomic indicators of the Russian Federation, and the feasibility and correctness of the inclusion and exclusion must be assessed for each individual dependent variable and used model.</p>

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