Observed and unobserved regional determinants of FDI inflows : micro level analysis of the food industry firms in Russia

Observed and unobserved regional determinants of FDI inflows: micro level analysis of the food industry firms in Russia The development of Russian food industry is strategically important. Theoretically, the foreign capital inflow will help to renovate, modernize it and increase the productivity. But is it also interesting for foreign investors? What do foreign companies take into account when they invest in Russian food industry enterprises? Could it be special aspects of regional development (observed or unobserved) or only firm level data matters? Does the institutional environment in Russian regions significantly stimulate the inflow of foreign direct investment in Russian food industry enterprises or is the investor interested only in the size of a market? Two samples for 2009 and 2012 years of correspondingly about 5000 and about 7000 food industry companies of different subindustries from different Russian regions are analyzed to give the answer to these questions. The main idea of this investigation is to determine significant regional factors which effect the distribution of the FDI or to show that these items are not important for foreign investors. Russia has more than 80 regions and all of them are highly heterogeneous in terms of climate, geographical characteristics, level of economic and institutional development, industrial specialization, etc. Moreover, enterprises of different industries and subindustrues are different. In this research we take into account these facts investigating a hierarchical structure of the FDI distribution levels. This research consists of several parts: the theoretical part with hypotheses and the overview of the background and the empirical part with testing whether different regional characteristics like the infrastructure, taxation and the regulations in the region and in the neighboring ones play an important role. Spatial effects of these factors and of the economic development are also of our interest. The estimation of a multilevel binary model with spatial effects of analyzed factors gives the idea for the possible solution on the problem discovered above. The comparison of the results for two samples for different years and the investigation of dynamics also are taken into consideration.