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The additional explanatory variable that is going to be included in the extended core model is also assumed to have a certain effect on the regional output. This variable, structure of the regional economies, is sometimes believed to be a contributing factor by some regional economic researchers, like Bliend and Wolf (Uwe Blien, 2001) or Cziraky et all (Dario Cziraky, 2004). The economic structure can explain the regional disparity through the differences in kinds of activities common for each locality. Different types of economic activities bring different returns as well as require different human capital, which affects the regional productivity. In more developed urban parts with higher output per capita the share of employment in agriculture is typically less than that in the less developed areas. If this assumption finds support in the model, it can have important implications for the regional policy of the country.
The effect of the explanatory variables on average real wage per region, which is estimated in the supplementary model, is very similar to their effect on regional output per capita. The reason why I am including the supplementary model is to check if the regional policy program has any effect on the real wage in the regions. The increase in production per capita is expected to be highly correlated with an increase in the regional average earnings. Nevertheless, the production per capita is more relevant to the current study since it reflects exactly the production on regional level, and, thus, is selected for the core model.
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the committee, the data is taken for each region/city, which increases the number of observations used to estimate the model.
As explained before, some areas do not get any investments due to occupation by Armenia; and, due to the absence of variation in explanatory variables, they are excluded from the analysis. The areas that get investments from the country, even if in a small amount, are still considered by the quantitative analysis. The number of regions and/or cities contained in each economic region can be seen in Table 6, whereas more a detailed description of regions can be seen in Appendix 1.
Table 6 Economic regions breakdown
Economic region
Number of areas in the region
Number of included areas
Number of excluded areas
1 Baku city 1 1 0
2 Absheron 3 3 0
3 Ganja-Gazakh 11 11 0
4 Shaki-Zagatal 6 6 0
5 Lankaran 6 6 0
6 Guba-Khachmaz 5 5 0
7 Aran 18 18 0
8
Yukhari
Qarabagh 7 7 0
9 Kalbajar-Lachin 4 1 3
10 Dakhlikh Shirvan 4 4 0
11 Nakhchivan 8 1 7
Total 73 63 10
Source: Author’s own work
For the core model with the regional productivity as an explained variable, the database used for the estimation contains the panel data for 63 regions with yearly observations for the time period of 6 year from 2006 to 2011 (N=63, T=6, NT=378). For the supplementary model
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with the regional real wage as an explained variable, the number of regions remains unchanged and time span is extended to 7 years from 2005 until 2011 (N=63, T=7, NT=441).
The yearly data on output per capita for each region, large and medium investments per region, and small investments per region, are taken from the AzStat. The dependent variables, the regional output per capita (out_pc) and the average real wage per region (rwage), are measured in the current prices in local currency, manats.
In order to calculate the real wage, the nominal wage was taken from the AzStat and then adjusted to the inflation. The yearly data for inflation is taken from the International Monetary Fund database. Inflation is an average yearly consumer price index change, measured in percentage. The base year is 20043.
The large and medium construction investments per region (inv_lm) show the large and medium investments in fixed capital made by both public and private sector, and small construction investments per region (inv_s) show the same about the small investments in fixed capital. All investments in fixed capital are measured in thousands manats. The yearly amounts of discounted loans provided for each region in previous year (dloans_1) are not available in the annual reports of the NFES available for the general public. In those reports the data is grouped by the economic regions without their further breakdown. Nevertheless, for the current research the NFES exclusively provided the breakdown of statistical information. The discounted loans in database are measured is thousands manats.
3 The real wage is equal to the nominal wage divided to the inflation change from the base level.
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The last variable, structure (struc), is the ratio of the employees working in agricultural sector to the total number of employees for each region. The ratio is converted into percentage.
The data is calculated by the author, but the initial values are taken from the AzStat.
To summarize the description of the data, it is worth looking at the way it is distributed as it can be used in the interpretation of the findings. The large and medium regional investments, directed to construction, have an average level of 113.9 million manats per year. The average amount of regional small investments constitutes 6.8 million manats per year, and the average value of the provided discounted loans is 1.4 million manats per year. The same values change significantly if we calculate them without the capital city, Baku. In this case, the average of regional large and medium investments reduces to 26.4 million manats, the average of regional small investments makes up 3.8 million manats, and the average of provided discounted loans for regions is 1 million manats. From the aforementioned it can be concluded that, on average, 80%
of the discounted loans are distributed across the regions, which is not the case for other types of investments. In the case of large and medium investments, 76% falls on Baku, and in the case of small investments, 43% is directed to Baku.