The article analyses balance between the capital and labor market in the CIS countries rich in hydrocarbon resources -Azerbaijan, Kazakhstan and Russia. For this purpose, the impact of capital (fixed assets) and labor (employed population) on the production volume (on GDP) was estimated based on the relevant statistical data from these countries using production function analysis. The parameters of CES production function were determined in the Mathcad system by the nonlinear least-squares method. The subject of the research has enhanced relevance due to the lack of extensive research of the problem posed in the oil and gas-rich countries of the CIS, and the research evaluates the balance between capital and labor markets for the first time in resource-abundant countries. From the results, it can be seen that for each of these three countries the distribution coefficient for capital is significantly higher than that for the labor factor. This means that there is an excess of capital that cannot be started. This is typical for the countries rich in natural resources. The main reason for this process is the complex structure of increasing capital with oil revenues and low level of specialization of the existing labor force to launch this capital. Moreover, according to the results obtained from the CES production function, the substitute elasticity coefficient in oil-rich countries of the CIS is less than one. The study summarizes the current problem as an imbalance between the capital (fixed assets created using modern technology) and the labor market (labor to leverage key assets using potential opportunities). Based on the analysis, the results obtained from modeling is formulated and scientifically grounded recommendations have been provided for the improvement of education and its quality in these three countries, especially in Russia and Azerbaijan.
The present study proposes an alternative explanation for the negative natural-resource-growth nexus. Based on the theoretical analysis, the study shows that a balanced capital–labor ratio plays an essential role in the absorption of complex capital goods. It estimates the parameters of the constant elasticity of the substitution production function in Mathcad using nonlinear least squares, i.e., an approximate Marquardt method of optimization. The empirical analysis is based on the time-series data of these countries for the time interval between 2000 and 2020. We conducted analyses by calculating the elasticity of substitution between capital and labor. Specifically, for these countries, the elasticity of substitution of capital and labor appeared to be less than one, which indicates a lack of labor, or, more precisely, a qualified labor force. Each of these countries receives windfall profits from the exploitation of natural resources, which greatly influences the import of capital-intensive products of complex technologies—in other words, the import of capital. However, the lack of an adequate labor force that could utilize the increased capital led to a decrease in the elasticity of capital and labor substitution. A comparison of the optimal and the observed capital–labor ratio coefficient shows that this coefficient is significantly higher than optimal in all three countries. Therefore, while keeping the wage fund in balance with fixed capital costs, investments in the knowledge economy and human capital appear to be the preferred areas for the efficient allocation of oil revenues.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.