Using Nonlinear Multiple Regression Models to Assess the Impact of Labor Resources and Employment on the Gross Regional Product

Abstract

The main indicator that determines the level of economic development of the region is the gross regional product (GRP). Differences in the key resources that determine its dynamics determine the features of the gross regional product of a particular territory. The most complex of the studied relationships, on which researchers have not yet formed a common opinion, is the relationship between population growth and growth in the volume of public product (C.A. Taylor, M. Madden [1], P. Batey [2], D.E. Bloom, R.B. Freeman [3], K. Prettner, A. Prskawetz [4] and other). In this regard, the task is to isolate the degree of influence of employment and other labor factors in the total set of socio-economic factors studied on the gross regional product of a particular region - the Lipetsk region. The impact assessment was carried out through the construction of nonlinear GRP dependencies based on the application of step-by-step algorithms for including significant variables. The need to use nonlinear multiple regression models is due to the fact that in the previously constructed linear models, there is no significant relationship between the dynamics of the working population of the Lipetsk region and the regional product. The results obtained in this study allow us to supplement the hierarchy of multi-factor models of the dependence of the Lipetsk region's GRP on socio-economic factors [5]; [6]. The use of mathematical modeling tools will make it possible to make more informed management decisions when forecasting regional economic systems.