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National Interests: Priorities and Security
 

Building the model for predicting the region’s staffing needs through the Cobb–Douglas production function

Vol. 14, Iss. 2, FEBRUARY 2018

PDF  Article PDF Version

Received: 5 October 2017

Received in revised form: 26 October 2017

Accepted: 13 November 2017

Available online: 15 February 2018

Subject Heading: SUSTAINABLE DEVELOPMENT OF ECONOMY

JEL Classification: C03, Ñ33, O18, R58

Pages: 253–268

https://doi.org/10.24891/ni.14.2.253

Pakhomova E.A. Dubna State University, Dubna, Moscow Oblast, Russian Federation
uni-dubna@mail.ru

ORCID id: not available

Pisareva D.A. Administration of Dubna, Dubna, Moscow Oblast, Russian Federation
pisarevada@mail.ru

ORCID id: not available

Kharcheva K.S. Dubna State University, Dubna, Moscow Oblast, Russian Federation
kharcheva562@gmail.com

ORCID id: not available

Importance The article proposes the model for predicting staffing needs of municipal districts in the Moscow Oblast through economic and mathematical modeling and some programming techniques.
Objectives The research analyzes staffing needs of municipal districts of the Moscow Oblast.
Methods The proposed methodology for a staffing needs analysis follows our research into staffing needs and distribution of human resources among regions and sectors in order to determine whether staffing needs can be forecasted regionally for ensuring the competitiveness of the national economy and increasing living standards. Inputs are processed using methods of norm setting, deflation, assessment of integral indicators in five modifications. We also apply the Cobb–Douglas functions, classical method of least squares, non-linear unconstrained optimization and Levenberg–Marquardt algorithm.
Results Using MS Excel, STATISTICA 12, Wolfram Mathematica 11, we set regression models of the Cobb–Douglas functions. We selected the correlations, which adequately approximate empirical material to quality criteria. The Cobb–Douglas classical function with restricted specification parameters is not suitable for describing the Russian non?stationary economy. However, a modified function can be constructed.
Conclusions and Relevance The progress of the analysis may underlie the formation of the techniques for predicting the region’s staffing needs. The research materials may be used by public authorities to analyze and forecast regional labor markets and plan educational institutions’ activities.

Keywords: region, staffing needs, production function, modeling, forecasting

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