HUMAN RESOURCE FORECASTING MODELS

Madalina-Gabriela Anghel, Constantin Anghelache, Georgiana Nita and Tudor Samson
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Madalina-Gabriela Anghel: „Artifex" University of Bucharest
Constantin Anghelache: Bucharest University of Economic Studies/„Artifex" University of Bucharest
Georgiana Nita: Bucharest University of Economic Studies
Tudor Samson: Bucharest University of Economic Studies

Romanian Statistical Review Supplement, 2017, vol. 65, issue 4, 87-98

Abstract: In this article the authors have proposed to study the effect they have human resources on economic growth. Any forecast on GDP growth, factor in achieving economic growth must also focus on analyzing the ratio population / economy. Of course, the population is the main source of the active population in employment and in the end the number of employees. In this article the authors focused on identifying the main models used in forecasting human resources. n this respect, the widely used modern theory of economic growth, then demo-economic models of economic growth, focusing on the R.F. Harrod model, R.M. Solow model, L. Stoleru model or J. J. Spengler modelul. All these enable interpretation and then analyzing and then adapting to forecast labor resources. Further emphasis on identifying elements that underlie the comprehensive design of population trends by extrapolating the total number of people directly based on observed statistically term trend. Used statistical quantities such as average rate of growth and finally using polynomial function that provides an increase in these resources. Summarizing the above mentioned here, the authors also focuses on the role that occupies projection of the number of households, households, the number of families, etc., so as to give a clearer idea of the prospects reaalizãrii growth of labor resources. Finally, it has a structure based on labor resources that can be identified structural events underlying this analysis.

Keywords: forecasting; human resources; population; demographic model; demoeconomic (search for similar items in EconPapers)
Date: 2017
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