Mathematical processing of sampling inquiry data to form and forecast the age and gender number of employed people

Aim . The work aimed to develop the methods for calculating the age and gender number of employed people among the region’s population by annual age categories based on the indicators of sampling inquiry of the labor force. Objectives . The work seeks to analyze the initial data on the number of employed people among the permanent population by one-year and ten-year age categories, available in federal and departmental statistics; to develop and test methods for obtaining a profile of employed people in terms of one-year age and gender categories based on scaling the employment profile of workers and based on smoothing the indicators of a sampling inquiry of the labor force; to evaluate the capabilities of the results of modeling the age and gender number of employed people in terms of one-year age and gender categories using two methods (scaling and smoothing) to calculate the total and replacement staffing requirements. Methods . The study employed the method of scaling the profile of the number of employees and the method of smoothing the microdata of sampling inquiry of the labor force. Results. The authors developed two methods for reconstructing the annual number of employed people taking into account the age and gender structure based on the indicators of sampling inquiry of the labor force. For the Republic of Karelia, the number of employed people by annual age categories was calculated using scaling and smoothing methods. The results of calculating the number of employed people by annual age categories were compared using different methods. The number of retired employees and the attrition rate were calculated. Conclusions . The reconstructed indicators of the age and gender profile of employed people in terms of annual age categories were used to obtain the characteristics of the workforce with distribution by gender and age, as well as to track the dynamics of changes in the number of employed people in different age cohorts. The reconstructed indicators of the number of employed people in terms of annual age categories cannot be used to calculate correctly the outflow of employed people in older age categories and thereby determine the natural age attrition rates. In this regard, it is required to refine the mathematical model for reconstructing the indicators of the number of employed people in terms of annual age categories.