ESTIMATING EMPLOYMENT STATUS OF POPULATION USING INDIRECT METHOD IN KABBA, KOGI STATE

Fashagba Irewolede () and Yusuf, I.
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Fashagba Irewolede: Department of Geography and Environmental Management, Postal: University of Ilorin, Ilorin, https://fssunilorinedu.org/ijbss/index.php
Yusuf, I.: Department of Geography, Postal: Kwara State Polytechnic, Ilorin, Nigeria, https://fssunilorinedu.org/ijbss/index.php

Ilorin Journal of Business and Social Sciences, 2016, vol. 18, issue 1, 100-114

Abstract: Unemployment rate has been on the increase in Nigeria. In 1999, unemployment rate was 8.2%. This rose to 12.6% in 2002, but later declined to 11.5% in 2005. By 2007, the rate rose to 13.1% and further to about 23.9% in 2014. The rate thus appears to have been increasing. Unfortunately, census, the primary source of the population data which can be used to determine the unemployment rate has been carried out infrequently in Nigeria. Thus, the data used in estimating the unemployment rate would appear a mere guess. This study seeks to develop a model for estimating the unemployed population using Kabba as a case study. Primary and secondary data were used for the study. Four hundred and eleven copies of a questionnaire which accounted for about 10% of the household heads was administered using systematic sampling technique. The primary data and the 2014 immunization data of Kabba were analysed using descriptive and inferential statistics. The primary and secondary data were regressed to establish a relationship. Two models; (i) Y=-0455+307x; and (ii) Y=80.627+601x were developed and used to estimate the unemployed and under-employed populations, respectively. When the average number of unemployed and under-employed persons per quarter was multiplied by the total number of houses in the quarter, the unemployed and underemployed populations of Kabba were 1,034 and 3,642, respectively. Using the first model, Kogi State 2014 estimated unemployed population was put at 43,044. With the second model, the estimated under-employed population for the state was 86,387.The study thus recommended that these models are good to estimate the unemployment population.

Keywords: Population; Unemployment; Under-employment; Model and Estimate (search for similar items in EconPapers)
Date: 2016
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