UNEMPLOYMENT RATE ESTIMATION IN BALI PROVINCE: A SMALL AREA ESTIMATION APPROACH

  • I Komang Gde Sukarsa Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University
  • G. K. Gandhiadi Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University
  • I Putu Eka Nila Kencana Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University
Keywords: empirical best linear unbiased prediction, small area estimation, unemployment

Abstract

Good development and economic growth increase the opportunities for people in the related areas to become more prosperous so that they can become a benchmark for the country's economy. One way that can be used to measure the level of development and economic growth is through microeconomic indicators such as the unemployment rate. Detailed information on the unemployment rate will certainly be a good consideration in the formation of economic policy. The development of estimation methods up to a very small area is very well used to estimate a parameter in a small area where there is not an adequate sample for use in direct estimation. This study discusses the unemployment rate at the sub-district level in Bali Province in 2020 with the result that estimating a small area using the empirical best linear unbiased prediction method gives a smaller mean square error value than the direct estimation method. The results obtained are that East Denpasar District has the largest unemployment rate of 8.49%.

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Published
2022-03-21
How to Cite
[1]
I. K. Sukarsa, G. K. Gandhiadi, and I. P. E. Kencana, “UNEMPLOYMENT RATE ESTIMATION IN BALI PROVINCE: A SMALL AREA ESTIMATION APPROACH”, BAREKENG: J. Math. & App., vol. 16, no. 1, pp. 157-162, Mar. 2022.