Analysis of Labor Force Participation Rate in Riau Province: A Spatial Autoregressive Approach

The labor force participation rate (LFPR) is one of the important indicators for measuring the participation of the labor force involved in economic activities. In Riau Province, LFPR has exceeded half the population, resulting in increasingly tight job competition. This research aims to model the factors influencing LFPR in Riau Province in 2021 using the Spatial Autoregressive Model (SAR). Based on the Moran Index, there is positive spatial autocorrelation in LFPR, while based on the Lagrange Multiplier test, the SAR model is appropriate to use because of the lag dependence on the dependent variable. SAR analysis shows that the non-labor force variables (????1), poverty line (????2), productive age population (15-64 years) (????3), and population growth rate (????4) have a significant positive influence on LFPR. In contrast, the type ratio variable gender (????5) has a negative influence. Apart from that, a lag coefficient of 0.4935 was obtained, which means that if the value of the LFPR figure in a region increases by 1 unit, it will increase by 0.4935 times the average LFPR in neighboring areas of the region. This highlights the need for policies aimed at increasing the LFPR to account for regional coordination, as changes in one area's LFPR can influence adjacent regions. Consequently, the Riau Provincial Government should promote collaboration among districts and cities to formulate a cohesive strategy, while each district should design policies that align with their unique local characteristics and the spatial dynamics of surrounding areas.

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Publication Details

Journal
Jurnal Ketenagakerjaan
Published
2024-12-31
DOI
https://doi.org/10.47198/jnaker.v19i3.345
Primary Topic
Economic Growth and Fiscal Policies
Type
article
Field-Weighted Citation Impact
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article

Analysis of Labor Force Participation Rate in Riau Province: A Spatial Autoregressive Approach

Gustriza Erda, Arisman Adnan, Tesa Theresia Sirait
Jurnal Ketenagakerjaan
Economic Growth and Fiscal Policies
article

Analysis of Labor Force Participation Rate in Riau Province: A Spatial Autoregressive Approach

Gustriza Erda, Arisman Adnan, Tesa Theresia Sirait
article en

Abstract

The labor force participation rate (LFPR) is one of the important indicators for measuring the participation of the labor force involved in economic activities. In Riau Province, LFPR has exceeded half the population, resulting in increasingly tight job competition. This research aims to model the factors influencing LFPR in Riau Province in 2021 using the Spatial Autoregressive Model (SAR). Based on the Moran Index, there is positive spatial autocorrelation in LFPR, while based on the Lagrange Multiplier test, the SAR model is appropriate to use because of the lag dependence on the dependent variable. SAR analysis shows that the non-labor force variables (????1), poverty line (????2), productive age population (15-64 years) (????3), and population growth rate (????4) have a significant positive influence on LFPR. In contrast, the type ratio variable gender (????5) has a negative influence. Apart from that, a lag coefficient of 0.4935 was obtained, which means that if the value of the LFPR figure in a region increases by 1 unit, it will increase by 0.4935 times the average LFPR in neighboring areas of the region. This highlights the need for policies aimed at increasing the LFPR to account for regional coordination, as changes in one area's LFPR can influence adjacent regions. Consequently, the Riau Provincial Government should promote collaboration among districts and cities to formulate a cohesive strategy, while each district should design policies that align with their unique local characteristics and the spatial dynamics of surrounding areas.

Jurnal KetenagakerjaanVol. 19(3)
Riau University (ID)
Universitas Riau
Openalex Percentile: Top 68%
Economic Growth and Fiscal Policies
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Analysis of Labor Force Participation Rate in Riau Province: A Spatial Autoregressive Approach — Gustriza Erda, Arisman Adnan, et al. · Jurnal Ketenagakerjaan (2024) | TGRS Research Map | TGRS