{"title":"SPATIAL DURBIN MODEL OF UNEMPLOYMENT RATE IN CENTRAL JAVA","authors":"F. Fauzi, G. H. Wenur, R. Wasono","doi":"10.22487/27765660.2023.v3.i1.16423","DOIUrl":null,"url":null,"abstract":"Unemployment is a labor problem that is often faced by developing countries like Indonesia. The number of unemployed in Indonesia has fluctuated from year to year, including in Central Java Province. One of the efforts made to overcome this problem is to know the factors that influence unemployment. The region effect greatly affects the open unemployment rate. Modeling involving area effects is very precise, one of which is the Spatial Durbin Model (SDM). In this study, modeling of the open unemployment rate was carried out using a spatial approach in each district/city in Central Java. The models used in this study are Ordinary Last Square (OLS), Spatial Auto Regressive (SAR), Spatial Error Models (SEM), Spatial Durbin Model (SDM), Spatial Error Durbin Model (SDEM). The five methods were evaluated using the Akaike Information Criteria (AIC). The spatial weighting used in this study is Queen Contiguity. Based on the smallest AIC value (115.42), the best method in this study is HR. Meanwhile, the significant factors are the percentage of labor force participation rate (X1), the number of poor people (X4), the lag of economic growth, the lag of poverty, and the lag of the district/city minimum wage","PeriodicalId":337689,"journal":{"name":"Parameter: Journal of Statistics","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parameter: Journal of Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22487/27765660.2023.v3.i1.16423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Unemployment is a labor problem that is often faced by developing countries like Indonesia. The number of unemployed in Indonesia has fluctuated from year to year, including in Central Java Province. One of the efforts made to overcome this problem is to know the factors that influence unemployment. The region effect greatly affects the open unemployment rate. Modeling involving area effects is very precise, one of which is the Spatial Durbin Model (SDM). In this study, modeling of the open unemployment rate was carried out using a spatial approach in each district/city in Central Java. The models used in this study are Ordinary Last Square (OLS), Spatial Auto Regressive (SAR), Spatial Error Models (SEM), Spatial Durbin Model (SDM), Spatial Error Durbin Model (SDEM). The five methods were evaluated using the Akaike Information Criteria (AIC). The spatial weighting used in this study is Queen Contiguity. Based on the smallest AIC value (115.42), the best method in this study is HR. Meanwhile, the significant factors are the percentage of labor force participation rate (X1), the number of poor people (X4), the lag of economic growth, the lag of poverty, and the lag of the district/city minimum wage
失业是印尼等发展中国家经常面临的劳工问题。印度尼西亚的失业人数每年都在波动,中爪哇省也是如此。为克服这一问题所作的努力之一是了解影响失业的因素。区域效应极大地影响了公开失业率。涉及区域效应的建模是非常精确的,其中之一是空间杜宾模型(SDM)。在本研究中,采用空间方法对中爪哇每个地区/城市的公开失业率进行了建模。本研究使用的模型有:普通末方(OLS)、空间自动回归(SAR)、空间误差模型(SEM)、空间杜宾模型(SDM)、空间误差杜宾模型(SDEM)。采用赤池信息标准(Akaike Information Criteria, AIC)对5种方法进行评价。本研究中使用的空间加权是皇后连续度。基于AIC最小值(115.42),本研究的最佳方法是HR。同时,显著性因素为劳动力参与率百分比(X1)、贫困人口数量(X4)、经济增长的滞后性、贫困人口的滞后性、区/市最低工资的滞后性