{"title":"动态多元空间有序概率模型的贝叶斯分析","authors":"P. Gao, Zixiang Lu","doi":"10.1080/17421772.2023.2181384","DOIUrl":null,"url":null,"abstract":"ABSTRACT Spatial econometrics has few studies on multivariate ordinal responses. This study proposes a dynamic multivariate spatial ordered probit (DMSOP) model, which is the first attempt to capture temporal and spatial dependencies simultaneously for multivariate ordinal responses. The parameters are calculated using Bayesian inference based on Markov chain Monte Carlo sampling. The DMSOP model performs effectively with the simulated data. Furthermore, the DMSOP model is applied to two response variables, namely, the life satisfaction and self-rated health of adults in 25 provinces in China. The empirical results show that the model can effectively measure the spatial and temporal dependencies for multivariate ordinal responses.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"18 1","pages":"462 - 485"},"PeriodicalIF":1.5000,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Bayesian analysis of a dynamic multivariate spatial ordered probit model\",\"authors\":\"P. Gao, Zixiang Lu\",\"doi\":\"10.1080/17421772.2023.2181384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Spatial econometrics has few studies on multivariate ordinal responses. This study proposes a dynamic multivariate spatial ordered probit (DMSOP) model, which is the first attempt to capture temporal and spatial dependencies simultaneously for multivariate ordinal responses. The parameters are calculated using Bayesian inference based on Markov chain Monte Carlo sampling. The DMSOP model performs effectively with the simulated data. Furthermore, the DMSOP model is applied to two response variables, namely, the life satisfaction and self-rated health of adults in 25 provinces in China. The empirical results show that the model can effectively measure the spatial and temporal dependencies for multivariate ordinal responses.\",\"PeriodicalId\":47008,\"journal\":{\"name\":\"Spatial Economic Analysis\",\"volume\":\"18 1\",\"pages\":\"462 - 485\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spatial Economic Analysis\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/17421772.2023.2181384\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Economic Analysis","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/17421772.2023.2181384","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Bayesian analysis of a dynamic multivariate spatial ordered probit model
ABSTRACT Spatial econometrics has few studies on multivariate ordinal responses. This study proposes a dynamic multivariate spatial ordered probit (DMSOP) model, which is the first attempt to capture temporal and spatial dependencies simultaneously for multivariate ordinal responses. The parameters are calculated using Bayesian inference based on Markov chain Monte Carlo sampling. The DMSOP model performs effectively with the simulated data. Furthermore, the DMSOP model is applied to two response variables, namely, the life satisfaction and self-rated health of adults in 25 provinces in China. The empirical results show that the model can effectively measure the spatial and temporal dependencies for multivariate ordinal responses.
期刊介绍:
Spatial Economic Analysis is a pioneering economics journal dedicated to the development of theory and methods in spatial economics, published by two of the world"s leading learned societies in the analysis of spatial economics, the Regional Studies Association and the British and Irish Section of the Regional Science Association International. A spatial perspective has become increasingly relevant to our understanding of economic phenomena, both on the global scale and at the scale of cities and regions. The growth in international trade, the opening up of emerging markets, the restructuring of the world economy along regional lines, and overall strategic and political significance of globalization, have re-emphasised the importance of geographical analysis.