{"title":"基于地理信息系统的经济金融风险分析:以欧洲和中亚为例","authors":"Yusuf Kalkan, A. Çam","doi":"10.25115/sae.v41i2.8239","DOIUrl":null,"url":null,"abstract":"The study has two purposes. The first purpose is, using the economic and financial risk factors determined by the International Country Risk Guide (ICRG) rating agency, to reclassify the scores that countries get from these factors with the Jenks Natural Breaks (JNB) classification technique and to compare countries by creating their thematic maps according to this classification. The second purpose of our study is to create economic and financial risk maps of countries by using the Geographical Weighted Regression (GWR) method, which is one of the Geographical Information System (GIS) analysis techniques, based on the economic and financial risk factors determined by the ICRG. Before the GWR analysis for the variables included in the research, Moran Index analysis was performed as the main measurement of spatial autocorrelation. As a result of the Moran analysis, it was determined that there was a statistically significant positive autocorrelation between the countries. In other words, it has been seen that the countries examined have spatial dependence on each other in terms of economic and financial risk. According to the results of the GWR analysis, risk maps of the examined countries were created and more dynamic, more meaningful or more sensitive, more specific and visually easier to understand results were revealed. And according to these results, it has been seen that the GWR technique can also be used in the fields of economy and finance. In addition, the study brought a different interdisciplinary perspective by bringing together the fields of economy, finance and geography.","PeriodicalId":210068,"journal":{"name":"Studies of Applied Economics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geographic Information System Based Economic And Financial Risk Analysis: The Case Of Europe And Central Asia\",\"authors\":\"Yusuf Kalkan, A. Çam\",\"doi\":\"10.25115/sae.v41i2.8239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study has two purposes. The first purpose is, using the economic and financial risk factors determined by the International Country Risk Guide (ICRG) rating agency, to reclassify the scores that countries get from these factors with the Jenks Natural Breaks (JNB) classification technique and to compare countries by creating their thematic maps according to this classification. The second purpose of our study is to create economic and financial risk maps of countries by using the Geographical Weighted Regression (GWR) method, which is one of the Geographical Information System (GIS) analysis techniques, based on the economic and financial risk factors determined by the ICRG. Before the GWR analysis for the variables included in the research, Moran Index analysis was performed as the main measurement of spatial autocorrelation. As a result of the Moran analysis, it was determined that there was a statistically significant positive autocorrelation between the countries. In other words, it has been seen that the countries examined have spatial dependence on each other in terms of economic and financial risk. According to the results of the GWR analysis, risk maps of the examined countries were created and more dynamic, more meaningful or more sensitive, more specific and visually easier to understand results were revealed. And according to these results, it has been seen that the GWR technique can also be used in the fields of economy and finance. In addition, the study brought a different interdisciplinary perspective by bringing together the fields of economy, finance and geography.\",\"PeriodicalId\":210068,\"journal\":{\"name\":\"Studies of Applied Economics\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Studies of Applied Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25115/sae.v41i2.8239\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies of Applied Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25115/sae.v41i2.8239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geographic Information System Based Economic And Financial Risk Analysis: The Case Of Europe And Central Asia
The study has two purposes. The first purpose is, using the economic and financial risk factors determined by the International Country Risk Guide (ICRG) rating agency, to reclassify the scores that countries get from these factors with the Jenks Natural Breaks (JNB) classification technique and to compare countries by creating their thematic maps according to this classification. The second purpose of our study is to create economic and financial risk maps of countries by using the Geographical Weighted Regression (GWR) method, which is one of the Geographical Information System (GIS) analysis techniques, based on the economic and financial risk factors determined by the ICRG. Before the GWR analysis for the variables included in the research, Moran Index analysis was performed as the main measurement of spatial autocorrelation. As a result of the Moran analysis, it was determined that there was a statistically significant positive autocorrelation between the countries. In other words, it has been seen that the countries examined have spatial dependence on each other in terms of economic and financial risk. According to the results of the GWR analysis, risk maps of the examined countries were created and more dynamic, more meaningful or more sensitive, more specific and visually easier to understand results were revealed. And according to these results, it has been seen that the GWR technique can also be used in the fields of economy and finance. In addition, the study brought a different interdisciplinary perspective by bringing together the fields of economy, finance and geography.