{"title":"印度货币稳定需求的协整实证分析","authors":"Hemachandra Padhan","doi":"10.2139/ssrn.2867551","DOIUrl":null,"url":null,"abstract":"The recent macroeconomics and emerging market economics have contributed to the growing integration of financial innovation; financial markets integration, and financial dis intermediaries. This study investigates the long run and short run stability demand for money in India and relationship among M3 (Broad money), income level (Y), interest rate (call money) and exchange rate. The empirical results have analyzed from CUSUM test, CUSUMSQ test, co-integration, and VECM (vector error correction model) by taking the financial year data from 1970-71 to 2013-14. The results reveal that three co-integrating vectors at 5% significance level whereas the maximum eigenvalue test indicates the presence of two co-integrating vectors at 5% level of significance. VECM explains the speed of adjustment. Equation 1,","PeriodicalId":247622,"journal":{"name":"ERN: Fiscal & Monetary Policy in Developing Economies (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An Empirical Analysis of Stable Demand for Money in India with Co-Integration Approach\",\"authors\":\"Hemachandra Padhan\",\"doi\":\"10.2139/ssrn.2867551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent macroeconomics and emerging market economics have contributed to the growing integration of financial innovation; financial markets integration, and financial dis intermediaries. This study investigates the long run and short run stability demand for money in India and relationship among M3 (Broad money), income level (Y), interest rate (call money) and exchange rate. The empirical results have analyzed from CUSUM test, CUSUMSQ test, co-integration, and VECM (vector error correction model) by taking the financial year data from 1970-71 to 2013-14. The results reveal that three co-integrating vectors at 5% significance level whereas the maximum eigenvalue test indicates the presence of two co-integrating vectors at 5% level of significance. VECM explains the speed of adjustment. Equation 1,\",\"PeriodicalId\":247622,\"journal\":{\"name\":\"ERN: Fiscal & Monetary Policy in Developing Economies (Topic)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Fiscal & Monetary Policy in Developing Economies (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2867551\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Fiscal & Monetary Policy in Developing Economies (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2867551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Empirical Analysis of Stable Demand for Money in India with Co-Integration Approach
The recent macroeconomics and emerging market economics have contributed to the growing integration of financial innovation; financial markets integration, and financial dis intermediaries. This study investigates the long run and short run stability demand for money in India and relationship among M3 (Broad money), income level (Y), interest rate (call money) and exchange rate. The empirical results have analyzed from CUSUM test, CUSUMSQ test, co-integration, and VECM (vector error correction model) by taking the financial year data from 1970-71 to 2013-14. The results reveal that three co-integrating vectors at 5% significance level whereas the maximum eigenvalue test indicates the presence of two co-integrating vectors at 5% level of significance. VECM explains the speed of adjustment. Equation 1,