{"title":"印度主要马铃薯市场的价格行为和市场整合","authors":"","doi":"10.35716/ijed-22510","DOIUrl":null,"url":null,"abstract":"Variation in potato output over time causes wide price fluctuations, subjecting its producers to a high-risk situation. Using a monthly wholesale price of potato from January 2012 to December 2020, the current study examined the price behaviour of major potato-producing and consuming markets. The study employed correlation analysis, the Johansen Co-integration Test, the Vector Error Correction Model, and Granger Causality test. As determined by the seasonality index, farmers received higher-than-average prices between June and December. Johansen's co-integration result demonstrated that all the selected markets were well integrated in the long run. The Patna market had the fastest adjustment rate (80 per cent), followed by the Mumbai market. Most states had uni-directional price transmission, with Patna being the only state to establish a bidirectional flow of potato prices with the Kolkata market. The Delhi market was discovered to be the key market influencing the prices of all other markets. Keywords: Co-integration, Granger causality, instability, price transmission. JEL Codes: C21, C23, C32, Q13.","PeriodicalId":43367,"journal":{"name":"Indian Journal of Economics and Development","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Price Behaviour and Market Integration Amongst the Major Potato Markets in India\",\"authors\":\"\",\"doi\":\"10.35716/ijed-22510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Variation in potato output over time causes wide price fluctuations, subjecting its producers to a high-risk situation. Using a monthly wholesale price of potato from January 2012 to December 2020, the current study examined the price behaviour of major potato-producing and consuming markets. The study employed correlation analysis, the Johansen Co-integration Test, the Vector Error Correction Model, and Granger Causality test. As determined by the seasonality index, farmers received higher-than-average prices between June and December. Johansen's co-integration result demonstrated that all the selected markets were well integrated in the long run. The Patna market had the fastest adjustment rate (80 per cent), followed by the Mumbai market. Most states had uni-directional price transmission, with Patna being the only state to establish a bidirectional flow of potato prices with the Kolkata market. The Delhi market was discovered to be the key market influencing the prices of all other markets. Keywords: Co-integration, Granger causality, instability, price transmission. JEL Codes: C21, C23, C32, Q13.\",\"PeriodicalId\":43367,\"journal\":{\"name\":\"Indian Journal of Economics and Development\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indian Journal of Economics and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35716/ijed-22510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Economics and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35716/ijed-22510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
Price Behaviour and Market Integration Amongst the Major Potato Markets in India
Variation in potato output over time causes wide price fluctuations, subjecting its producers to a high-risk situation. Using a monthly wholesale price of potato from January 2012 to December 2020, the current study examined the price behaviour of major potato-producing and consuming markets. The study employed correlation analysis, the Johansen Co-integration Test, the Vector Error Correction Model, and Granger Causality test. As determined by the seasonality index, farmers received higher-than-average prices between June and December. Johansen's co-integration result demonstrated that all the selected markets were well integrated in the long run. The Patna market had the fastest adjustment rate (80 per cent), followed by the Mumbai market. Most states had uni-directional price transmission, with Patna being the only state to establish a bidirectional flow of potato prices with the Kolkata market. The Delhi market was discovered to be the key market influencing the prices of all other markets. Keywords: Co-integration, Granger causality, instability, price transmission. JEL Codes: C21, C23, C32, Q13.