Suresh Kumar Oad Rajput, Namarta Kumari Bajaj, Tariq Aziz Siyal
{"title":"Impact of Geopolitical Risk on Foreign Remittances","authors":"Suresh Kumar Oad Rajput, Namarta Kumari Bajaj, Tariq Aziz Siyal","doi":"10.2139/ssrn.3491587","DOIUrl":null,"url":null,"abstract":"This study seeks to examine the hidden-cointegration among Geopolitical Risk (GPR) and foreign remittances. The suitable models for this study are Nonlinear Autoregressive Distributed Lag (NARDL) model to find the nature of impact (symmetric or asymmetric), and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the volatility of foreign remittances using data for BRIC economies. The findings from NARDL suggests that in short-run geopolitical risk is asymmetric to foreign remittances in BRIC economies. Whereas, in long-run geopolitical risk is asymmetric to foreign remittances in the case of Brazil, Russia and India. We find volatility in GPR transmits to volatility in foreign remittances in the case of Brazil, Russia, and India. Remittances in China are found to be least volatile during geopolitical risk. The policymakers, migrants, and recipients should consider the asymmetric and volatile nature of geopolitical risk while making decisions about policies and transfer of remittances respectively.","PeriodicalId":391101,"journal":{"name":"Econometric Modeling: International Economics eJournal","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: International Economics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3491587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This study seeks to examine the hidden-cointegration among Geopolitical Risk (GPR) and foreign remittances. The suitable models for this study are Nonlinear Autoregressive Distributed Lag (NARDL) model to find the nature of impact (symmetric or asymmetric), and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the volatility of foreign remittances using data for BRIC economies. The findings from NARDL suggests that in short-run geopolitical risk is asymmetric to foreign remittances in BRIC economies. Whereas, in long-run geopolitical risk is asymmetric to foreign remittances in the case of Brazil, Russia and India. We find volatility in GPR transmits to volatility in foreign remittances in the case of Brazil, Russia, and India. Remittances in China are found to be least volatile during geopolitical risk. The policymakers, migrants, and recipients should consider the asymmetric and volatile nature of geopolitical risk while making decisions about policies and transfer of remittances respectively.