A. Taheri, S. Nessabian, R. Moghaddasi, F. Arbabi, M. Damankeshideh
{"title":"Drivers of business cycles in Iran and some selected oil producing countries","authors":"A. Taheri, S. Nessabian, R. Moghaddasi, F. Arbabi, M. Damankeshideh","doi":"10.20885/EJEM.VOL13.ISS1.ART4","DOIUrl":null,"url":null,"abstract":"Purpose ─ This study is aimed at analyzing the main drivers of business cycle in Iran and some selected oil producing countries during the 1970:Q1-2015:Q4 period. In addition, the study evaluates causality of leading macroeconomic indicators for each different regimes of the business cycles. Methods ─ This study proposes a new methodological approach by combining Markov-Switching Vector Autoregressive (MSVAR) and MS-Granger causality approach. Findings ─ The results show that there are diverse sources of business cycle. Iran experienced higher volatility of GDP where machinery investment and export are found as main driver of its business cycle. Meanwhile, consumer price index has countercyclical effect in all countries. We also find some similarities to the US, the UK, and Canada regarding the probability of a business cycle, number of observations, and the average duration, especially in the first regime of MS-VAR models. The high level of oil price volatility relative to the GDP volatility indicates the power of oil price shock to generate cycles. In addition, the results of the traditional Granger causality test confirm the Markov-Switching Granger Causality (MS-GC) test in all countries except export from the UK. Implication ─ Identification the main driver of business cycles is very significant to formulate the steady growth path so that the government able to select the most adequate economic policy. Originality ─ The novelty of this study is the adoption of a new approach by combining stylized facts and MS-VAR and MS-Granger causality to analyze the business cycles in different regime.","PeriodicalId":41472,"journal":{"name":"Economic Journal of Emerging Markets","volume":"12 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Journal of Emerging Markets","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20885/EJEM.VOL13.ISS1.ART4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose ─ This study is aimed at analyzing the main drivers of business cycle in Iran and some selected oil producing countries during the 1970:Q1-2015:Q4 period. In addition, the study evaluates causality of leading macroeconomic indicators for each different regimes of the business cycles. Methods ─ This study proposes a new methodological approach by combining Markov-Switching Vector Autoregressive (MSVAR) and MS-Granger causality approach. Findings ─ The results show that there are diverse sources of business cycle. Iran experienced higher volatility of GDP where machinery investment and export are found as main driver of its business cycle. Meanwhile, consumer price index has countercyclical effect in all countries. We also find some similarities to the US, the UK, and Canada regarding the probability of a business cycle, number of observations, and the average duration, especially in the first regime of MS-VAR models. The high level of oil price volatility relative to the GDP volatility indicates the power of oil price shock to generate cycles. In addition, the results of the traditional Granger causality test confirm the Markov-Switching Granger Causality (MS-GC) test in all countries except export from the UK. Implication ─ Identification the main driver of business cycles is very significant to formulate the steady growth path so that the government able to select the most adequate economic policy. Originality ─ The novelty of this study is the adoption of a new approach by combining stylized facts and MS-VAR and MS-Granger causality to analyze the business cycles in different regime.