Is the oil price pass-through in India any different?

Mandal, Kaushik; Bhattacharyya, Indranil; Bhoi, Binod B.

doi:10.1016/j.jpolmod.2012.06.001

Cited by 19 publications

(10 citation statements)

References 10 publications

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“…Shah and Wang (2012) showed positive but minimal effects of oil price shocks on real output in Malaysia, Pakistan and Thailand, and negative effects on Indonesian output. Mandal et al (2012) concluded that higher oil prices led to significant upsurge in inflation with debilitating effect on output in India. Ran and Voon (2012) detected insignificant impact of oil price shocks on economic activity in Hong Kong, South Korea, Singapore and Taiwan.…”

Section: Literature Reviewmentioning

confidence: 99%

Asymmetric effects of oil price shocks on Asian economies: a nonlinear analysis

et al. 2018

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Section: Literature Reviewmentioning

confidence: 99%

Asymmetric effects of oil price shocks on Asian economies: a nonlinear analysis

et al. 2018

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“…Therefore, it is possible good monetary policy can help to minimise the impact of changes in the global oil price for this country. 3 This view is supported by the findings of Hooker (2002), Taylor (2000), Cologni and Manera (2008), Chen (2009), LeBlance and Chinn (2004), Mandal, Bhattcharya, and Bhoi (2012) and Dedeoglu and Kaya (2014) who indicate that the effect of the oil price on inflation is weaker when adequate monetary policies are implemented.…”

Section: Resultsmentioning

confidence: 91%

Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Ajayi

2019

Business, Management and Education

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Purpose – This study identifies the most appropriately selected multivariate model for forecasting inflation in different economic environments. In specifying the multivariate models, the study test for the orders of integration of variables and for those that are nonstationary. For non-stationary variables, this study examines whether they are cointegrated. Engle and Granger (1987) establish that a cointegrating equation can be represented as an error correction model that incorporates both changes and levels of variables such that all of the elements are stationary. However, VARs estimated with cointegrated data will be misspecified if all of the data are differenced because long-run information will be omitted, and will have omitted stationarity inducing constraints if all the data are used in levels. Further, including variables in both levels and differences should sat-isfy stationarity requirements. However, they will omit cointegrating restrictions that may improve the model. Of course, these constraints will be satisfied asymptotically; but efficiency gains and improved multi-step forecasts may be achieved by imposing the constraints (Engle and Granger 1987, p. 259). Therefore, this study test for order of integration and compare inflation forecasting performance of different multivariate models for BRICS and OPEC countries. Research methodology – The following approaches were considered; the first approach is to construct a VAR model in differences (stationary form) to forecast inflation. The second approach is to construct a VECM without imposing cointegrating restrictions. The third approach is to construct a VEC that imposes cointegrating restrictions on the VECM. This will help to understand whether imposing cointegrating restrictions via a VEC improves long-run forecasts. Research limitation – The proposed multivariate models focused on differencing and cointegrating restrictions to ensure the stationarity of the data, the available variables were combined and specified based on their level of integration to forecast inflation. For instance, a VAR model is estimated based on differenced variables I(0); the same holds true for VECM and VEC models, where differenced variables and linear combinations of I(I) covariates are stationary. In future, multivariate models guided by economic theory rather than the order of integration of variables are suggested. Findings – The result shows that the forecast performance of inflation depends on the nature of the economy and whether the country experiencing higher inflation or low inflation. For instance, the model that includes long-run information in the form of a specified cointegrated equation generally improves the inflation forecasting performance for BRICS countries and one OPEC country (Saudi Arabia) that has a history of low inflation. Practical implications – This research will improve the policy makers decision on how to select appropriate model to forecast inflation over different economic environment. Originality/Value – These methods have not been used to forecast inflation for many emerging economies such as OPEC and BRICS countries despite the importance of many of these countries to the global economy. This study fills this gap by evaluating the forecasting performance of inflation using multivariate VAR and cointegrating models for OPEC and BRICS economies.

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“…Gregorio, Landerretche, Neilson, Broda, & Rigobon (2007) found that the impact of oil price doubling on CPI was 5 point from 1965 to 2004. Examining the monthly, time-series data for the period April 1994 to March 2010, Mandal, Bhattacharyya, & Bhoi (2012) found that frequent price adjustment of some of the petroleum products in line with the international crude oil price amplified the impact of oil price on domestic inflation in India after 2002.…”

Section: Review Of Empirical Studiesmentioning

confidence: 99%

Measuring the Impact of Oil Prices and Exchange Rate Shocks on Inflation: Evidence from India

Sharma

Rishad

Gupta

2019

EJBE

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The purpose of this study is to examine the long-run and short-run impact of crude oil price and exchange rate shocks on domestic inflation in India within the framework of the Autoregressive Distributed Lag (ARDL) model. The results show that the exchange rate and oil price shocks significantly influence domestic inflation during the study period (April 1994 to February 2018. Further, the breakpoint unit root test revealed the severe impact of the 2008 financial crisis on inflation in India. The findings show that any move to scale down fuel subsidies will escalate cost-push inflation severely, as the country is an energy-dependent economy. So, policymakers shall stabilise the impact of these shocks through suitable monetary policy actions.

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Is the oil price pass-through in India any different?

Cited by 19 publications

References 10 publications

Asymmetric effects of oil price shocks on Asian economies: a nonlinear analysis

Asymmetric effects of oil price shocks on Asian economies: a nonlinear analysis

Comparing Multivariate Models’ Forecasts of Inflation for Brics and Opec Countries

Measuring the Impact of Oil Prices and Exchange Rate Shocks on Inflation: Evidence from India

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