Revisiting the Phillips curve for India and inflation forecasting
Journal of Asian Economics, 2013, vol. 25, issue C, 17-27
This paper focuses on modeling and forecasting inflation in India using an augmented Phillips curve framework. Both demand and supply factors are seen as drivers of inflation. Demand conditions are found to have a stronger impact on non-food manufactured products (NFMP) inflation vis-a-vis headline wholesale price inflation; moreover, NFMP inflation is found to be more persistent than headline inflation. Both these findings support the use of NFMP inflation as a core measure of inflation. But, the impact of global non-fuel commodities on NFMP inflation is found to be substantial. Inflation in non-fuel commodities is seen as a more important driver of domestic inflation rather than fuel inflation. The exchange rate pass-through coefficient is found to be modest, but nonetheless sharp depreciation in a short period of time can add to inflationary pressures. The estimated equations show a satisfactory in sample as well as out-of-sample performance based on dynamic simulations. Nonetheless, forecasting challenges emanate from volatility in international oil and other commodity prices and domestic food supply dynamics.
Keywords: Exchange rate pass-through; India; Inflation; Monetary policy; Phillips curve (search for similar items in EconPapers)
JEL-codes: E31 E32 E52 E58 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:asieco:v:25:y:2013:i:c:p:17-27
Access Statistics for this article
Journal of Asian Economics is currently edited by C. Wiemer
More articles in Journal of Asian Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().