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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/9318
Title: A Periodic Autoregressive Model of Indian WPI Inflation
Authors: Kar, Sujata
Published in: Margin
Abstract: A growing literature in the field of econometrics is on the treatment of seasonal variables. However, so far, very few studies in India have applied advanced seasonal modelling techniques to important macroeconomic variables. This paper examines the seasonal properties of Indian monthly WPI inflation and their usefulness in modelling the series more efficiently. Monthly WPI inflation was found to be a periodic process with 18 lags and periodic integration of order two. A comparison between the performances of a PAR (18) and an AR (18) model showed that the former performed substantially better in terms of R2, AIC, in-sample predictive ability and residual properties. However, the out-of-sample forecasts from the PAR model were only reasonable. The best forecasts obtained for a horizon of 22 months, however, had good ‘direction of change’ predictions. The model could also produce interval forecasts of modest accuracy. ©.
Citation: Margin (2010), 4(3): 279-292
URI: https://doi.org/10.1177/097380101000400302
http://repository.iitr.ac.in/handle/123456789/9318
Issue Date: 2010
Publisher: SAGE Publications Ltd
Keywords: Inflation
JEL Classification: C53
JEL Classification: E31
Out-of-Sample Forecasts
Periodic Autoregressive Model
Periodic Integration
ISSN: 9738010
Author Scopus IDs: 57081884700
Author Affiliations: Kar, S., University of Petroleum and Energy Studies, Dehradun, India
Corresponding Author: Kar, S.; Department of Humanities and Social Sciences, IITIndia; email: sujata.kar@gmail.com
Appears in Collections:Journal Publications [MS]

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