Forecasting Inflation: Autoregressive Integrated Moving Average Model

  • Muhammad Iqbal Department of Economics, University of Vienna, Austria
  • Amjad Naveed Department of Business and Economics, University of Southern Denmark, Denmark

Abstract

This study compares the forecasting performance of various Autoregressive integrated moving average (ARIMA) models by using time series data. Primarily, The Box-Jenkins approach is considered here for forecasting. For empirical analysis, we used CPI as a proxy for inflation and employed quarterly data from 1970 to 2006 for Pakistan. The study classified two important models for forecasting out of many existing by taking into account various initial steps such as identification, the order of integration and test for comparison. However, later model 2 turn out to be a better model than model 1 after considering forecasted errors and the number of comparative statistics.

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Published
2016-01-29
How to Cite
Iqbal, M., & Naveed, A. (2016). Forecasting Inflation: Autoregressive Integrated Moving Average Model. European Scientific Journal, ESJ, 12(1), 83. https://doi.org/10.19044/esj.2016.v12n1p83