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Inflation Forecasting in Pakistan using Artificial Neural Networks

Adnan Haider and Muhammad Hanif

MPRA Paper from University Library of Munich, Germany

Abstract: An artificial neural network (hence after, ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. In previous two decades, ANN applications in economics and finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP Growth and currency in circulation etc. In this paper, we have attempted to forecast monthly YoY inflation for Pakistan by using ANN for FY08 on the basis of monthly data of July 1993 to June 2007. We also compare the forecast performance of the ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed that RMSE of ANN based forecasts is much less than the RMSE of forecasts based on AR(1) and ARIMA models. At least by this criterion forecast based on ANN are more precise.

Keywords: artificial neural network; forecasting; inflation (search for similar items in EconPapers)
JEL-codes: C51 C52 C53 E31 E37 (search for similar items in EconPapers)
Date: 2007-07-13
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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