A Univariate Time Series Modelling of Dates Exports in Pakistan?
Journal: Journal of Contemporary Issues in Business Research (Vol.1, No. 2)Publication Date: 2012-11-01
Authors : Farah Naz;
Page : 57-68
Keywords : ARIMA model; Box-Jenkins methodology; Dates; Exports; Forecasting; Pakistan; Time series modeling.;
Abstract
Export plays a significant role in the economic growth of a country. Increase in export led to an increase in production and ultimate outcome is economic growth. The purpose of this study was to build a forecast model meant for the Exports of Dates in Pakistan for the next 15 years. The yearly data of dates export for the period 1962-2008 was used based on the assumptions that past trends (area planted and yield) and existence of normal weather pattern will hold. The Box-Jenkins methodology was taken as an appropriate set of Autoregressive integrated Moving Average (ARIMA) models that were constructed for future forecast of date exports of Pakistan. The final results of ARIMA showed that date exports of Pakistan provided better results in upward trend for future. Besides this, model selection criteria includes e.g. AIC, SIC, BIC, MAPE and RMSE were used.
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