Title: Integration of macro and micro level forecasting methods for volatile environments: applications in durable goods industries
Authors: Emre A. Veral
Addresses: Department of Management, Baruch College, Zicklin School of Business, B9 – 240 One Bernard Baruch Way, NY, NY 10010, USA
Abstract: This paper proposes an integrated forecasting system that combines an econometric method with a time series method and applies the system to the forecasting of Turkish monthly automobile sales data. An econometric model is used to generate initial base levels of quarterly sales forecasts upon which dynamic time series adjustments are made as actual monthly data are realised. Of particular concern are the effects of macro economic changes that occur more frequently in developing economies, thus, causing consumers to change their behaviour regarding major purchases. The proposed model considers long-term and short-term effects that influence sales of durable goods when economic disruptions are severe and/or temporary. The proposed integrative mechanism dynamically updates and revises medium-term econometric forecasts via short-term time series methods. Analysis of real life data supports the effectiveness of the proposed methodology in a growing-economy automotive market and simulation experiments facilitate generalisation of specific findings.
Keywords: forecasting; time series; simulation; durable goods industries; volatility; econometrics; Turkey; monthly sales; automotive sales data; automobile industry.
International Journal of Applied Decision Sciences, 2008 Vol.1 No.4, pp.418 - 434
Published online: 05 Feb 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article