Rationality of business operational forecasts: evidence from Malaysian distributive trade sector

• Main Authors: Puah, Chin-Hong, Wong, Shirly Siew-Ling, Muzafar Shah, Habibullah
• Format: Working Paper
• Language: English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2012
• Subjects: AC Collections. Series. Collected works; HB Economic Theory; HG Finance
• Online Access: http://ir.unimas.my/id/eprint/3230/1/Puah%20Chin%20Hong.pdf; http://ir.unimas.my/id/eprint/3230/

The underlying nature of forecast optimization makes the rational expectations hypothesis (REH) a framework that is theoretically consistent with the expectations formation produced by economic agents under well-defined assumptions of unbiased forecasts and efficient utilization of available information. Most of the recent literature on REH testing has favored a direct procedure based on survey data to validate the theoretical soundness of REH.However, the ability of survey materials to reflect the economic agent’s true expectations remains unconvincing, as previous empirical studies on survey-based expectations have offered mixed evidence of forecast rationality. The present study involved an attempt to evaluate the forecast rationality of survey materials from the Malaysian perspective, as empirical evidence from the view of a developing nation is clearly limited. An expectational series on gross revenue and capital expenditure, spanning 1978 through 2007, was subjected to tests of unbiasedness, non-serial correlation, and efficiency to observe whether the business operational forecasts contributed by the distributive trade sector in Malaysia can be accepted as rational forecasts of the actual realized values. We found that both operational variables are being irrationally constructed, suggesting that forecasters in the distributive trade sector are not rational when they formulate business expectations. Thus, business firms in the examined sector are encouraged to incorporate more relevant information into their business operational forecasts to facilitate more accurate and realistic business forecasting.