Business cycle forecasting: Industry forecasting in trade associations

Lisa Agerskov Jensen

Student thesis: Master thesis


High quality forecasts are becoming more and more important for the successful strategic planning of rms, due to increased turbulence in business conditions. Based on their position, which grants them in-depth knowledge of their industry, trade associations are considered to be in a advantageous position to create quality forecasts. This thesis investigates the possibilities for business cycle forecasting in trade associations. Indicator based methods for forecasting are evaluated from a theoretical perspective, and the possibilities for applying these in trade associations are analyzed based on an empirical study into trade associations' use of forecasting. Forecasting methods are found to have di erent properties, and the forecaster is faced with a trade o between requirements and quality. No forecasting method is found to be superior from a theoretical standpoint, and the optimal method for forecasting therefore depends on the situation in which it is applied. Industry di erences makes it impossible to forecast with a standardized set of indicators, and such industry speci c indicators are needed to forecast each industry. Indicators should be selected on the basis of subjective knowledge of empirical relationships, or business cycle theories. Forecasting with the same method in all industries seems realistic. Low amounts of forecasting is currently being done in trade associations, and the demand for forecasts from member rms is relatively low. There is no signi cant correlation between forecasting done, the industry's sensitivity to uctuations in the economy, and the demand for forecasts. There is a general interest in forecasting among trade associations but few resources are available. The current demand justi es value creation through forecasting in trade associations, and the thesis nds that trade associations should engage in industry forecasting to improve the strategic planning of their member rms. Forecasting in trade associations should be done with composite indicators and an industry speci c set of indicators. Furthermore, an automated visualization of index characteristics, to improve the interpretation process and reduce the resources required, is suggested.

EducationsMSc in Finance and Strategic Management, (Graduate Programme) Final Thesis
Publication date2012
Number of pages99