Developing Composite Leading Indicators to Forecast Industrial Business Cycles in Iran

Abstract

Economic cycles are referred as repeatable movement of economic indicators with different domain and duration. Detection of these cycles may help in forecasting the contraction period or expansions of important parts of the economy specifically industry. In this regard, many economist and researchers have focused on composite leading indicators which are growing in terms of diversity of econometric methods. This paper studies 13 macro economical time series in order to develop the best composite indicator, reflecting business cycles of Iran's industry. Number of established licenses, production index of large industrial units, producer price index and import value index are the chosen variables that make the proposed composite leading indicator. The result of comparison between composite leading indicator and value added time series in the studied period (1997 up to 2012) showed a good correlation between the fluctuations of composite indicators and value added of industry. The result also showed that the proposed leading indicator has the ability to predict the business cycle for maximum 4 and minimum 1 period ahead and in average the forecasted period is equal to 3.2 seasons.