| dc.description.abstract | In this paper, we examine whether the current business leading indicator components can forecast business cycle effectively. This study proceeds with empirical analysis about seven business leading indicator components and business cycle published by CEPD (Council for Economic Planning and Development).
In order to prevent business leading indicator components from the influence of short-term incidents and factors which can not forecast business cycle, this paper uses the Empirical Mode Decomposition, the primary method of Hilbert-Huang Transform developed by Huang, extracts the shortest-term fluctuations from the variables, and then compose new business leading indicator components. As a result, we find that there are only two leading indicator components, Index of Producer’s Inventory and Building Permit (including housing, mercantile, business and service, industrial warehousing), in empirical analysis under shorter lag periods VAR model, are effective leading indicators in Granger causality test. While under longer lag periods VAR model, all of the seven leading indicator components behave poor in Granger causality test.
However, under shorter lag periods VAR model, there are three leading indicator components (including Index of Export Orders, Index of Producer’s Inventory, and Stock Price Index) are effective leading indicators in Granger causality test within seven modified leading indicator components recommended by this paper. Under longer lag periods VAR model, all of the seven leading indicator components behave well in Granger causality test, which can be business leading indicators.
Finally, this paper uses out-of-sample test to evaluate the modified leading indicator components. This result proves that new business leading indicator components suggested by this paper forecast business cycle more accurately. | en_US |