Abstract
As an alternative to the method currently used by the Council for Economic Planning and Development (CEPD), we apply the least angle regression (LARS) method proposed by Efron et al. (2004) to select the macroeconomic series used to construct composite business indicators. We use a two-step approach. First, we obtain 103 macroeconomic series and assign each of them to one of three subgroups-leading, coincident and lagging-based on their ability to predict the reference cycle series. Second, within each subgroup, we rank the assigned series based on their ability to predict the reference cycle series and construct a composite business indicator based on these rankings. Our results suggest that the macroeconomic series selected via the LARS method tend to agree with those currently used by the CEPD. However, the power of the selected macroeconomic series to predict reference cycle series varies with the size of the sample selected. Moreover, the composite leading indicator constructed from the macroeconomic series selected via the LARS method predicts turning points of the business cycle more effectively than the existing CEPD leading indicator.