• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.103-114
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• 2015

The role of small and medium enterprises as an economic growth factor has been accentuated; consequently, the need to develop a business forecast model and indexes that accurately examine business situation of small and medium enterprises has increased. Most current business model and indexes concerning small and medium enterprises, released by public and private institutions, are based on Business Survey Index (BSI) and depend on subjective (business model and) indexes; therefore, the business model and indexes lack a capacity to grasp an accurate business situation of these enterprises. The business forecast model and indexes suggested in the study have been newly developed with Principal Component Analysis(PCA) and weight method to accurately measure a business situation based on reference dates addressed by the National Statistical Office(NSO). Empirical studies will be presented to prove that the newly proposed business model and indexes have their basis in statistical theory and their trend that resembles the existing Composite Index.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.903-924
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• 2000

This paper examines the alternative method to measure the state of overall economic activity. The macroeconomic variables, used for business cycle, take more than a month after a period for collection and aggregation. The electricity generation data is compiled in mechanical ways just after the period. Based on this fact, we develop the two stage estimation method for coincident economic indicators in order to detect the business cycle in an earlier period, using Stock-Watson's Dynamic Factor Model. Using monthly data from 1970 to 1999, it is found that the experimental coincidence economic indicators are well-fitted to data and also that the estimates of two stage estimation method have good explanatory power, equivalent to the experimental coincidence economic indicators. While the RMSE of coincidence economic indicators is found to be 1.27%, that of the experimental coincidence economic indicators is found to be 1.31% and that of the two stage estimation method is around 1.44%. If we take consideration into the fact that it measures the business cycle in one month earlier, we come to the conclusion that the two stage estimation is of great use.