Looking into the black box of the Korean economy: the sparse factor model approach1

Hyun Hak Kim

Journal of the Asia Pacific Economy, 2018, vol. 23, issue 1, 1-16

Abstract: This paper investigates the usefulness of the factor model, which extracts latent information from a large set of data, in forecasting Korean macroeconomic variables such as inflation, GDP growth, exports, consumption and investment. In addition to the well-known principal component analysis (PCA), we apply sparse principal component analysis (SPCA) to build a forecasting model and combine the estimated factors with various shrinkage methods. We look into the component of Korean macroeconomy using SPCA and then identify the key variables of the component. Our major findings are that various hybrid models outperform benchmark models including an autoregressive model, and that this result becomes clearer as the forecast horizons lengthen. We also find that the main ingredients of Korean macroeconomic black box as indicated by SPCA include interest rates, construction orders received and employment variables. Among them, the interest rates have stronger impact on economy than others.

Date: 2018
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DOI: 10.1080/13547860.2017.1349995

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