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Forecasting macroeconomic variables using data dimension reduction methods : The case of Korea

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Frame of Image yun Jeong Kim, Ki-ho Kim, Youngjae Chang, and other seminar participants for their valuable comments.
Contents
Ⅰ . Introduction ··············································································· 1 Ⅱ . Forecasting Model ···································································· 3 Ⅲ . Sparse Principal Component Analysis ··································· 7 Ⅳ . Data and Estimation ······························································ 9 Ⅴ . Comparison of Two Principal Components ······················· 12 Ⅵ . Experimental Results ······························································ 18
1. Experimental Setup ············································································ 18 2. Results: Consumer Price Index ···························································· 19 3. Results: GDP growth rate ··································································· 23 4. Results: Consumption ········································································· 24 5. Results: Exports ··················································································· 26 6. Results: Gross Capital Formation ······················································· 27
Ⅶ . Concluding Remarks ······························································· 29 References ······················································································ 31 Appendix: List of predictors ················································


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Title Forecasting macroeconomic variables using data dimension reduction methods
Similar Titles
Sub Title

The case of Korea

Material Type Reports
Author(English)

Jain-Chndra, Sonali; Kim, Min Jung; Park, Sung Ho; Shin, Jerome

Publisher

[Seoul]:The Bank of Korea

Date 2013-12
Series Title; No BOK Working Paper / no. 2013-26
Pages 50
Subject Country South Korea(Asia and Pacific)
Language English
File Type Documents
Original Format pdf
Subject Economy < Macroeconomics
Holding The Bank of Korea; KDI School

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. In addition to the well-known principal component analysis (PCA), we apply sparse principal component analysis (SPCA) to build a parsimonious model, and combine the estimated factors with various shrinkage methods, following Stock and Watson (2012) and Kim and Swanson (2013a), to forecast CPI inflation, GDP growth, exports, consumption and gross capital formation (GCF) of Korea from 2003:01 to 2012:12. Our major findings are that, in predicting growth rates, various hybrid models outperform benchmark models including an autoregressive model, and that this result becomes clearer as the forecast horizons lengthens. Specifically, in forecasting for more volatile periods like the global financial crisis during 2008-09, various hybrid models predict the inflection point better than AR model does.