KRED: Korea Research Economic Database for Macroeconomic Research

TL;DR

Addresses the lack of a unified Korean monthly macro panel by building KRED in a FRED-MD style from public sources. The authors apply PCA to a balanced panel to produce four interpretable factors that capture core co-movement, and they distilled these into diffusion indices to summarize major episodes. They further validate utility with factor-augmented VAR analyses showing improved monetary-policy transmission and reduced price puzzles, including clear spillovers from U.S. policy to Korea. The work delivers an open, reproducible macro-database for Korea that supports research, forecasting, and policy analysis, with plans to expand coverage and real-time vintages.

Abstract

We introduce KRED (Korea Research Economic Database), a new FRED MD style macroeconomic dataset for South Korea. KRED is constructed by aggregating 88 key monthly time series from multiple official sources (e.g., Bank of Korea ECOS, Statistics Korea KOSIS) into a unified, publicly available database. The dataset is aligned with the FRED MD format, enabling standardized transformations and direct comparability; an Appendix maps each Korean series to its FRED MD counterpart. Using a balanced panel of 80 series from 2009 to 2024, we extract four principal components via PCA that explain approximately 40% of the total variance. These four factors have intuitive economic interpretations, capturing monetary conditions, labor market activity, real output, and housing demand, analogous to diffusion indexes summarizing broad economic movements. Notably, the factor based diffusion indexes derived from KRED clearly trace major macroeconomic fluctuations over the sample period such as the 2020 COVID 19 recession. Our results demonstrate that KRED's factor structure can effectively condense complex economic information into a few informative indexes, yielding new insights into South Korea's business cycles and co movements.

Figures (8)

• Figure 1: Scree plot and cumulative variance share.
• Figure 2: Estimated principal-component factors ($r=4$).
• Figure 3: Incremental explanatory power $mR_i^2(k)$ by group ($k=1,\ldots,4$).
• Figure 4: Overall fit $R_i^2(4)$ (top 60 series).
• Figure 5: Factor-based diffusion indices.