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...

We propose factor-based out-of-sample forecast models for the financial stress index and its 4 sub-indices developed by the Bank of Korea. We employ the method of the principal components for 198 monthly frequency macroeconomic data to extract multiple latent factors that summarize the common...

Korean Abstract: 노동시장에서의 이력현상이란 경기침체 등으로 일시적으로 증가했던 실업이 경기가 회복되어도 다시 줄어들지 않고 이전의 높은 수준으로 정착되는 현상을 말한다. 만약 노동시장에 이력현상이 존재하고...

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...

We investigate a network of financial institutions in Korea using the Korea Consumer Credit Panel (KCCP). The main contribution of this paper is that we construct the network of financial institution from the consumer credit level. We assume each consumer make a loan from multiple institutions...

Korean Abstract: 최근 들어 경제전망의 예측 오차를 줄이기 위한 방안으로 예측조합에 의한 전망(forecast combination)과 밀도함수에 의한 전망(density forecast)이 주목받고 있다. 예측조합에 의한 전망은 하나의 모형에 의한 전망이...

This paper estimates the trend inflation of Korea in the framework of an unobserved component model with allowance of outliers and stochastic volatility. The model is estimated in the univariate and the multivariate manner, which considers disaggregate inflation as an indicator of aggregate...

A number of recent studies in the economics literature have focused on the usefulness of factor models in the context of prediction using "big data". In this paper, our over-arching question is whether such "big data" are useful for modelling low frequency macroeconomic variables such as...