In Choi
Dukpa Kim
Yun Jung Kim
Noh-Sun Kwark

a multilevel factor model: identification, asymptotic theory and applications (replication data)

This paper studies a multilevel factor model with global and country factors. The global factors affect all individuals, whereas the country factors affect only those within each specific country. A sequential procedure to identify the global and country factors separately is proposed. In the initial step, the global factors are estimated by canonical correlation analysis. Using this initial estimator, the principal component estimators (PCEs) of the global and country factors are constructed. It is shown that the PCEs estimate the spaces of the global and country factors consistently and are normally distributed in the limit. Several information criteria that can estimate the number of country factors are proposed. The number of global factors is assumed to be known. Extensive simulation results demonstrate that the sequential procedure and information criteria work well in finite samples. The method of this paper is applied to 25 OECD countries to identify an international business cycle. It is reported that the method extracts a global factor reasonably well.

Data and Resources

Suggested Citation

Choi, In; Kim, Dukpa; Kim, Yun Jung; Kwark, Noh-Sun (2018): A multilevel factor model: Identification, asymptotic theory and applications (replication data). Version: 1. Journal of Applied Econometrics. Dataset.