Estimating Cambodia’s Economic Conditions by Dynamic Factor Model

Kimleng Sa

Asian Journal of Economics and Empirical Research, 2020, vol. 7, issue 2, 268-281

Abstract: This study constructed a coincident indicator (CI) as the unobserved state of the economy in Cambodia by combining principal components and a dynamic factor model (DFM). In the first step, it estimated the factor loadings (coefficients of the unobserved state variables) by ordinary least squares (OLS) and feasible generalized least squares (FGLS) methods using the state variable produced by the first principal component. In the second step, it estimated the unobserved state variables through the DFM by replacing the coefficients with their estimators in the first step. Doz, Giannone, and Reichlin (2011) introduced this hybrid approach for stationary data. The coincident indicator showed that Cambodia’s economy fell below its potential level between 2016 and 2017 and started recovering after mid-2017. By exploiting the coincident index, the study examined comovement between the foreign direct investment (FDI) inflow and the state of the economy by using the autoregressive distributed lags (ARDL) model. The result showed that an acceleration of the economic condition contributed to an increase in FDI inflow in the short-term for all models; the long-term coefficient became negative. One reason for this could be the diminishing marginal product of capital that made foreign capital investment less attractive.

Keywords: Coincident indicator; Dynamic factor model; Principal components; Kalman filter; State of the economy; Foreign direct investment. (search for similar items in EconPapers)
Date: 2020
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