Forecasting Economic Cycle With a Structural Equation Model: Evidence From Thailand

Abstract

The study proposes a partial least squares structural equation modeling (PLS-SEM) evaluating the relationship among composite leading indices (CLIs) to forecast the economic cycle (EC) instead of using only individual CLI. The model of quarterly data in Thailand during 2013-2018 includes five constructs representing economic sectors that have the potential to be CLIs of EC. Those are two short-term CLIs including Short-leading economic index (SLEI) and International transmission (Trade channel) (ITT). SLEI composes Narrow money, Business sentiment index (Next 3 months), and Export volume index while ITT constructs from CLI of the major export partners. The Financial cycle (FC) has the potential to be the medium-term CLI, which includes Housing price index, Household debt to GDP, and Household debt. While Monetary condition (MC) and International transmission (Monetary channel) (ITM) are the long-term CLI. MC consists of Policy interest rate and real effective exchange rate whereas ITM is represented by the global economy using CLI for OECD and non-member economies as a proxy. The evidence from the forecasting performance in the out-of-sample by PLS-SEM outperforms the alternative models for all short-term, middle-term, and long-term periods. Therefore, the study convinces to apply the PLS-SEM to forecast EC.

Covid-19 Disruption of Middle-Class Monthly Household Income and Budget

“…The government should take appropriate, timely and effective steps for the revival of the economy in such situation of crisis (Lahoti et al, 2020). The Financial cycle includes Housing price index, Household debt to GDP, and Household debt (Pumjaroen et al, 2020). The investors should not follow sentiment indicators blindly and found that aggressive stocks have high volatility and gain investor attention during optimistic and pessimistic market conditions (Yelamanchili, 2019).…”