Analyzing and Forecasting Movements of the Philippine Economy using the Dynamic Factor Models (DFM)

Mapa, Dennis S. and Simbulan, Maria Christina (2014): Analyzing and Forecasting Movements of the Philippine Economy using the Dynamic Factor Models (DFM).

Abstract

The country’s small and open economy is vulnerable to both internal and external shocks. Is it therefore important for policy makers to have timely forecasts on the movement of the country’s Gross Domestic Product (GDP), whether it will increase or decrease in the current quarter, to be able to guide them in coming up with appropriate policies to mitigate say, the impact of a shock. The current method used to forecast the movements of the GDP is the composite Leading Economic Indicators System (LEIS) developed by the National Economic Development Authority (NEDA) and the National Statistical Coordination Board (NSCB). The LEIS, using 11 economic indicators, provides one-quarter forecast of the movement of the GDP. This paper presents an alternative, and perhaps better, procedure to the LEIS in nowcasting the movements of the GDP using the Dynamic Factor Model (DFM). The idea behind the DFM is the stylized fact that economic movements evolve in a cycle and are correlated with co-movements in a large number of economic series. The DFM is a commonly used data reduction procedure that assumes economic shocks driving economic activity arise from unobserved components or factors. The DFM aims to parsimoniously summarize information from a large number of economic series to a small number of unobserved factors. The DFM assumes that co-movements of economic series can be captured using these unobserved common factors. This paper used 31 monthly economic indicators in capturing a common factor to nowcast movements of GDP via the DFM. The results show that the common factor produced by the DFM performed better in capturing the movements of the GDP when compared with the LEIS. The DFM is a promising and useful methodology in extracting indicators of the country’s economic activity.

• Item Type: MPRA Paper
• Language: English
• Keywords: Dynamic Factor Model, Leading Economic Indicators, Common Factor
• Subjects: C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles; E - Macroeconomics and Monetary Economics > E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook > E61 - Policy Objectives ; Policy Designs and Consistency ; Policy Coordination

References

Stock, James H. and Watson W. Mark (2006), “Forecasting with many predictors”. Handbook of Economic Forecasting

Kim, Chang-Jin and Nelson, Charles R (1999),”State-Space Models with Regime Switching”. The MIT Press, Cambridge Massachusetts

Chow, Hwee Kwan and Choy, Keen Meng (2009). “Analyzing and Forecasting Business Cycle in a Small Open Economy: A Dynamic Factor Model for Singapore”. Singapore Management University

Gerlach, Stefan and Yiu, Matthew S. (2004). “A Dynamic Factor Model for Current-Quarter Estimate of Economic activity in Hong Kong”

Stock, James H. and Watson W. Mark (1991), “New Indexes of Coincident and Leading Economic Indicators”. National Bureau of Economic Research

Martin, Vance L. (1990),”Derivation of Leading Index for the United States using Kalman filters”. University of Melbourne, Parkville

Bandholz, Harm and Funke, Michael (2001), “In search of Leading Indicators of Economic Activity in Germany”. Hamburg University

Schulz,Christian (2007), “Forecasting Economic Growth for Estonia: Application of Common Factor methodologies”. Eesti Pank

Fukuda, Shin-Ichi and Onodera, Takashi (2001), “A New Composite Index of Coincident Economic Indicators in Japan: How can we improve the forecast performance”

Bersales Lisa Grace S, Reyes Regina S and de Guia John Frederick P. (2004). “A Composite Leading Indicator for the Philippines”. NSCB

Tsouma, Ekaterini (2009). “A Coincident Economic Indicator of Economic Actvity in Greece”. Center for Planning and Economic Research (KEPE)