Nowcasting Household Consumption and Investment in Indonesia
Keywords:
Nowcasting, Mixed Frequency Regression, Dynamic Factor Model
Abstract
It is imperative for the Central Bank to know the current state of the economy as the basis underlying projections of future economic conditions. To that end, current economic conditions, in this case household consumption and investment, could be predicted using nowcasting. In this research, a nowcasting model was developed for the two aforementioned macroeconomic variables using a Dynamic Factor Model (DFM). Theindicators used when nowcasting household consumption included: motor vehicle sales, total deposits, the lending rate on consumer loans, M1 and the rupiah exchange rate (NEER), while the indicators used for nowcasting investment included: cement sales, motor vehicle production, electric energy consumption, outstanding loans and M1. Accuracy testing showed that the nowcasting model for household consumption using DFM was sound, while the forecast error for nowcasting investment was significant but remained below the benchmark.
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References
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Angelini, Elena; Camba-Méndez, Gonzalo; Giannone, Domenico; Rünstler,
Gerhard; and Reichlin, Lucrezia. (2008). Short-Term Forecasts of Euro Area GDP Growth.ECB Working Paper Series, No. 949.
Aruoba, S. Boragan; Diebold, Francis X.; and Scotti, Chiara. “Real-Time
Measurement of Business Conditions. (2012).Journal of Business and Economic Statistics, No. 27:4.
Baffigi, Alberto; Golinelli, Roberto; and Parigi, Giuseppe. (2004). Bridge Models to Forecast the Euro Area GDP. International Journal of Forecasting, 20.
Bańbura, Marta and Rünstler, Gerhard. (2011). A Look into the Factor Model Black Box: Publication Lags and the Role of Hard and Soft Data in Forecasting GDP. International Journal of Forecasting, 27.
Bańbura, Marta; Giannone, Domenico; and Reichlin, Lucrezia. (2011). Nowcasting. The Oxford Handbook of Economic Forecasting.
Bańbura, Marta; Giannone, Domenico; Modugno, Michele; and Reichlin, Lucrezia. (2012). Now-Casting and the Real-Time Data Flow.ECARES Working Paper, No. 2012-026.
Bell, Venetia; Co, Lai Wah; Stone, Sophie; and Wallis, Gavin. (2014). Nowcasting UK GDP Growth. Bank of England Quarterly Bulletin Q1-2014.
Burns, Arthur F. and Mitchell, Wesley C. Measuring Business Cycles. (1946). New York: NBER.
Camacho, Maximo and Perez-Quiros, Gabriel. (2010). Introducing the Euro-Sting: Short-Term Indicator of Euro Area Growth. Journal of Applied Econometrics, 25(4).
Diebold, Francis X. and Rudebusch, Glenn D. (1996). Measuring Business Cycles: A Modern Perspective. The Review of Economics and Statistics, 78(1).
Doz, Catherine; Giannone, Domenico; and Reichlin, Lucrezia. (2011). A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering. Journal of Econometrics, 164.
Foroni, Claudia and Marcellino, Massimiliano. (2013). A Survey of Econometric Methods for Mixed-Frequency Data. Norges Bank Research Working Paper, No. 2013/06.
Ghysels, Eric; Santa-Clara, Pedro; and Valkanov, Rossen. (2004). The MIDAS Touch: Mixed Data Sampling Regression Models.
Giannone, Domenico; Reichlin, Lucrezia; and Small, David. (2008). Nowcasting: The Real-Time Informational Content of Macroeconomic Data.Journal of Monetary Economics, 55.
Hamilton, James D. (1994). State-Space Models in Engle, R.F. and McFadden, D.L. Handbook of Econometrics. Elsevier Science B.V.
Kurniawan, Ferry. (2015). Nowcasting Indonesian Economy. Jakarta: Bank
Indonesia.
Luciani, Matteo; Pundit, Madhavi; Ramayandi, Arief; and Veronese, Giovanni. (2015). Nowcasting Indonesia. FRB Finance and Economics Discussion Series, No. 2015-100.
Mariano, Roberto S. and Murasawa, Yasutomo. (2003). A New Coincident Index of Business Cycles Based on Monthly and Quarterly Series. Journal of Applied Econometrics, 18(4).
Mariano, Roberto S. and Murasawa, Yasutomo. (2010). A Coincident Index,
Common Factors, and Monthly Real GDP.Oxford Bulletin of Economics and
Statistics, 72(1).
OECD System of Composite Leading Indicators. (2012). OECD.
Schorfheide, Frank and Song, Dongho. (2013). Real-Time Forecasting with a Mixed-Frequency VAR. NBER Working Paper Series, No. 19712.
Sørensen, Jonas. (2011). Indicator Models for Private Consumption.Monetary Review, 1st Quarter 2011.
Stock, James H. and Watson, Mark W. (1989). New Indexes of Coincident and Leading Economic Indicators. Blanchard, Olivier Jean dan Fischer, Stanley (Eds.). NBER Macroeconomics Annual 1989, Volume 4.
The Conference Board. Business Cycle Indicators Handbook. (2001).
Published
2018-01-31
How to Cite
Tarsidin, ., Idham, ., & Rakhman, R. (2018). Nowcasting Household Consumption and Investment in Indonesia. Buletin Ekonomi Moneter Dan Perbankan, 20(3), 375-403. https://doi.org/10.21098/bemp.v20i3.858
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Buletin Ekonomi Moneter dan Perbankan / Bulletin of Monetary Economics and Banking is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
