Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model
a National Bank of Ukraine, Kyiv, Ukraine
Abstract

This article presents an approach for nowcasting the current value of Ukraine’s quarterly GDP. The approach uses leading indicators with a different disclosure frequency. We generalize data from a set of explanatory variables into several factors by using principal components analysis and estimate the factor-augmented VAR (FAVAR) model. Our system incorporates new data as they are published throughout a quarter to adjust GDP nowcasts. In addition, we research the influence of separate data releases on the accuracy of forecasts.

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Avaliable online 27 December 2017
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Cite as: Grui, A., Lysenko, R. (2017). Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model. Visnyk of the National Bank of Ukraine, 242, 5-13. https://doi.org/10.26531/vnbu2017.242.005
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Altissimo, F., Bassanetti, A., Cristadoro, R., Forni, M., Hallin, M., Lippi, M., Veronese, G. (2001). EuroCOIN: A real time coincident indicator of the euro area business cycle. Discussion Papers, 3108. CEPR. https://doi.org/10.2139/ssrn.1005171

Angelini, E., Camba-Mendez, G., Giannone, D., Reichlin, L., Rünstler, G. (2011). Short-term forecasts of euro area GDP growth. Econometrics Journal, 14(1), C25-C44. https://doi.org/10.1111/j.1368-423X.2010.00328.x

Artis, M. J., Banerjee, A., Marcellino, M. (2005). Factor forecasts for the UK. Journal of Forecasting, 24(4), 27-298. https://doi.org/10.1002/for.957

Banbura, M., Runstler, G. (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(2), 333-346. https://doi.org/10.1016/j.ijforecast.2010.01.011

Bernanke, B.S., Boivin, J. (2003). Monetary policy in a data-rich environment. Journal of Monetary Economics, 50(3), 525-546. https://doi.org/10.1016/S0304-3932(03)00024-2

Bernanke, B.S., Boivin, J., Eliasz, P. (2005). Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach. Quarterly Journal of Economics, 120(1), 387-422. https://doi.org/10.1162/0033553053327452

Boivin, J., Ng, S. (2005). Understanding and comparing factor-based forecasts. International Journal of Central Banking, 1(3), 117-151. Retrieved from https://www.ijcb.org/journal/ijcb05q4a4.pdf

Bragoli, D., Metelli, L., Modugno, M. (2014). The importance of updating: evidence from a Brazilian nowcasting model. Finance and Economics Discussion Series, 2014-94. Washington: Federal Reserve Board. https://doi.org/10.17016/feds.2014.94

Brave, S.A., Butters, R. A. (2014). Nowcasting using the Chicago FED national activity index. Economic Perspectives, 38, 19-37. Retrieved from https://www.chicagofed.org/publications/economic-perspectives/2014/1q-brave-butters

Breitung, J., Eickmeier, S. (2006). Dynamic factor models. Modern Econometric Analysis, 25-40. https://doi.org/10.1007/3-540-32693-6_3

Brisson, M., Campbell, B., Galbraith, J. W. (2003). Forecasting some low-predictability time series using diffusion indices. Journal of Forecasting, 22(6-7), 515-531. https://doi.org/10.1002/for.872

Cristadoro, R., Forni, M., Reichlin, L., Veronese, G. (2001). A core inflation index for the euro area. Working Papers, 435. Bank of Italy. Retrieved from https://www.bancaditalia.it/pubblicazioni/temi-discussione/2001/2001-0435/index.html

Forni, M., Giannone, D., Lippi, M., Reichlin, L. (2004). Opening the black box: structural factor models vs structural VARs. Working Paper Series, 712. European Central Bank. Retrieved from https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp712.pdf

Forni, M., Hallin, M., Lippi, M., Reichlin, L. (2005). The generalized dynamic factor model: one-sided estimation and forecasting. Journal of the American Statistical Association, 100(471), 830-840. https://doi.org/10.1198/016214504000002050

Giannone, D., Reichlin, L., Sala, L. (2004). Monetary policy in real time. NBER Macroeconomics Annual, 19, 161-200. https://doi.org/10.1086/ma.19.3585335

Giannone, D., Reichlin, L., Small, D. (2008). Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, 55(4), 665-676. https://doi.org/10.1016/j.jmoneco.2008.05.010

Giannone, D., Reichlin, L., Small, D.H. (2006). Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases. Working Paper Series, 633. European Central Bank. https://doi.org/10.17016/feds.2005.42

Gupta, R., Kabundi, A., Ziramba, E. (2010). The effect of defense spending on US output: a factor augmented vector autoregression (favar) approach. Defence and Peace Economics, 21(2), 135-147. https://doi.org/10.1080/10242690903569056

Itkonen, J. (2016). How do we know where the economy is heading today? Bank of Finland Bulletin, 90(3), 51-61.

Kaiser, H.F. (1960). The application of electronic computers to factor analysis. Educational and psychological measurement, 20(1), 141-151. https://doi.org/10.1177/001316446002000116

Kapetanios, G. (2004). A note on modelling core inflation for the UK using a new dynamic factor estimation method and a large disaggregated price index dataset. Economics Letters, 85(1), 63-69. https://doi.org/10.1016/j.econlet.2003.07.018

Lysenko, R., Kolesnichenko, N. (2016). Nowcasting of economic development indicators using the NBU's business survey results. Visnyk of the National Bank of Ukraine, 235, 43-56. https://doi.org/10.26531/vnbu2016.235.043

Porshakov, A., Deryugina, E., Ponomarenko, A. A., Sinyakov, A. (2015). Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model. Discussion Papers, 19/2015, 4-40. BOFIT Bank of Finland, https://doi.org/10.2139/ssrn.2616248

Stock, J.H., Watson, M.W. (2002). Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association, 97(460), 1167-1179. https://doi.org/10.1198/016214502388618960

Stock, J.H., Watson, M.W. (2006). Forecasting with many predictors. Handbook of Economic Forecasting, Chapter 10, 515-554. https://doi.org/10.1016/S1574-0706(05)01010-4

Stock, J.H., Watson, M.W. (1999). Forecasting inflation. Journal of Monetary Economics, 44(2), 293-335. https://doi.org/10.1016/S0304-3932(99)00027-6
 

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