Composite Leading Indicators in Forecasting Inflation in Poland

Grzegorz Szafrański

doi:https://doi.org/10.59139/ps.2013.03.7

Grzegorz Szafrański Uniwersytet Łódzki oraz Instytut Ekonomiczny NBP Przegląd Statystyczny. Statistical Review, vol. 60, 2013, 3, pages: 395-416 Published online: 30 September 2013 DOI https://doi.org/10.59139/ps.2013.03.7

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ARTICLE

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ABSTRACT

We present the procedure for a systematic selection of short-term leading indicators for Polish consumer inflation (CPI) from large number of predictors. Using data set of 189 economic and financial time series (available from July 2009 to November 2012) we select the indicators highly (in-sample) correlated with future inflation from 1 to 12 months ahead. Then we perform a direct forecasting exercise on a real-time data base from December 2010 to November 2012. Compared to individual leading indicators we find that few common factors extracted from a principal component analysis (named composite leading indicators) are successful tools for predicting future inflation being precise, unbiased, and more robust to changes in a number of predictors and common factors.

KEYWORDS

leading indicators, factor analysis, inflation in Poland

REFERENCES

[1] Ang, A., Bekaert, G., Wei, M., (2007), Do Macro Variables, Asset Markets, or Surveys Forecast Inflation Better? Journal of Monetary Economics, 54 (4), 1163–1212.

[2] Angelini, E., Henry, J., Mestre, R., (2001), Diffusion Index-based Inflation Forecasts for the Euro Area. Working Paper Series 061, European Central Bank.

[3] Arratibel, O., Kamps, C., Leiner-Killinger, N., (2009), Inflation Forecasting in the New EU Member States. Working Paper Series 1015, European Central Bank.

[4] Bai, J., (2003), Inferential Theory for Factor Models of Large Dimensions, Econometrica, Elsevier, 71 (1), 135–172.

[5] Bai, J., Ng, S., (2008), Forecasting Economic Time Series Using Targeted Predictors, Journal of Econometrics, Elsevier, 146 (2), 304–317.

[6] Banerjee, A., Marcellino, M., Masten, I., (2004), Forecasting Macroeconomic Variables for the Acceding Countries. Working Papers 260, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

[7] Banerjee, A., Marcellino, M., Masten, I., (2005), Leading Indicators for Euro-Area Inflation and GDP Growth. Oxford Bulletin of Economics and Statistics, 67 (s1), 785–813.

[8] Baranowski, P., Leszczyńska, A., Szafrański, G., (2010), Krótkookresowe prognozowanie inflacji z użyciem modeli czynnikowych, Bank i Kredyt, 41 (4), 23–44.

[9] Białowolski, P., Żochowski, D., (2006), Analiza własności prognostycznych komponentów WPI, w: Drozdowicz-Bieć M., (red.), Wskaźniki wyprzedzające. Prace i Materiały Instytutu Rozwoju Gospodarczego SGH. Warszawa.

[10] Białowolski, P., Żochowski, D., (2006), Wskaźniki wyprzedzające. Prace i Materiały Instytutu Rozwoju Gospodarczego SGH, Rozdz. w: Analiza własności prognostycznych komponentów WPI, 167–197.

[11] Boivin, J., Ng, S., (2005), Understanding and Comparing Factor-Based Forecasts, International Journal of Central Banking, 1 (3), 117–151.

[12] Boivin, J., Ng, S., (2006), Are More Data Always Better for Factor Analysis?, Journal of Econometrics, Elsevier, 132(1), 169–194.

[13] Burns, A. F., Mitchell, W. C., (1946), Measuring Business Cycles, Nowy Jork, NBER.

[14] Brzoza-Brzezina, M., Kotłowski, J., (2009), Bezwzględna stopa infl acji w gospodarce polskiej, Gospodarka Narodowa, 9 (37), 1–21.

[15] Cristadoro, R., Forni, M., Reichlin, L., Veronese, G., (2005), A Core Inflation Indicator for the Euro Area, Journal of Money, Credit and Banking, 37 (3), 539–560.

[16] Doz, C., Giannone, D., Reichlin, L., (2006), A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models, Working Paper Series 674, European Central Bank.

[17] 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, 830–840.

[18] Giannone, D., Matheson, T., (2007), A New Core Inflation Indicator for New Zealand, CEPR Discussion Papers 6469.

[19] Hendry, D. F., Hubrich, K., (2006), Forecasting Economic Aggregates by Disaggregates, Working Paper Series 589, European Central Bank.

[20] Hertel, K., Leszczyńska, A., (2013), Uporczywość inflacji i jej komponentów – badanie empiryczne dla Polski, Przegląd Statystyczny, 60 (2), 187–210.

[21] Hofmann, B., (2008), Do Monetary Indicators Lead Euro Area inflation?, Working Paper Series 867, European Central Bank.

[22] 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.

[23] Kotłowski, J., (2008), Forecasting Infl ation with Dynamic Factor Model – the Case of Poland, Working Papers 24, Department of Applied Econometrics, Warsaw School of Economics.

[24] Łupiński M., (2012), Short-term Forecasting and Composite Indicators Construction with Help of Dynamic Factor Models Handling Mixed Frequencies Data with Ragged Edges, Przegląd Statystyczny, 59 (1), 48–73.

[25] Łyziak, T., Stanisławska, E., (2008), Consumer Infl ation Expectations in Europe: Some Cross-Country Comparisons, Bank i Kredyt, 39 (9), 14–28.

[26] Reis, R., Watson, M. W., (2010), Relative Goods’ Prices, Pure Inflation, and the Phillips Correlation, American Economic Journal: Macroeconomics, 2 (3), 128–157.

[27] Stock, J. H., Watson, M. W., (1989), New Indexes of Coincident and Leading Economic Indicators, w: Blanchard, O. J., Fischer, S., (red.), NBER Macroeconomics Annual 1989, 4, NBER Chapters, National Bureau of Economic Research, Inc, 351–409.

[28] Stock, J. H., Watson, M. W., (2002a), Forecasting Using Principal Components From a Large Number of Predictors, Journal of the American Statistical Association, 97 (460), 1167–1179.

[29] Stock, J. H., Watson, M. W., (2002b), Macroeconomic Forecasting Using Diffusion Indexes, Journal of Business and Economic Statistics, 20 (2), 147–162.

[30] Stock, J. H., Watson, M. W., (2003), Forecasting Output and Infl ation: The Role of Asset Prices, Journal of Economic Literature, 41 (3), 788–829.

[31] Stock, J. H., Watson, M. W., (2006), Forecasting with Many Predictors, w: Elliot G., Granger C.W.J., Timmermann A., (red.), Handbook of Economic Forecasting, Elsevier, Roz. 10 (1), 515–554.

[32] Stock, J. H., Watson, M. W., (2008), Phillips Curve Infl ation Forecasts, NBER Working Papers 14322, National Bureau of Economic Research, Inc.

[33] Szafrański G., (2011), Krótkoterminowe prognozy polskiej infl acji w oparciu o wskaźniki wyprzedzające, Materiały i Studia, Zeszyt nr 263, NBP, Warszawa.