Euro Area Growth Signals from Industrial Production: Warnings from a Comparison of Gross Value Added and Production

Gabe Jacob de Bondt; Stanimira Vasileva Kosekova

doi:10.1515/jbnst-2017-0136

Article

Euro Area Growth Signals from Industrial Production: Warnings from a Comparison of Gross Value Added and Production

Gabe Jacob de Bondt and Stanimira Vasileva Kosekova

Published/Copyright: October 13, 2018

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From the journal Jahrbücher für Nationalökonomie und Statistik Volume 238 Issue 6

Abstract

This study compares industrial production and gross value added in volume terms in the euro area and euro area countries, because real GDP growth signals from industrial production growth might be misleading and earlier released industrial production growth is not one-to-one translated into industrial value added growth. This is an important issue for analysts and policy makers, because industrial production is a standard element in tools for nowcasting real GDP in real time. It also raises the question about the factors explaining these differences. Differences in terms of (changes in) quarterly growth between production and gross value added include sign reversals and can last for consecutive quarters. Persistent level differences might also exist. The explanatory factors for these differences are the treatment of prices, seasonality and coverage. Data limitations prevent a detailed analysis of the price factor, but the other two factors are more closely evaluated. It turns out that the relative importance of these factors varies over time and thus is difficult to assess ex ante for a specific quarter. A remedy is that statisticians further harmonize national accounts and short-term statistics as well as national practices for seasonal adjustment.

Keywords: industrial production; industrial value added; statistical measurement; national accounts; nowcasting euro area GDP

JEL Classification: C43; C49; E23

Acknowledgment

The authors would like to acknowledge the contributions on seasonal adjustment of Sylwia Grudkowska. We are grateful for the comments from Heinz Dieden, Michal Doliak, Martin Eiglsperger, Matthias Mohr, Maria Svagrovska, and the European System of Central Banks (ESCB) Working Group on General Economic Statistics and participants of the CESS 2016 conference. The work has also benefited from feedback from Neale Kennedy, Hans-Joachim Klöckers, Henrik Schwartzlose and Caroline Willeke (all ECB). Comments from the editor and two anonymous referees are highly appreciated. Any errors or omissions are exclusively the responsibility of the authors. The views expressed are those of the authors and do not necessarily reflect those of the European Central Bank.

References

Andreoni, A., S. Upadhyaya (2014), Growth and Distribution Pattern of the World Manufacturing Output: A Statistical Profile. United Nations Industrial Development Organization Working Paper 02/2014.Search in Google Scholar

Banbura, M., D. Giannone, M. Modugno, L. Reichlin 2013, Now-Casting and the Real-Time Data Flow. In G. Elliott, A. Timmermann (Hrsg.),Handbook of Economic Forecasting. Vol. 2. ch. 4. Amsterdam: Elsevier.10.2139/ssrn.2284274Search in Google Scholar

Bengoechea, P., M. Camacho, G. Perez-Quiros 2006, A Useful Tool for Forecasting the Euro-Area Business Cycle Phases. International Journal of Forecasting 22: 735–749.10.1016/j.ijforecast.2006.01.002Search in Google Scholar

Bhatia, D.P. (1987), Estimates of Value Added at Constant Prices: An Erroneous Methodology. Weekly 22, April 18: 721–723.Search in Google Scholar

Bureau of Economic Analysis (2014), What Is Gross Output by Industry and How Does It Differ from Gross Domestic Product by Industry? April 22. Can be downloaded at: https://www.bea.gov/faq/index.cfm?faq_id=1034Search in Google Scholar

Camba-Mendez, G., G. Kapetanios, M.R. Weale, F. Papailias 2017, An Automatic Leading Indicator, Variable Reduction and Variable Selection Methods Using Small and Large Datasets: Forecasting the Industrial Production Growth for Euro Area Economies. in G.L. Mazzi, A. Ozyildirim (Hrsg.), Handbook on Cyclical Composite Indicators for Business Cycle Analysis. ch. 16. Luxembourg: United Nations and Eurostat.Search in Google Scholar

Carstensen, K., K. Wohlrabe, C. Ziegler 2011. Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production. Journal of Economics and Statistics 231 (1): 82–106.10.1515/9783110510843-006Search in Google Scholar

De Bondt, G.J. (2012), Nowcasting: Trust the Purchasing Managers’ Index or Wait for the Flash GDP Estimate?. Conference Paper, presented at EcoMod2012, International Conference on Economic Modeling, July 4-6. Seville.Search in Google Scholar

De Bondt, G.J., E. Hahn (2010), Predicting Recessions and Recoveries in Real Time: The Euro Area-Wide Leading Indicator (ALI), ECB Working Paper 1246.10.2139/ssrn.1677859Search in Google Scholar

De Bondt, G.J., E. Hahn 2014, Introducing the Euro Area-Wide Leading Indicator (ALI): Real-Time Signals of Turning Points from 2007-2011. Journal of Forecasting 33 (1): 47–68.10.1002/for.2273Search in Google Scholar

Durand, R. 1994, Alternative Estimates of Real Value Added by Industry for Canada. Economic Systems Research 8: 225–234.10.1080/09535319600000016Search in Google Scholar

European Central Bank (2004), Differences between Industrial Production and Value Added Data in Industry in the First Quarter of 2004, Monthly Bulletin, August: 40–42.Search in Google Scholar

European Central Bank 2016, A Closer Look at Differences between Industrial Gross Value Added and Industrial Production. Economic Bulletin 1: 19–22.Search in Google Scholar

European Commission (2017), ESI and Other BCS Indicators Vs PMI – Properties and Empirical Performance, Special Topic In: European Business Cycle Indicators 2nd Quarter 2017, European Economy Technical Paper 017, July, 18-26.Eurostat (2003), Methodology of short-term business statistics.Search in Google Scholar

Eurostat 2002, Methodology of Short-term Business Statistics. Luxembourg: Office for Official Publications of the European Communities, 2002. Can be downloaded at: http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-BG-02-002.Search in Google Scholar

Eurostat 2013a, European System of Accounts - ESA 2010. Luxembourg: Publications Office of the European Union, 2013. Can be downloaded at: http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-02-13-269.Search in Google Scholar

Eurostat 2013b, Handbook on Quarterly National Accounts. Luxembourg: Publications Office of the European Union, 2013. Can be downloaded at: http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-004.Search in Google Scholar

Eurostat (2016a), Building the System of National Accounts - Non-Observed Sector, Last Modified 20 September. Can be downloaded at: http://ec.europa.eu/eurostat/statistics-explained/index.php/Building_the_System_of_National_Accounts_-_non-observed_sectorSearch in Google Scholar

Eurostat 2016b, Handbook on Prices and Volume Measures in National Accounts. Luxembourg: Publications Office of the European Union, 2016. Can be downloaded at: http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-14-005.Search in Google Scholar

Girardi, A., C. Gayer, A. Reuter 2016, The Role of Survey Data in Nowcasting Euro Area GDP Growth. Journal of Forecasting 35 (5): 400–418.10.1002/for.2383Search in Google Scholar

Girardi, A., R. Golinelli, C. Pappalardo 2017, The Role of Indicator Selection in Nowcasting Euro-Area GDP in Pseudo-Real Time. Empirical Economics 53: 79–99.10.1007/s00181-016-1151-zSearch in Google Scholar

György, G., P. Van De Ven (2014), The Non-Observed Economy in the System of National Accounts. Organisation for Economic Co-Operation and Development Statistics Brief 18. Can be downloaded at: https://www.oecd.org/std/na/Statistics%20Brief%2018.pdfSearch in Google Scholar

Keeney, M., B. Kennedy, J. Liebermann 2012, The Value of Hard and Soft Data for Short-Term Forecasting of GDP. Central Bank of Ireland Economic Letter Series (2012): 11.Search in Google Scholar

Kuzin, V., M. Massimiliano, C. Schumacher 2011, MIDAS Vs. Mixed-Frequency VAR: Nowcasting GDP in the Euro Area. International Journal of Forecasting 27 (2): 529–542.10.1016/j.ijforecast.2010.02.006Search in Google Scholar

Lucke, D., J.-P. Weiß (2002), International Comparison of Industrial Development in the European Context – The Problems. Economic Bulletin 39. German Institute for Economic Research: 215–220.10.1007/BF02677743Search in Google Scholar

Mazzi, G.L., J. Mitchell, G. Montana 2014, Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession. Oxford Bulletin of Economics and Statistics 76 (2): 233–256.10.1111/obes.12015Search in Google Scholar

Organisation for Economic Co-operation and Development (2005), Overview of Industrial Statistics at the OECD, 7 April. Can be downloaded at: https://www.oecd.org/sti/ind/overviewofindustrialstatisticsattheoecd.htm.Search in Google Scholar

Vanhaelen, -J.-J., L. Dresse, J. De Mulder (2000), The Belgian Industrial Confidence Indicator: Leading Indicator of Economic Activity in the Euro Area? National Bank of Belgium Working Paper 12.10.2139/ssrn.1705085Search in Google Scholar

Waldmann, R.J. 1991, Implausible Results or Implausible Data? Anomalies in the Construction of Value-Added Data and Implications for Estimates of Price-Cost Markups. Journal of Political Economy 99: 1315–1328.10.1086/261802Search in Google Scholar

Code and Datasets

The author(s) published code and data associated with this article in the ZBW Journal Data Archive, a storage platform for datasets. See: https://doi.org/10.15456/jbnst.2018299.083130.

Received: 2017-08-30

Revised: 2018-02-19

Accepted: 2018-03-23

Published Online: 2018-10-13

Published in Print: 2018-10-25

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Articles in the same Issue

https://doi.org/10.1515/jbnst-2017-0136

Keywords for this article

industrial production; industrial value added; statistical measurement; national accounts; nowcasting euro area GDP