IDEAS home Printed from https://ideas.repec.org/p/ces/ifowps/_370.html
   My bibliography  Save this paper

Quarterly GDP Estimates for the German States

Author

Listed:
  • Robert Lehmann
  • Ida Wikman

Abstract

To date, only annual information on economic activity is published for the 16 German states. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2020, thereby improving the regional database in Germany. The new data set will regularly be updated when quarterly economic growth for Germany becomes available. We use the new data for an in-depth business cycle analysis and find large heterogeneities in the duration and amplitudes of state-specific business cycles as well as in the degrees of cyclical concordance.

Suggested Citation

  • Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:ifowps:_370
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/wp-2022-370-lehmann-wikman-gdp-estimates.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
    3. Oliver Krebs, 2018. "RIOTs in Germany – Constructing an interregional input-output table for Germany," Working Papers 182, Bavarian Graduate Program in Economics (BGPE).
    4. Hochmuth, Brigitte & Kohlbrecher, Britta & Merkl, Christian & Gartner, Hermann, 2021. "Hartz IV and the decline of German unemployment: A macroeconomic evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    5. Martin Beraja & Erik Hurst & Juan Ospina, 2019. "The Aggregate Implications of Regional Business Cycles," Econometrica, Econometric Society, vol. 87(6), pages 1789-1833, November.
    6. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    7. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    8. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October.
    9. Robert Lehmann & Klaus Wohlrabe, 2017. "Boosting and regional economic forecasting: the case of Germany," Letters in Spatial and Resource Sciences, Springer, vol. 10(2), pages 161-175, July.
    10. Balleer, Almut & Gehrke, Britta & Lechthaler, Wolfgang & Merkl, Christian, 2016. "Does short-time work save jobs? A business cycle analysis," European Economic Review, Elsevier, vol. 84(C), pages 99-122.
    11. Magnus Reif, 2022. "Time‐Varying Dynamics of the German Business Cycle: A Comprehensive Investigation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 80-102, February.
    12. Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
    13. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2020. "Computationally efficient inference in large Bayesian mixed frequency VARs," Economics Letters, Elsevier, vol. 191(C).
    14. Henzel Steffen R. & Lehmann Robert & Wohlrabe Klaus, 2015. "Nowcasting Regional GDP: The Case of the Free State of Saxony," Review of Economics, De Gruyter, vol. 66(1), pages 71-98, April.
    15. Robert Lehmann & Klaus Wohlrabe, 2014. "Regional economic forecasting: state-of-the-art methodology and future challenges," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.
    16. Harding, Don & Pagan, Adrian, 2003. "A comparison of two business cycle dating methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1681-1690, July.
    17. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    18. Andrew T. Foerster & Andreas Hornstein & Pierre-Daniel G. Sarte & Mark W. Watson, 2022. "Aggregate Implications of Changing Sectoral Trends," Journal of Political Economy, University of Chicago Press, vol. 130(12), pages 3286-3333.
    19. Gießler Stefan & Heinisch Katja & Holtemöller Oliver, 2021. "(Since When) Are East and West German Business Cycles Synchronised?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(1), pages 1-28, February.
    20. Robert Lehmann & Magnus Reif, 2021. "Predicting the German Economy: Headline Survey Indices Under Test," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 215-232, November.
    21. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    22. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
    23. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-44, February.
    24. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    25. Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.
    26. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    27. Alexandra Ferreira‐Lopes & Tiago Neves Sequeira, 2011. "Business Cycles In Reunified Germany: Closer Together Or Further Apart?," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 23(2‐3), pages 94-113, July.
    28. Andrew Foerster & Andreas Hornstein & Pierre-Daniel Sarte & Mark W. Watson, 2019. "Aggregate Implications of Changing Sectoral Trends," NBER Working Papers 25867, National Bureau of Economic Research, Inc.
    29. Bokun, Kathryn O. & Jackson, Laura E. & Kliesen, Kevin L. & Owyang, Michael T., 2023. "FRED-SD: A real-time database for state-level data with forecasting applications," International Journal of Forecasting, Elsevier, vol. 39(1), pages 279-297.
    30. Joachim Ragnitz, 2019. "Thirty Years after the Berlin Wall Came Down: Economic Transition Completed, but Structural Deficit Remains," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(03), pages 22-27, October.
    31. Wolfgang Nierhaus, 2007. "Vierteljährliche volkswirtschaftliche Gesamtrechnungen für Sachsen mit Hilfe temporaler Disaggregation," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(04), pages .24-36, August.
    32. Michael Artis & Christian Dreger & Konstantin Kholodilin, 2011. "What Drives Regional Business Cycles? The Role Of Common And Spatial Components," Manchester School, University of Manchester, vol. 79(5), pages 1035-1044, September.
    33. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
    34. Konstantin Arkadievich Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2008. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 195-207.
    35. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    36. Cuevas Ángel & Quilis Enrique M. & Espasa Antoni, 2015. "Quarterly Regional GDP Flash Estimates by Means of Benchmarking and Chain Linking," Journal of Official Statistics, Sciendo, vol. 31(4), pages 627-647, December.
    37. Ulrich K. Muller & James H. Stock & Mark W. Watson, 2022. "An Econometric Model of International Growth Dynamics for Long-Horizon Forecasting," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 857-876, December.
    38. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    39. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    40. Anirban Bhattacharya & Debdeep Pati & Natesh S. Pillai & David B. Dunson, 2015. "Dirichlet--Laplace Priors for Optimal Shrinkage," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1479-1490, December.
    41. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    42. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2020. "Reconciled Estimates And Nowcasts Of Regional Output In The Uk," National Institute Economic Review, National Institute of Economic and Social Research, vol. 253, pages 44-59, August.
    43. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    44. Theodore M. Crone & Alan Clayton-Matthews, 2005. "Consistent Economic Indexes for the 50 States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 593-603, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    2. Blagov, Boris & Schmidt, Torsten C., 2022. "Schätzung der Wirtschaftsentwicklung in NRW im dritten Quartal 2022: Ein Mixed-Frequency-Ansatz," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 73(4), pages 53-59.
    3. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    4. Robert Lehmann, 2024. "A real-time regional accounts database for Germany with applications to GDP revisions and nowcasting," Empirical Economics, Springer, vol. 67(2), pages 817-838, August.
    5. Robert Lehmann & Stefan Sauer & Klaus Wohlrabe & Timo Wollmershäuser, 2022. "Gesamtwirtschafliche ifo Kapazitätsauslastungen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 29(03), pages 19-25, June.
    6. Robert Lehmann & Ida Wikman, 2023. "Eine Analyse der Konjunkturzyklen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 30(02), pages 15-21, April.
    7. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robert Lehmann, 2024. "A real-time regional accounts database for Germany with applications to GDP revisions and nowcasting," Empirical Economics, Springer, vol. 67(2), pages 817-838, August.
    2. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    3. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    4. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    5. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    6. Robert Lehmann & Ida Wikman, 2023. "Eine Analyse der Konjunkturzyklen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 30(02), pages 15-21, April.
    7. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    8. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    9. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    10. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    11. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
    12. Francis W. Ahking, 2015. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities (With Appendix A)," Working papers 2015-06, University of Connecticut, Department of Economics.
    13. Beate Schirwitz, 2013. "Business Fluctuations, Job Flows and Trade Unions - Dynamics in the Economy," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 47.
    14. Ahking, Francis W., 2014. "Measuring U.S. business cycles: A comparison of two methods and two indicators of economic activities," Journal of Economic and Social Measurement, IOS Press, issue 4, pages 199-216.
    15. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    16. Gießler Stefan & Heinisch Katja & Holtemöller Oliver, 2021. "(Since When) Are East and West German Business Cycles Synchronised?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(1), pages 1-28, February.
    17. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    18. Maria Gadea & Ana Gómez-Loscos & Antonio Montañés, 2012. "Cycles inside cycles: Spanish regional aggregation," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(4), pages 423-456, December.
    19. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, July.
    20. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.

    More about this item

    Keywords

    Regional economic activity; mixed-frequency vectorautoregression; concordance; regional business cycles; Bayesian methods;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ifowps:_370. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/ifooode.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.