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Thomas A. Knetsch

Personal Details

First Name:Thomas
Middle Name:A.
Last Name:Knetsch
Suffix:
RePEc Short-ID:pkn32
[This author has chosen not to make the email address public]

Affiliation

Deutsche Bundesbank

Frankfurt, Germany
http://www.bundesbank.de/

: 0 69 / 95 66 - 0
0 69 / 95 66 30 77
Postfach 10 06 02, 60006 Frankfurt
RePEc:edi:dbbgvde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Books

Working papers

  1. Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.
  2. Knetsch, Thomas A. & Nagengast, Arne J., 2016. "On the dynamics of the investment income balance," Discussion Papers 21/2016, Deutsche Bundesbank.
  3. Kajuth, Florian & Knetsch, Thomas A. & Pinkwart, Nicolas, 2013. "Assessing house prices in Germany: Evidence from an estimated stock-flow model using regional data," Discussion Papers 46/2013, Deutsche Bundesbank.
  4. Knetsch, Thomas A. & Sonderhof, Katja & Kempe, Wolfram, 2013. "Das Erwerbspersonenpotenzial zu Vollzeitäquivalenten: Messkonzept, Projektion und Anwendungsbeispiele," Discussion Papers 26/2013, Deutsche Bundesbank.
  5. Knetsch, Thomas A., 2012. "A user cost approach to capital measurement in aggregate production functions," Discussion Papers 01/2012e, Deutsche Bundesbank.
  6. Knetsch, Thomas A., 2012. "Ein nutzungskostenbasierter Ansatz zur Messung des Faktors Kapital in aggregierten Produktionsfunktionen," Discussion Papers 01/2012, Deutsche Bundesbank.
  7. Knetsch, Thomas A., 2010. "Trend and cycle features in German residential investment before and after reunification," Discussion Paper Series 1: Economic Studies 2010,10, Deutsche Bundesbank.
  8. Knetsch, Thomas A. & Molzahn, Alexander, 2009. "Supply-side effects of strong energy price hikes in German industry and transportation," Discussion Paper Series 1: Economic Studies 2009,26, Deutsche Bundesbank.
  9. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank.
  10. Knetsch, Thomas A., 2006. "Forecasting the price of crude oil via convenience yield predictions," Discussion Paper Series 1: Economic Studies 2006,12, Deutsche Bundesbank.
  11. Knetsch, Thomas A., 2005. "Short-run and long-run comovement of GDP and some expenditure aggregates in Germany, France and Italy," Discussion Paper Series 1: Economic Studies 2005,39, Deutsche Bundesbank.
  12. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo Group Munich.
  13. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.
  14. Knetsch, Thomas A., 2004. "Evaluating the German Inventory Cycle Using Data from the Ifo Business Survey," Discussion Paper Series 1: Economic Studies 2004,10, Deutsche Bundesbank.

Articles

  1. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
  2. Thomas A. Knetsch & Arne J. Nagengast, 2017. "Penny wise and pound foolish? On the income from Germany’s foreign investments," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(4), pages 753-778, November.
  3. Thomas A. Knetsch & Katja Sonderhof & Wolfram Kempe, 2014. "Das Erwerbspersonenpotenzial zu Vollzeitäquivalenten: Messkonzept, Projektion und Anwendungsbeispiele," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 134(1), pages 1-24.
  4. Knetsch Thomas A., 2013. "Ein nutzungskostenbasierter Ansatz zur Messung des Faktors Kapital in aggregierten Produktionsfunktionen / A User Cost Approach to Capital Measurement in Aggregate Production Functions," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 638-660, October.
  5. Thomas Knetsch & Alexander Molzahn, 2012. "Supply-side effects of strong energy price hikes in German industry and transportation," Empirical Economics, Springer, vol. 43(3), pages 1215-1238, December.
  6. Thomas A. Knetsch & Hans-Eggert Reimers, 2010. "Do benchmark revisions affect the consumption-to-output and investment-to-output ratios in Germany?," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-14.
  7. Thomas~A.~Knetsch, 2010. "The Bundesbank's Macroeconomic Real-time Database for the German Economy," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 130(2), pages 241-252.
  8. Thomas A. Knetsch & Hans‐Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real‐Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, April.
  9. Thomas A. Knetsch, 2007. "Forecasting the price of crude oil via convenience yield predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 527-549.
  10. Thomas Knetsch & Ulrich Hauptmanns, 2005. "Integration of Stochastic Effects and Data Uncertainties into the Design of Process Equipment," Risk Analysis, John Wiley & Sons, vol. 25(1), pages 189-198, February.

Books

  1. Derry O'Brien & Thomas Westermann & Zbigniew Krysiak & Kazimierz Kirejczyk & Michael Lea & Florian Kajuth & Thomas A. Knetsch & Nicolas Pinkwart & Guenter Karl & Andrey Tumanov & Evgeniya Zhelezova & , 2013. "Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis, 2013," NBP Conference Publications, Narodowy Bank Polski, Economic Research Department, number 1 edited by Hanna Augustyniak & Jacek Łaszek & Krzysztof Olszewski, Enero-Mar.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.

    Cited by:

    1. Götz, Thomas B. & Knetsch, Thomas A., 2017. "Google data in bridge equation models for German GDP," Discussion Papers 18/2017, Deutsche Bundesbank.
    2. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    3. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
    4. María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    5. Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.

  2. Knetsch, Thomas A. & Nagengast, Arne J., 2016. "On the dynamics of the investment income balance," Discussion Papers 21/2016, Deutsche Bundesbank.

    Cited by:

    1. Christian Grimme & Timo Wollmershäuser, 2017. "Zu den Auswirkungen von Rohstoffpreisänderungen auf den Leistungsbilanzsaldo," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(14), pages 44-46, July.
    2. Thomas A. Knetsch & Arne J. Nagengast, 2017. "Penny wise and pound foolish? On the income from Germany’s foreign investments," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(4), pages 753-778, November.
    3. Giacomo Oddo & Enrico Tosti, 2017. "The evolution of Italy’s investment income balance," Questioni di Economia e Finanza (Occasional Papers) 386, Bank of Italy, Economic Research and International Relations Area.
    4. Jannsen, Nils & Potjagailo, Galina, 2018. "Mittelfristige Projektion der Vermögenseinkommen aus grenzüberschreitenden Kapitalanlagen," IfW-Box 2018.14, Kiel Institute for the World Economy (IfW).
    5. Nierhaus. Wolfgang, 2017. "Vierteljährlicher Realwert des BIP und Terms of Trade: Ölpreisanstieg dämpft Expansion," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(09), pages 39-42, May.
    6. Fiedler, Salomon & Görg, Holger & Hornok, Cecília & Jannsen, Nils & Kooths, Stefan & Marchal, Léa & Potjagailo, Galina, 2018. "Direktinvestitionen im Ausland - Effekte auf die deutsche Leistungsbilanz und Spillovers in den Empfängerländern," Kieler Beiträge zur Wirtschaftspolitik 16, Kiel Institute for the World Economy (IfW).
    7. Timo Wollmershäuser & Wolfgang Nierhaus & Nikolay Hristov & Dorine Boumans & Marcell Göttert & Christian Grimme & S. Lauterbacher & Robert Lehmann & Wolfgang Meister & Andreas Peichl & Magnus Reif & F, 2017. "ifo Konjunkturprognose 2017/2018: Deutsche Wirtschaft stark und stabil," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(12), pages 30-83, June.
    8. Guido Baldi & Björn Bremer & Thore Schlaak, 2017. "Internationale Investitionen und Leistungsbilanzungleichgewichte: Die Bedeutung von Wertschwankungen," DIW Roundup: Politik im Fokus 117, DIW Berlin, German Institute for Economic Research.

  3. Kajuth, Florian & Knetsch, Thomas A. & Pinkwart, Nicolas, 2013. "Assessing house prices in Germany: Evidence from an estimated stock-flow model using regional data," Discussion Papers 46/2013, Deutsche Bundesbank.

    Cited by:

    1. Oestmann, Marco & Bennöhr, Lars, 2015. "Determinants of house price dynamics. What can we learn from search engine data?," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113198, Verein für Socialpolitik / German Economic Association.
    2. Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2018. "Speculative price bubbles in urban housing markets," Empirical Economics, Springer, vol. 55(4), pages 1957-1983, December.
    3. Darius Kulikauskas, 2015. "Measuring fundamental housing prices in the Baltic States: empirical approach," ERES eres2015_31, European Real Estate Society (ERES).
    4. Bienert, Sven & Sebastian, Steffen P. & Just, Tobias, . "Niedrigzinsumfeld und die Auswirkungen auf die Immobilienwirtschaft," Beiträge zur Immobilienwirtschaft, University of Regensburg, Department of Economics, number 8.
    5. Hiller, Norbert & Lerbs, Oliver W., 2016. "Aging and urban house prices," ZEW Discussion Papers 15-024, ZEW - Leibniz Centre for European Economic Research.
    6. Muellbauer, John & Geiger, Felix & Rupprecht, Manuel, 2016. "The housing market, household portfolios and the German consumer," Working Paper Series 1904, European Central Bank.
    7. Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2014. "Speculative Price Bubbles in Urban Housing Markets in Germany," Discussion Papers of DIW Berlin 1417, DIW Berlin, German Institute for Economic Research.
    8. Hana Hejlová & Michal Hlaváček & Luboš Komárek, 2017. "A Comprehensive Method for House Price Sustainability Assessment in the Czech Republic," Prague Economic Papers, University of Economics, Prague, vol. 2017(3), pages 269-285.
    9. Hiller, Norbert & Lerbs, Oliver W., 2016. "Aging and urban house prices," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 276-291.
    10. Ch. Warisse, 2017. "Analysis of the developments in residential property prices : Is the Belgian market overvalued ?," Economic Review, National Bank of Belgium, issue i, pages 61-77, June.
    11. Konstantin Kholodilin, 2015. "Speculative Bubbles in Urban Housing Markets in Germany," ERSA conference papers ersa15p67, European Regional Science Association.

  4. Knetsch, Thomas A., 2010. "Trend and cycle features in German residential investment before and after reunification," Discussion Paper Series 1: Economic Studies 2010,10, Deutsche Bundesbank.

    Cited by:

    1. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    2. Barigozzi, Matteo & Conti, Antonio & Luciani, Matteo, 2012. "Do Euro area countries respond asymmetrically to the common monetary policy?," LSE Research Online Documents on Economics 43344, London School of Economics and Political Science, LSE Library.
    3. an de Meulen, Philipp & Bauer, Thomas K. & Micheli, Martin & Schmidt, Torsten & Kiefer, Michael & Wilke, Lars-Holger & Feuerschütte, Sven, 2011. "Ein hedonischer Immobilienpreisindex auf Basis von Internetdaten 2007-2011," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 69972.
    4. Álvarez, L-J. & Bulligan, G. & Cabrero, A. & Ferrara, L. & Stahl, H., 2009. "Housing cycles in the major euro area countries," Working papers 269, Banque de France.
    5. Nombulelo Gumata & Alain Kabundi & Eliphas Ndou, 2013. "Important channels of transmission of monetary policy shock in South Africa," Working Papers 6021, South African Reserve Bank.
    6. Naik, Prasad A., 2015. "Marketing Dynamics: A Primer on Estimation and Control," Foundations and Trends(R) in Marketing, now publishers, vol. 9(3), pages 175-266, December.
    7. Young Il Kim, 2014. "Housing and business cycles in Korea: assessing the role of housing volume cycles," Chapters, in: Susan Wachter & Man Cho & Moon Joong Tcha (ed.), The Global Financial Crisis and Housing, chapter 3, pages 40-61, Edward Elgar Publishing.

  5. Knetsch, Thomas A. & Molzahn, Alexander, 2009. "Supply-side effects of strong energy price hikes in German industry and transportation," Discussion Paper Series 1: Economic Studies 2009,26, Deutsche Bundesbank.

    Cited by:

    1. Solaymani, Saeed & Kari, Fatimah, 2013. "Environmental and economic effects of high petroleum prices on transport sector," Energy, Elsevier, vol. 60(C), pages 435-441.

  6. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank.

    Cited by:

    1. Jan Jacobs & Jan-Egbert Sturm, 2009. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
    2. JoachimMöller, 2012. "From a Bulwark of Eurosclerosis to a Flexibility Champion? Why Did the German Economy and the Labour Market Do So Well During and After the Recession?," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(02), pages 14-19, August.
    3. Jan Jacobs & Jan-Egbert Sturm, 2008. "The Information Content of KOF Indicators on Swiss Current Account Data Revisions," CESifo Working Paper Series 2370, CESifo Group Munich.
    4. Boysen-Hogrefe, Jens & Neuwirth, Stefan, 2012. "The impact of seasonal and price adjustments on the predictability of German GDP revisions," Kiel Working Papers 1753, Kiel Institute for the World Economy (IfW).
    5. Thomas A. Knetsch & Hans‐Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real‐Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, April.
    6. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.

  7. Knetsch, Thomas A., 2006. "Forecasting the price of crude oil via convenience yield predictions," Discussion Paper Series 1: Economic Studies 2006,12, Deutsche Bundesbank.

    Cited by:

    1. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
    2. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    3. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    4. Reitz Stefan & Rülke Jan-Christoph & Stadtmann Georg, 2010. "Regressive Oil Price Expectations Toward More Fundamental Values of the Oil Price," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(4), pages 454-466, August.
    5. Baumeister, Christiane & Kilian, Lutz, 2013. "Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis," CFS Working Paper Series 2013/09, Center for Financial Studies (CFS).
    6. Ekaterini Panopoulou & Theologos Pantelidis, 2014. "Speculative behaviour and oil price predictability," Discussion Paper Series 2014_09, Department of Economics, University of Macedonia, revised Dec 2014.
    7. Christiane Baumeister & Lutz Kilian, 2013. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," Staff Working Papers 13-28, Bank of Canada.
    8. Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.
    9. Julien Chevallier & Benoît Sévi, 2013. "A Fear Index to Predict Oil Futures Returns," Working Papers 2013.62, Fondazione Eni Enrico Mattei.
    10. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    11. Emanuele De Meo, 2013. "Are Commodity Prices Driven by Fundamentals?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(1), pages 19-46, February.
    12. Reitz, Stefan & Ruelke, Jan & Stadtmann, Georg, 2009. "Are oil-price-forecasters finally right? -- Regressive expectations towards more fundamental values of the oil price," MPRA Paper 15607, University Library of Munich, Germany.
    13. Slabá, Monika & Gapko, Petr & Klimešová, Andrea, 2013. "Main drivers of natural gas prices in the Czech Republic after the market liberalisation," Energy Policy, Elsevier, vol. 52(C), pages 199-212.
    14. Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
    15. Funk, Christoph, 2018. "Forecasting the real price of oil - Time-variation and forecast combination," Energy Economics, Elsevier, vol. 76(C), pages 288-302.
    16. Kuper, Gerard H., 2012. "Inventories and upstream gasoline price dynamics," Energy Economics, Elsevier, vol. 34(1), pages 208-214.
    17. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    18. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    19. Carlos Caceres & Leandro Medina, 2012. "Measures of Fiscal Risk in Hydrocarbon-Exporting Countries," IMF Working Papers 12/260, International Monetary Fund.
    20. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    21. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    22. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    23. Chau, Frankie & Kuo, Jing-Ming & Shi, Yukun, 2015. "Arbitrage opportunities and feedback trading in emissions and energy markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 130-147.

  8. Knetsch, Thomas A., 2005. "Short-run and long-run comovement of GDP and some expenditure aggregates in Germany, France and Italy," Discussion Paper Series 1: Economic Studies 2005,39, Deutsche Bundesbank.

    Cited by:

    1. Dungey, Mardi & Jacobs, Jan & Tian, Jing & Norden, Simon van, 2012. "On trend-cycle decomposition and data revision," Research Report 12009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Kilian, Lutz, 2005. "The Effects of Exogenous Oil Supply Shocks on Output and Inflation: Evidence from the G7 Countries," CEPR Discussion Papers 5404, C.E.P.R. Discussion Papers.

  9. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo Group Munich.

    Cited by:

    1. Sascha Becker & Klaus Wohlrabe & Sascha O. Becker, 2007. "Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," ifo Working Paper Series 47, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.
    3. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe & Sascha O. Becker, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung: Bestand, Verwendung, Zugang," ifo Working Paper Series 44, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

  10. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.

    Cited by:

    1. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo Group Munich.
    2. Obermaier, Robert, 2012. "German inventory to sales ratios 1971–2005—An empirical analysis of business practice," International Journal of Production Economics, Elsevier, vol. 135(2), pages 964-976.
    3. Katsuyuki Shibayama, 2008. "On the Periodicity of Inventories," Studies in Economics 0806, School of Economics, University of Kent.
    4. Döpke, Jörg, 2004. "Real-time data and business cycle analysis in Germany," Discussion Paper Series 1: Economic Studies 2004,11, Deutsche Bundesbank.
    5. Knetsch, Thomas A., 2004. "Evaluating the German Inventory Cycle Using Data from the Ifo Business Survey," Discussion Paper Series 1: Economic Studies 2004,10, Deutsche Bundesbank.
    6. Warmedinger, Thomas & Vetlov, Igor, 2006. "The German block of the ESCB multi-country model," Working Paper Series 654, European Central Bank.

  11. Knetsch, Thomas A., 2004. "Evaluating the German Inventory Cycle Using Data from the Ifo Business Survey," Discussion Paper Series 1: Economic Studies 2004,10, Deutsche Bundesbank.

    Cited by:

    1. Sascha Becker & Klaus Wohlrabe & Sascha O. Becker, 2007. "Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," ifo Working Paper Series 47, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.
    3. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe & Sascha O. Becker, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung: Bestand, Verwendung, Zugang," ifo Working Paper Series 44, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

Articles

  1. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    See citations under working paper version above.
  2. Thomas A. Knetsch & Arne J. Nagengast, 2017. "Penny wise and pound foolish? On the income from Germany’s foreign investments," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(4), pages 753-778, November.
    See citations under working paper version above.
  3. Thomas Knetsch & Alexander Molzahn, 2012. "Supply-side effects of strong energy price hikes in German industry and transportation," Empirical Economics, Springer, vol. 43(3), pages 1215-1238, December. See citations under working paper version above.
  4. Thomas A. Knetsch & Hans-Eggert Reimers, 2010. "Do benchmark revisions affect the consumption-to-output and investment-to-output ratios in Germany?," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-14.

    Cited by:

    1. Dieter Brümmerhoff & Michael Grömling, 2013. "Ökonomische Auswirkungen von VGR-Revisionen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(3), pages 133-148, March.

  5. Thomas A. Knetsch & Hans‐Eggert Reimers, 2009. "Dealing with Benchmark Revisions in Real‐Time Data: The Case of German Production and Orders Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 209-235, April.

    Cited by:

    1. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
    2. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisionen der deutschen Industrieproduktion und die ifo Indikatoren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
    3. Pascal Bührig & Klaus Wohlrabe, 2016. "Forecasting revisions of German industrial production," Applied Economics Letters, Taylor & Francis Journals, vol. 23(15), pages 1062-1064, October.
    4. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    5. Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
    6. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.

  6. Thomas A. Knetsch, 2007. "Forecasting the price of crude oil via convenience yield predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 527-549. See citations under working paper version above.

Books

  1. Derry O'Brien & Thomas Westermann & Zbigniew Krysiak & Kazimierz Kirejczyk & Michael Lea & Florian Kajuth & Thomas A. Knetsch & Nicolas Pinkwart & Guenter Karl & Andrey Tumanov & Evgeniya Zhelezova & , 2013. "Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis, 2013," NBP Conference Publications, Narodowy Bank Polski, Economic Research Department, number 1 edited by Hanna Augustyniak & Jacek Łaszek & Krzysztof Olszewski, Enero-Mar.

    Cited by:

    1. Augustyniak, Hanna & Leszczyński, Robert & Łaszek, Jacek & Olszewski, Krzysztof & Waszczuk, Joanna, 2014. "On the dynamics of the primary housing market and the forecasting of house prices," MPRA Paper 61015, University Library of Munich, Germany.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 12 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-MAC: Macroeconomics (9) 2004-07-04 2006-08-05 2009-10-10 2010-07-03 2012-04-03 2012-04-03 2013-08-23 2013-11-29 2016-07-23. Author is listed
  2. NEP-ECM: Econometrics (3) 2006-08-05 2007-01-14 2017-07-09
  3. NEP-ENE: Energy Economics (2) 2006-08-05 2009-10-10
  4. NEP-FOR: Forecasting (2) 2006-08-05 2017-07-09
  5. NEP-GER: German Papers (2) 2012-04-03 2013-08-23
  6. NEP-URE: Urban & Real Estate Economics (2) 2010-07-03 2013-11-29
  7. NEP-BIG: Big Data (1) 2017-07-09
  8. NEP-EEC: European Economics (1) 2017-07-09
  9. NEP-EFF: Efficiency & Productivity (1) 2012-04-03
  10. NEP-ORE: Operations Research (1) 2017-07-09

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