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Malte Knüppel
(Malte Knueppel)

Personal Details

First Name:Malte
Middle Name:
Last Name:Knueppel
Suffix:
RePEc Short-ID:pkn23
[This author has chosen not to make the email address public]
https://sites.google.com/view/malteknueppel-research/home
Terminal Degree:2004 Fachbereich Volkswirtschaftslehre; Universität Hamburg (from RePEc Genealogy)

Affiliation

Deutsche Bundesbank

Frankfurt, Germany
http://www.bundesbank.de/
RePEc:edi:dbbgvde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
  2. Cecion, Martina & Coenen, Günter & Gerke, Rafael & Le Bihan, Hervé & Motto, Roberto & Aguilar, Pablo & Ajevskis, Viktors & Giesen, Sebastian & Albertazzi, Ugo & Gilbert, Niels & Al-Haschimi, Alexander, 2021. "The ECB’s price stability framework: past experience, and current and future challenges," Occasional Paper Series 269, European Central Bank.
  3. Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
  4. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
  5. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
  6. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.
  7. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
  8. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.
  9. Òscar Jordà & Malte Knuppel & Massimiliano Marcellino, 2012. "Empirical simultaneous prediction regions for path-forecasts," Working Paper Series 2012-05, Federal Reserve Bank of San Francisco.
  10. Knüppel, Malte, 2011. "Evaluating the calibration of multi-step-ahead density forecasts using raw moments," Discussion Paper Series 1: Economic Studies 2011,32, Deutsche Bundesbank.
  11. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
  12. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "Evaluating macroeconomic risk forecasts," Discussion Paper Series 1: Economic Studies 2011,14, Deutsche Bundesbank.
  13. Marcellino, Massimiliano & Knüppel, Malte & Jordà , Òscar, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," CEPR Discussion Papers 7797, C.E.P.R. Discussion Papers.
  14. Knüppel, Malte, 2009. "Efficient estimation of forecast uncertainty based on recent forecast errors," Discussion Paper Series 1: Economic Studies 2009,28, Deutsche Bundesbank.
  15. Knüppel, Malte & Schultefrankenfeld, Guido, 2008. "How informative are macroeconomic risk forecasts? An examination of the Bank of England's inflation forecasts," Discussion Paper Series 1: Economic Studies 2008,14, Deutsche Bundesbank.
  16. Knüppel, Malte, 2008. "Can capacity constraints explain asymmetries," Discussion Paper Series 1: Economic Studies 2008,01, Deutsche Bundesbank.
  17. Knüppel, Malte & Tödter, Karl-Heinz, 2007. "Quantifying risk and uncertainty in macroeconomic forecasts," Discussion Paper Series 1: Economic Studies 2007,25, Deutsche Bundesbank.
  18. Knüppel, Malte, 2004. "Testing for business cycle asymmetries based on autoregressions with a Markov-switching intercept," Discussion Paper Series 1: Economic Studies 2004,41, Deutsche Bundesbank.

Articles

  1. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
  2. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
  3. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
  4. Knüppel, Malte, 2018. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, vol. 34(1), pages 105-116.
  5. Knüppel Malte, 2017. "Graham Elliott and Allan Timmermann: Economic Forecasting," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 63-65, February.
  6. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
  7. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
  8. Knüppel, Malte, 2014. "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, vol. 30(2), pages 257-267.
  9. Knüppel, Malte, 2014. "Can Capacity Constraints Explain Asymmetries Of The Business Cycle?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 65-92, January.
  10. Jordà, Òscar & Knüppel, Malte & Marcellino, Massimiliano, 2013. "Empirical simultaneous prediction regions for path-forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 456-468.
  11. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
  12. Knüppel, Malte, 2009. "Testing Business Cycle Asymmetries Based on Autoregressions With a Markov-Switching Intercept," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 544-552.

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. Cecion, Martina & Coenen, Günter & Gerke, Rafael & Le Bihan, Hervé & Motto, Roberto & Aguilar, Pablo & Ajevskis, Viktors & Giesen, Sebastian & Albertazzi, Ugo & Gilbert, Niels & Al-Haschimi, Alexander, 2021. "The ECB’s price stability framework: past experience, and current and future challenges," Occasional Paper Series 269, European Central Bank.

    Cited by:

    1. Corbisiero, Giuseppe & Lawton, Neil, 2021. "The ECB’s Review of its Monetary Policy Strategy," Quarterly Bulletin Articles, Central Bank of Ireland, pages 70-103, October.
    2. Gerdesmeier, Dieter & Reimers, Hans-Eggert & Roffia, Barbara, 2023. "Investigating the inflation-output-nexus for the euro area: Old questions and new results," Wismar Discussion Papers 01/2023, Hochschule Wismar, Wismar Business School.
    3. Hans-Eggert Reimers & Dieter Gerdesmeier & Barbara Roffia, 2023. "Investigating the Inflation–Output Nexus for the Euro Area: Old Questions and New Results," Economies, MDPI, vol. 11(11), pages 1-15, October.
    4. BENIGNO, Pierpaolo & CANOFARI, Paola & DI BARTOLOMEO, Giovanni & MESSORI, Marcello, 2023. "The ECB’s new inflation target from a short- and long-term perspective," Working Papers 2023006, University of Antwerp, Faculty of Business and Economics.
    5. Gerke, Rafael & Kienzler, Daniel & Scheer, Alexander, 2022. "On the macroeconomic effects of reinvestments in asset purchase programmes," Discussion Papers 47/2022, Deutsche Bundesbank.
    6. Stéphane Dupraz & Hervé Le Bihan & Julien Matheron, 2022. "Make-up Strategies with Finite Planning Horizons but Forward-Looking Asset Prices," Working Papers 2218, Banco de España.
    7. Brand, Claus & Obstbaum, Meri & Coenen, Günter & Sondermann, David & Lydon, Reamonn & Ajevskis, Viktors & Hammermann, Felix & Angino, Siria & Hernborg, Nils & Basso, Henrique & Hertweck, Matthias & Bi, 2021. "Employment and the conduct of monetary policy in the euro area," Occasional Paper Series 275, European Central Bank.
    8. Debrun, Xavier & Masuch, Klaus & Ferrero, Guiseppe & Vansteenkiste, Isabel & Ferdinandusse, Marien & von Thadden, Leopold & Hauptmeier, Sebastian & Alloza, Mario & Derouen, Chloé & Bańkowski, Krzyszto, 2021. "Monetary-fiscal policy interactions in the euro area," Occasional Paper Series 273, European Central Bank.
    9. Edouard Djeutem & Mario He & Abeer Reza & Yang Zhang, 2022. "Household Heterogeneity and the Performance of Monetary Policy Frameworks," Staff Working Papers 22-12, Bank of Canada.
    10. Lucian Briciu & Stefan Hohberger & Luca Onorante & Beatrice Pataracchia & Marco Ratto & Lukas Vogel, 2023. "The ECB Strategy Review - Implications for the Space of Monetary Policy," European Economy - Discussion Papers 193, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    11. Eleni Argiri & Ifigeneia Skotida, 2021. "The 2021 review of the monetary policy strategy of the Eurosystem: an economy of forces," Economic Bulletin, Bank of Greece, issue 54, pages 23-57, December.
    12. Martina Cecioni & Adriana Grasso & Alessandro Notarpietro & Massimiliano Pisani, 2021. "Revisiting monetary policy objectives and strategies: international experience and challenges from the ELB," Questioni di Economia e Finanza (Occasional Papers) 660, Bank of Italy, Economic Research and International Relations Area.
    13. Ignazio Visco, 2023. "Inflation Expectations and Monetary Policy in the Euro Area," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 51(2), pages 111-129, September.
    14. Dobrew, Michael & Gerke, Rafael & Kienzler, Daniel & Schwemmer, Alexander, 2023. "Monetary policy rules under bounded rationality," Discussion Papers 18/2023, Deutsche Bundesbank.

  2. Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.

    Cited by:

    1. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    2. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    3. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

  3. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.

    Cited by:

    1. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.

  4. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.

    Cited by:

    1. Stamer, Vincent, 2022. "Thinking Outside the Container: A Sparse Partial Least Squares Approach to Forecasting Trade Flows," VfS Annual Conference 2022 (Basel): Big Data in Economics 264096, Verein für Socialpolitik / German Economic Association.
    2. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    3. Jean-Yves Pitarakis, 2023. "Direct Multi-Step Forecast based Comparison of Nested Models via an Encompassing Test," Papers 2312.16099, arXiv.org.
    4. Zhu, Tiantian & Haugen, Stein & Liu, Yiliu & Yang, Xue, 2023. "A value of prediction model to estimate optimal response time to threats for accident prevention," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Carola Binder & Tucker S. Mcelroy & Xuguang S. Sheng, 2022. "The Term Structure of Uncertainty: New Evidence from Survey Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(1), pages 39-71, February.
    6. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
    7. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    8. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    9. Suarez, Javier & ,, 2018. "The Procyclicality of Expected Credit Loss Provisions," CEPR Discussion Papers 13135, C.E.P.R. Discussion Papers.
    10. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    11. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    12. Kuethe, Todd H. & Regmi, Hari, 2023. "An Evaluation of Congressional Budget Office’s Baseline Projections of USDA Mandatory Farm and Nutrition Programs," 2023 Annual Meeting, July 23-25, Washington D.C. 335690, Agricultural and Applied Economics Association.
    13. Jörg Döpke & Karsten Müller & Lars Tegtmeier, 2023. "Moments of cross‐sectional stock market returns and the German business cycle," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(2), July.

  5. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.

    Cited by:

    1. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    3. Joscha Beckmann & Robert L. Czudaj, 2022. "Fundamental determinants of exchange rate expectations," Chemnitz Economic Papers 056, Department of Economics, Chemnitz University of Technology, revised Mar 2022.
    4. Joscha Beckmann & Robert L. Czudaj, 2018. "Monetary Policy Shocks, Expectations, And Information Rigidities," Economic Inquiry, Western Economic Association International, vol. 56(4), pages 2158-2176, October.
    5. Barbara Rossi & Tatevik Sekhposyan, 2017. "Macroeconomic uncertainty indices for the Euro Area and its individual member countries," Empirical Economics, Springer, vol. 53(1), pages 41-62, August.
    6. Hoffmann, Mathias & Hürtgen, Patrick, 2016. "Inflation expectations, disagreement, and monetary policy," Discussion Papers 31/2016, Deutsche Bundesbank.
    7. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    8. Juan Camilo Galvis Ciro & Juan Camilo Anzoátegui Zapata, 2019. "Disagreement in inflation expectations: empirical evidence for Colombia," Applied Economics, Taylor & Francis Journals, vol. 51(40), pages 4411-4424, August.
    9. Camba-Méndez, Gonzalo & Werner, Thomas, 2017. "The inflation risk premium in the post-Lehman period," Working Paper Series 2033, European Central Bank.
    10. Boonlert Jitmaneeroj & Michael Lamla, 2018. "The Implications of Central Bank Transparency for Uncertainty and Disagreement," KOF Working papers 18-445, KOF Swiss Economic Institute, ETH Zurich.
    11. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    12. Heinisch, Katja & Behrens, Christoph & Döpke, Jörg & Foltas, Alexander & Fritsche, Ulrich & Köhler, Tim & Müller, Karsten & Puckelwald, Johannes & Reichmayr, Hannes, 2023. "The IWH Forecasting Dashboard: From forecasts to evaluation and comparison," IWH Technical Reports 1/2023, Halle Institute for Economic Research (IWH).
    13. Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
    14. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
    15. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.

  6. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.

    Cited by:

    1. Travis J. Berge, 2023. "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1191-1206, September.
    2. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    3. MORIKAWA Masayuki, 2019. "Uncertainty in Long-Term Macroeconomic Forecasts: Ex post Evaluation of Forecasts by Economics Researchers," Discussion papers 19084, Research Institute of Economy, Trade and Industry (RIETI).

  7. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.

    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.
    3. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    4. Monica Jain & Christopher S. Sutherland, 2018. "How Do Central Bank Projections and Forward Guidance Influence Private-Sector Forecasts?," Staff Working Papers 18-2, Bank of Canada.
    5. Otmar Issing, 2013. "A New Paradigm for Monetary Policy?," International Finance, Wiley Blackwell, vol. 16(2), pages 273-288, June.
    6. Guido Schultefrankenfeld, 2020. "Appropriate monetary policy and forecast disagreement at the FOMC," Empirical Economics, Springer, vol. 58(1), pages 223-255, January.
    7. Issing, Otmar, 2013. "A new paradigm for monetary policy?," CFS Working Paper Series 2013/02, Center for Financial Studies (CFS).
    8. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    9. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    10. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    11. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.

  8. Òscar Jordà & Malte Knuppel & Massimiliano Marcellino, 2012. "Empirical simultaneous prediction regions for path-forecasts," Working Paper Series 2012-05, Federal Reserve Bank of San Francisco.

    Cited by:

    1. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    2. Svetlana Makarova, 2014. "Risk and Uncertainty: Macroeconomic Perspective," UCL SSEES Economics and Business working paper series 129, UCL School of Slavonic and East European Studies (SSEES).
    3. David F. Hendry & Felix Pretis, 2020. "Analyzing Differences between Scenarios," Economics Papers 2020-W05, Economics Group, Nuffield College, University of Oxford.
    4. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    7. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    8. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
    9. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    10. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

  9. Knüppel, Malte, 2011. "Evaluating the calibration of multi-step-ahead density forecasts using raw moments," Discussion Paper Series 1: Economic Studies 2011,32, Deutsche Bundesbank.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    3. Dillschneider, Yannick & Maurer, Raimond, 2019. "Functional Ross recovery: Theoretical results and empirical tests," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    4. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    5. Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
    6. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    7. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    8. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    9. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
    10. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    11. Gelain, Paolo & Iskrev, Nikolay & J. Lansing, Kevin & Mendicino, Caterina, 2019. "Inflation dynamics and adaptive expectations in an estimated DSGE model," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 258-277.
    12. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    13. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    14. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    15. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    16. Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
    17. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    18. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    19. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    20. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
    21. James Mitchell & Martin Weale, 2021. "Censored Density Forecasts: Production and Evaluation," Working Papers 21-12R, Federal Reserve Bank of Cleveland, revised 16 Aug 2022.
    22. Christian Pape & Arne Vogler & Oliver Woll & Christoph Weber, 2017. "Forecasting the distributions of hourly electricity spot prices," EWL Working Papers 1705, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised May 2017.
    23. Jackwerth, Jens Carsten & Menner, Marco, 2020. "Does the Ross recovery theorem work empirically?," Journal of Financial Economics, Elsevier, vol. 137(3), pages 723-739.
    24. Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal, 2020. "Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height," International Journal of Forecasting, Elsevier, vol. 36(2), pages 515-530.
    25. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.

  10. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.

    Cited by:

    1. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    2. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.
    3. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    4. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
    5. Galbraith, John W. & van Norden, Simon, 2019. "Asymmetry in unemployment rate forecast errors," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1613-1626.
    6. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    7. Andrade, P. & Ghysels, E. & Idier, J., 2012. "Tails of Inflation Forecasts and Tales of Monetary Policy," Working papers 407, Banque de France.
    8. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    9. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    10. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    11. Juan C. Méndez-Vizcaíno & Alexander Guarin & César Anzola-Bravo & Anderson Grajales-Olarte, 2021. "Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia," Borradores de Economia 1178, Banco de la Republica de Colombia.
    12. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    13. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    14. Tsuchiya, Yoichi, 2022. "Evaluating the European Central Bank’s uncertainty forecasts," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 321-330.
    15. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    16. Yoichi Tsuchiya, 2021. "The value added of the Bank of Japan's range forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 817-833, August.
    17. Andrew Binning & Junior Maih, 2016. "Forecast uncertainty in the neighborhood of the effective lower bound: How much asymmetry should we expect?," Working Paper 2016/13, Norges Bank.
    18. G. Kenny, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 500-504, October.
    19. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    20. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).

  11. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "Evaluating macroeconomic risk forecasts," Discussion Paper Series 1: Economic Studies 2011,14, Deutsche Bundesbank.

    Cited by:

    1. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
    2. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.

  12. Marcellino, Massimiliano & Knüppel, Malte & Jordà , Òscar, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," CEPR Discussion Papers 7797, C.E.P.R. Discussion Papers.

    Cited by:

    1. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    2. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    3. Tara Sinclair & Herman O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-2, The George Washington University, Institute for International Economic Policy.
    4. Svetlana Makarova, 2014. "Risk and Uncertainty: Macroeconomic Perspective," UCL SSEES Economics and Business working paper series 129, UCL School of Slavonic and East European Studies (SSEES).
    5. Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    6. David F. Hendry & Felix Pretis, 2020. "Analyzing Differences between Scenarios," Economics Papers 2020-W05, Economics Group, Nuffield College, University of Oxford.
    7. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    10. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
    11. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based priors for BVARs and quasi-Bayesian DSGE estimation," Bank of England working papers 716, Bank of England.
    12. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    13. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.
    14. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
    15. Thomai Filippeli, 2011. "Theoretical Priors for BVAR Models & Quasi-Bayesian DSGE Model Estimation," 2011 Meeting Papers 396, Society for Economic Dynamics.
    16. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    17. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based Priors for BVARs & Quasi-Bayesian DSGE Estimation," Cardiff Economics Working Papers E2018/5, Cardiff University, Cardiff Business School, Economics Section.
    18. Michael Wolf & Dan Wunderli, 2012. "Bootstrap joint prediction regions," ECON - Working Papers 064, Department of Economics - University of Zurich, revised May 2013.
    19. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

  13. Knüppel, Malte, 2009. "Efficient estimation of forecast uncertainty based on recent forecast errors," Discussion Paper Series 1: Economic Studies 2009,28, Deutsche Bundesbank.

    Cited by:

    1. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    2. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    3. Travis J. Berge, 2023. "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1191-1206, September.
    4. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    5. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    6. Knüppel, Malte, 2014. "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, vol. 30(2), pages 257-267.
    7. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).

  14. Knüppel, Malte & Schultefrankenfeld, Guido, 2008. "How informative are macroeconomic risk forecasts? An examination of the Bank of England's inflation forecasts," Discussion Paper Series 1: Economic Studies 2008,14, Deutsche Bundesbank.

    Cited by:

    1. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.
    2. Bratu, Mihaela, 2013. "The Assessment And Improvement Of The Accuracy For The Forecast Intervals," Working Papers of Macroeconomic Modelling Seminar 132602, Institute for Economic Forecasting.
    3. Tura-Gawron, Karolina, 2019. "Consumers’ approach to the credibility of the inflation forecasts published by central banks: A new methodological solution," Journal of Macroeconomics, Elsevier, vol. 62(C).
    4. Mihaela BRATU, 2012. "The prediction of inflation in Romania in uncertainty conditions," EuroEconomica, Danubius University of Galati, issue 1(31), pages 87-94, February.

  15. Knüppel, Malte, 2008. "Can capacity constraints explain asymmetries," Discussion Paper Series 1: Economic Studies 2008,01, Deutsche Bundesbank.

    Cited by:

    1. Baum, Anja & Koester, Gerrit B., 2011. "The impact of fiscal policy on economic activity over the business cycle - evidence from a threshold VAR analysis," Discussion Paper Series 1: Economic Studies 2011,03, Deutsche Bundesbank.
    2. Moritz A. Roth, 2018. "International co-movements in recessions," Working Papers 1804, Banco de España.
    3. Chacko George & Florian Kuhn, 2019. "Business Cycle Implications of Capacity Constraints under Demand Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 94-121, April.
    4. Atolia, Manoj & Gibson, John & Marquis, Milton, 2018. "Asymmetry And The Amplitude Of Business Cycle Fluctuations: A Quantitative Investigation Of The Role Of Financial Frictions," Macroeconomic Dynamics, Cambridge University Press, vol. 22(2), pages 279-306, March.
    5. Xu Zhang & Xiaoxing Liu & Jianqin Hang & Dengbao Yao, 2018. "The dynamic causality between commodity prices, inflation and output in China: a bootstrap rolling window approach," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 407-425, January.

  16. Knüppel, Malte & Tödter, Karl-Heinz, 2007. "Quantifying risk and uncertainty in macroeconomic forecasts," Discussion Paper Series 1: Economic Studies 2007,25, Deutsche Bundesbank.

    Cited by:

    1. Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.

  17. Knüppel, Malte, 2004. "Testing for business cycle asymmetries based on autoregressions with a Markov-switching intercept," Discussion Paper Series 1: Economic Studies 2004,41, Deutsche Bundesbank.

    Cited by:

    1. Almeida, Pedro Cameira de & Fuinhas, José Alberto & Marques, António Cardoso, 2011. "A assimetria dos ciclos económicos: Evidência internacional usando o teste triples [The asymmetry of business cycles: International evidence using triples test]," MPRA Paper 35208, University Library of Munich, Germany.
    2. Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Staff Working Papers 07-38, Bank of Canada.
    3. Narayan, Paresh Kumar & Popp, Stephan, 2009. "Investigating business cycle asymmetry for the G7 countries: Evidence from over a century of data," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 583-591, October.
    4. Alexandra Krystalogianni & Sotiris Tsolacos, 2005. "Regime switching in yield structures and real estate investment," Journal of Property Research, Taylor & Francis Journals, vol. 21(4), pages 279-299, May.
    5. Apergis, Nicholas & Eleftheriou, Sofia, 2016. "Gold returns: Do business cycle asymmetries matter? Evidence from an international country sample," Economic Modelling, Elsevier, vol. 57(C), pages 164-170.

Articles

  1. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    See citations under working paper version above.
  2. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
    See citations under working paper version above.
  3. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    See citations under working paper version above.
  4. Knüppel, Malte, 2018. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, vol. 34(1), pages 105-116.
    See citations under working paper version above.
  5. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
    See citations under working paper version above.
  6. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    See citations under working paper version above.
  7. Knüppel, Malte, 2014. "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, vol. 30(2), pages 257-267.
    See citations under working paper version above.
  8. Knüppel, Malte, 2014. "Can Capacity Constraints Explain Asymmetries Of The Business Cycle?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 65-92, January.
    See citations under working paper version above.
  9. Jordà, Òscar & Knüppel, Malte & Marcellino, Massimiliano, 2013. "Empirical simultaneous prediction regions for path-forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 456-468.
    See citations under working paper version above.
  10. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    See citations under working paper version above.
  11. Knüppel, Malte, 2009. "Testing Business Cycle Asymmetries Based on Autoregressions With a Markov-Switching Intercept," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 544-552.
    See citations under working paper version above.Sorry, no citations of articles recorded.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 18 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-FOR: Forecasting (16) 2007-11-03 2008-09-20 2009-11-07 2010-05-22 2012-02-20 2012-06-13 2013-04-27 2014-02-02 2015-01-31 2016-08-21 2017-11-05 2018-05-21 2019-02-11 2019-09-02 2023-01-09 2023-02-06. Author is listed
  2. NEP-ECM: Econometrics (10) 2007-11-03 2009-11-07 2010-05-22 2012-02-20 2012-06-13 2015-01-31 2017-11-05 2018-05-21 2019-09-02 2023-01-09. Author is listed
  3. NEP-CBA: Central Banking (7) 2008-03-25 2008-09-20 2010-05-22 2013-04-27 2014-02-02 2019-02-11 2021-09-27. Author is listed
  4. NEP-MAC: Macroeconomics (7) 2007-11-03 2008-03-25 2008-09-20 2012-06-13 2014-02-02 2016-08-21 2021-09-27. Author is listed
  5. NEP-MON: Monetary Economics (5) 2008-09-20 2013-04-27 2014-02-02 2019-02-11 2021-09-27. Author is listed
  6. NEP-ETS: Econometric Time Series (3) 2009-11-07 2012-02-20 2018-05-21
  7. NEP-RMG: Risk Management (2) 2008-09-20 2023-01-09
  8. NEP-DGE: Dynamic General Equilibrium (1) 2008-03-25
  9. NEP-EEC: European Economics (1) 2021-09-27
  10. NEP-ISF: Islamic Finance (1) 2021-09-27

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