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Rolf Scheufele

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. 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).

    Cited by:

    1. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    2. Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. 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.

  2. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.

    Cited by:

    1. Erhan Uluceviz & Kamil Yilmaz, 2020. "Real-financial connectedness in the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-20, December.
    2. Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    3. Santiago Etchegaray Alvarez, 2022. "Proyecciones macroeconómicas con datos en frecuencias mixtas. Modelos ADL-MIDAS, U-MIDAS y TF-MIDAS con aplicaciones para Uruguay," Documentos de trabajo 2022004, Banco Central del Uruguay.
    4. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    5. Chikamatsu, Kyosuke & Hirakata, Naohisa & Kido, Yosuke & Otaka, Kazuki, 2021. "Mixed-frequency approaches to nowcasting GDP: An application to Japan," Japan and the World Economy, Elsevier, vol. 57(C).
    6. Liudmila Kitrar & Tamara Lipkind, 2021. "Assessment Of GDP Growth After The Corona Crisis Using The Results Of Business And Consumer Surveys," HSE Working papers WP BRP 118/STI/2021, National Research University Higher School of Economics.

  3. Gregor Bäurle & Rolf Scheufele, 2016. "Credit cycles and real activity - the Swiss case," Working Papers 2016-13, Swiss National Bank.

    Cited by:

    1. Josef Bajzik & Jan Janku & Simona Malovana & Klara Moravcova & Ngoc Anh Ngo, 2023. "Monetary Policy Has a Long-Lasting Impact on Credit: Evidence from 91 VAR Studies," Working Papers 2023/19, Czech National Bank.
    2. Guevara, Carlos & Rodríguez, Gabriel, 2020. "The role of credit supply shocks in pacific alliance countries: A TVP-VAR-SV approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

  4. Sandra Hanslin Grossmann & Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.

    Cited by:

    1. Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. 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.

  5. Hanslin Grossmann, Sandra & Scheufele, Rolf, 2015. "Foreign PMIs: A reliable indicator for Swiss exports," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112830, Verein für Socialpolitik / German Economic Association.

    Cited by:

    1. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    2. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Radoslaw Sobko & Maria Klonowska-Matynia, 2021. "The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 198-219.

  6. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    2. Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," IREA Working Papers 201821, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    3. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    4. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    5. Klaus Abberger & Matthias Bannert & Andreas Dibiasi, 2014. "Metaumfrage im Dienstleistungssektor," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 8(2), pages 51-62, June.
    6. Bialowolski, Piotr & Kuszewski, Tomasz & Witkowski, Bartosz, 2015. "Bayesian averaging vs. dynamic factor models for forecasting economic aggregates with tendency survey data," Economics Discussion Papers 2015-28, Kiel Institute for the World Economy (IfW Kiel).
    7. Kristian Jönsson, 2020. "Machine Learning and Nowcasts of Swedish GDP," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 123-134, November.
    8. W. Hölzl & S. Kaniovski & Y. Kaniovski, 2019. "Exploring the dynamics of business survey data using Markov models," Computational Management Science, Springer, vol. 16(4), pages 621-649, October.
    9. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas & Irena Pekarskiene, 2024. "Future directions in nowcasting economic activity: A systematic literature review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1199-1233, September.
    10. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.
    11. Kristian Jönsson, 2024. "Neighbor Weighting and Distance Metrics in Nearest Neighbor Nowcasting of Swedish GDP," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(4), pages 1077-1089, December.
    12. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    13. Daniel Roash & Tanya Suhoy, 2019. "Sentiment Indicators Based on a Short Business Tendency Survey," Bank of Israel Working Papers 2019.11, Bank of Israel.
    14. Sandra Hanslin Grossmann & Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.

  7. Rina Rosenblatt-Wisch & Rolf Scheufele, 2014. "Quantification and characteristics of household inflation expectations in Switzerland," Working Papers 2014-11, Swiss National Bank.

    Cited by:

    1. Łyziak, Tomasz & Paloviita, Maritta, 2016. "Anchoring of inflation expectations in the euro area: recent evidence based on survey data," Working Paper Series 1945, European Central Bank.
    2. Tomasz Lyziak, 2016. "Financial crisis, low inflation environment and short-term inflation expectations in Poland," Bank i Kredyt, Narodowy Bank Polski, vol. 47(3), pages 285-300.
    3. Mellina, Sathya & Schmidt, Tobias, 2018. "The role of central bank knowledge and trust for the public's inflation expectations," Discussion Papers 32/2018, Deutsche Bundesbank.
    4. Nitschka Thomas & Markov Nikolay, 2016. "Semi-Parametric Estimates of Taylor Rules for a Small, Open Economy – Evidence from Switzerland," German Economic Review, De Gruyter, vol. 17(4), pages 478-490, December.
    5. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.
    6. Alain Galli, 2016. "How reliable are cointegration-based estimates for wealth effects on consumption? Evidence from Switzerland," Working Papers 2016-03, Swiss National Bank.
    7. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    8. Tomasz Łyziak, 2016. "The impact of financial crisis and low inflation environment on short-term inflation expectations in Poland," NBP Working Papers 235, Narodowy Bank Polski.
    9. Koichiro Kamada & Jouchi Nakajima & Shusaku Nishiguchi, 2015. "Are Household Inflation Expectations Anchored in Japan?," Bank of Japan Working Paper Series 15-E-8, Bank of Japan.
    10. Gießler, Stefan, 2020. "The evolution of monetary policy in Latin American economies: Responsiveness to inflation under different degrees of credibility," IWH Discussion Papers 9/2020, Halle Institute for Economic Research (IWH).

  8. Katja Drechsel & Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.

    Cited by:

    1. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    2. Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo.
    3. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
    5. Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017. "Nowcasting des deutschen BIP," Weidener Diskussionspapiere 59, University of Applied Sciences Amberg-Weiden (OTH).
    6. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    7. Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    8. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    10. Cobb, Marcus P A, 2017. "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper 76556, University Library of Munich, Germany.
    11. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    12. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    13. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    14. Hanslin Grossmann, Sandra & Scheufele, Rolf, 2015. "Foreign PMIs: A reliable indicator for Swiss exports," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112830, Verein für Socialpolitik / German Economic Association.
    15. Holtemöller, Oliver & Kozyrev, Boris, 2024. "Forecasting economic activity using a neural network in uncertain times: Monte Carlo evidence and application to the German GDP," IWH Discussion Papers 6/2024, Halle Institute for Economic Research (IWH).
    16. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    17. Jokubaitis, Saulius & Celov, Dmitrij & Leipus, Remigijus, 2021. "Sparse structures with LASSO through principal components: Forecasting GDP components in the short-run," International Journal of Forecasting, Elsevier, vol. 37(2), pages 759-776.
    18. Robert Lehmann & Klaus Wohlrabe, 2012. "Forecasting GDP at the Regional Level with Many Predictors," CESifo Working Paper Series 3956, CESifo.
    19. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
    20. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    21. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    22. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    23. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    24. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    25. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    26. Weber, Enzo & Zika, Gerd, 2013. "Labour market forecasting : is disaggregation useful?," IAB-Discussion Paper 201314, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    27. Dées, Stéphane & Güntner, Jochen, 2014. "Analysing and forecasting price dynamics across euro area countries and sectors: a panel VAR approach," Working Paper Series 1724, European Central Bank.
    28. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    29. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    30. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    31. Larson, William D. & Sinclair, Tara M., 2022. "Nowcasting unemployment insurance claims in the time of COVID-19," International Journal of Forecasting, Elsevier, vol. 38(2), pages 635-647.
    32. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas & Irena Pekarskiene, 2024. "Future directions in nowcasting economic activity: A systematic literature review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1199-1233, September.
    33. Schumacher, Christian, 2014. "MIDAS regressions with time-varying parameters: An application to corporate bond spreads and GDP in the Euro area," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100289, Verein für Socialpolitik / German Economic Association.
    34. Saulius Jokubaitis & Dmitrij Celov & Remigijus Leipus, 2019. "Sparse structures with LASSO through Principal Components: forecasting GDP components in the short-run," Papers 1906.07992, arXiv.org, revised Oct 2020.
    35. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.
    36. 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.
    37. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    38. Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    39. Sandra Hanslin Grossmann & Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.
    40. Mahmut Gunay, 2016. "Forecasting Turkish GDP Growth : Bottom-Up vs Direct?," CBT Research Notes in Economics 1622, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    41. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    42. Marcus Cobb, 2014. "GDP Forecasting Bias due to Aggregation Inaccuracy in a Chain- Linking Framework," Working Papers Central Bank of Chile 721, Central Bank of Chile.
    43. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.

  9. Drechsel, Katja & Scheufele, Rolf, 2011. "The Financial Crisis from a Forecaster’s Perspective," IWH Discussion Papers 5/2011, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    2. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    3. Drechsel, Katja & Giesen, Sebastian & Lindner, Axel, 2014. "Outperforming IMF Forecasts by the Use of Leading Indicators," IWH Discussion Papers 4/2014, Halle Institute for Economic Research (IWH).
    4. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
    6. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.

  10. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52.
    2. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    3. Agne Reklaite, 2015. "Globalisation Effect Measure Via Hierarchical Dynamic Factor Modelling," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 10(3), pages 139-149, September.
    4. Drechsel, Katja & Scheufele, Rolf, 2011. "The Financial Crisis from a Forecaster’s Perspective," IWH Discussion Papers 5/2011, Halle Institute for Economic Research (IWH).
    5. Máximo Camacho & Gonzalo Palmieri, 2021. "Evaluating the OECD’s main economic indicators at anticipating recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 80-93, January.
    6. Anna Sophia Ciesielski & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
    7. Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.
    8. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," ifo Working Paper Series 126, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Katja Rietzler & Sabine Stephan, 2012. "Monthly recession predictions in real time: A density forecast approach for German industrial production," IMK Working Paper 94-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.

  11. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2010. "A First Look on the New Halle Economic Projection Model," IWH Discussion Papers 6/2010, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Makram El-Shagi & Sebastian Giesen, 2013. "Testing for Structural Breaks at Unknown Time: A Steeplechase," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 101-123, January.

  12. Aumann, Bernd & Scheufele, Rolf, 2009. "Is East Germany Catching Up? A Time Series Perspective," IWH Discussion Papers 14/2009, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Frank Scharr, 2009. "Aufbau Ost 20 Jahre nach dem Mauerfall: Ziele und Aufgaben für die nächsten Jahre," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(18), pages 43-48, September.
    2. Bönisch, Peter & Schneider, Lutz, 2010. "Why are East Germans not More Mobile? Analyzing the Impact of Social Ties on Regional Migration," IWH Discussion Papers 16/2010, Halle Institute for Economic Research (IWH).
    3. Michael Weber & Jan Kluge, 2015. "Decomposing the German East-West wage gap," ERSA conference papers ersa15p636, European Regional Science Association.
    4. Peter Mihalyi, 2012. "The Causes of Slow Growth in Hungary during the Post-Communist Transformation Period," CERS-IE WORKING PAPERS 1216, Institute of Economics, Centre for Economic and Regional Studies.
    5. Jan Kluge & Michael Weber, 2018. "Decomposing the German East–West wage gap," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(1), pages 91-125, January.
    6. Wolfgang Nagl, 2014. "Lohnrisiko und Altersarmut im Sozialstaat," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 54.

  13. Scheufele, Rolf, 2008. "Das makroökonometrische Modell des IWH: Eine angebotsseitige Betrachtung," IWH Discussion Papers 9/2008, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Projektgruppe Gemeinschaftsdiagnose, 2008. "Gemeinschaftsdiagnose Frühjahr 2008: Folgen der US-Immobilienkrise belasten Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(08), pages 03-71, April.
    2. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2010. "A First Look on the New Halle Economic Projection Model," IWH Discussion Papers 6/2010, Halle Institute for Economic Research (IWH).
    3. Sebastian Böhm, 2012. "The Effects of Factor Market Integration on the Macroeconomic Development in Unified Germany," DEGIT Conference Papers c017_023, DEGIT, Dynamics, Economic Growth, and International Trade.
    4. Holtemöller, Oliver & Irrek, Maike & Schultz, Birgit, 2012. "A Federal Long-run Projection Model for Germany," IWH Discussion Papers 11/2012, Halle Institute for Economic Research (IWH).
    5. Projektgruppe Gemeinschaftsdiagnose, 2010. "Gemeinschaftsdiagnose Frühjahr 2010: Erholung setzt sich fort – Risiken bleiben groß," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(08), pages 03-78, April.
    6. Projektgruppe Gemeinschaftsdiagnose, 2009. "Gemeinschaftsdiagnose Frühjahr 2009: Im Sog der Weltrezession," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(08), pages 03-81, April.

  14. Scheufele, Rolf, 2008. "Evaluating the German (New Keynesian) Phillips Curve," IWH Discussion Papers 10/2008, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Capazario, Michele, 2022. "Developing an Income-Distribution- Sensitive Taylor Rule: An Application to South Africa," MPRA Paper 112740, University Library of Munich, Germany.
    2. Malikane, Christopher, 2013. "A New Keynesian Triangle Phillips Curve," MPRA Paper 43548, University Library of Munich, Germany.
    3. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2010. "A First Look on the New Halle Economic Projection Model," IWH Discussion Papers 6/2010, Halle Institute for Economic Research (IWH).
    4. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2012. "The Halle Economic Projection Model," Economic Modelling, Elsevier, vol. 29(4), pages 1461-1472.
    5. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).
    6. Engelbert Stockhammer & Dimitris Sotiropoulos, 2012. "Rebalancing the Euro area: The costs of internal devaluation," Working Papers PKWP1206, Post Keynesian Economics Society (PKES).
    7. El-Shagi, Makram, 2011. "Inflation expectations: Does the market beat econometric forecasts?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 298-319.
    8. Friedrich L. SELL & David C. REINISCH, 2013. "How do the Eurozone's Beveridge and Phillips curves perform in the face of global economic crisis?," International Labour Review, International Labour Organization, vol. 152(2), pages 191-204, June.
    9. Sell, Friedrich L. & Reinisch, David C., 2013. "How do Beveridge and Phillips curves in the euro area behave under the stress of the world economic crisis?," Working Papers in Economics 2013,1, Bundeswehr University Munich, Economic Research Group.
    10. Choi, Yoonseok, 2021. "Inflation dynamics, the role of inflation at different horizons and inflation uncertainty," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 649-662.
    11. Christopher Malikane, 2017. "The labour share and the dynamics of output," Applied Economics, Taylor & Francis Journals, vol. 49(37), pages 3741-3750, August.

  15. Knedlik, Tobias & Scheufele, Rolf, 2007. "Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?," IWH Discussion Papers 17/2007, Halle Institute for Economic Research (IWH).

    Cited by:

    1. Klaus Abberger & Wolfgang Nierhaus & Shynar Shaikh, 2009. "Findings of the Signal Approach for Financial Monitoring in Kazakhstan," CESifo Working Paper Series 2774, CESifo.
    2. Basabi Bhattacharya & Tanima Niyogi Sinha Roy, 2012. "Indicators of Banking Fragility in India: An Empirical Test," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 13(2), pages 265-290, September.

Articles

  1. Sandra Hanslin Grossmann & Rolf Scheufele, 2019. "PMIs: Reliable indicators for exports?," Review of International Economics, Wiley Blackwell, vol. 27(2), pages 711-734, May.

    Cited by:

    1. Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    5. Christian Grimme & Robert Lehmann, 2020. "The ifo Export Climate – A Leading Indicator to Forecast German Export Growth," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 20(04), pages 36-42, January.

  2. Gregor Bäurle & Rolf Scheufele, 2019. "Credit cycles and real activity: the Swiss case," Empirical Economics, Springer, vol. 56(6), pages 1939-1966, June.
    See citations under working paper version above.
  3. Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
    See citations under working paper version above.
  4. Alain Galli & Christian Hepenstrick & Rolf Scheufele, 2019. "Mixed-Frequency Models for Tracking Short-Term Economic Developments in Switzerland," International Journal of Central Banking, International Journal of Central Banking, vol. 15(2), pages 151-178, June.
    See citations under working paper version above.
  5. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    See citations under working paper version above.
  6. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    See citations under working paper version above.
  7. Sebastian Giesen & Rolf Scheufele, 2016. "Impulse response analysis in a misspecified DSGE model: a comparison of full and limited information techniques," Applied Economics Letters, Taylor & Francis Journals, vol. 23(3), pages 162-166, February.

    Cited by:

    1. Giesen, Sebastian & Scheufele, Rolf, 2016. "Effects of incorrect specification on the finite sample properties of full and limited information estimators in DSGE models," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 1-18.

  8. Rina Rosenblatt-Wisch & Rolf Scheufele, 2015. "Quantification and characteristics of household inflation expectations in Switzerland," Applied Economics, Taylor & Francis Journals, vol. 47(26), pages 2699-2716, June.
    See citations under working paper version above.
  9. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.

    Cited by:

    1. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    2. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    3. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    4. Steffen Henzel & Sebastian Rast, 2013. "Prognoseeigenschaften von Indikatoren zur Vorhersage des Bruttoinlandsprodukts in Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(17), pages 39-46, September.
    5. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
    6. Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    7. Schwarzmüller, Tim, 2015. "Model pooling and changes in the informational content of predictors: An empirical investigation for the euro area," Kiel Working Papers 1982, Kiel Institute for the World Economy (IfW Kiel).
    8. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    9. Christian Seiler, 2014. "Mode Preferences in Business Surveys: Evidence from Germany," ifo Working Paper Series 193, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. Jens Boysen-Hogrefe, 2012. "A note on predicting recessions in the euro area using real M1," Economics Bulletin, AccessEcon, vol. 32(2), pages 1291-1301.
    11. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    12. Christian Seiler & Klaus Wohlrabe, 2013. "Das ifo Geschäftsklima und die deutsche Konjunktur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(18), pages 17-21, October.
    13. Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
    14. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    15. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
    16. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    17. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Munich Reprints in Economics 78264, University of Munich, Department of Economics.
    18. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    19. 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.
    20. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    21. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, July.
    22. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    23. Christian Seiler, 2014. "The determinants of unit non-response in the Ifo Business Survey," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 161-177, September.
    24. David Iselin & Boriss Siliverstovs, 2016. "Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1103-1118, March.
    25. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model An application to the German business cycle," Munich Reprints in Economics 84736, University of Munich, Department of Economics.
    26. Schlösser, Alexander, 2020. "Forecasting industrial production in Germany: The predictive power of leading indicators," Ruhr Economic Papers 838, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    27. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    28. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    29. Anna Sophia Ciesielski & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
    30. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," ifo Working Paper Series 126, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    31. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
    32. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions With Boosted Regression Trees," Working Papers 2015-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    33. Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    34. Kajal Lahiri & Liu Yang, 2023. "Predicting binary outcomes based on the pair-copula construction," Empirical Economics, Springer, vol. 64(6), pages 3089-3119, June.
    35. Kitlinski, Tobias, 2015. "With or without you: Do financial data help to forecast industrial production?," Ruhr Economic Papers 558, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    36. Kitlinski, Tobias & an de Meulen, Philipp, 2015. "The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area," Ruhr Economic Papers 559, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    37. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
    38. Katja Rietzler & Sabine Stephan, 2012. "Monthly recession predictions in real time: A density forecast approach for German industrial production," IMK Working Paper 94-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.

  10. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2012. "The Halle Economic Projection Model," Economic Modelling, Elsevier, vol. 29(4), pages 1461-1472.

    Cited by:

    1. Drygalla, Andrej & Holtemöller, Oliver & Lindner, Axel, 2017. "Internationale Konjunkturprognose und konjunkturelle Szenarien für die Jahre 2016 bis 2021," IWH Online 3/2017, Halle Institute for Economic Research (IWH).
    2. Brautzsch, Hans-Ulrich & Dany-Knedlik, Geraldine & Drygalla, Andrej & Gebauer, Stefan & Holtemöller, Oliver & Kämpfe, Martina & Lindner, Axel & Michelsen, Claus & Rieth, Malte & Schlaak, Thore, 2019. "Kurzfristige ökonomische Effekte eines "Brexit" auf die deutsche Wirtschaft: Studie im Auftrag des Bundesministeriums für Wirtschaft und Energie," IWH Online 3/2019, Halle Institute for Economic Research (IWH).
    3. Lindner, Axel & Drygalla, Andrej, 2015. "Internationale Konjunkturprognose und konjunkturelle Stressszenarien für die Jahre 2014 bis 2018," IWH Online 3/2015, Halle Institute for Economic Research (IWH).
    4. Projektgruppe Gemeinschaftsdiagnose, 2014. "Gemeinschaftsdiagnose Frühjahr 2014: Deutsche Konjunktur im Aufschwung – aber Gegenwind von der Wirtschaftspolitik," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(08), pages 03-64, April.
    5. Holtemöller, Oliver & Lindner, Axel & Drygalla, Andrej, 2013. "Internationale Konjunkturprognose und konjunkturelle Stressszenarien für die Jahre 2013 bis 2015," IWH Online 6/2013, Halle Institute for Economic Research (IWH).
    6. Nikolay Hristov, 2016. "The Ifo DSGE Model for the German Economy," ifo Working Paper Series 210, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Holtemöller, Oliver & Lindner, Axel & Giesen, Sebastian, 2013. "Internationale Konjunkturprognose und konjunkturelle Stressszenarien für die Jahre 2012 bis 2014," IWH Online 1/2013, Halle Institute for Economic Research (IWH).
    8. Drygalla, Andrej & Holtemöller, Oliver & Lindner, Axel, 2021. "Internationale Konjunkturprognose und konjunkturelle Szenarien für die Jahre 2020 bis 2025," IWH Studies 2/2021, Halle Institute for Economic Research (IWH).
    9. Holtemöller, Oliver & Brautzsch, Hans-Ulrich & Drechsel, Katja & Drygalla, Andrej & Giesen, Sebastian & Hennecke, Peter & Kiesel, Konstantin & Loose, Brigitte & Meier, Carsten-Patrick & Zeddies, Götz, 2015. "Ökonomische Wirksamkeit der Konjunktur stützenden finanzpolitischen Maßnahmen der Jahre 2008 und 2009. Forschungsvorhaben im Auftrag des Bundesministeriums der Finanzen," IWH Online 4/2015, Halle Institute for Economic Research (IWH).
    10. Holtemöller, Oliver & Drygalla, Andrej & Lindner, Axel, 2016. "Internationale Konjunkturprognose und konjunkturelle Stressszenarien für die Jahre 2015 bis 2020," IWH Online 4/2016, Halle Institute for Economic Research (IWH).

  11. van Deuverden, Kristina & Scheufele, Rolf, 2011. "Mittelfristprojektion des IWH: Wirtschaftsentwicklung und Staatsfinanzen – Eine Vorausschau der Jahre 2011 bis 2015," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 17(1), pages 33-49.

    Cited by:

    1. Projektgruppe Gemeinschaftsdiagnose, 2011. "Gemeinschaftsdiagnose Frühjahr 2011: Aufschwung setzt sich fort - Europäische Schuldenkrise noch ungelöst," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(08), pages 03-63, April.

  12. Rolf Scheufele, 2011. "Are Qualitative Inflation Expectations Useful to Predict Inflation?," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2011(1), pages 29-53.

    Cited by:

    1. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    2. Pär Stockhammar & Pär Österholm, 2018. "Do inflation expectations granger cause inflation?," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(2), pages 403-431, August.
    3. Halina Kowalczyk & Tomasz Lyziak & Ewa Stanisławska, 2013. "A new approach to probabilistic surveys of professional forecasters and its application in the monetary policy context," NBP Working Papers 142, Narodowy Bank Polski.
    4. Mellina, Sathya & Schmidt, Tobias, 2018. "The role of central bank knowledge and trust for the public's inflation expectations," Discussion Papers 32/2018, Deutsche Bundesbank.
    5. Sunil Kumar, 2016. "Latent class analyisis for reliable measure of inflation expectation in the indian public," Papers 1603.01397, arXiv.org.
    6. Ina Nurmalia Kurniati, 2015. "Forecasting Growth Of Third Party Funds," Working Papers WP/10/2015, Bank Indonesia.
    7. Piotr Białowolski, 2011. "Forecasting inflation with consumer survey data – application of multi-group confirmatory factor analysis to elimination of the general sentiment factor," NBP Working Papers 100, Narodowy Bank Polski.
    8. Brückbauer Frank & Schröder Michael, 2023. "The ZEW Financial Market Survey Panel," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(3-4), pages 451-469, June.
    9. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
    10. Piotr Białowolski, 2016. "The influence of negative response style on survey-based household inflation expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 509-528, March.
    11. Tomasz Łyziak, 2016. "Do inflation expectations matter in a stylised New Keynesian model? The case of Poland," NBP Working Papers 234, Narodowy Bank Polski.
    12. Raïsa Basselier & David de Antonio Liedo & Jana Jonckheere & Geert Langenus, 2018. "Can inflation expectations in business or consumer surveys improve inflation forecasts?," Working Paper Research 348, National Bank of Belgium.
    13. Brückbauer, Frank & Schröder, Michael, 2021. "Data resource profile: The ZEW FMS dataset," ZEW Discussion Papers 21-100, ZEW - Leibniz Centre for European Economic Research.
    14. Mossfeldt, Marcus & Stockhammar, Pär, 2016. "Forecasting Goods and Services Inflation in Sweden," Working Papers 146, National Institute of Economic Research.

  13. Scheufele, Rolf, 2010. "Evaluating the German (New Keynesian) Phillips curve," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 145-164, August.
    See citations under working paper version above.
  14. Bernd Aumann & Rolf Scheufele, 2010. "Is East Germany catching up? A time series perspective," Post-Communist Economies, Taylor & Francis Journals, vol. 22(2), pages 177-192.
    See citations under working paper version above.
  15. Scheufele, Rolf, 2009. "Im Fokus: Konjunkturprogramme und ihre Wirkung – Eine Simulation mit dem makroökonometrischen Modell des IWH," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 15(1), pages 4-7.

    Cited by:

    1. Projektgruppe Gemeinschaftsdiagnose, 2009. "Im Sog der Weltrezession: Gemeinschaftsdiagnose Frühjahr 2009," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 15(1. Sonder), pages 1-101.
    2. Holtemöller, Oliver & Brautzsch, Hans-Ulrich & Drechsel, Katja & Drygalla, Andrej & Giesen, Sebastian & Hennecke, Peter & Kiesel, Konstantin & Loose, Brigitte & Meier, Carsten-Patrick & Zeddies, Götz, 2015. "Ökonomische Wirksamkeit der Konjunktur stützenden finanzpolitischen Maßnahmen der Jahre 2008 und 2009. Forschungsvorhaben im Auftrag des Bundesministeriums der Finanzen," IWH Online 4/2015, Halle Institute for Economic Research (IWH).
    3. Bach, Hans-Uwe & Gartner, Hermann & Hummel, Markus & Klinger, Sabine & Rothe, Thomas & Spitznagel, Eugen & Zika, Gerd, 2009. "Projektion 2009: Arbeitsmarkt im Sog der Rezession (Forecast 2009: Deep recession will hit German labour market)," IAB-Kurzbericht 200906, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

  16. Scheufele, Rolf & Ludwig, Udo, 2009. "Der lange Weg der Konvergenz," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 15(10), pages 400-407.

    Cited by:

    1. K. Haaf & C.J.M. Kool, 2017. "Determinants of regional growth and convergence in Germany," Working Papers 17-12, Utrecht School of Economics.
    2. Holtemöller, Oliver & Irrek, Maike & Schultz, Birgit, 2012. "A Federal Long-run Projection Model for Germany," IWH Discussion Papers 11/2012, Halle Institute for Economic Research (IWH).
    3. Michael Gühne & Gunther Markwardt, 2014. "Lohnunterschiede zwischen Ost- und Westdeutschland: Neue Einsichten," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(03), pages 37-44, June.
    4. Blum, Ulrich, 2011. "An Economic Life in Vain − Path Dependence and East Germany’s Pre- and Post-Unification Economic Stagnation," IWH Discussion Papers 10/2011, Halle Institute for Economic Research (IWH).

  17. Tobias Knedlik & Rolf Scheufele, 2008. "Forecasting Currency Crises: Which Methods Signaled The South African Crisis Of June 2006?," South African Journal of Economics, Economic Society of South Africa, vol. 76(3), pages 367-383, September.

    Cited by:

    1. Knedlik, Tobias & von Schweinitz, Gregor, 2011. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," IWH Discussion Papers 12/2011, Halle Institute for Economic Research (IWH).
    2. Geraldine Dany-Knedlik & Martina Kämpfe & Tobias Knedlik, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 123-139, February.
    3. Haakon Kavli & Kevin Kotzé, 2014. "Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 209-238, June.
    4. Diemo Dietrich & Tobias Knedlik & Axel Lindner, 2011. "Central and Eastern European countries in the global financial crisis: a typical twin crisis?," Post-Communist Economies, Taylor & Francis Journals, vol. 23(4), pages 415-432, April.
    5. Daniel King & Ferdi Botha, 2014. "Modelling Stock Return Volatility Dynamics in Selected African Markets," Working Papers 410, Economic Research Southern Africa.
    6. El-Shagi, Makram & Knedlik, Tobias & von Schweinitz, Gregor, 2012. "Predicting Financial Crises: The (Statistical) Significance of the Signals Approach," IWH Discussion Papers 3/2012, Halle Institute for Economic Research (IWH).
    7. Fiona Tregenna & Kabeya C. Mulamba, 2019. "Spatial dependence of per capita property tax income in South Africa," Working Papers 202, Economic Research Southern Africa.
    8. Andrew S. Duncan & Guangling Dave Liu, 2009. "Modelling South African Currency Crises as Structural Changes in the Volatility of the Rand," Working Papers 140, Economic Research Southern Africa.
    9. Duncan, Andrew S. & Kabundi, Alain, 2013. "Domestic and foreign sources of volatility spillover to South African asset classes," Economic Modelling, Elsevier, vol. 31(C), pages 566-573.
    10. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.

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