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Frieder Mokinski

Personal Details

First Name:Frieder
Middle Name:
Last Name:Mokinski
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RePEc Short-ID:pmo659
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Affiliation

Deutsche Bundesbank

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

Research output

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Jump to: Working papers Articles

Working papers

  1. Kolb, Benedikt & Mokinski, Frieder & Unger, Robert, 2021. "Corporate debt in Germany in the course of the COVID-19 pandemic: An evaluation based on the AnaCredit dataset," Technical Papers 07/2021, Deutsche Bundesbank.
  2. Mokinski, Frieder, 2017. "A severity function approach to scenario selection," Discussion Papers 34/2017, Deutsche Bundesbank.

Articles

  1. Elias Wolf & Frieder Mokinski & Yves Schüler, 2026. "On Adjusting the One‐Sided Hodrick–Prescott Filter," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 58(3), pages 919-931, April.
  2. Mokinski, Frieder & Roth, Markus, 2026. "Forecasting with log-linear (S)VAR models: Incorporating annual growth rate conditions," Economics Letters, Elsevier, vol. 265(C).
  3. Christoph Frey & Frieder Mokinski, 2016. "Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1083-1099, September.
  4. Mokinski, Frieder, 2016. "Using time-stamped survey responses to measure expectations at a daily frequency," International Journal of Forecasting, Elsevier, vol. 32(2), pages 271-282.
  5. Frieder Mokinski & Xuguang (Simon) Sheng & Jingyun Yang, 2015. "Measuring Disagreement in Qualitative Expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(5), pages 405-426, August.
  6. Heidorn, Thomas & Mokinski, Frieder & Rühl, Christoph & Schmaltz, Christian, 2015. "The impact of fundamental and financial traders on the term structure of oil," Energy Economics, Elsevier, vol. 48(C), pages 276-287.
  7. Frieder Mokinski & Nikolas Wölfing, 2014. "The effect of regulatory scrutiny: Asymmetric cost pass-through in power wholesale and its end," Journal of Regulatory Economics, Springer, vol. 45(2), pages 175-193, April.
  8. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.

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. Mokinski, Frieder, 2017. "A severity function approach to scenario selection," Discussion Papers 34/2017, Deutsche Bundesbank.

    Cited by:

    1. Falter, Alexander & Kleemann, Michael & Strobel, Lena & Wilke, Hannes, 2021. "Stress testing market risk of German financial intermediaries," Technical Papers 11/2021, Deutsche Bundesbank.

Articles

  1. Elias Wolf & Frieder Mokinski & Yves Schüler, 2026. "On Adjusting the One‐Sided Hodrick–Prescott Filter," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 58(3), pages 919-931, April.

    Cited by:

    1. Adam Geršl & Thomas Mitterling, 2021. "Forecast-Augmented Credit-to-GDP Gap as an Early Warning Indicator of Banking Crises," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(4), pages 323-351, December.
    2. Tihana Škrinjarić & Maja Bukovšak, 2022. "New Indicators of Credit Gap in Croatia: Improving the Calibration of the Countercyclical Capital Buffer," Working Papers 69, The Croatian National Bank, Croatia.
    3. Zsuzsanna Hosszu & Gergely Lakos, 2022. "Early Warning Performance of Univariate Credit-to-GDP Gaps," MNB Occasional Papers 2022/142, Magyar Nemzeti Bank (Central Bank of Hungary).
    4. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    5. Tihana Skrinjaric & Maja Bukovsak, 2022. "Improving The Calibration Of Countercyclical Capital Buffer: New Indicators Of Credit Gap In Croatia," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 31(2), pages 541-568, december.
    6. Schüler, Yves S., 2020. "On the credit-to-GDP gap and spurious medium-term cycles," Economics Letters, Elsevier, vol. 192(C).
    7. Panizza, Ugo, 2025. "Do countries default in bad times? The role of alternative detrending techniques," Economics Letters, Elsevier, vol. 246(C).
    8. Coussin, Maximilien, 2022. "Singular spectrum analysis for real-time financial cycles measurement," Journal of International Money and Finance, Elsevier, vol. 120(C).
    9. Quast, Josefine & Wolters, Maik H., 2020. "Reliable real-time output gap estimates based on a modified Hamilton filter," Kiel Working Papers 2158, Kiel Institute for the World Economy.

  2. Christoph Frey & Frieder Mokinski, 2016. "Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1083-1099, September.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. Krüger, Fabian & Clark, Todd E. & Ravazzolo, Francesco, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113077, Verein für Socialpolitik / German Economic Association.
    3. Roth, Markus, 2020. "Partial pooling with cross-country priors: An application to house price shocks," Discussion Papers 06/2020, Deutsche Bundesbank.
    4. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
    5. Kenourgios, Dimitris & Papadamou, Stephanos & Dimitriou, Dimitrios & Zopounidis, Constantin, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    6. Clark, Todd E. & Ganics, Gergely & Mertens, Elmar, 2024. "Constructing fan charts from the ragged edge of SPF forecasts," Discussion Papers 38/2024, Deutsche Bundesbank.
    7. Ellis W. Tallman & Saeed Zaman, 2018. "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series) 1809, Federal Reserve Bank of Cleveland.

  3. Mokinski, Frieder, 2016. "Using time-stamped survey responses to measure expectations at a daily frequency," International Journal of Forecasting, Elsevier, vol. 32(2), pages 271-282.

    Cited by:

    1. 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.
    2. Brückbauer, Frank & Schröder, Michael, 2021. "Data resource profile: The ZEW FMS dataset," ZEW Discussion Papers 21-100, ZEW - Leibniz Centre for European Economic Research.

  4. Frieder Mokinski & Xuguang (Simon) Sheng & Jingyun Yang, 2015. "Measuring Disagreement in Qualitative Expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(5), pages 405-426, August.

    Cited by:

    1. Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2024. "Quantifying Qualitative Survey Data with Panel Data Structure," CESifo Working Paper Series 11013, CESifo.
    2. Botsis, Alexandros & Görtz, Christoph & Sakellaris, Plutarchos, 2024. "Quantifying qualitative survey data with panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 167(C).
    3. Ewa Stanisławska, 2018. "Czy pytając konsumentów o wartość przewidywanej inflacji, można uzyskać wiarygodne i użyteczne informacje?," Bank i Kredyt, Narodowy Bank Polski, vol. 49(5), pages 515-556.
    4. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    5. Siklos, Pierre, 2017. "What Has Publishing Inflation Forecasts Accomplished? Central Banks And Their Competitors," LCERPA Working Papers 0098, Laurier Centre for Economic Research and Policy Analysis, revised 01 Apr 2017.
    6. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    7. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    8. Lena Dräger & Michael J. Lamla, 2015. "Disagreement à la Taylor: Evidence from Survey Microdata," Macroeconomics and Finance Series 201503, University of Hamburg, Department of Socioeconomics.
    9. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    10. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    11. Alexandros Botsis & Christoph Gortz & Plutarchos Sakellaris, 2023. "Quantifying Qualitative Survey Data: New Insights on the (Ir)Rationality of Firms' Forecasts," Discussion Papers 23-06, Department of Economics, University of Birmingham.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
    13. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    14. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
    15. Tomasz Łyziak & Xuguang Simon Sheng, 2023. "Disagreement in Consumer Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2215-2241, December.
    16. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    17. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    18. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    19. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
    20. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    21. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    22. Andreas Dibiasi & David Iselin, 2021. "Measuring Knightian uncertainty," Empirical Economics, Springer, vol. 61(4), pages 2113-2141, October.
    23. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    24. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    25. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    26. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    27. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    28. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.

  5. Heidorn, Thomas & Mokinski, Frieder & Rühl, Christoph & Schmaltz, Christian, 2015. "The impact of fundamental and financial traders on the term structure of oil," Energy Economics, Elsevier, vol. 48(C), pages 276-287.

    Cited by:

    1. Dirk G. Baur & Lee A. Smales, 2022. "Trading behavior in bitcoin futures: Following the “smart money”," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1304-1323, July.
    2. Lee A. Smales, 2022. "Trading Behavior in Agricultural Commodity Futures around the 52-Week High," Commodities, MDPI, vol. 1(1), pages 1-15, June.
    3. Liu, Li & Wang, Yudong & Wu, Chongfeng & Wu, Wenfeng, 2016. "Disentangling the determinants of real oil prices," Energy Economics, Elsevier, vol. 56(C), pages 363-373.
    4. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    5. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    6. Michael Grote & Dariusz Wojcik & Matthew Zook, 2024. "Sticky substance with sticky power: Oil in global production and financial networks," Environment and Planning A, , vol. 56(2), pages 436-453, March.
    7. Oguzhan Cepni & Duc Khuong Nguyen & Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, , vol. 43(1_suppl), pages 1-30, June.
    8. Lajos Horváth & Zhenya Liu & Curtis Miller & Weiqing Tang, 2024. "Breaks in term structures: Evidence from the oil futures markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2317-2341, April.
    9. Christina Anderl & Guglielmo Maria Caporale, 2024. "Functional Oil Price Expectations Shocks and Inflation," CESifo Working Paper Series 10998, CESifo.
    10. Lin, Boqiang & Tian, Weimin, 2025. "Exploring the cost of carry in Chinese energy futures: Does it interact with the energy stock market?," Energy, Elsevier, vol. 337(C).
    11. van Huellen, Sophie, 2019. "Price discovery in commodity futures and cash markets with heterogeneous agents," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 1-13.
    12. Bianchi, Robert J. & Fan, John Hua & Miffre, Joëlle & Zhang, Tingxi, 2023. "Exploiting the dynamics of commodity futures curves," Journal of Banking & Finance, Elsevier, vol. 154(C).
    13. Sophie van Huellen, 2018. "Too Much of a Good Thing? Speculative Effects on Commodity Futures Curves," Working Papers 211, Department of Economics, SOAS University of London, UK.

  6. Frieder Mokinski & Nikolas Wölfing, 2014. "The effect of regulatory scrutiny: Asymmetric cost pass-through in power wholesale and its end," Journal of Regulatory Economics, Springer, vol. 45(2), pages 175-193, April.

    Cited by:

    1. Yin Chu & J. Scott Holladay & Jacob LaRiviere, 2017. "Opportunity Cost Pass-through from Fossil Fuel Market Prices to Procurement Costs of the U.S. Power Producers," Working Papers 2017-02, University of Tennessee, Department of Economics.
    2. Wang, M. & Zhou, P., 2017. "Does emission permit allocation affect CO2 cost pass-through? A theoretical analysis," Energy Economics, Elsevier, vol. 66(C), pages 140-146.
    3. Brucal, Arlan & Tarui, Nori, 2021. "The effects of utility revenue decoupling on electricity prices," Energy Economics, Elsevier, vol. 101(C).
    4. Simeone, Christina E. & Lange, Ian & Gilbert, Ben, 2023. "Pass-through in residential retail electricity competition: Evidence from Pennsylvania," Utilities Policy, Elsevier, vol. 80(C).
    5. Germeshausen, Robert, 2018. "The European Union emissions trading scheme and fuel efficiency of fossil fuel power plants in Germany," ZEW Discussion Papers 18-007, ZEW - Leibniz Centre for European Economic Research.
    6. Castagneto-Gissey, Giorgio, 2014. "How competitive are EU electricity markets? An assessment of ETS Phase II," Energy Policy, Elsevier, vol. 73(C), pages 278-297.
    7. Joltreau, Eugénie & Sommerfeld, Katrin, 2017. "Why Does Emissions Trading under the EU ETS Not Affect Firms' Competitiveness? Empirical Findings from the Literature," IZA Discussion Papers 11253, IZA Network @ LISER.
    8. Anderson, Brilé & Bernauer, Thomas, 2016. "How much carbon offsetting and where? Implications of efficiency, effectiveness, and ethicality considerations for public opinion formation," Energy Policy, Elsevier, vol. 94(C), pages 387-395.
    9. Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.

  7. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.

    Cited by:

    1. 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.
    2. Brückbauer, Frank & Schröder, Michael, 2021. "Data resource profile: The ZEW FMS dataset," ZEW Discussion Papers 21-100, ZEW - Leibniz Centre for European Economic Research.
    3. Piotr Białowolski & Tomasz Kuszewski & Bartosz Witkowski, 2010. "Business Survey Data in Forecasting Macroeconomic Indicators with Combined Forecasts," Contemporary Economics, Vizja University, vol. 4(4), December.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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-RMG: Risk Management (1) 2017-12-18

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