IDEAS home Printed from https://ideas.repec.org/f/pmo659.html
   My authors  Follow this author

Frieder Mokinski

Personal Details

First Name:Frieder
Middle Name:
Last Name:Mokinski
Suffix:
RePEc Short-ID:pmo659
[This author has chosen not to make the email address public]

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. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.
  2. Mokinski, Frieder, 2017. "A severity function approach to scenario selection," Discussion Papers 34/2017, Deutsche Bundesbank.
  3. Heidorn, Thomas & Mokinski, Frieder & Rühl, Christoph & Schmaltz, Christian, 2014. "The impact of fundamental and financial traders on the term structure of oil," Frankfurt School - Working Paper Series 209, Frankfurt School of Finance and Management.
  4. Mokinski, Frieder & Wölfing, Nikolas, 2013. "The effect of regulatory scrutiny asymmetric cost pass-through in power wholesale and its end," ZEW Discussion Papers 13-055, ZEW - Leibniz Centre for European Economic Research.

Articles

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.

    Cited by:

    1. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    2. Schüler, Yves S., 2020. "On the credit-to-GDP gap and spurious medium-term cycles," Economics Letters, Elsevier, vol. 192(C).
    3. Quast, Josefine & Wolters, Maik H., 2019. "Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203535, Verein für Socialpolitik / German Economic Association.
    4. Coussin, Maximilien, 2022. "Singular spectrum analysis for real-time financial cycles measurement," Journal of International Money and Finance, Elsevier, vol. 120(C).

  2. Heidorn, Thomas & Mokinski, Frieder & Rühl, Christoph & Schmaltz, Christian, 2014. "The impact of fundamental and financial traders on the term structure of oil," Frankfurt School - Working Paper Series 209, Frankfurt School of Finance and Management.

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. van Huellen, Sophie, 2020. "Too much of a good thing? Speculative effects on commodity futures curves," Journal of Financial Markets, Elsevier, vol. 47(C).
    8. Christina Anderl & Guglielmo Maria Caporale, 2024. "Functional Oil Price Expectations Shocks and Inflation," CESifo Working Paper Series 10998, CESifo.
    9. 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).
    10. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    11. 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).

  3. Mokinski, Frieder & Wölfing, Nikolas, 2013. "The effect of regulatory scrutiny asymmetric cost pass-through in power wholesale and its end," ZEW Discussion Papers 13-055, ZEW - Leibniz Centre for European Economic Research.

    Cited by:

    1. 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.
    2. Brucal, Arlan & Tarui, Nori, 2021. "The effects of utility revenue decoupling on electricity prices," Energy Economics, Elsevier, vol. 101(C).
    3. Joltreau, Eugénie & Sommerfeld, Katrin, 2016. "Why does emissions trading under the EU ETS not affect firms' competitiveness? Empirical findings from the literature," ZEW Discussion Papers 16-062, ZEW - Leibniz Centre for European Economic Research.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Simeone, Christina E. & Lange, Ian & Gilbert, Ben, 2023. "Pass-through in residential retail electricity competition: Evidence from Pennsylvania," Utilities Policy, Elsevier, vol. 80(C).
    9. 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.

Articles

  1. 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. 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. Fabian Kr�ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    4. Pérez Quirós, Gabriel & Pérez, Javier J. & Paredes, Joan, 2015. "Fiscal targets. A guide to forecasters?," Working Paper Series 1834, European Central Bank.
    5. Dimitris Kenourgios & Stephanos Papadamou & Dimitrios Dimitriou & Constantin Zopounidis, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Post-Print hal-02880071, HAL.
    6. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36, Federal Reserve Bank of Cleveland.
    7. Roth, Markus, 2020. "Partial pooling with cross-country priors: An application to house price shocks," Discussion Papers 06/2020, Deutsche Bundesbank.

  2. 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.

  3. 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. 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.
    2. 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.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
    4. 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.
    5. 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.
    6. 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.
    7. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    8. Pierre L. Siklos, 2017. "What has publishing inflation forecasts accomplished? Central banks and their competitors," CAMA Working Papers 2017-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. 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.
    10. David Iselin & Andreas Dibiasi, 2019. "Measuring Knightian Uncertainty," KOF Working papers 19-456, KOF Swiss Economic Institute, ETH Zurich.
    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. 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.
    13. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    14. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    15. 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.
    16. Alexandros Botsis & Christoph Görtz & Plutarchos Sakellaris, 2024. "Quantifying Qualitative Survey Data with Panel Data Structure," CESifo Working Paper Series 11013, CESifo.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    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. 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.
    25. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    26. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.

  4. 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.
    See citations under working paper version above.
  5. 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.
    See citations under working paper version above.
  6. 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, University of Economics and Human Sciences in Warsaw., vol. 4(4), December.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 4 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-COM: Industrial Competition (1) 2013-08-31
  2. NEP-ECM: Econometrics (1) 2020-04-06
  3. NEP-ENE: Energy Economics (1) 2014-04-18
  4. NEP-ETS: Econometric Time Series (1) 2020-04-06
  5. NEP-EUR: Microeconomic European Issues (1) 2013-08-31
  6. NEP-IND: Industrial Organization (1) 2013-08-31
  7. NEP-MAC: Macroeconomics (1) 2020-04-06
  8. NEP-REG: Regulation (1) 2013-08-31
  9. NEP-RMG: Risk Management (1) 2017-12-18

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Frieder Mokinski should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

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

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