IDEAS home Printed from https://ideas.repec.org/p/bny/wpaper/0123.html

Bayesian Mode Inference for Discrete Distributions in Economics and Finance

Author

Listed:
  • Jamie L. Cross

  • Lennart Hoogerheide

  • Paul Labonne

  • Herman K. van Dijk

Abstract

Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective technique for mode inference in discrete data distributions which involves fitting a mixture of novel shifted-Poisson distributions. The credibility and utility of our proposed approach is demonstrated through empirical investigations on datasets pertaining to loan default risk and inflation expectations.

Suggested Citation

  • Jamie L. Cross & Lennart Hoogerheide & Paul Labonne & Herman K. van Dijk, 2023. "Bayesian Mode Inference for Discrete Distributions in Economics and Finance," Working Papers No 11/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0123
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/11250/3095578
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.
    2. Haroon Mumtaz & Paolo Surico, 2009. "Time-varying yield curve dynamics and monetary policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 895-913.
    3. Caggiano, Giovanni & Castelnuovo, Efrem & Groshenny, Nicolas, 2014. "Uncertainty shocks and unemployment dynamics in U.S. recessions," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 78-92.
    4. Mary A. Burke & Michael Manz, 2014. "Economic Literacy and Inflation Expectations: Evidence from a Laboratory Experiment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1421-1456, October.
    5. Afonso, António & Martins, Manuel M.F., 2012. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1789-1807.
    6. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
    7. Haroon Mumtaz & Francesco Zanetti, 2013. "The Impact of the Volatility of Monetary Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 535-558, June.
    8. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, July.
    9. Dionne, Georges & Artis, Manuel & Guillen, Montserrat, 1996. "Count data models for a credit scoring system," Journal of Empirical Finance, Elsevier, vol. 3(3), pages 303-325, September.
    10. Pfajfar, Damjan & Santoro, Emiliano, 2010. "Heterogeneity, learning and information stickiness in inflation expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 426-444, September.
    11. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    12. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    13. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    14. Efrem Castelnuovo, 2019. "Yield Curve and Financial Uncertainty: Evidence Based on US Data," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 52(3), pages 323-335, September.
    15. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2008. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," Journal of Econometrics, Elsevier, vol. 146(2), pages 351-363, October.
    16. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2021. "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 369-410, October.
    17. Peter Tillmann, 2020. "Monetary Policy Uncertainty and the Response of the Yield Curve to Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(4), pages 803-833, June.
    18. repec:mcb:jmoncb:v:45:y:2013:i::p:535-558 is not listed on IDEAS
    19. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2022. "Uncertainty and monetary policy in good and bad times: A replication of the vector autoregressive investigation by Bloom (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 210-217, January.
    20. Haltiwanger, John & Waldman, Michael, 1985. "Rational Expectations and the Limits of Rationality: An Analysis of Heterogeneity," American Economic Review, American Economic Association, vol. 75(3), pages 326-340, June.
    21. Efrem Castelnuovo, 2023. "Uncertainty before and during COVID‐19: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(3), pages 821-864, July.
    22. Markus Leippold & Felix Matthys, 2022. "Economic Policy Uncertainty and the Yield Curve [Pricing the term structure with linear regressions]," Review of Finance, European Finance Association, vol. 26(4), pages 751-797.
    23. Leo Krippner, 2015. "A Theoretical Foundation for the Nelson–Siegel Class of Yield Curve Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 97-118, January.
    24. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    25. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    26. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    27. Markus Leippold & Felix Matthys, 2022. "Economic Policy Uncertainty and the Yield Curve," Swiss Finance Institute Research Paper Series 22-36, Swiss Finance Institute.
    28. Atsushi Inoue & Barbara Rossi, 2021. "A new approach to measuring economic policy shocks, with an application to conventional and unconventional monetary policy," Quantitative Economics, Econometric Society, vol. 12(4), pages 1085-1138, November.
    29. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    30. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    31. Leombroni, Matteo & Vedolin, Andrea & Venter, Gyuri & Whelan, Paul, 2021. "Central bank communication and the yield curve," Journal of Financial Economics, Elsevier, vol. 141(3), pages 860-880.
    32. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
    33. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    34. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    35. Liu, Yan & Wu, Jing Cynthia, 2021. "Reconstructing the yield curve," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1395-1425.
    36. P. M. Hartigan, 1985. "Computation of the Dip Statistic to Test for Unimodality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(3), pages 320-325, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Knut Are Aastveit & Jamie L. Cross & Francesco Furlanetto & Herman K. Van Dijk, 2024. "Taylor Rules with Endogenous Regimes," Working Papers No 04/2024, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. Yoosoon Chang & Steven N. Durlauf & Bo Hu & Joon Y. Park, 2024. "Accounting for Individual-Specific Heterogeneity in Intergenerational Income Mobility," Working Papers No 03/2024, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    4. Knut Are Aastveit & Jamie Cross & Francesco Furlanetto & Herman K van Dijk, 2024. "Asymmetric Gradualism in US Monetary Policy," Tinbergen Institute Discussion Papers 24-074/III, Tinbergen Institute.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mathias Krogh & Giovanni Pellegrino, "undated". "Real Activity and Uncertainty Shocks: The Long and the Short of It," "Marco Fanno" Working Papers 0310, Dipartimento di Scienze Economiche "Marco Fanno".
    2. Hwang, Youngjin, 2025. "Information content in yield curve dynamics: Implications for monetary policy," Journal of Macroeconomics, Elsevier, vol. 83(C).
    3. Han, Yang & Jiao, Anqi & Ma, Jun, 2021. "The predictive power of Nelson–Siegel factor loadings for the real economy," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 95-127.
    4. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    5. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    6. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    7. Lastauskas, Povilas & Nguyen, Anh Dinh Minh, 2024. "Spillover effects of US monetary policy on emerging markets amidst uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    8. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org, revised Jul 2025.
    9. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
    10. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    11. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.
    12. Ioannis A. Venetis & Avgoustinos Ladas, 2023. "Co-movement and global factors in sovereign bond yields," Bulletin of Applied Economics, Risk Market Journals, vol. 10(2), pages 17-45.
    13. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    14. Carlos Cañizares Martínez & Arne Gieseck, 2025. "The effects of macro uncertainty shocks in the euro area: a FAVAR approach," Empirical Economics, Springer, vol. 68(6), pages 2829-2872, June.
    15. Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
    16. Eksi, Ozan & Onur Tas, Bedri Kamil, 2022. "Time-varying effect of uncertainty shocks on unemployment," Economic Modelling, Elsevier, vol. 110(C).
    17. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    18. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    19. Firmin Doko Tchatoka & Qazi Haque & Madison Terrell, 2022. "Monetary Policy Shocks and Exchange Rate Dynamics in Small Open Economies," CAMA Working Papers 2022-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • D00 - Microeconomics - - General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bny:wpaper:0123. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Helene Olsen (email available below). General contact details of provider: https://edirc.repec.org/data/cambino.html .

    Please note that corrections may 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.