IDEAS home Printed from https://ideas.repec.org/a/eee/reecon/v77y2023i1p185-201.html
   My bibliography  Save this article

Inflation volatility: A Bayesian approach

Author

Listed:
  • Koirala, Niraj P.
  • Nyiwul, Linus

Abstract

The ongoing trend of high inflation across much of the world has reignited interest in inflation volatility with varying foci and methods. In this paper, we employ a Bayesian framework to estimate inflation volatility using a sample of G20 countries. Estimation results suggest persistent heterogeneity in price volatility across time and countries. Furthermore, we use the Bayesian estimates of volatility to conduct several empirical analyses on the implications of interdependence of economies, development status for uncertainty. Further analyses on the determinants of price volatility suggest that trade openness, COVID-19, and the Ukraine crisis have positive impacts on volatility. Additionally, the nature of the political institutions and the share of manufacturing in total national output are also found to affect volatility to some extent.

Suggested Citation

  • Koirala, Niraj P. & Nyiwul, Linus, 2023. "Inflation volatility: A Bayesian approach," Research in Economics, Elsevier, vol. 77(1), pages 185-201.
    • Handle: RePEc:eee:reecon:v:77:y:2023:i:1:p:185-201
    DOI: 10.1016/j.rie.2023.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1090944323000042
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rie.2023.01.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Helmut Lütkepohl, 2005. "New Introduction to Multiple Time Series Analysis," Springer Books, Springer, number 978-3-540-27752-1, December.
    2. Ari Aisen & Francisco Veiga, 2008. "Political instability and inflation volatility," Public Choice, Springer, vol. 135(3), pages 207-223, June.
    3. Jamie Hall & Jarkko P. Jääskelä, 2011. "Inflation Volatility and Forecast Accuracy," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 44(4), pages 404-417, December.
    4. Lane, Philip R. & Milesi-Ferretti, Gian Maria, 2007. "The external wealth of nations mark II: Revised and extended estimates of foreign assets and liabilities, 1970-2004," Journal of International Economics, Elsevier, vol. 73(2), pages 223-250, November.
    5. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108437493, September.
    6. Campolmi, Alessia & Faia, Ester, 2011. "Labor market institutions and inflation volatility in the euro area," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 793-812, May.
    7. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    8. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108437493, September.
    9. Caglayan, Mustafa & Xu, Bing, 2016. "Inflation volatility effects on the allocation of bank loans," Journal of Financial Stability, Elsevier, vol. 24(C), pages 27-39.
    10. Arsić, Milojko & Mladenović, Zorica & Nojković, Aleksandra, 2022. "Macroeconomic performance of inflation targeting in European and Asian emerging economies," Journal of Policy Modeling, Elsevier, vol. 44(3), pages 675-700.
    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. Hamza, Taher & Ben Haj Hamida, Hayet & Mili, Mehdi & Sami, Mina, 2024. "High inflation during Russia–Ukraine war and financial market interaction: Evidence from C-Vine Copula and SETAR models," Research in International Business and Finance, Elsevier, vol. 70(PB).

    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. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    2. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2019. "Identification of Financial Factors in Economic Fluctuations," The Economic Journal, Royal Economic Society, vol. 129(617), pages 311-337.
    3. Liu, De-Chih & Chang, Yu-Chien, 2022. "Systematic variations in exchange rate returns," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 569-583.
    4. Hasan, Iftekhar & Horvath, Roman & Mares, Jan, 2020. "Finance and wealth inequality," Journal of International Money and Finance, Elsevier, vol. 108(C).
    5. Obryan Poyser, 2017. "Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series," Papers 1706.01437, arXiv.org.
    6. Rob Luginbuhl, 2020. "Estimation of the Financial Cycle with a Rank-Reduced Multivariate State-Space Model," CPB Discussion Paper 409, CPB Netherlands Bureau for Economic Policy Analysis.
    7. Bin Jiang & Anastasios Panagiotelis & George Athanasopoulos & Rob Hyndman & Farshid Vahid, 2016. "Bayesian Rank Selection in Multivariate Regression," Monash Econometrics and Business Statistics Working Papers 6/16, Monash University, Department of Econometrics and Business Statistics.
    8. Joshua C. C. Chan, 2018. "Specification tests for time-varying parameter models with stochastic volatility," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 807-823, September.
    9. Baştürk, Nalan & Grassi, Stefano & Hoogerheide, Lennart & Opschoor, Anne & van Dijk, Herman K., 2017. "The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i01).
    10. Babatunde O. Abidoye & Joseph A. Herriges & Justin L. Tobias, 2012. "Controlling for Observed and Unobserved Site Characteristics in RUM Models of Recreation Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1070-1093.
    11. Knut Are Aastveit & Gisle James Natvik & Sergio Sola, 2013. "Economic uncertainty and the effectiveness of monetary policy," Working Paper 2013/17, Norges Bank.
    12. Moukam, Claudiane Yanick & Atewamba, Calvin, 2023. "Incorporating expert knowledge in the estimate of farmers’ opportunity cost of supplying environmental services in rural Cameroon," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 12(3), October.
    13. Wang, Zheqi & Crook, Jonathan & Andreeva, Galina, 2020. "Reducing estimation risk using a Bayesian posterior distribution approach: Application to stress testing mortgage loan default," European Journal of Operational Research, Elsevier, vol. 287(2), pages 725-738.
    14. Dahem, Ahlem, 2015. "Short term Bayesian inflation forecasting for Tunisia," MPRA Paper 66702, University Library of Munich, Germany.
    15. Baltagi, Badi H. & Bresson, Georges & Chaturvedi, Anoop & Lacroix, Guy, 2022. "Robust Dynamic Space-Time Panel Data Models Using ?-Contamination: An Application to Crop Yields and Climate Change," IZA Discussion Papers 15815, Institute of Labor Economics (IZA).
    16. Bernardi Mauro & Della Corte Giuseppe & Proietti Tommaso, 2011. "Extracting the Cyclical Component in Hours Worked," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-28, May.
    17. Saqib Amin & Ruhamah Yousaf & Muhammad Awais Anwar & Noman Arshed, 2022. "Assessing the impact of diversity and ageing population on health expenditure of United States," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(2), pages 913-929, March.
    18. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    19. Colson, Gregory, 2009. "Improving nutrient content through genetic modification: Evidence from experimental auctions on consumer acceptance and willingness to pay for intragenic foods," ISU General Staff Papers 200901010800001872, Iowa State University, Department of Economics.
    20. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.

    More about this item

    Keywords

    Inflation volatility; Bayesian; G20; Covid-19; Ukraine invasion; Panel data;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

    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:eee:reecon:v:77:y:2023:i:1:p:185-201. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622941 .

    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.