IDEAS home Printed from https://ideas.repec.org/a/sgm/resrep/v2i35y2021p76-92.html
   My bibliography  Save this article

The Markov Process as a Model of Migration Based on the Example of the Movement of Banknotes (Proces Markowa jako model migracji na przykladzie przemieszczania sie banknotow)

Author

Listed:
  • Arkadiusz Manikowski

    (Faculty of Management, University of Warsaw; Cash & Issue Department, National Bank of Poland)

Abstract

This paper presents a way of using the Markov chain model for the analysis of migration based on the example of banknote migration between regions in Poland. We have presented the application of the methodology for estimating one-step transition probabilities for the Markov chain based on macro-data gathered during the project conducted in the National Bank of Poland (NBP) in the period of December 2015–2018. We have shown the usefulness of state-aggregated Markov chain not only as a model of banknote migration but as migration in general. The banknotes are considered here as goods, so their migration is strictly related to, inter alia, the movement of people (commuting to work, business trips, etc.).Thus, the gravity-like properties of cash migration pointed to the gravity model as one of the most pervasive empirical models in regional science. Transition probability of the Markov chain expressing the attractive force between regions allows for estimating the gravity model for the identification of relevant reasons of note and, consequently, people migration.

Suggested Citation

  • Arkadiusz Manikowski, 2021. "The Markov Process as a Model of Migration Based on the Example of the Movement of Banknotes (Proces Markowa jako model migracji na przykladzie przemieszczania sie banknotow)," Research Reports, University of Warsaw, Faculty of Management, vol. 2(35), pages 76-92.
    • Handle: RePEc:sgm:resrep:v:2:i:35:y:2021:p:76-92
    as

    Download full text from publisher

    File URL: http://www.sim.wz.uw.edu.pl/sites/default/files/artykuly/arkadiusz_manikowski_0.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Raul Ramos, 2016. "Gravity models: A tool for migration analysis," IZA World of Labor, Institute of Labor Economics (IZA), pages 239-239, February.
    2. Fischer, Andreas M., 2014. "Immigration And Large Banknotes," Macroeconomic Dynamics, Cambridge University Press, vol. 18(4), pages 899-919, June.
    3. Seitz, Franz & Stoyan, Dietrich & Tödter, Karl-Heinz, 2009. "Coin migration within the euro area," Discussion Paper Series 1: Economic Studies 2009,27, Deutsche Bundesbank.
    4. Uhl, Matthias, 2020. "Coin migration between Germany and other euro area countries," Discussion Papers 49/2020, Deutsche Bundesbank.
    5. MacRae, Elizabeth Chase, 1977. "Estimation of Time-Varying Markov Processes with Aggregate Data," Econometrica, Econometric Society, vol. 45(1), pages 183-198, January.
    6. Dietrich Stoyan & Helga Stoyan & Gunter Döge, 2004. "Statistical Analyses and Modelling of the Mixing Process of Euro Coins in Germany and Europe," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 46(1), pages 67-77, March.
    Full references (including those not matched with items on IDEAS)

    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. Seitz Franz & Stoyan Dietrich & Tödter Karl-Heinz, 2012. "Diskussionsbeitrag / Discussion. Paper Coin: Migration and Seigniorage within the Euro Area," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(1), pages 84-92, February.
    2. Hugo Storm & Thomas Heckelei & Ron C. Mittelhammer, 2016. "Bayesian estimation of non-stationary Markov models combining micro and macro data," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(2), pages 303-329.
    3. Andrew Coleman & Guanyu Zheng, 2020. "Job-to-job transitions and the regional job ladder," Working Papers 2020/01, New Zealand Productivity Commission.
    4. Karantininis, Kostas, 2002. "Information-based estimators for the non-stationary transition probability matrix: an application to the Danish pork industry," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 275-290, March.
    5. Pasanisi, Alberto & Fu, Shuai & Bousquet, Nicolas, 2012. "Estimating discrete Markov models from various incomplete data schemes," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2609-2625.
    6. Mabel Sanchez-Barrioluengo & Sara Flisi, 2017. "Student Mobility in Tertiary Education: institutional factors and regional attractiveness," JRC Research Reports JRC108895, Joint Research Centre.
    7. Arie ten Cate, 2014. "Maximum likelihood estimation of the Markov chain model with macro data and the ecological inference model," CPB Discussion Paper 284, CPB Netherlands Bureau for Economic Policy Analysis.
    8. Jeffrey M. Gillespie & Joan R. Fulton, 2001. "A Markov chain analysis of the size of hog production firms in the United States," Agribusiness, John Wiley & Sons, Ltd., vol. 17(4), pages 557-570.
    9. Melanie Parravano & Luis Enrique Pedauga, 2008. "Oil market dynamics: A Markow chain analysis," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, vol. 33(25), pages 87-115, january-j.
    10. Keisuke Kondo, 2023. "Measuring the Attractiveness of Trip Destinations: A Study of the Kansai Region of Japan," Discussion Paper Series DP2023-07, Research Institute for Economics & Business Administration, Kobe University, revised Apr 2024.
    11. Legrand D. F. Saint-Cyr & Laurent Piet, 2017. "Movers and stayers in the farming sector: accounting for unobserved heterogeneity in structural change," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 777-795, August.
    12. Zepeda, Lydia & Chavas, Jean-Paul, 1991. "The Structure of Wisconsin Milk production: a Dynamic Analysis," WAEA/ WFEA Conference Archive (1929-1995) 321485, Western Agricultural Economics Association.
    13. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
    14. Michael P. Cameron, 2017. "Climate Change, Internal Migration and the Future Spatial Distribution of Population: A Case Study of New Zealand," Working Papers in Economics 17/03, University of Waikato.
    15. Mohamed Arouri & Nguyen Viet Cuong, 2020. "Wealth inequality and inter-governorate migration: Evidence from Egypt," Progress in Development Studies, , vol. 20(2), pages 119-139, April.
    16. Silke Huettel & Anne Margarian, 2009. "Structural change in the West German agricultural sector," Agricultural Economics, International Association of Agricultural Economists, vol. 40(s1), pages 759-772, November.
    17. Barsotti, Flavia & De Castro, Yohann & Espinasse, Thibault & Rochet, Paul, 2014. "Estimating the transition matrix of a Markov chain observed at random times," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 98-105.
    18. Love, H. Alan & Karp, Larry, 1988. "The Effect of Anticipated Farm Failure on the.Agricultural Land Market," 1988 Annual Meeting, August 1-3, Knoxville, Tennessee 270186, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Andreas M. Fischer & Lucca Zachmann, 2020. "Do the rich pay their taxes early?," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 27(1), pages 194-214, February.
    20. Ginzinger, Felix Sebastian Veit, 2020. "A spatial analysis of the determinants of Inter-regional migration: evidence from Ghana," MPRA Paper 114945, University Library of Munich, Germany, revised Oct 2022.

    More about this item

    Keywords

    migration of people; migration of banknotes; Markov chain; gravity model;
    All these keywords.

    JEL classification:

    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers

    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:sgm:resrep:v:2:i:35:y:2021:p:76-92. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/somuwpl.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.