IDEAS home Printed from https://ideas.repec.org/p/rim/rimwps/21-08.html
   My bibliography  Save this paper

How effective is financial education? Evidence from the Emilia-Romagna region

Author

Listed:
  • Stefania Mignani

    (Department of Statistical Sciences, University of Bologna, Italy)

  • Marcello Pagnini

    (economic research unit, Bologna branch, Bank of Italy; Rimini Centre for Economic Analysis)

Abstract

This paper describes the results from a questionnaire administered to students of schools in the Emilia-Romagna Region who participated in the Banca d'Italia-Miur project in the field of economic and financial education during the 2016-7 school year. The results show a significant increase in students' knowledge following a 10-hour course attended by schools teachers and held by personnel of the Bank of Italy. In particular, between the pre and post teaching activity phase, students increased the number of correct answers by about 5 units out of the 30 items in the questionnaire, compared to the improvement achieved by a group of students not involved in the teaching activity linked to the course held by the Bank of Italy. Our findings are robust to a wide set of controls suggested by literature on the topic.

Suggested Citation

  • Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:21-08
    as

    Download full text from publisher

    File URL: http://rcea.org/RePEc/pdf/wp21-08.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
    3. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    4. Richard, J. -F. & Tompa, H., 1980. "On the evaluation of poly-t density functions," Journal of Econometrics, Elsevier, vol. 12(3), pages 335-351, April.
    5. Cécile Denis & Daniel Grenouilleau & Kieran Mc Morrow & Werner Röger, 2006. "Calculating potential growth rates and output gaps - A revised production function approach," European Economy - Economic Papers 2008 - 2015 247, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    6. Pagan, Adrian R, 1975. "A Note on the Extraction of Components from Time Series," Econometrica, Econometric Society, vol. 43(1), pages 163-168, January.
    7. Planas, Christophe & Roeger, Werner & Rossi, Alessandro, 2007. "How much has labour taxation contributed to European structural unemployment?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1359-1375, April.
    8. Douglas O. Staiger & James H. Stock & Mark W. Watson, 1997. "How Precise Are Estimates of the Natural Rate of Unemployment?," NBER Chapters, in: Reducing Inflation: Motivation and Strategy, pages 195-246, National Bureau of Economic Research, Inc.
    9. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    10. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
    11. Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 7, pages 327-412, Elsevier.
    12. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    13. Hansen, Gary D., 1997. "Technical progress and aggregate fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1005-1023, June.
    14. Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
      • BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2004. "Econometrics," LIDAM Reprints CORE 1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Harvey, Andrew, 2001. "Testing in Unobserved Components Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(1), pages 1-19, January.
    16. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
    17. Planas, Christophe & Rossi, Alessandro & Fiorentini, Gabriele, 2008. "Bayesian Analysis of the Output Gap," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 18-32, January.
    18. Froeb, Luke & Koyak, Robert, 1994. "Measuring and comparing smoothness in time series the production smoothing hypothesis," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 97-122.
    19. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    20. Hall, Robert E & Mishkin, Frederic S, 1982. "The Sensitivity of Consumption to Transitory Income: Estimates from Panel Data on Households," Econometrica, Econometric Society, vol. 50(2), pages 461-481, March.
    21. Joseph Stiglitz, 1997. "Reflections on the Natural Rate Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 3-10, Winter.
    22. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
    23. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    24. Sylvia Fruhwirth-Schnatter, 2004. "Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 143-167, June.
    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. Philippe Moës, 2012. "Multivariate models with dual cycles: implications for output gap and potential growth measurement," Empirical Economics, Springer, vol. 42(3), pages 791-818, June.

    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. Christophe Planas & Alessandro Rossi & Gabriele Fiorentini, 2008. "The marginal likelihood of Structural Time Series Models, with application to the euro area and US NAIRU," Working Paper series 21_08, Rimini Centre for Economic Analysis.
    2. De la Serve, M-E. & Lemoine, M., 2011. "Measuring the NAIRU: a complementary approach," Working papers 342, Banque de France.
    3. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    4. Andrew Harvey, 2011. "Modelling the Phillips curve with unobserved components," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 7-17.
    5. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    6. Cayen, Jean-Philippe & van Norden, Simon, 2005. "The reliability of Canadian output-gap estimates," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 373-393, December.
    7. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    8. Rodríguez, Gabriel, 2010. "Using A Forward-Looking Phillips Curve to Estimate the Output Gap in Peru," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 6(1-2), pages 1-13, April.
    9. Basistha, Arabinda & Nelson, Charles R., 2007. "New measures of the output gap based on the forward-looking new Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 498-511, March.
    10. repec:hal:spmain:info:hdl:2441/784ilbkihi9tkblnh7q2514823 is not listed on IDEAS
    11. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    12. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    13. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    14. Marian Vavra, 2016. "Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions," Working and Discussion Papers WP 4/2016, Research Department, National Bank of Slovakia.
    15. 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.
    16. Tommaso Proietti & Alessandra Luati, 2013. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362, Edward Elgar Publishing.
    17. Emilian Dobrescu, 2006. "Integration of Macroeconomic Behavioural Relationships and the Input-output Block (Romanian Modelling Experience)," EcoMod2006 272100018, EcoMod.
    18. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    19. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    20. Michael O’Grady, 2019. "Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 35-76.
    21. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).

    More about this item

    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:rim:rimwps:21-08. 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: Marco Savioli (email available below). General contact details of provider: https://edirc.repec.org/data/rcfeait.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.