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Discussing Measures of Financial Inclusion for the Main Euro Area Countries

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Abstract

Since financial inclusion has become a policy target in many countries, properly measuring it is crucial. Usual indexes of financial inclusion include inappropriate variables and don’t take into account other relevant aspects, thus misrepresenting the phenomenon. In this work we focus on the diffusion of electronic cards, generally not included in the usual indexes of financial inclusion notwithstanding they provide alternatives to usual saving practices and allow less costly transactions across larger markets and wider geographic areas. We show that, taking these instruments into account, the comparative valuation of the degree of financial inclusion between the main euro area countries changes substantially. We also employ survey data to analyze cross-country differences in the degree of financial inclusion and the distribution of multidimensional deprivations of specific sub-groups of populations.

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Fig. 1

Source: Computations on data taken from IFM Financial Access Indicators and World Bank Global Findex database. The list of the variables used to compute the indicators includes: branches per 100,000 adults, ATMs per 1000 Km2, percentage of adults with an account, deposits over GDP, percentage of adults that borrowed from a financial institution, loans over GDP

Fig. 2

Source: Computations on data taken from IFM Financial Access Indicators and World Bank Global Findex database. The list of the variables used to compute the indicators includes: branches per 100,000 adults, ATMs per 1000 Km2, percentage of adults with an account, deposits over GDP

Fig. 3

Source: Computations on data taken from IFM Financial Access Indicators and World Bank Global Findex database. The list of the variables used to compute the indicators includes: ATMs per 1000 Km2, percentage of adults with an account, deposits over GDP

Fig. 4

Source: Computations on data taken from IFM Financial Access Indicators, World Bank Global Findex database and ECB Euro area payment statistics. The list of the variables used to compute the indicators includes: ATMs per 1000 Km2, percentage of adults with an account, deposits over GDP, number of debit cards and prepaid cards scaled to population

Fig. 5

Source: Computations on individual data taken from the World Bank Global Findex database. On the horizontal axis it is shown the number of deprivations considering the following four dimensions: the ownership of an account, the ownership of a debit card, the use of the internet to access an account and the use of the internet to make payments

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Notes

  1. Before the recent financial crisis most of the literature underlined the positive relationship between financial development and economic growth (King and Levine 1993; Levine 2004). More recently, the literature underlined the risks associated to an excess of finance and excess of credit (Berkes et al. 2012; Schularick and Wachtel 2014).

  2. http://www.worldbank.org/en/topic/financialinclusion/brief/achieving-universal-financial-access-by-2020.

  3. http://www.worldbank.org/en/topic/financialinclusion/overview.

  4. Whereas the issue of the correct unit of measurement has not been adequately discussed yet in the literature about financial inclusion, there are academic contributions in other fields, such as the poverty analysis. Vijaya et al. (2014), for instance, argue that, when constructing multidimensional measures of poverty, equating the household with the individual is problematic because intra-household differences in resource allocation and interconnected deprivations are ignored.

  5. World Bank (2006a) and World Bank (2006b) were among the first attempts to describe data availability and data needs to measure financial inclusion.

  6. It is worth to cite Goodhart’s law which says that “when a measure becomes a target, it ceases to be a good measure” (Beck 2016).

  7. For a literature survey on “access to finance” see Karlan and Morduch (2010).

  8. Kempson et al. (2004) define the notion of “underbanked” or “marginally banked” people as those who, despite having a bank account, do not make adequate use of it.

  9. Among the dimensions of financial inclusion most commonly considered—each one measured, in the various works, by selected indicators—there are the availability, accessibility and usage of financial services. One can think of many other dimensions of an inclusive financial systems, such as the “quality”, “affordability” and “timeliness” of financial services. Nonetheless, data measuring these aspects are not readily available and these dimensions are not generally incorporated in financial inclusion indexes.

  10. In Germany, France, Italy and Spain data are obtained through landline and cellular phone interviews with a sample of 1000 adults in each country.

  11. Data for France show discontinuity in time series for the period 2014–2016. We impute new data by using the number of debit cards in Germany as benchmark and the relative position of France with respect to Germany in the percentage of debit cards holders reported in Findex database.

  12. Missing or discontinuous data for prepaid cards for Spain and France in the period 2013–2016 have been replaced by the corresponding data in 2012.

  13. In general, the linear operator expressed by the arithmetic mean is not used because it is recognized that the different dimensions should not be characterized by perfect substitutability, and hence different combinations of variables pertaining to different dimensions should not lead to same levels of financial inclusion. Amidzic et al. (2014), for instance, use a non-linear exponential geometric mean.

  14. The structural small size of Spanish bank branches is confirmed by ECB Banking Structural financial indicators statistics, for which in 2017 in Spain the ratio between the number of employees of domestic credit institutions and the number of domestic branches was 6.66 versus 10.27 employees per branches in Italy. In 2013 the ratios were 6.40 in Spain and 9.65 in Italy. See ECB, “Structural Indicators for the EU Banking Sector”, May 2018.

  15. On the relationship between the increase of online banking services and the reduction of bank branches in Italy see Carmignani et al. (2018).

  16. The information collected is “the use of a mobile phone or the internet to access a financial institution account in the past year”.

  17. In Italy, along with an increasing share of population being electronic cardholders, we observe an increasing share of population that is replacing current accounts with prepaid cards. Using data from Bank of Italy’s “Survey on Household Income and Wealth” (Banca d’Italia 2018), based on a sample of around 8000 households (20,000 individuals) in each wave, we obtain that the share of population having a prepaid cards while not having an account with a bank or a post office institution constantly increased during the last decade: it was 0.2% in 2008 and 2010, 0.7% in 2012, 0.9% in 2014 and 1.4% of the overall population in 2016. The latter share is higher for people living in the south of Italy and for households with an education level lower than the university degree (2 and 1.6% respectively). If we consider just the population that do not have a current account, the share of people holding a prepaid cards increased from the 1.5% in 2008 to the 11.5% in 2016.

  18. Among the potentially disadvantaged segments in terms of financial inclusion, it would have been interesting to consider the immigrant population (see Osili and Paulson 2006 for the US). Unfortunately, Findex survey does not provide data about this group.

  19. For a study on the preferred methods of payments by different sub-groups of population across the European countries see Esselink and Hernandez (2017).

  20. Also for the US, Osili and Paulson (2006) show that education is an important factor in affecting financial inclusion for disadvantaged segments. In particular, they show that the US the immigrants that are more educated and that come from countries with more effective institutions are more likely to make use of basic banking services and to use formal financial markets and services more extensively.

  21. Banca Etica analysis (2018) confirms the positive correlation in the Italian provinces between financial exclusion and poverty as well as low level of education.

  22. The analysis is performed using only the 2017 wave of Findex since two dimensions, the use of the internet to access an account and the use of the internet to make payments, are not present in the previous Findex waves.

  23. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Archive:Overindebtedness_and_financial_exclusion_statistics&oldid=220617.

  24. In Findex survey a question on the diffusion of mobile money accounts has been introduced in the 2017 wave, but the answer is missing for the main euro area countries.

  25. In particular, as an additional attribute of the information collected on the number of overnight deposits and on the number of debit and prepaid cards.

References

  • Aaberge, R., & Brandolini, A. (2015). Multidimensional poverty and inequality. In Handbook of income distribution, Chapter 3 (Vol. 2A, pp. 141–216). Elsevier.

  • Abel, S., Mutandwa, L., & le Roux, P. (2018). A review of determinants of financial inclusion. International Journal of Economics and Financial Issues,8(3), 1–8.

    Google Scholar 

  • Akin, O., Montalvo, J. G., Villar, J. G., Peydrò, J., & Raya J. M. (2014). The real estate and credit bubble: Evidence from Spain. Barcelona GSE Working Paper Series, No. 772.

  • Amidzic, G., Massara, A., & Mialou, A. (2014). Assessing countries’ financial inclusion standing—A new composite index. IMF Working Paper, 36.

  • Ampudia, M., & Ehrmann, M. (2017). Financial inclusion: What’s it worth?. European Central Bank, Working Paper Series No. 1990.

  • Atkinson, A. B. (2003). Multidimensional deprivations: Contrasting social welfare and counting approaches. The Journal of Economic Inequality,1, 51–65.

    Article  Google Scholar 

  • Banca d’Italia. (2018). Survey on household income and wealth—2016.

  • Banca Etica. (2018). L’esclusione finanziarie in Italia: dinamica e determinanti del fenomeno nel periodo 2012–2016.

  • Bank for International Settlements. (2016). Payment aspects of financial inclusion. Committee on Payments and Market Infrastructures, World Bank Group.

  • Beck, T. (2016). Financial Inclusion—Measuring progress and progress in measuring. London: Cass Business School, Univeristy of London, mimeo.

    Google Scholar 

  • Beck, T., Demirguc-Kunt, A., & Martinez Peria, M. S. (2007). Reaching out: Access to and use of banking services across countries. Journal of Financial Economics,85, 234–266.

    Article  Google Scholar 

  • Beck, T., Peria, M. S. M., Obstfeld, M., & Presbitero, A. (2018). Financial inclusion: Drivers and real effects. VOX CEPR’s Policy Portal.

  • Berkes, E. G., Panizza, U., & Arcand, J. L. (2012). Too much finance?. IMF Working Papers 12/161.

  • Cámara, N., & Tuesta, D. (2014). Measuring financial inclusion: A multidimensional index. BBVA Research, Working Paper, No. 14/26.

  • Carbo, S., Gardener, E. P., & Molyneux, P. (2005). Financial exclusion. London: Palgrave MacMillan.

    Book  Google Scholar 

  • Carmignani, A., Manile, M., Orame, A., & Pagnini, M. (2018). Servizi bancari online e dinamica degli sportelli bancari. Rome: Banca d’Italia, mimeo.

    Google Scholar 

  • Chakravarty, S., & Pal, R. (2010). Measuring financial inclusion: An axiomatic approach. Indira Gandhi Institute of Development Research, Working Paper No. WP 2010/003.

  • Demirguc-Kunt, A., & Klapper, L. (2012). Measuring financial inclusion: The global Findex database. The World Bank Policy Research Working Paper 6025.

  • Demirguc-Kunt, A., Klapper, L., & Singer, D. (2017). Financial inclusion and inclusive growth. A review of recent empirical evidence. The World Bank Policy Research Working Paper 8040.

  • Esselink, H., & Hernandez, L. (2017). The use of cash by households in the euro area. ECB Occasional Paper Series, No. 201, November 2017.

  • Estrada, A., & Saurina, J. (2016). Spanish boom-bust and macroprudential policy. Banco de España Financial Stability Review, No. 30, May 2016.

  • European Central Bank. (2018). Structural indicators for the EU banking sector.

  • Faia, E., & Paiella, M. (2017). P2P lending: Information externalities, social networks and loans’ substititution. CEPR Discussion Papers 12235.

  • Honohan, P. (2008). Cross-country variation in household access to financial services. Journal of Banking & Finance,32, 2493–2500.

    Article  Google Scholar 

  • Karlan, D., & Morduch, J. (2010). Access to finance. In D. Rodrik & M. R. Rosenzweig (Eds.), Handbook of development economics (pp. 4703–4784). Amsterdam: Elsevier.

    Chapter  Google Scholar 

  • Kempson, E., Atkinson, A., & Pilley, O. (2004). Policy level response to financial exclusion in developed economies: lessons for developing countries. Report of Personal Finance Research Centre, University of Bristol.

  • Kim, J. (2016). A study on the effect of financial inclusion on the relationship between income inequality and economic growth. Emerging Markets Finance and Trade,52(2), 498–512.

    Article  Google Scholar 

  • King, R. G., & Levine, R. (1993). Finance and growth: Schumpeter might be right. The Quarterly Journal of Economics,108, 717–737.

    Article  Google Scholar 

  • Levine, R. (2004). Finance and growth; theory and evidence. NBER Working Paper Series, No. 10766.

  • Leyshon, A., & Thrift, N. (1995). Geographies of financial exclusion: Financial abandonment in Britain and the United States. Transactions of the Institute of British Geographers, New Series,20(3), 312–341.

    Article  Google Scholar 

  • Mehrotra, A., & Yetman, J. (2015). Financial inclusion—Issues for Central Banks. BIS Quarterly Review, 83–96.

  • Osili, U. O., & Paulson, A. (2006). What can we learn about financial access from U.S. immigrants?. Federal Reserve Bank of Chicago, WP 2006-25.

  • Panetta, F. (2018). 21st century cash: Central banking, technological innovation and digital currencies. In Keynote address at the conference ‘Do we need central bank digital currencies? Economics, technology and psychology’. Bocconi University, Milan, 7 June 2018.

  • Sarma, M. (2008). Index of financial inclusion. ICRIER Working Paper 215.

  • Sarma, M. (2012). Index of financial inclusion—A measure of financial sector inclusiveness. Berlin Working Papers on Money, Finance, Trade and Development, No. 7.

  • Schularick, M., & Wachtel, P. (2014). The making of America’s imbalances. CESifo Economic Studies,60(1), 62–88.

    Article  Google Scholar 

  • Sinclair, S. P. (2001). Financial exclusion: An introductory survey. Report of Centre for Research in Socially Inclusive Services, Heriot-Watt University, Edinburgh.

  • UNDP. (2014). Human development report.

  • Vijaya, R. M., Lahoti, R., & Swaminathan, H. (2014). Moving from the household to the individual: Multidimensional poverty analysis. World Development,59, 70–81.

    Article  Google Scholar 

  • Weill, L., & Zins, A. (2016). The determinants of financial inclusion in Africa. Review of Development Finance,6, 46–57.

    Article  Google Scholar 

  • World Bank. (2006a). Measuring financial access: Outlining the scope of current data collection efforts. Washington, DC.

  • World Bank. (2006b). Indicators of financial access. Household—Level surveys. Washington, DC.

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    Giorgio Nuzzo & Stefano Piermattei

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Appendix

Appendix

See Table 3.

Table 3 Summary statistics of the variables by country (2007–2016).
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Nuzzo, G., Piermattei, S. Discussing Measures of Financial Inclusion for the Main Euro Area Countries. Soc Indic Res 148, 765–786 (2020). https://doi.org/10.1007/s11205-019-02223-8

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