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Empirical Economics

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26.06.2018

Demographics and the demand for currency

verfasst von: Geoffrey R. Dunbar

Erschienen in: Empirical Economics | Ausgabe 4/2019

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Abstract

I use data from the Bank of Canada’s Bank Note Distribution System and exploit a natural experiment offered by the timing of Easter in the Gregorian calendar to analyse the effects of demographic change for bank note demand by financial institutions from the Bank of Canada. I find that the main drivers of low-denomination bank note demand are merchants. Merchants and the youngest age group, aged 15–24, are also a significant source of demand for twenty-dollar bank notes and for the total dollar value of withdrawals. In contrast, increases in the demographic age groups 25–54 and 55 plus tend to lower bank note withdrawals. Finally, I find no evidence that employment status is related to bank note demand, but that there is a difference between the bank note demand of men aged 15–24 and women aged 15–24: increases in the share of women aged 15–24 lead to increases in bank note demand.

Vorheriger Artikel Nowcasting Swedish GDP with a large and unbalanced data set

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Such an identification strategy is infeasible for age-related, and gender-related, demographic demand because there is no plausible exogenous link between lagged measures of age cohorts or genders, whereas it is plausible that lagged immigration may instrument current immigration patterns through, for example, cultural or linguistic similarity. While it might be interesting to estimate the effect of immigration for cash demand in Canada, monthly immigration data for the Canadian provinces at the monthly data are not reported by Statistics Canada.

Estimating the effects of demographic factors such as age and gender for the demand for cash is challenging using either time-series or cross-sectional data. Regression estimates of the demographic effects for the demand for cash may be biased by an(y) omitted variable(s). Possible omitted variables include institutional changes, such as the emergence of ATMs, that co-move with demographics such as the ageing of the baby-boom generation; improvements in financial literacy that are correlated with demographic patterns; sectoral reallocations and/or income shocks that are correlated with demographic patterns; or immigration patterns that affect money demand and are correlated with demographic variables.

Recall that the standard Baumol–Tobin model predicts an income elasticity of 0.5 and cash-in-demand models predict income elasticities of 1.

There is also a burgeoning literature on the methods of payment chosen by consumers. For example, Schuh and Stavins (2010) examine the adoption rates of new payment technologies using survey data and find mixed evidence that other payment methods reduce the demand for cash. Benton et al. (2007) find evidence that the adoption rates of new payment technologies do not systematically vary as much across demographic age groups as they do within. These studies examine the payment choices of individuals at the point-of-sale and not the demand for cash from the central bank by financial institutions, as is examined here.

The regions are British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec and the Atlantic provinces.

Technically, withdrawal and deposit data are available at the level of the financial institutions in the BNDS, but cannot be disclosed at this level since, even with anonymous identifiers, regional differences in branch distribution would potentially identify individual financial institutions. For the purpose of this paper, these disclosure restrictions are not particularly problematic since the demographic distribution of bank clients is unknown.

The housing completions data are adjusted by the housing CPI in each region, as described in Sect. 3.

I assume that financial institutions are profit maximizing and earn positive revenue on bank note withdrawals.

Although this latter assumption may seem unusual, the frequency of cash withdrawals by financial institutions is daily and the short-run nominal interest cost is the overnight interest rate. Thus, expectation errors on the real interest costs are likely to be very small, and in any event could be hedged.

Note that regional pricing heterogeneity introduces additional concerns regarding the possible endogeneity of demographic regressors, since errors in price indices may be correlated with demographic shares because of price competition driven by demographic tastes.

Note the implicit assumption that retail sales and housing completions are not deflated by the inflation rate. I choose this specification to ensure that there is no spurious correlation owing to the same deflator being applied to the regressor and regressand. In unreported results, I examine a specification using deflated retail sales and housing completions and find statistically similar results to those reported in this paper. Indeed, as would be expected, there are more individually significant estimates using the deflated series, which suggests that some of the correlation may be due to the common deflator. Thus, I choose to report the results using nominal retail sales and housing completions, since these are, in some sense, the more conservative estimates.

I check the correlations between the Easter dummy and the included regressors and find that they are all near zero, to ensure that the Easter effect is uncorrelated with the included regressors.

When regional trends are used, I include a dummy variable for the change in the BNDS.

I also examine the partial autocorrelation function for the residuals from each region, and these do not exhibit evidence of a significant pattern of autocorrelation. I also test the residuals for each region using Bartlett’s (1955) periodogram test for white noise and do not reject the hypothesis that the residuals are normally distributed for any region.

For example, Arango and Welte (2012) report that the typical withdrawal by Canadians was roughly $100 in 2009. Typical Interac fees are 0.75–1.50 per transaction, which implies $\kappa _j \approx 0.01$.

Some caution is warranted for these conclusions, because the estimates are strictly valid only for months with Easter. If currency demand by age groups and merchants is different on Easter holidays than during other periods, then the estimates cannot be generalized. This would, however, require that age groups behave differently in more than simply a level effect, because of the inclusion of region-specific Easter dummies.

These results are available upon request.

See http://www.interac.ca/index.php/en/interac-about/about-us, doi 03.03.14.

I do not provide estimates for the employment and gender differences because the general pattern of demands is similar to those of the twenty-dollar and total value notes reported. The significance of the estimated demands is, however, in some cases, marginal. These results are available upon request.

This exercise implicitly assumes that the Easter estimates are representative of typically daily demands and that the estimated effects are similar across provinces.

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Titel: Demographics and the demand for currency
verfasst von: Geoffrey R. Dunbar
Publikationsdatum: 26.06.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 4/2019
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-018-1486-8

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