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learn$ave Project: Final Reportto earn high-return matched credits. They then savedless than the control group during subsequent monthswhen they were withdrawing their savings and cashingout their credits to purchase education or starting a smallbusiness. At the 54-month survey point, any positivereturns to those investments in education or selfemploymenthad yet not translated into positive growthin financial assets. Such a return in financial well-beingcould take place later on. However, as far as the availabledata suggest, the net result is that the only significanteffects the project had on financial assets occurred early(at 18 months) and learn$ave had no significant effect onthe amount of financial savings at the 54-month mark.It is worth noting at this point that the observedpattern in the average value of overall financial assetsand net worth (discussed below) is largely determinedby the specific uses of savings considered eligible underthe learn$ave program. Indeed, by their very nature, thetwo eligible uses of accumulated savings under learn$ave,adult education and business start-up, do not appear as“assets” in the financial balance sheet of participants atthe time they are acquired. Instead, it is assumed thattheir acquisition of human capital would lead to futureTable 6.2Baseline to18 monthsBaseline to40 monthsBaseline to54 monthsSource:Note:Impacts on Savings (Change in Financial Assets)(Average Dollars), All Participants – AdjustedImpact ofMatched SavingCreditsImpact ofServices whenOffered withCredits ∑Combined Impactof Credits+ Services583** 91 674***-639 673 34-536 303 -233Calculations from 54-month, 40-month and 18-month surveydata.Overall sample sizes for the control, learn$ave-only andlearn$ave-plus groups are 748, 920 and 915, respectively,for the 18-month survey; 607, 833 and 814, respectively,for the 40-month survey; and 568, 842 and 859 for the54-month survey. Sample sizes vary for individual measuresbecause of missing values.Two-tailed t-tests were applied to impacts estimated by regression-adjusteddifferences in outcomes between research(program and control) groups.Statistical significance levels are indicated as * = 10 percent; ** = 5 per cent; *** = 1 per cent.Rounding may cause slight discrepancies in sums and differences.∑The figures in this column show the extra impact of thefinancial management training and enhanced case managementservices when given to those eligible to receivematched credits. It does not represent the impact of thoseservices alone for those not eligible to receive the matchedsaving credit; it represents the impact of the services whenprovided with the credits.returns in terms of increased earnings or employment.If learn$ave had been opened to multiple uses, such asretirement income or the acquisition of a house, it wouldhave been possible to record these types of assets at theirmarket value as soon as they are acquired. In that case,we could have seen total financial assets increase at thebeginning of the period and stay high during Phase 3, thetime of assets acquisition.One could attempt to approximate the value of humancapital acquisition by calculating a present value basedon the expected future returns on investments made ineducation, learning, or micro-enterprise development.However, in the absence of a methodologically sound wayto do that, and to avoid mixing up observations basedon factual information with some broad estimates offuture returns, we feel that is more appropriate to treatthe investment in adult education and small businessstart-up as pure expenditures and to omit these itemsfrom the calculation of average assets and net worth. Asa result, it is not surprising to see participants’ savingsand net worth decrease when participants cash outtheir learn$ave account (their own savings as well as thematched credits).In addition to looking at changes in financial assetsover time (“revealed saving behaviour”), another way tomeasure savings impacts is to ask participants whetherthey are saving money or not (“self-reported saving”) andcompare responses across research groups. Based on selfreportedsavings in the last 12 months, learn$ave did havesome modest positive impacts on saving incidence. Table6.3 shows that matched credits, alone and combined withthe services, increased the proportion of self-reportedsavers by 6.5 and 5.0 percentage points, respectively.Further, learn$ave did have an effect on regular saving. Animplicit goal of learn$ave was to encourage regular savingby requiring participants to make at least 12 monthly depositsinto their learn$ave account to become eligible formatched credits. While Table 6.3 shows the credits alonehad no effect on regular saving, the credits in combinationwith services did have a modest impact (5.8 percentagepoints). In other words, the program does seem to havea lasting impact on saving activity, even when no furthermatched credits were available to participants. Thecredits alone were sufficient to encourage a small butsignificant increase in self-reported savings of any kind inthe past year, but only when combined with the services(in the learn$ave-plus group) did the project encourageparticipants to continue saving regularly by month 54.Moreover, learn$ave had a positive impact on futuresaving intentions (data not shown). Compared tothe control group, the program group was about 8.5Social Research and Demonstration Corporation Chapter 6 | 69