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Measuring Financial Literacy to Understand Preparedness for Retirement

By: Ekaterina Kalantyrski

University of Guelph

Gordon S. Lang School of Business and Economics

Department of Marketing & Consumer Studies

Copyright © 2023 Ekaterina Kalantyrski. All right reserved.

1. Rationale for the Choice of Ecosystem Priority 1: Communicate in Ways People Understand

1.1. Introduction

There are many research and managerial reasons to study financial literacy and capability which have progressively become a focus of attention for many stakeholders internationally in recent years.

One of the reasons is developing communication of financial information, products, and services to Ca-nadian consumers in such a way that the consumers will be able to understand it and adopt an appro-priate course of action to support their financial well-being. This type of communication is one of the Ecosystem Priorities of the National Financial Literacy Strategy (Government of Canada, 2023) and developing such communication requires an understanding of how to measure the level of consumers’ financial literacy and consumers’ abilities to understand and use financially related information and resources.

Overall, the population does not show a great level of financial literacy. Based on the results of the Adult Financial Literacy survey, with twenty-six countries from Asia, Europe, and Latin America participating, the reported average financial literacy score is below 61% (Organisation for Economic Co-operation and Development (OECD, 2020). Furthermore, only 26% of adults gave correct answers to questions about simple and compound interest (OECD, 2020).

The cost of being financially illiterate and making poor financial choices is high. Disney and Gathergood (2013) show that consumers with lower financial literacy are more likely to have more expensive debt. It is estimated that up to 40 percent of wealth disparity at retirement could be caused by the lack of financial knowledge (Lusardi et al., 2017).

The financial decisions that consumers are required to make are complex and require significant financial knowledge and ability to collect and analyze complex data (Hung et al., 2009). The need for the consumers’ financial capability arises from market complexity, increasing personal responsibility for financial decisions, a growing number of financial products, and increasing financial information load (Luukkanen & Uusitalo, 2014; Lusardi et al., 2017; West, 2012). Consequently, policymakers and researchers design and use financial literacy measures to assist in understanding the level of consumer financial well-being, and to assess a population’s ability to perform well financially (Huston, 2010; Kunovskaya et al., 2014; Financial Consumer Agency of Canada, 2019).

Therefore, this paper, drawing from the literature in the area of financial literacy and its impact on financial decision-making and well-being, aims to provide further insights on the measurement of financial literacy. Given the complexity of consumer financial decisions, one universal financial literacy scale might not provide the detailed insights on specific areas where consumers might lack knowledge and skills. The paper proposes that multiple scales covering specific financial literacy areas like investments or savings will provide such specific insights. This paper focuses on developing a retirement-related financial literacy scale as an enhancement to the existing financial literacy scale to address the specific needs of consumers as they prepare for retirement.

1.2 Literature Review

A. Multiple Definitions and Scales

The financial literacy concept has been used by policymakers and in research since the late 1990’s, originally, it was defined as “the ability to use knowledge and skills to manage one's financial resources effectively for lifetime financial security” (Hastings et al., 2012). Since then, many variations of the definition have been introduced, and there is no one consistent definition of financial literacy (Xiao et al. 2014; Hung et al., 2009; Goyal & Kumar, 2021; Financial Consumer Agency of Canada, 2021a; Kunovskaya et al., 2014; President’s Advisory Council on Financial Literacy (PACFL), 2008 as cited in Hung et al., 2009; Moore, 2003, as cited in Hung et al., 2009; Luukkanen & Uusitalo, 2014), and there has been some effort at developing a uniform measure (Rieger, 2020; Huston, 2010; Kunovskaya et al., 2014).

Multiple financial literacy scales have been used in literature, and these scales typically include a set or a sub-set of five questions evaluating knowledge about interest/inflation, compounding, diversification, mortgage, and bond prices (Hastings et al., 2012; Henager & Wilmarth, 2018; Xiao et al., 2014; Anderson et al., 2017). Some papers add other financial literacy questions related to specific domains, like investment to these basic scales (Kunovskaya et al., 2014; Bianchi, 2018; Burke & Manz, 2014; Ćumurović & Hyll, 2019; Gathergood & Weber, 2017; Lusardi & Mitchell, 2011; Van Ooijen & Van Rooij, 2016; OECD, 2018).

The existence of multiple definitions and measures of financial literacy indicates that a general scale might be used as a base for measuring financial literacy. However, given, that different segments of the population have different needs in financial knowledge depending on the stage of their lifecycle, their educational background, gender, age, and income level (Lusardi et al., 2017; Hung et al., 2009; OECD, 2020; Potrich et al., 2015), specific financial literacy measures need to be developed to provide the relevant insight to facilitate supporting these groups.

B. Inconsistency in Research Findings; Scale Adjustments

Much research was done to examine the effect of financial literacy on consumer behaviour and well-being (Kaiser et al., 2020; Hung et al., 2009; Widdowson & Hailwood, 2007). Notably, the research results point in different directions. In many studies, financial literacy and financial education have been found to have a positive relationship with the desired financial outcomes or behaviour (Burke & Manz, 2014; Gathergood & Weber, 2017; van Ooijen & van Rooij, 2016; Christiansen et al., 2008; Chu et al., 2016). However, some research does not find a link between financial knowledge and financial outcomes (Fernandes et al., 2014; Anderson et al., 2017; Schmeiser & Seligman, 2013; van Rooij et al., 2011; West, 2012; Hung et al., 2009).

The use of numerous financial literacy scales might lead to inconsistency of the results. Also, the research suggests that there is no one financial literacy scale that would enable policymakers to define consumers’ needs; existing financial literacy measures have low reliability and some of the questions are not understood correctly by respondents; and more specialized measures of financial literacy might be required (Kunovskaya et al., 2014; Hung et al., 2009; Van Rooij et al., 2011; Hastings et al., 2012; Dew & Xiao, 2011; Smith et al., 2016). It suggests that a few specialized financial literacy scales could be developed for specific topics such as investments, retirement, and budgeting to provide a consistent basis for evaluation of financial literacy and its relationship with financial behaviour.

2. Proposed solution and Conceptual Definitions

Based on life cycle and permanent income hypotheses, an individual is assumed to adjust their spending and saving behaviour based on their level of income, spend within their expected long-term income and to be able to execute financial actions (Lusardi et al., 2017; Jappelli & Padula, 2013; Chu et al., 2016 ). Yet, there is ample literature showing that individuals might not posses enough financial knowledge required to perform these tasks correctly and make rational decisions (Lusardi & Mitchell, 2014; Jappelli & Padula, 2013; Chu et al., 2016; Campbell et al., 2011; De Meza et al., 2008 as cited in Xiao et al., 2014).

To resolve this inconsistency, different theories are applied to understanding the consumers’ decision-making process. For example, consumers’ mental accounting (Zhang & Sussman, 2018) might influence how consumers see their savings and perceive their financial actions. Behavioural economics recognizes psychological aspects and cognitive biases in consumers’ financial decision-making processes and their effect on financial capability (Hilgert, & Hogarth, 2003; West, 2012). The differences in financial outcomes between different groups of consumers can be attributed to the use of "rule of thumb”, mental accounting, and hyperbolic discounting (Bernheim et al., 2001; Foster et al., 2015).

To summarize, consumers might not make rational financial decisions, they have psychological differences and biases, they create mental accounts and might change their behaviour in response to nudges. Consequently, consumers might require simplified tools, such as professionally managed financial products, like mutual funds, and be aware of these tools and possess an ability to use these tools properly.

Therefore, a financial literacy measure needs to include items related to various topics to facilitate an understanding of consumers’ basic financial literacy, and of what consumers know about financial tools and how to use them. Given the complexity of financial decisions and different tools required for each financial area (such as retirement, investments, budgeting, savings, etc.), it follows, once again, that different specialized financial literacy scales in addition to a 5-question base scale will provide more precise insight.

3. How the Proposed Solution is Designed to Meet the Target Outcomes of the Ecosystem Priority 1

3.1 Retirement – Introduction - What to Measure to Achieve Ecosystem Target Outcomes

One of the major foundations of financial well-being is preparedness for retirement, thus it is one of the areas that will benefit from a deeper understanding which can be facilitated by developing a specialized financial literacy scaleFootnote 1 . This scale can contribute to achieving all three target outcomes of Ecosystem Priority 1: Communicate in Ways People Understand of the National Financial Literacy Strategy (Government of Canada, 2023) by providing policymakers, financial institutions, and consumer advocates with clear measurement of what Canadians know and what they do not know about the products and services (Outcomes 1 and 3), and about the appropriateness of the use of these products and services depending on consumers’ specific circumstances (Outcome 2). This measurement can provide insights to support decisions on communication, intervention, and services and products that are required to assist consumers in achieving their financial goals.

3.2 What to Measure

There is a shift of responsibility for retirement planning and savings from public entities to individuals, enabling more choices and control when it comes to investing or saving for retirement, however it requires consumers to have knowledge and tools to do so (van Rooij et al., 2011; Foster et al., 2015). Yet, the Financial Consumer Agency of Canada (2019) reports that less than half of the population (47%) have knowledge on “how much they need to save” for retirement. Additionally, large groups of consumers do not know the amount they could “safely withdraw from a portfolio” (Clements, 2006). On the other hand, research shows that financial literacy positively affects retirement-related financial management behaviour (Herrador-Alcaide et al., 2020; Arrondel et al., 2013).

Since the objectives of policymakers are to enable consumers to “put saving routines or systems in place”, and to understand consumer behaviour to be able to educate and improve intervention strategies (Financial Consumer Agency of Canada, 2021a; Waine, 2009), it follows that there is a need to measure consumer behaviour and knowledge in many specific areas including retirement-related area.

3.3 Are Specific Measures Included in Existing Studies?

The literature review shows that the current measures of financial literacy in retirement-related studies include only items related to numeracy and no specific retirement-related items (Kunovskaya et al., 2014; Anderson et al., 2017; Bianchi, 2018; Burke & Manz, 2014; Ćumurović & Hyll, 2019; Gathergood & Weber, 2017; Lusardi & Mitchell, 2011; Van Ooijen & Van Rooij, 2016). The fact that some of this research shows the link between financial literacy and retirement planning and in some cases this link is not found and the reported range of explained variance is low suggesting that some additional specific retirement-related items might further contribute to the explanation of variance in retirement planning behaviour. Consequently, this paper proposes to develop a retirement-related financial literacy measure that will help to determine to what degree a consumer is prepared for their retirement.

4. A Plan for the Development of the Proposed Solution and Evaluation of the Solution’s Validity

4.1 The Methodology

The methodology for the current research is adopted from the following studies: Park et al. (2020), Ashley et al. (2013), Tian & Hunter (2001), Kunovskaya et al. (2014), Hsee et al., 2015, and Diamond (2007). The psychometric validity of the retirement-related scale will be assessed and its external validity will be established using a representative sample (Dew & Xiao, 2011).

Development of Items

First, a list of topics and the related questions to be included in the financial literacy measure will be created based on a review of the relevant literature. Next, two focus groups will be held with industry professionals and consumers to refine the preliminary lists of topics and questions.

Refinement of Items

A. Content Validity

Delphi method will be used to assess content validity (Park et al., 2020) of the preliminary questionnaire. Several financial services experts will be asked to assess whether each of the questions relates to their designated topic (Park et al., 2020). Content Validity Ratio (CVR) will be calculated (Lawshe, 1975). Items will be modified if required. The rounds will continue until all items will have an appropriate level of validity.

B. Bartlett’s Test of Sphericity and Kaiser-Meyer-Olkin (KMO) Test

The preliminary set of questions will be administered as an online survey to a sample of consumers and the items will be examined by running Bartlett’s and KMO Tests (Hsee et al., 2015) to identify whether number of items can be reduced by using factor analysis.

C. Reduction of Number of Items

Following Ashley et al. (2013) and Park et al. (2020) approaches, Principal Components Analysis (PCA) will be run for each topic to identify if some items need to be removed. Next, Principal Axis Factor Analysis will be run on the remaining items to identify the underlying latent variables (Ashley et al., 2013).

D. Reliability and Model Fit

Cronbach alpha will be calculated to establish the reliability of the scale (Ramsey & Deeter-Schmelz, 2008; Hsee et al., 2015). For assessing the fit of the resulting model, a Confirmatory Factor Analysis will be completed (Ashley et al., 2013).

Final Questionnaire and the Sample

The full questionnaire will include the final set of items of the retirement financial literacy score and the typical five financial literacy items, demographic, and savings and retirement planning behaviour items. A representative sample will be drawn from the general population to facilitate establishing external validity of the scale (Dew & Xiao, 2011).

4.2 Evaluation of the Solution’s Validity

Construct validity and predictive validity of the solution will be evaluated.

Construct Validity

A. Known-groups Validity

Following Tian and Hunter (2001) approach, known-groups validity will be assessed for the retirement-related financial literacy score. It is expected that financial advisors and instructors possess more financial knowledge compared to the general population and their mean scores would be higher than the general population sample score.

B. Correlation with Other Scores

Building on the Park et al. (2020) and Ashley et al. (2013) approach, correlations between the retirement-related financial literacy score and two measurements of related concepts will be assessed. The objective financial literacy score (Xiao et al. 2014) and self-awareness of understanding of core financial concepts items (Disney & Gathergood, 2013) will be used for this purpose.

C. Factors Predicting the Score

To establish that the construct can be predicted by independent variables as expected (Hung et al., 2009), an ordered logistic regression analysis (Henager & Wilmarth, 2018) will be performed to estimate whether the demographic variables predict retirement-related financial literacy as expected (Lusardi et al., 2017; Hung et al., 2009; OECD, 2020; Potrich et al., 2015).

Predictive Validity

Predictive validity of the proposed scale will be done by assessing whether the retirement related financial literacy construct has an ability to predict retirement related financial behaviour (planning and saving) and outcomes (reported savings balance for retirement) (Hung et al. 2009; Boisclair et al. 2017). Literature uses Ordinary Least Squares (OLS) regression to estimate these predictions, controlling for demographic variables (van Rooij et al., 2011; Ashley et al., 2013).

Conclusions and Contribution

Financial literacy has become a strong focus of attention of scholars, policymakers, and marketers in sight of increased need to support financial resilience of the population. Additionally, measuring specific financial literacy can aid in developing appropriate communication in financial domain supporting Canadian consumers in achieving their financial goals which is one of the Ecosystem Priorities of the National Financial Literacy Strategy (Government of Canada, 2023). This provides an impetus to further examine the definition and the impact of financial literacy on the financial well-being of consumers and develop appropriate measures of financial literacy.

Based on the literature review this paper examined how financial literacy has been defined, the results of research of the effect of financial literacy on financial behaviour and outcomes in general and in the retirement related domain. Also, the paper reviewed conceptual foundations for understanding consumers’ financial behaviour, their needs for support and consequently, items that need to be included in a financial literacy scale. The paper further reviewed how financial literacy scales were used in research related to retirement planning and based on that, proposed the development of a retirement-related financial literacy scale. And, finally, the paper outlined the methodology for development and validation of this new scale that will serve as an enhancement for the existing general financial literacy scale to support future research in the area of retirement related financial literacy and wellbeing.

Additionally, from the contribution to the academic research domain, this scale might provide value in further empirical research on theories of consumer behaviour, and decision making related to the financial well-being domain. From the managerial perspective, the retirement related financial literacy scale can provide specific insights to developers of financial education programs, policymakers, consumer advocacy groups, and financial products marketers about areas where consumers might lack knowledge and skills to build and maintain their financial resilience. These insights will highlight the areas where consumers might need various support mechanisms which can equip consumers to make better retirement decisions, aiding in achieving the target outcomes of Ecosystem Priority 1: Communicate in Ways People Understand of the National Financial Literacy Strategy (Government of Canada, 2023) by providing clear measurement of what Canadians know and what they do not know about the financial products and services (Outcomes 1 and 3), and about the appropriateness of the use of these products and services depending on consumers’ specific circumstances (Outcome 2).

References

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