Economic Enfranchisement, Goal Setting, and Rural Development

Abstract

This analysis introduces a conceptual framework for economic enfranchisement and studies its effect on an individual’s likelihood to set strong financial goals. A conceptual and empirical model is developed to investigate how economic enfranchisement influences an individual’s likelihood to set a goal and the strength of that goal. The empirical analysis employs an ordered probit to account for the two-stage goal-setting and goal strength decision process. Results show that economic enfranchisement has a significant effect on an individual’s likelihood to set financial goals where more enfranchised individuals are more likely to set strong goals than their disenfranchised counterparts.

1. Introduction

Previous research has shown that goal setting is an effective mechanism for economic mobility; simply having a goal to improve one’s financial well-being (FWB) has shown to increase outcomes, regardless of effort put forth toward achieving the goal (Aguinaga et al., 2019). However, there are still many uncertain factors related to goal setting such as “what leads individuals to set financial goals?” and “why do some people set stronger goals?”. While development economics has typically focused on studying resource constraints, or external constraints, research in behavioral economics and psychology has indicated that issues of perceived control and enfranchisement may be relevant in the goal-setting process (Dalton, Ghosal, and Mani, 2016; Lybbert and Wydick, 2018). We propose a conceptual framework for economic enfranchisement, a concept that reflects an individual’s perceived influence over their financial future, and study its effect on whether or not and how strongly individuals set goals.

The study of psychological factors, or internal constraints, is becoming increasingly relevant in economics. The field of behavioral economics has emerged, applying psychology principles to economics to analyze behavior. Even more recently, over the past decade, a new area of research has emerged—behavioral development economics—applying a behavioral economics framework to development economics (Kremer, Rao, and Schilbach, 2019). This research field examines the interaction of economic, psychological, and social factors, and their role in development, particularly around poverty and welfare analysis.

An emerging area of research within behavioral development economics relates to goals and aspirations. Studies focused on pathways out of poverty have found relationships between aspirations and economic mobility, although the type of relationship is unclear. Lybbert and Wydick (2018) provide a framework for incorporating aspirations into decision-making and outcomes, while Dalton, Ghosal, and Mani (2016) find that poor individuals slip into a feedback cycle where they begin to aspire less, coining the term “aspirations failure,” defining that term as a level of aspiration (i.e., goal setting) that is lower than the person would otherwise be expected to be able to achieve. In other words, Dalton, Ghosal, and Mani (2016) find that “poverty curtails a poor person’s capacity to aspire.” The model by Heath, Larrick, and Wu (1999) on goals as reference points may indicate that both effects occur; people worse off may set higher goals, but they may also have difficulty finding the motivation to start. Additionally, much of the research surrounding goals focuses on effort put toward achieving them or outcomes once an exogenously dictated goal is set (Wuepper and Lybbert, 2017). Despite research indicating the importance of setting goals (Aguinaga et al., 2019), little research has been conducted surrounding why some people set goals and others do not.

In the absence of a consensus in the literature surrounding what leads individuals to set financial goals, and how strong they set goals, we study the effect of economic enfranchisement on goal setting. Economic enfranchisement, defined as the extent to which a person has influence on their economic well-being, has not been directly studied. We propose a conceptual framework for economic enfranchisement, highly related to but distinguishing it from other measures of perceived control and efficacy (ability) that have been studied in the behavioral economics and psychology literature. More specifically, economic enfranchisement specifically relates to the degree of control that a person has on their economic outcomes, rather than other personal outcomes that would be enveloped in a broader locus of control (LOC).

This research also opens additional pathways for research within behavioral development economics by highlighting the importance of economic enfranchisement in individual decision-making. We hypothesize that more enfranchised individuals are more likely to set strong goals, and less enfranchised individuals are less likely to set goals at all. This research tests the theory of aspirations failure, questioning whether people in poverty are indeed less likely to set goals and set strong goals, extending the theory’s context beyond income to consider disenfranchisement as a reason for failure to set goals. We maintain that goal setting and the strength of goals set is directly related to a person’s aspirations. Additionally, this research contributes to the literature around goals as reference points, considering both enfranchisement as an internal constraint and income as an external constraint. Further, this research deviates from prior research on goals by studying how an individual sets a goal, rather than goals that are set exogenously and assigned to an individual.

The empirical analysis uses survey data from the Area Sector Analysis Process (ASAP) program (Bordigioni et al., 2020; Salaghe et al., 2020), which surveys rural Americans about their individual and community economic goals and priorities. ASAP is a United States Department of Agriculture (USDA) NIFA-funded economic development extension and research program that seeks to assist communities in identifying their goals and then quantifying how those goals align with different targeted economic development efforts.

We employ a two-stage Heckman selection model with an ordered probit model in the second stage (De Luca and Perotti, 2011). The results confirm that there is a positive relationship between economic enfranchisement and the likelihood of setting a goal, and an even stronger likelihood of setting a strong goal. More broadly, this research emphasizes the importance of behavioral factors in economic mobility, providing a basis for future research and economic development initiatives.

2. Literature Review

There are three topics around which existing literature has provided a basis for research on economic enfranchisement and goal setting: (1) subjective well-being (SWB) and FWB, (2) perceived control, and (3) goals and aspirations. Research on subjective and FWB provides context for why people may seek to improve their financial situation, and how their financial situation can affect their overall utility. FWB sets the stage for studying individual goals to improve FWB, and why some individuals may be dissatisfied with their current FWB. While economic enfranchisement has not been directly studied, researchers have indicated that a related concept, perceived control over one’s circumstances, can affect subjective FWB. Finally, research on goals and aspirations, while relatively recent in economics, shows the importance of personal financial goals in questions of economic mobility.

2.1. Subjective and Financial Well-Being

SWB has long been investigated as a means to measure the ever elusive concept of “utility.” SWB enables researchers to study social and psychological aspects of life and their relation to economic outcomes, providing a reasonable proxy for experienced utility (Helliwell and Barrington-Leigh, 2010; Dolan, Peasgood and White, 2008). Although the level of SWB can be changed due to objective events or circumstances, there is no universal relationship, as each individual exhibits different preferences (Kahneman and Krueger, 2006).

Easterlin’s (1995) work has found that more money raises SWB at low levels of income, but does so less and less as income raises; in other words, there is a decreasing marginal utility to income. This is largely because income helps individuals meet certain universal needs (e.g., food, shelter, clothing), which makes a drastic difference for individuals in poverty (Diener et al., 1993). Once those basic needs are met, the effect of income is stronger when relative (rather than absolute) income is measured. Therefore, research on relative income is relevant in discussions of well-being (Miles and Rossi, 2007).

Relative income considers one’s income relative to others. Although people do not often know how much the people around them earn, the literature on relative income suggests that it considers changeable standards derived from expectancies, standards of living, and social comparisons (Diener et al., 1993). Both absolute and relative income have implications for perceived well-being but have different effects at different levels of development (Blanchflower and Oswald, 2004; Chang, 2013; Clark and Oswald, 1996). For example, absolute income has a large effect on utility for people in poverty, whereas relative income has a larger effect on utility for people in more developed countries.

While SWB is helpful for understanding overall utility, it is usually measured in a global, context-free manner, that is, with survey questions asking questions like “How happy are you with your life as a whole these days?” Global SWB certainly has its place, but narrow, context-specific well-being, which is assessed in a single area of life, can be more helpful for designing policy instruments with the intent to improve well-being. Van Praag, Frijters, and Ferrer-i-Carbonell (2003) proposed a model where SWB depends on satisfaction with different domains of life: work, financial, household, health, leisure, and environment. Their tests found that financial satisfaction was the strongest indicator of total SWB.

Other research has found a similar relationship. A study by Gerrans, Speelman, and Campitelli (2014) examining the effects of financial literacy interventions found that financial wellness was one of the strongest contributors to SWB. Satisfaction with one’s financial status, or FWB, relies more on objective measures than does SWB (e.g., assets, debt, etc.), but those objective factors cannot completely account for variation in FWB among individuals, as individuals exhibit different preferences for living standards (Brüggen et al., 2017). FWB is still strongly affected by subjective factors, like financial knowledge, attitudes, and behaviors (Gerrans, Speelman, and Campitelli, 2014; Shim et al., 2009).

Brüggen et al. (2017) defined FWB as "the perception of being able to sustain current and anticipated desired living standards and financial freedom" and discussed FWB’s distinction from financial efficacy. Financial efficacy surrounds a person’s skills and ability to control their financial matters. While financial efficacy can be one factor in FWB, FWB more broadly reflects a person’s ability to enact change.

2.2. Perceived Control

While financial efficacy is about having the necessary knowledge to control one’s finances, an individual may still feel they have little control over their finances. This concept has been studied in the psychology literature as perceived control and LOC. LOC is a concept that captures an individual’s perception of their ability to control what happens to them. It is generally divided into two categories—internal and external (Prawitz et al., 2013; Sumarwan and Hira, 1993). An individual with an internal LOC believes they are personally responsible for what happens to them, while someone with an external LOC believes that events in their life are the result of external factors, such as chance, fate, or powerful others. LOC has been called a companion concept to self-efficacy; control is perceived by the individual, although its perception is often based on past experiences (Lybbert and Wydick, 2018).

An individual’s LOC can affect their decisions by changing the perceived probability that their decisions will result in their desired outcome, affecting an individual’s choices and the desired outcomes themselves. An individual who attributes events in their lives to external factors alone may feel that they cannot change their circumstances because the effort they put in will have little effect on achieving the desired outcome. Further, LOC can also affect a person’s views of their current circumstances. LOC has been linked to life satisfaction (Johnson and Krueger, 2006) and related well-being indicators. Individuals with a more internal LOC tend to report greater satisfaction with various aspects of life. In the financial realm, an internal LOC has been linked to greater perceived income adequacy and satisfaction with one’s financial status (Prawitz, Kalkowski, and Cohart, 2013; Sumarwan and Hira, 1993). Danes’ (1991) study of farm women found that an internal LOC was a significant predictor of the perceived gap between living standards and living levels; women with a more internal LOC perceived a smaller gap between living standards and levels.

Throughout the literature on perceived control and LOC, there is no consensus regarding whether LOC is a consequence of past outcomes and circumstances, or a trait that affects decisions and perceptions, which then have implications for current circumstances and future decisions. Many studies implicitly assume that LOC determines behavior, but others have noted that the direction of causality may be reversed (Gerstenberg et al., 2018; Grinfeld et al., 2020). Further, LOC is often assessed in a very general sense, rather than in relation to specific domains of life. Furnham (1986) was the first to apply LOC to the financial domain, proposing an economic LOC scale. Survey respondents were asked their views on statements surrounding poverty, economic mobility, and wealth in relation to internal and external factors. Furnham’s scale distinguished between different types of internal and external factors, including work ethic, luck, fate, and powerful others.

Furnham’s economic LOC scale has been criticized for losing the previously considered unidimensionality of LOC. Interestingly, Furnham’s research found that both the richest and the poorest groups had the lowest internal LOC. An analysis of the sub-scores for the different factors reveals that each group had drastically different reasons for this. Poorer individuals had high “powerful others” scores, attributing their circumstances to power imbalances that hinder economic mobility. Wealthy individuals had higher “chance” scores, with the author noting that at high levels of wealth, there is a greater amount of risk in relation to investments and gross economic forces.

2.3. Goals and Aspirations

Much of the research surrounding perceived control and well-being focuses on past or current events and circumstances; however, perceived control also has the potential to affect future behavior through influencing an individual’s goals and aspirations. The relationship between perceived control, goals, and aspirations has been studied less in the realm of economics. While there is a plethora of psychology research surrounding goals and aspirations, much of it focuses on personal affective characteristics and cognitive biases (Locke and Latham, 2006).

It has been shown that one’s LOC has a connection to aspirations. Burlin’s (1976) study of career aspirations for high school girls investigated how an internal or external LOC influenced occupation aspirations. Subjects answered questions that would later lead to an internal-external LOC classification, as well as their occupational aspirations in an “ideal world” versus their actual occupational intentions. Girls with an internal LOC were more likely to choose occupations categorized as “innovative” in the “ideal-world” scenario. Girls with an external LOC were more likely to perceive that their futures were dictated by the “system,” choosing more traditionally female occupations, even in a hypothetical scenario where gender norms did not apply. However, when asked about their realistic intentions to choose an occupation, both types indicated they would choose more traditionally female occupations. While these findings have implications for the study of identity and gender norms, they also have implications for aspirations research, implying that an external LOC limits individuals’ ability to aspire to heights which they might otherwise not aspire (Akerlof and Kranton, 2000, 2010).

A study by Prawitz, Kalkowski, and Cohart (2013) examined the relationship between LOC and hope in the context of personal finances. Findings showed that individuals with an external LOC tended to be less hopeful about their financial futures and were less likely to direct efforts toward the achievement of financial goals. This suggests that LOC is an important factor in making progress toward goal achievement, but the study did not examine how LOC comes into play when an individual is conceiving of the goals themselves. The authors discuss the results of their analysis within a framework of goals; however, their surveys asked respondents whether they participated in various financial adjustment behaviors in recent months, such as cutting spending, dipping into savings, or postponing major purchases. The vast majority of “goals” were evaluated as such after the fact and represented behaviors or actions more than goals.

Danes and Rettig (1993) studied the role of perceived control in the intention to change one’s family financial situation. They defined intentions as “plans of action in pursuit of behavioral goals” using a survey that asked subjects their likelihood of changing their overall financial situation. The authors noted that both financial resource flexibilities and perceptual factors, like LOC, can influence such intentions. Findings showed that perceptual factors were crucial in the intention to change the family financial situation, in most cases outweighing resource flexibility factors. This again indicates the importance of perceived control but does not examine how it affects the setting of the goals themselves.

While the desired outcomes of goals are important for many individuals wishing to change their financial situation, it has been shown that the mere act of setting goals can improve outcomes. A study by Aguinaga et al. (2019) examined the effects of various interventions designed to help bring individuals out of poverty. Subjects participated in an experiment where they were asked to set a goal each month (selected from a list compiled by the researchers) and surveyed over the course of the months, where they were also randomly assigned to other interventions such as attending support groups or given monetary incentives for completing goals, or given no intervention beyond goal setting. The simple act of setting a goal was shown to be significant in improving financial outcomes, independent of the other interventions.

Interventions can help people in poverty set goals, but many in poverty lose hope and aspire to less than what they optimally could achieve. Dalton, Ghosal, and Mani (2016) studied this phenomenon, called aspirations failure. They argue that wealthy and poor people share the same preferences and behavioral biases in setting aspirations, but that poverty exacerbates the effect of a behavioral bias where people fail to realize how much their effort influences their aspirations. This results in a cycle where aspirations gradually lower. The authors view their framework as “the first step in a bigger project,” noting while poverty itself is linked to lower aspirations levels, it does not fully explain lack of aspirations.

It should be noted that although goals and aspirations are conceptually similar and the terms are often used interchangeably, they are distinct notions. Aspirations represent a broad hope or ambition of achieving something (Kremer, Rao, and Schilbach, 2019). For example, an individual might aspire to be wealthy or have a successful career. Aspirations are often based on societal norms; with the example of aspiring to have a successful career, societal norms dictate what “successful” is. Lybbert and Wydick (2018) regard aspirations as exogenously given, whether by culture, norms, environment, or one’s peers. This is a sentiment echoed by others, including Easterlin (1995) who proposed that aspirations can influence happiness, but that aspirations likely vary with levels of economic development. Goals, on the other hand, are more precise. A goal is a “discrete, tangible, extrinsic reward that has real consequences for physiological well-being” (Heath, Larrick, and Wu, 1999). Goals relate to specific objectives. Therefore, while one’s aspiration could be to “achieve financial freedom,” there are a variety of goals that could underpin the aspiration, like “pay off my student loans” or “save $5,000 this year.”

Heath, Larrick, and Wu (1999) model of goals as reference points provides a valuable framework for researching goals. In this framework, goals alter the psychological values of outcomes, affecting how individuals exert effort toward goals. Analyzing goals using prospect theory, the authors equate goals to reference points on a value function, where individuals experience loss aversion and diminishing sensitivity to gains and losses, which varies the closer or farther they are from their goal. In this model, people are risk-seeking when they are below their goals and will be more likely to make aggressive goals. In addition, higher goals (relative to one’s position on the value function) tend to guide individuals to exert more effort toward achievement of their goals and persist longer. Nevertheless, diminishing sensitivity means that those at extreme ends of the value function may have less motivation to achieve their goals. This theoretical model presents further basis for the study of goals and how an individual’s position relative to the goal (e.g., having low FWB versus a higher FWB) can affect goal setting.

3. Conceptual Framework and Theoretical Model

In this section, we propose a conceptual framework for economic enfranchisement and a theoretical model for evaluating its effect on setting goals and outline the ways that, while LOC is similar in application to economic enfranchisement, economic enfranchisement is a distinct concept.

3.1. A Proposed Conceptual Framework for Economic Enfranchisement

Economic enfranchisement is the extent to which a person has influence on their economic well-being. This concept is similar to LOC but distinct in some important ways. First, LOC focuses on perceived responsibility (or lack thereof) for life events. It does not take into account the individual’s skills, knowledge, or agency to change their economic well-being. Per Rotter (1966), LOC assesses whether an individual believes their behavior is linked to its consequences. Economic enfranchisement, on the other hand, takes into account both internal (perceptual) and external (objective) constraints and focuses on the degree of personal influence on personal economic outcomes.

One of the greatest criticisms of the LOC concept is that it is not unidimensional (O'Brien, 1981). LOC is thought to be internal or external; however, many have theorized that there are different types of externals. An individual’s belief that external factors are responsible for the events in their life could be referencing drastically different external factors, such as power structures or fate. Furnham (1986) noted this distinction when developing his economic LOC scale. Because of this, it can be difficult to consider the relationship between perceived control and issues of economic mobility. If the rich and the poor both feel that external factors are responsible for their life events, while the middle class feels the opposite; the concept of LOC has limited applicability for studying economic mobility.

Economic enfranchisement implies a unidimensionality from enfranchised to disenfranchised. Consider the example of a poor and a wealthy person who both have an external LOC. It is valid for both to have an external LOC, but the poor person may feel that way for reasons of systematic economic barriers, while the rich person may feel that way due to the riskiness of their investments. In the framework of economic enfranchisement, however, the wealthy person in this example would not feel disenfranchised due to these risky investments, while the poor individual would likely feel disenfranchised due to the systematic barriers.

Economic enfranchisement recognizes the importance of economic, psychological, and social factors when assessing well-being and the opportunities for change. Economic factors include the availability of resources; psychological factors include internal biases and perceptions; and social factors include one’s circumstances and environment. For this reason, it is a better measure for assessing economic mobility, goals, and aspirations than LOC.

There are notable gaps in the literature surrounding economic enfranchisement and goal setting. While there has been research studying the relationship between perceived control and hope or aspirations, economic literature has not explicitly studied economic enfranchisement as it is conceptualized in this paper. Further, the research on goals focuses on aspirations, effort toward goals, intention to change, or the efficacy of poverty interventions where individuals choose from exogenously dictated goals. Heath, Larrick, and Wu (1999) model of goals as reference points indicates that the individuals who are relatively worse off have greater incentive to set higher goals, but if they are too worse off (e.g., the worst off person in the community), they may have difficulty getting started, a phenomenon referred to as the “starting problem.” We also build on Dalton, Ghosal, and Mani (2016) research on aspirations failure, which indicates that individuals in poverty set lower aspirations. Based on the conflicting views of previous research, it is not clear whether less enfranchised individuals are likely to set higher or lower goals, or if they fail to set goals altogether.

This research looks at the act of setting goals—whether individuals set them or not, and whether they set goals that they think will make them significantly better-off or marginally better-off if achieved. Will increasing individual economic enfranchisement increase the likelihood of setting high financial goals?

3.2. Theoretical Model

The concept of the effect of economic enfranchisement on goal setting can be illustrated with the following utility function:

(1) $${\rm{U}} = \left( {1 + {\rm{g}}\left( {{\rm{I}},\,{\rm{E}},\omega } \right)} \right){{\rm{U}}_{\rm{0}}}$$

where U ₀ denotes an individual’s initial level of utility, and g denotes a goal as a function of income (I), economic enfranchisement (E), and a set of personal characteristics ω. The literature on goals, particularly Heath, Larrick, and Wu (1999), has established that when an individual sets a goal, it creates a reference point (the desired outcome) that is above one’s initial utility. Therefore, if g is greater than or equal to zero, (1 + g) is positive, and

(2) $$\left( {1 + {\rm{g}}} \right){{\rm{U}}_0} \ge {{\rm{U}}_{0.}}$$

It then follows that g(I, E, ω) ≥ 0. The functional form of U = (1 + g) U ₀ follows from the model of aspirations by Dalton, Ghosal, and Mani (2016). While that model considered effort toward a goal rather than the magnitude of the goal itself, the functional form illustrates how an individual sets a goal. If g = 0 (a goal is not set), then U = U ₀. In other words, the individuals do not seek to increase their utility in this way. On the other hand, if a goal is set, then U > U _0.

It has been established in the literature that income increases utility (Diener et al., 1993; Easterlin, 1995); ${dU \over dI}$ > 0. The effect of economic enfranchisement E on goals has not been studied. We hypothesize that ${dg \over dE}$ > 0; in other words, increasing economic enfranchisement increases goals; if the magnitude of E increases, the individual is more likely to set a goal (g > 0), and the magnitude, or strength, of the goal increases with E.

4. Data and Empirical Model

The data used in this analysis are from a survey administered to rural communities through the ASAP program (Bordigioni et al., 2020; Salaghe et al., 2020). The ASAP program is a research and outreach project administered through the USDA’s Western Rural Development Center that aims to support economic development initiatives by incorporating community preferences. The survey developed for the ASAP program, entitled “the Survey of Community Priorities for Quality of Life,” asks respondents about their individual and community economic, environmental, and social priorities and goals. The sample used in this study consists of data collected from 2014 to 2018 in rural counties in Arizona, Idaho, New Mexico, and Utah. Participants of the ASAP goals survey consisted of community members who volunteered to be a part of the program. ¹ While this is not a randomized selection method, outreach efforts were employed to ensure that participants were recruited from a broad swath of the community. We recognize that nonrandom sampling is often considered less than ideal for research purposes, and we also recognize that community-level extension-driven research often requires tradeoffs to garner adequate community “buy in” and support. After excluding samples for missing data (samples where respondents did not answer the questions of interest or provide demographic data), a sample of 2,130 respondents was used for this analysis.

Table 1 presents demographic characteristics for the sample, and Table 2 provides descriptive statistics. Of the respondents, 49% were female and 51% were male. The mean age of respondents was 49. The respondents reported their highest level of education attained and the mean year of education for the sample was 14.9 years, corresponding to a two-year college education. The mean household income for the sample, measured as the mean of midpoints of income ranges, was $74,142. The standard deviation for income was $47,320, indicating a large variance in household income for respondents.

Table 1. Demographic characteristics of sample (N = 2,321)

Table 2. Descriptive statistics for sample

Respondents answered a series of questions relating to their perceived level of economic enfranchisement and recent goal setting. The question “How much influence do you feel you have on your personal future economic well-being?” was used to indicate perceived economic enfranchisement. Respondents chose from the following options: 1. “I have little influence, my personal future is mostly dictated by outside forces”, 2. “My personal future is equally dictated by myself and outside forces”, and 3. “I have a lot of influence on my personal future, outside forces play only a small role.” This scale indicates one’s level of perceived economic enfranchisement, with option 3 indicating the highest level of enfranchisement and option 1 indicating the lowest. About one-third of respondents (33.1%) reported the highest level of economic enfranchisement, while 11.8% selected option 1, corresponding to disenfranchisement. The remaining 55.1% of respondents selected option 2, indicating moderate economic enfranchisement.

To indicate goal setting, respondents were asked “Over the past year, have you made any specific goals to improve your personal economic condition?” Over 65% of respondents indicated that they had set a goal, while the other 35% had not (Table 3). Respondents who reported setting a goal were asked about the strength of the goal using the question “If you stated a personal financial goal in [the previous question], how much better-off do you think you will be if you achieve this goal(s) this year?” Response options ranged from 1 for “the same” to 5 for “much better-off.” About 4.6% of respondents reported setting goals that would not make them any better-off, 5.4% set goals that would make them barely better-off, and 27.8% set goals that would make them a little better-off if achieved. “Moderately better-off” was the most common response (35.7%), and 26.4% of respondents indicated they would be much better-off if they achieved their financial goal(s).

Table 3. Survey questions and response distributions

To determine the effect of economic enfranchisement on goal setting, the two questions relating to goals are used as dependent variables in the study. Table 4 provides descriptions of the variables used in this study. The variable SetGoal, using the response to the question “Over the past year have you made any specific goals…” is a dummy variable indicating if the respondent set a goal. The variable GoalStrength, using the response to “…how much better off do you think you will be if you achieve this goal(s) this year?” indicates the strength of the goal that was set. However, there is a concern with sample selection of GoalStrength, as respondents only answered this question if they responded “yes” to SetGoal. To correct for selection bias, we employed a Heckman’s two-stage selection model (Heckman, 1979). This model combines two equations: the first, a selection equation, where a dependent variable determines whether another variable will be observed or not, ergo selecting a sample for the second dependent variable to be observed. Heckman’s two-stage model estimates these selection and outcome equations together using a maximum likelihood estimation, where the second stage of the model calculates likelihood using conditional probabilities that the first dependent variable (the selection variable) occurs.

Table 4. Variable descriptions

The strength of the goal was selected from a series of ordered responses. While ordinal, these responses cannot be treated as a continuous variable; we are unable to assume equal interval distances between options. Therefore, an ordered probit model is used. Ordered probit regression is used to preserve the ordering of categorial response options without treating them as a continuous variable. This type of model is frequently used in measures of FWB, life satisfaction, or other analyses where respondents assess a value on a scale without a uniform distribution (Cameron and Trivedi, 1986). An ordered probit model is used in the second stage of a two-stage Heckman model when the dependent variable of the outcome equation is an ordered categorical variable (Chiburis and Lokshin, 2007). Finally, to control for variations across communities, fixed effects are included for each county. We employ county fixed effects rather than community specific characteristics in order to control for the maximum amount of spatial variation for our investigation of goal setting and economic enfranchisement. However, further research into how specific county-level characteristics influence goal setting interact with economic enfranchisement is a fruitful topic for future research. The final specified model for individual i in county j is

$$SetGoa{l_{ij}} = \alpha 1*{\rm{E}}{{\rm{E}}_{{\rm{ij}}}} + \alpha 2*{\rm{LogIncom}}{{\rm{e}}_{{\rm{ij}}}} + \alpha 3*{\rm{LogAg}}{{\rm{e}}_{{\rm{ij}}}} + \alpha 4*{\rm{Mal}}{{\rm{e}}_{{\rm{ij}}}} + \alpha 5*{\rm{Colleg}}{{\rm{e}}_{{\rm{ij}}}}\,{\rm{ + }}{\varepsilon _{ij}}$$

$$\matrix{ {(GoalStrengt{h_{ij}}|SetGoa{l_{ij}}) = \beta 1*{\rm{E}}{{\rm{E}}_{{\rm{ij}}}} + \beta 2*{\rm{LogIncom}}{{\rm{e}}_{{\rm{ij}}}} + \beta 3*{\rm{LogAg}}{{\rm{e}}_{{\rm{ij}}}} + \beta 4*{\rm{Mal}}{{\rm{e}}_{{\rm{ij}}}} + \beta 5} \hfill\cr {\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad *{\rm{Colleg}}{{\rm{e}}_{{\rm{ij}}}} + {\varepsilon _{ij}}} \hfill\cr} $$

Table 5 presents descriptive statistics for the subsamples that differentiate the two stages of the model. These subsamples are defined by responses to SetGoal. The sample for SetGoal = 1 is the selected sample, which feeds into the second stage of the model for conditional analysis of GoalStrength. Significant differences between the subsamples can be seen, particularly across age and income, with respondents who reported setting a goal being 5 years younger, on average, than those who did not, and having annual household income $10,000 higher on average than those who did not set a goal. Further, the means for EE, the measure of economic enfranchisement, also vary significantly across the two samples, with the sample for SetGoal = 1 appearing to be more enfranchised than the sample of individuals who did not set goals.

Table 5. Descriptive statistics for subsamples, SetGoal = 1 versus SetGoal = 0

5. Results and Discussion

Results for the final model (omitting county fixed effects) are presented in Table 6. The full results including the fixed effects are presented in Appendix Table A.1. The regression output shows the maximum likelihood estimation of the probit model. The bottom panel shows the probit coefficients for SetGoal, while the top panel shows ordered probit coefficients for GoalStrength after correcting for the selection bias of SetGoal. The Wald chi-squared (232.76) and p-statistic (<0.0001) suggest the overall model is highly significant.

Table 6. Regression output for two-stage model, excluding county fixed effects

*p < 0.1, **p < 0.05, ***p < 0.01.

See Appendix A for full table with county fixed effects.

The first stage of the model, the probit equation for SetGoal, shows the independent variables’ effects on the dependent variable SetGoal. Nearly every independent variable of interest, except for gender, has a highly significant effect on setting a goal. An increase in perceived economic enfranchisement is associated with an increased likelihood to set a goal. Similarly, the log of income is associated with increased likelihood to set a goal. The log of age is negatively associated with likelihood to set a goal. A possible explanation for this is that older individuals have less time to improve their financial circumstances, so may feel discouraged from setting goals. College, a dummy variable for having education past a high school degree, had the largest coefficient.

The results for the second stage of the model show the effects on the dependent variable GoalStrength. Economic enfranchisement again has a significant positive effect. The effect of income is not as significant. Age again has a significant negative effect. While gender did not have a significant effect on the likelihood of setting a goal, it did have a slightly significant negative effect on the strength of the goal, indicating that males are slightly less likely to set strong goals than females. Interestingly, the effect of having a college education does not have a significant effect on the strength of a goal. This is peculiar, given that it had the strongest significant effect in determining likelihood to set a goal.

Recall that the second stage of the model is an ordered probit model. The interpretation of probit coefficients is difficult due to the non-linearity of the probability function. The model coefficients provide the change in the z value resulting from a unit change in an independent variable. Marginal effects can be used to better understand the impact of the independent variables. Marginal effects change at each value of each independent variable; thus, they can show the effect of isolated values of the variables but do not infer the exact relationship for all points, as in OLS.

Table 7 shows the average marginal effects on GoalStrength for each value of EE. Given that these are average marginal effects, the absolute magnitude and statistical significance of the coefficients is not as meaningful as the direction, relative magnitudes across the various levels of economic enfranchisement. The most significant results appear for the highest level of GoalStrength, indicating the likelihood of respondents selecting the response of “Much better off” when asked how much better-off they would be if the goal they set was achieved. While this effect is significant and positive for all three observed levels of economic enfranchisement, it is about twice as high for enfranchised individuals (EE = 3) than disenfranchised individuals (EE = 1). This result indicates that economically enfranchised individuals are not only more likely to set goals, but more likely to set strong goals compared to disenfranchised individuals. Furthermore, it is interesting to note that respondents who answered either 1, 2, or 3 on the GoalStrengh question all have negative marginal coefficients on the likelihood of setting a goal and the marginal coefficients on people who set strong goals (with a GoalStrength of 4 or 5) were positive. The marginal coefficients were all statistically significant and positive for respondents who answered who set the strongest goals (GoalStrength of 5).

Table 7. Average marginal effects for GoalStrength at all values of economic enfranchisement (EE)

Values in parentheses are standard errors. *p < 0.1, **p < 0.05, ***p < 0.01.

These results expand upon findings from Heath, Larrick, and Wu (1999) about goals in a value function framework. In their framework, those who are financial worse off will tend to set higher goals. These results contradict their theory, showing that those who set higher goals have higher incomes. However, economic enfranchisement comes into play as an additional factor in the goal-setting framework. Those who feel they have more influence on their financial situation will be more inclined to set goals and more inclined to set higher goals. These findings add the consideration of an internal constraint in models of goals and economic mobility, one that has a more significant effect than income or postsecondary education. By considering these internal constraints, policy makers, economic developers, and the general public can be more sensitive and responsive to individuals in extreme poverty and consider the role of psychological and behavioral factors in policy options.

While these results have implications for micro-level economic development policy relating to goals, they open broader questions surrounding the factors that affect an individual’s economic enfranchisement. While economic enfranchisement may not necessarily depend on income in a causal manner, the data in this sample suggest that the disenfranchised tends to be in lower income groups than the enfranchised (Table 8). The highest earners of the sample also appear to be the most enfranchised; over 44% of respondents with income over $100,000 reported the highest level of economic enfranchisement, while only 6% reported feeling disenfranchised. The data also suggest that the more educated tends to be more enfranchised. Respondents who indicated feeling disenfranchised tended to have lower levels of educational attainment, while more educated individuals tended to report feeling more enfranchised. This is suggestive of relationships between economic enfranchisement, education, and income, although the direction of the relationship is unclear. These relationships may provoke questions of multicollinearity; however, variance inflation factors were calculated in the early stages of the model to test for multicollinearity, and no multicollinearity was found (see Appendix A, Table A.2).

Table 8. Cross tabulations of select variables and economic enfranchisement (EE)

This model, like others discussed previously, has its limitations. First, it does not make claims of the direction of causality. Behavioral economists often struggle with issues of causality, as a number of mechanisms muddy the waters. Literature on LOC has suggested that an internal LOC may be the result of past life events and their outcomes, accumulating to shape an individual’s perceptions of the world around them. The same could be theorized of economic enfranchisement and goals; a disenfranchised individual may feel disenfranchised because the goals they set throughout their life were not achieved. However, this relationship between enfranchisement and goals relies on the experience of attempting many goals over time. When broken down to a singular goal or a few goals in a short time period, as in this analysis, there is less basis for claims about the effect of a goal on one’s economic enfranchisement.

6. Encouraging Economic Enfranchisement

We have demonstrated that economic enfranchisement is an important antecedent to setting strong personal economic goals and that there is a deep literature demonstrating the importance of goal setting in personal financial improvement (Aguinaga et al., 2019; Heath et al., 1999; Lybbert and Wydick, 2018). While further research is needed to fully understand the factors that contribute to people feeling economically enfranchised, we can say that economic enfranchisement is associated with certain personal attributes (Table 9).

Table 9. Correlations between economic enfranchisement (EE) and respondent characteristics

Unsurprisingly, economic enfranchisement is positively correlated with income and educational attainment. It is certainly understandable that higher income and more educated people would feel more in control of their personal financial situation. Furthermore, people who expressed that they felt secure about their personal financial situation and people who expressed the expectation that their personal financial situation would increase in the next 5 years were more likely to also feel economically enfranchised. Possibly more surprising is that age and the length of residency in the community are negatively associated with a feeling of economic enfranchisement. This may indicate that more needs to be done to reach out to older workers who may be feeling more disenfranchised and who may be less likely to set economic goals. This result is also related to the community embeddedness literature. Community embeddedness, or the extent to which individuals are enmeshed in their communities, has previously been investigated as a factor in job satisfaction (Mitchell et al., 2001; Ng and Feldman, 2014). Lastly, economic enfranchisement is not significantly associated with some factors which might be hypothesized to correlate, such as the perception of the quality of k-12 education in the region. However, there is some association with the perceived quality of the public safety services (e.g., police and fire protection) in the region.

To reiterate, these correlations are suggestive but not a definitive analysis of the causal factors associated with economic enfranchisement. We believe that a formal analysis of the causal factors associated with economic enfranchisement is a fertile area for future research and would greatly benefit the economic development literature.

A fruitful opportunity for future research would be to use the community capitals framework (CCF) (or similar theoretical construct) to determine specific factors that contribute to goal setting and interact with economic enfranchisement. The CCF was originally developed by Flora and Flora (2008) and expanded upon in the rural wealth formation framework (Pender, Marré, and Reeder, 2012). The CCF includes seven types of community capitals: social, cultural, political, human, financial, natural, and built (or physical) capital. Flora and Flora (2008) observed that communities that were successfully supporting sustainable local community and economic development were focusing on these capitals. Since its creation, the CCF has been used as an analysis tool that allows researchers and community leaders alike to adopt a systems view of each community, accounting for “various elements, resources, and relationships within a community and their contribution to the overall functioning of the community” (Mattos, 2015). The CCF is generally applied to guide efforts to promote economic, social, and environmental sustainability, design community development initiatives, and is used as a framework for explaining community development processes and potential investment interactions.

7. Conclusions

This analysis has introduced a conceptual framework for the role of economic enfranchisement, a concept indirectly studied but explicitly absent from economic literature. Economic enfranchisement, which is the extent to which a person has influence on their economic well-being, is shown in this analysis to have a significant effect on an individual’s likelihood to set financial goals; more enfranchised individuals are more likely to set goals than their disenfranchised counterparts. Further, the goals they set are more likely to be strong than goals set by disenfranchised individuals.

This work contributes to the growing literature on goals in two main ways. First, most of the research on goals uses exogenously set goals assigned to individuals and analyzes effort, persistence, or achievement, whereas this research analyzes factors that influence whether or not an individual sets a goal in the first place, and how strong they set their goal. Second, much of the literature on goals focuses on external resource constraints, while this research considers economic enfranchisement as an internal, or behavioral, constraint to the goal-setting process.

The results of this analysis have implications for economic development on a micro-level. As recent research on goals has indicated that goals are an effective mechanism for economic mobility (Aguinaga et al., 2019; Lybbert and Wydick, 2018), interventions that aim to increase goal setting may be worthy of further research. While Aguinaga et al. (2019) endorsed assigning goals to individuals, this research suggests that helping individuals feel more enfranchised can guide them to set their own goals—a strategy that may be a less traditional intervention but potentially less costly as well. Further research on financial outcomes for individuals who experience an increase in economic enfranchisement is needed; however, positive results for such research could indicate that these micro-level interventions could be highly effective.

The concept of economic enfranchisement and its effects on economic behaviors such as goal setting represents an exciting area for future research. First, while this analysis has shown that economic enfranchisement is a significant factor in one’s decision to set goals, there is still much research to be done to determine how economic enfranchisement can be increased. This research was conducted using survey data that asked respondents about goal-setting behavior after the fact. It could be further expanded by analyzing goal-setting behavior over time, looking at not only whether goals were set, but if they were achieved and how much effort was put forth toward them.