WESTERN TANAGER MANUSCRIPT REVIEW HISTORY … · WESTERN TANAGER MANUSCRIPT REVIEW HISTORY...

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This document is part of a JCR Manuscript Review History. It should be used for educational purposes only.

WESTERN TANAGER MANUSCRIPT REVIEW HISTORY MANUSCRIPT (ROUND 2)

Abstract Concentration on consumption in material environments characterized by too much rather than too little has left important gaps in understanding of how most of the earth’s population navigates the marketplace. Accordingly, we investigate bottom-of-the-pyramid or impoverished consumers, who increasingly are considered viable market segments by consumer researchers and marketing practitioners. Our primary research objective is to better comprehend the relationship between societal poverty and subjective well-being as moderated by psychological need deprivation and described by self-determination theory. Data were gathered in the world’s poorest countries, and we find that greater societal poverty reduces well-being as life satisfaction but not as happiness. Life satisfaction is further explored, revealing that autonomy and relatedness improve poverty’s negative influence on life satisfaction, but only if the basic necessities of life are available as described in the literature by the term consumption adequacy. Our findings inform consumer research and provide directions for future studies.

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Understanding bottom-of-the-pyramid (BOP) or impoverished consumers has attracted recent attention by academics as well as marketing executives from major global corporations (Jenkins and Ishikawa 2009). These consumers are concentrated in four regions of the world—Africa, Asia, Eastern Europe, and Latin America and the Caribbean—and they number between four and five billion strong depending upon the metric employed (Pitta, Guesalaga, and Marshall 2008). What they lack in personal income, with many subsisting on less than US $2.50 per day, they make up for in sheer volume across individuals and communities to about $5 trillion in UN designated purchasing power parity (Hahn 2009). Given the expansive nature of these interests, it is surprising that BOP research has centered on hurdles to product development and distribution, with little empirically-based information on consumption. The profiles that do exist often are incomplete and derived from case examples, failing to represent broader populations. As a consequence, many findings involve the ability of the poor to enter into exchange relationships rather than their preferences, fulfillment of important needs, and other psychological outcomes associated with consumer behavior (Olsen and Boxenbaum 2009).

Visual representation in figure 1 shows how widespread the various levels of poverty are based on human development categories advanced by the United Nations. About three-fourths of the planet’s population lives in less than ideal material conditions, defined by much lower levels of marketplace abundance and a lack of the bargaining power necessary to access this abundance. Recent statistics fill in the details (www.globalissues.org) and reveal that nearly half the world’s population lives in absolute poverty. The poorest 40% of the planet’s people account for only 5% of total income, yet the wealthiest 20% have almost three-fourths. Over one billion people in the least developed countries have inadequate access to potable water, and nearly twice that number lack any basic sanitation. Almost half the children in the world (one billion) live in poverty, with one-in-three without appropriate shelter, and one-in-seven without access to health services. These figures suggest that much of humanity experiences their consumption environments in markedly different ways than does most of the developed and predominantly western world (Hill 2001).

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---------------------------------------------------------------- Thus, our research perspective is that understanding BOP consumers requires a depth of knowledge of their consumption and its outcomes, which is lacking in the marketing literature in general and the consumer behavior literature in particular (Chakravarti 2006).The context of too much, which captures marketplace experiences of consumers who exist at the top of the pyramid, may not be appropriate for consumers who occupy the much larger bottom two rungs of figure 1, and are forced to live with too little. As a consequence, our study objective is to better understand the relationship between societal poverty and consumer well-being to fill part of this important gap. We next explore subjective well-being and societal poverty to develop hypotheses about BOP consumers. Self-determination theory (Deci and Ryan 2000) is then used to look at relationships between impoverishment and individual well-being moderated by psychological need fulfillment. Data from more than 77,000 consumers across 51 developing and least developed nations in the world are juxtaposed with multidimensional poverty data. Our analyses provide nuanced portrayals of impoverished consumers, and findings have implications for consumer research that go beyond more typical understanding of the world’s affluent citizens.

RESEARCH PERSPECTIVES AND HYPOTHESES

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Subjective Well-Being and Impoverishment Looking more broadly and beyond the consumer research domain, subjective well-being research has seen considerable progress and continues to flourish, particularly in the economics and psychology literatures (Frey and Stutzer 2002; Kahneman and Krueger 2006). Over several years, researchers have learned that poor health, lack of social contact, unemployment, and other factors, negatively influence subjective well-being (Diener and Seligman 2004; Dolan and White 2007; Easterlin 2006). Yet comprehensive findings summarized in a review of the well-being literature highlight that a complete understanding of the impact of subjective well-being remains elusive (Dolan, Peasgood, and White 2008), even though volumes of research explore the relationships between income and well-being or overall happiness (Diener and Biswas-Diener 2002; Easterlin 1995). More current studies seek to fill this gap, and they provide a detailed comprehension of the income-well-being relationship, showing both contingent and conditional effects among variables (Diener et al. 2010). Subjective well-being encompasses individuals’ affective and cognitive evaluations of their lives (Diener 2000). The affective dimension of subjective well-being involves happiness, or one’s pleasant/unpleasant experience of her/his moods and emotions (Diener et al. 1999). Life satisfaction constitutes a person’s global evaluation of her/his life situation (Diener and Diener 1995). Given the implied judgment of overall satisfaction inherent in such a definition, scholars suggest that our life satisfaction is a relatively enduring and stable evaluation distinct from one’s affective state (Diener, Oishi, and Lucas 2003). Indeed, rigorous discriminant validity testing reveals the distinctiveness of cognitive well-being or life satisfaction from affective well-being or happiness (Lucas, Diener, and Suh 1996). As such, well-being theorists (Diener 2000; Diener et al. 1999, 2010; Schimmack et al. 2002) advocate the treatment of these dimensions as separate yet equally important components for understanding subjective well-being. Grounded in such work, we also adopt this conceptualization.

Given the plight of BOP consumers, as well as consumers in moderately to moderately-low developed nations, it is surprising that research examining impoverishment and well-being is lacking. Although some individual consumption components of impoverishment are considered (e.g., health and education), capturing the comprehensive impact of poverty on subjective well-being may be very difficult (Duclos, Sahn, and Younger 2006). A possible explanation involves the misspecification by economists of low income as equal to poverty (Christoph 2010; Heady 2008). Consumer research has long considered the multifaceted nature of poverty and restriction beyond a simple lack of income (Hill 1991; 2001; Hill and Stamey 1990). For example, scholars investigating consumer choice identified the attributes of restriction that impact emotional and physiological reactions, with greater constraint profiles leading to negative outcomes. Salient factors include: (1) self-imposed or other-imposed; (2) short-term, long-term, or permanent; (3) loss of item or lack of access; (4) intensity of need; (5) existence /applicability of alternatives; and (6) level of acceptance and agreement. These restrictions and goals combine in ways that lead to a variety of cognitions, affective states, and behaviors that ultimately determine consumer well-being (Botti et al. 2008).

This perspective is substantiated by the current global research programs led by Oxford Poverty and Human Development Initiative and United Nations Human Development Program, emphasizing that poverty has multiple, distinct, and differential components (Alkire and Santos 2010). However, multifaceted views of the poverty impact on well-being and other psychological factors remains understudied. Moreover, much of the literature claiming to explore poverty’s role in subjective well-being provides novel approaches or nuances for testing the familiar income and well-being relationship (Sahn and Younger 2006). Thus, taking cue from research positing a multidimensional approach to poverty (Duclos et al. 2006; Sahn and Younger 2006), we examine

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impoverishment according to three categories as delineated by recent global poverty research (Alkire and Santos 2010). Specifically, we consider impoverishment to be a composite of deprivations of consumption in education, healthcare and nutrition, and key services such as water, sanitation, and electricity. This typology accounts for the most crucial disparities across societies. Thus, we are interested in understanding the nature of individual subjective well-being in the face of societal impoverishment among BOP consumers. In spite of the empirical differences between affective and cognitive well-being, we predict that impoverishment’s multidimensional nature will negatively influence both happiness and life satisfaction. Unlike income or monetary wealth, which is one-dimensional, poverty involves aspects of deprivation related to individuals’ overall quality of life. Although limited research reveals the individual integrity and underlying social strength within many poverty subgroups (Hill 1991; Viswanathan et al. 2010), evidence indicates that powerful and unrelenting deprivation faced by poor consumers may take a heavy physiological and psychological toll (Hill, Felice, and Ainscough 2007). Consider the most likely scenario given previous investigations: other-imposed restrictions because of constraints associated with caste, socioeconomic heritage, and/or racial or gender prejudices; perceptions of inescapable poverty from birth to death; lifetime history of little or no access to needed much less desired goods and services; few if any other options that come close to meeting these demands; and acceptance that the situation will continue indefinitely despite its unfairness. This scenario represents the worst possible consumptive circumstances. We expect these conditions may lead to what Chakravarti (2006) refers to collectively as “ill-being,” negatively impacting happiness and life satisfaction. As such, we predict that:

H1: Societal consumption impoverishment negatively relates to individual affective well-being or happiness. H2: Societal consumption impoverishment negatively relates to individual cognitive well-being or life satisfaction.

Self-Determination Theory

An apt theoretical paradigm to bring together this disparate literature, which has been advocated in recent BOP research dialogues (Chakravarti 2006), is self-determination theory (SDT). At its foundation, this theoretical approach to understanding psychological development focuses on social-contextual conditions that give rise to healthy engagement with one’s living environment in contrast to alienation from and passivity towards the world (Ryan and Deci 2000). Empirical results from these investigations reveal three primary psychological needs that must be met in order for people to experience fulfillment with their existences: (1) autonomy or perceptions of power/control over one’s actions; (2) competence or belief in one’s capability to perform the essential tasks in life; and (3) relatedness or intimate and long-lasting connections to important others (Patrick et al. 2007; Ryan and Deci 2000). While applications to a variety of subpopulations and for a number of purposes have elicited relevant factors, having choices, positive experiences, and an acknowledgement of human value clearly are necessary (Deci, Connell, and Ryan 1989). This need structure manifests in healthy individuals as feelings of volition, and they are important regardless of whether the cultural milieu is collectivistic or individualistic or whether the culture is horizontal or vertical in power distribution (Chirkov et al. 2003; Ryan and Deci 2000). Thus, our desire for self-regulation is best defined by high degrees of sovereignty over individual decision making, with the opposite viewed as heteronomy or interference with vital choices that ultimately lack self-endorsement (Ryan and Deci 2006). A spectrum of possibilities is described by

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Moller, Deci, and Ryan (2006, 1025), and they show that “controlled regulation involves feeling pressured, coerced, or seduced into action, whereas autonomous regulation involves doing what one finds interesting or important and would be inclined to do more freely.” Of course, most relevant psychological outcomes differ as well, with persons under the greatest external control experiencing alienation, lack of motivation, and lower well-being, and persons under self-regulation experiencing social cohesion, intrinsic motivation, and higher well-being. Research confirms that when psychological needs comprising self-determination theory are met, individuals experience much greater well-being (Patrick et al. 2007). Central to our study is how these needs, especially autonomy and relatedness, influence the relationship between societal impoverishment and well-being as moderating influences. SDT researchers allude to such possible relationships, describing how the context and social conditions might interact with psychological fulfillment of human potential to create disparate effects on our well-being (Ryan and Deci 2000). Accordingly, we might expect consumers with greater need fulfillment to experience diminished negative effects on their individual well-being, even in the face of social conditions characterized by consumption impoverishment. However, an alternative perspective suggests that with conditions of extreme poverty, this ameliorating effect may not occur since consumption may be dominated by survival that disallows a focus on high-order needs. These approaches require our use of alternative hypotheses grounded in the logic provided next.

Autonomy. Self-determination theory considers a person to be autonomous “when his or her behavior is experienced as willingly enacted and when he or she fully endorses the actions in which he or she is engaged [in] and/or the values expressed by them” (Chirkov et al. 2003, 98). Thus, autonomy’s converse conceptualization, importantly, does not imply dependence on others but, rather, a state of heteronomy as described above. Indeed, autonomy is diminished if behaviors and choices are seen as constrained by external (or internal [Deci et al. 1989]) forces beyond one’s control that limit or even force an individual to behave in a manner opposed to his or her beliefs or values (Chaturvedi, Chiu, and Viswanathan 2009; Moller, Ryan, and Deci 2006). Therefore, if consumers experience significantly greater autonomy, we expect that feelings of control, choice, and power will reduce the negative influence of impoverishment on subjective well-being. Even in spite of the relative educational, nutritional, and living standard consumption deprivations that characterize their situations, the ability to have say in their fate or destiny may soften poverty’s impact. When heteronomy prevails to constrain individual options and diminish one’s control over his or her fate, however, the already negative effects of societal impoverishment on well-being may be even more devastating. Thus, we predict the first competing autonomy hypothesis:

H3a: The relationship between societal impoverishment and subjective well-being is moderated by individual autonomy—greater autonomy reduces the negative relationship between impoverishment and well-being.

Relatedness. Individuals experience fulfillment of the psychological need relatedness

through intimate and long-lasting connections with important others (Baumeister and Leary 1995). Although need to feel connected to friends and family often characterizes psychological feelings of relatedness, studies also have explored the relatedness between students and teachers and between individuals and the larger community (Clark, Frijters, and Shields 2008; Deci and Ryan 2000). An individual’s feelings of relatedness, along with other SDT psychological needs variables, have been shown to positively impact subjective well-being (Jorgensen, Jamieson, and Martin 2010). Taking a more nuanced perspective of SDT as moderating this relationship, we expect that individual-level relatedness curbs the negative impact of societal-level consumption impoverishment on subjective well-being. Therefore, our most intimate connections to family and friends may enhance well-being

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by offsetting some of the detrimental effects of societal impoverishment. Lack of such connections, however, can worsen the negative impact of poverty on individual well-being. As such, we predict the first competing relatedness hypothesis:

H4a: The relationship between societal impoverishment and subjective well-being is moderated by individual relatedness—greater relatedness reduces the negative relationship between impoverishment and well-being.

Competing perspective. The materialism literature in consumer research is mixed on its emphasis, with Kasser (2002) suggesting that there is a “paucity” of research that examines the materialism-well-being connection, and Rindfleisch, Burroughs, and Wong (2009) noting that well-being is the primary focus rather than any consumption behaviors. Nonetheless, there is widespread agreement that people in advanced societies characterized by materialistic values tend to experience lower levels of well-being in the form of life satisfaction (Arndt et al. 2004). Indeed, consumers who persist under the very worst possible material circumstances because of extreme impoverishment, and are forced to seek the barest necessities of life in order to survive, are not able to experience much subjective well-being regardless of any other more positive aspects of their lives (Kasser 2002). The potential dividing line has been described in the consumer behavior literature as consumption adequacy, defined as the most essential goods and services that must be acquired before citizens within a nation can rise above a short-term focus on continued existence and our able to concentrate on consumption behaviors associated with long-term desires and fulfillment (Hill 2005; Hill et al. 2007). Accordingly, fulfillment of psychological needs including autonomy and relatedness may improve well-being, but only for those individuals in societies existing above the consumption adequacy threshold. For individuals in societies below the consumption adequacy threshold, autonomy and relatedness will have little to no influence on subjective well-being. Given this perspective, we offer the second set of competing hypotheses:

H3b: The relationship between societal impoverishment and subjective well-being is only improved by individual autonomy when nations have advanced to or beyond the point of consumption adequacy.

H4b: The relationship between societal impoverishment and subjective well-being is only improved by individual relatedness when nations have advanced to or beyond the point of consumption adequacy.

METHOD

Sample and Data Sources

Given extant knowledge of global impoverishment as depicted in figure 1, our goal was to develop a broad-based model of societal poverty, individual well-being, and psychological need fulfillment for BOP consumers. To empirically accomplish this task, we assembled a multilevel dataset that included both individual consumer- and society-level information. Individual-level data are derived from a large-scale multinational investigation, the World Values Survey (World Values Survey, 5 Wave Aggregate, 1981-2008). Country-level data are derived from the Oxford Poverty and Human Development Initiative of Oxford University and United Nations Human Development Program. Details on each data source follow.

We obtained individual-level measures, including subjective well-being dimensions, self-determination theory variables, and individual demographic variables from the World Values

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Survey (WVS). Given that we relied on this secondary data source for our individual measures, we were not able to control the design and measurement of variables of interest—a natural limitation inherent in using any such data sources. The WVS is conducted by University of Michigan Inter-University Consortium for Political and Social Research. Our study employed the comprehensive version of the WVS that spans from 1981-2008 across 87 societies. The extensive coverage allowed us to select countries characterized as medium, medium-low, and low human development. We also were able to match the year of the survey with the corresponding year of our national poverty data—a range that was between 2003 and 2008.

WVS data are gathered in each country by local universities and social science research organizations through personal interviews using survey instruments translated/back-translated to promote consistency and, importantly, to promote functional equivalence of items. Nonetheless, we performed multiple group confirmatory factor analysis on the individual-level items to evaluate measurement invariance in support of our theoretical comparisons (Steenkamp and Baumgartner 1998), which is described in the analysis section of the paper. In each country, respondents were recruited by local research organizations using a stratified systematic design to ensure the sample was representative of the country’s population by age, education, ethnicity, and gender. Each nation produced a minimum of 1,000 completed responses. Average sample size for the countries included in our study is 1,523.

We were interested in how societal poverty influences individual outcomes. Our goal was to maximize the national coverage so as to represent as much of the developing world’s population as possible; however, we also were constrained to those countries with available poverty data that overlapped with the WVS sample. Naturally, this is a limitation of our study, as with most cross-national research relying on secondary measures. Appropriate society-level data are available for the 51 nations listed in table 1, corresponding with our individual-level sample. This produced an individual-level sample (level 1) of 77,646 consumers and a country-level sample (level 2) of 51nations. The mean age of sample respondents was 39 years old, 52% were female, and 57% were married. Respondents averaged a tenth-grade education, and reported an average income in the third decile, where one is the lowest and 10 is the highest category relative to local economic situations. The predominant self-reported social classification was working class.

As described in our conceptual development, we sought multidimensional poverty statistics that incorporate multiple sources of consumer impoverishment. Accordingly, we utilized the Multidimensional Poverty Index (MPI) as part of the Oxford Poverty and Human Development Initiative (OPHI). Their officials analyzed data from 104 countries with a combined population of 5.2 billion (78% of the world total). About 1.7 billion people in these countries constitute nearly one-third of the entire sampling frame, and they live in multidimensional poverty according to the MPI. This exceeds the 1.3 billion people in the same countries estimated to live on $1.25 a day or less, the commonly accepted measure of extreme poverty (Alkire and Santos 2010). Further, the MPI captures deprivations directly with regard to consumption of health/nutrition and educational outcomes, as well as with respect to essential key services. In some countries these resources are provided free or at low cost, yet in others they are out of reach even for many working people with regular incomes. Disparities in their provision are accommodated for in the formation of the MPI. Variables

Impoverishment. As described previously, OPHI research surfaced in response to lack of multidimensional global poverty instruments. Founding researchers of the program argued that looking at a single deprivation measure did not yield very accurate representations of individual, household, or societal poverty (Alkire and Santos 2010). Accordingly, MPI scholars noted that poverty measurement should be a composite of various consumption deprivations that include

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education impoverishment, health impoverishment, and impoverishment related to standard of living. Specifically, education impoverishment constitutes both average years of schooling and percent child enrollment. Health impoverishment considers mortality rates and nutrition quality. Living standard impoverishment includes restricted access to clean drinking water and sanitation, consumption of electricity and cooking fuel, and household assets. Estimates were created for each dimension within the three broad categories and compiled to determine national MPI scores. Prior to analysis, we computed correlations for the three dimensions corresponding to countries in our sample. Each exceeded .80 and, thus, we determined that evaluating poverty with a single MPI measure was more parsimonious than looking individually at the dimensions.

Subjective well-being. Our analysis examined how consumption deprivation defined as impoverishment impacts subjective well-being at the individual level. Our dependent measures of well-being included respondents’ assessments of their happiness (affective well-being) as well as their overall evaluations of life satisfaction (cognitive well-being). These items are provided in the WVS and are commonly accepted variables for such research (Bruni and Porta 2005; Diener et al. 2003; Dolan et al. 2008). Consistent with past investigations and the psychometric properties of these two components (Lucas et al. 1996), our sample produced a correlation of .42 between affective and cognitive dimensions of well-being, validating their distinctiveness. As shown in appendix A, respondents were asked to state their subjective level of happiness on a four-point scale, and their life satisfaction on a 10-point scale ranging from completely dissatisfied to completely satisfied. Because of the differences in metrics between these and other items, all measures were standardized.

Self-determination theory variables. As noted, we drew from seminal works developing self-determination theory (Deci and Ryan 2002; Ryan and Deci 2000) to extract measures for the psychological needs variables from the WVS. Specifically, autonomy was assessed through an item asking individuals the degree of freedom of choice and control they have over their lives. We utilized items regarding importance of family and friends to capture relatedness. As mentioned, the WVS lacked sufficient items corresponding to the third component of SDT or competence. Again, this represents a limitation of the data instrument and presents an important area for future research. As with all study variables, the SDT items are featured in appendix A.

Individual-level control variables. Because we are interested in forces at the society level that influence individual, subjective well-being, we controlled for a number of individual-level factors, which is common practice in cross-national well-being research (Schimmack et al. 2007). Although literature suggests that personal income and social class self-assignments are important in such evaluations (Clark et al. 2008; Coleman 1983; Henry 2005; Schaninger 1981), we are only interested in individuals’ psychological needs fulfillment from self-determination theory and how broader environmental characteristics manifest consumption impoverishment. Thus, we controlled for individual income and social class to isolate their effects. Income is a continuous variable that is broken into deciles relevant to local economies. Also included is a measure of social class, which provides a scale of relevant labels with which individuals identify (e.g., middle class, working class, lower class). Findings also controlled for respondents’ age (Easterlin 2006) and gender (Alesina, Di Tella, and MacCulloch 2004). These variables also were obtained from the WVS.

Of note, control variables featured in our analyses have been tested in various functional forms in past research. For example, income and social class have been tested as nonlinear and quadratic functions, and as both continuous and categorical variables (Howell and Howell 2008). So too, age has been tested as a nonlinear function, with similarities reported between consumers at different age extremes (Blanchflower and Oswald 2004; Ferrer-i-Carbonell and Gowdy 2007). To be thorough, the analyses that follow were computed using all possible functional forms of control

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variables as suggested in the literature. Importantly, none of our findings, in terms of the direction, significance, or strength, varied with different control variable forms. Accordingly, we report the least complex analyses that feature control variables as they appear on the WVS.

Analysis

Hierarchical linear modeling. We concentrated on the relationships between well-being at the individual level and impoverishment as manifested at the society level. Thus, our analysis mandated a multilevel modeling technique where variance could be partitioned between individual-level and country-level variables (Hofmann 1997). Hierarchical linear modeling (HLM) with restricted maximum likelihood estimation using HLM 6.08 was employed (Raudenbush and Bryk 2001), which provides a platform for investigating relationships between variables at different levels of analysis. Specifically, HLM models individual- and group-level residuals, recognizing the partial interdependence of individuals within the same group or, in our case, the same country. Thus, this approach allowed us to investigate individual- and country-level unit variance in the well-being outcome measures.

To accomplish this task, HLM simultaneously estimates two models: the first modeling relationships within each individual-level unit, and the second modeling how these relationships within units vary between countries (Hofmann 1997). We depict equations for models employed to test study hypotheses in appendix B. In two-level hierarchical models such as those employed in this study, level 2 analyses use intercepts from level 1 analyses as dependent variables. In relation to our hypotheses, model 1 looks at the impact of poverty (MPI) on happiness or affective well-being; model 2 examines the impact of MPI on life satisfaction or cognitive well-being. Finally, in model 3 we test the impact of poverty on well-being as moderated by the SDT psychological need variables of autonomy and relatedness. These cross-level interactions were created using product terms that attached society-level MPI data to each individual case corresponding to SDT variables. We tested each model with a random coefficients approach (Boyce 2010). In addition to equations, technical details for the HLM procedure and analyses are found in appendix B.

Measurement invariance. Before making comparative assessments regarding theoretically relevant groups (individuals in higher versus lower poverty societies), it is important to ascertain that any differences between the groups are not due to discrepancies in the interpretation of the measurement instrument. We performed a multiple group confirmatory factor analysis on the individual-level items to assess invariance, gradually increasing constraints and comparing each model to an unconstrained model (Steenkamp and Baumgartner 1998). The overall χ² for the multiple group model with structural covariances constrained was 251533, d.f. = 13, whereas the χ² for the unconstrained model was 251453, d.f. = 10. The difference in χ² statistics was 80, with d.f. = 3 (p > .10), evidencing partial measurement invariance, which is both a necessary and sufficient condition for making structural comparisons across groups (Steenkamp and Baumgartner 1998).

RESULTS

Descriptive statistics are provided in table 1. Since variables of interest were measured at

different levels of analysis (individual- and society-level), we attached the country-level items to each individual case to obtain correlations. We then counterweighted by country sample size so that nations with larger sample sizes would not be overrepresented. This approach to correlations with multilevel data is common in cross-national research (Martin et al. 2007); however, it is subject to a disaggregation bias as described by Hofmann (1997). Thus, although correlations provide insight

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into the nature of variable relationships, the HLM models that follow provide a more conservative test and truer picture. We present the HLM results below, interpreting the findings in greater detail in the discussion and conclusions section.

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We analyzed the impact of societal impoverishment on both of the aspects of individual subjective well-being, including affective and cognitive components, using the two hierarchical linear models featured in table 2. As seen, societal impoverishment had no significant influence on individual happiness or reports of affective well-being. Thus, hypothesis 1 is not supported. Cognitive well-being, or individuals’ reported satisfaction with their lives, however, is strongly and negatively related to societal impoverishment (γ = -1.13, p < .001), supporting hypothesis 2. In these models, we controlled for individual income, social class, age, and gender to isolate the poverty effects. Each, except for gender, was significantly related to well-being. As described above, the effects of poverty on well-being in the two models remained unchanged in terms of direction, strength, and significance when examining control variables in different functional forms consistent with past research. To understand the variance explained by the models, we computed R² coefficients for each level of analysis according to prescriptions suggested by Raudenbush and Bryk (2001). More specifically, for model 2, which supported our theoretical predictions, individual-level controls explain 37% of the variance in life satisfaction, while poverty explains 28%. We also computed total variance for the model, which combines both levels of analyses. This more conservative prescription best represents model effect sizes, according to HLM methodologists (Roberts et al. 2010). Using their recommended total variance computations, we find that model 2 explains about 23% of the overall variance in cognitive well-being.


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The next phase of our study involved testing the role of individual psychological need fulfillment advanced in self-determination theory, as it relates to individual subjective well-being and societal impoverishment. Given impoverishment had no significant influence on affective well-being, we limited this portion of the investigation to the cognitive well-being outcome of life satisfaction. Results for this model, corresponding to model 3, are featured in table 3. Here we are interested in the role of individual, psychological needs as moderators of the societal poverty-cognitive well-being relationship. We find support for SDT cross-level interactions hypothesized. Results show individual autonomy significantly moderates the relationship between societal impoverishment and individual life satisfaction (γ = -.20, p < .05). Looking at the two competing hypotheses proposed, results reflect the more nuanced consumption adequacy (H3b) explanation rather than the traditional take on self-determination theory. As predicted in competing hypotheses discussion, high individual autonomy significantly improves life satisfaction for those consumers in less impoverished nations possessing consumption adequacy. As described, these individuals most likely possess some basic minimum consumption options. Thus, in these cases, greater autonomy promotes greater life satisfaction. For individuals in societies lacking even basic consumption necessities, enhanced psychological needs in the form of greater autonomy had a negligible effect on their life satisfaction.

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Similarly, results confirm the competing perspective of individual relatedness as moderating societal poverty and individual well-being, with a strong and significant negative effect (γ = -.03, p < .01). As noted in our contrasting hypotheses discussion that led to H4b, relatedness has a strong and significant influence improving life satisfaction for those in lower poverty societies. Again, this result more closely evidences the argument for the existence of consumption adequacy in that consumers whose needs meet a basic standard benefit from greater relatedness to important others as assessed through their reports of life satisfaction. Individuals in high poverty societies absent even basic minimum consumption of necessities (lack of consumption adequacy) experience little benefit from their relatedness to others on individual well-being.


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As with the two main effects models, we were interested in understanding the variance explained by this model. Unlike analyses for models 1 and 2 that posited distinct relationships at levels 1 and 2, the model featured in table 3 tested hypotheses 3(a,b) and 4(a,b) using cross-level interactions. Accordingly, computing the explained variance separately at the individual and societal levels did not make sense. Thus, we computed total variance/effect size calculations prescribed by Roberts and colleagues (2010). Our broader model featured in table 3 predicts about 54% of total variance in cognitive well-being or individual life satisfaction among consumers in our sample, demonstrating the significant improvement over the main effects models in table 2.

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As we transition to the discussion section of the paper, we provide graphical depictions of the significant, cross-level interactions predicted in hypotheses 3b and 4b. Plots are featured in figures 2 and 3, and we interpret relationships below. Graphs were created by standardizing all variables for direct comparability. Median splits allowed for distinctions between low/high autonomy and relatedness, and low/high poverty. Of course, it is noteworthy that the low/high poverty distinction is relative to the sample of countries featured in this study. This is particularly important given our bottom-of-pyramid sample and focus since low poverty among these countries constitutes considerable poverty relative to developed parts of the world. To illustrate, we denote which countries were classified high poverty and those classified low poverty in appendix A.

CONCLUSIONS AND DISCUSSION

Ultimately, the 51-country sample provides a focused look at poverty and well-being at the bottom-of-the-pyramid. Given the difficulties inherent with data collection in these parts of the world, our study offers a rare glimpse into some of the most impoverished societies. This set of nations also provides an apt test of the impoverishment-subjective well-being relationship and promotes the external validity of our findings. The study interweaves limited research on bottom-of-the-pyramid consumers with work by scholars seeking theoretical insights on consumption. Taken collectively, prior studies yield an incomplete profile absent empirical validation within a framework that brings value to potential findings. Consequently, we consider limited access as impoverishment guided by research that looks broadly at meanings across a variety of contexts (Chakravarti 2006). This approach called for additional depth provided by self-determination

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theory. SDT’s foundations are grounded in the premise that significantly fewer options in important life situations lead to a sense of other- versus self-regulation of behaviors, which may manifest as a lack of autonomy and relatedness. Our findings enhance extant evidence that higher levels of these factors improve well-being as life satisfaction, but to a much greater extent for consumers who live in nations that appear to meet the standards for consumption adequacy, allowing for their long-term focus on needs and desires that go beyond mere survival. Consumers’ current states of happiness and life satisfaction have been shown to be strong predictors of future behavior (Clark et al. 2008). In our study, the first analysis phase examined the impact of countrywide impoverishment on happiness and life satisfaction, affective and cognitive components of well-being respectively. Our findings support past evidence that these dimensions are distinct (Lucas et al. 1996), refuting other characterizations that they must go in tandem with one another (Easterlin 2004). This lack of association or separateness between affective and cognitive well-being requires some additional discussion. A possible explanation is that impoverished consumers are able to distinguish among things that yield intrinsic rewards or a feeling of happiness versus extrinsic rewards or a satisfactory life station. This justification is consistent with consumer research demonstrating that a perceptual shift may occur after the loss of material possessions and a refocused attention on survival, which enhances the importance of things with much deeper meanings but also leads to self-preservation tactics (Hill and Stamey 1990; Hill 1991). Thus, impoverished consumers are capable of distinguishing between what has real value in material landscapes that continue to fail them, yet their broader and enduring perceptions of life satisfaction are reflective of the material conditions around them. The second set of results involves the moderating influence of individual psychological needs delineated by self-determination theory. As table 3 indicates, autonomy and relatedness may positively impact life satisfaction. Given the impressive stream of past work (Ryan and Deci 2006), we did not hypothesize any main effects relationships with SDT variables and well-being. Yet, results do confirm nations that provide basic life necessities are an appropriate context for improved subjective well-being for those consumers fortunate enough to have control over the significant aspects of their living environments and experience positive relationships with important others. However, our primary interest was in how psychological need fulfillment positively impacts the societal poverty-well-being relationship. The resulting significant interactions bring to light some predicted moderating effects, showing that greater autonomy and relatedness mitigate some of the negative influence of impoverishment on life satisfaction under conditions of consumption adequacy. These results reveal the true value to consumers who live in less restrictive material environments of positive psychological feelings. On the other hand, results show that individuals living in extreme poverty are less likely to experience ameliorating effects, revealing the added damage to the lives of consumers who experience the worst possible material conditions. Post-Hoc Analyses: Societal- and Individual-Level Poverty

As shown, results support our competing perspectives regarding SDT and poverty. The positive effects of the psychological needs of autonomy and relatedness were limited to individuals in societies possessing a basic level of consumption adequacy. In those societies, autonomy and relatedness improved assessments of life satisfaction. Although beyond the scope of our theoretical framework, we wondered whether simple individual wealth could offset the damaging effects of societal poverty on life satisfaction. Accordingly, we conducted post-hoc analyses that considered if individual wealth, conceptualized through income and social class, might ameliorate these negative effects. The results of this analysis are featured in table 4. Consistent with the analyses employed

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for hypotheses testing, we created cross-level product terms for income and social class with society-level poverty. All other analytical properties were identical to previous reports.

As shown, we find support only for the moderating role of social class on societal poverty-life satisfaction relationships (γ = -.17, p < .01). Interestingly, improvements in social class work to offset the negative effects of societal poverty more dramatically for individuals in the high poverty societies, however, this effect is far less pronounced for individuals in low poverty societies. This result is counter to moderating effects uncovered for psychological need fulfillment conceptualized in SDT. Further, this relationship shows that when individuals’ standing in society relative to their peers improves, self-reported life satisfaction also improves for those in high poverty societies. As with SDT interactions, we use median splits to plot this relationship in figure 4. Again, the figure illustrates life satisfaction levels using demarcations of low/high poverty societies with individuals classified as low/high in social class. This interesting contrast warrants future research exploration.

---------------------------------------------------------------- Insert table 4 and figure 4 about here

---------------------------------------------------------------- Theoretical Implications In a recent article in this journal, Markus and Schwartz (2010, 345) examine the impact of choice behavior and concede that “the relationship between choice, freedom, autonomy, and well-being is complex.” Implicitly, their discussion acknowledges the Easterlin Paradox, which reveals that increasing access to the material world advances happiness up to a particular point and levels off or even declines beyond that point (Easterlin 2004). They posit a possible reason described as “choice overload” (Schwartz 2004), leading them to ponder, as Easterlin did but with regard to income, where the proverbial tipping point occurs. This perspective runs counter to many studies supporting self-determination theory and their results, which show that greater access improves the experience of choice as long as the decision context remains important (Moller et al. 2006). As such we ask, how can divergent beliefs be reconciled given our model based on bottom-of-the-pyramid consumers and findings that yield support for SDT? Our contention is that, if such a curvilinear relationship does exist between income and happiness or consumption options and well-being, the point at which it is relevant is so far beyond lived experiences of the poor that it is inconsequential to our thinking. Thus, the possibility exists that individuals may face negative psychological reactions which come from having too much. Yet we agree with Markus and Schwartz (2010) that the theoretical basis for these conclusions focuses on elite citizens of the world who represent most study participants but whose lives have little in common with the more impoverished global population facing too little. Thus, the more important tipping point is the level of basic goods and services necessary before autonomy and relatedness are able to impact consumer well-being as life satisfaction. For this poverty subset, positive reactions and conclusions are due, in part, to the perception of self- versus other control. Our work begins addressing these issues, and our hope is that other consumer behavior scholars will follow suit. Germane to our original premise is that the consumer behavior literature has not fully informed those interested in understanding and helping impoverished peoples around the world, which begs the larger question: How well does collective research speak to ways in which the entire earth’s population experiences the material landscape? Clearly, most studies examine consumers who occupy the highest rung on the socioeconomic ladder, which contains about 15% of humankind as denoted in figure 1. The more typical sampling of one of four human development profiles suggests that many findings may not be representative of any group other than elite,

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western consumers. If the distinction is context rather than process, results may hold true across strata, and we can take the same theoretical frames and apply them to conditions of greater poverty. However, if impoverished consumers face more than simply different circumstances but actually respond to them in unique ways, applying similar theories without any additional considerations will likely prove inaccurate. This research does not provide a complete answer, but it does inform the issue. Our earlier comments about choice suggest that it is a defining value of exchange relationships, yet the field only has a lengthy history of recognizing the downside of too much, emphasizing concepts such as information overload (Jacoby 1977). Consequently, it has fostered much less scholarship that looks at the other side, described here as impoverished consumption (Hill 2001). Can both be right? In an attempt to reconcile such differences, we return to Marcus and Schwartz (2010) and Ryan and Deci (2000). It is possible that consumers who have the affluence necessary to engage abundant markets may be overwhelmed by choices among nearly identical products that proliferate on characteristics and associated benefits that hold little consequence. Yet their poor counterparts, who may be aware of but lack access to this material abundance, experience far fewer options not as a source of relief but as unwanted and, sometimes, externally-controlled interference with their consumption that leads to lower life satisfaction. Such extremes may each produce decreases in the psychological variables that lead to well-being but for different reasons. Other domains in consumer behavior may reveal further opportunities for similar reflection. Future Research Opportunities

Our hope is that consumer behavior scholars will take this opportunity to expand their focus beyond top-of-the-pyramid consumers to include many different dimensions of global citizenship that recognize the types and extent of constraints which inhibit consumption across various needs and desires. One such factor that is unexplored in most of our work is location. Although research on European, Asian, and Indian consumers continues to surface in the literature, these studies have, for the most part, considered individuals with the same socioeconomic profile as affluent and elite consumers. Collectively, what would consumer research reveal if it was broadened to include areas like South Asia, Sub-Saharan Africa, and impoverished sections of the Caribbean? Simple taken-for-granted tasks of accessing clean water, eating healthful meals daily, and receiving preventative health services take on new meanings ripe for examination and discussion. Further, scholars could employ ethnographic methods that were used in earlier consumer studies of the poor that clarified lived experiences and differences in perceptions as viewed through their lenses of impoverished consumption (Hill 1991; Hill and Stamey 1990).

Another area for additional research involves the conceptualization and measurement of important constructs. In our study, we were limited to items in the secondary database as proxies for the self-determination variables rather than more complete sets of scales developed by the theory founders (Deci and Ryan 2002). While we are confident in their validity, it remains possible that there are dimensions to autonomy and relatedness that could be captured by such well-designed and proven instruments, allowing for more nuanced interpretations of our subsequent findings. Further, lack of relevant metrics for the competency variable in the WVS dataset poses other opportunities if this factor can be tied theoretically to consumer behavior. Of course, the natural tradeoffs between large-scale secondary data collections with multiple purposes but significantly wider reach must be juxtaposed against smaller studies with a more focused approach. It may serve scholars by using both methods to inform important consumer behavior questions since their relative strengths and weaknesses often counterbalance each other.

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A final issue includes the need to consider how impoverished consumers in developed economies fare based on various levels of perceived autonomy and relatedness. Our discovery of the tipping point beyond which consumers are able to actualize higher-order needs and reap their benefits under conditions of greater autonomy and relatedness is an important finding, and it begs the question of whether or not additional such plateaus may be uncovered when examining affluent nations that occupy the top two rungs shown in figure 1. Under these circumstances, the variable individual poverty should be included so that the different levels of access across higher levels of countrywide affluence than in this study can be used to determine potential moderating effects of autonomy and relatedness on various combinations of poverty and well-being. This research may best be conducted by looking into possible effects for both happiness and life satisfaction, with consideration given to relative versus absolute poverty and importance of social comparisons.

CONCLUDING REMARKS

The field has recently seen a resurgence of interest in well-being of humankind as part of the transformative consumer research (TCR) movement. This small but growing community of scholars has demonstrated much energy for publication, spawning special issues of two journals including Journal of Consumer Research, an edited volume from the leaders of this movement, and three conferences with attendees from around the globe. Their interests cover a variety of topics such as materialism, obesity, health care, poverty, social welfare, and the viability of subsistence markets (Mick et al. 2012). This research is consonant with broader interests and speaks directly to constructs associated with quality of life of impoverished citizens worldwide. The movement suggests that fruits of consumer researchers’ labors must do more than increase enthusiasm for application of theory to intractable problems, and it should also demand interactions with politicians and other policy makers, executives in for-profit and nonprofit firms, and members of advocacy groups that can impact people’s lives. Hopefully, this investigation will be a catalyst for such conversations that reveal the true value of consumer research to the larger society.

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APPENDIX A

Study Measures*

Individual-Level Variables World Values Study Group, World Values Survey, 5 Wave Aggregate, 1981-2008, Inter-University Consortium for Political and Social Research.

Subjective Well-Being Happiness: “Taking all things together, would you say you are: 1 = very happy; 2 = rather

happy; 3 = not very happy; 4 = not at all happy.” (reverse coded) Life Satisfaction: “All things considered, how satisfied are you with your life as a whole these

days?” Where 1 = completely dissatisfied and 10 = completely satisfied. Self-Determination Psychological Needs Autonomy: “Some people feel they have completely free choice and control over their lives,

while other people feel that what they do has no real effect on what happens to them. Please use this scale to indicate how much freedom of choice and control you feel you have over the way your life turns out.” Where 1 = none at all and 10 = a great deal.

Relatedness: “For each of the following, indicate how important it is in your life.” 1) Family; 2) Friends, Where 1 = very important and 4 = not at all important. (reverse coded)

Individual Controls Income: Grouped by decile; unique to each country, where 1 = lowest decile; 10 = highest

decile. Social Class: “People sometimes describe themselves as belonging to the working class, the

middle class, or the upper or lower class. Would you describe yourself as belonging to the…” (where 1 = upper class; 2 = upper middle class; 3 = lower middle class; 4 = working class; 5 = lower class; reverse coded)

Age: “Can you tell me your year of birth, please? This means you are _______ years old.” Gender: male = 1; female = 0; Completed by interviewer.

Society-Level Consumption Impoverishment

Multidimensional Poverty Index (MPI): Alkire and Santos (2010), Multidimensional Poverty Index: 2010 Data. Oxford Poverty and Human Development Initiative.

MPI Scores by median split; Used for figures 2-4 distinctions listed below; High Poverty Countries: Bangladesh, Brazil, Burkina Faso, China, Colombia, Dominican

Republic, Egypt, Estonia, Ethiopia, Ghana, Guatemala, India, Indonesia, Iraq, Mali, Morocco, Nigeria, Pakistan, Peru, Philippines, Rwanda, Tanzania, Turkey, Vietnam, Zambia, and Zimbabwe.

Low Poverty Countries: Albania, Argentina, Armenia, Azerbaijan, Belarus, Bosnia/Herzegovina, Croatia, Czech Republic, Georgia, Hungary, Jordan, Kyrgyzstan, Latvia, Macedonia, Mexico, Moldova, Russia, Serbia, Slovakia, Slovenia, South Africa, Thailand, Trinidad and Tobago, Ukraine, Uruguay.

* All items standardized prior to analysis to account for different metrics.

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APPENDIX B

HLM simultaneously estimates two models: the first modeling relationships within each of the individual-level units, and the second modeling how those relationships within units vary between countries (Hofmann 1997). The equations for models employed to test the hypotheses are presented below. Three separate models are required owing to two well-being dependent variables and subsequent testing of interaction effects.

Model 1: Affective Well-Being (H1)

Level 1 (Individual level)

HAPPYij = β0j + β1jINCij + β2jSOCICLSij + β3jAGEij + β4jGENDij + rij

Level 2 (Country level)

β0j = γ00 + γ01MPIj + U0j

β1j = γ10 + U1j

β2j = γ20 + U2j

β3j = γ30 + U3j

β4j = γ40 + U4j

Model 2: Cognitive Well-Being (H2)


LIFESATISij = β0j + β1jINCij + β2jSOCICLSij + β3jAGEij + β4jGENDij + rij


β0j = γ00 + γ01MPIj + U0j

β1j = γ10 + U1j

β2j = γ20 + U2j

β3j = γ30 + U3j

β4j = γ40 + U4j

Model 3: SDT Cross-Level Interactions (H3a,b, H4a,b)


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WELLBGij = β0j + β1jINCij + β2jSOCICLSij + β3jAGEij + β4jGENDij + β5jAUTONij +

β6jRELATij + rij


β0j = γ00 + γ01MPIj + γ02MPIxAUTONj + γ03MPIxRELATj + U0j

β1j = γ10 + U1j

β2j = γ20 + U2j

β3j = γ30 + U3j

β4j = γ40 + U4j

β5j = γ50 + U5j

β6j = γ60 + U6j

where WELLBG represents the outcome measure, individual well-being, for individual i in country j. HAPPY: happiness or the affective component of well-being; LIFESATIS: life satisfaction or the cognitive component of well-being. β0j is the intercept, and β1j through β7j are slopes estimated separately for each country, signified by the subscript j. Individual-level controls are represented as INC: individual income category reported; SOCICLS: individual social class; AGE: individual’s age in years; GEND: gender, which is a dummy coded variable. In model 3, SDT variables are introduced where AUTON signifies autonomy; and RELAT signifies relatedness. Finally, for the level 1 equations, rij is the residual, which is normally distributed with a zero mean and variance σ2. In our model, level 2 analyses use the intercept from the level 1 analysis as a dependent variable. In these equations, γ00 through γ60 represent the second stage intercept terms, and γ01 through γ07 are the slopes relating the country-level variables in each of the three models to the intercept terms from the level 1 equation. Finally, U0j through U6j are the level 2 residuals, which are multivariate and normally distributed, with an expected value of zero and variance τ00 (Bryk and Raudenbush, 1992). In each model for β1j – β6j in the level 2 equations, we do not include the country-level variables (MPI or the SDT interactions with MPI) since we do not hypothesize country-level effects on the individual-level slopes (i.e., slopes-as-outcomes models for the SDT variables or the individual controls, investigating intercepts-as-outcomes for each of the three models. Specifically, at the country-level of analysis and in relation to our hypotheses, model 1 looks at the role of poverty (MPI) on happiness or affective well-being; model 2 examines the MPI on life satisfaction or cognitive well-being. Finally, in model 3 we test the role of poverty and its cross-level moderation with the SDT variables.

We test each model using a random coefficients approach advocated by methodologists working with well-being variables in large samples (Boyce 2010). To clarify, as shown in the equations above, each level 1 intercept has two estimates. The first comes from the regression equation estimated for the individual at level 1 in each model. The second estimate comes from the level 2 regression model (β0j from the level 2 equations). Put simply, for any unit two predicted intercept and slope values are estimated: one from the level-1 regression equation and one from the

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level-2 regression model. As described by Hofmann (1997), instead of forcing a choice between the estimates, HLM computes an optimally weighted combination using an empirical Bayesian estimate approach. The Bayes estimates are a weighted composite of the two estimates based on reliability of the regression estimates (where reliability = true variance/total parameter variance; variance in β0j = true variance in β0j + error variance in β0j).

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TABLE 1

Descriptive Statistics: Correlations, Mean, and Standard Deviationsa,b,c

Study Variables Mean s.d. 1 2 3 4 5 6 7 8

1. Affective Well-being 2.95 0.84 1.00 2. Cognitive Well-being 5.93 2.64 .42 1.00 3. Impoverishment 0.11 0.16 .07 -.10 1.00 4. Autonomy 6.28 2.84 .21 .38 -.09 1.00 5. Relatedness 3.58 0.48 .13 .09 .02 .06 1.00 6. Income 3.92 2.50 .10 .15 .02 .11 .04 1.00 7. Social Class 2.44 1.17 .17 .20 -.10 .11 .07 .28 1.00 8. Age 38.83 15.32 -.10 -.06 -.17 -.05 -.06 -.06 -.07 1.00 9. Gender 0.48 0.50 .01 -.01 .04 .06 .01 .04 .02 .01

aN = 77,646, level 1; n = 51, level 2. Level 2 countries include Albania, Argentina, Armenia, Azerbaijan, Bangladesh, Belarus, Bosnia/Herzegovina, Brazil, Burkina Faso, China, Colombia, Croatia, Czech Republic, Dominican Republic, Egypt, Estonia, Ethiopia, Georgia, Ghana, Guatemala, Hungary, India, Indonesia, Iraq, Jordan, Kyrgyzstan, Latvia, Macedonia, Mali, Mexico, Moldova, Morocco, Nigeria, Pakistan, Peru, Philippines, Russia, Rwanda, Serbia, Slovakia, Slovenia, South Africa, Tanzania, Thailand, Trinidad and Tobago, Turkey, Ukraine, Uruguay, Vietnam, Zambia, and Zimbabwe. bIncome and social class are categorical variables; gender (male = 1) is dummy coded. cCorrelations computed by attaching country level variables to each individual level variable and counterweighting by country sample size to adjust for countries with greater representation. Correlations .01 or greater are significant at p < .05; correlations .02 or greater are significant at p < .01.

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TABLE 2

Impoverishment and Individual Subjective Well-Being: Main Effectsa

Affective Well-Being (Happiness)

Cognitive Well-Being (Life Satisfaction)

γ s.e. t-value γ s.e. t-value Societal-Level Variable Impoverishment H1 (-) -.17 .29 -0.61 H2 (-) -1.13 .25 -4.53 *** Individual-Level Controls Income .11 .01 10.03 *** .17 .02 9.08 *** Social Class .13 .01 11.09 *** .14 .01 10.58 *** Age -.00 .00 -8.02 *** -.00 .00 -5.44 *** Gender -.00 .01 -0.39 -.01 .01 -1.30

Individual-Level R2 = .23 .37 Society-Level R2 = .20 .28

Overall Model R2 = .18 .23

(*p < .05; **p < .01; ***p < .001) aHierarchical Linear Model: (Individual) Level 1 = 77,646; (Societal) Level 2 = 51;

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TABLE 3

The Role of Impoverishment and SDT Interactions on Cognitive Well-Beinga

Dependent Variable: Cognitive Well-Being (Life Satisfaction)

Main Effects Model

Cross-Level Interactions

γ

s.e.

t-value

γ

s.e.

t-value

Societal-Level Impoverishment -.70 .25 -2.84 ** -.80 .25 -3.16 ** SDT: Individual Psychological Needs Autonomy .27 .02 16.72 *** .29 .02 16.10 *** Relatedness .03 .00 9.94 *** .04 .00 9.27 *** SDT: Cross-Level Interactions Impoverishment x Autonomy (H3a,b) -.20 .10 -1.96 * Impoverishment x Relatedness (H4a,b) -.03 .01 -2.44 ** Individual-Level Controls Income .14 .02 7.89 *** .14 .02 7.93 *** Social Class .10 .01 10.28 *** .10 .01 10.27 *** Age -.00 .00 -4.81 *** -.00 .00 -4.79 *** Gender -.04 .01 -3.53 ** -.04 .01 -3.51 **

Overall Model R²: .54


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TABLE 4

Post-Hoc Analyses: Societal- and Individual-Level Poverty Interactionsa

Dependent Variable: Cognitive Well-Being (Life Satisfaction)

γ

s.e.

t-value

Societal-Level Impoverishment -.77 .25 -3.06 ** Individual-Level Income .16 .02 6.53 *** Social Class .15 .02 9.34 *** Cross-Level Interactions Impoverishment x Income .12 .09 1.34 Impoverishment x Social Class -.17 .06 -3.06 ** Individual-Level Controls Age -.00 .00 -5.42 *** Gender -.01 .01 -1.30

Overall Model R²: .42


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FIGURE 1

Human Development and Consumption Pyramid

HDI Rank 2007 Population (Millions) % Total Population Very High 986.5 14.79%

High 918.4 13.77% Medium 4380.5 65.67%

Low 385.1 5.77% Total 6670.5

Low Human Development Countries (5.77% of total world population)

Medium Human Development Countries (65.67% of total world population)

Very High Human Development Countries (14.79% of total world population)

High Human Development Countries (13.77% of total world population)

Marketplace Abundance

Bargaining Power

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FIGURE 2

Life Satisfaction and Impoverishment by Autonomy

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FIGURE 3

Life Satisfaction and Impoverishment by Relatedness

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FIGURE 4

Life Satisfaction and Impoverishment by Social Class

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