nep-hap New Economics Papers
on Economics of Happiness
Issue of 2016‒09‒04
five papers chosen by
Viviana Di Giovinazzo
Università degli Studi di Milano-Bicocca

  1. Income Inequality and Well-Being in the U.S.: Evidence of Geographic-Scale- and Measure-Dependence By Ifcher, John; Zarghamee, Homa; Graham, Carol Lee
  2. Well-Being, Poverty and Labor Income Taxation: Theory and Application to Europe and the U.S. By Maniquet, François; Neumann, Dirk
  3. The impact of terrorism on expectations, trust and happiness. The Case of the November 13 attacks in Paris, France By Tom Coupe
  4. Findings on Relative Deprivation from the Survey of Household Economics and Decisionmaking By Samuel Dodini
  5. Social Capital, Trust and Well-being in the Evaluation of Wealth By Kirk Hamilton; John F. Helliwell; Michael Woolcock

  1. By: Ifcher, John (Santa Clara University); Zarghamee, Homa (Barnard College); Graham, Carol Lee (Brookings Institution)
    Abstract: U.S. income inequality has risen dramatically in recent decades. Researchers consistently find that greater income inequality measured at the state or national level is associated with diminished subjective well-being (SWB) in the U.S. We conduct the first multi-scale analysis (i.e., at the ZIP-code, MSA, and state levels) of the inequality-SWB relationship using SWB data from the U.S. Gallup Healthways Well-Being Index and income inequality data from the American Community Survey. We use the rich set of well-being measures afforded by the dataset (evaluative, positive- and negative-affective hedonic, and health measures) to examine the consistency of the relationship. We find that the relationship is both scale-dependent and measure-dependent: income inequality is SWB-diminishing in large regions for all measures, SWB-diminishing in small regions for negative-affective hedonic measures, and SWB-improving in small regions for most other measures. Lastly, we find that taking all regions together, the net relationship between income inequality and SWB is negative.
    Keywords: subjective well-being, income inequality, happiness, distribution of income, health, scale-dependence, measure-dependence
    JEL: D3 I14 D6
    Date: 2016–08
  2. By: Maniquet, François (CORE, Université catholique de Louvain); Neumann, Dirk (Université catholique de Louvain)
    Abstract: In a model in which agents differ in wages and preferences over labor time-consumption bundles, we study labor income tax schemes that alleviate poverty. To avoid conflict with individual well-being, we require redistribution to take place between agents on both sides of the poverty line provided they have the same labor time. This requirement is combined with efficiency and robustness properties. Maximizing the resulting social preferences under incentive compatibility constraints yields the following evaluation criterion: tax schemes should minimize the labor time required to reach the poverty line. We apply this criterion to European countries and the US.
    Keywords: well-being, poverty, labor income taxation
    JEL: D63 H21 I32
    Date: 2016–08
  3. By: Tom Coupe (Kyiv School of Economics)
    Abstract: We use quasi-experimental evidence to measure the impact of the November 13, 2015 attacks in Paris, France on various channels through which terrorism can affect the economy. The evidence suggest the attacks reduced optimism and increased trust in the national government but did not affect current life satisfaction nor political orientation.
    Keywords: terrorism, trust, happiness, expectations
    JEL: I31 F52 Z13
    Date: 2016–08
  4. By: Samuel Dodini
    Abstract: FEDS Notes Print{{p}}June 29, 2016{{p}}Findings on Relative Deprivation from the Survey of Household Economics and{{p}}Decisionmaking{{p}}Sam Dodini{{p}}The Federal Reserve's Survey of Household Economics and Decisionmaking (SHED) contains questions designed to ascertain overall{{p}}economic well-being and fragility, which can be used to gauge both the perceptions individuals have about their own economic status and{{p}}an approximation of their actual financial health.1 The SHED contains valuable information that can be used to explore how the well-being{{p}}of others in their community may impact an individual's assessment of their own well-being and their choices.{{p}}Typical measures of financial well-being often focus on income distributional statistics such as one's income or wealth level. Under the{{p}}standard consumer utility framework, income is important for well-being by determining the budget constraint and impacting the level of{{p}}consumption that one can afford. Since well-being is based solely on one's own income and consumption, well-being will have no direct{{p}}relation to the income or consumption of others.{{p}}However, under theories first developed by Duesenberry (1949), individual utility may not depend on consumption subject to absolute{{p}}income constraints and prices, but also upon relative income. As one's relative income falls, their level of relative deprivation increases, as{{p}}does their disutility, even if their own income or consumption remains unchanged.{{p}}Under this theory of relative deprivation, not only do quantities consumed matter to utility, but in order to combat the disutility of lower{{p}}relative income, individuals reallocate their income toward consumption goods designed to keep up with their higher-income peers.{{p}}Spending is particularly focused on "positional goods"--a term first coined by Hirsch (1977) to mean goods that represent more expensive{{p}}outward signals of success and whose utility comes from exclusivity. Examples include expensive cars, the newest electronic gadgets, or{{p}}fashionable clothing. The prediction of relative deprivation theory is that lower relative income households attempt to maintain a higher{{p}}quality lifestyle in order to keep up with higher relative income households in a kind of expenditure arms race (the proverbial "Keeping up{{p}}with the Joneses"), as discussed extensively by Frank (2007). Based on relative deprivation theory, increases (decreases) in inequality{{p}}can reduce (increase) individual well-being beyond that which would be expected from changes in any individual's own income.{{p}}While relative deprivation is one way in which inequality levels can impact individual well-being, it is not the only avenue by which an{{p}}impact may occur. To the extent that inequality increases the cost of living due to competition for scarce resources--which often occur{{p}}simultaneously with the economic growth of cities and gentrification--the higher prices will reduce the consumption possibility frontier for{{p}}an individual with a given level of income2. As an example, Glaeser, et al (2012), relate their findings that city centers with more poverty,{{p}}coupled with higher-income periphery areas, saw the greatest house price growth from 1996-2006 as the central cities revitalized (and{{p}}local inequality increased), which may have negatively affected the well-being of those lower-income residence who occupied those city{{p}}centers.{{p}}In this case, the relationship between consumption and well-being from classical economic theory will adequately predict lower well-being{{p}}for those in high-cost areas due to price effects without relying on this relative deprivation explanation. Local prices are key to{{p}}understanding the amount of weight to place upon relative deprivation theory vis-à-vis price theory.{{p}}For this analysis, I focus on two main questions in the SHED related to this theory of relative deprivation. Respondents are asked how{{p}}they perceive themselves to be faring financially, ranging from "Finding it difficult to get by" to "Living comfortably" and also about their{{p}}expenses relative to their income as a measure of savings. If relative deprivation leads to overspending or viewing one's household as{{p}}financially worse off than others, we would expect those with lower relative incomes to report lower levels of financial health and savings.{{p}}In making comparisons that may affect one's perceptions of relative economic standing, individuals depend heavily upon their social{{p}}interactions and their immediate environment. They draw from their experiences in communities, not across countries. For this reason,{{p}}analyses that attempt to fully explore these issues should examine them at the local rather than national level.{{p}}The restricted use version of the 2014 SHED data contain demographic information measuring age, income, education, household size,{{p}}marital status, and race/ethnicity along with the ZIP code information of each of the approximately 5,800 survey respondents across more{{p}}than 4,600 ZIP codes. Using the ZIP code information of the respondents, we can compare the reported income of the respondent to the{{p}}ZIP code level 5-year estimates of income as measured by the American Community Survey (ACS) in order to measure how one's own{{p}}income compares to the incomes of those above them in the income distribution.{{p}}Measuring Relative Deprivation{{p}}Gini-based indexes of relative deprivation account for the concentration of income as well as the proportion of the income distribution{{p}}above a household of interest (e.g. Yitzhaki, 1979), i.e. the distribution of income. The SHED, however, reports household-level incomes{{p}}and other important facets of well-being. In terms of individual knowledge of their own position in a community, I argue that households{{p}}are unlikely to readily perceive the distribution of income that surrounds them as much as they perceive the difference in the levels of{{p}}income between themselves and those that are relatively well off in the community.3 Thompson (2016) makes a similar argument that Gini{{p}}measurements do not adequately capture changes at the top of the income distribution nor address the true relative income of those at{{p}}the middle and bottom. To measure this perception in the SHED, I construct a metric of each household's income as a percentage of the{{p}}90th percentile income in their ZIP code. The lower the percentage below one, the more relative deprivation applies to the respondent{{p}}and/or their household. I adjust the measure for those whose income is greater than the 90th percentile to 1, as they face no relative{{p}}deprivation in connection to the reference group.4{{p}} FRB: FEDS Notes: Findings on Relative Deprivation from the Survey of Household Econ... Page 1 of 5{{p}} 6/29/2016{{p}}A Snapshot of Current Well-Being{{p}}First, I examine the relationship between both absolute and relative income and self-reported financial well-being in the SHED. Figure 1{{p}}shows the straightforward relationship between stated living conditions and absolute income. The results are exactly what we would{{p}} expect: those in lower income buckets are more likely to respond that they are finding it difficult to get by.{{p}} Source: 2014 Survey of Household Economics and Decisionmaking (SHED){{p}}Accessible version{{p}} Source: 2014 Survey of Household Economics and Decisionmaking (SHED) and American Community Survey (ACS){{p}}Accessible version{{p}}Figure 2 shows a similar relationship between financial well-being and relative income. Among those whose income is less than 25{{p}}percent the 90th percentile value, only eight percent responded that they are "living comfortably" compared to 34 percent of those whose{{p}}income is 75 to 100 percent of the 90th percentile income. In the lowest category, 24 percent of those whose incomes are less than 25{{p}}percent of the 90th percentile say they are "finding it difficult to get by", compared to 4-5 percent of those whose incomes are near or{{p}}above the 90th percentile.{{p}}The similarities between Figures 1 and 2 underscore the need to adequately control for absolute income when examining the effects of{{p}}relative income. I use an ordered probit regression model to isolate these effects. I also include other controls that may influence{{p}}Figure 1: Which of the following best describes how well you are managing financially these days? by absolute{{p}}income, percent{{p}}Figure 2: Which of the following best describes how well you are managing financially these days? by relative{{p}}income, percent{{p}} FRB: FEDS Notes: Findings on Relative Deprivation from the Survey of Household Econ... Page 2 of 5{{p}} 6/29/2016{{p}}household perceptions of well-being and financial behavior. These are personal demographics that reflect life cycle and preferences, i.e.{{p}}ethnicity, age, and education; the household characteristics of household size and marital status; employment status; and the ZIP-level{{p}}considerations of average household size and cost of living measured by median house value. Table 1 shows the incremental results of{{p}}including these controls.{{p}} Note: The regression includes unreported categories for race/ethnicity of Hispanic, Other/Non-Hispanic, 2+ Non-Hispanic and for education groups of high{{p}}school and some college (no degree) and work status of not employed, each of which are not statistically significant. Absolute income is controlled by including{{p}}categorical buckets so as to allow for nonlinear effects of absolute income.{{p}} Source: Author's calculations of SHED data.{{p}}These regressions control for absolute income. However, other characteristics are also important factors in what social comparisons{{p}}people may draw and the financial decisions they may make. The age of the respondents in particular plays an important role because{{p}}individual incomes vary predictably over the life cycle. The education of the respondent is also important because higher levels of{{p}}education are correlated with preferences for patience and financial literacy, which factor into financial well-being. In addition, nominal{{p}}dollars of income do not buy someone the same level of consumption across different locations. For example, housing and other{{p}}expenses are far higher in Manhattan than they are in Ithaca, NY. Someone making $60,000 per year in Manhattan is not necessarily{{p}}better off than someone making $58,000 in Ithaca. In order to effectively compare these individuals to each other and to others within their{{p}}cities, we must control for the cost of living. While a measure of local consumer prices is not directly available, house prices are available,{{p}}which constitute a major contributor to local cost of living calculations.5 Columns 2 and 4 include the log of median house price as a proxy{{p}}for local costs.{{p}}In all specifications, there is no statistically significant relationship between relative deprivation and self-reported financial well-being{{p}}(columns 1-2).6 This may be due to the fact that there are only four response categories that may miss more narrow changes in{{p}}Table 1: Ordered and standard probit regression results controlling for absolute income: effects of relative income{{p}}on self-reported financial well-being and probability of saving{{p}}Overall Financial Well-Being Income Greater than Expenses (Savings){{p}}(1) (2) (3) (4){{p}}Relative Income as % of 90th Percentile 0.0783{{p}}(0.149){{p}}-0.00133{{p}}(0.188){{p}}0.527***{{p}}(0.175){{p}}0.264{{p}}(0.226){{p}}Relative Income as % of 90th Percentile Squared 0.141{{p}}(0.0914){{p}}0.144{{p}}(0.0930){{p}}0.125{{p}}(0.108){{p}}0.151{{p}}(0.108){{p}}Age 30-44 -0.175***{{p}}(0.0578){{p}}-0.291***{{p}}(0.0605){{p}}-0.105{{p}}(0.0735){{p}}-0.161**{{p}}(0.0767){{p}}Age 45-59 -0.0851{{p}}(0.0581){{p}}-0.256***{{p}}(0.0637){{p}}0.0512{{p}}(0.0709){{p}}-0.0612{{p}}(0.0776){{p}}Age 60+ 0.456***{{p}}(0.0569){{p}}0.273***{{p}}(0.0715){{p}}0.173***{{p}}(0.0669){{p}}0.0699{{p}}(0.0829){{p}}Black, Non-Hispanic -0.153**{{p}}(0.0611){{p}}-0.112*{{p}}(0.0631){{p}}-0.167**{{p}}(0.0769){{p}}-0.161**{{p}}(0.0778){{p}}Bachelor's degree or higher 0.345***{{p}}(0.0751){{p}}0.282***{{p}}(0.0765){{p}}0.239***{{p}}(0.0916){{p}}0.150{{p}}(0.0930){{p}}Divorced/Widowed/Separated/Living with Partner -0.265***{{p}}(0.0480){{p}}-0.180***{{p}}(0.0588){{p}}Never Married -0.238***{{p}}(0.0564){{p}}-0.0698{{p}}(0.0700){{p}}Household Size -0.0811***{{p}}(0.0154){{p}}-0.0967***{{p}}(0.0210){{p}}Not Employed -0.0524{{p}}(0.0467){{p}}-0.113**{{p}}(0.0551){{p}}Average Household Size (ZIP) -0.0890*{{p}}(0.0460){{p}}-0.0545{{p}}(0.0603){{p}}Log Median House Value (ZIP) -0.0277{{p}}(0.0420){{p}}-0.107**{{p}}(0.0533){{p}}Observations 5,815 5,801 5,779 5,767{{p}}Personal Controls Yes Yes Yes Yes{{p}}Household, Work Status, ZIP Characteristics No Yes No Yes{{p}}Log Likelihood -6806 -6746 -3711 -3665{{p}}Pseudo R2 0.0903 0.0966 0.0535 0.0635{{p}} FRB: FEDS Notes: Findings on Relative Deprivation from the Survey of Household Econ... Page 3 of 5{{p}} 6/29/2016{{p}}perception or may reflect the idea that these differences may simply not enter their financial "big picture" but may play a role in their day-to-{{p}}day decisions. More concrete measures of financial health would help us understand what other factors may be related. If relative{{p}}deprivation had a negative association with utility or self-perception, we would expect to see a negative relationship. These results are{{p}}inconsistent with the positional goods theory of relative deprivation.{{p}}Concrete Financial Status{{p}}In addition to asking about the way individuals perceive their overall financial well-being, the SHED also asks questions designed to{{p}}understand the financial health of the household in a more concrete way.{{p}}To understand overall and emergency savings, the SHED asks respondents how their spending compares to their income over the{{p}}previous 12 months. Prolonged household budget deficits can lead to the accumulation of debt, increased stress and economic fragility,{{p}}and limit upward mobility. In addition, if prices are driven upward by the spending of high-income households, or if concerns about relative{{p}}position in the community drive households to spend more on positional, nonessential, or other goods, they are less likely to have money{{p}}set aside for emergency expenses. Therefore, the relationship between savings and relative deprivation can inform the overarching{{p}}consumption decisions of these individuals. In a similar vein, using payment to income ratios as a measure of debt and state-level income{{p}}distributions in the Survey of Consumer Finances (SCF), Thompson (2016) finds that as the income of the state's 95th percentile increase{{p}}relative to the rest of the distribution, payment to income ratios for those in the middle of the distribution also increase. These effects are{{p}}not observed in the bottom of the distribution. As with other studies, state-level distributional analyses leave considerable room for{{p}}heterogeneity in cost within states and within metro areas, which this analysis seeks to address.{{p}}Similar to the ordered probit regression discussed above, I also run a probit analysis of the binary outcome of whether or not a{{p}}household's income was greater than their expenses, or in other words, whether or not the household set aside any real savings. Table 1,{{p}}columns 3-4 outline the results of interest for each specification.{{p}}Column 3 indicates that, even after controlling for absolute income, those who are further away from the 90th percentile income are less{{p}}likely than those who are closer to the 90th percentile to report that their income was greater than their expenditures, a relationship similar{{p}}to Thompson's results. This is consistent with the sociological positional goods argument. Taken alone, this would suggest that relative{{p}}deprivation is resulting in an increase in spending relative to income as individuals are attempting to keep up with the "Joneses."{{p}}However, Column 4 shows that this relationship between relative income and spending beyond one's means declines and becomes{{p}}statistically indistinguishable from zero upon inclusion of log median house value in the regression. This indicates that cost of living is{{p}}highly connected to how relative deprivation relates to savings.7 Column 4 results are inconsistent with relative deprivation theory.{{p}}These results cast some doubt on the "Keeping up with the Joneses" and positional goods explanation of consumption. After controlling{{p}}for absolute income, other important demographic covariates, and cost of living, those who face larger amounts of relative deprivation are{{p}}not necessarily less likely to set aside savings over the course of a year. Rather, those with lower relative income appear to have lower{{p}}levels of savings because they live in areas with higher prices and not necessarily because they are spending more in reaction to the{{p}}higher-income "Joneses". Controlling for cost of living in these analyses is key to understanding the possible effects of relative deprivation{{p}}on well-being independent of price effects.{{p}}Conclusion{{p}}Taken together, these analyses suggest that relative deprivation is weakly associated with lower marginal savings, but these influences{{p}}may simply be manifestations of the effects of costs. Relative deprivation does not appear to be a large enough factor to shift individual{{p}}perceptions of their overall financial well-being. Further analyses may utilize more measures of relative deprivation to investigate other{{p}}components of the relationship between well-being and relative deprivation such as the percentage of income saved, their perceptions of{{p}}mobility, and their preferences for work.{{p}}References{{p}}Cruces, Guillermo, Ricardo Perez-Truglia, and Martin Tetaz. 2013. Biased Perceptions of Income Distribution and Preferences for{{p}} Redistribution: Evidence from a Survey Experiment. Journal of Public Economics 98: 100-112.{{p}}Duesenberry, J.S. 1949. Income, Saving and the Theory of Consumer Behavior. Harvard University Press, Cambridge, Mass.{{p}}Frank, Robert H. 2007. Falling Behind: How Rising Inequality Harms the Middle Class. University of California Press.{{p}}Glaeser, Edward L., Joshua Gottlieb, and Kristina Tobio. 2012. Housing Booms and City Centers. American Economic Review: Papers &{{p}}Proceedings 102(3): 127-133.{{p}}Hirsch, Fred. 1977. Social Limits to Growth. Routledge & Kegan Paul Ltd.{{p}}Thompson, Jeffrey. 2016. Do Rising Top Incomes Lead to Increased Borrowing in the Rest of the Distribution? Finance and Economics{{p}}Discussion Series 2016-046. Board of Governors of the Federal Reserve System.{{p}}Yitzhaki, Shlomo. 1979. Relative Deprivation and the Gini Coefficient. The Quarterly Journal of Economics 93(2): 321-324.{{p}}1. For the full report of survey results from each year, the instrument, and technical notes, see Return{{p}}to text{{p}}2. For this reason, national income distributional statistics routinely adjust for cost of living. However, for local analyses, changes in cost of living will still play a{{p}}role to the extent that local cost trends diverge from national averages. Return to text{{p}}3. Research from Argentina suggests that individuals are poor judges of their place in and the shape of the income distribution (Cruces, Perez-Truglia, and{{p}}Tetaz, 2013). However, individuals are able to see positional goods or conspicuous consumption from which to infer ostensible differences in income levels.{{p}}Return to text{{p}}4. I also compare these values using the 75th, 85th, and 95th percentiles for robustness. Return to text{{p}} FRB: FEDS Notes: Findings on Relative Deprivation from the Survey of Household Econ... Page 4 of 5{{p}} 6/29/2016{{p}}Last update: June 29, 2016{{p}}Home | Economic Research & Data{{p}}5. BEA produces a regional price parity index. The correlation between median house price and this price parity for all goods at the state level is very high at{{p}}0.91. For more information, see Return to text{{p}}6. This also holds when comparing the 75th and 85th percentile levels to household income. However, distance from the 95th percentile appears to give mixed{{p}}results. Return to text{{p}}7. Comparing these results to regressions using the gap between the household's income and the 75th, 85th, and 95th percentiles yields similar results,{{p}}although column 3 results are not statistically significant for the 95th percentile. Return to text{{p}}Please cite this note as:{{p}}Dodini, Samuel (2016). "Findings on Relative Deprivation from the Survey of Household Economics and Decisionmaking," FEDS Notes.{{p}} Washington: Board of Governors of the Federal Reserve System, June 29, 2016,{{p}} Disclaimer: FEDS Notes are articles in which Board economists offer their own views and present analysis on a range of topics in{{p}}economics and finance. These articles are shorter and less technically oriented than FEDS Working Papers.{{p}}Accessibility Contact Us Disclaimer Website Policies FOIA PDF Reader{{p}} FRB: FEDS Notes: Findings on Relative Deprivation from the Survey of Household Econ... Page 5 of 5{{p}} 6/29/2016
    Date: 2016–06–29
  5. By: Kirk Hamilton; John F. Helliwell; Michael Woolcock
    Abstract: We combine theory with data from different domains to provide an empirical analysis of the scale and variability of social capital as wealth. This is used to argue, given what we have learned in the literature on social capital, that the welfare returns to investing in trust could be substantial. Using social trust data from 132 nations covered by the Gallup World Poll, we present a range of estimates of social trust’s wealth-equivalent values. The estimates of the wealth embodied in social capital are very large, and with a structure and distribution quite different from those for physical capital. These estimates reflect values above and beyond what social trust contributes to supporting incomes and health. Although social trust is an important component of total wealth in all regions and country groupings, there are nonetheless big variations within and among regions, ranging from as low as 12% of total wealth in Latin America to 28% in the OECD.
    JEL: E21 E22 I31
    Date: 2016–08

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