Median Wealth Research Articles

An alternative approach to measuring the welfare implications of input subsidies: Evidence from Malawi

AbstractMost studies that have evaluated the welfare impacts of agricultural input subsidy programmes (ISPs) in developing countries have focused on measuring their effects on various outcomes of interest such as agricultural productivity. I estimate the consumer surplus accrued by direct and indirect beneficiaries of ISPs in Malawi. Malawi's Farm Input Subsidy Programme (FISP), introduced in 2005, is the largest such scheme in sub‐Saharan Africa. I find that the programme provides low direct benefits compared to the public costs of the programme. At the national level, the benefit‐cost ratio (BCR) is up to 0.37 for FISP households with no option to resell the fertiliser accessed through the programme. When reselling of the fertiliser is allowed for, the BCR increases to 0.64 including spillover benefits to direct non‐beneficiaries of FISP. I also found 60% of all fertiliser vouchers and benefits accrued to farm households with above the median wealth level. Many farmers demand 25 kg of fertiliser or less at the subsidised price. Thus, when resource poor direct beneficiaries have the option to buy 25 kg bags of fertiliser in addition to the 50 kg bags currently being offered under FISP, their benefits increase by about 53% compared to the status quo. Overall, my results suggest that a more flexible redemption of the fertiliser vouchers as well as complementary investments such as improved access to credit could increase the programme's contribution to farmers’ welfare.

Can Results-Based Financing improve health outcomes in resource poor settings? Evidence from Zimbabwe

Result Based Financing (RBF) has been implemented in health systems across low and middle-income countries (LMICs), with the objective of improving population health. Most evaluations of RBF schemes have focused on average programme effects for incentivised services. There is limited evidence on the potential effect of RBF on health outcomes, as well as on the heterogeneous effects across socio-economic groups and time periods. This study analyses the effect of Zimbabwe's national RBF scheme on neonatal, infant and under five mortality, using Demographic and Health Survey data from 2005, 2010 and 2015. We use a difference in differences design, which exploits the staggered roll-out of the scheme across 60 districts. We examine average programme effects and perform sub-group analyses to assess differences between socio-economic groups. We find that RBF reduced under-five mortality by two percentage points overall, but that this decrease was only significant for children of mothers with above median wealth (2.7 percentage points) and education (2.1 percentage points). RBF increased institutional delivery by seven percentage points – with a statistically significant effect for poorer socio-economic groups and least educated. We also find that RBF reduced c-section rates by three percentage points. We find no detectable effect of RBF on other incentivised services. When considering programme effects over time, we find that effects were only observed during the second phase of the programme (March 2012) with the exception of c-sections, which only reduced in the longer term. Further research is needed to examine whether these findings can be generalised to other settings.

Development of a temporally harmonized asset index: evidence from across 50\u2009years of follow up of a birth cohort in Guatemala

BackgroundAsset-based indices are widely-used proxy measures of wealth in low and middle-income countries (LMIC). The stability of these indices within households over time is not known.MethodsWe develop a harmonized household asset index using Principal Component Analysis for the participants (n = 2392) of INCAP Longitudinal Study, Guatemala using data from six waves of follow-up over the period of 1965–2018. We estimate its cross-sectional association with parental schooling (in 1967–75) and attained schooling (in 2015–18) of cohort members. We study how patterns of cross-sectional loadings change over time and between urban-rural settings. We assess its robustness to omission of assets or study waves and alternate specifications of factor extraction procedure (exploratory factor analysis, multiple correspondence analysis).ResultsThe harmonized index constructed using 8 assets and 11 housing characteristics explained 32.4% of the variance. Most households increased in absolute wealth over time with median wealth (25th percentile, 75th percentile; households) increasing from − 3.74 (− 4.42, − 3.07; 547) in 1967 to 2.08 (1.41, 2.67; 1145) in 2017–18. Ownership of television, electricity, quality of flooring and sanitary installation explained the largest proportion of variance. The index is positively associated with measures of schooling (maternal: r = 0.16; paternal: r = 0.10; attained: r = 0.35, all p < 0.001). In 2015–18, house ownership versus housing characteristics and ownership of electronic goods differentiate households in urban and rural areas respectively. The index is robust for omission of assets or study waves, indicator categorization and factor extraction method.ConclusionA temporally harmonized asset index constructed from consistently administered surveys in a cohort setting over time may allow study of associations of life-course social mobility with human capital outcomes in LMIC contexts. The approach permits exploration of trends in household wealth of the sample over a follow-up period against repeated cross-sectional surveys which permit the estimation of only the mean trajectory.

Abstract 20: Patterns of Stroke Center Certification and the Impact on Stroke Mortality in Counties of New York State

Introduction: To establish a statewide stroke system in March 2019, New York State (NYS) created the Stroke Designation Program. Stroke centers (SCs) must be certified by a state-approved certifying organization (CO), which is tasked with initial designation and ongoing re-certification. Previous research has found an association at the national level between socioeconomic status and access to higher levels of acute stroke care. Objective: This study characterizes the relationship between socioeconomic status of NYS populations and stroke care level access by comparing median household income and wealth in counties with and without certified SCs. Methods: Population and median household income from the U.S. Census (2010), stroke epidemiological data from the Center for Disease Control, and Area Deprivation Index (ADI) data (ranked within NYS) from the Neighborhood Atlas, a project that quantifies disadvantage by census tract, were collected and averaged for each county. Income has been used to assess local wealth and ADI to analyze community health risks. Certification data were mined from quality check databases for The Joint Commission and Det Norske Veritas, the most commonly used COs. Student’s t-tests compared income and ADI in counties with at least one certified SC to those without. Linear regression characterized the relationship between income and ADI with number of certified SCs, stroke incidence and stroke mortality. Results: All 62 counties in NYS were investigated to yield 40 certified SCs. Counties with at least one certified SC had a significantly higher income ($68,183.63 vs. $57,155.12; p=0.03) and lower ADI (5.90 vs. 7.37; p=0.004) compared to counties with no certified SC. Higher income (p&lt;0.001) and lower ADI (p&lt;0.001) were also associated with more certified SCs. Counties with fewer certified SCs had significantly higher stroke mortality (p&lt;0.001) despite having similar stroke incidence. Conclusion: Socioeconomic heterogeneity in NYS counties is correlated to differential access to certified SCs and quality stroke care, as fewer centers are found in lower-income and disadvantaged communities. Although populations with less access experience stroke at similar rates, this study finds higher death rates in these counties.

Abstract P142: The Impact of Regional Socioeconomic Status on Stroke Center Certification in the Northeastern United States

Introduction: The northeastern United States has been a national leader in stroke healthcare delivery. The current roster of designated comprehensive, primary, thrombectomy-capable and acute stroke ready centers is the result of respective state initiatives. Access to certified stroke centers (SCs) varies by county as states have widely varied certification processes and typically rely on certifying organizations (COs) to identify stroke centers. Previous research has found an association at the national level between likelihood of stroke certification and local socioeconomic status. Objective: This study describes the relationship between socioeconomic status of patient populations in the Northeast U.S. and their access to quality stroke care by comparing median household income and wealth in counties with and without certified SCs. Methods: Population and median household income for 218 counties in Connecticut, Delaware, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island and Vermont were collected from the U.S. Census (2010), stroke epidemiological data were collected from the Center for Disease Control, and Area Deprivation Index (ADI) data (ranked within the U.S.) were collected from the Neighborhood Atlas, a project that quantifies disadvantage. Median household income has been used to quantify local population wealth and ADI to analyze community health risks. Certification data were mined from quality check databases for The Joint Commission and Det Norske Veritas, the most commonly used COs, and yielded 259 certified centers. Linear regression characterized the relationship between income and ADI with number of certified SCs, stroke incidence and stroke mortality. Results: Higher income (p&lt;0.001) and lower ADI (p&lt;0.001) were associated with having more certified SCs (p&lt;0.001). Counties with a higher stroke incidence had significantly more certified SCs (p=0.01). Conclusions: Throughout the counties of the Northeastern U.S., access to quality stroke care depends on local wealth and resources. At the same time, the current analysis indicates that SC certification distribution does appear to correlate to those counties where stroke incidence is highest.

Household Wealth Trends in the United States, 1962 to 2019: Median Wealth Rebounds... But Not Enough

Median household wealth shot up by 21.2 percent in real terms between 2016 and 2019, as asset prices continued to rebound. However, 2007 still remains the watershed year, and median wealth was down 20.4 percent relative to 2007, though mean wealth more than fully recovered. There was a modest remission in wealth inequality, with the share of the top one percent down by 1.4 percentage points, that of the top 20 percent down by 1.0 percentage points, the Gini coefficient down by 0.008, and the mean wealth of the top one percent also down by 1.9 percent. The homeownership rate finally rebounded a bit, by 1.2 percentage points, to 64.9 percent. The stock ownership rate advanced by 0.4 percentage points to 49.6 percent, though still down from its 2001 peak. Though the mean debt of the middle class rose by 10.7 percent in real terms, the debt-income and debt-net worth ratios remained largely unchanged. The black-white gap in mean net worth remained unchanged, as did the Hispanic-white wealth gap. The wealth of households under age 35 continued to deteriorate in both absolute and relative terms between 2016 and 2019.

Inflation, Interest, and the Secular Rise in Wealth Inequality in the U.S.: Is the Fed Responsible?

Two hallmarks of U.S. monetary policy since the 1981-1982 recession have been declining interest rates and moderation in inflation. Coincident with these trends has been a surge in U.S. wealth inequality, with the Gini coefficient up by 0.070 between 1983 and 2019. This paper analyzes the connection between these two developments on the basis of the Survey of Consumer Finances. Contrary to expectations, the paper finds that these two monetary effects have reduced wealth inequality rather than increasing it. The effect is sizeable, with the Gini coefficient declining by 0.045 over these years. Asset price changes and debt devaluation accounted for 72.6 percent of the advance of mean wealth over 1983-2019. They also would have led to a 204.9 percent gain in median wealth, compared to the actual rise of 23.4 percent. Moreover, they have helped lower the racial wealth gap rather than enlarging it. These results are at odds with previous literature in which estimates range from a weak negative effect on inequality to neutral, small positive, and strong positive. In terms of methodology, this paper differs from previous work by focusing on only the direct effects of interest rate changes and inflation on the household balance sheet.

Investment, Saving, and Borrowing for Children: Trends by Wealth, Race, and Ethnicity, 1998–2016

This article examines the link between wealth inequality and families’ financial investment, saving, and borrowing for the sake of children. Using the 1998–2016 Survey of Consumer Finances data, we show that American families have increasingly engaged in financially more intensive parenting but that there are substantial differences by wealth and race-ethnicity. Over time, White families above median wealth accumulate more financial assets and education savings as well as less education debt for children. In contrast, Black and Hispanic families across the wealth distribution have low financial assets and education savings for children. In addition, for Black families across the wealth distribution education debt has grown to substantial amounts. These findings suggest that the contemporary norm of intensive parenting has unequal financial manifestations, which have likely contributed to the widening of wealth and racial inequalities, especially between White and Black child households.

Addressing Longevity Risk: How Best to Annuitize Defined Contribution Assets?

Unlike defined benefit pensions, 401(k) plans provide little guidance on how to turn accumulated assets into income. The key risk that retirees face is outliving their assets. Insurance against such risk is available through several routes, including immediate annuities, deferred annuities, and additional Social Security through delayed claiming. Under this Social Security bridge option, participants would tap their 401(k) for payments equal to their Social Security to delay claiming. This paper compares these three options in simulations against a baseline in which no assets are used to obtain lifetime income. In each option, assets not allocated to purchasing lifetime income are consumed following the Required Minimum Distribution rules. The analysis finds that, when market and health shocks are included alongside longevity uncertainty, the Social Security bridge option is generally the best for households with median wealth. Wealthier households can benefit from combining the bridge option with a deferred annuity. Part of a symposium sponsored by the Economics of Aging Interest Group.

Are They All the Same? The Distribution of Personal Wealth Between the Left and the Right in Latin America

Conventional wisdom indicates that politicians in Latin America are all wealthy. However, the literature on both political elites and social origins of political parties indicates that we should expect differences in the capital accumulation of politicians depending on their ideological position. This study seeks to explore that question using financial disclosure forms made available in six Latin American countries: Argentina, Bolivia, Brazil, Chile, Peru, and the Dominican Republic. We calculate the median wealth of the main political parties in each country and compared them according to their ideological position on the left–right continuum. We consistently find that the most right-leaning party in each country had a higher median wealth than the most left-leaning one. This relation is non-linear since centrist parties often represent anomalies in the distribution of wealth. When there are no ideological differences, we do not observe significant wealth differences either.

How best to annuitize defined contribution assets?

Abstract401(k) plans provide little guidance on turning accumulated assets into income. Insurance against the risk of outliving one's assets is available through immediate annuities, deferred annuities, and additional Social Security through delayed claiming. Under this Social Security bridge option, participants would tap their 401(k) for payments equal to their Social Security to delay claiming. This paper compares these three options in simulations against a baseline in which no assets are annuitized. In each option, assets not allocated to purchasing lifetime income are consumed following the required minimum distribution; robustness of results to optimal drawdown conditional on annuitization strategy is also assessed. The analysis finds that, when market and health shocks are included alongside longevity uncertainty, the Social Security bridge option is generally the best for households with median wealth. Wealthier households can benefit from combining the bridge option with a deferred annuity.

The long-run effects of noncommunicable disease shocks.

The health shocks literature typically does not take into account the temporal patterns of loss since the time of the shock. This limits understanding of the long-run impact of health shocks and the capacity of individuals to cope over time. This study estimates the dynamic effects of a noncommunicable disease shock on the economic well-being of working-age individuals in China up to 6 years after onset. We find that after a period of temporal loss, individuals and their families can insure consumption against the average noncommunicable disease shock over the long-run. We observe significant heterogeneity according to the persistence of the disease, value of household wealth, and health insurance status. Individuals with consistent onset, with below median wealth, and without health insurance are least equipped to smooth consumption over the long-term.

Salud ambiental del río ranchería a través de macroinvertebrados acuáticos en el área de influencia del complejo carbonífero el cerrejón

Objetivo: Esta investigación tuvo como objetivo evaluar la salud ambiental del ecosistema lótico río Ranchería en el área de influencia del complejo carbonífero El Cerrejón, a través de bioindicación con macroinvertebrados acuáticos.&#x0D; Metodología: Se establecieron tres estaciones de monitoreo (E1, E2 y E3), en las cuales se realizaron mediciones de variables fisicoquímicas como: temperatura (ºC), oxígeno disuelto (mg/l), pH, salinidad (%o), conductividad (µS/cm), turbidez (UNT), sólidos suspendidos totales (mg/l), cloruros (mg/l), amonios (µg/l), nitritos -(µg/l), nitratos (µg/l), fosfatos (µg/l) y demanda bioquímica de oxígeno (mg/l) Los macroinvertebrados acuáticos se colectaron a través de muestreo multihábitat por arrastre con red surber, red D-net y recolección de organismos bentónicos, usando nucleadores PVC. La calidad de las aguas en cada estación de monitoreo se clasificó mediante el índice BMWP/col.&#x0D; Resultados: Como resultados relevantes, se encontró que las familias de macroinvertebrados acuáticos con más abundancia en E1 fueron Baetidae, Coenagrionidae, Philopomamidae, Leptohyphidae y Leptophlebiidae; en E2, Culicidae, Hydrophilidae, Coenagrionidae, Psephenidae e Hydrobiidae, y en E3, Coenagrionidae, Hydrobiidae, Belastomatidae y Palaemonidae.&#x0D; Conclusiones: Se concluye que E1 posee aguas de buena calidad (BMWP/col = 130; ASPT = 6,50), con alta diversidad y riqueza (H’E1 = 3,75 bits/ind; IE1 = 4,76); E2 y E3 poseen aguas de calidad aceptable (BMWP/col = 65; ASPT = 5,00) y calidad dudosa (BMWP/col = 50; ASPT = 5,25), respectivamente, con mediana diversidad de familias (H’E2 = 2,97 bits/ind y H’E3 = 2,32 bits/ind) y mediana riqueza (IE2 = 2,82 y IE3 = 1,88).&#x0D; &#x0D;

Spatial and epidemiological drivers of Plasmodium falciparum malaria among adults in the Democratic Republic of the Congo

BackgroundAdults are frequently infected with malaria and may serve as a reservoir for further transmission, yet we know relatively little about risk factors for adult infections. In this study, we...

Changing Wealth Accumulation Patterns: Evidence and Determinants

The patterns and determinants of household wealth accumulation have long been of interest to economists. Using the 1989 and 2016 Surveys of Consumer Finance, we examine the determinants of changes in mean and median wealth of households of given ages across different birth cohorts. While the Great Recession reduced wealth in all age groups, longer-term trends show that wealth of older age groups has increased while the wealth of younger age groups has declined. We show that a substantial share of these changes, in both directions, can be explained by the evolution of household demographic and economic characteristics.

The Wealth of Generations, with Special Attention to the Millennials

We examine household wealth across birth cohorts and over time using data from the Survey of Consumer Finances. We show that although the Great Recession reduced wealth in every age group, longer-term trends indicate that the wealth of older age groups has increased while the wealth of younger age groups has declined. A substantial share of these changes, in both directions, can be explained by changes in household demographic and economic characteristics. As for the millennial generation, their median wealth in 2016 was lower than the wealth of any similarly aged cohort between 1989 and 2007. Millennials will have several advantages in wealth accumulation relative to previous generations, such as more education and longer working lives, but also several disadvantages, including weak prospects for economic growth and delays in home purchase and marriage. The millennial generation contains a significantly higher percentage of minorities than previous generations. We estimate that minority households have tended to accumulate less wealth than whites in the past, controlling for household characteristics, and the difference appears to be growing over time for Blacks relative to whites. These results apply to the period before the COVID-19 pandemic and are best interpreted as addressing generational wealth patterns through 2016 and providing a pre-COVID benchmark against which future studies can be compared.

Wealth inequality and economic mobility in the post-revolutionary Pennsylvania backcountry

Township tax lists for 1783 and 1793 are used to examine the distribution of wealth and economic mobility in York County, Pennsylvania following the Revolutionary War. Measures of inequality are inconclusive, but the typical York County household was worse off in 1793 than in 1783: median wealth fell 5 percent. The poorest households recorded an increase in assessed wealth. Over 40 percent of households disappeared from the tax lists, with the least wealthy being the most likely to leave. Households that remained in the county were far more likely to see an improvement in their relative status than a decline.

Can income differences explain the racial wealth gap? A quantitative analysis

We use a quantitative, overlapping-generations, incomplete markets, life-cycle model to explore the extent to which income differences can explain the racial wealth gap. The model features race, education, and family structure-specific stochastic household income processes estimated using data from the PSID, race and education-specific lifespan risk, an income floor, and intergenerational transfers of wealth and labor market ability. A calibrated version of the model fully accounts for the racial wealth gap observed in the data. In addition, it endogenously generates an empirically plausible degree of wealth inequality, both conditional and unconditional on race, and is broadly consistent with observed patterns of wealth accumulation over the life cycle. Simulations of the model suggest that income differences, on their own, can explain 43.0% of the racial wealth gap in levels, while bequest motives and intergenerational transfers of wealth, in the presence of income differences, account for 28.6% and 25.8% of the gap, respectively. We find that the income floor has a negligible impact on the racial wealth gap in levels, but causes the ratio of median wealth (white/black) to more than double as it disproportionately reduces the incentive that low income, low wealth households, the majority of whom are black, have to save. We also find that differences in lifespan risk have only a small impact on the racial wealth gap levels, but lead to a 13.7% increase in the ratio of median wealth.

Intergenerational Differences in Income and Wealth: Evidence from Britain

AbstractHow do average levels of income and wealth differ in Britain for those born between the 1930s and 1980s? Those in the 1980s cohort are the first post‐war generation not to have higher median incomes in their early 30s than those born a decade earlier, though they have much higher incomes than those born in the 1960s and earlier. Median wealth for those in the 1980s cohort is 20 per cent lower in their early 30s than it was for those born in the 1970s. This is driven by lower property wealth and homeownership: 40 per cent at age 30 for the 1980s cohort, compared with 55 per cent for the 1970s cohort.

Do criminally accused politicians affect economic outcomes? Evidence from India

We study the causal impact of electing criminally accused politicians to state legislative assemblies in India on the subsequent economic performance of their constituencies. Using data on the criminal background of candidates running in state assembly elections for the period 2004–2008 period and a constituency-level measure of economic activity proxied by the intensity of night-time lights, we employ a regression discontinuity design and find that narrowly electing a criminally accused politician lowers the growth of the intensity of night-time lights by about 24 percentage points (approximately 2.4 percentage point lower GDP growth). The negative impact is more pronounced for legislators who are accused of serious or financial charges, have multiple accusations, are from the non-ruling party, have less than a college education, or have below median wealth. Overall, we find that the effect appears to be concentrated in the less developed and the more corrupt states. Similar findings emerge for the provision of public goods using data on India's major rural roads construction program.