SOCY 234 Midterm

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Income concentration in .1%

Back to the same level as the 1920s (12%)

Head Start and Early Start

Established in 1965 as part of Johnson's "Great Society" programsToday Federal government provides grants to local agencies to provide head start services. In 2016, served nearly one million children•Enrolled in "head Start" programs or "early head start" programs Impacts: Early childhood programs have long-term effects on educational attainment and related outcomes Effect seems to operate largely through improving self-control and other "soft" skills Impact of early childhood programs can be enhanced or muted depending on subsequent K-12 environment By most any measure, early childhood interventions 'pays for itself' over the long run

Median Family Wealth Gap b/w Black and White and White and Hispanic

Increasing

Inequality in Parental Investments

Its not just that children of middle- and upper-income parents benefit from having more resources (+ more educated parents, etc.) Class-based differences in 'concerted cultivation' Not just parenting styles, differences in time and $$ available to invest in children Kids of higher income parents are more likely to be in extracurricular activities Mothers and fathers with higher incomes can spend more time with their kids Financial investments in children proportional to income percentile rank This disparity is greater in places with higher levels of incomeinequality.

Give examples of policies in the U.S. that use 'poverty' in eligibility

MedicaidSNAP (Food Stamps) & WICHead StartEnergy/Heating Assistance

Measuring Mobility (what, time, data) | Approaches

What are we measuring and how do we compare over time? •Occupational prestige (changes over time) •Income levels (dollar value hard to compare over time) •Who? Fathers and Sons? Parents and Children? Data intensive - requires reliable data from at least two points in time Any measure of social mobility is RETROSPECTIVE •Only tells us about social processes in the past; be careful about extrapolating to the present Approaches - Mobility transition matrix -origin occupation (father) and destination (son) tabulations - percents of quintiles ended up in what quintiles

How do States shape market inequality? (pre and re distribution)

"Predistribution" •Setting wage floors (min wage) •Setting wage ceilings either directly or indirectly via marginal tax rates •(Company Boards wont pay CEOs 100 million if 90% of that goes straight to government!) •Labor contracts (rules around firing, hiring, credentials, etc.) •Facilitating (or impeding) unionization •Investing in healthcare, education, transportation, etc. •Industrial policy, research and development, etc. Bottom line: Governments play a central and essential role in determining the nature of markets, and by extension, of inequality. "Redistribution" •Taxation (of households, corporations, land, consumption, etc.) •Transfers (cash benefits, near-cash benefits like SNAP food stamps, etc.) To determine level of redistribution often compare "market" income to "disposable" income. That is, income 'pre-' and 'post-' taxes and transfers

Housing Affordability Crisis || Eviction and Social Disruption

"Today, there is not one U.S. state, metropolitan area, or county in which a minimum wage worker who clocks 40 hours a week can afford a two-bedroom apartment. And only in 28 of the country's counties can a 40-hour-a-week minimum wage worker afford a one-bedroom."

Measuring Mobility: IGE (not time)

(GE = Intergenerational Elasticity (typically of income) Measures how a 1% increase in (log) parent's income affects (log) child's income IGE Score range from 0-1; higher IGE, lower mobility. Estimate for USA ~0.4 IGE of 0.4 means for 1% higher parental income, child income is 0.4% higher; if two households have incomes that differ by 10 percent, their children's income will differ by about 4 percent Common summary metric of economic mobility; specific to time and place

OPM Threshold, Measure of resources, Equivalence Scales, Aggregation, Data

* Threshold - 3 x (Price of TFP in 1963) •Set in the 1960s •Updated for inflation using the CPI-U * Measure of resources - cash money * Equivalence Scales - + set amount per additional person. * Aggregation - annual; related persons living together (aka family/household). * Data - Uses the March Current Population Survey.

Comparative perspective on US mobility

- American Dream alive and well in Canada Relative mobility is almost twice as high there - Son's earnings are tied more closely to father in US than Canada and Europe (except UK) Mobility appears to be lower in the U.S. relative to peer countries; at least for recent observable birth cohorts. Put another way: Parent's economic position is more determinative of child's economic position in the USA relative to Canada, Germany, Norway, etc.

Official Poverty Measure (OPM) - Developed by whom & under what circumstances - What was it before? - Describe purpose

- Developed by Mollie Orshansky, an analyst at the Social Security Administration (SSA), in the early 1960s - Designed to improve upon a prior standard: any family of two or more with annual income of less than $3,000 and any single person (living alone) with less than $1,500 in annual income to be poor - Intended for internal program planning and evaluation, not to be elevated to the OPM - indeed the SSA did not refer to the threshold as a "poverty line" or the measure as a "poverty measure" - The Office of Economic Opportunity (OEO), which was created as part of the War on Poverty, later adopted it as the official poverty measure.

COVID poverty levels

- Dropped a ton with govt transfers - International: Dropped a lot as well in comparison to other countries

Section 8

- Housing Choice Voucher Program (known as Section 8) established in 1974. - Administered by the feds but "run" locally by 2400 local/state/regional "Public housing agencies" - Currently assists more than 2 million households - NOT an entitlement: because of funding limitations, only one in 4 or 5 households eligible for vouchers receive assistance. Eligibility: - Income eligibility set as percentage of median income in local area -between 50 and 80 percent. - Housing agencies are required to have 75% of new entrants be 30% of area median income or below ("extremely low income") How it works: - Family applies through local PHA; gets put on waitlist Once awarded a voucher, family must lease a unit within ~60 days. •Once unit picked, housing agency must inspect for quality; ensure rent is reasonable. Landlords don't have to take Section 8 (but many want to...) Once unit approved, family pays 30% of income in rent - > remainder is covered by voucher. Incredibly long waiting lists... 20,000-50,000 families... about 300 people leave each year.

How does income concentration compare in other countries? Is US an Inequality outlier?

- Many other countries also have wealth that concentrates at the top (UK, Canada, US) | U Shaped concentration - but, not everywhere: there are countries with an L shape France, Japan, Sweden: top 1% is low and they were also exposed to globalization, computers, etc. US is nor an outlier before redistribution, it's the worst at reducing inequality of all high-income OECD countries Market level income inequality in U.S. is in linewith other OECD countries Post-tax and transfer inequality in U.S. ismuch higher than most OECDcountries Taxes and Transfers do less to reduce market income inequality in U.S. relative to other countries.

Markets and the Govt (Adam Smith)

- Markets CANT exist without the government. Commerce flourishes better with confidence in govt - Great property = great inequality Often heralded as the father of "laissez-faire" capitalism...In fact knew well that markets are createdby—and depend on—the government (for regulation, redistribution, education, etc.) "The Economy" or "The Market" is not a natural phenomenonIt does not sit outside (or next to) government Governments (societies) CREATE Markets -Recognize and enforce property rights Establish rules of trade, labor contracts Provides essential public goods (schools, roads, healthcare) Protects the environment; Prevents child labor/exploitation, etc.

Gini Index/Coefficient + Lorenz Curve (horizontal axis, vertical axis, diagonal line, calculations)

- The Gini coefficient is a numerical measure of inequality based on the Lorenz curve - Provides a summary of the entire income distribution - Lorenz Curve: a graphical device used to represent distributional inequality. •Along the horizontal axis we measure the Cumulative Percent of Households (poorest to richest). •Along the vertical axis we measure the Cumulative Percent of Income or Wealth. So, at the 20% mark is 20% of total income or wealth held by the population and at the 60% mark 60% of wealth. •The diagonal line represents exact equality in income or wealth distribution. Now we plot the cumulative percentage of income earned as we move up the income distribution. The more "bowed" the curve—the further from the line of equality—the more inequality. We can summarize this distribution by simply comparing Area A to the area of total equality.The Gini Coefficient = A /A+B

Measurements of residential segregation (even..exp...con...cent...clus) Most common measure?

1. Evenness •Compares the spatial distributions of different groups among area units in a metropolitan area. •Segregation is smallest when groups are evenly distributed across space Most common measure: Dissimilarity Index - measures the percentage of a group's population that would have to move for each neighborhood to have representative mix of metro pop. Other measures: Gini Coefficient, Entropy, Atkinson 2. Exposure •"Exposure measures the degree of potential contact, or possibility of interaction, between minority and majority group members" •Similar to evenness measure, but incorporates information on relative sizes of the two groups (which informs likelihood folks will interact) Most common measure: Isolation index - computed as the minority-weighted average of the minority proportion in each area. 3. Concentration •"Concentration refers to the relative amount of physical space occupied by a minority group in the metropolitan area." •Minority groups of the same relative size occupying less space would be more concentrated and therefore more segregated Measures: Delta; Absolute Concentration; Relative Concentration 4. Centralization •"Centralization is the degree to which a group is spatially located near the center of an urban area" •Typically defined as location relative to the 'central business district' -or population centroid Measures: Relative centralization—relative share of minority pop that would have to move to match centralization of the majority 5. Clustering "The extent to which areal units inhabited by minority members adjoin one another, or cluster, in space"Measures: Relative clustering—compares the average distance between [minority] members with the average distance between [majority] group members.

Fertility and Parenthood trends

1. Overall Fertility Decline Has declined a lot among all races, highest in Hispanic but big decline, lowest in Asian and white, even more low Amer-indian 2. Dramatic, Recent Decline in Teenage Pregnancy historic lows of US teen pregnancy, birth, and abortion rate | was high in baby boom years 3. Rise in Age at First Birth Was really high at 18-20, now more so late 20s and 30s Big rise in women having babies older than 35 4. Decoupling of Marriage and Childbearing Rise in births to unmarried women, especially in the black population Nonmarital childbearing has increased for women of all education levels 5. Rise in Multi-partner Fertility More parents with multiple partners

Changes in household structure....

1. Rise of Single Parent Families (two-parent decreasing, one parent increasing) 2. Increasing Variation in Household Composition (less children with two parents in first marriage, now there are two parents, cohabiting, single, etc) •Rise of Persons Living Alone •Increasing variation in child household context Black children and those with less educated parents are less likely to be living with two-parent households

Factors related to schools (inputs)

1. Student background & home life•Early childhood/school readiness•Safe environment; adequate food, shelter, care 2. Classroom Effects•Teacher quality•Peer effects 3. School or 'Building' Effects•Principal/Quality of Administration•Peer effects 4. Neighborhood effects•Violence, poverty, crime, peers 5. District (and/or City/Town and State gov't) Effects•School finance (inequality)•Curriculum, policies, etc. Difficult to make "all else equal", "nesting"

Poverty Trends: OPM vs SPM (2016, COVID, 1967-2012)

2016: - All people: SPM higher - under 18: OPM higher - 18-64: SPM higher - 62+: SPM a lot higher (because of medical bills) COVID: - SPM dropped significantly below the OPM due to the expanded Child Tax Credit during COVID - Tax credit became fully refundable, usually only benefits middle class since it's a tax deductible - Cut Child SPM poverty by almost half - OPM appears to have changed little in recent decades, but SPM shows how important govt tax credits have been to keeping poverty low - Public policies and programs have become MORE important in reducing poverty levels (effect of taxes/transfers on reducing pvoerty has increased 10X with the SPM) According to OPM, poverty has changed little since the 1960s (failure of war on p?) BUT SPM shows a bit of improvement on poverty rates and the increasing importance of govt policies in mitigating poverty.

Public Housing/Hope VI / Tax Credit

Approximately 1.2 million public housing units in the US—home to about 2.1 million Americans. •Declined by more than 250K since mid 1990s; cities demolished massive public housing "projects" Hope VI is program that funds investment in public housing/redevelopment Like section 8, households pay 30% of income in rent. Created as part of 1986 Tax reform to provide incentives for private development of affordable housingCost to Feds ~6 billion per annum - administered by the states who apportion tax credits to developers through a competitive process.Accounts for 90% of all new affordable housing in country.

New Evidence by Chetty

Beyond MTO, Chetty and colleagues used their income tax data to ask: what is the effect of being "exposed" to a given city for a year on later life earnings? Take advantage of families who move from one city to another (and the different ages of siblings in those families) to isolate causal effects. - Able to estimate the 'causal' effect of place on earnings - "Neighborhood" here is county/city level Key Takeaway: Place matters. A lot. So place-based interventions may be both efficient and effective.

History of Mobility studies in sociology (Blau and Duncan, Wisconsin)

Blau and Duncan's "status attainment model" (early 1960s)Aims to decompose the effect of 'achieved' factors (e.g. education level) and 'ascribed' factors (e.g. parent income) on an individual's 'occupational status' in adulthood. - only considered five predictors (father's education & occupation, individual's education and first job, individual's later job) "Wisconsin Model" of status attainment extended this work by incorporating more factors (S/O, aspiration, academic performance, mental ability) Today sociologists continue to study social mobility--levels, trends, determinants, etc.—from multiple vantage points including class, occupation, education, health and income/wealth.

US Comparison to other countries in family demographic measures (prevalence vs penalties framework)

Bottom Line: The United States is experiencing similar levels/trends in non-marital births, delayed/decline marriage, rise of cohabitation, etc. There is nothing unique or exceptional about the demography of the family in the United States. BUT... the Child Relative income poverty rate is much higher in the US Across countries, four main risk factors for household poverty: 1. Young headship (age of household head) 2. Single motherhood 3. Low education (of household head) 4. Unemployment (of household head) Permits us to ask: Is (relative) poverty higher in the U.S. due to higher prevalence of risk factors or higher penalty associated with those risks? In other words, is poverty higher because we have 'more' X [young hh, single mothers, low education HH, unemployed HH] or because the penalty associated with being X is higher? "The United States has high poverty partly because it has the highest penalties [associated with these risk factors] despite below average prevalences [of the risk factors]."Policy Context Matters!

What is higher education?

Broadly: Any education or skills training after achieving a high school diploma or GED This includes •Bachelors (aka '4 year' degrees) •Associates (aka '2 year' degrees) •Certificates•Etc. 'Some college' typically refers to individuals who have enrolled in college level course work but did not complete a bachelors degree Often 'some college' includes AA degree holders 'Some College' is fastest growing—and most heterogeneous group! Moving away for 4 year college is NOT typical, ~35% of college students older than 25; ~25% raising children• 58% of college students are working while in school; 40% of full time students •10% of full time students work 35+ hours per week

How to measure mobility through time...

But how do we compare incomes from different time periods? Particularly with changing levels of inequality in income distribution? How to compare 2 IGEs: Parent Income 1940s Child Income 1960sParent Income 1980s Child Income 2000s Rank Rank Correlations Instead of comparing parent-child income levels (IGE) compare their income percentile ranks! Assign everyone a percentile rank in the national income distribution relative to others same age; then compare child's income percentile rank to that of their parents' income percentile rank measured years earlier. A measure of economic mobility that maps on to changes in economic (social) position.

Immigration and mobility

Children of foreign born parents more upwardly mobile than children of U.S. born parents True in late 19th century....True 'today' Even though the composition of sending countries has changed dramatically (+ rising inequality, etc.)

AFDC/TANF Benefits Over Time

Declined significantly

COVID 19 Effects on Education

Decreased math scores with covid in many places, mostly decrease in reading scores "Free/Reduced Price Lunch" SES: FRPL

Critique of the OPM: Threshold

Doesn't vary by geographic region (other than AK+HI) The 'Thrifty Food Plan' measure was problematic from the start -USDA in 60's estimated that only about 10 percent of persons spending the amount of the TFP were able to get an adequate diet. Doesn't reflect changes in spending patterns - families now spend a much lower fraction of income on food Doesn't reflect changes in standards of living - productivity and median income have increased faster than the rate of inflation Doesn't comport with subjective measures of poverty CPI-U may not be right inflation adjuster

Percent of children earning more than their parents

Down

Poverty

Dynamic process - Levels are SNAPSHOTS at a given point in time ' an 'annual' aggregation - But poverty is NOT static, not the 'same stock' of people - Most are only in poverty for a given period of time - Families cycle in and out of poverty (job loss, divorce, illness, etc) Bouts of poverty extremely commonexperience for: •Households with children •Persons with less education •Female-headed households •Black and Hispanic households.

Economic Inequality

Economic inequality measures the disparity between a percentage of population and the percentage of resources (such as income)received (or owned) by that population. Inequality increases as the disparity increases.

New Estimates of Economic Mobility (Rank-rank) KEY FINDINGS

Economists (and other social scientists) have increased attention to social/economic mobility Raj Chetty & "Opportunity Insights" Team •New estimates of intergenerational economic mobility using IRS administrative data New mobility estimates generated using IRS Administrative Data on 40 million children born between 1980 and 1993 and their parents (Chetty et al. 2014). Comparing the national income rank of child at age 26 to the national income rank of their parents years earlier. Step 1. Take all people born in a given year (e.g. 1980). Rank order all of those individuals according to income at age 26. Assign an income percentile based on that ranking. Step 2. Now take all the PARENTS of children born in that year (1980). Rank order all of those PARENTS according to their income when child was ~12. Assign an income percentile based on that ranking. Step 3. Calculate the correlation between the income percentile ranks of parents and their children. Higher "rank-rank correlation" (aka "rank-rank slope") means lower economic mobility. •Rank-Rank Slope (Percentile Income Mobility): Correlation betweenincome percentile ranks of parents and children measured at age 26.•About 0.34; +10 percentile in parents rank ~ +3.4 percentile increase for children •Absolute Upward Mobility: Mean percentile rank of children born to parents at X income percentile. Two Key Findings from work by Chetty and Colleagues 1. The level of economic mobility in the United States has remained unchanged in recent decades. (RELATIVE) Relative stable over time 2. There has been a dramatic decline in the percentage of children who earn more than their parents in adulthood. (ABSOLUTE) Children are less likely to earn more than their parents did in adulthood. ABSOLUTE mobility has declines (REAL DOLLARS EARNED)

Chetty: colleges and economic mobility

Enter Raj Chetty and the Opportunity Insights Using those tax records, Chetty and colleagues were able to examine the degree to which a given institution is mobility enhancing. To do this they compare two key features: •"Access" - degree to which low-income students are represented at that institution •"Success Rate" - probability that a low-income (Q1) student will reach Q5 after graduation. •Mobility = Access x Success Rate Mobility enhancing institutions: Cal State in LA Fact #1: Income segregation across colleges is comparable to segregation across Census tracts in the average American city. (that is, very segregated!) Fact #2: At any given college, students from low- and high- income families have very similar earnings outcomes •Colleges effectively "level the playing field" across students with different socioeconomic backgrounds whom they admit. Fact #3: Certain mid-tier public institutions (e.g., CUNY, Cal-State) have the highest bottom-to-top quintile mobility rates Free college? Higher income students more likely to go to college. Thus, any broad policies (free college, reduction in student loan interest, forgiving student loan debt, etc.) may actually serve to INCREASE inequality across income levels and racial and ethnic groups.•By reducing the cost of attaining a credential that ultimately leads to very high returns in the form of higher wages.

Spatial correlates of mobility

Equality of opportunity vs equality of outcomes - Correlation, not causation Harness spatial/temporal variation in U.S. mobility levels to recover causal determinants of mobility. A few findings so far: •Medicaid coverage in utero + infancy •Pollution exposure (Air, Ground) •Violent Crime •School funding •Industrial mix/presence of manufacturing And many, many other studies still in progress!

Environmental Inequality (lead poisoning, pollution, literature)

Fast growing literature documenting association between pollution (air, water, soil, etc.) and life outcomes (birthweight, test scores, graduation rates, labor market outcomes, etc.). Pollution exposure varies dramatically across localities Pollution levels tend to be highest in low-income & minority neighborhoods. Lead Exposure and Lead Poisoning Dangerous feedback loop Literature documenting the causal effect of air pollution, super fund sites, lead levels, etc. on not only health but education and labor market outcomes Literature quickly connecting dots to economic mobility as well •We find that children who grew up in Census tracts with higher levels of traffic-related air pollution and housing-derived lead risk experienced lower adult incomes on average relative to their parents and higher likelihoods of being incarcerated as an adult or having children as teenagers, after controlling for standard socio-demographic characteristics and metropolitan-level effects. •The spatial distribution of these two pollutants is surprisingly different, however, with air pollution varying mostly between regions of the country while lead risk varies dramatically between neighborhoods within the same city •Yet, each pollutant predicts the three aspects of social mobility similarly, and we show important disparities in exposure by race. Differential exposure to environmental toxins in childhood may be a contributor to racial inequality in socioeconomic outcomes among adults.

Housing Policies for the rich

Home mortgage interest deduction Property tax deduction Bottom Line: Gov't spends (way, way) more subsidizing housing (homeownership) for the rich than it does subsidizing housing (rental) for the poor. •For the five-year period from 2017 to 2021, the JCT estimates that federal expenditures for five significant benefits for homeowners will be $409.9 billion. •Meanwhile, the JCT estimates federal tax expenditures for rental housing during the 2017-2021 period at $71.7 billion-including $46.9 billion for LIHTCs.

Zoning Laws and U.S. Income Inequality

In recent decades, we've seen people moving AWAY from high productivity/high wage cities to low-productivity/low-wage cities...Why? Well in part due to THE COST OF HOUSING! •And whats the most effective way to reduce the cost of housing in a city? (Typically Liberal) NIMBYs and ZoningIf we want to increase wages, need to increase housing availability in high wage, high growth cities This means increased density in urban cores, public transit, etc. EXTREMELY difficult because of existing zoning laws (SFH districts in large cities; parking to unit ratios, etc.) Current (typically liberal) residents block efforts to develop new housing (SF, NYC, Boston, DC, etc.) in order to preserve views, "character", etc. Change Zoning to Combat Inequality - One of the single most effective non-tax policies to reduce income inequality is to expand housing availability in high demand cities... - By some estimates, U.S. would be 10% RICHER overall if workers couldafford to live in high wage cities... - Current residents often standing in the way... - Exciting movement on this front (MN, CA, etc.)...but a long ways to go

Effects of higher education

In social science we think of the 'effect' of higher education on life chances (ielabor market outcomes) operating through two main channels: 1. Skills development and training •Specific: learn computer programming or biochemistry •General: learn how to learn, read, think, interact with people from different backgrounds, etc.—flexible skills for a lifetime 2. Credentialism •Labor market rewards having the degree, not actually the skills Strong 'selection' into higher education—certain people more likely to go than others. These are the type of people who might already be set up for success. [Like you!] Figuring out the 'returns to college education' requires us to deal with this 'selection' effect - and its why the answer to 'is college worth it?' is not so straightforward.

Race and Mobility

In the United States, Black Americans (+Hispanic Americans, +Native Americans) are: 1) Less likely to experience upward mobility 2) More likely to experience downward mobility...relative to White Americans White boys who grow up rich are likely to remain that way, while black boys raised in similarly wealthy households are more likely to fall to the bottom than stay at the top in their own adult households. Black and white women raised in families with comparable incomes earn more similar amounts as individuals in adulthood. The household incomes of white women, as a result, are higher on average. Both Asian-Americans and whites are likelier to move up the income ladder than down it. Note that for Black women vs white women born at 25th percentile: •Mobility rates (conditional on parent income) are similar if we look at individual income in adulthood •Mobility rates (conditional on parent income) lower for black women if we look at household income Black-White mobility gap using individual income is large for men, small for women. BUT Black-White mobility gap using household income large for both men and women. •Why? Less likely to marry. And, assortative mating. Underscores specific challenges and obstacles facing Black men (labor markets, incarceration, policing) Similar story with wealth mobility

Gini Coefficient Trends in the US. Why is this happening?

Increasing a lot from 1970-2020 (means inequality up) 1917-1947: sooo much inequality What's really increasing is the wealth of the top 1%, but even closer it's actually the top .01% High levels of inequality in 1920s precedes stock marketcrash and great depression.Mid-century we have the "great compression" -characterized by increasing productivity/wages, broadlyshared prosperity...Starting in 1970s, inequality starts to take off,with new income gains being concentrated among higher incomeearners.

Credentialism in occupations

Increasing number of jobs requiring licenses and certificates, which can be very time consuming and expensive!!! Peak Credentialism? Movement to reduce the # and extent of occupational licensing. Also to remove 'college degree requirement' for many jobs.^PA Governor changing rules for state government jobs. Key to provide pathways to stable/quality income for those without acollege degree

Racial and Ethnic Wealth Gaps | Drivers | Why it's not closing

Increasing wealth gap over time - has NOT fallen - slight decrease white-hispanic - increase white - black - Racial wealth gap growing over life course of those born in 1950s Driven by: History - slavery, Jim Crow, - Govt Policies: redlining, discrimination in access to housing, education, employment Not closing because... - Wealth begets wealth - Wealth as summary metric of cumulative advantage or disadvantage Lifetime income / Accumulated earnings - higher for white people, lower for black and hispanic men - lower overall for women, but same trend Homeownership is much higher among white people, about less than half for black and hispanic Retirement savings much, mich higher for white people, low for black and hispanic Black families provide higher rates of unofficial financial assistance to others compared to white people, especially if they're earning more money Student loan debt is highest for black people, lowest for hispanic Persistence over time is striking, given narrowing of gap in other domains Speaks to nature of wealth; Power of history; and the inadequacy of the present (trajectory, policy)

Diverging Destinies

Introduced by sociologist and demographer Sara McLanahan Describes two different trajectories for women and children as a function of maternal education (SES). Mothers with a college degree: •More likely to be married •More likely to enter first marriage at later age•Higher age at first birth •Much more likely to be employed & have higher HH income •Less likely to divorce Less likely to be a single parent Mothers with less education: •Less likely to be married •More likely to enter first marriage at an early age•Lower age at first birth •Much less likely to be employed & have lower HH income •More likely to divorce• More likely to be a single parent Bottom line: Increasing overlap between 'economic' inequality and 'demographic' inequality - mutually reinforcing Households with less education/low-income are now also: •More likely to be headed by one adult (not two)•Younger at transition to parenthood; more likely to parent solo •Less likely to (ever) marry; conditional on marriage more likely to divorce

Marriage and cohabitation: why do trends matter for inequality, poverty, mobility? What trends are there?

Key Trends: 1. Increase Age to First Marriage A little lower among white people, hispanics 2. Decline of Marriage all time low in US in 2019 (33) Amount of people never married gone up Education gap in marriage (high education = more marriage) Race and ethnicity gap (black people way less likely to marry, native americans) 3. Rise and Fall of Divorce Rose until 1980, dropped, lowest rate in 2019 4. Rise of Cohabitation Less people living with spouses, more with partners. Adults ages 25-34 are most likely to be cohabiting (though most are married) Rise in the percentage of women who have every cohabited from 1987 to 2010

Why is inequality rising since the 70s?

Manyfactors contribute to (or correlated with) rising inequality since '70s,including: Increasing returns toeducation Skill-Biased Technological Change (SBTC) Financialization of Economy Globalization (trade); Automation,etc. But these forces are happening in every country...and yet growth in inequality in US more extreme than elsewhere Gap between productivity and typical worker;s compensation has increased dramatically since 1973 | CEOs make 312 more times than typical workers - Union membership is dropping, income going to top 10% is going up - Top MTR (marginal tax rate) has fallen quite a bit since the 1960s - Average tax rates for highest income taxpayers are dropping (1945-2009) - even lower for .01

Market, Pre, Post Tax income

Market income is highest, post tax income lowest, pre middle

How might where you live affect your life chances?

Material Pathways (jobs, housing stock, etc.) Institutional Pathways (schools, criminal justice, etc.) Psycho-Social-Physical Pathways (peer effects, social interactions, isolation of built environment) Examples of neighborhood factors: K-12 School Quality Quality of Public ServicesHigher Ed Presence Quality of Civil/Non-Profit SpherePeer effects Built environment (eg sidewalks)Pollution/Green Space Police/Criminal Justice

Measuring Income Inequality (concerned with...)

Measures of Income Inequality are therefore primarily concerned with summarizing the shape of an Income Distribution 2019 US: Median 68,703 Mean 98,088

Inequality and mobility relationship

Mechanically: harder to move up (or down) ladder when rungs are further apart. Theoretically: inequality may shape access to (and quality of) mobility enhancers such as education, jobs, healthcare, housing etc. Great Gatsby curve: as Gini goes up, mobility goes down

Why should we measure poverty?

More than 85 policies in the U.S. use 'poverty' in eligibility determinations || Poverty as a material construct, social construct, moral construct, political construct, policy construct

SPM: Supplemental Poverty Measure (+ difference from OPM in measurement threshold, poverty threshold, threshold adjustment, resource measure)

NAS reports (1995, 2005) lead to SPM (2011-2014) Three Big Goals: 1. Better capture basic needs (food, clothing, shelter, utilities—FCSU) 2. Allow for adjustments due to cost of living, different household arrangements. 3. Incorporate more than just cash (including government benefits!!) Measurement threshold: Families (including any coresident unrelated children, foster children, unmarried partners and their relatives) or unrelated individuals (who are not otherwise included in the family definition) Poverty threshold: The mean of expenditures on food, clothing, shelter, and utilities (CSU over all two-child consumer units in the 30th to 36th percentile range multiplied by 1.2 Threshold Adjustments: Geographic adjustments for differences in housing costs by tenure and a three-parameter equivalence scale for family size and composition Updating Thresholds: Five-year moving average of expenditures on FCSU Resource Measure: Sum of cash income, plus noncash benefits that families can use to meet their FCSU needs, minus taxes ouplus. tax keedited cainus wensk expenses. support paid to another household

Critiques of OPM (Resources)

Narrow definition of income •Doesn't take into account taxes paid or transfers received (sales/income taxes, EITC, food stamps, housing assistance) •Doesn't consider asset levels, permanent income, or savings Aggregation •Annual aggregation misses shorter bouts of hardship due to low income. •Aggregation to family level implicitly only related persons are assumed to share resources •What about cohabitating couples? •What about roommates? Don't they share resources?

Wealth Inequality (general)

Note: Wealth has proven hard to measure, especially at the very top - Rise in upper strata wealth - There has been a fall in middle-class percentage wealth - 99 percentile owns a ridiculous amount now

What are the usual concepts and measures of poverty?

Objective --> Quantitative --> Single-Dimension --> Income --> Relative, Absolute, Anchored

PROS and CONS of Gini measure

Pros: Incorporates shape of entire distribution. Cons: Requires comprehensive data about incomedistribution; provides no indication of what part ofdistribution driving overall disparity. The Lorenz Curve and Gini coefficient can be used to summarize the distribution of any discreet item: income, wealth, taxes, etc. No measure of inequality is perfect: important to compare measures to get an accurate sense of what is happening over time.

Effects of redlining (history, today, HOLC). Beyond redlining?

Redlining, broadly, is the practice of denying services to residents of certain areas based on the racial or ethnic composition of those areas In housing, banks would refuse loans (or make other investment) in neighborhood areas "redlined" on a "residential security map" Practice codified in 1935 when a federal agency asked the Home Owners Loan Corporation to create residential security maps for 239 cities classifying neighborhoods based on their desirability. Not just redlining Discrimination in access to mortgages, neighborhoods Persists in slower/less housing appreciation; lower fiscal capacity Federal subsidy of construction of suburbs, highways that demolished inner city neighborhoods, etc. -- facilitated 'white flight'

SOCIOLOGISTS

Regina Baker (UPENN) - causes and consequences of poverty in the US Deidre Bloome(Harvard Kennedy School) - Economic Self-Reliance, Educational Inequality and IG Income Persistence Xi Song (UPENN) - Educational mobility, intergenerational occupational mobility, grandparents effects on educational attainment Christina Cross (Harvard) - Family structure and dynamics influence well-being across life course Christine Schwartz (Wisconsin) - Assortative mating expert

Other Approaches to Poverty Measurement

Relative Poverty --Threshold set as fraction of national median (e.g. 60%). •Commonly used in Europe; tracks with notions of social exclusion •Measure therefore also captures income inequality •Example of Irish Celtic Tiger in the early 2000s-->living standards went up but so did "poverty"! Consumption Poverty - use a resources measure based on consumption on food (at home), shelter, and clothing with imputed rents from car and home ownership rather than income (however you define it). •Better reflects permanent income, borrowing, and savings •Better captures black market activities/income sources •Consumption data is better suited for imputing values the rental flow value of cars and homes •Unit of analysis more appropriate (spending unit versus household or family). •Requires a threshold Poverty budget - figure out the specific items that a individual or family needs to just be considered not poor and add up their costs (Self-Sufficiency Standard) Subjective measures - ask people who they consider poor, average, and apply this threshold to a resource measure Gallup: Periodically asked respondents what is the minimum amount of income that a family of 4 would need to "get along in your local community." Poverty Pulse (Catholic Campaign for Human Development): "How much income would you say a family of 4 living in the US needs to cover their basic needs?" - In 2004, the mean was over $44,000 and the median was $40,000

Residential segregation pattens in the US

Residential segregation tends to be higher in northern metros (Northeast/Midwest) •In part because housing patterns set before 1968 Fair Housing Act and little new housing developed since then; Contrast with Atlanta, Dallas, etc.Small but real reductions in segregation since 2000; Although segregation still very high by any standard Growth of Latino population increased diversity of neighborhoods for both White and Black Americans

Extreme Poverty

Rising among children, SNAP increasingly important - Debate: a lot of technical questions around measurement - Substantial rise in households with virtually no income - Homeless people (over 550,000) not counter in these official measures

Income/Wealth and the Marital Divide (selection into marriage, marriageable men, men vs women education + employment)

Selection into marriage: Substantial evidence linking male economic opportunities/outcomes to marriage rates. At the individual level, men more likely to marry only after achieving a certain level of wealth (e.g., a car) and/or stable income At a population level, we see lower marriage rates where/when male unemployment is high, where deindustrialization weakens labor markets, etc. "Marriageable Man" - term used by William Julius Wilson Local 'marriage markets' Ratio of employed (black) men to employed (black) women in an area Collapse of jobs for men with less education -> reduction in # of 'marriageable men' -> reduction in marriage/rise of single parent families. Relative rise of women in education and employment •Earn more BA degrees than men •Quickly closing gap (and passing) on advanced degrees •Rise of work requiring 'soft skills' Relative decline of men in education and employment •Earning fewer degrees relative to women •Decline of 'blue collar'/physical work •Rise of 'idleness' •Rise of incarceration and criminal justice supervision (e.g. probation) Result: mismatch in (assortative) marriage markets; more extreme for some subgroups (Black Americans overall, particularly college educated) Bottom line: Supply of 'marriageable' men is declining due to transformations in the economy; and for Black men, incarceration and early mortality ....alongside persistent + strong norms about what a 'husband' and 'father' should be; and what the relative (education + income) status position of 'husband' vs 'wife' should be Affecting some subgroups more than others (e.g., Black Americans, those with less education, etc.)

What is social mobility? (talk about stickiness, dimensions it includes)

Social mobility is the movement of individuals, families, households, or other categories of people within or between social strata in a society. It is a change in social status relative to one's current social location within a given society. It is movement between layers or tiers in an open system of social stratification. Open stratification systems are those in which at least some value is given to achieved status characteristics in a society. The movement can be in a downward or upward direction. Can describe a process occurring within- (intra-) or between (inter-) generations. Stickiness or fluidity of social 'status' or 'position' •Typically between linked generations (parent to child) 'Social' Mobility includes: •Economic mobility •Income, wealth •Other achieved status •Occupational prestige, Education •Other personal characteristics •Health & Disability Bottom Line: Its not just about money and wealth! Sociologists are interested in social position - which is not always coupled with economic position!

Schools (variations in achievement)

Spatial: lower achievement in the South, high learning rates in the west White-Black Gap White-Hispanic Gap White-Asian Gap (asians perform better) White-Native American Gap Females perform better across the board Higher income performs better than poor across the board, correlation between test scores and socioeconomic status Racial/Ethnic Achievement Gaps are declining overtime Why? Black and Hispanic Scores are Rising Faster than Whites Strong Correlation between size of achievement Gap and SES disparity Yet... some states do better/worse than predicted by SES disparities SES achievement gap is growing/ National income gap is growing, racial is dropping *SES explain large portion of achievement gap by race/ethnicity) But substantial heterogeneity in achievement gaps across states (districts, schools), even after adjusting for racial composition or SES^Suggests schools + policy context matters!

Decommodification and Boundaries of the Market (America)

States determine what aspects of social + economic life are market dependent Welfare states are characterized by degree of 'decommodification' - extent to which individuals are reliant on market Example: child care is 'decommodified' in many welfare states; Americans must rely on the market. Education, healthcare, retirement security, sick leave/disability insurance, parental leave, unemployment insurance, etc.

Social Demography Approach + Group Approach

Studying populations Individuals: can give very specific, personal reasons for somebody's actions Groups: have to draw conclusions about patterns, make generalizations Construct empirical narratives

Education trends || Is college worth it?

Substantial narrowing of HS graduation gaps across racial/ethnic groups. Variation by institution type A comparatively large share of black and Hispanic students' completions are certificates Increase in college enrollment over time•Now very large fraction of young people with 'some college' but no BA degree Women now outpacing Men in college enrollment and completionHispanic-White and Black-White college enrollment gaps narrowed in the United States between 1986 and 2014 - due to narrowing of HS grad gap BUT, among students who enroll in college, growing gaps in quality of institution attended between Black-Whites (no real change for Hispanic-White gap) See Study Even with rising cost of attendance, college still 'worth it' *on average* given increasing wage premium to college graduates. But college is only 'worth it' if you finish the degree! And tremendous heterogeneity in payoff, depending on major, selectivity/quality of institution.

TANF Program

TANF = Temporary Assistance for Needy Families Only true Cash welfare program restricted to households with children, adult must engage in work-related activities; lifetime limit TANF Benefits still leve families well below federal poverty line despite increases

What is the effect of govt redistribution policy on inequality?

Tax Policy: The US has a progressive national income tax• Progressive tax rate schedule• Large cash transfer benefits delivered via tax code (EITC) Government Transfers • Includes benefits targeted to low-income households (TANF, SNAP, etc.) • Progressive benefit structure of 'universal' programs/social insurance (social security, unemployment insurance, etc.) Gini index goes down a lot with reductio from government transfers and federal taxes

Residential Segregation... Importance for inequality, poverty mobility?

The physical separation of two or more groups into different neighborhoods—a form of segregation that "sorts population groups into various neighborhood contexts and shapes the living environment at the neighborhood level". While it has traditionally been associated with racial segregation, it generally refers to any kind of sorting based on some criteria populations (e.g. race, ethnicity, income).

Other Measures of Income Inequality (Theil's, Robin Hood, specifics)

Theil's Index: measures each individual's "distance" from the mean; provides overall summary metric like Gini. Robin Hood (aka Hoover aka Schutz) Index: proportion of total community income that would have to be redistributed for there to be income uniformity. Can also be derived from Lorenz Curve. Focusing on specific parts of distribution:Income Percentile Ratios: 90/10, 90/50, 50/10 Income Shares, for example, share of income earnedby top 10% or top 1%(more soon...)

Assortative Mating & Inequality

These factors: 1. Increased educational attainment among women 2. Rising labor market returns to education 3. Increasing marriage gap by education level 4. Increase in Assortative Mating, ie, increasing correlation in the education and earnings of partners In combination helps drive inequality across households; narrows one pathway to upward social mobility. More men marrying women who are more educated than them, now women are more likely to be educated than their husbands

Moving to Opportunity Study

Thousands of families randomly assigned to one of three groups: 1. Receive a Section 8 Voucher with requirement they move to a low poverty neighborhood 2. Receive a Section 8 Voucher (can move anywhere) 3. Do not receive a section 8 Voucher Initially: No effect of restricted vouchers on adults earnings or employment No consistent effects on child behavior or academic performance Perhaps some small positive effects on adult mental and physical health Debates: Sociologists argued (in part) that experiment failed since many families moved to other high poverty neighborhoods (or moved back), there are costs to moving that outweigh benefits, etc. Has chilling effect on causal claims in fast-growing neighborhood effects literature (despite lots of good evidence of a causal effect in other studies) Using their data on tax returns, Chetty and colleagues revisit MTO Simple idea that when looking at effect of neighborhoods on children, it likely matters a great deal at what age the children moved. If we look just at younger (less than 13) children in families who received a voucher... MTO has large effects on children's earnings in adulthood! Chetty and colleagues estimates imply that moving a child out of public housing to a low-poverty area around age 8 increases lifetime earnings by $302,000 •The higher taxes paid offsets the costs of the program.They conclude that "efforts to integrate disadvantaged families into mixed-income communities are likely to reduce the persistence of poverty across generations."

How was the OPM constructed/calculated?

Thresholds: •Constructed using consumer expenditure surveys conducted by the Department in Agriculture in 1948 and 1955; •These surveys indicated average expenditures on food by all families was about one-third of income - so they took the cost of a low price food plan (Thrifty Food Plan or TFP) and multiplied by 3. •Designed to "specify the minimum money income that could support an average family of given composition at the lowest level consistent with standards of living prevailing this county." (Orshansky, 1969) •Originally thresholds varied across farm and nonfarm families and sex (men needing more calories than women). Resource measure - cash income (that's it!)

What is Wealth? Difference from income?

Wealth = assets - liabilities Financial assets: savings, stocks, bonds, retirement savings (401(k), IRA), life insurance, etc. Physical assets: homes, property, cars, jewelry, art Also liabilities: credit card debt, mortgage debt, etc. - Assets as a "Spring Board" and a "Safety Net" | wealth-building as an anti-poverty strategy

Income segregation... What drives it?

Whereas racial residential segregation has been (somewhat) declining, residential segregation by income has increased in recent years! Across Metro Areas (Manduca 2019):•In 1980, almost 90 percent of the US population lived in metropolitan areas whose mean family incomes were within 20 percent of the nation as a whole. •By 2013, that share had fallen below 70 percent. •The fraction of Americans living in metros that were exceptionally rich or exceptionally poor had almost tripled in 30 years. At the neighborhood level (Bischoff and Reardon 2012): In 1970, 65% of Americans lived in middle-class neighborhoods.•By 2010, that number decline to 42% Recent study (Ann Owens of USC) found that between 1990 and 2012 income segregation increased only among families with children.What might this tell us about what is driving the uptick in income segregation?

Equivalence Scales

describes how thresholds change with family size and composition

Threshold (absolute or relative) [defining poverty]

the level of countable resources below which a resource sharing unit is defined as poor

Resource measure [defining poverty]

the resources (earned income only? Also gov't transfers?) to be compared to the threshold in determining poverty status.

aggregation [defining poverty]

what units are we considering, several dimensions Resource sharing unit: in a household setting the persons that are presumed to share resources Time: Annual, monthly, weekly Place: national, regional

Household Dynamics in terms of assortative mating and preferences

•Men are OK with 'marrying up' w/r/t education if they earn more •Women in gender atypical occupations do MORE housework; Men in gender atypical occupations do LESS housework •Many (many, many) studies examining howwage/education/occupation differences in couples impacts household division of labor •Nascent literature on same-sex couples show entirely different patterns

Concentration of poverty in neighborhoods...

•The number of neighborhoods (census tracts) with >30% poverty doubled 1980-2010 •Increase insuburban poverty •Poor Americans have become relatively more concentrated since 2000 •From 2000 to 2018, number of (non-Hispanic) white poor households living in high poverty neighborhoods doubled; Black poor + 20%, Hispanic poor +38% •Black poor households >3X more likely to live in high povertyneighborhoods than White poor household.(Source EIG)


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