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A family’s freedom to control its own destiny is a key indicator of its economic prospects – and vice versa. The Family Self-Sufficiency major index measures the degree to which such factors as incarceration, dependence on government aid, and the capacity for charitable giving are reflected in a family’s overall prosperity, as well as their effect on the larger community.
The level of incarceration in America has exploded in the past few decades with 2.3 million Americans serving time in federal and state prisons. The cost to state governments now exceeds $50 billion per year. However, the direct cost of running the prison system is only the tip of the iceberg when it comes to the total costs to the economy and society.
First, incarceration permanently lowers an individual’s long-term earning potential. A study from the The Pew Charitable Trusts found:
Past incarceration reduced subsequent wages by 11 percent, cut annual employment by nine weeks and reduced yearly earnings by 40 percent.
Second, incarceration may be behind the precipitous decline in male labor force participation. According to Nicholas Eberstadt, The Henry Wendt Chair in Political Economy at the American Enterprise Institute:
Everyone knows that millions of criminal offenders today are behind bars–but few consider that many millions more are in the general population: ex-prisoners, probation cases and convicted felons who never served time. In all, America may now be home to over 20 million persons with a felony conviction in their past, and over 1 in 8 adult men. Men with a criminal history have much worse odds of being or staying in the labor force, regardless of their ethnicity or educational level. The explosive growth of our felon population, unfortunately, helps to explain some of the otherwise puzzling peculiarities of America’s male work crisis.
Third, a recent study estimated that more than 5 million children have had at least one parent in prison at some point in their life. These children have to deal with a number of additional challenges including:
a higher number of other major, potentially traumatic life events—stressors that are most damaging when they are cumulative;more emotional difficulties, low school engagement, and more problems in school, among children ages 6 to 11; and a greater likelihood of problems in school among older youth (12 to 17), as well as less parental monitoring.
Overall, the negative economic and social consequences of incarceration are intergenerational. One important transmission mechanism is that incarceration of one member of the family, by definition, leaves the other member as a single parent—depriving them of the advantages of marriage (see section on marriage). This problem is especially acute among black women who face a skewed male-to-female ratio due to the high incarceration rate among black men.
Another factor in determining family self-sufficiency is reliance on public assistance. Government at all levels (federal, state, and local) employs various welfare programs to mitigate the ill effects of poverty—Medicaid, Temporary Assistance for Needy Families (TANF), and Supplemental Nutrition Assistance Program (SNAP) to name a few. As such, these programs are means-tested so they phase out as one’s income grows. However, all of the various rules and regulations create implicit incentives and disincentives related to work effort and family structure decisions.
For example, the Earned Income Tax Credit (EITC), since it is managed through the personal income tax, is one of the most transparent welfare programs for discerning these incentive effects. The EITC has a defined phase-in (where benefits increase), plateau (where benefits remain constant), and phase-out (where benefits decrease) from which to calculate what economists call the implicit “effective marginal tax rate” (EMTR).
The current EITC can impose an EMTR of 21.1 percent in the phase-out range which presents a significant barrier to work. Put simply: After reaching a certain level of annual pay, it is less advantageous for an individual to increase his income because every additional dollar earned will come with a higher price tag in the form of lower EITC benefits. Therefore, someone in the EITC phase-out loses $0.21 cents for every additional dollar earned.
In one of the most comprehensive EMTR studies to date, University of Chicago economist Casey Mulligan finds that EMTRs for non-elderly heads of household and spouses with median earnings potential have ranged from between 44 and 46 percent. The enactment of the Affordable Care Act (Obamacare) pushes the EMTR to over 50 percent!
The higher Obamacare EMTR stems from the law’s numerous new provisions such as the employer and employee health insurance mandates, health insurance subsidies for individuals on the state health exchanges, and Medicaid expansion.
Yet, there is a wide variation in welfare parameters by state that can amplify or mitigate these EMTRs. A study by economists Mickey Hepner and Robert Reed calculated the Oklahoma–specific EMTRs created by their welfare system and found them to be a major barrier to both work effort, especially for those seeking high-paying work, and marriage. A more recent study in Georgia found the same issues in that state’s welfare system.
In particular, the impact of TANF on marriage has been of serious concern. In fact, the federal welfare reforms of 1996 were, in part, meant to remedy the rise in single-parenthood incentivized by welfare. A new study finds that these reforms were effective at boosting marriage rates among welfare recipients:
The strongest and most consistent effects we find are for the severity, or harshness, of TANF policies on family structure. Those policies appear to reduce the prevalence of single parenthood and to increase the prevalence of mothers partnering with males who are the biological parents of their children. Further, increases in biological partnership from harsh TANF policies occur primarily through marriage. We also find that the combined effects of family-oriented policies (i.e. two-parent rules, family caps, and stepparent rules) have significant negative effects on single parenthood and significant positive effects on biological partnering (primarily through marriage).
Tax policy can also significantly undermine a family’s self-sufficiency, not only by reducing their personal after-tax income, but also by undermining the economy in which the family operates.
According to Dr. David Romer and Dr. Christina Romer (former Chair of the Council of Economic Advisors under President Obama), both highly reputable economics professors at the University of California, Berkeley, who studied federal tax law changes over the last 50 years:
This paper investigates the impact of tax changes on economic activity . . . [T]he behavior of output following these more exogenous changes indicates that tax increases are highly contractionary. The effects are strongly significant, highly robust, and much larger than those obtained using broader measures of tax changes.
Economist Robert Reed’s findings were similar:
I estimate the relationship between taxes and income growth using data from 1970-1999 and the forty-eight continental U.S. states. I find that taxes used to fund general expenditures are associated with significant, negative effects on income growth.
Finally, high tax burdens hurt state economies via the out-migration of private firms, as economists Xavier Giroud and Joshua Rauh found:
In this paper we have estimated economic responses to state-level business taxation by multistate firms on both the extensive and intensive margins. We find evidence consistent with substantial responses of these firms to state tax rates for the relevant tax rules. Corporate entities reduce the number of establishments per state and the number of employees and amount of capital per plant when state tax rates increase. Pass-through entities respond similarly to changes in state-level personal tax rates, although in somewhat smaller magnitude. Our specifications suggest that around half of these responses are due to reallocation of business activity to lower-tax states.
Additionally, government spending is the redistribution of income first extracted by taxes. Yet, the very process of redistribution also comes at a very high economic cost. As noted by prominent Harvard economist Martin Feldstein:
The appropriate size and role of government depends on the deadweight burden caused by incremental transfers of funds from the private sector. The magnitude of that burden depends on the increases in tax rates required to raise incremental revenue and on the deadweight loss that results from higher tax rates… [R]ecent econometric work implies that the deadweight burden caused by incremental taxation (the marginal excess burden) may exceed one dollar per one dollar of revenue raised, making the cost of incremental government spending more than two dollars for each dollar of government spending.
According to the findings of economists Stephen Brown, Kathy Hayes, and Lori Taylor at the state level:
If anything, most public services do not appear to justify the taxes needed to finance them. Any tax savings financed by slower growth in environmental services, health and hospitals, or elementary and secondary education is positively associated with growth in private capital. Similarly, any tax savings financed by slower growth in public safety or education spending is positively associated with growth in private employment . . . [T]his finding would seem to imply that other state and local public capital has been increased to the point of negative returns, perhaps because a growing stock of other public capital is indicative of an increasingly intrusive government.
Finally, economists Taehyun Kim and Quoc H. Nguyen reach similar conclusions:
To summarize, we find strong evidence that supports the hypothesis that government spending crowds out firm investment. We further provide novel and direct evidence that limited mobility of workers is an important channel through which the crowding-out effect can occur.
Charitable giving, an outgrowth of family self-sufficiency, has a number of beneficial effects on individuals and society as a whole. This is due, in large part, to the correlation between charitable giving and religion. In fact, 61 percent of charitable giving is for “religious purposes” and it is an increasing and stable source of funds for charities.
As discussed in the section on religion, people who are the most religious enjoy healthier lives, report less depression, and enjoy overall greater well-being. This also has important public policy implications as discussed in a recent study:
. . . [A] growing body of literature documents that giving to others reduces stress and strengthens the immune system, which results in better health and longer life expectancy. These findings imply that tax subsidies for charitable giving may have positive spillover effects on health.
Thus, charitable giving is a win-win for both the receiver and giver.
The pattern of charitable giving also illustrates why increasing overall family prosperity is so important. Of the $194 billion given in 2013, 71 percent ($138 billion) came from those earning over $100,000. This is why the FPI examines the charitable giving of all taxpayers and those earning over $100,000.
Unfortunately, there has been a noticeable downswing in charitable contributions, especially after the “Great Recession.” A recent study found that this phenomenon may not be simply a matter of lower incomes, but rather, suggests “broader shifts in attitudes towards giving or increased uncertainty at work.” Given the importance of religion to charitable giving, perhaps the “shift in attitudes” relates to the ongoing decline in religious attendance. Clearly, more research is needed on this vital measure of family self-sufficiency.
As shown in Chart 28 and Table 4:
As shown in Chart 29, state prisoners (as a percent of population) declined nationally by 6 percent to 0.42 percent in 2015 from 0.44 percent in 2000. In 2015, Louisiana had the highest percentage of state prisoners at 0.78 percent, while Massachusetts had the lowest at 0.15 percent—a difference of 433 percent.
Overall, for the state prisoners sub-index, Massachusetts had the top score (8.78), followed by New Jersey (7.74), Utah (7.64), Vermont (7.17), and Maine (7.17). Oklahoma had the lowest score (0.94), followed by Louisiana (1.35), Alaska (1.75), Delaware (1.87), and Arkansas (2.34).
Per Capita Medicaid Spending
As shown in Chart 30, Medicaid spending (per person) increased nationally by 138 percent to $1,685 in 2015 from $708 in 2000. In 2015, New York had the highest level of Medicaid spending at $3,044, while Utah had the lowest at $746—a difference of 308 percent.
Overall, for the Medicaid spending sub-index, Utah had the top score (7.61), followed by Wyoming (7.24), South Dakota (7.22), Georgia (7.11), and Florida (6.91). New York had the lowest score (1.31), followed by New Mexico (1.85), Vermont (2.00), Rhode Island (2.44), and Kentucky (2.52).
Charts 31, 32, 33, and 34 show the variance in welfare enrollment and spending—examining both the Earned Income Tax Credit (EITC) and the Supplemental Nutrition Assistance Program (SNAP)—nationally and in the 50 states from 2000 to 2014 for EITC and 2000 to 2015 for SNAP.
As shown in Chart 31, the EITC rate (as a percent of taxpayers) increased nationally by 29 percent to 19.2 percent in 2014 from 14.8 percent in 2000. In 2014, Mississippi had the highest EITC rate at 32.1 percent, while North Dakota had the lowest at 11.9 percent—a difference of 170 percent.
As shown in Chart 32, the amount of EITC spending (per EITC recipient) increased nationally by 45 percent to $2,399 in 2014 from $1,659 in 2000. In 2014, Mississippi had the highest spending on EITC at $2,823. while Vermont had the lowest at $1,893—a difference of 49 percent.
As shown in Chart 33, the SNAP rate (as a percent of population) increased nationally by 115 percent to 14.2 percent in 2015 from 6.1 percent in 2000. In 2015, New Mexico had the highest SNAP rate at 21.7 percent, while Wyoming had the lowest at 5.6 percent—a difference of 291 percent.
As shown in Chart 34, the amount of SNAP spending (per person) increased nationally by 61 percent to $127.57 in 2015 from $72.62 in 2000. In 2015, Hawaii had the highest SNAP spending at $222.99, while New Hampshire had the lowest at $103.87—a difference of 115 percent.
Overall, for the welfare sub-index, New Hampshire had the best score (7.60) followed by North Dakota (7.46), Wyoming (7.07), Utah (6.60), and Minnesota (6.48). Mississippi had the lowest score (1.83), followed by Georgia (2.82), Louisiana (2.94), Alabama (3.10), and New Mexico (3.11).
Note: EITC rate, EITC spending, SNAP rate, and SNAP spending were weighted equally in the welfare sub-index.
Charts 35 and 36 show the variance in the burden of government—examining both the state and local tax burden and spending—nationally and in the 50 states from Fiscal Years 2000 to 2014.
As shown in Chart 35, the state and local tax burden (as a percent of private sector personal income) increased nationally by 4 percent to 14.6 percent in 2014 from 13.9 percent in 2000. In 2014, North Dakota had the highest tax burden at 22.9 percent, while New Hampshire had the lowest at 10.3 percent—a difference of 121 percent.
As shown in Chart 36, state and local tax expenditures (as a percent of private sector personal income) increased nationally by 15 percent to 32 percent in 2014 from 27.9 percent in 2000. In 2014, Alaska had the highest expenditures at 67.5 percent, while New Hampshire had the lowest at 21.3 percent—a difference of 217 percent.
Overall, for the government burden sub-index, New Hampshire had the top score (7.11) followed by Oklahoma (6.63), South Dakota (6.51), Florida (6.50), and Texas (6.44). New Mexico had the lowest score (2.75), followed by New York (2.75), Hawaii (2.78), North Dakota (2.96), and West Virginia (2.98).
Notes: Tax burdens and expenditures were weighted equally in the government burden sub-index.
Alaska annually distributes dividends from the Permanent Fund created from oil and gas revenue. These funds are treated as a reduction in the tax burden.
Charts 37, 38, 39, and 40 show the variance in charitable giving—including the rate and level of charitable giving for all taxpayers and taxpayers earning over $100,000—nationally and in the 50 states from 2000 to 2014.
As shown in Chart 37, the charity rate (as a percent of all taxpayers) declined nationally by 16 percent to 24.6 percent in 2014 from 29.2 percent in 2000. In 2014, Maryland had the highest charity rate at 38.2 percent, while West Virginia had the lowest at 12.3 percent—a difference of 210 percent.
As shown in Chart 38, charitable contributions (per taxpayer) increased nationally by 60 percent to $5,793 in 2014 from $3,618 in 2000. In 2014, Wyoming had the highest charity giving at $16,644, while Rhode Island had the lowest at $3,344—a difference of 398 percent.
As shown in Chart 39, the charity rate for taxpayers earning more than $100,000 (as a percent of all taxpayers earning more than $100,000) declined nationally by 16 percent to 72.9 percent in 2014 from 87 percent in 2000. In 2014, Maryland had the highest charity rate at 84.2 percent, while North Dakota had the lowest at 37.6 percent—a difference of 124 percent.
As shown in Chart 40, charitable contributions for taxpayers earning more than $100,000 (per taxpayer earning more than $100,000) increased nationally by 9 percent to $9,028 in 2014 from $8,324 in 2000. In 2014, Wyoming had the highest charity giving at $30,291, while Rhode Island had the lowest at $5,135—a difference of 490 percent.
Overall, for the charity sub-index, Utah had the top score (8.77), followed by Georgia (7.62), Washington (7.31), New York (7.08), and Oklahoma (6.90). West Virginia had the lowest score (2.28), followed by Maine (2.33), Alaska (2.83), Hawaii (3.33), and New Hampshire (3.41).
Note: In the charity sub-index, the state charity rates for all taxpayers and for taxpayers earning over $100,000 were weighted 30 percent and 20 percent, respectively. Similarly, state charitable contributions per taxpayer and per taxpayer earning over $100,000 were weighted 30 percent and 20 percent, respectively.
Wyoming’s charity contributions were very high relative to the other states. The IRS confirmed, via email correspondence, that there are no errors in the reporting of Wyoming’s charity data.
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 Pettit, Becky and Western, Bruce, “Collateral Costs: Incarceration’s Effect on Economic Mobility,” The Pew Charitable Trusts, 2010. http://www.pewtrusts.org/~/media/legacy/uploadedfiles/pcs_assets/2010/collateralcosts1pdf.pdf
 Cooper, P. Mae and Murphey, David, “Parents Behind Bars: What Happens to Their Children?,” Child Trends, October 2015. http://www.childtrends.org/wp-content/uploads/2015/10/2015-42ParentsBehindBars.pdf
 Hall, Arthur P. and Moody, J. Scott, “Growth of the Earned Income Tax Credit,” Tax Foundation, Special Report, No. 53, September 1995. http://taxfoundation.org/sites/taxfoundation.org/files/docs/7b76310a7234556cb06bdc66974385bb.pdf
 Many states piggyback on the federal EITC which increases the MTR. For example, see: Moody, J. Scott, “The Earned Income Tax Credit Does Not Help Working Families,” Illinois Policy Institute, March 4, 2014. https://www.illinoispolicy.org/policy-points/the-earned-income-tax-credit-does-not-help-working-families/
 Mulligan, Casey B., “Average Marginal Labor Income Tax Rates Under Affordable Care Act,” National Bureau of Economic Research, Working Paper No. 19365, August 2013. http://home.uchicago.edu/~cbm4/MulliganMTRACA.pdf
 Hepner, Mickey and Reed, W. Robert, “The Effect of Welfare on Work and Marriage: A View from the States,” Cato Journal, Vol. 24, No. 3, Fall 2004. http://www.econ.canterbury.ac.nz/personal_pages/bob_reed/Papers/Work_Marriage_Incentives_Paper.pdf The authors also provide an Excel spreadsheet to calculate your own MTRs by changing various program parameters. It can be found at
 Randolph, Erik,, “Disincentives for Work and Marriage in Georgia’s Welfare System,” Georgia Center for Opportunity, September 2016. http://georgiaopportunity.org/wp-content/uploads/2016/09/GCO1611_White_Paper_Online.pdf
 Moffitt, Robert A., Phelan, Brian J., and Winkler, Anne E., “Welfare Rules, Incentives, and Family Structure,” National Bureau of Economic Research, Working Paper 21257, June 2015. http://www.nber.org/papers/w21257
 Romer, Christina D. and Romer, David H., “The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks,” American Economic Review 100, June 2010, pp. 763-801. http://eml.berkeley.edu/~dromer/papers/RomerandRomerAERJune2010.pdf
 Reed, W. Robert, “The Robust Relationship between Taxes and U.S. State Income Growth,” National Tax Journal, Vol. LXI, No. 1, March 2008. http://www.ntanet.org/NTJ/61/1/ntj-v61n01p57-80-robust-relationship-between-taxes.pdf
 Giroud, Xavier and Rauh, Joshua, “State Taxation and the Reallocation of Business Activity: Evidence from Establishment-Level Data,” NBER Working Paper 21534, September 2015. http://www.mit.edu/~xgiroud/Taxes.pdf
 Feldstein, Martin, “How Big Should Government Be?” National Tax Journal, Vol. 50, No. 2 (June 1997), pp. 197-213. https://www.ntanet.org/NTJ/50/2/ntj-v50n02p197-213-how-big-should-government.pdf?v=%CE%B1&r=15017736809172388
 Brown, Stephen, P.A., Hayes, Kathy J., and Taylor, Lori L. “State and Local Policy, Factor Markets, and Regional Growth,” The Review of Regional Studies, Vol. 33, No. 1, 2003, pp. 40–60. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.493.6001&rep=rep1&type=pdf
 Kim, Taehyun and Nguyen, Quoc H., “The Effect of Public Spending on Private Investment: Evidence from Census Shocks,” Working Paper, August 27, 2015. http://publish.illinois.edu/taehyunkim/files/2015/09/TK_fiscalPolicy.pdf
 List, John A., “The Market for Charitable Giving,” Journal of Economic Perspectives, Vol. 25, No. 2, Spring 2011, pp. 157-180. http://home.uchicago.edu/~jlist/papers/The%20Market%20for%20Charitable%20Giving.pdf
 Yoruk, Baris K., “Does Giving to Charity Lead to Better Health? Evidence from Tax Subsidies for Charitable Giving,” Journal of Economic Psychology, Vol. 45, December 2014, pp. 71-83. http://www.albany.edu/economics/research/workingp/2013/yoruk1.pdf
 However, tax subsidies may not yield the best outcome for charities. To the extent that higher marginal tax rates lead to higher government spending and/or slower economic growth, this impact results in a “crowd-out” of charitable activity. For more information, see: Gruber, Jonathan and Hungerman, Daniel M., “Faith-based Charity and Crowd-Out During the Great Depression,” Journal of Public Economics, No. 91, 2007, pp. 1043-1069. http://economics.mit.edu/files/6424
 Meer, Jonathan, Miller, David, and Wulfsberg, Elisa, “The Great Recession and Charitable Giving,” November, 2016. http://people.tamu.edu/~jmeer/Meer_Miller_Wulfsberg_Great_Recession_and_Charitable_Giving_161120.pdf
 Regional Data, U.S. Department of Commerce: Bureau of Economic Analysis http://www.bea.gov/itable/iTable.cfm?ReqID=70&step=1#reqid=70&step=1&isuri=1
 Revenue Service, Statistics of Income, SOI Tax Stats – Historic Table 2. https://www.irs.gov/uac/SOI-Tax-Stats-Historic-Table-2
 U.S. Department of Agriculture: Food and Nutrition Service http://www.fns.usda.gov/pd/supplemental-nutrition-assistance-program-snap
 Internal Revenue Service, Statistics of Income, SOI Tax Stats – Historic Table 2. https://www.irs.gov/uac/SOI-Tax-Stats-Historic-Table-2