Using financial incentives to encourage welfare recipients to become economically self-sufficient

Public welfare ; Poverty ; Employment (Economic theory)

The Limits to Wage Growth: Measuring the Growth Rate of Wages For Recent Welfare Leavers

We study the rate of wage growth among welfare leavers in the Self Sufficiency Program (SSP), an experimental earnings subsidy offered to long-term welfare recipients in Canada. Single parents who started working in response to the SSP incentive are younger, less educated, and have more young children than those who would have been working regardless of the program. They also earn relatively low wages in their first few months of work: typically within $1 of the minimum wage. Despite these differences, their rate of wage growth is similar to other welfare leavers. We estimate that people who were induced to work by SSP experienced real wage growth of about 2.5 - 3 percent per year - a rate consistent with conventional measures of the return to experience for similar workers.

Do Financial Incentives Encourage Welfare Recipients to Work? Evidence from a Randomized Evaluation of the Self-Sufficiency Project

This paper reports on a randomized evaluation of an earnings subsidy offered to long-term welfare recipients in Canada. The program -- known as the Self-Sufficiency Project (SSP) -- provides a supplement equal to one-half of the difference between a target earnings level and a participant's actual earnings. The SSP supplement is similar to a negative income tax with two important differences: (1) eligibility is limited to long-term welfare recipients who find a full-time job; and (2) the payment depends on individual earnings rather than family income. Our evaluation is based on a classical randomized design: one half of a group of single parents who had been on welfare for over a year were eligible to receive the SSP supplement, while the other half were assigned to a control group. Results for an early cohort of SSP participants and controls suggest that the financial incentives of the Self-Sufficiency Program increase labor market attachment and reduce welfare participation.

Have Welfare-To-Work Programs Improved Over Time In Putting Welfare Recipients To Work?

Data from 76 experimental welfare-to-work programs conducted in the United States between 1983 and 1998 are used to investigate whether the impacts of such programs on employment had been improving over time and whether specific program features influencing such changes can be identified. Over the period, an increasing percentage of control group members received services similar to those offered to program group members. As a result, differential participation in program service activities between program and control group members decreased steadily over time. This reduction in the net receipt of program services tended to reduce the impact of these programs on employment. However, the negative influence of the reduced incremental services was offset by other factors that resulted in program impacts remaining essentially constant from 1983 to 1998. Suggestions are made for possibly improving program impacts in future experiments.Welfare Programs; Program Evaluation; Employment Behavior of Low-Income Families; Meta Analysis

Quantifying evolutionary constraints on B cell affinity maturation

The antibody repertoire of each individual is continuously updated by the evolutionary process of B cell receptor mutation and selection. It has recently become possible to gain detailed information concerning this process through high-throughput sequencing. Here, we develop modern statistical molecular evolution methods for the analysis of B cell sequence data, and then apply them to a very deep short-read data set of B cell receptors. We find that the substitution process is conserved across individuals but varies significantly across gene segments. We investigate selection on B cell receptors using a novel method that side-steps the difficulties encountered by previous work in differentiating between selection and motif-driven mutation; this is done through stochastic mapping and empirical Bayes estimators that compare the evolution of in-frame and out-of-frame rearrangements. We use this new method to derive a per-residue map of selection, which provides a more nuanced view of the constraints on framework and variable regions.Comment: Previously entitled "Substitution and site-specific selection driving B cell affinity maturation is consistent across individuals

What You Do in High School Matters: The Effects of High School GPA on Educational Attainment and Labor Market Earnings in Adulthood

Using abstracted grades and other data from Add Health, we investigate the effects of cumulative high school GPA on educational attainment and labor market earnings among a sample of young adults (ages 24-34). We estimate several models with an extensive list of control variables and high school fixed effects. Results consistently show that high school GPA is a positive and statistically significant predictor of educational attainment and earnings in adulthood. Moreover, the effects are large and economically important for each gender. Interesting and somewhat unexpected findings emerge for race. Various sensitivity tests support the stability of the core findings.High school grades; Educational attainment; Earnings; Panel data

Genome-Wide Association with Select Biomarker Traits in the Framingham Heart Study

BACKGROUND: Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS: We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. RESULTS: With GEE, 58 SNPs had p < 10-6: the top SNPs were rs2494250 (p = 1.00*10-14) and rs4128725 (p = 3.68*10-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10-8) and rs2808629 (p = 3.19*10-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10-8, and rs2494250, p = 3.55*10-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at . CONCLUSION: The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC25195); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1); National Institutes of Health (HL064753, HL076784, AG028321, HL71039, 2 K24HL04334, 1K23 HL083102); Doris Duke Charitable Foundation; American Diabetes Association Career Developement Award; National Center for Research Resources (GCRC M01-RR01066); US Department of Agriculture Agricultural Research Service (58-1950-001, 58-1950-401); National Institute of Aging (AG14759

Using Administrative Data to Explore the Effect of Survey Nonresponse in the UK Employment Retention and Advancement Demonstration

Background: Even a well-designed randomized control trial (RCT) study can produce ambiguous results. This paper highlights a case in which full-sample results from a large-scale RCT in the United Kingdom (UK) differ from results for a sub-sample of survey respondents. Objectives: Our objective is to ascertain the source of the discrepancy in inferences across data sources and, in doing so, to highlight important threats to the reliability of the causal conclusions derived from even the strongest research designs. Research design: The study analyzes administrative data to shed light on the source of the differences between the estimates. We explore the extent to which heterogeneous treatment impacts and survey non-response might explain these differences. We suggest checks which assess the external validity of survey measured impacts, which in turn provides an opportunity to test the effectiveness of different weighting schemes to remove bias. The Subjects included 6,787 individuals who participated in a large-scale social policy experiment. Results: Our results were not definitive but suggest non-response bias is the main source of the inconsistent findings. Conclusions. The results caution against overconfidence in drawing conclusions from RCTs and highlight the need for great care to be taken in data collection and analysis. Particularly, given the modest size of impacts expected in most RCTs, small discrepancies in data sources can alter the results. Survey data remain important as a source of information on outcomes not recorded in administrative data. However, linking survey and administrative data is strongly recommended whenever possible