National Policies Affect Poverty Rates in Rich Nations

The labour market alone cannot move struggling families out of poverty. The social welfare programs in a country have a great impact on the level of poverty among minority and native population.York's Knowledge Mobilization Unit provides services and funding for faculty, graduate students, and community organizations seeking to maximize the impact of academic research and expertise on public policy, social programming, and professional practice. It is supported by SSHRC and CIHR grants, and by the Office of the Vice-President Research & Innovation. [email protected] www.researchimpact.c

What can we learn about SARS-CoV-2 prevalence from testing and hospital data?

Measuring the prevalence of active SARS-CoV-2 infections is difficult because tests are conducted on a small and non-random segment of the population. But people admitted to the hospital for non-COVID reasons are tested at very high rates, even though they do not appear to be at elevated risk of infection. This sub-population may provide valuable evidence on prevalence in the general population. We estimate upper and lower bounds on the prevalence of the virus in the general population and the population of non-COVID hospital patients under weak assumptions on who gets tested, using Indiana data on hospital inpatient records linked to SARS-CoV-2 virological tests. The non-COVID hospital population is tested fifty times as often as the general population. By mid-June, we estimate that prevalence was between 0.01 and 4.1 percent in the general population and between 0.6 to 2.6 percent in the non-COVID hospital population. We provide and test conditions under which this non-COVID hospitalization bound is valid for the general population. The combination of clinical testing data and hospital records may contain much more information about the state of the epidemic than has been previously appreciated. The bounds we calculate for Indiana could be constructed at relatively low cost in many other states

Impacts of State Reopening Policy on Human Mobility

This study quantifies the effect of state reopening policies on daily mobility, travel, and mixing behavior during the COVID-19 pandemic. We harness cell device signal data to examine the effects of the timing and pace of reopening plans in different states. We quantify the increase in mobility patterns during the reopening phase by a broad range of cell-device-based metrics. Soon (four days) after reopening, we observe a 6% to 8% mobility increase. In addition, we find that temperature and precipitation are strongly associated with increased mobility across counties. The mobility measures that reflect visits to a greater variety of locations responds the most to reopening policies, while total time in vs. outside the house remains unchanged. The largest increases in mobility occur in states that were late adopters of closure measures, suggesting that closure policies may have represented more of a binding constraint in those states. Together, these four observations provide an assessment of the extent to which people in the U.S. are resuming movement and physical proximity as the COVID-19 pandemic continues

Back to Business and (Re)employing Workers? Labor Market Activity During State COVID-19 Reopenings

We study the effect of state reopening policies on a large set of labor market indicators through May 2020 to: (1) understand the recent increase in employment using longitudinal as well as cross-sectional data, (2) assess the likely trajectory of reemployment going forward, and (3) investigate the strength of job matches that were disrupted by COVID-19. Estimates from event studies and difference-in-difference regressions suggest that some of the recent increases in employment activity, as measured by cellphone data on work-related mobility, internet searches related to employment, and new and continuing unemployment insurance claims, were likely related to state reopenings, often predating actual reopening dates somewhat. We provide suggestive evidence that increases in employment stem from people returning to their prior jobs: reopenings are only weakly related to job postings, and longitudinal CPS data show that large shares of the unemployed-on-layoff and employed-but-absent in April who transitioned to employment in May remain in the same industry or occupation. Longitudinal CPS estimates further show declines in reemployment probabilities with time away from work. Taken together, these estimates suggest that employment relationships are durable in the short run, but raise concerns that employment gains requiring new employment matches may not be as rapid.Weinberg gratefully acknowledges support from UL1 TR002733 and R24 HD058484

Path dependence in energy systems and economic development

Energy systems are subject to strong and long-lived path dependence, owing to technological, infrastructural, institutional and behavioural lock-ins. Yet, with the prospect of providing accessible cheap energy to stimulate economic development and reduce poverty, governments often invest in large engineering projects and subsidy policies. Here, I argue that while these may achieve their objectives, they risk locking their economies onto energy-intensive pathways. Thus, particularly when economies are industrializing, and their energy systems are being transformed and are not yet fully locked-in, policymakers should take care before directing their economies onto energy-intensive pathways that are likely to be detrimental to their long-run prosperity

Three essays on voluntary HIV testing and the HIV epidemic

This dissertation examines voluntary HIV testing in three specific contexts. The first chapter evaluates the effects of written informed consent regulations on HIV testing rates using a difference-in-differences approach to analyze a natural experiment that occurred when New York State weakened its HIV testing written informed consent regulations. The study finds that streamlining the consent process in New York increased HIV testing rates about 1.7 percentage points, which is a large relative increase of approximately 31%. The second chapter uses methods from the econometric literature on partially identified models to estimate HIV prevalence from biometric survey data in which some fraction of respondents opt out of the HIV testing module and are not tested for HIV. The method is applied to biometric survey data collected in four African countries: Kenya, Ethiopia, Lesotho, and Zimbabwe. A key finding is that the estimates of HIV prevalence that are standard in the literature represent an optimistic interpretation of the data. The biometric survey data are consistent with a range of levels of HIV prevalence, and standard estimates typically are much closer to the lower end of this range than they are to the higher end. The third chapter reports reanalyzes data from a field experiment conducted in Malawi (Thornton, 2008). The experiment was intended to evaluate the effect of participation in voluntary counseling and testing (VCT) on condom purchasing. The experiment employed a non-standard design. Subjects were randomly assigned one of 27 differently valued VCT participation incentives that were meant to induce self-selection into treatment and control groups. The design makes it difficult to understand what treatment effects are uncovered by the data. The reanalysis uses statistical tools from the literature on treatment effect heterogeneity to clarify what the incentives experiment reveals about the causal effects of VCT. It also evaluates the strengths and weaknesses of the incentive based design. One interesting result is that VCT participation caused an increase in condom purchasing among the initial people induced to participate in VCT. But expansions of the program to cover more than about 65% of the population actually reduced condom purchasing among the new program entrants

Replication Data for: What Can Instrumental Variables Tell Us About Nonresponse in Household Surveys and Political Polls?

The archive contains the stata code used to produce the results in the paper. To run the code, researchers must download Swiss Electoral Study (Selects) 2011 Online Experiment. These data are not included in the archive. However, they are available from a public data repository called FORSbase. To download the data, users are required to register with FORSbase. Instructions are included in the ReadMe file in this archive

How Has COVID-19 Affected Job Markets Worldwide?

Kosali Simon is a nationally-known health economist. At IU, she is Associate Vice Provost for Health Sciences, and a Herman B. Wells Endowed Professor in the O’Neill School of Public and Environmental Affairs. Coady Wing is an Associate Professor in the O’Neill School of Public and Environmental Affairs. This presentation starts by discussing how COVID-19 has affected job markets worldwide, key questions, methods, and data sources used. I will then focus on the research my colleagues and I have conducted in the last year, paying most attention to the focal paper using Current Population Survey monthly data from the US. In that paper, we make several contributions to understanding the socio-demographic ramifications of the COVID-19 epidemic and policy responses on employment outcomes of subgroups in the U.S., benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanics, younger workers, and those with high school degrees and some college. Between April and May, all the demographic subgroups considered regained some employment. Reemployment in May was broadly proportional to the employment drop that occurred through April, except for Blacks. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Third, we show that the extent to which workers in various demographic groups sort (pre-COVID-19) into occupations and industries can explain a sizeable portion of the gender, race, and ethnic gaps in recent unemployment. However, there remain substantial unexplained differences in employment losses across groups. We also demonstrate the importance of tracking workers who report having a job but are absent from work, in addition to tracking employed and unemployed workers. We conclude with a discussion of policy priorities and future research needs implied by the disparities in labor market losses from the COVID-19 crisis that we identify