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Previous estimates indicate that COVID-19 led to a large drop in the number of operating businesses operating early in the pandemic, but surprisingly little is known on whether these shutdowns turned into permanent closures and whether small businesses were disproportionately hit. This paper provides the first analysis of permanent business closures using confidential administrative firm-level panel data covering the universe of businesses filing sales taxes from the California Department of Tax and Fee Administration. We find large increases in closure rates in the first two quarters of 2020, but a strong reversal of this trend in the third quarter of 2020. The increase in closures rates in the first two quarters of the pandemic was substantially larger for small businesses than large businesses, but the rebound in the third quarter was also larger. The disproportionate closing of small businesses led to a sharp concentration of market share among larger businesses as indicated by the Herfindahl-Hirschman Index with only a partial reversal after the initial increase. The findings highlight the fragility of small businesses during a large adverse shock and the consequences for the competitiveness of markets.

One frequently cited yet understudied channel through which funding levels impact college students is course availability--colleges are often forced to respond to budgetary pressure by reducing course offerings. We provide the first causal evidence on this mechanism at a community college, using administrative course registration data and a novel research design that exploits discontinuities in course admissions created by waitlists. Community colleges enroll about half of U.S. undergraduates and over half of minority students in public colleges. The impacts of course availability in this setting may be especially salient relative to four-year colleges due to open admissions policies, binding class size constraints, and a heavy reliance on state funding. Across a range of bandwidths, we find that students stuck on a waitlist and shut out of a course section were 22-28 percent more likely to take zero courses that term relative to a baseline of about 10 percent. Shutouts also increased transfer rates to nearby, but potentially less-desirable two-year colleges. These results offer some evidence that course availability can disrupt community college students' educational trajectories.

In response to the COVID-19 epidemic, many education systems have relied on distance learning and educational technologies to an unprecedented degree. However, rigorous empirical research on the impacts on learning under these conditions is still scarce. We present the first large-scale, quantitative evidence detailing how school closures affected education in China. The data set includes households and teachers of 4,360 rural and urban primary school students. We find that although the majority of students engaged in distance education, many households encountered difficulties including barriers to learning (such as access to appropriate digital devices and study spaces), curricular delays, and costs to parents equivalent to between 3.5 and 6 months of income. We also find significant disparities across rural and urban households.

The previous expansion of EdTech as a substitute for traditional learning around the world, the recent full-scale substitution due to COVID-19, and potential future shifts to blended approaches suggest that it is imperative to understand input substitutability between in-person and online learning. We explore input substitutability in education by employing a novel randomized controlled trial that varies dosage of computer-assisted learning (CAL) as a substitute for traditional learning through homework. Moving from zero to a low level of CAL, we find positive substitutability of CAL for traditional learning. Moving from a lower to a higher level of CAL, substitutability changes and is either neutral or even negative. The estimates suggest that a blended approach of CAL and traditional learning is optimal. The findings have direct implications for the rapidly expanding use of educational technology worldwide prior to, during, and after the pandemic.

Graduate student teaching assistants from underrepresented groups may provide salient role models and enhanced instruction to minority students in STEM fields. We explore minority student-TA interactions in an important course in the sciences and STEM - introductory chemistry labs - at a large public university. The uncommon assignment method of students to TA instructors in these chemistry labs overcomes selection problems, and the small and active learning classroom setting with required attendance provides frequent interactions with the TA. We find evidence that underrepresented minority students are less likely to drop courses and are more likely to pass courses when assigned to minority TAs, but we do not find evidence of effects for grades and medium-term outcomes. The effects for the first-order outcomes are large with a decrease in the drop rate by 5.5 percentage points on a base of 6 percent, and an increase in the pass rate of 4.8 percentage points on a base of 93.6 percent. The findings are similar when we focus on Latinx student - Latinx TA interactions. The findings are robust to first-time vs. multiple enrollments in labs, specifications with different levels of fixed effects, limited choice of TA race, limited information of TAs, and low registration priority students. The findings have implications for debates over increasing diversity among PhD students in STEM fields because of spillovers to minority undergraduates.

Seeking ways to encourage broad compliance with health guidelines during the pandemic, especially among youth, we test two hypotheses pertaining to the optimal design of instructional interventions for improving COVID-19-related knowledge, attitudes, and behaviors. We randomly assigned 8376 lower-middle income youth in urban India to three treatments: a concentrated and targeted fact-based, instructional intervention; a longer instructional intervention that provided the same facts along with underlying scientific concepts; and a control. Relative to existing efforts, we find that both instructional interventions increased COVID-19-related knowledge immediately after intervention. Relative to the shorter fact-based intervention, the longer intervention resulted in sustained improvements in knowledge, attitudes, and self-reported behavior. Instead of reducing attention and comprehension by youth, the longer scientific based treatment appears to have increased understanding and retention of the material. The findings are instrumental to understanding the design of instruction and communication in affecting compliance during this and future pandemics.

Social-distancing restrictions and health- and economic-driven demand shifts from COVID-19 are expected to shutter many small businesses and entrepreneurial ventures, but there is very little early evidence on impacts. This paper provides the first analysis of impacts of the pandemic on the number of active small businesses in the United States using nationally representative data from the April 2020 Current Population Survey-the first month fully capturing early effects. The number of active business owners in the United States plummeted by 3.3 million or 22% over the crucial 2-month window from February to April 2020. The drop in active business owners was the largest on record, and losses to business activity were felt across nearly all industries. African-American businesses were hit especially hard experiencing a 41% drop in business activity. Latinx business owner activity fell by 32%, and Asian business owner activity dropped by 26%. Simulations indicate that industry compositions partly placed these groups at a higher risk of business activity losses. Immigrant business owners experienced substantial losses in business activity of 36%. Female business owners were also disproportionately affected (25% drop in business activity). Continuing the analysis in May and June, the number of active business owners remained low-down by 15% and 8%, respectively. The continued losses in May and June, and partial rebounds from April were felt across all demographic groups and most industries. These findings of early-stage losses to small business activity have important implications for policy, income losses, and future economic inequality.

Social-distancing restrictions and health- and economic-driven demand shifts from COVID-19 are expected to shutter many small businesses and entrepreneurial ventures, but there is very little early evidence on impacts. This paper provides the first analysis of impacts of the pandemic on the number of active small businesses in the United States using nationally representative data from the April 2020 Current Population Survey-the first month fully capturing early effects. The number of active business owners in the United States plummeted by 3.3 million or 22% over the crucial 2-month window from February to April 2020. The drop in active business owners was the largest on record, and losses to business activity were felt across nearly all industries. African-American businesses were hit especially hard experiencing a 41% drop in business activity. Latinx business owner activity fell by 32%, and Asian business owner activity dropped by 26%. Simulations indicate that industry compositions partly placed these groups at a higher risk of business activity losses. Immigrant business owners experienced substantial losses in business activity of 36%. Female business owners were also disproportionately affected (25% drop in business activity). Continuing the analysis in May and June, the number of active business owners remained low-down by 15% and 8%, respectively. The continued losses in May and June, and partial rebounds from April were felt across all demographic groups and most industries. These findings of early-stage losses to small business activity have important implications for policy, income losses, and future economic inequality.

The field of entrepreneurship is growing rapidly and expanding into new areas. This article presents a new compilation of administrative panel data on the universe of business start-ups in the United States, which will be useful for future research in entrepreneurship. To create the US start-up panel data set, the authors link the universe of non-employer firms to the universe of employer firms in the Longitudinal Business Database (LBD). Start-up cohorts of more than five million new businesses per year, which create roughly three million jobs, can be tracked over time. To illustrate the potential of the new start-up panel data set for future research, the authors provide descriptive statistics for a few examples of research topics using a representative start-up cohort.

This paper provides the first evidence on the earnings, employment and college enrollment effects of computers and acquired skills from a randomized controlled trial providing computers to entering college students. We matched confidential administrative data from California Employment Development Department (EDD)/Unemployment Insurance (UI) system earnings records, the California Community College system, and the National Student Clearinghouse to all study participants for seven years after the random provision of computers. The experiment does not provide evidence that computer skills have short- or medium-run effects on earnings. These null effects are found along both the extensive and intensive margins of earnings (although the estimates are not precise). We also do not find evidence of positive or negative effects on college enrollment. A non-experimental analysis of CPS data reveals large, positive and statistically significant relationships between home computers, and earnings, employment and college enrollment, raising concerns about selection bias in non-experimental studies.

A common finding in the entrepreneurship literature is that business creation increases in recessions. This counter-cyclical pattern is examined by separating business creation into two components: "opportunity" and "necessity" entrepreneurship. Although there is general agreement in the previous literature on the conceptual distinction between these two factors driving entrepreneurship, there are many challenges to creating a definition that is both objective and empirically feasible. We propose an operational definition of opportunity versus necessity entrepreneurship using readily available nationally representative data.We create a distinction between the two types of entrepreneurship based on the entrepreneur's prior work status that is consistent with the standard theoretical economic model of entrepreneurship. Using this definition we document that "opportunity" entrepreneurship is pro-cyclical and "necessity" entrepreneurship is counter-cyclical. We also find that "opportunity" vs. "necessity" entrepreneurship is associated with the creation of more growth-oriented businesses. The operational distinction proposed here may be useful for future research in entrepreneurship.

Concerns over the perceived negative impacts of computers on social development among children are prevalent but largely uninformed by plausibly causal evidence. We provide the first test of this hypothesis using a large-scale randomized control experiment in which more than one thousand children attending grades 6–10 across 15 different schools and 5 school districts in California were randomly given computers to use at home. Children in the treatment group are more likely to report having a social networking site, but also report spending more time communicating with their friends and interacting with their friends in person. There is no evidence that computer ownership displaces participation in after-school activities such as sports teams or clubs or reduces school participation and engagement.

EdTech, which includes computer-assisted learning (CAL), online education, and remote instruction, was expanding rapidly even before the COVID-19 pandemic. Studies of CAL interventions often find positive effects; however, these "CAL programs" often include non-technology-based inputs such as more time spent on learning and additional instructional support by facilitators. In this paper, we discuss the possible channels by which CAL programs affect academic outcomes among schoolchildren. We isolate the technology-based effects of CAL from the total program effects by designing and performing a novel multitreatment field experiment in rural China. For the full sample, we find null effects for both the total CAL program and the technology-based effects of CAL on math test scores. For boys, however, we find a positive and statistically significant effect of the CAL program but do not find evidence of a positive effect for the technology-based effect of CAL. When focusing on grades, we find evidence of positive CAL program effects but find null effects when we isolate the technology-based effects of CAL. Our empirical results suggest that the "Tech" in EdTech may have relatively small additional effects on academic outcomes, yet tech programs can substitute at least to a certain extent for traditional learning. [ABSTRACT FROM AUTHOR]

The widespread closing of businesses in the United States and around the world due to the coronavirus has been unprecedented. Stores, factories, and many other businesses have closed as a [...]

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.

Labor force transitions are empirically examined using CPS data matched across months from 1996-2012 for Hispanics, African-Americans and whites. Transition probabilities are contrasted prior to the Great Recession and afterwards. Estimates indicate that minorities are more likely to be fired as business cycle conditions worsen. Estimates also show that minorities are usually more likely to be hired when business cycle conditions are weak. During the Great Recession, the odds of losing a job increased for minorities although cyclical sensitivity of the transition declined. Odds of becoming re-employed declined dramatically for blacks, by 2-4 percent, while the probability was unchanged for Hispanics.

type="main" xml:id="irel12127-abs-0001"> Employer-provided health insurance may restrict job mobility, resulting in “job lock.” Previous research on job lock finds mixed results using several methodologies. We take a new approach to examine job lock by exploiting the discontinuity created at age 65 through the qualification for Medicare. Using a novel procedure for identifying age in months from matched monthly Current Population Survey data and a relatively unexplored administration measure of job mobility, we compare job mobility among male workers in the months just prior to turning age 65 to job mobility in the months just after turning age 65. We find no evidence that job mobility increases at the age 65 threshold when Medicare eligibility starts. We also do not find evidence that other factors such as retirement, reduction in hours worked, Social Security eligibility, pension eligibility, and sample changes confound the results on job mobility in the month individuals turn 65.

A substantial amount of money is spent on technology by schools, families and policymakers with the hope of improving educational outcomes. This chapter explores the theoretical and empirical literature on the impacts of technology on educational outcomes. The literature focuses on two primary contexts in which technology may be used for educational purposes: i) classroom use in schools, and ii) home use by students. Theoretically, ICT investment and CAI use by schools and the use of computers at home have ambiguous implications for educational achievement: expenditures devoted to technology necessarily offset inputs that may be more or less efficient, and time allocated to using technology may displace traditional classroom instruction and educational activities at home. However, much of the evidence in the schooling literature is based on interventions that provide supplemental funding for technology or additional class time, and thus favor finding positive effects. Nonetheless, studies of ICT and CAI in schools produce mixed evidence with a pattern of null results. Notable exceptions to this pattern occur in studies of developing countries and CAI interventions that target math rather than language. In the context of home use, early studies based on multivariate and instrumental variables approaches tend to find large positive (and in a few cases negative) effects while recent studies based on randomized control experiments tend to find small or null effects. Early research focused on developed countries while more recently several experiments have been conducted in developing countries.

The Kauffman Index: Startup Activity is a novel early indicator of new business creation in the United States, integrating several high-quality sources of timely entrepreneurship information into one composite indicator of startup activity. The Index captures business activity in all industries, and is based on both a nationally representative sample size of more than a half million observations each year and on the universe of all employer businesses in the United States. This allows us to look at both entrepreneurs and the startups they create. Broad-based entrepreneurship in America appears to be slowly crawling its way out of the depths it has been stuck in since 2010. Startup activity rose in 2015, reversing a five-year downward trend in the United States, giving rise to hope for a revival of entrepreneurship. However, the return remains tepid and well below historical trends. A principle driver of this year’s uptick is the growth of male opportunity entrepreneurship, accompanied by the continued strength of immigrant entrepreneurship. Trends in entrepreneurship rates are analyzed for several additional demographic groups.

Boys are doing worse in school than are girls, which has been dubbed "the Boy Crisis." An analysis of the latest data on educational outcomes among boys and girls reveals extensive disparities in grades, reading and writing test scores, and other measurable educational outcomes, and these disparities exist across family resources and race. Focusing on disadvantaged schoolchildren, I then examine whether time investments made by boys and girls related to computer use contribute to the gender gap in academic achievement. Data from several sources indicate that boys are less likely to use computers for schoolwork and are more likely to use computers for playing games, but are less likely to use computers for social networking and email than are girls. Using data from a large field experiment randomly providing free personal computers to schoolchildren for home use, I also test whether these differential patterns of computer use displace homework time and ultimately translate into worse educational outcomes among boys. No evidence is found indicating that personal computers crowd out homework time and effort for disadvantaged boys relative to girls. Home computers also do not have negative effects on educational outcomes such as grades, test scores, courses completed, and tardies for disadvantaged boys relative to girls.

A growing body of research on immigrant entrepreneurship has developed over the past several years. In this chapter we provide an overview of the economics literature with respect to some of the most fundamental immigrant entrepreneurship issues as well as the empirical methods and data used. We review this literature through the lens of estimating the net contribution made by immigrant entrepreneurs to the host economy. Immigration is a very hotly debated topic because of the contrasting concerns over lowering wages for existing workers, increasingly public assistance rolls, security and changing the demographic makeup of host countries, and the need for less- and high-skilled workers, supporting an aging population, insourcing instead of outsourcing labor, and family reunification. Central to the debate is whether immigrants provide a net positive or net negative contribution to host economy. Partly fueled by this debate, an extremely large literature in economics examines the separate impacts of immigrants on various parts of the economy such as the labor market, public assistance, tax system, and educational systems. Since much of the attention of the relevant research has been on the United States, this will be the focus of our discussion.

Theories of market failures and targeting motivate the promotion of entrepreneurship training programs and generate testable predictions regarding heterogeneous treatment effects from such programs. Using a large randomized evaluation in the United States, we find no strong or lasting effects on those most likely to face credit or human capital constraints, or labor market discrimination. We do find a short-run effect on business ownership for those unemployed at baseline, but this dissipates at longer horizons. Treatment effects on the full sample are also short-term and limited in scope: we do not find effects on business sales, earnings, or employees. (JEL I26, J24, J68, L25, L26, M13)

Using a recently released confidential dataset from the National Center for Educational Statistics (NCES), we find some evidence of "white flight" from public schools into private schools partly in response to minority schoolchildren. We also examine whether "white flight" is from all minorities or only from certain minority groups, delineated by race or income. We find that white families are fleeing public schools with large concentrations of poor minority schoolchildren. In addition, the clearest flight appears to occur from poor black schoolchildren. The results for "white flight" from Asians and Hispanics are less clear.