A Quantity-Driven Theory of Term Premia and Exchange Rates -- by Robin Greenwood, Samuel G. Hanson, Jeremy C. Stein, Adi Sunderam
We develop a model in which specialized bond investors must absorb shocks to the supply and demand for long-term bonds in two currencies. Since long-term bonds and foreign exchange are both exposed to unexpected movements in short-term interest rates, a shift in the supply of long-term bonds in one currency influences the foreign exchange rate between the two currencies, as well as bond term premia in both currencies. Our model matches several important empirical patterns, including the co-movement between exchange rates and term premia, as well as the finding that central banks' quantitative easing policies impact exchange rates. An extension of our model sheds light on the persistent deviations from covered interest rate parity that have emerged since 2008.
The paper examines changes in labor regulation between 1898 and 1940 in the context of issues related to rule of law in two areas. 1) Many see the 1905 Lochner Supreme Court decision on men’s hours laws as the beginning of 30 years in which labor regulation was stymied by the doctrine of “freedom of contract.” Seeing close votes and substantial turnover of judges on the Supreme Court, the de facto situation was more complex as some states maintained their laws or passed new ones. 2) Labor disputes led to some of the greatest threats to rule of law. To limit descents into violence, states passed arbitration laws, pro-union laws, and anti-union laws. Uncertainty about the rules led to a sharp rise in strikes and violence after World War I and again when Congress and the states sought to establish the rules for collective bargaining between 1932 and 1937. A panel analysis of the impact of state laws in bituminous coal mining from 1902 to 1941 shows that the arbitration and pro-union laws were associated with less violence during periods of uncertainty. During several periods state pro-union laws were associated with more strikes and state anti-union laws with fewer strikes.
Measuring the labor market at the onset of the COVID-19 crisis -- by Alexander W. Bartik, Marianne Bertrand, Feng Lin, Jesse Rothstein, Matt Unrath
We use traditional and non-traditional data to measure the collapse and partial recovery of the U.S. labor market from March to early July, contrast this downturn to previous recessions, and provide preliminary evidence on the effects of the policy response. For hourly workers at both small and large businesses, nearly all of the decline in employment occurred between March 14 and 28. It was driven by low-wage services, particularly the retail and leisure and hospitality sectors. A large share of the job losses in small businesses reflected firms that closed entirely, though many subsequently reopened. Firms that were already unhealthy were more likely to close and less likely to reopen, and disadvantaged workers were more likely to be laid off and less likely to return. Most laid off workers expected to be recalled, and this was predictive of rehiring. Shelter-in-place orders drove only a small share of job losses. Last, states that received more small business loans from the Paycheck Protection Program and states with more generous unemployment insurance benefits had milder declines and faster recoveries. We find no evidence that high UI replacement rates drove job losses or slowed rehiring.
Collaborating During Coronavirus: The Impact of COVID-19 on the Nature of Work -- by Evan DeFilippis, Stephen Michael Impink, Madison Singell, Jeffrey T. Polzer, Raffaella Sadun
We explore the impact of COVID-19 on employee's digital communication patterns through an event study of lockdowns in 16 large metropolitan areas in North America, Europe and the Middle East. Using de- identified, aggregated meeting and email meta-data from 3,143,270 users, we find, compared to pre- pandemic levels, increases in the number of meetings per person (+12.9 percent) and the number of attendees per meeting (+13.5 percent), but decreases in the average length of meetings (-20.1 percent). Collectively, the net effect is that people spent less time in meetings per day (-11.5 percent) in the post- lockdown period. We also find significant and durable increases in length of the average workday (+8.2 percent, or +48.5 minutes), along with short-term increases in email activity. These findings provide insight from a novel dataset into how the nature of work has changed for a large sample of knowledge workers. We discuss these changes in light of the ongoing challenges faced by organizations and workers struggling to adapt and perform in the face of a global pandemic.
Twenty Year Economic Impacts of Deworming -- by Joan Hamory ⓡ, Edward Miguel ⓡ, Michael W. Walker ⓡ, Michael Kremer ⓡ, Sarah J. Baird
This study exploits a randomized school health intervention that provided deworming treatment to Kenyan children and utilizes longitudinal data to estimate impacts on economic outcomes up to 20 years later. The effective respondent tracking rate was 84%. Individuals who received 2 to 3 additional years of childhood deworming experience an increase of 14% in consumption expenditure, 13% in hourly earnings, 9% in non-agricultural work hours, and are 9% more likely to live in urban areas. Most effects are concentrated among males and older individuals. Given deworming's low cost, a conservative annualized social internal rate of return estimate is 37%.
We develop a tractable dynamic model of credit markets in which lending standards and the quality of potential borrowers are endogenous. Competitive banks privately choose their lending standards: whether to pay a cost to screen out some unprofitable borrowers. Lending standards have negative externalities and are dynamic strategic complements: tighter screening worsens the future pool of borrowers for all banks and increases their incentives to screen in the future. Lending standards can amplify and prolong temporary downturns, affecting lending volume, credit spreads, and default rates. We characterize constrained-optimal policy which can generally be implemented as a government loan insurance program. When markets recover, they may do so only slowly, a phenomenon we call “slow thawing.” Finally, we show that limits on lending such as from capital constraints naturally incentivize tight lending standards, further amplifying shocks to credit markets.
At What Level Should One Cluster Standard Errors in Paired Experiments, and in Stratified Experiments with Small Strata? -- by Clément de Chaisemartin, Jaime Ramirez-Cuellar
In paired experiments, units are matched into pairs, and one unit of each pair is randomly assigned to treatment. To estimate the treatment effect, researchers often regress their outcome on a treatment indicator and pair fixed effects, clustering standard errors at the unit-of-randomization level. We show that the variance estimator in this regression may be severely downward biased: under constant treatment effect, its expectation equals 1/2 of the true variance. Instead, we show that researchers should cluster their standard errors at the pair level. Using simulations, we show that those results extend to stratified experiments with few units per strata.
Nursing homes and other long term-care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes---and the crucial role these connections serve in spreading a highly contagious respiratory infection---is currently unknown given the lack of centralized data on cross-facility nursing home employment. In this paper, we perform the first large-scale analysis of nursing home connections via shared staff using device-level geolocation data from 30 million smartphones, and find that 7 percent of smartphones appearing in a nursing home also appeared in at least one other facility---even after visitor restrictions were imposed. We construct network measures of nursing home connectedness and estimate that nursing homes have, on average, connections with 15 other facilities. Controlling for demographic and other factors, a home's staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Results suggest that eliminating staff linkages between nursing homes could reduce COVID-19 infections in nursing homes by 44 percent.