Research Database

In this paper, we ask how to best allocate a given time-varying supply of vaccines across individuals of different ages during the second phase of the Covid-19 pandemic . Building on our previous heterogeneous household model of optimal economic mitigation and redistribution (Glover et al., 2021), we contrast the actual vaccine deployment path, which prioritized older, retired individuals, with one that first vaccinates younger workers. Vaccinating the old first saves more lives but slows the economic recovery, relative to inoculating the young first. Vaccines deliver large welfare benefits in both scenarios (relative to a world without vaccines), but the old-first policy is optimal under a utilitarian social welfare function. The welfare gains from having vaccinated the old first are especially significant once the economy is hit by a more infectious Delta variant in the summer of 2021.

We investigate the credibility of central bank research by searching for traces of researcher bias, which is a tendency to use undisclosed analytical procedures that raise measured levels of statistical significance (stars) in artificial ways. To conduct our search, we compile a new dataset and borrow 2 bias-detection methods from the literature: the p-curve and z-curve. The results are mixed. The p-curve shows no traces of researcher bias but has a high propensity to produce false negatives. The z-curve shows some traces of researcher bias but requires strong assumptions. We examine those assumptions and challenge their merit. At this point, all that is clear is that central banks produce results with patterns different from those in top economic journals, there being less bunching around the 5 per cent threshold of statistical significance.

We develop a theory of sweat equity—the value of business owners' time and expenses to build customer bases, client lists, and other intangible assets. We discipline the theory using data from U.S. national accounts, business censuses, and brokered sales to estimate a value for sweat equity in the private business sector equal to 1.2 times U.S. GDP, which is about the same magnitude as the value of fixed assets in use in these businesses. For a typical owner, 26 percent of the sweat equity is transferable through inheritance or sale. The equity values are positively correlated with business incomes and standard measures of markups based on accounting data, but not with owners' financial assets or standard measures of business total factor productivity. We use our theory to show that abstracting from sweat activity leads to a significant understatement of the impacts of lowering business income tax rates on private business activity for both the extensive and intensive margins. Despite finding larger responses, our model's implied tax elasticities of establishments and owner hours are in line with empirical estimates in the public finance literature. Allowing for financial constraints and superstar firms does not overturn our main findings.

The prevailing neo-Wicksellian view holds that the central bank's objective is to track the natural rate of interest (r *), which itself is largely exogenous to monetary policy. We challenge this view using a fixed-cost model of durable consumption demand, in which expansionary monetary policy prompts households to accelerate purchases of durable goods. This yields an intertemporal trade-off in aggregate demand as encouraging households to increase durable holdings today leaves fewer households acquiring durables going forward. Interest rates must be kept low to support demand going forward, so accommodative monetary policy today reduces r * in the future. We show that this mechanism is quantitatively important in explaining the persistently low level of real interest rates and r * after the Great Recession.

Using a novel meta-analytical method, Brodeur et al. (2016) argue that hypothesis tests in top economic journals have exaggerated levels of statistical significance. Brodeur et al. (2020) apply the same method to another sample of hypothesis tests, obtaining similar results. We investigate the reliability of the method by highlighting questionable assumptions and compiling a dataset to examine their merits. Our findings support the original conclusions.

In this paper, we review the relationship between inflation rates, nominal interest rates, and rates of growth of monetary aggregates for a large group of OECD countries. If persistent changes in the monetary policy regime are accounted for, the behavior of these series maintains the close relationship predicted by standard quantity theory models. With an estimated model, we show those relationships to be relatively invariant to alternative frictions that can deliver quite different high-frequency dynamics. We also show that the low-frequency component of the data derived from statistical filters does reasonably well in capturing these regime changes. We conclude that the quantity theory relationships are alive and well, and thus they are useful for policy design aimed at controlling inflation.

I present a behavioral epidemiological model of the evolution of the COVID epidemic in the United States and the United Kingdom over the past 12 months. The model includes the introduction of a new, more contagious variant in the UK in early fall and the US in mid December. The model is behavioral in that activity, and thus transmission, responds endogenously to the daily death rate. I show that with only seasonal variation in the transmission rate and pandemic fatigue modeled as a one-time reduction in the semi-elasticity of the transmission rate to the daily death rate late in the year, the model can reproduce the evolution of daily and cumulative COVID deaths in the both countries from Feb 15, 2020 to the present remarkably well. I find that most of the end-of-year surge in deaths in both the US and the UK was generated by pandemic fatigue and not the new variant of the virus. I then generate forecasts for the evolution of the epidemic over the next two years with continuing seasonality, pandemic fatigue, and spread of the new variant.

Education services in the United States are determined predominantly by non-market institutions, the rules of which are defined by state constitutions. This paper empirically examines the effect of changes in constitutional provisions on education outcomes in the United States. To show causal effects, we exploit discontinuities in the procedure for adopting constitutional amendments to compare outcomes when an amendment passed with those when an amendment failed. Our results show that adoption of an amendment results in higher per-pupil expenditure, higher teacher salaries, smaller class size, and improvements in reading and math test scores. We examine the underlying mechanism driving these results by studying the actions of the legislature and the courts after an amendment is passed. We find that, on average, the legislature responds with a one-year lag in enacting education policies satisfying the minimum standards imposed by the amendment, and there is no increase in the number of education cases reaching appellate courts. Using school finance reforms, we also show that in situations where the legislature fails to enact education policies, courts intervene to enforce constitutional standards to improve outcomes. This enforcement mechanism is more impactful in states that have higher constitutional minimum standards. Taken together, the causal effects on education outcomes and the patterns in legislative bill enactments and court cases provide a novel test of the hypothesis that a strong constitutional provision improves the bargaining position of citizens vis-à-vis that of elected leaders. If citizens do not receive education services as mandated in the constitution, they can seek remedy in court.

We show that a simple model of COVID-19 that incorporates feedback from disease prevalence to disease transmission through an endogenous response of human behavior does a remarkable job fitting the main features of the data on the growth rates of daily deaths observed across a large number countries and states of the United States from March to November of 2020. This finding, however, suggests a new empirical puzzle. Using an accounting procedure akin to that used for Business Cycle Accounting as in Chari et al. (2007), we show that when the parameters of the behavioral response of transmission to disease prevalence are estimated from the early phase of the epidemic, very large wedges that shift disease transmission rates holding disease prevalence fixed are required both across regions and within a region over time for the model to match the data on deaths from COVID-19 as an equilibrium outcome exactly. We show that these wedges correspond to large shifts in model forecasts for the long-run attack rate of COVID-19 both across locations and over time. Future research should focus on understanding the sources in these wedges in the relationship between disease prevalence and disease transmission.