Knowledge that Transforms

We document dramatic changes in euro area interbank money markets during the financial and sovereign debt crises: unsecured borrowing declined across the euro area, while secured market haircuts on sovereign bonds increased, and bank borrowing from the European Central Bank rose in southern countries. We construct a quantitative general equilibrium model to assess the macroeconomic impact of these developments and the associated policy response. Our model features heterogeneous banks and sovereign bonds, secured and unsecured money markets, and a central bank. We compare a benchmark policy—the central bank providing collateralized lending to banks at haircuts lower than the market—with an alternative policy that maintains a constant central bank balance sheet. We show that the fall in output, investment, and capital would have been twice as high under the alternative policy.

A common challenge in estimating the impact of interventions (e.g. job training programmes, educational programmes) is that many outcomes of interest (e.g. lifetime earnings or other labour market outcomes) are observed with a long delay. In biomedical settings, this is often addressed by using short-term outcomes as so-called “surrogates” for the outcome of interest, e.g. tumour size as a surrogate for mortality in cancer studies. We build on this literature by combining multiple, possibly qualitatively distinct, short-term outcomes (e.g. short-run earnings and employment indicators) systematically into a “surrogate index”. Under the Prentice surrogacy assumption, which requires that the primary outcome is independent of the treatment conditional on the surrogates, we show that the average treatment effect on the surrogate index equals the treatment effect on the long-term outcome. We also relate the surrogacy assumption to a set of structural, causal assumptions. We then characterize the bias that arises from violations of each of the key assumptions, and we provide simple methods to validate these assumptions using additional observed outcomes. We apply our method to analyse the long-term impacts of a multi-site job training experiment in California. Rather than waiting a full 9 years to directly observe the long-term impact, we show that it is possible to use short-term (the first six quarters) outcomes as surrogates. Given the surrogacy assumption one could have estimated the programme’s long-term impacts on mean employment rates using the employment rates observed in the first six quarters, with a 35% reduction in standard errors relative to a simple difference in means estimator based on all 9 years of data.

I study racial disparities in the criminal justice system by analysing abnormal bunching in the distribution of crack-cocaine amounts used in federal sentencing. I compare cases sentenced before and after the Fair Sentencing Act, a 2010 law that changed the 10-year mandatory minimum threshold for crack-cocaine from 50 g to 280 g. First, I find that after 2010, there is a sharp increase in the fraction of cases sentenced at 280 g (the point that now triggers a 10-year mandatory minimum), and that this increase is disproportionately large for black and Hispanic offenders. I then explore several possible explanations for the observed racial disparities, including racial discrimination that occurs after entry into the criminal justice system. I analyse data from multiple stages in the criminal justice system and find that the increased bunching for minority offenders is driven by prosecutorial discretion, specifically as used by about 20–30% of prosecutors. Moreover, the fraction of cases at 280 g falls in 2013 when evidentiary standards become stricter. Finally, the racial disparity in the increase cannot be explained by differences in education, sex, age, criminal history, seized drug amount, or other elements of the crime, but it can be largely explained by a measure of state-level racial animus. These results shed light on the role of prosecutorial discretion and racial discrimination as causes of racial disparities in sentencing.

We build a quantitative spatial model in which some workers can substitute on-site effort with work done from home. Ability and propensity to telecommute vary by education and industry. We quantify our framework to match the distribution of jobs and residents across 4,502 U.S. locations. Then, we simulate permanent increases in the attractiveness and productivity of telework that lead to greater adoption of hybrid and fully remote work. To validate our model, we show that our results are positively correlated with local changes in residents, jobs, and housing costs since 2019. The rise of telework results in a rich non-monotonic pattern of reallocations of residents and jobs within and across cities. Workers who can telecommute experience welfare gains, and those who cannot suffer losses. Broader access to jobs reduces wage inequality across residential locations, and heralds a partial reversal in the spatial concentration of talent and spending power known as the “Great Divergence”.

In a data economy, transactions of goods and services generate data, which is stored, traded and depreciates. How are the economics of this economy different from traditional production economies? How do these differences matter for measurement of GDP, firm values, depreciation rates, welfare and externalities? We incorporate active experimentation and data as an intangible asset to devise a tractable recursive representation of the data economy. The model rationalizes why apps are often “free” and why even non-digital economic activity might be greater than GDP suggests. Calibrating the model using a combination of macroeconomic and financial moments suggests that the mis-measurement in U.S. GDP due to missing value of data has been as high as 6% in 2018.

Digitization reforms have been hailed as an effective way of strengthening state capacity. However, digitization can also fundamentally reshape the organization of bureaucracies. Using a unique administrative dataset on agricultural taxation and surveys of local bureaucrats from Punjab, Pakistan, we show that digitization reforms can have unintended consequences for state capacity. We exploit the staggered rollout of the digitization of land records in Punjab to show that digitization had a negative effect on tax collection. The fall in taxes was not due to a decrease in the tax base. Instead, digitization affected the bureaucrats’ capacity to collect taxes. (JEL D73, H11, H71, O12, O17)

We study a canonical collective action game with incomplete information. Individuals attempt to coordinate to achieve a shared goal, while also facing a temptation to free-ride. More similar information can help them coordinate, but it can also exacerbate free-riding. Our main result shows that more similar information facilitates (impedes) achieving the common goal when it is sufficiently challenging (easy). We apply this insight to show why less powerful authoritarian governments may face larger protests if they restrict press freedom, when committee diversity is beneficial in costly voting, and when a more diverse community contributes more to public good provision. (JEL C71, D71, D72, D81, D82, D83, H41)

How does information transmission change when it requires attracting the attention of receivers? This paper combines an experiment that varies freelance professionals’ incentives to attract attention about scientific findings, with several online experiments that exogenously expose receivers to the content created. Attention incentives lead to significantly less information being transmitted, but not more factually inaccurate content. These incentives increase information demand and the knowledge of interested receivers. However, among the majority of receivers who do not demand more information, attention incentives lower knowledge and increase biases in beliefs, revealing that missing information can be a channel through which misperceptions arise.

We examine how social interactions and friendships shape students' political opinions in a natural experiment at Sciences Po, a leading French university specializing in social and political sciences. The quasi-random assignment of students into short-term integration groups before their academic curriculum reduces political opinion gaps and fosters friendship formation. Using same-group membership as an instrumental variable for friendship, we find that friendship reduces opinion differences by 40% of a standard deviation in the opinion gap. Our evidence supports a homophily-enforced mechanism: friendships form among initially politically similar students, leading them to join political associations together, reinforcing their similarity. However, friendship does not significantly influence politically dissimilar pairs. Instead, it reduces opinion divergence without enforcing ideological convergence.

We consider an economy in which long-lived experts are matched with short-lived clients. Experts choose the type of client with whom they match, unobserved by the market. The interaction outcome depends on both the expert’s and the client’s type. We study the effects of supplying information about otherwise unobservable outcomes, such as “medical report cards,” to help clients identify better experts. Such information can lead to inefficient matches, as experts reject risky clients to build their reputation. Hence, information can reduce welfare. Withholding information can mitigate these perverse incentives at the cost of misallocating experts known to be inept. (JEL C78, D82, D83)