Knowledge that Transforms

We study how incentive constraints can be relaxed by randomization in a repeated-game setting. Our study is motivated by the workings of a detected bidding cartel that adopted a protocol of keeping the winning bid secret from the designated losers when defection was a concern. Keeping the winning bid secret makes accurately undercutting the winning bid more difficult and makes defection less attractive as potential defectors risk not winning the auction even if they deviate. We formalize these ideas in the context of a repeated-game setting and show that a cartel can attain higher payoffs by having the pre-selected winner randomize its bid and keep it secret from other members. Calibration of the model to the bid data of the cartel suggests that randomization may increase firms’ profits by about 56%.

We propose a novel channel through which rising income inequality affects job creation and macroeconomic outcomes. High-income households save relatively more in stocks and bonds but less in bank deposits. A rising top income share thereby increases the relative financing cost for bank-dependent firms, which in turn create fewer jobs compared to other firms. Exploiting variation in top income shares across US states and an instrumental variable strategy, we provide evidence for this channel. We then build a general equilibrium macroeconomic model with heterogeneous households and heterogeneous firms and calibrate it to our empirical estimates. The model shows that the secular rise in top incomes accounts for 13% of the decline in the employment share of small firms since 1980. Through the new channel, rising inequality also reduces the labour share and aggregate output. Model experiments show that ignoring the link between inequality and job creation understates welfare effects of income redistribution.

We exploit Germany’s temporary three-percentage-point value-added tax (VAT) cut in the second half of 2020 to study the spending response to unconventional fiscal policy. We use survey and scanner data on household consumption expenditures and their perceived pass-through of the tax change into prices, and a HANK model to quantify the effects of this VAT policy. The survey and scanner data show that the temporary VAT reduction led to a relative increase in durable and, to a lesser extent, semi-durable spending for individuals with high perceived pass-through. According to the HANK model, the VAT policy increased total aggregate consumption spending by 4.4% on impact.

Environmental externalities—uncompensated damages imposed on others—lie at the root of climate change, pollution, deforestation and biodiversity loss. Empirical evidence is limited, however, as to how externalities drive private decision making. We study one such behaviour, illegal tropical forest fires, using 15 years of daily satellite data covering over 107,000 fires across Indonesia. Weather-induced variation in fire spread risk and variation in who owns surrounding land allow us to identify how far externalities influence the decision to use fire. Relative to when all spread risks are internalized, we find that firms overuse fire when surrounded by unleased government lands where property rights are weak. In contrast, and consistent with the Coase Theorem, firms treat risks to nearby private concessions similarly to risks to their own land. Government sanctions, concentrated on fires spreading to populated areas, also deter fires, consistent with Pigouvian deterrence.

We investigate optimal monetary and macroprudential policies in an open economy with aggregate demand externalities and an occasionally binding zero lower bound constraint. Our analysis highlights that the optimal policy balances output stabilization and capital flow management. When macroprudential policy is available, monetary policy stabilizes the output gap. By contrast, when macroprudential policy is not available, monetary policy is used prudentially. However, contrary to a widespread view, raising the interest rate is not necessarily the optimal prudential policy. Finally, we show that international spillovers operate through the world real rate, but macroprudential policies provide insulation from the adverse effects of foreign policies.

This article views hiring as a contextual bandit problem: to find the best workers over time, firms must balance “exploitation” (selecting from groups with proven track records) with “exploration” (selecting from under-represented groups to learn about quality). Yet modern hiring algorithms, based on supervised learning approaches, are designed solely for exploitation. Instead, we build a resume screening algorithm that values exploration by evaluating candidates according to their statistical upside potential. Using data from professional services recruiting within a Fortune 500 firm, we show that this approach improves the quality (as measured by eventual hiring rates) of candidates selected for an interview, while also increasing demographic diversity, relative to the firm’s existing practices. The same is not true for traditional supervised learning-based algorithms, which improve hiring rates but select far fewer Black and Hispanic applicants. Together, our results highlight the importance of incorporating exploration in developing decision-making algorithms that are potentially both more efficient and equitable.

We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school starting age on one’s genetic predisposition towards educational attainment. We argue that gene–environment (G×E) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.

We develop a model of a Financial Stability Fund (the “Fund” henceforth) for a union of sovereign countries. By design, the contract prevents country defaults, as well as undesired expected losses, which in a union translate into excessive risk mutualizations. A participant country has greater ability to borrow and share risks than using sovereign debt financing. The Fund contract also provides better incentives for the country to reduce endogenous risks. These efficiency gains arise from the ability of the Fund to offer long-term contingent financial contracts, subject to limited enforcement and moral hazard constraints. We develop the theory and quantitatively compare the constrained-efficient Fund economy with an incomplete markets economy with default. We calibrate our economy to the euro area “stressed countries” in the debt crisis (2010–2). Substantial welfare gains are achieved, particularly in times of crisis. The Fund is, in fact, a risk-sharing, crisis prevention and resolution mechanism, which transforms the participant countries’ defaultable sovereign debt into the union’s safe assets. In sum, our theory can help to improve current official lending practices and, for example, to eventually design a European Fiscal Fund.

We explore the power that precise information about consumers’ preferences grants an intermediary in shaping competition. We think of an intermediary as an information designer who chooses what information to reveal to firms, which then compete à la Bertrand in a differentiated product market. We analyse the information designs that maximize consumer and producer surplus and uncover systematic differences in how information can be used to intensify or soften competition. Our analysis demonstrates the power that users’ data can endow intermediaries with and speaks directly to current regulatory debates regarding digital marketplaces.

Labour productivity in manufacturing differs starkly across regions in China. We document that productivity, wages, and start-up rates of non-state firms have nevertheless experienced rapid unconditional regional convergence after 1995. To analyse these patterns, we construct a Hopenhayn model that incorporates location-specific capital wedges, output wedges, and entry barriers. Using Chinese Industry Census data, we estimate these wedges and examine their role in explaining differences in performance and growth across prefectures. Entry barriers explain most of the differences. We investigate the empirical covariates of these entry barriers and find that changes in barriers are causally related to changes in the size of the state sector: a smaller state sector leads to lower entry barriers.