Knowledge that Transforms

We analyse discontinuous Markovian strategies for differential games. The best response correspondence uniquely maps almost all profiles of opponents’ strategies back to the strategy space. We thus make Markov-perfect equilibria in a wide class of differential games well-behaved, resolving a long-standing open problem. We provide a readily applicable necessary and sufficient condition for best responses and Markov-perfect Nash equilibria. We demonstrate our methods in a canonical model of non-cooperative mitigation of climate change. Our approach provides novel, economically important results: we obtain the entire set of symmetric Markov-perfect equilibria and demonstrate that the best equilibria can yield a major welfare improvement over the equilibrium which previous literature has focused on. International climate negotiations can be seen as being about coordination on good equilibria, rather than about bargaining over the limited surplus available in a dynamic prisoner’s dilemma.

We study aggregate capital dynamics in an investment model with idiosyncratic productivity shocks, fixed capital adjustment costs, and irreversibility driven by a wedge between capital purchase and resale prices. We derive sufficient statistics that capture the role of investment frictions in aggregate capital fluctuations, measure these statistics using investment microdata, and exploit them to discipline the capital price wedge. Irreversibility doubles the persistence of capital fluctuations and is crucial for reconciling micro-level investment behaviour with macroeconomic propagation.

How do localized conflicts disrupt supply chains and prompt firms to reorganize them? How do these forces affect firm-level and aggregate economic activity? Using firm-to-firm Ukrainian railway-shipment data before and during the 2014 Russia–Ukraine conflict, we document that firms with prior supplier and buyer exposure to the conflict areas substantially decreased their output. Simultaneously, firms reorganized their production linkages away from partners directly or indirectly exposed to the conflict shock. We build a general-equilibrium production-network model with endogeneous link formation, and we show that our model’s sufficient statistics accurately explains the observed relative decline in firm output once we account for network reorganization. Calibrating our model to the Ukrainian economy, we find that the localized conflict decreased aggregate output in nonconflict areas by 5.5%. This effect increases to 8.4% if we abstract from endogeneous link formation, suggesting that production-network reorganization partially mitigates the detrimental, far-reaching aggregate economic costs of conflicts.

Non-family-based institutions for socializing young people may play a vital role in creating close-knit, inclusive communities. We study the potential for youth camps—integrating rituals, sports, and civics training—to strengthen intergroup cohesion. We randomly assigned Hindu and Muslim adolescent boys, from West Bengal, India, to 2-week camps or to a pure control arm. To isolate mechanisms, we cross-randomized collective rituals (such as singing the national anthem, wearing uniforms, chanting support during matches, and synchronous dancing) and the intensity of intergroup contact. We find that camps reduce ingroup bias, increase willingness to interact with outgroup members, and enhance psychological well-being. Campers continue to have twice as many outgroup friends than control participants 1 year after the camps ended. Meanwhile, additional camp elements have heterogeneous effects: rituals have more positive impacts for the Hindu majority than the Muslim minority, while higher intergroup contact backfires among Hindus but not Muslims. Our findings demonstrate that inclusive youth camps may be a powerful tool for bridging deep social divides. Yet, we also highlight the conceptual challenges in crafting optimal integrative camps that help all groups.

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.