Knowledge that Transforms

How do movements in the distributions of bank size and income affect the macroeconomy? To answer this question, we develop a dynamic general equilibrium model with heterogeneous financial intermediaries, incomplete markets, and aggregate uncertainty. We find that market incompleteness and uninsured idiosyncratic bank rate of return risk generate minimal concentration in the bank net worth distribution, leading to an “as-if” result, whereby the economy behaves as if it had a representative bank. However, introducing ex ante heterogeneity in the banks’ rates of return significantly raises concentration and amplifies real and financial fluctuations relative to the representative-bank case, as this increases a key sufficient statistic, the average marginal propensity to lend. We then extend the model with two empirically validated features of the banking sector—countercyclical return risk and deposit market power—and show that these amplify and dampen aggregate fluctuations, respectively. Finally, because in the model with ex ante heterogeneity the distribution of bank size is highly concentrated, shocks to the largest banks can account for almost all of the aggregate variation that is due to idiosyncratic risk, leading to granular banking and economic cycles. The failure of granular banks (“too big to fail”) produces sizeable macroeconomic crises.

We develop a satisficing model of choice in which the available alternatives differ in their inherent complexity. We assume—and experimentally validate—that complexity leads to errors in the perception of alternatives’ values. The model yields sharp predictions about the effect of complexity on choice probabilities, some of which qualitatively contrast with those of maximization-based choice models. We confirm the predictions of the satisficing model—and thus reject maximization—in a novel data set with information on hundreds of millions of real-world chess moves by highly experienced players. Looking beyond chess, our work offers a blueprint for incorporating complexity at the level of individual objects into models of choice and for detecting satisficing outside of the laboratory.

Firms are allowed to use aggregate data on market salaries to set pay, a practice known as salary benchmarking. Using national payroll data, we study firms that gain access to a tool that reveals market benchmarks for each job title. Using a difference-in-differences design, we find that the benchmark information reduces salary dispersion by 25%. Thus, salary dispersion must stem partly from aggregate uncertainty about the salaries offered by other firms. Our model formalizes how salary dispersion can arise even in competitive labour markets for identical workers when such uncertainty exists, and we discuss implications for an ongoing policy debate.

Economists have studied the impact of numerous state laws, from welfare rules to voting ID requirements. Yet for all this policy evaluation, what do we know about policy diffusion—how these policies are introduced and spread from state to state? We present a series of facts based on a data set of 602 U.S. state policies spanning the past seven decades. First, proxies of state capacity do not predict a higher likelihood of innovating new policies, but the political leaning of the state does predict a higher likelihood of introducing partisan laws since 1990. Second, the diffusion of policies from 1950 to 2000 is best predicted by proximity—a state is more likely to adopt a policy if nearby states have already done so—as well as similarity in voter policy preferences. Third, since 2000, party alignment has become the strongest predictor of diffusion, and the speed of adoption has increased. Models of learning and correlated preferences can account for the earlier patterns, but the findings for the last two decades indicate a sharply increasing role of party control. We conclude that party polarization has emerged as a key factor recently for policy adoption, plausibly leading to a worse match between state policies and voter preferences.

This paper estimates the Brazilian Amazon’s carbon-efficient forest cover—i.e. when farmers internalize the social cost of carbon. We propose a dynamic discrete choice land-use model and estimate it using a panel of land use and carbon stock of 5.7 billion pixels between 2008 and 2017. The business-as-usual scenario implies an inefficient release of 42 billion tons of CO2 in the long run, resulting from the deforestation of an area twice the size of France. A carbon tax that makes farmers internalize the social cost of carbon would implement the efficient allocation and generate welfare gains exceeding 1.6 trillion dollars. Responses from a carbon tax are highly convex: a carbon tax of only $10/ton would preserve 95% of the efficient carbon stock. An excise tax on cattle ranching, a second-best policy, achieves at most 87% of the first-best welfare gains.

Developing countries face massive urbanization and slum upgrading is a popular policy to improve shelter for many. Yet, preserving slums at the expense of formal developments can raise concerns of misallocation of land. We estimate causal, long-term impacts of the 1969–84 KIP programme, which provided basic upgrades to 5 million residents covering 25% of land in Jakarta, Indonesia. We assemble high-resolution data on programme boundaries and 2015 outcomes and address programme selection bias through localized comparisons. On average, KIP areas today have lower land values, shorter buildings, and are more informal, per a photographs-based slum index. The negative effects are concentrated within 5 km of the CBD. We develop a spatial equilibrium model to characterize the welfare implications of KIP. Counterfactuals suggest that 79% of the welfare effects stem from removing KIP in the centre and highlight how to mitigate losses to displaced residents.

Do periods of persistently loose monetary policy increase financial fragility and the likelihood of a financial crisis? This is a central question for policymakers, yet the literature does not provide systematic empirical evidence about this link at the aggregate level. In this article, we fill this gap by analysing long-run historical data. We find that when the stance of monetary policy is accommodative over an extended period, the likelihood of financial turmoil in the medium term increases considerably. We investigate the causal pathways that lead to this result and argue that credit creation and asset price overheating are important intermediating channels.

We study the relationship between international trade and development in a model where countries differ in their capability, goods differ in their complexity, and capability growth is a function of a country’s pattern of specialization. Theoretically, we show that it is possible for international trade to increase capability growth in all countries and, in turn, to push all countries up the development ladder. This occurs if (i) shifting employment towards more complex sectors raises capability growth and if (ii) foreign competition is tougher in less complex sectors for all countries. Empirically, we provide causal evidence consistent with (i) using the entry of countries into the World Trade Organization as an instrumental variable for other countries’ patterns of specialization. The opposite of (ii), however, holds in the data. Through the lens of our model, these two empirical observations imply dynamic welfare losses from trade that are pervasive, albeit small for the median country. The same economic forces also suggest that the emergence of China has held back capability growth for a number of African countries who are pushed away from their most-complex sectors, which China exports, and into their least-complex sectors, which China imports.

How do global value chain (GVC) linkages modify countries’ incentives to impose import protection? Are these linkages important determinants of trade policy in practice? We develop a new approach to modelling tariff setting with GVCs, in which optimal policy depends on the nationality of value-added content embedded in home and foreign final goods. Theory predicts that discretionary tariffs will be decreasing in the domestic content of foreign-produced final goods and the foreign content of domestically produced final goods. Using data for 14 countries between 1995 and 2015, we show that governments set lower tariffs and curb their use of temporary trade barriers where GVC linkages are strongest, consistent with theory. Turning to quantitative model counterfactuals, we find that severing GVC linkages would lead to the disappearance of tariff preferences. Further, targeted policies to decouple China from GVCs would increase the optimal tariff set by G7 countries on Chinese exports.

We study the aggregate and redistributive effects of currency devaluations in a small open economy model with leverage-constrained banks and heterogeneous households. Our framework captures three stylized facts about financial dollarization in emerging economies: (1) a sizable share of domestic deposits is denominated in foreign currency; (2) these deposits represent significant foreign currency liabilities for local banks; and (3) dollar deposits are mainly held by wealthier households. A devaluation increases the real burden of foreign currency debt, causing an erosion of banks’ net worth, which depresses credit supply and economic activity. While richer households are partially insulated through their dollar deposits, poorer households cut consumption sharply in response to rising borrowing costs and falling real labor income. In our model deposit, dollarization amplifies the contractionary effects of a devaluation on output, investment, and consumption, in line with new empirical evidence for emerging economies. To achieve this result, both constrained intermediaries and heterogeneous households are crucial. In our framework, regulating dollarization can result in widespread welfare gains, especially for poorer households.