We develop a new method to construct instruments in a broad class of economic environments. In the economies we study, a few large firms, industries, or countries account for an important share of economic activity. Idiosyncratic shocks to these large players significantly affect aggregate outcomes and are valid instruments. We provide a methodology to extract these idiosyncratic shocks to create granular instrumental variables (GIVs), which are size-weighted sums of idiosyncratic shocks. We show how GIVs enable us to estimate causal parameters, such as elasticities and multipliers, and are applicable in a broad range of empirically relevant settings.

In the United States, households obtain health insurance through distinct market segments. To explore the economics of this segmentation, we consider the effects of pooling coverage provided through small employers and through individual marketplaces. We model households’ demand for insurance and health care along with insurers’ price setting to predict equilibrium choices and premiums. Applying our model to data from Oregon, we find that pooling can mitigate adverse selection in the individual market and benefit small group households without raising taxpayer costs. Our estimates provide insight into the effects of new regulations that allow employers to shift coverage to individual marketplaces.

Will stock exchanges innovate to address latency arbitrage and the arms race for speed? This paper models how exchanges compete in the modern electronic era and how this shapes incentives for market-design innovation. In the status quo, exchange trading fees are competitive, but exchanges earn economic rents from selling speed. These rents create a wedge between private and social incentives to innovate and support the persistence of an inefficient market design in equilibrium of a market-design adoption game. We discuss implications for policy and insights for the literatures on market design, innovation, and platforms.

We use a large-scale randomized experiment to study the impact of augmenting staffing in the world’s largest public early-childhood program: India’s Integrated Child Development Services. Adding a worker doubled net preschool instructional time and led to increases of 0.28σ and 0.46σ in math and language test scores after 18 months for children who remained enrolled in the program and 0.13σ and 0.10σ for all children enrolled at baseline. Rates of stunting and severe malnutrition were also lower in the treatment group for children who remained enrolled. A cost-benefit analysis suggests that the benefits of augmenting staffing significantly exceed its costs. These effects are likely to replicate even at larger scales of program implementation.

We empirically establish that unemployed individuals maintain significant access to credit and that upon a layoff, the unconstrained borrow while the constrained default and delever. Motivated by these findings, we develop a theory of credit lines and labor income risk to analyze optimal transfers to the unemployed. Since credit lines offer fixed interest rates and limits, credit lines are unresponsive to layoffs and provide greater consumption insurance relative to when debt is repriced period by period. At US levels of credit lines, the government can optimally reduce transfers to the unemployed, whereas this is not true when debt is counterfactually repriced period by period.

In economies with fixed exchange rates, the adjustment to government-spending shocks is asymmetric. Expansionary shocks are absorbed by the real exchange rate, contractionary shocks by output. This result emerges in a small open-economy model with downward nominal wage rigidity and is supported by new empirical evidence based on panel data from different exchange-rate regimes. The exchange-rate regime, economic slack, inflation, and how spending is financed all matter for the fiscal transmission mechanism in the way predicted by the model. Estimates that fail to distinguish between the effects of positive and negative shocks are subject to a “depreciation bias.”

“Big G” typically refers to aggregate government spending on a homogeneous good. We confront this notion with five facts for the universe of federal purchases. First, they are volatile and account for the largest part of the short-run variation in total spending. Second, the origin of their variation is granular. Third, purchases are subject to procurement and bidding. Fourth, they are concentrated in long-term contracts. Fifth, their composition is biased toward sectors in which private sector prices are sticky. We develop a two-sector New Keynesian model consistent with these facts and find where the government spends is key for aggregate effects.