Mitchell VanVuren

Ph.D. Candidate

Phone: (503) 206-9032


Job Market Paper

Aggregate Effects of Public Health Insurance Expansion: The Role of Delayed Medical Care  (PDF)

A substantial body of evidence suggests that many U.S. adults delay medical care until after age 65, when they become eligible for Medicare. In this paper, I study the aggregate consequences of expanding public health insurance access for younger individuals, accounting for the subsequent reduction in delayed care. I focus on two main channels. First, expanding public health insurance can reduce delayed care, resulting in long-run cost savings, since early treatment tends to be less expensive than later treatment. Second, expanding public insurance can raise the total number of people over age 65, raising long-run costs, since earlier care tends to reduce mortality. Both channels raise welfare from an ex-ante perspective, but the second leads to larger increases in distortionary taxation. To study these channels, I construct a heterogeneous-agent overlapping generations general-equilibrium model featuring health investment, endogenous mortality, and public and private health insurance. I estimate the model to match quasi-experimental evidence on the extent of delayed medical care in older U.S. adults and on the effects of the 2014 ACA Medicaid expansion on mortality. Both channels are quantitatively important in determining the long-run costs of expansion; however, the cost savings of the first outweigh the cost increases of the second, reducing long-run costs and the need for distortionary taxes.

Working Papers

Macroeconomic Effects of COVID-19 Across the World Income Distribution  (PDF) (with Titan Alon, Minki Kim, and David Lagakos)

The macroeconomic effects of the COVID-19 pandemic were most severe for emerging market economies, representing the middle of the world income distribution. This paper provides a quantitative economic theory for why emerging markets fared worse, on average, relative to advanced economies and low-income countries. To do so we adapt a workhorse incomplete-markets macro model to include epidemiological dynamics alongside key economic and demographic characteristics that distinguish countries of different income levels. We focus in particular on differences in lockdown stringency, public insurance programs, age distributions, healthcare capacity, and the sectoral composition of employment. The calibrated model predicts greater output declines in emerging markets, as in the data, and greater excess mortality, albeit to a smaller extent than what is observed in the data. Quantitatively, stricter lockdowns and a higher share of jobs requiring social interaction explain a large fraction of the especially severe outcomes in emerging markets. Low-income countries fared relatively better mainly due to their younger populations, which are less susceptible to the disease, and larger agricultural sectors, which require fewer social interactions.

How Should Policy Responses to the COVID-19 Pandemic Differ in the Developing World?  (PDF) (with Titan Alon, Minki Kim, and David Lagakos)

The COVID-19 pandemic has already led to dramatic policy responses in most advanced economies, and in particular sustained lockdowns matched with sizable transfers to much of the workforce. This paper provides a preliminary quantitative analysis of how aggregate policy responses should differ in developing countries. To do so we build an incomplete-markets macroeconomic model with epidemiological dynamics that features several of the main economic and demographic distinctions between advanced and developing economies relevant for the pandemic. We focus in particular on differences in population structure, fiscal capacity, healthcare capacity, the prevalence of “hand-to-mouth” households, and the size of the informal sector. The model predicts that blanket lockdowns are generally less effective in developing countries at reducing the welfare costs of the pandemic, saving fewer lives per unit of lost GDP. Age-specific lockdown policies, on the other hand, may be even more potent in developing countries, saving more lives per unit of lost output than in advanced economies.

The Aggregate Effects of "Free" Secondary Schooling in the Developing World  (PDF) (with Junichi Fujimoto and David Lagakos)

This paper explores the aggregate and distributional effects of publicly funded secondary schooling in the developing world. To do so, we build a general equilibrium model of human capital accumulation by overlapping generations of heterogeneous households. Households face borrowing constraints that can lead to misallocation of talent of high-ability children from low-income households in equilibrium. We estimate the model to match a randomized controlled trial that provided scholarships for free secondary education to a random set of low-income, highability children in Ghana. We then use the estimated model to simulate the effects of scaling up to a nationwide policy of taxpayer-financed secondary schooling in general equilibrium. We find that low-income families gain whether or not their children attend school through a rise in the relative wages of low-skilled workers. The highest-income families lose through higher taxes and lower relative wages of the skilled. Overall GDP per capita rises by around 7 percent in steady-state, which arise through less misallocation of talent and lower population growth.

Works in Progress

Aggregate Effects of Subsidizing Job Search in the Developing World: Crowd In or Crowd Out?

Recent empirical work has shown that high search costs may contribute to the low level of wage work in many developing countries, but the aggregate effects of subsidizing search for wage jobs are unclear. Greatly increasing the number of searchers without an equivalent increase in the number of jobs could lead to substantial crowd out effects. Conversely, making it easier for firms to find qualified workers could reduce the cost of hiring and grow the wage sector, crowding in additional workers. I address this question through the lens of a two-sector general equilibrium search model with a frictional wage sector and frictionless traditional sector. The model allows for both crowd in and crowd out, but neither effect dominates in general. I calibrate the model to data from an experiment that subsidized job search in Ethiopia and find that the model qualitatively matches observed search behavior and quantitatively replicates the effect of offering search subsidies to potential job seekers, despite the fact that treatment data is unused in calibration. I evaluate the effects of providing a subsidy to all job seekers funded by a tax on wage workers. The results suggest that there is moderate crowd out. There are small welfare gains from the policy equal to about 0.6% of consumption and these gains would be twice as large in the absence of crowd out effects.

Labor Market Frictions, Firm Growth, and TFP

Low TFP, a small firm size distribution, and high levels of self-employment are three features that characterize developing economies. I show that cross-country variation in labor market frictions can jointly explain all three facts in a model with borrowing constrained households, borrowing constrained firms, and search-and-matching frictions. High frictions limit the growth of productive firms and lead to smaller firm size and lower TFP in equilibrium. High frictions also lead households to turn to self-employment as insurance against job-finding risk. The calibrated suggests that cross-country differences in labor market frictions can explain about 10% of observed TFP differences.

An Envelope Condition Algorithm for Solving Non-Concave Value Functions with Occasionally Binding Constraints

Many interesting economic phenomena involve discrete choices with differential risk. In recursive models with self-insurance, these choices can lead to value functions which are non-concave. Intuitively, there is a cutoff in self-insurance above which households will take the high-risk choice. A marginal gain in self-insurance that pushes the household over the cutoff is substantially more valuable than a marginal gain that keep the household below the cutoff, leading to non-concavity. In these models, the first order conditions and Euler equation are no longer sufficient conditions for optimality. As a result, traditional high-performance solutions algorithms that rely on these conditions perform poorly. I derive an envelope condition in for this class of models and show that it is both necessary and sufficient for optimality even under non-concavity. I then provide an algorithm exploiting this condition that substantially outperforms traditional high-performance algorithms. Finally, I demonstrate the algorithm in an application to a model of job search under imperfect insurance