April 4 and 5, 2013
Judith A. Frias, Instituto Mexicano del Seguro Social; Todd Kumler, Columbia University; and Eric Verhoogen, Columbia University and NBER
Non-compliance of firms with tax regulations is a major constraint on state capacity in developing countries. Kumler, Verhoogen, and Frias focus on an arguably under-appreciated dimension of non-compliance: under-reporting of wages by formal firms to evade payroll taxes. Comparing wage distributions for similar sets of workers in the administrative records of the Mexican social security agency and a household labor-force survey, they document extensive under-reporting of wages. They further argue that the 1997 Mexican pension reform had a differential effect by age on the incentives of workers to ensure that their wages were reported accurately. Using a difference-in-differences strategy, they present evidence that the increase in the incentive for workers to ensure accurate reports led to a significant decline in under-reporting. The results suggest that enlisting workers in monitoring their employers is an effective way to increase payroll tax compliance.
Patrick Kline, University of California, Berkeley and NBER, and Melissa Tartari, Yale University
Kline and Tartari study the impact of the Connecticut Jobs First (JF) welfare reform experiment on the labor supply and program participation decisions of a sample of welfare applicants and recipients. They develop a rich optimizing model incorporating underr-eporting decisions, labor supply constraints, fixed costs of work, and welfare stigma and hassle. Qualitatively, the model rationalizes the large empirical impacts of the JF experiment on the distribution of earnings, despite the absence of bunching at a program induced notch in agents' budget sets. They show that the model places nonparametric restrictions on experimental impacts that can be used to develop bounds on the magnitude of a variety of intensive and extensive margin responses to reform. The results indicate that, in addition to incentivizing work at the extensive margin, the JF experiment induced a substantial welfare "opt-in" response among women with relatively high earnings potential.
Casey Rothschild, Wellesley College, and Florian Scheuer, Stanford University and NBER
Rothschild and Scheuer consider optimal redistribution in a model where individuals can self-select into one of several possible sectors based on heterogeneity in a multidimensional skill vector. They first show that when the government does not observe the sectoral choice or underlying skills of its citizens, the constrained Pareto frontier can be implemented with a single non-linear income tax. They then characterize this optimal tax schedule. If sectoral inputs are complements, then a many-sector model with self-selection leads to optimal income taxes that are less progressive than the corresponding taxes in a standard single-sector model under natural conditions. However, taxes are more progressive than in canonical multi-sector economies with discrete types and without occupational choice or overlapping sectoral wage distributions.
Mikhail Golosov, Princeton University and NBER; John Hassler, Stockholm University; Per Krusell, Stockholm University and NBER; and Aleh Tsyvinski, Yale University and NBER
Golosov, Hassler, Krusell, and Tsyvinski analyze a dynamic stochastic general-equilibrium (DSGE) model with an externality, through climate change, from using fossil energy. Their central result is a simple formula for the marginal externality damage of emissions (or, equivalently, the optimal carbon tax). This formula, which holds under quite plausible assumptions, reveals that the damage is proportional to current GDP. The proportion depends on three factors: discounting; the expected damage elasticity (how many percent of the output flow is lost from an extra unit of carbon in the atmosphere;, and the structure of carbon depreciation in the atmosphere. Thus, the stochastic values of future output, consumption, and the atmospheric CO 2 concentration, as well as the paths of technology (whether endogenous or exogenous) and population, and so on, all disappear from the formula. They find that the optimal tax should be a bit higher than the median, or most well-known, estimates in the literature. They also formulate a parsimonious yet comprehensive and easily solved model allowing them to compute the optimal and market paths for the use of energy and the corresponding climate change. They find coal, rather than oil, to be the main threat to economic welfare, largely because of its abundance. They also find that the costs of inaction are particularly sensitive to the assumptions regarding the substitutability of different energy sources and technological progress.
James Poterba, MIT and NBER; Steven Venti, Dartmouth College and NBER; and David Wise, Harvard University and NBER
How households draw down their balances in personal retirement accounts (PRAs), such as 401(k) plans and IRAs, can have an important effect on retirement income security and on federal income tax revenues. Poterba, Venti, and Wise examine the withdrawal behavior of retirement-age households in the SIPP and find a modest rate of withdrawals prior to the age of 70½, the age at which required minimum distributions (RMDs) must begin. In a typical year, only 7 percent of PRA-owning households between the ages of 60 and 69 take an annual distribution of more than 10 percent of their PRA balance, and only 18 percent make any withdrawals at all. For these households, annual withdrawals represent about 2 percent of account balances. The rate of distributions rises sharply after age 70½, with annual withdrawals of about 5 percent per year. During the period studied here, the average rate of return on account balances exceeded this withdrawal rate, so average PRA balances continued to grow through at least age 85. These findings suggest that households tend to preserve PRA assets, perhaps to self-insure against large and uncertain late-life expenses, and that RMD rules have important effects on withdrawal patterns.
Eric Budish, University of Chicago; Benjamin Roin, Harvard Law School; and Heidi Williams, MIT and NBER
Patents award innovators a fixed period of market exclusivity, for example, 20 years in the United States. But because in many industries firms file patents at the time of discovery ("invention") rather than first sale ("commercialization"), effective patent terms vary: inventions that commercialize at the time of invention receive a full patent term, whereas inventions that have a long time lag between invention and commercialization receive substantially reduced - or in extreme cases, zero - effective patent terms. Budish, Roin, and Williams present a simple model formalizing how this variation may inefficiently distort research and development (R&D). They then explore this distortion empirically in the context of cancer R&D, where clinical trials are shorter - and hence, effective patent terms longer - for drugs targeting late-stage cancer patients, relative to drugs targeting early-stage cancer patients or cancer prevention. Using a newly constructed dataset on cancer clinical trial investments, they provide several sources of evidence consistent with fixed patent terms distorting cancer R&D. Back-of-the-envelope calculations suggest that the number of life-years at stake is large. They discuss three specific policy levers that could eliminate this distortion - patent design, targeted R&D subsidies, and surrogate (non-mortality) clinical trial endpoints - and provide empirical evidence that surrogate endpoints can be effective in practice.
Naoki Aizawa, University of Pennsylvania, and Hanming Fang, University of Pennsylvania and NBER
Aizawa and Fang present and empirically implement an equilibrium labor market search model in which risk-averse workers facing medical expenditure shocks are matched with firms making health insurance coverage decisions. This model delivers a rich set of predictions that can account for a wide variety of phenomena observed in the data, including the correlations among firm size, wages, health insurance offering rates, turnover rates, and workers' health composition. The authors estimate the model by Generalized Method of Moments, using a combination of micro data sources that include Survey of Income and Program Participation, Medical Expenditure Panel Survey, and Robert Wood Johnson Foundation Employer Health Insurance Survey. They use the estimated model to evaluate the equilibrium impact of the 2010 Affordable Care Act (ACA) and find that it would reduce the uninsured rate among the workers in their estimation sample from 20.12 percent to 7.27 percent. They also examine a variety of alternative policies to understand the roles of different components of the ACA in contributing to these equilibrium changes. Interestingly, they find that the uninsured rate will be even lower (at 6.44 percent) if the employer mandate in the ACA is eliminated.