The ranking of alternative tariff and quota policies in the presence of domestic monopoly

Bhagwati demonstrated the nonequivalence between tariffs and quotas in the presence of monopoly. This paper also assumes domestic production to be monopolized and shows that giving import licenses or tariff revenues to the domestic producer may raise or lower the welfare cost of protection and the price paid by consumers from the price under other tariff and quota arrangements which maintain the same market share for the domestic producer. However, if the monopolist realizes that commercial policy is an instrument used to maximize the policymaker's welfare function, instead of being a goal in itself, the equivalence of tariffs and quotas re-emerges. © 1977.

Impact of economic, regulatory, and patent policies on innovation in cancer chemoprevention.

Chemoprevention agents are an emerging new scientific area that holds out the promise of delaying or avoiding a number of common cancers. These new agents face significant scientific, regulatory, and economic barriers, however, which have limited investment in their research and development (R&D). These barriers include above-average clinical trial scales, lengthy time frames between discovery and Food and Drug Administration approval, liability risks (because they are given to healthy individuals), and a growing funding gap for early-stage candidates. The longer time frames and risks associated with chemoprevention also cause exclusivity time on core patents to be limited or subject to significant uncertainties. We conclude that chemoprevention uniquely challenges the structure of incentives embodied in the economic, regulatory, and patent policies for the biopharmaceutical industry. Many of these policy issues are illustrated by the recently Food and Drug Administration-approved preventive agents Gardasil and raloxifene. Our recommendations to increase R&D investment in chemoprevention agents include (a) increased data exclusivity times on new biological and chemical drugs to compensate for longer gestation periods and increasing R&D costs; chemoprevention is at the far end of the distribution in this regard; (b) policies such as early-stage research grants and clinical development tax credits targeted specifically to chemoprevention agents (these are policies that have been very successful in increasing R&D investment for orphan drugs); and (c) a no-fault liability insurance program like that currently in place for children's vaccines.

Environmental and technology policies for climate mitigation

We assess different policies for reducing carbon dioxide emissions and promoting innovation and diffusion of renewable energy. We evaluate the relative performance of policies according to incentives provided for emissions reduction, efficiency, and other outcomes. We also assess how the nature of technological progress through learning and research and development (R&D), and the degree of knowledge spillovers, affects the desirability of different policies. Due to knowledge spillovers, optimal policy involves a portfolio of different instruments targeted at emissions, learning, and R&D. Although the relative cost of individual policies in achieving reductions depends on parameter values and the emissions target, in a numerical application to the U.S. electricity sector, the ranking is roughly as follows: (1) emissions price, (2) emissions performance standard, (3) fossil power tax, (4) renewables share requirement, (5) renewables subsidy, and (6) R&D subsidy. Nonetheless, an optimal portfolio of policies achieves emissions reductions at a significantly lower cost than any single policy. © 2007 Elsevier Inc. All rights reserved.

Essays on Job Search and Labor Market Dynamics

This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.

In the second essay, “A Framework for Estimating Persistence of Local Labor

Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.

In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.