7 resultados para Optimal design of experiments

em Repositório digital da Fundação Getúlio Vargas - FGV


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Whether human capital increases or decreases wage uncertainty is an open question from an empirical standpoint. Yet, most policy prescriptions regarding human capital formation are based on models that impose riskiness on this type of investment. In a two period and finite type optimal income taxation problem we derive prescriptions that are robust to the risk characteristics of human capital: savings should be discouraged, human capital investments encouraged and both types of investment driven to an efficient level from an aggregate perspective. These prescriptions are also robust to the assumptions regarding what choices are observed, despite policy instruments being not.

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The purpose of this work is to provide a brief overview of the literature on the optimal design of unemployment insurance systems by analyzing some of the most influential articles published over the last three decades on the subject and extend the main results to a multiple aggregate shocks environment. The properties of optimal contracts are discussed in light of the key assumptions commonly made in theoretical publications on the area. Moreover, the implications of relaxing each of these hypothesis is reckoned as well. The analysis of models of only one unemployment spell starts from the seminal work of Shavell and Weiss (1979). In a simple and common setting, unemployment benefits policies, wage taxes and search effort assignments are covered. Further, the idea that the UI distortion of the relative price of leisure and consumption is the only explanation for the marginal incentives to search for a job is discussed, putting into question the reduction in labor supply caused by social insurance, usually interpreted as solely an evidence of a dynamic moral hazard caused by a substitution effect. In addition, the paper presents one characterization of optimal unemployment insurance contracts in environments in which workers experience multiple unemployment spells. Finally, an extension to multiple aggregate shocks environment is considered. The paper ends with a numerical analysis of the implications of i.i.d. shocks to the optimal unemployment insurance mechanism.

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Neste trabalho é analisada a relação entre um regulador e uma empresa petrolífera. Há várias incertezas inerentes à essa relação e o trabalho se concentra nos efeitos da assimetria de informação. Fazemos a caracterização da regulação ótima sob informação assimétrica, quando o regulador deve desenhar um mecanismo que induz a firma a revelar corretamente sua informação privada. No caso em que a rma não pode se comprometer a não romper o acordo, mostramos que o regulador pode não implementar o resultado ótimo que é obtido sob informação completa. Nesse caso, o regulador não consegue compartilhar os riscos com a firma de forma ótima. Por fim, é apresentado um exemplo, em que mostramos que a condição de Spence-Mirrlees (SMC) pode não valer. Esse resultado aparece de forma natural no modelo.

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The author argues that by applying problem-solving negotiation skills in the design of public policies, public administrators benefit from more effective and wide-ranging outcomes in the realization of their goals. In order to demonstrate this idea, the author analyzes how negotiation skills – such as identifying key actors and their interests, recognizing hardbargaining tactics and changing the players, knowing your best alternative, creating value and building trust – permeated and contributed to the success of the City of São Paulo’s Invoice Program (“Programa Nota Fiscal Paulistana”), a public policy aimed at combating tax evasion of service tax in the City of São Paulo.

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This paper investigates the importance of the fiow of funds as an implicit incetive provided by investors to portfolio managers in a two-period relationship. We show that the fiow of funds is a powerful incentive in an asset management contract. We build a binomial moral hazard model to explain the main trade-ofIs in the relationship between fiow, fees and performance. The main assumption is that efIort depend" on the combination of implicit and explicit incentives while the probability distrioutioll function of returns depends on efIort. In the case of full commitment, the investor's relevant trade-ofI is to give up expected return in the second period vis-à-vis to induce efIort in the first período The more concerned the investor is with today's payoff. the more willing he will be to give up expected return in the following periods. That is. in the second period, the investor penalizes observed low returns by withdrawing resources from non-performing portfolio managers. Besides, he pays performance fee when the observed excess return is positive. When commitment is not a plausible hypothesis, we consider that the investor also learns some symmetríc and imperfect information about the ability of the manager to generate positive excess returno In this case, observed returns reveal ability as well as efIort choices exerted by the portfolio manager. We show that implicit incentives can explain the fiow-performance relationship and, conversely, endogenous expected return determines incentives provision and define their optimal leveIs. We provide a numerical solution in Matlab that characterize these results.

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This work analyzes the optimal design of an unemployment insurance program for couples, whose joint search problem in the labor market differ significantly from the problem faced by single agents. We use a version of the sequential search model of the labor market adapted to married agents to compare optimal constant policies for single and married agents, as well as characterize the optimal constant policy when the agency faces single and married agents simultaneously. Our main result is that an agency that gives equal weights to single and married agents will want to give equal utility promises to both types of agents and spend more on the single agent.

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We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.