Likelihood estimate of treatment effects under selection bias

We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

Is there a price puzzle in Brazil? An application of Bias-Corrected Bootstrap

Using data from the United States, Japan, Germany , United Kingdom and France, Sims (1992) found that positive innovations to shortterm interest rates led to sharp, persistent increases in the price level. The result was conÖrmed by other authors and, as a consequence of its non-expectable nature, was given the name "price puzzle" by Eichenbaum (1992). In this paper I investigate the existence of a price puzzle in Brazil using the same type of estimation and benchmark identiÖcation scheme employed by Christiano et al. (2000). In a methodological improvement over these studies, I qualify the results with the construction of bias-corrected bootstrap conÖdence intervals. Even though the data does show the existence of a statistically signiÖcant price puzzle in Brazil, it lasts for only one quarter and is quantitatively immaterial

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

Inflationary bias and state owned financial institutions

This article explains why the existence of state owned financial institutions makes it more difficult for a country to balance its budget. We show that states can use their financiaI institutions to transfer their deficits to the federal govemment. As a result, there is a bias towards Iarge deficits and high inflation rates. Our model also predicts that state owned financiaI institutions should underperform the market, mainly because they concentrate their portfolios on non-performing loans to their own shareholders, that is, the states. Brazil and Argentina are two countries with a history of high inflation that confirm our predictions .

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

Welfare costs of inflation when interest-bearing deposits are disregarded: a calculation of the bias

Most estimates of the welfare costs of in ation are devised considering only noninterest- bearing assets, ignoring that since the 80s technological innovations and new regulations have increased the liquidity of interest-bearing deposits. We investigate the resulting bias. Suscient and necessary conditions on its sign are presented, along with closed-form expressions for its magnitude. Two examples dealing with bidimensional bilogarithmic money demands show that disregarding interest-bearing monies may lead to a non-negligible overestimation of the welfare costs of in ation. An intuitive explanation is that such assets may partially make up for the decreased demand of noninterest-bearing assets due to higher in ation.

Brazil: the pressure points in labor legislation

Brazil’s experience shows that the economic and political history of a country is a critical determinant of which labor laws influence wages and employment, and which are not binding. Long periods of high inflation, illiteracy of the workforce, and biases in the design and enforcement of labor legislation bred by the country’s socioeconomic history are all important in determining the reach of labor laws. Defying conventional wisdom, these factors are shown to affect labor market outcomes even in the sector of employment regarded as unregulated. Following accepted practice in Brazil, we distinguish regulated from unregulated employment by determining whether or not the contract has been ratified by the Ministry of Labor, viz., groups of workers with and without signed work booklet. We then examine the degree of adherence to labor laws in the formal and informal sectors, and finds “pressure points” – viz., evidence of the law on minimum wage, work-hours, and payment timing being binding on outcomes – in both the formal and informal sectors of the Brazilian labor market. The findings of the paper imply that in terms of the design of legislation, informality in Brazil is mainly a fiscal, and not a legal phenomenon. But the manner in which these laws have been enforced is also critical determinant of informality in Brazil: poor record-keeping has strengthened the incentives to stay informal that are already built into the design of the main social security programs, and ambiguities in the design of labor legislation combined with slanted enforcement by labor courts have led to workers effectively being accorded the same labor rights whether or not they have ratified contracts. The incentives to stay informal are naturally higher for workers who are assured of protection under labor legislation regardless of the nature of their contract, which only alters their financial relationship with the government. The paper concludes that informality in Brazil will remain high as long as labor laws remain ambiguous and enforced with a clear pro-labor bias, and social security programs lack tight benefitcontribution linkages and strong enforcement mechanisms.

Comportamento de ajuda entre os "bóias-frias": um estudo exploratório

Esta pesquisa visou levantar as manifestações do comportamento de ajuda entre "bóias-frias" através de seu próprio reato, com o objetivo de analisar as implicações deste comportamento para sua organização social enquanto um grupo específico. Foram entrevistados 47 sujeitos, de ambos os sexos, no seu local de trabalho . O instrumento utilizado foi uma entrevista estruturada construída pela autora desta pesquisa , composta de 26 questões. Estas questões buscaram levantar frequência, razões e situações de ajudai solicitada ou espontânea, do entrevistado em relação aos colegas e de seus colegas em relação a ele mesmo, no trabalho e fora dele . Observou-se que quando perguntados se prestam e recebem ajuda, houve um grande índice de respostas afirmativas e quando solicitados a relatar as situações ocorridas, o índice de respostas diminuiu consideravelmente . Foram discutidas as possíveis razões para a ocorrência de tal fato. A análise das situações de ajuda narradas serviu para a compreensão de como a estrutura do trabalho volante determina as formas que assumem as relações de ajuda entre os "bóias-frias" e o quanto estas relações I por sua vez, influenciam a estruturação das relações sociais destes trabalhadores.

A irracionalidade na tomada de decisão: uma abordagem sobre os efeitos chamariz e âncora

Diversos modelos e teorias econômicas neoclássicas se baseiam nos princípios de racionalidade dos indivíduos. No entanto, muitos estudos vêm mostrando como tais princípios podem ser falhos em diversos contextos. Esta pesquisa buscou contribuir com tal literatura através do desenvolvimento de um experimento realizado com alunos de graduação no qual foram testadas aplicações dos vieses de racionalidade conhecidos como Efeito Chamariz e Efeito Âncora. Foram analisados 142 questionários que aparentemente visavam traçar o perfil dos estudantes através de perguntas sobre suas preferências quanto a oportunidades de emprego considerando múltiplos aspectos (remuneração, estabilidade, carga horária e chances de crescimento profissional). Ao longo das questões, no entanto, foram inseridas âncoras e chamarizes. Como resultados, observamos que, ao procurar um emprego, a maioria dos estudantes valoriza principalmente as chances de crescimento profissional e a remuneração oferecida pelo trabalho, ao passo que a carga horária é o atributo de menor peso em suas decisões. Embora o restante de suas respostas fosse bastante coerente com o perfil traçado, os vieses de racionalidade se mostraram influentes. Os chamarizes usados levaram a alterações nas respostas de 7 a 8%, enquanto que o uso de âncoras se mostraram capazes de influenciar o valor mínimo pelo qual os respondentes aceitariam prestar um serviço, violando os princípios de racionalidade.

Is there a price puzzle in Brazil? an application of bias- corrected bootstrap

Using data from the United States, Japan, Germany , United Kingdom and France, Sims (1992) found that positive innovations to shortterm interest rates led to sharp, persistent increases in the price leveI. The result was confirmed by other authors and, as a consequence of its non-expectable nature, was given the name "price puzzle" by Eichenbaum (1992). In this paper I investigate the existence of a price puzzle in Brazil using the same type of estimation and benchmark identification scheme employed by Christiano et aI. (2000). In a methodological improvement over these studies, I qualify the results with the construction of bias-corrected bootstrap confidence intervals. Even though the data does show the existence of a statistically significant price puzzle in Brazil, it lasts for .only one quarter and is quantitatively immaterial.