The best are never normal : exploring the distribution of firm performance

Competitive Strategy literature predicts three different mechanisms of performance generation, thus distinguishing between firms that have competitive advantage, firms that have competitive disadvantage or firms that have neither. Nonetheless, previous works in the field have fitted a single normal distribution to model firm performance. Here, we develop a new approach that distinguishes among performance generating mechanisms and allows the identification of firms with competitive advantage or disadvantage. Theorizing on the positive feedback loops by which firms with competitive advantage have facilitated access to acquire new resources, we proposed a distribution we believe data on firm performance should follow. We illustrate our model by assessing its fit to data on firm performance, addressing its theoretical implications and comparing it to previous works.

Análise de portfólio: uma perspectiva bayesiana

Este trabalho tem com objetivo abordar o problema de alocação de ativos (análise de portfólio) sob uma ótica Bayesiana. Para isto foi necessário revisar toda a análise teórica do modelo clássico de média-variância e na sequencia identificar suas deficiências que comprometem sua eficácia em casos reais. Curiosamente, sua maior deficiência não esta relacionado com o próprio modelo e sim pelos seus dados de entrada em especial ao retorno esperado calculado com dados históricos. Para superar esta deficiência a abordagem Bayesiana (modelo de Black-Litterman) trata o retorno esperado como uma variável aleatória e na sequência constrói uma distribuição a priori (baseado no modelo de CAPM) e uma distribuição de verossimilhança (baseado na visão de mercado sob a ótica do investidor) para finalmente aplicar o teorema de Bayes tendo como resultado a distribuição a posteriori. O novo valor esperado do retorno, que emerge da distribuição a posteriori, é que substituirá a estimativa anterior do retorno esperado calculado com dados históricos. Os resultados obtidos mostraram que o modelo Bayesiano apresenta resultados conservadores e intuitivos em relação ao modelo clássico de média-variância.

Income inequality in a job-search model with heterogeneous discount factors: (revised version, forthcoming 2006, Revista Economia)

This paper investigates the income inequality generated by a jobsearch process when di§erent cohorts of homogeneous workers are allowed to have di§erent degrees of impatience. Using the fact the average wage under the invariant Markovian distribution is a decreasing function of the discount factor (Cysne (2004, 2006)), I show that the Lorenz curve and the between-cohort Gini coe¢ cient of income inequality can be easily derived in this case. An example with arbitrary measures regarding the wage o§ers and the distribution of time preferences among cohorts provides some insights into how much income inequality can be generated, and into how it varies as a function of the probability of unemployment and of the probability that the worker does not Önd a job o§er each period.

Income inequality: the role of impatience in a job-search process

This paper investigates the income inequality generated by a jobsearch process when di§erent cohorts of homogeneous workers are allowed to have di§erent degrees of impatience. Using the fact the average wage under the invariant Markovian distribution is a decreasing function of the time preference (Cysne (2004)), I show that the Lorenz curve and the between-cohort Gini coe¢ cient of income inequality can be easily derived in this case. An example with arbitrary measures regarding the wage o§ers and the distribution of time preferences among cohorts provides some quantitative insights into how much income inequality can be generated, and into how it varies as a function of the probability of unemployment and of the probability that the worker does not Önd a job o§er each period.

The Olympic impact on hosting candidate countries

In this paper, we analyze the impact of hosting the Summer Olympics on macroeconomic aggregates such as GDP, consumption, government consumption and investments per capita. The data is in panel structure and includes the period of ten years before and ten years after the event containing the Olympic Summer Games between 1960 and 1996. The sample countries comprise only candidates to host the games. This sampling strategy allows us to estimate the average treatment effect consistently, because it is assumed that these countries are comparable to each other, including those that ultimately hosted the games. The impact of hosting the Olympic games is measured by Fixed Effect and First Difference regressions. Moreover, we do a structural break test developed by Andrews (1993) to identify if hosting the Olympic Games creates anticipation effects for demand changes that stimulate current GDP, consumption, government consumption and investments. The results indicate a positive effect of the Summer Olympics in all variables of interest. However, the distribution in time and anticipation of these effects is unclear in the tests, changing significantly depending on the model and the significance level used.

Os efeitos da política monetária sobre a poupança financeira, o emprego, a produção e o consumo: 1990-1996

Este trabalho tem por objetivo estimar o tempo que diferentes segmentos econômicos levam para responder a mudanças na taxa de juros. A investigação abrangeu o período de janeiro de 1990 a junho de 1996, compreendendo, portanto, o Plano Collor e os dois anos iniciais do Plano Real. O intuito de medir essa defasagem temporal prende-se ao fato de que, no Brasil, tornou-se hábito adotar, como parâmetros de tempo de resposta à política monetária, aqueles encontrados nos Estados Unidos. Naquele país, o tempo de reação da sociedade à política monetária tem sido estimado, freqüentemente, entre 6 e 12 meses. Este estudo encontrou que, no Brasil, dependendo do segmento (poupança, consumo ou produção), o tempo de resposta é imediato, podendo chegar a 2 ou 3 meses. Para estimar a defasagem de tempo, foi usada a técnica de correlações cruzadas entre variáveis pré-filtradas pelos respectivos ARIMAS.

Implantação de tecnologia de monitoramento remoto para e-service: um estudo exploratório

The purpose of this study is to define measures to increase customer satisfaction and company competitiveness using a remote monitoring technology, in an exploratory study of Alpha Elevator Company (nick name chosen to the company by the actor of the dissertation). Regarding the competitive market, the service industry is striving to achieve productivity, following the example of the manufacturing industry. Nevertheless, these efforts are limited by the amount of hours worked per week, month or year, since the sector charges its services based on the hours spent working on the equipment of the client or based on the numbers of visits. This study is based in the overcoming of the traditional paradigm of selling number of hours by a system of selling results and performance. Employing a remote monitoring system, the elevators under the company service are monitored continually and defects are detected and transmitted to the customer care center, via phone line. The customers can access this data through the Internet and obtain information like availability rate of their elevators and call back response time rate, besides being able to buy products on the company¿s home page and to send feedback. The results were obtained by participating in conferences among experts of the company, in Japan and the United States. Through the analysis of the business environment and based on the bibliographic reference, a strategy was developed to implement e-service as a competitive differentiation.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.