O crescimento da empresa: uma análise da variabilidade das taxas de crescimento

Esta pesquisa investigou a variabilidade da taxa de crescimento das empresas, associando-a a grupos de fatores como os associados ao ramo de negócios, ao período ou ano em que se observa o crescimento, ao país e, finalmente, o grupo de fatores associado à empresa individual de forma idiossincrática. O trabalho inspirou-se na linha de pesquisa de componentes de variância do desempenho financeiro em estratégia usando o crescimento como variável dependente. Os achados indicam que a firma individual é a responsável pela maior parte da variância observada nas taxas de crescimento. País e ano também são fontes de variação relevantes. O ramo de negócios no qual a firma está inserida, contudo, tem uma pequena relevância na explicação da variabilidade. O trabalho usou a base de dados Compustat Global como fonte principal. Os resultados têm implicações tanto para a gestão de empresas ao nível corporativo como para a criação de políticas de desenvolvimento e crescimento. Esta pesquisa fez uma avaliação de uma amostra internacional para poder avaliar o efeito país, mas abre espaço para vários outros estudos mais profundos, com maior foco na realidade brasileira.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

Monopoly power, trade protection and growth: cross industry evidence

This paper investigates the impact of monopoly power on trade policy. Annual panel-databases of Brazilian industries for the years 1988 through 1994 were used. The regressions reported here are robust to openness indicator, concentration index, control variables and sample size, and suggest that industries with higher monopoly power are more protected than competitive sectors. In the period of study the country experienced a major trade liberalization, but the results in the paper show that the reduction in protection was smaller in sectors with higher monopoly power. We thus have evidence favoring recent growth literature which stresses that interest groups with control over creasing productivity. The results here confirm the first part of this argument and show that organized groups in fact are able to obtain policy advantages that reduce competition.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.

Sustentabilidade e equilíbrio do crescimento: uma abordagem contábil-financeira

Este trabalho transita por duas áreas de conhecimento, gestão contábil-financeira e sustentabilidade, que precisam se aproximar na troca de conceitos e práticas para que se viabilize a contribuição das empresas para o desenvolvimento sustentável. O propósito do estudo é verificar se o crescimento equilibrado está associado ao desempenho sustentável das empresas. Partindo do pressuposto que o crescimento desequilibrado é um fator de risco para a empresa e para todos os que se relacionam com ela (stakeholders), podendo gerar impactos econômico-financeiros, sociais e ambientais, é de se esperar que as empresas sustentáveis apresentem um crescimento mais equilibrado, medido pelo indicador equilíbrio do crescimento, que reflete se há preocupação com a pressão sobre o uso de todos os tipos de recursos e a sua forma de financiamento. O desempenho sustentável das empresas deve ser avaliado de forma ampla, com base no conceito do Triple Bottom Line, buscando atender às necessidades de vários stakeholders; neste trabalho o desempenho sustentável será operacionalizado de duas maneiras: pela adesão aos segmentos diferenciados de governança corporativa da Bovespa e pela participação na carteira do Índice de Sustentabilidade Empresarial da Bovespa (ISE-Bovespa). Os objetivos do trabalho são: verificar se as empresas consideradas sustentáveis, pelos critérios separados e depois em conjunto, apresentam menor variabilidade no indicador equilíbrio do crescimento do que as empresas não consideradas sustentáveis pelos mesmos critérios; verificar se as empresas apresentam menor variabilidade no indicador equilíbrio do crescimento no segundo período da análise do que no primeiro, períodos estes separados pela divulgação da primeira carteira do ISE-Bovespa, em 2005. Foram utilizados dados de empresas de capital aberto no período de dezembro de 1999 a dezembro de 2009; as empresas foram divididas em grupos e o estudo se concentrou na variabilidade do equilíbrio do crescimento nos grupos, medida pelo desvio padrão, considerando-se que todos os grupos apresentam médias próximas da unidade. Um grupo com baixa variabilidade no equilíbrio do crescimento mostra uma maior preocupação com o uso de recursos de forma equilibrada, refletindo uma postura compatível com a contribuição das empresas para o desenvolvimento sustentável. A confirmação de dez em doze hipóteses de pesquisa permite interpretar que, no conjunto, o resultado é fortemente aderente à hipótese de associação entre o crescimento equilibrado e o desempenho sustentável

Uso de internet no Brasil: uma análise baseada na Teoria de Resposta ao Item (TRI)

A presente dissertação visa identificar como se dá o uso da internet pelos brasileiros considerando as dimensões: governo eletrônico, lazer, informação, comunicação, educação, comércio eletrônico, e analisando itens são melhores discriminadores da dimensão bem como construir um indicador de precedência nos tipos de uso. Para tal será utilizada a fonte de dados secundária fornecida pelo centro de estudos CETIC referente à pesquisa TIC Domicílios 2009. E por intermédio da técnica estatística Teoria da Resposta ao Item (TRI) cada brasileiro da amostra receberá uma pontuação relacionada às suas respostas aos itens da dimensão. Este trabalho apresenta resultados que permitem explicar aspectos relacionados ao uso de internet pelos brasileiros. Para algumas dimensões agrupou-se os itens de modo a apresentar a dimensão discriminada em grupos. Para as dimensões de Comércio Eletrônico e de Governo Eletrônico concluiu-se que os itens de suas dimensões não discriminam grupos de brasileiros com relação o seu uso, pois pela curva característica do item, cada item discrimina os brasileiros na mesma dimensão da mesma forma. Já para Comunicação, Educação, Informação e Lazer são discriminados por grupos de itens mais prováveis ao uso pelo brasileiro e usos menos prováveis.

A monthly indicator of Brazilian GDP. The Brazilian business cycle and growth cycle

This paper constructs an indicator of Brazilian GDP at the monthly ftequency. The peculiar instability and abrupt changes of regimes in the dynamic behavior of the Brazilian business cycle were explicitly modeled within nonlinear ftameworks. In particular, a Markov switching dynarnic factor model was used to combine several macroeconomic variables that display simultaneous comovements with aggregate economic activity. The model generates as output a monthly indicator of the Brazilian GDP and real time probabilities of the current phase of the Brazilian business cycle. The monthly indicator shows a remarkable historical conformity with cyclical movements of GDP. In addition, the estimated filtered probabilities predict ali recessions in sample and out-of-sample. The ability of the indicator in linear forecasting growth rates of GDP is also examined. The estimated indicator displays a better in-sample and out-of-sample predictive performance in forecasting growth rates of real GDP, compared to a linear autoregressive model for GDP. These results suggest that the estimated monthly indicator can be used to forecast GDP and to monitor the state of the Brazilian economy in real time.

Monopoly power and trade protection: cross- industry evidence

This paper investigates the impact of industry concentration on trade policy. Annual panel-databases of Brazilian industries for the years 1988 through 1994 were used. The regressions reported here are robust to openness indicator. concentration index, control variables and sample size, and suggest that the higher the concentration of a given industry the higher its leveI of trade protection. In the period of study the country experienced a major trade liberalization, but the results in the paper show that the reduction in protection was smaller in more concentrated sectors. Assuming that concentration is ;1 gCl()d proX\' for mOllopoh' po\\'er as it reduces the free-rider problem in coordinating a lobby the results in this paper indicates that interest groups with control over specific markets in fact are able to obtain policy advantages that reduce (international) competition.

Formation and destruction of coalition groups under economic growth

This paper introduces a model economy in which formation of coalition groups under technological progress is generated endogenously. The coalition formation depends crucially on the rate of arrival of new technologies. In the model, an agent working in the saroe technology for more than one period acquires skills, part of which is specific to this technology. These skills increase the agent productivity. In this case, if he has worked more than one period with the same technology he has incentives to construct a coalition to block the adoption of new technologies. Therefore, in every sector the workers have incentives to construct a coalition and to block the adoption of new technologies. They will block every time that a technology stay in use for more than one period.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).