Um estudo sobre a produtividade total dos fatores em setores de diferentes intensidades tecnólogicas

Este trabalho investigou o problema da determinação da produtividade total dos fatores em diversos setores industriais. Tal determinação se dá por meio de estimação de funções de produção, obtendo-se a produtividade a partir do resíduo destas estimações. A questão que aflora deste procedimento é a existência de correlação entre os resíduos e as variáveis explicativas, implicando em diversos vieses, entre eles o de simultaneidade, de variáveis omitidas e de seleção. Neste trabalho foram abordados diversos métodos de estimação de funções de produção, entre eles os métodos de Olley e Pakes e Levinsohn e Petrin. Todos os métodos foram aplicados a diversos setores da economia. A escolha dos setores se deu com base na intensidade tecnológica de cada um, sendo então escolhidos quatro setores de alta intensidade tecnológica e quatro de baixa intensidade tecnológica. A hipótese básica, fio condutor deste trabalho, é que os diversos métodos de estimação de funções de produção apresentam diferentes resultados quando aplicados a setores de diferentes intensidades tecnológicas. Um dos objetivos deste estudo foi identificar se determinado método seria mais adequado a setores de baixa intensidade tecnológica, enquanto outro seria mais apropriado a setores de alta intensidade tecnológica. Conclui-se que o método de Olley e Pakes é levemente superior ao de Levinsohn e Petrin em ambos os grupos de setores, mas não a ponto de se descartar o segundo método. A sensibilidade dos resultados aos diferentes métodos sugere que todos devem ser consultados. Um resultado adicional deste trabalho é a constatação de que houve queda ou estagnação da produtividade nos setores selecionados para a década de 1996 a 2005.

The effect of social security, health, demography and technology on retirement

This article studies the determinants of the labor force participation of the elderly and investigates the factors that may account for the increase in retirement in the second half of the last century. We develop a life-cycle general equilibrium model with endogenous retirement that embeds Social Security legislation and Medicare. Individuals are ex ante heterogeneous with respect to their preferences for leisure and face uncertainty about labor productivity, health status and out-of-pocket medical expenses. The model is calibrated to the U.S. economy in 2000 and is able to reproduce very closely the retirement behavior of the American population. It reproduces the peaks in the distribution of Social Security applications at ages 62 and 65 and the observed facts that low earners and unhealthy individuals retire earlier. It also matches very closely the increase in retirement from 1950 to 2000. Changes in Social Security policy - which became much more generous - and the introduction of Medicare account for most of the expansion of retirement. In contrast, the isolated impact of the increase in longevity was a delaying of retirement.

Mhealth entrepreneurship: an exploratory research for a managerial model for mhealth start ups in low and middle income countries

Since some years, mobile technologies in healthcare (mHealth) stand for the transformational force to improve health issues in low- and middle-income countries (LMICs). Although several studies have identified the prevailing issue of inconsistent evidence and new evaluation frameworks have been proposed, few have explored the role of entrepreneurship to create disruptive change in a traditionally conservative sector. I argue that improving the effectiveness of mHealth entrepreneurs might increase the adoption of mHealth solutions. Thus, this study aims at proposing a managerial model for the analysis of mHealth solutions from the entrepreneurial perspective in the context of LMICs. I identified the Khoja–Durrani–Scott (KDS) framework as theoretical basis for the managerial model, due to its explicit focus on the context of LMICs. In the subsequent exploratory research I, first, used semi-structured interviews with five specialists in mHealth, local healthcare systems and investment to identify necessary adaptations to the model. The findings of the interviews proposed that especially the economic theme had to be clarified and an additional entrepreneurial theme was necessary. Additionally, an evaluation questionnaire was proposed. In the second phase, I applied the questionnaire to five start-ups, operating in Brazil and Tanzania, and conducted semi-structured interviews with the entrepreneurs to gain practical insights for the theoretical development. Three of five entrepreneurs perceived that the results correlated with the entrepreneurs' expectations of the strengths and weaknesses of the start-ups. Main shortcomings of the model related to the ambiguity of some questions. In addition to the findings for the model, the results of the scores were analyzed. The analysis suggested that across the participating mHealth start-ups the ‘behavioral and socio-technical’ outcomes were the strongest and the ‘policy’ outcomes were the weakest themes. The managerial model integrates several perspectives, structured around the entrepreneur. In order to validate the model, future research may link the development of a start-up with the evolution of the scores in longitudinal case studies or large-scale tests.