Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

The dissertation analyzes the impact of Foreign Direct Investment (FDI) on Economic Growth by extension and economic development of the regions of the Czech Republic (CZ) in 1998 -- 2011. Statistical data empirically study determined motivation of investors to locate in economically strong regions. Following the analysis of statistical data, available resources and a field survey, whose output includes three case studies of specific Foreign Investments in the Czech Republic, the analysis examines whether the arrival of a significant foreign direct investor in the region significantly influenced selected characteristics of economic performance, or other selected areas in region (social, environmental, transport etc.). Moreover, in the context of econometric analysis to test the tightness of the relationship between Foreign Direct Investment and Economic Growth using Pearson's coefficient and characteristics of variability. The causal effect of Foreign Direct Investment on Economic Growth (and vice versa) is analyzed using Granger causality test. The conclusion gives an assessment of the significance of Foreign Direct Investment in the regions of the Czech Republic together with the identification of significant effects brought by investments.

Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

This research was geared towards the investigation of management strategies (factors) that affect the performance ofMSMEs in Kenya. Many developed countries record a time in history when entrepreneurial activities led to revival of economical growth after decline. This implies MSMEs is a very vital sector especially for a developing country like Kenya. MSMEs stagnate and their performance is uncertain according to writers such as Namusonge, Management inadequacies have been suggested in several studies. The objectives of this research was to, 1. To identifY the critical management factors affecting the performance of MSMEs in Kenya; ii. To establish the process through which managerial factors affect the performance of a MSMEs in Kenya ; m. To determine the integrative effect of various management factors in the MSMES in Kenya; IV. To establish the effect of demographics and management factors on performance, v. To establish effects of external environment on internal management factors A conceptual model was formulated from the literature review showing relationships of the management strategies and the environment they operate in. These relationships became the basis for the hypotheses which were later tested. In chapter 4, a mini research (pilot study) was conducted in May 2007,whose main aim was to test the reliability and validity of the research instruments. The 36 questionnaires returned were analysed through descriptive method. Results obtained indicated the instruments were reliable and the results valid. A few corrections suggested were made. The major correction was addition of question 35 to collect financial information. The data collection was done between mid August and mid October 2007.In chapter 5, the researcher analysesd the results of the survey after receiving 180 questionnaires. Time was a constraint. In chapter 6, the hypotheses and conceptual model were analysed and the results obtained suggested that, most strategies did not affect the profitability separately but severally. The integrated effect of the management strategies and the associated factors had a higher impact on performance of the MSMES than any individual strategies. In chapter 7, the conclusions, summaries and Recommendations are given. / Business Management / D. Com. (Business Management and Policy)

This research was geared towards the investigation of management strategies (factors) that affect the performance ofMSMEs in Kenya. Many developed countries record a time in history when entrepreneurial activities led to revival of economical growth after decline. This implies MSMEs is a very vital sector especially for a developing country like Kenya. MSMEs stagnate and their performance is uncertain according to writers such as Namusonge, Management inadequacies have been suggested in several studies. The objectives of this research was to, 1. To identifY the critical management factors affecting the performance of MSMEs in Kenya; ii. To establish the process through which managerial factors affect the performance of a MSMEs in Kenya ; m. To determine the integrative effect of various management factors in the MSMES in Kenya; IV. To establish the effect of demographics and management factors on performance, v. To establish effects of external environment on internal management factors A conceptual model was formulated from the literature review showing relationships of the management strategies and the environment they operate in. These relationships became the basis for the hypotheses which were later tested. In chapter 4, a mini research (pilot study) was conducted in May 2007,whose main aim was to test the reliability and validity of the research instruments. The 36 questionnaires returned were analysed through descriptive method. Results obtained indicated the instruments were reliable and the results valid. A few corrections suggested were made. The major correction was addition of question 35 to collect financial information. The data collection was done between mid August and mid October 2007.In chapter 5, the researcher analysesd the results of the survey after receiving 180 questionnaires. Time was a constraint. In chapter 6, the hypotheses and conceptual model were analysed and the results obtained suggested that, most strategies did not affect the profitability separately but severally. The integrated effect of the management strategies and the associated factors had a higher impact on performance of the MSMES than any individual strategies. In chapter 7, the conclusions, summaries and Recommendations are given. / Business Management / D. Com. (Business Management and Policy)

This master's thesis is focused on problem of orders of ingredients in McDonald's. It's an analysis of usage changes depending on outside temperature. Thesis includes theoretical background for correct analysis of the problem and possibilities to figuring it out. There is also an algorithmus for more efficient solution of problem with needs or excess of ingredients. There is also a program written in VBA language, that makes more simple usage of this algorithm on restaurants.

The South African Government in 2002 accepted the Public Service Anti-Corruption Strategy (PSACS) with the objective to reduce the manifestation of malfeasance in the public service. The PSACS identified various goals and objectives to be achieved at both the systemic and departmental levels. At the departmental level, the PSACS set out to increase the institutional capacity of departmental institutions, and encourage the management of risk and of discipline in the public service. Departments are required to establish the necessary capacity to formulate fraud prevention and anti-corruption policies, receive and manage allegations of corruption, and investigate allegations of corruption and detected risks at a preliminary level. To manage ethics departments should inter alia identify early signs of a lack of discipline, improve the accountability and capacity of managers to manage discipline, and encourage managers to act against transgressions. However, various authors have been critical of the formulation of policies and the establishment of structures as a policy response to public service corruption. In their view, such an approach often leads to a reduction in the efficiency and effectiveness of public programmes, and even creates opportunities for corruption. In response to such deficiencies, some argue that a compliance-based approach to public service malfeasance should be supplemented by a value-based approach with an emphasis on the development of internal selfcontrol of individuals, the promotion of trust among employees, and the promotion of a culture of responsibility. In this context, this researcher proposes that the promotion of an ethical culture could enhance the implementation of the PSACS. In this dissertation, this researcher set out to evaluate, among others, the ethical culture of the Department of Correctional Services (DCS). It was decided that a survey would be the most appropriate data collection method. A questionnaire was administered and the data was captured, analysed and interpreted. Various statistical tests were performed and the findings suggest inter alia that the promotion of an ethical culture coincides with lower levels of observed malfeasance. Consequently, when greater clarity of operational and ethics policies is obtained, an increase occurs in both the severity and frequency of penalties for malfeasance, and officials gain greater access to resources and time to execute their responsibilities, the level of observed malfeasance is likely to be reduced. The promotion of an ethical culture could significantly enhance the implementation of the PSACS. / Public Administration / D. Litt. et Phil. (Public Administration)

Esta dissertação de mestrado apresenta os resultados de uma investigação sobre os métodos de co-estimativa comumente utilizados em geoestatística. Estes métodos são: cokrigagem ordinária; cokrigagem colocalizada e krigagem com deriva externa. Além disso, a krigagem ordinária foi considerada apenas a título de ilustração como esse método trabalha quando a variável primária estiver pobremente amostrada. Como sabemos, os métodos de co-estimativa dependem de uma variável secundária amostrada sobre o domínio a ser estimado. Adicionalmente, esta variável deveria apresentar correlação linear com a variável principal ou variável primária. Geralmente, a variável primária é pobremente amostrada enquanto a variável secundária é conhecida sobre todo o domínio a ser estimado. Por exemplo, em exploração petrolífera, a variável primária é a porosidade medida em amostras de rocha retiradas de testemunhos e a variável secundária é a amplitude sísmica derivada de processamento de dados de reflexão sísmica. É importante mencionar que a variável primária e a variável secundária devem apresentar algum grau de correlação. Contudo, nós não sabemos como eles funcionam dependendo do grau de correlação. Esta é a questão. Assim, testamos os métodos de co-estimativa para vários conjuntos de dados apresentando diferentes graus de correlação. Na verdade, esses conjuntos de dados foram gerados em computador baseado em algoritmos de transformação de dados. Cinco valores de correlação foram considerados neste estudo: 0,993, 0,870, 0,752, 0,588 e 0,461. A cokrigagem colocalizada foi o melhor método entre todos testados. Este método tem um filtro interno que é aplicado no cálculo do peso da variável secundária, que por sua vez depende do coeficiente de correlação. De fato, quanto maior o coeficiente de correlação, maior é o peso da variável secundária. Então isso significa que este método funciona mesmo quando o coeficiente de correlação entre a variável primária e a variável secundária é baixo. Este é o resultado mais impressionante desta pesquisa. / This master dissertation presents the results of a survey into co-estimation methods commonly used in geostatistics. These methods are ordinary cokriging, collocated cokriging and kriging with an external drift. Besides that ordinary kriging was considered just to illustrate how it does work when the primary variable is poorly sampled. As we know co-estimation methods depend on a secondary variable sampled over the estimation domain. Moreover, this secondary variable should present linear correlation with the main variable or primary variable. Usually the primary variable is poorly sampled whereas the secondary variable is known over the estimation domain. For instance in oil exploration the primary variable is porosity as measured on rock samples gathered from drill holes and the secondary variable is seismic amplitude derived from processing seismic reflection data. It is important to mention that primary and secondary variables must present some degree of correlation. However, we do not know how they work depending on the correlation coefficient. That is the question. Thus, we have tested co-estimation methods for several data sets presenting different degrees of correlation. Actually, these data sets were generated in computer based on some data transform algorithms. Five correlation values have been considered in this study: 0.993; 0.870; 0.752; 0.588 and 0.461. Collocated simple cokriging was the best method among all tested. This method has an internal filter applied to compute the weight for the secondary variable, which in its turn depends on the correlation coefficient. In fact, the greater the correlation coefficient the greater the weight of secondary variable is. Then it means this method works even when the correlation coefficient between primary and secondary variables is low. This is the most impressive result that came out from this research.

Esta dissertação de mestrado apresenta os resultados de uma investigação sobre os métodos de co-estimativa comumente utilizados em geoestatística. Estes métodos são: cokrigagem ordinária; cokrigagem colocalizada e krigagem com deriva externa. Além disso, a krigagem ordinária foi considerada apenas a título de ilustração como esse método trabalha quando a variável primária estiver pobremente amostrada. Como sabemos, os métodos de co-estimativa dependem de uma variável secundária amostrada sobre o domínio a ser estimado. Adicionalmente, esta variável deveria apresentar correlação linear com a variável principal ou variável primária. Geralmente, a variável primária é pobremente amostrada enquanto a variável secundária é conhecida sobre todo o domínio a ser estimado. Por exemplo, em exploração petrolífera, a variável primária é a porosidade medida em amostras de rocha retiradas de testemunhos e a variável secundária é a amplitude sísmica derivada de processamento de dados de reflexão sísmica. É importante mencionar que a variável primária e a variável secundária devem apresentar algum grau de correlação. Contudo, nós não sabemos como eles funcionam dependendo do grau de correlação. Esta é a questão. Assim, testamos os métodos de co-estimativa para vários conjuntos de dados apresentando diferentes graus de correlação. Na verdade, esses conjuntos de dados foram gerados em computador baseado em algoritmos de transformação de dados. Cinco valores de correlação foram considerados neste estudo: 0,993, 0,870, 0,752, 0,588 e 0,461. A cokrigagem colocalizada foi o melhor método entre todos testados. Este método tem um filtro interno que é aplicado no cálculo do peso da variável secundária, que por sua vez depende do coeficiente de correlação. De fato, quanto maior o coeficiente de correlação, maior é o peso da variável secundária. Então isso significa que este método funciona mesmo quando o coeficiente de correlação entre a variável primária e a variável secundária é baixo. Este é o resultado mais impressionante desta pesquisa. / This master dissertation presents the results of a survey into co-estimation methods commonly used in geostatistics. These methods are ordinary cokriging, collocated cokriging and kriging with an external drift. Besides that ordinary kriging was considered just to illustrate how it does work when the primary variable is poorly sampled. As we know co-estimation methods depend on a secondary variable sampled over the estimation domain. Moreover, this secondary variable should present linear correlation with the main variable or primary variable. Usually the primary variable is poorly sampled whereas the secondary variable is known over the estimation domain. For instance in oil exploration the primary variable is porosity as measured on rock samples gathered from drill holes and the secondary variable is seismic amplitude derived from processing seismic reflection data. It is important to mention that primary and secondary variables must present some degree of correlation. However, we do not know how they work depending on the correlation coefficient. That is the question. Thus, we have tested co-estimation methods for several data sets presenting different degrees of correlation. Actually, these data sets were generated in computer based on some data transform algorithms. Five correlation values have been considered in this study: 0.993; 0.870; 0.752; 0.588 and 0.461. Collocated simple cokriging was the best method among all tested. This method has an internal filter applied to compute the weight for the secondary variable, which in its turn depends on the correlation coefficient. In fact, the greater the correlation coefficient the greater the weight of secondary variable is. Then it means this method works even when the correlation coefficient between primary and secondary variables is low. This is the most impressive result that came out from this research.

Submitted by Willians Gaspar (willians.gaspar@fgv.br) on 2018-01-22T16:33:59Z No. of bitstreams: 1 A Correlação entre Jornada de Trabalho e Produtividade - Uma Perspectiva Macroeconômica entre Países.pdf: 1651221 bytes, checksum: 10a95ba6074b04f5e4e0f6d88a9bf7b6 (MD5) / Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2018-01-24T12:00:40Z (GMT) No. of bitstreams: 1 A Correlação entre Jornada de Trabalho e Produtividade - Uma Perspectiva Macroeconômica entre Países.pdf: 1651221 bytes, checksum: 10a95ba6074b04f5e4e0f6d88a9bf7b6 (MD5) / Made available in DSpace on 2018-01-29T18:55:15Z (GMT). No. of bitstreams: 1 A Correlação entre Jornada de Trabalho e Produtividade - Uma Perspectiva Macroeconômica entre Países.pdf: 1651221 bytes, checksum: 10a95ba6074b04f5e4e0f6d88a9bf7b6 (MD5) Previous issue date: 2017-12-19 / This research has as general objective to identify the variables or contributing factors to subsidize the discussion about reduction of the Working Day. As a specific objective, what is proposed is to verify how these same variables affect Productivity. For both objectives the macroeconomic aspects of the countries analyzed are considered. The criterion for selecting these countries is based on the "ranking" of the OECD and World Bank database for the year 2013, considering all the major world economies, which together represent 65.22% of global GDP. The data extracted refer to the "Gross Domestic Product - GDP at (PPP) - Purchasing Power Parity", which consists of the Gross Domestic Product, in international dollars, with a view to the comparative possibility of these economies by purchasing power parity (PPP). Other sources of information were considered as objects of analysis and observations, including the statistical series of secondary data from the International Labor Office (ILO), the International Monetary Fund (IMF), the United Nations (UNDP), the Brazilian Institute of Geography and Economics (IBGE), the Department of Statistics and Socioeconomic Studies (DIEESE) and the Institute of Economic and Applied Research (IPEA). The research was conducted at the macroeconomic level of the countries, with a longitudinal temporal cut between the years 2007 and 2013, in order to observe the behavior of these economies, including during the period of the 2008 global crisis. evolution of the historical series of GDP, revealing the size of the economy, GDP per capita, which captures wealth in relation to the population. Finally, we consider the labor productivity factor itself, which deals with the relationship between GDP, the number of people and the number of hours worked in the period. This research has as general objective to identify the variables or contributing factors to subsidize the discussion about reduction of the Working Day. As a specific objective, what is proposed is to verify how these same variables affect Productivity. For both objectives the macroeconomic aspects of the countries analyzed are considered. The criterion for selecting these countries is based on the "ranking" of the OECD and World Bank database for the year 2013, considering all the major world economies, which together represent 65.22% of global GDP. The data extracted refer to the "Gross Domestic Product - GDP at (PPP) - Purchasing Power Parity", which consists of the Gross Domestic Product, in international dollars, with a view to the comparative possibility of these economies by purchasing power parity (PPP). Other sources of information were considered as objects of analysis and observations, including the statistical series of secondary data from the International Labor Office (ILO), the International Monetary Fund (IMF), the United Nations (UNDP), the Brazilian Institute of Geography and Economics (IBGE), the Department of Statistics and Socioeconomic Studies (DIEESE) and the Institute of Economic and Applied Research (IPEA). The research was conducted at the macroeconomic level of the countries, with a longitudinal temporal cut between the years 2007 and 2013, in order to observe the behavior of these economies, including during the period of the 2008 global crisis. evolution of the historical series of GDP, revealing the size of the economy, GDP per capita, which captures wealth relative to the population. Finally, we consider the labor productivity factor itself, which deals with the relationship between GDP, the number of people and the number of hours worked in the period. Design/Methodology/ approach – The method is a qualitative research of the exploratory type, subsidized by quantitative correlation analysis, and the statistical design is directed to the verification of the degree of association between the variables: Working day and Labor productivity; that is, calculation and interpretation of the degree of correlation between these two variables. Findings – In the final conclusion of the study, it is inferred based on the theoretical reference and the analysis of the statistical data, if the reduction in the working day contributes to changes in productivity indexes, and just as other variables are considered in this discussion. Research limitations – No aspects of the national culture, climatic conditions and segregation of nations by percentage of participation in agriculture, industry, and services were considered in the composition of their economies, with a view to performing comparative analysis by subgroups. In addition, the sample set is restricted both in number of countries and in relation to the relatively short period between 2007 and 2013, in addition to being marked by an atypical event such as the global economic crisis of 2008. Practical contributions – To governments, organizations and workers to rethink the possible economic and social benefits, through public policies that allow greater flexibility in working hours, focusing on the competitive advantages and the balance of the relation between labor and capital, observing the legal aspects, productivity, quality of life, unit costs and the generation of jobs / Esta pesquisa tem como objetivo geral identificar as variáveis ou fatores contribuintes para subsidiar a discussão sobre redução da Jornada de Trabalho. Como objetivo específico, o que se propõe é verificar como essas mesmas variáveis afetam a Produtividade. Para ambos os objetivos são considerados os aspectos macroeconômicos dos países analisados. O critério para seleção desses países se fundamenta no “ranking” da base de dados da Organização para a Cooperação e Desenvolvimento Econômico – OCDE e do Banco Mundial, ano base 2013, considerando-se o conjunto das maiores economias mundiais, que, juntas, representam 65,22% do PIB global. Os dados extraídos são referentes ao “Gross Domestic Product – GDP at (PPP) - Purchasing Power Parity”, que consiste no Produto Interno Bruto, em dólares internacionais, com vistas à possibilidade comparativa destas economias pela paridade do poder de compra (PPC). Outras fontes de informações foram consideradas como objetos de análise e observações, incluindo-se as séries estatísticas de dados secundários do Instituto Internacional do Trabalho (OIT), do Fundo Monetário Internacional (FMI), das Nações Unidas (UNDP), do Instituto Brasileiro de Geografia e Economia (IBGE), do Departamento Intersindical de Estatística e Estudos Socioeconômicos (DIEESE) e do Instituto de Pesquisa Econômica e Aplicada (IPEA). A pesquisa foi conduzida no nível macroeconômico dos países, com corte temporal longitudinal entre os anos de 2007 a 2013, com o objetivo de observar-se o comportamento dessas economias, inclusive durante o período da crise mundial de 2008. Nesse sentido, foi avaliada a evolução da série histórica do PIB, como reveladora do tamanho da economia, o PIB per capita, que captura a riqueza em relação à população. Por último, considera-se o fator produtividade do trabalho propriamente dito, que trata da relação entre o PIB, o número de pessoas e o número de horas trabalhadas no período. Quanto ao método, trata-se de pesquisa qualitativa do tipo exploratória, subsidiada por análise quantitativa correlacional, sendo o delineamento estatístico direcionado para a verificação do grau de associação entre as varáveis: Jornada de trabalho e Produtividade do trabalho; ou seja, cálculo e interpretação do grau de correlação entre essas duas variáveis. Na conclusão final do trabalho, infere-se com base no referencial teórico e na análise dos dados estatísticos, se a redução na jornada de trabalho contribui para alterações nos índices de produtividade, e assim como outras variáveis são consideradas nesta discussão. Não foram considerados aspectos da cultura nacional, condições climáticas e segregação das nações por percentual de participação respectivamente em agricultura, indústria, e serviços, na composição de suas economias, visando realizar análise comparativa por subgrupos. Além disto o conjunto amostral é restrito, tanto em número de países, quanto em relação ao período, relativamente curto, entre 2007 e 2013, além de ter sido marcado por fato atípico como a crise econômica mundial de 2008. Á governos, organizações e trabalhadores para repensarem os eventuais benefícios econômicos e sociais, através de políticas públicas que permitam maior flexibilização das jornadas de trabalho, com foco nas vantagens competitivas e no equilíbrio da relação entre mão de obra e capital, observando os aspectos legais, a produtividade, a qualidade de vida, os custos unitários e a geração de empregos