13 resultados para 2016 model

em Repositório digital da Fundação Getúlio Vargas - FGV


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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.

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In this work we focus on tests for the parameter of an endogenous variable in a weakly identi ed instrumental variable regressionmodel. We propose a new unbiasedness restriction for weighted average power (WAP) tests introduced by Moreira and Moreira (2013). This new boundary condition is motivated by the score e ciency under strong identi cation. It allows reducing computational costs of WAP tests by replacing the strongly unbiased condition. This latter restriction imposes, under the null hypothesis, the test to be uncorrelated to a given statistic with dimension given by the number of instruments. The new proposed boundary condition only imposes the test to be uncorrelated to a linear combination of the statistic. WAP tests under both restrictions to perform similarly numerically. We apply the di erent tests discussed to an empirical example. Using data from Yogo (2004), we assess the e ect of weak instruments on the estimation of the elasticity of inter-temporal substitution of a CCAPM model.

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The following paper was conducted with the support of several entrepreneurs and startups from Brazil. The aim of the research was to find out which impact the Business Model Canvas, further abbreviated as BMC, has on technology-oriented startups in Brazil. The first step of the study was identify some general concepts of entrepreneurship, as well as the conditions and environment of the country. Afterwards, it was focused on defining and comparing different business model tools and concepts to the BMC. After the literature review and meeting with several professionals in the area of entrepreneurship and startups, a questionnaire was formulated in order to conduct the qualitative study and identify the main impact of the tool. The questionnaire was answered by ten startups. In order to check the validity and credibility of the research outcomes, theory and investigator triangulation was used. As a result, the usage of the BMC could be evaluated by obtaining the outcomes and the theory, which showed that Brazilian tech startups are using Osterwalder’s model for the reason of idea creation and testing, validating and pivoting their business model. Interestingly, the research revealed that the entrepreneurs are using the tool often not in the traditional way of printing it, but rather applying it as a thinking approach. Besides, the entrepreneurs are focusing mostly on developing a strong Value Proposition, Customer Segment and sustainable Revenue Streams, while afterwards the remaining building blocks are built. Moreover, the research showed that the startups are using also other concepts, such as the Customer Development Process or Build-Measure-Learn Feedback Loop. These methodologies are often applied together with the BMC and helps to identify the most sustainable components of the business idea. Keywords: Business

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Brazil is under political and financial crises where the end seems far away. Because of that, researchers argue that the hotel rooms offered by Rio de Janeiro, built to host the Olympic Games 2016, will be difficult to occupy after the event. It is then necessary for the hotels to understand how guests perceive the service quality in order to adapt to this new era. If guests’ perceptions meet or exceed their expectations, they will be satisfied and will probably return. Thus based on the SERVQUAL approach, this paper aims to study the impact of the service dimensions on the guests’ overall satisfaction at hotels of Rio de Janeiro. Two hotels were considered representative of the city in terms of service quality and customers’ profile. Interviews to the hotel managers were performed, and questionnaires to the guests were administered. Among the five SERVQUAL dimensions – Reliability, Tangibles, Responsiveness, Assurance, and Empathy – the Empathy dimension appears to be the only one that affects the guests’ overall satisfaction. The study could also identify that gender, country of residence, home country and family income have an impact on guests’ satisfaction. This study has no intention of generalization, but rather of refining the theory about services and the SERVQUAL model.

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O objetivo desta dissertação foi estimar a demanda de tratores agrícolas para o mercado brasileiro no triênio 2016-2018, utilizando-se para isto de técnicas de econometria de séries temporais, neste caso, modelos univariados da classe ARIMA e SARIMA e ou multivariados SARIMAX. Justifica-se esta pesquisa quando se observa a indústria de máquinas agrícolas no Brasil, dados os ciclos econômicos e outros fatores exógenos aos fundamentos econômicos da demanda, onde esta enfrenta muitos desafios. Dentre estes, a estimação de demanda se destaca, pois exerce forte impacto, por exemplo, no planejamento e custo de produção de curto e médio prazo, níveis de inventários, na relação com fornecedores de materiais e de mão de obra local, e por consequência na geração de valor para o acionista. Durante a fase de revisão bibliográfica foram encontrados vários trabalhos científicos que abordam o agronegócio e suas diversas áreas de atuação, porém, não foram encontrados trabalhos científicos publicados no Brasil que abordassem a previsão da demanda de tratores agrícolas no Brasil, o que serviu de motivação para agregar conhecimento à academia e valor ao mercado através deste. Concluiu-se, após testes realizados com diversos modelos que estão dispostos no texto e apêndices, que o modelo univariado SARIMA (15,1,1) (1,1,1) cumpriu as premissas estabelecidas nos objetivos específicos para escolha do modelo que melhor se ajusta aos dados, e foi escolhido então, como o modelo para estimação da demanda de tratores agrícolas no Brasil. Os resultados desta pesquisa apontam para uma demanda de tratores agrícolas no Brasil oscilando entre 46.000 e 49.000 unidades ano entre os anos de 2016 e 2018.

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Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.

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The search for efficiency in supply chains has usually focused on logistic optimization aspects. Initiatives like the ECR are an example. This research questions the appropriateness of this focus comparing detailed cost structures of fifteen consumer products, covering five different product categories. It compares supply chains of private label products, presumably more efficient due to closer collaboration between chain members, to national brands supply chains. The major source of cost differences lies in other indirect costs incurred by the national brands and not directly assignable to advertising. Results indicate that a complete reconception of the supply chain, exploring different governance structures offers greater opportunities for cost savings than the logistic aspect in isolation. Research was done in the UK in 1995-1997, but results are only now publishable due to confidentiality agreements

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Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

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This work aims to understand the interaction between competition and network formation in the banking market. Combining Matutes and Padilla (1994) and Matutes and Vives (2000), we build a model of imperfect bank competition for deposits in which an interbank relationship network is a key strategic decision: it affects banks’ profit and risk position. The competition level exerts influence in the banking network structure since it affects the network outcomes. As result, we have that different competition levels imply different network topologies. Specifically, greater competition imply denser networks. Finally, when we allow for the possibility of collusion, the denser network can come out in the least competitive environment.

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We construct a frictionless matching model of the marriage market where women have bidimensional attributes, one continuous (income) and the other dichotomous (home ability). Equilibrium in the marriage market determines intrahousehold allocation of resources and female labor participation. Our model is able to predict partial non-assortative matching, with rich men marrying women with low income but high home ability. We then perform numerical exercises to evaluate the impacts of income taxes in individual welfare and find that there is considerable divergence in the female labor participation response to taxes between the short run and the long run.

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Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

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The Import Substitution Process in Latin Amer ica was an attempt to enhance GDP growth and productivity by rising trade barriers upon capital-intensive products. Our main goal is to analyze how an increase in import tariff on a particular type of good affects the production choices and trade pattern of an economy. We develop an extension of the dynamic Heckscher-Ohlin model – a combination of a static two goods, two-factor Heckscher-Ohlin model and a two-sector growth model – allowing for import tariff. We then calibrate the closed economy model to the US. The results show that the economy will produce less of both consumption and investment goods under autarky for low and high levels of capital stock per worker. We also find that total GDP may be lower under free trade in comparison to autarky.

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This study aimed to determine if accounting and governance indicators are relevant to foresee the stages of financial stress of companies by using a logistic regression. With the formation of two samples was possible to verify if the inclusion of insolvency data defined by cash flow shortage events were relevant to increase model capacity for prediction of insolvency. The remaining insolvency stages were judicial reorganization and bankruptcy. The control sample is formed by healthy companies, from the same sector and size. The period of analysis includes events that occurred between January 2008 and March 2016. The main variables that showed significant results to predict insolvency states, a year before the event happens, were Profitability, Efficiency and Payment Capacity indicators. The Governance indicator was only significant to predict insolvency arising from judicial reorganization and bankruptcy. Among the models studied, the most accurate model presented total correctness capacity of 88,7%, classifying correctly 88% of solvent companies and 89,3% of insolvent companies. The results indicate the usefulness of financial indicators of Payment Capacity, Efficiency and Profitability, as well as the Governance variable, to discriminate the insolvency of companies.