943 resultados para dummy variables
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Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientadora: Professora Doutora Maria Clara Ribeiro Coorientadora: Mestre Maria Luísa Verdelho Alves
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Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.
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When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.
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Canonical correspondence analysis and redundancy analysis are two methods of constrained ordination regularly used in the analysis of ecological data when several response variables (for example, species abundances) are related linearly to several explanatory variables (for example, environmental variables, spatial positions of samples). In this report I demonstrate the advantages of the fuzzy coding of explanatory variables: first, nonlinear relationships can be diagnosed; second, more variance in the responses can be explained; and third, in the presence of categorical explanatory variables (for example, years, regions) the interpretation of the resulting triplot ordination is unified because all explanatory variables are measured at a categorical level.
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The purpose of the thesis is to analyze whether the returns of general stock market indices of Estonia, Latvia and Lithuania follow the random walk hypothesis (RWH), and in addition, whether they are consistent with the weak-form efficiency criterion. Also the existence of the day-of-the-week anomaly is examined in the same regional markets. The data consists of daily closing quotes of the OMX Tallinn, Riga and Vilnius total return indices for the sample period from January 3, 2000 to August 28, 2009. Moreover, the full sample period is also divided into two sub-periods. The RWH is tested by applying three quantitative methods (i.e. the Augmented Dickey-Fuller unit root test, serial correlation test and non-parametric runs test). Ordinary Least Squares (OLS) regression with dummy variables is employed to detect the day-of-the-week anomalies. The random walk hypothesis (RWH) is rejected in the Estonian and Lithuanian stock markets. The Latvian stock market exhibits more efficient behaviour, although some evidence of inefficiency is also found, mostly during the first sub-period from 2000 to 2004. Day-of-the-week anomalies are detected on every stock market examined, though no longer during the later sub-period.
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This paper examines cyclical behaviour in commercial property values over the period 1956 to 1996, using a structural times series (unobserved components) approach. The influence of the transition to short rent reviews during the late 1960s and the short and long-term impacts of the 1974 and 1990 property crashes are also incorporated into the analysis, via dummy variables. It is found that once these variables are taken into account a fairly regular cyclical pattern can be discerned, with a period of about 7.8 years. Furthermore, the 1974 and 1990 property crashes are shown to have had a major long-term impact on property value growth (presumably via their influence on investors' expectations).
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This paper examines the evidence for a day-of-the-week effect in five Southeast Asian stock markets: South Korea, Malaysia, the Philippines, Taiwan and Thailand. Findings indicate significant seasonality for three of the five markets. Market risk, proxied by the return on the FTA World Price Index, is not sufficient to explain this calendar anomaly. Although an extension of the risk-return equation to incorporate interactive seasonal dummy variables can explain some significant day-of-the-week effects, market risk alone appears insufficient to characterize this phenomenon.
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Market timing performance of mutual funds is usually evaluated with linear models with dummy variables which allow for the beta coefficient of CAPM to vary across two regimes: bullish and bearish market excess returns. Managers, however, use their predictions of the state of nature to deÞne whether to carry low or high beta portfolios instead of the observed ones. Our approach here is to take this into account and model market timing as a switching regime in a way similar to Hamilton s Markov-switching GNP model. We then build a measure of market timing success and apply it to simulated and real world data.
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Best corporate governance practices published in the primers of Brazilian Securities and Exchange Commission and the Brazilian Corporate Governance Institute promote board independence as much as possible, as a way to increase the effectiveness of governance mechanism (Sanzovo, 2010). Therefore, this paper aims at understanding if what the managerial literature portraits as being self-evident - stricter governance, better performance - can be observed in actual evidence. The question answered is: do companies with a stricter control and monitoring system perform better than others? The method applied in this paper consists on comparing 116 companies in respect to the their independence level between top management team and board directors– being that measured by four parameters, namely, the percentage of independent outsiders in the board, the separation of CEO and chairman, the adoption of contingent compensation and the percentage of institutional investors in the ownership structure – and their financial return measured in terms return on assets (ROA) from the latest Quarterly Earnings release of 2012. From the 534 companies listed in the Stock Exchange of Sao Paulo – Bovespa – 116 were selected due to their level of corporate governance. The title “Novo Mercado” refers to the superior level of governance level within companies listed in Bovespa, as they have to follow specific criteria to assure shareholders ´protection (BM&F, 2011). Regression analyses were conducted in order to reveal the correlation level between two selected variables. The results from the regression analysis were the following: the correlation between each parameter and ROA was 10.26%; the second regression analysis conducted measured the correlation between the independence level of top management team vis-à-vis board directors – namely, CEO relative power - and ROA, leading to a multiple R of 5.45%. Understanding that the scale is a simplification of the reality, the second part of the analysis transforms all the four parameters into dummy variables, excluding what could be called as an arbitrary scale. The ultimate result from this paper led to a multiple R of 28.44%, which implies that the combination of the variables are still not enough to translate the complex reality of organizations. Nonetheless, an important finding can be taken from this paper: two variables (percentage of outside directors and percentage of institutional investor ownership) are significant in the regression, with p-value lower than 10% and with negative coefficients. In other words, counter affirming what the literature very often portraits as being self-evident – stricter governance leads to higher performance – this paper has provided evidences to believe that the increase in the formal governance structure trough outside directors in the board and ownership by institutional investor might actually lead to worse performance. The section limitations and suggestions for future researches presents some reasons explaining why, although supported by strong theoretical background, this paper faced some challenging methodological assumptions, precluding categorical statements about the level of governance – measured by four selected parameters – and the financial return in terms of financial on assets.
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Medimos a validade da paridade descoberta de juros – PDJ - para o mercado brasileiro no período de janeiro de 2010 a julho de 2014. Testamos a equação clássica da PDJ usando o Método dos Mínimos Quadrados Ordinários. Após a estimação dos parâmetros, aplicamos o Teste de Wald e verificamos que a paridade descoberta de juros não foi validada. Estendemos a equação tradicional da PDJ para uma especificação alternativa que captura medidas de risco Brasil e de alteração na liquidez internacional. Especificamente, acrescentamos três variáveis de controle: duas variáveis dummy que capturam condições de liquidez externa e o índice de commoditie CRB, que captura o risco Brasil. Com a especificação alternativa, a hipótese de que os retornos das taxas de juros em Real, dolarizadas, são iguais aos retornos da taxas de juros contratadas em dólares, ambas sujeitas ao risco Brasil, não foi rejeitada. Em complemento à análise das taxas representativas do mercado brasileiro, procurou-se avaliar a predominância da PDJ nas operações de swap cambial realizadas pela Vale S.A.. Para tanto, a série de taxa de juros em dólares do mercado brasileiro foi substituída pela taxa em dólar dos swaps contratados pela Vale. Os resultados encontrados demonstram que, quando comparado ao comportamento do mercado, as taxas em dólares da VALE são mais sensíveis às variações das taxas em Reais.
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Nesta dissertação foi analisada se há uma relação significante entre estruturas de governança (estrutura e composição de conselho) e financial distress. Este trabalho focou neste tema porque os estudos acadêmicos em governança corporativa e sua relação com financial distress ainda são pouco explorados. Além disso, o tema tem relevância no mundo corporativo, pois entender quais estruturas e composições de conselho seriam mais eficientes para evitar financial distress é interessante para diversos stakeholders, principalmente para os acionistas e os credores. Para verificar a existência dessa relação, foram utilizados dados de empresas brasileiras de capital aberto e foram desenvolvidos modelos logit de financial distress. Sendo a variável resposta financial distress, partiu-se de um modelo base com variáveis financeiras de controle e, por etapas, foram adicionadas novos determinantes e combinações dessas variáveis para montar modelos intermediários. Por fim, o modelo final contou com todas as variáveis explicativas mais relevantes. As variáveis de estudo podem ser classificadas em variáveis de estrutura de governança (DUA, GOV e COF), qualidade do conselho (QUA) e estrutura de propriedade (PRO1 e PRO2). Os modelos base utilizados foram: Daily e Dalton (1994a) e um próprio, desenvolvido para modelar melhor financial distress e sua relação com as variáveis de estrutura de governança. Nos diversos modelos testados foram encontradas relações significativas no percentual de conselheiros dependentes (GOV), percentual de conselheiros da elite educacional (QUA), percentual de ações discriminadas (PRO1) e percentual de ações de acionista estatal relevante (PRO2). Portanto, não se descartam as hipóteses de que mais conselheiros dependentes, menos conselheiros da elite educacional e estrutura de propriedade menos concentrada contribuem para uma situação de financial distress futura. Entretanto, as variáveis dummy de dualidade (DUA) e de conselho fiscal (COF) não apresentaram significância estatística.
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Nesta dissertação foi analisada se há uma relação significante entre estruturas de governança (estrutura e composição de conselho) e financial distress. Este trabalho focou neste tema porque os estudos acadêmicos em governança corporativa e sua relação com financial distress ainda são pouco explorados. Além disso, o tema tem relevância no mundo corporativo, pois entender quais estruturas e composições de conselho seriam mais eficientes para evitar financial distress é interessante para diversos stakeholders, principalmente para os acionistas e os credores. Para verificar a existência dessa relação, foram utilizados dados de empresas brasileiras de capital aberto e foram desenvolvidos modelos logit de financial distress. Sendo a variável resposta financial distress, partiu-se de um modelo base com variáveis financeiras de controle e, por etapas, foram adicionadas novos determinantes e combinações dessas variáveis para montar modelos intermediários. Por fim, o modelo final contou com todas as variáveis explicativas mais relevantes. As variáveis de estudo podem ser classificadas em variáveis de estrutura de governança (DUA, GOV e COF), qualidade do conselho (QUA) e estrutura de propriedade (PRO1 e PRO2). Os modelos base utilizados foram: Daily e Dalton (1994a) e um próprio, desenvolvido para modelar melhor financial distress e sua relação com as variáveis de estrutura de governança. Nos diversos modelos testados foram encontradas relações significativas no percentual de conselheiros dependentes (GOV), percentual de conselheiros da elite educacional (QUA), percentual de ações discriminadas (PRO1) e percentual de ações de acionista estatal relevante (PRO2). Portanto, não se descartam as hipóteses de que mais conselheiros dependentes, menos conselheiros da elite educacional e estrutura de propriedade menos concentrada contribuem para uma situação de financial distress futura. Entretanto, as variáveis dummy de dualidade (DUA) e de conselho fiscal (COF) não apresentaram significância estatística
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In the present global era in which firms choose the location of their plants beyond national borders, location characteristics are important for attracting multinational enterprises (MNEs). The better access to countries with large market is clearly attractive for MNEs. For example, special treatments on tariffs such as the Generalized System of Preferences (GSP) are beneficial for MNEs whose home country does not have such treatments. Not only such country characteristics but also region characteristics (i.e. province-level or city-level ones) matter, particularly in the case that location characteristics differ widely between a nation's regions. The existence of industrial concentration, that is, agglomeration, is a typical regional characteristic. It is with consideration of these country-level and region-level characteristics that MNEs decide their location abroad. A large number of academic studies have investigated in what kinds of countries MNEs locate, i.e. location choice analysis. Employing the usual new economic geography model (i.e. constant elasticity of substitution (CES) utility function, Dixit-Stiglitz monopolistic competition, and ice-berg trade costs), the literature derives the profit function, of which coefficients are estimated using maximum likelihood procedures. Recent studies are as follows: Head, Rise, and Swenson (1999) for Japanese MNEs in the US; Belderbos and Carree (2002) for Japanese MNEs in China; Head and Mayer (2004) for Japanese MNEs in Europe; Disdier and Mayer (2004) for French MNEs in Europe; Castellani and Zanfei (2004) for large MNEs worldwide; Mayer, Mejean, and Nefussi (2007) for French MNEs worldwide; Crozet, Mayer, and Mucchielli (2004) for MNEs in France; and Basile, Castellani, and Zanfei (2008) for MNEs in Europe. At the present time, three main topics can be found in this literature. The first introduces various location elements as independent variables. The above-mentioned new economic geography model usually yields the profit function, which is a function of market size, productive factor prices, price of intermediate goods, and trade costs. As a proxy for the price of intermediate goods, the measure of agglomeration is often used, particularly the number of manufacturing firms. Some studies employ more disaggregated numbers of manufacturing firms, such as the number of manufacturing firms with the same nationality as the firms choosing the location (e.g., Head et al., 1999; Crozet et al., 2004) or the number of firms belonging to the same firm group (e.g., Belderbos and Carree, 2002). As part of trade costs, some investment climate measures have been examined: free trade zones in the US (Head et al., 1999), special economic zones and opening coastal cities in China (Belderbos and Carree, 2002), and Objective 1 structural funds and cohesion funds in Europe (Basile et al., 2008). Second, the validity of proxy variables for location elements is further examined. Head and Mayer (2004) examine the validity of market potential on location choice. They propose the use of two measures: the Harris market potential index (Harris, 1954) and the Krugman-type index used in Redding and Venables (2004). The Harris-type index is simply the sum of distance-weighted real GDP. They employ the Krugman-type market potential index, which is directly derived from the new economic geography model, as it takes into account the extent of competition (i.e. price index) and is constructed using estimators of importing country dummy variables in the well-known gravity equation, as in Redding and Venables (2004). They find that "theory does not pay", in the sense that the Harris market potential outperforms Krugman's market potential in both the magnitude of its coefficient and the fit of the model to be estimated. The third topic explores the substitution of location by examining inclusive values in the nested-logit model. For example, using firm-level data on French investments both in France and abroad over the 1992-2002 period, Mayer et al. (2007) investigate the determinants of location choice and assess empirically whether the domestic economy has been losing attractiveness over the recent period or not. The estimated coefficient for inclusive value is strongly significant and near unity, indicating that the national economy is not different from the rest of the world in terms of substitution patterns. Similarly, Disdier and Mayer (2004) investigate whether French MNEs consider Western and Eastern Europe as two distinct groups of potential host countries by examining the coefficient for the inclusive value in nested-logit estimation. They confirm the relevance of an East-West structure in the country location decision and furthermore show that this relevance decreases over time. The purpose of this paper is to investigate the location choice of Japanese MNEs in Thailand, Cambodia, Laos, Myanmar, and Vietnam, and is closely related to the third topic mentioned above. By examining region-level location choice with the nested-logit model, I investigate the relative importance of not only country characteristics but also region characteristics. Such investigation is invaluable particularly in the case of location choice in those five countries: industrialization remains immature in those countries which have not yet succeeded in attracting enough MNEs, and as a result, it is expected that there are not yet crucial regional variations for MNEs within such a nation, meaning the country characteristics are still relatively important to attract MNEs. To illustrate, in the case of Cambodia and Laos, one of the crucial elements for Japanese MNEs would be that LDC preferential tariff schemes are available for exports from Cambodia and Laos. On the other hand, in the case of Thailand and Vietnam, which have accepted a relatively large number of MNEs and thus raised the extent of regional inequality, regional characteristics such as the existence of agglomeration would become important elements in location choice. Our sample countries seem, therefore, to offer rich variations for analyzing the relative importance between country characteristics and region characteristics. Our empirical strategy has a further advantage. As in the third topic in the location choice literature, the use of the nested-logit model enables us to examine substitution patterns between country-based and region-based location decisions by MNEs in the concerned countries. For example, it is possible to investigate empirically whether Japanese multinational firms consider Thailand/Vietnam and the other three countries as two distinct groups of potential host countries, by examining the inclusive value parameters in nested-logit estimation. In particular, our sample countries all experienced dramatic changes in, for example, economic growth or trade costs reduction during the sample period. Thus, we will find the dramatic dynamics of such substitution patterns. Our rigorous analysis of the relative importance between country characteristics and region characteristics is invaluable from the viewpoint of policy implications. First, while the former characteristics should be improved mainly by central government in each country, there is sometimes room for the improvement of the latter characteristics by even local governments or smaller institutions such as private agencies. Consequently, it becomes important for these smaller institutions to know just how crucial the improvement of region characteristics is for attracting foreign companies. Second, as economies grow, country characteristics become similar among countries. For example, the LCD preferential tariff schemes are available only when a country is less developed. Therefore, it is important particularly for the least developed countries to know what kinds of regional characteristics become important following economic growth; in other words, after their country characteristics become similar to those of the more developed countries. I also incorporate one important characteristic of MNEs, namely, productivity. The well-known Helpman-Melitz-Yeaple model indicates that only firms with higher productivity can afford overseas entry (Helpman et al., 2004). Beyond this argument, there may be some differences in MNEs' productivity among our sample countries and regions. Such differences are important from the viewpoint of "spillover effects" from MNEs, which are one of the most important results for host countries in accepting their entry. The spillover effects are that the presence of inward foreign direct investment (FDI) aises domestic firms' productivity through various channels such as imitation. Such positive effects might be larger in areas with more productive MNEs. Therefore, it becomes important for host countries to know how much productive firms are likely to invest in them. The rest of this paper is organized as follows. Section 2 takes a brief look at the worldwide distribution of Japanese overseas affiliates. Section 3 provides an empirical model to examine their location choice, and lastly, we discuss future works to estimate our model.
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nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model