952 resultados para Economics, Finance


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This thesis comprehensively studies the causes and consequences of corruption in both crosscountry and within-country contexts, mainly focusing on China. The thesis commences by extensively investigating the causes of corruption. Using the standard economic approach, this study finds that in China regions with more anti-corruption efforts, higher education attainment, Anglo-American historic influence, higher openness, more access to media, higher relative wages of government employees, and a greater representation of women in legislature are markedly less corrupt; while the social heterogeneity, deregulation and abundance of resources, substantially breed regional corruption. Moreover, fiscal decentralization is discovered to depress corruption significantly. This study also observes a positive relationship between corruption and the economic development in current China that is mainly driven by the transition to a market economy. Focusing on the influence of political institutions on corruption, the thesis then provides evidence that a high level of political interest helps to reduce corruption within a society, while the effect of democracy upon corruption depends on property rights protection and income distribution. With the social economic approach, however, the thesis presents both cross-country and within-country evidence that the social interaction plays an important role in determining corruption. The thesis then continues by comprehensively evaluating the consequences of corruption in China. The study provides evidence that corruption can simultaneously have both positive and negative effects on economic development. And it also observes that corruption considerably increases the income inequality in China. Furthermore this study finds that corruption in China significantly distorts public expenditures. Local corruption is also observed to substantially reduce FDI in Chinese regions. Finally the study documents that corruption substantially aggravates pollution probably through a loosening of the environmental regulation, and that it also modifies the effects of trade openness and FDI on the stringency of environmental policy. Overall, this thesis adds to the current literature by a number of novel findings concerning both the causes and the consequences of corruption.

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We consider growth and welfare effects of lifetime-uncertainty in an economy with human capital-led endogenous growth. We argue that lifetime uncertainty reduces private incentives to invest in both physical and human capital. Using an overlapping generations framework with finite-lived households we analyze the relevance of government expenditure on health and education to counter such growth-reducing forces. We focus on three different models that differ with respect to the mode of financing of education: (i) both private and public spending, (ii) only public spending, and (iii) only private spending. Results show that models (i) and (iii) outperform model (ii) with respect to long-term growth rates of per capita income, welfare levels and other important macroeconomic indicators. Theoretical predictions of model rankings for these macroeconomic indicators are also supported by observed stylized facts.

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The explanation of social inequalities in education is still a debated issue in economics. Recent empirical studies tend to downplay the potential role of credit constraint. This article tests a different potential explanation of social inequalities in education, specifically that social differences in aspiration level result in different educational choices. Having existed for a long time in the sociology of education, this explanation can be justified if aspiration levels are seen as reference points in a prospect theory framework. In order to test this explanation, this article applies the method of experimental economics to the issue of education choice and behaviour. One hundred and twenty-nine individuals participated in an experiment in which they had to perform a task over 15 stages grouped in three blocks or levels. In order to continue through the experiment, a minimum level of success was required at the end of each level. Rewards were dependent on the final level successfully reached. At the end of each level, participants could either choose to stop and take their reward or to pay a cost to continue further in order to possibly receive higher rewards. To test the impact of aspiration levels, outcomes were either presented as gains or losses relative to an initial sum. In accordance with the theoretical predictions, participants in the loss framing group choose to go further in the experiment. There was also a significant and interesting gender effect in the loss framing treatment, such that males performed better and reached higher levels.

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In 2001, the Malaysian Code on Corporate Governance (MCCG) became an integral part of the Bursa Malaysia Listing Rules, which requires all listed firms to disclose the extent of compliance with the MCCG. Our panel analysis of 440 firms from 1999 to 2002 finds that corporate governance reform in Malaysia has been successful, with a significant improvement in governance practices. The relationship between ownership by the Employees Provident Fund (EPF) and corporate governance has strengthened during the period subsequent to the reform, in line with the lead role taken by the EPF in establishing the Minority Shareholders Watchdog Group. The implementation of MCCG has had a substantial effect on shareholders' wealth, increasing stock prices by an average of about 4.8%. Although there is no evidence that politically connected firms perform better, political connections do have a significantly negative effect on corporate governance, which is mitigated by institutional ownership.

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This paper contributes to the recent debate about the role of referees in the home advantage phenomenon. Specifically, it aims to provide a convincing answer to the newly posed question of the existence of individual differences among referees in terms of the home advantage (Boyko, Boyko, & Boyko, 2007; Johnston, 2008). Using multilevel modelling on a large and representative dataset we find that (1) the home advantage effect differs significantly among referees, and (2) this relationship is moderated by the size of the crowd. These new results suggest that a part of the home advantage is due to the effect of the crowd on the referees, and that some referees are more prone to be influenced by the crowd than others. This provides strong evidence to indicate that referees are a significant contributing factor to the home advantage. The implications of these findings are discussed both in terms of the relevant social psychological research, and with respect to the selection, assessment, and training of referees.

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We analyze the puzzling behavior of the volatility of individual stock returns over the past few decades. The literature has provided many different explanations to the trend in volatility and this paper tests the viability of the different explanations. Virtually all current theoretical arguments that are provided for the trend in the average level of volatility over time lend themselves to explanations about the difference in volatility levels between firms in the cross-section. We therefore focus separately on the cross-sectional and time-series explanatory power of the different proxies. We fail to find a proxy that is able to explain both dimensions well. In particular, we find that Cao et al. [Cao, C., Simin, T.T., Zhao, J., 2008. Can growth options explain the trend in idiosyncratic risk? Review of Financial Studies 21, 2599–2633] market-to-book ratio tracks average volatility levels well, but has no cross-sectional explanatory power. On the other hand, the low-price proxy suggested by Brandt et al. [Brandt, M.W., Brav, A., Graham, J.R., Kumar, A., 2010. The idiosyncratic volatility puzzle: time trend or speculative episodes. Review of Financial Studies 23, 863–899] has much cross-sectional explanatory power, but has virtually no time-series explanatory power. We also find that the different proxies do not explain the trend in volatility in the period prior to 1995 (R-squared of virtually zero), but explain rather well the trend in volatility at the turn of the Millennium (1995–2005).

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Durland and McCurdy [Durland, J.M., McCurdy, T.H., 1994. Duration-dependent transitions in a Markov model of US GNP growth. Journal of Business and Economic Statistics 12, 279–288] investigated the issue of duration dependence in US business cycle phases using a Markov regime-switching approach, introduced by Hamilton [Hamilton, J., 1989. A new approach to the analysis of time series and the business cycle. Econometrica 57, 357–384] and extended to the case of variable transition parameters by Filardo [Filardo, A.J., 1994. Business cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299–308]. In Durland and McCurdy’s model duration alone was used as an explanatory variable of the transition probabilities. They found that recessions were duration dependent whilst expansions were not. In this paper, we explicitly incorporate the widely-accepted US business cycle phase change dates as determined by the NBER, and use a state-dependent multinomial Logit modelling framework. The model incorporates both duration and movements in two leading indexes – one designed to have a short lead (SLI) and the other designed to have a longer lead (LLI) – as potential explanatory variables. We find that doing so suggests that current duration is not only a significant determinant of transition out of recessions, but that there is some evidence that it is also weakly significant in the case of expansions. Furthermore, we find that SLI has more informational content for the termination of recessions whilst LLI does so for expansions.

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Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into bankruptcy prediction models of capital market data such as excess stock returns and stock return volatility, along with the application of the Black–Scholes–Merton option-pricing model. In this note, we test five key bankruptcy models from the literature using an upto- date data set and find that they each contain unique information regarding the probability of bankruptcy but that their performance varies over time. We build a new model comprising key variables from each of the five models and add a new variable that proxies for the degree of diversification within the firm. The degree of diversification is shown to be negatively associated with the risk of bankruptcy. This more general model outperforms the existing models in a variety of in-sample and out-of-sample tests.

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In dynamic and uncertain environments such as healthcare, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. The uncertainty stems from the unpredictability of users’ operational needs as well as their private incentives to misuse permissions. In Role Based Access Control (RBAC), a user’s legitimate access request may be denied because its need has not been anticipated by the security administrator. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. This paper introduces a novel approach to access control under uncertainty and presents it in the context of RBAC. By taking insights from the field of economics, in particular the insurance literature, we propose a formal model where the value of resources are explicitly defined and an RBAC policy (entailing those predictable access needs) is only used as a reference point to determine the price each user has to pay for access, as opposed to representing hard and fast rules that are always rigidly applied.

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Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.