852 resultados para China, Capital structure, Dynamic panel data models, Listed property company


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This study re-examines whether the structure of share ownership by both directors and institutional ownership provides explanation for firm performances. These relationships are modelled and estimated using GMM based dynamic panel data over a period from 1997 to 2001 with a sample of 100 CI components companies listed on Main Board of Malaysia. The findings provide strong evidence of simultaneity between firm performance and managerial ownership. Although an insignificant relationship between firm performance and institutional ownership is~ observed, the institutional holdings provide strong substitute for managerial ownership with a strong negative relationship between managerial ownership and institutional ownership. This is in line with the managerial incentive hypothesis, which suggests that manager's share in the firm's ownership leads to better performance and the monitoring substitute hypothesis, which suggests that managerial ownership could be effectively replaced by institutional ownership.

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This paper estimates the elasticity of substitution of an aggregate production function. The estimating equation is derived from the steady state of a neoclassical growth model. The data comes from the PWT in which different countries face different relative prices of the investment good and exhibit different investment-output ratios. Then, using this variation we estimate the elasticity of substitution. The novelty of our approach is that we use dynamic panel data techniques, which allow us to distinguish between the short and the long run elasticity and handle a host of econometric and substantive issues. In particular we accommodate the possibility that different countries have different total factor productivities and other country specific effects and that such effects are correlated with the regressors. We also accommodate the possibility that the regressors are correlated with the error terms and that shocks to regressors are manifested in future periods. Taking all this into account our estimation resuIts suggest that the Iong run eIasticity of substitution is 0.7, which is Iower than the eIasticity that had been used in previous macro-deveIopment exercises. We show that this lower eIasticity reinforces the power of the neoclassical mo deI to expIain income differences across countries as coming from differential distortions.

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Prior work examining the antecedents of capital structure for small and medium-sized enterprises in emerging markets is limited. This paper sheds light on how the corporate governance mechanisms adopted by firms on the newly established Growth Enterprise Market (GEM) in China influence their use of debt. We find that the financial leverage of GEM firms is positively influenced by executives’ shareholding and their excess cash compensation. Ownership concentration appears to reduce leverage, whereas the percentage of tradable shares increases leverage. In contrast, institutional investors’ shareholding does not influence the level of debt. Traditional factors such as tax and operating cash flow are insignificant in explaining the debt levels among GEM firms.

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This paper investigates whether the effect of political institutions on sectoral economic performance is determined by the level of technological development of industries. Building on previous studies on the linkages among political institutions, technology and economic growth, we employ the dynamic panel Generalized Method of Moments (GMM) estimator for a sample of 4,134 country-industries from 61 industries and 89 countries over the 1990-2010 period. Our main findings suggest that changes of political institutions towards higher levels of democracy, political rights and civil liberties enhance economic growth in technologically developed industries. On the contrary, the same institutional changes might retard economic growth of those industries that are below a technological development threshold. Overall, these results give evidence of a technologically conditioned nature of political institutions to be growth-promoting.

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Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.

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Recent trade literature highlights the importance of export diversification and upgrading in fostering faster and sustainable economic growth. This study investigates the impact of FDI inflow and stock on the level of export diversification and sophistication in host country's export baskets. By utilizing the dynamic panel data model, we find that the five-year lagged FDI inflow correlates positively with both export diversification and sophistication, and FDI stock makes the positive contribution to export sophistication. These findings provide support for the possibility of successful capabilities transfer to and building by local firms. We also find that these positive impacts of FDI exist only in developing countries.

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This paper deals with the determinants of labour out-migration from agriculture across 149 EU regions over the 1990–2008 period. The central aim is to shed light on the role played by payments from the common agricultural policy (CAP) on this important adjustment process. Using static and dynamic panel data estimators, we show that standard neoclassical drivers, like relative income and the relative labour share, represent significant determinants of the intersectoral migration of agricultural labour. Overall, CAP payments contributed significantly to job creation in agriculture, although the magnitude of the economic effect was rather moderate. We also find that pillar I subsidies exerted an effect approximately two times greater than that of pillar II payments.

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Dissertação de Mestrado apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação de Doutora Alcina Augusta Sena Portugal Dias

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The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

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One of the most disputable matters in the theory of finance has been the theory of capital structure. The seminal contributions of Modigliani and Miller (1958, 1963) gave rise to a multitude of studies and debates. Since the initial spark, the financial literature has offered two competing theories of financing decision: the trade-off theory and the pecking order theory. The trade-off theory suggests that firms have an optimal capital structure balancing the benefits and costs of debt. The pecking order theory approaches the firm capital structure from information asymmetry perspective and assumes a hierarchy of financing, with firms using first internal funds, followed by debt and as a last resort equity. This thesis analyses the trade-off and pecking order theories and their predictions on a panel data consisting 78 Finnish firms listed on the OMX Helsinki stock exchange. Estimations are performed for the period 2003–2012. The data is collected from Datastream system and consists of financial statement data. A number of capital structure characteristics are identified: firm size, profitability, firm growth opportunities, risk, asset tangibility and taxes, speed of adjustment and financial deficit. A regression analysis is used to examine the effects of the firm characteristics on capitals structure. The regression models were formed based on the relevant theories. The general capital structure model is estimated with fixed effects estimator. Additionally, dynamic models play an important role in several areas of corporate finance, but with the combination of fixed effects and lagged dependent variables the model estimation is more complicated. A dynamic partial adjustment model is estimated using Arellano and Bond (1991) first-differencing generalized method of moments, the ordinary least squares and fixed effects estimators. The results for Finnish listed firms show support for the predictions of profitability, firm size and non-debt tax shields. However, no conclusive support for the pecking-order theory is found. However, the effect of pecking order cannot be fully ignored and it is concluded that instead of being substitutes the trade-off and pecking order theory appear to complement each other. For the partial adjustment model the results show that Finnish listed firms adjust towards their target capital structure with a speed of 29% a year using book debt ratio.

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This paper uses a panel data-fixed effect approach and data collected from Chinese public manufacturing firms between 1999 and 2011 to investigate the impacts of business life cycle stages on capital structure. We find that cash flow patterns capture more information on business life cycle stages than firm age and have a stronger impact on capital structure decision-making. We also find that the adjustment speed of capital structure varies significantly across life cycle stages and that non-sequential transitions over life cycle stages play an important role in the determination of capital structure. Our study indicates that it is important for policy-makers to ensure that products and financial markets are well-balanced.

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Using a newly developed integrated indicator system with entropy weighting, we analyzed the panel data of 577 recorded disasters in 30 provinces of China from 1985–2011 to identify their links with the subsequent economic growth. Meteorological disasters promote economic growth through human capital instead of physical capital. Geological disasters did not trigger local economic growth from 1999–2011. Generally, natural disasters overall had no significant impact on economic growth from 1985–1998. Thus, human capital reinvestment should be the aim in managing recoveries, and it should be used to regenerate the local economy based on long-term sustainable development.

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The paper examines the capital structure adjustment dynamics of listed non-financial corporations in seven east Asian countries before, during and after the crisis of 1997–1998. Our methodology allows for speeds of adjustment to vary, not only among firms, but also over time, distinguishing between cases of sudden and smooth adjustment.Whereas, compared with firms in the least affected countries, average leverages were much higher, generalized method-ofmoments analysis of the Worldscope panel data suggests that average speeds of adjustment were lower in the worst affected countries. This holds also for the severely financially distressed firms in some worst affected countries, though the trend reversed in the post-crisis period. These findings have important implications for the regulatory environment as well as access to market finance.

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The uncertainty of the future of a firm has to be modelled and incorporated into the evaluation of companies outside their explicit period of analysis, i.e., in the continuing or terminal value considered within valuation models. However, there is a multiplicity of factors that influence the continuing value of businesses which are not currently being considered within valuation models. In fact, ignoring these factors may cause significant errors of judgment, which can lead models to values of goodwill or badwill, far from the substantial value of the inherent assets. Consequently, these results provided will be markedly different from market values. So, why not consider alternative models incorporating life expectancy of companies, as well as the influence of other attributes of the company in order to get a smoother adjustment between market price and valuation methods? This study aims to provide a contribution towards this area, having as its main objective the analysis of potential determinants of firm value in the long term. Using a sample of 714 listed companies, belonging to 15 European countries, and a panel data for the period between 1992 and 2011, our results show that continuing value cannot be regarded as the current value of a constant or growth perpetuity of a particular attribute of the company, but instead be according to a set of attributes such as free cash flow, net income, the average life expectancy of the company, investment in R&D, capabilities and quality of management, liquidity and financing structure.