41 resultados para earnings volatility


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The flexible-price two-country monetary model is extended to include a consumption externality with habit persistence. Two methodologies are employed to explore this model's ability to generate volatile and persistent exchange rates. In the first, actual data is used for the exogenous driving processes. In the second, the model is simulated using estimated forcing processes. The theory, in both cases, is capable of explaining the high volatility and persistence of real and nominal exchange rates as well as the high correlation between real and nominal rates. © 2007 Elsevier B.V. All rights reserved.

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This paper investigates if benchmark African equity indices exhibit the stylized facts reported for financial time-series returns. The returns distributions of the Africa All-Share, Large, Medium and Small Company Indices were found to be leptokurtotic, had fat-tails, over time experienced volatility clustering and exhibited long memory in volatility. Both the All-Share and Large Company Indices were found to exhibit leverage effects. In contrast, positive shocks had a greater impact on future volatility for the Small Company Index which implies a reverse leverage effect. This finding could reflect a bull/bubble market for small capitalisation stocks in Africa.

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State aid - Tax exemption on earnings from exports - Recovery

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The paper extends Blackburn and Galindev's (Economics Letters, Vol. 79 (2003), pp. 417-421) stochastic growth model in which productivity growth entails both external and internal learning behaviour with a constant relative risk aversion utility function and productivity shocks. Consequently, the relationship between long-term growth and short-term volatility depends not only on the relative importance of each learning mechanism but also on a parameter measuring individuals' attitude towards risk.

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Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

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This paper examines the impact of minimum wages on earnings and employment in selected branches of the retail-trade sector, 1990-2005, using county-level data on employment and a panel regression framework that allows for county-specific trends in sectoral outcomes. We focus on specific subsectors within retail trade that are identified as particularly low-wage. We find little evidence of disemployment effects once we allow for geographic-specific trends. Indeed, in many sectors the evidence points to modest (but robust) positive employment effects. (C) 2009 Elsevier B.V. All rights reserved.

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Using matched employer-employee data from the German LIAB for 2001, the authors found that German works councils are in general associated with higher earnings, even after accounting for establishment- and worker heterogeneity. Works Council wage premia exceed those of collective bargaining and are higher, in fact, where both institutions are present in the workplace. The authors also found evidence indicating that works councils benefit women relative to men and appear to favor foreign, east-German, and service-sector workers as well. Separate evidence from quantile regressions suggests that the conjunction of works council presence and collective bargaining is important to the narrowing process. In smaller plants even the presence of a works council markup depends on the coexistence of the works council entity With the machinery of collective bargaining.

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We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

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Changes to software requirements not only pose a risk to the successful delivery of software applications but also provide opportunity for improved usability and value. Increased understanding of the causes and consequences of change can support requirements management and also make progress towards the goal of change anticipation. This paper presents the results of two case studies that address objectives arising from that ultimate goal. The first case study evaluated the potential of a change source taxonomy containing the elements ‘market’, ‘organisation’, ‘vision’, ‘specification’, and ‘solution’ to provide a meaningful basis for change classification and measurement. The second case study investigated whether the requirements attributes of novelty, complexity, and dependency correlated with requirements volatility. While insufficiency of data in the first case study precluded an investigation of changes arising due to the change source of ‘market’, for the remainder of the change sources, results indicate a significant difference in cost, value to the customer and management considerations. Findings show that higher cost and value changes arose more often from ‘organisation’ and ‘vision’ sources; these changes also generally involved the co-operation of more stakeholder groups and were considered to be less controllable than changes arising from the ‘specification’ or ‘solution’ sources. Results from the second case study indicate that only ‘requirements dependency’ is consistently correlated with volatility and that changes coming from each change source affect different groups of requirements. We conclude that the taxonomy can provide a meaningful means of change classification, but that a single requirement attribute is insufficient for change prediction. A theoretical causal account of requirements change is drawn from the implications of the combined results of the two case studies.

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Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they overestimate or underestimate affiliate activity varies systematically with host-country characteristics. First, most FDI into countries that serve as tax havens generate no actual productive activity; thus FDI stocks in such countries overestimate affiliate activity. Second, FDI stocks do not include locally raised external funds, funds widely used in countries with well-developed financial markets or volatile exchange rates, resulting in an underestimation of affiliate activity in such countries. Finally, the extent to which FDI translates into affiliate activity increases with affiliate labor productivity, so in countries where labor is more productive, FDI stocks also result in an underestimation of affiliate activity. We test these hypotheses by first regressing affiliate value-added and affiliate sales on FDI stocks to calculate a country-specific mismatch, and then by regressing this mismatch on a host country's tax haven status, level of financial market development, exchange rate volatility, and affiliate labor productivity. All hypotheses are supported, implying that FDI stocks are a biased measure of MNE affiliate activity, and hence that the results of FDI-data-based studies of such activity need to be reconsidered. [ABSTRACT FROM AUTHOR]

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We report four repetitions of Falk and Kosfeld's (Am. Econ. Rev. 96(5):1611-1630, 2006) low and medium control treatments with 476 subjects. Each repetition employs a sample drawn from a standard subject pool of students and demographics vary across samples. We largely confirm the existence of hidden costs of control but, contrary to the original study, hidden costs of control are usually not substantial enough to significantly undermine the effectiveness of economic incentives. Our subjects were asked, at the end of the experimental session, to complete a questionnaire in which they had to state their work motivation in hypothetical scenarios. Our questionnaires are identical to the ones administered in Falk and Kosfeld's (Am. Econ. Rev. 96(5):1611-1630, 2006) questionnaire study. In contrast to the game play data, our questionnaire data are similar to those of the original questionnaire study. In an attempt to solve this puzzle, we report an extension with 228 subjects where performance-contingent earnings are absent i.e. both principals and agents are paid according to a flat participation fee. We observe that hidden costs significantly outweigh benefits of control under hypothetical incentives.

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Quantification and speciation of volatile selenium (Se) fluxes in remote areas has not been feasible previously, due to the absence of a simple and easily transportable trapping technique that preserves speciation. This paper presents a chemo-trapping method with nitric acid (HNO3) for volatile Se species, which preserves speciation of trapped compounds. The recovery and speciation of dimethylselenide (DMSe) and dimethyl diselenide (DMDSe) entrained through both concentrated nitric acid and hydrogen peroxide (H2O2) were compared by HPLC-ICP-MS and HPLC-HG-AFS analyses. It was demonstrated that trap reproducibility was better for nitric acid and a recovery of 65.2 +/- 1.9% for DMSe and 81.3 +/- 3.9% for DMDSe was found in nitric acid traps. HPLC-ES-MS identified dimethyl selenoxide (DMSeO) as the trapped product of DMSe. Methylseleninic acid (MSA) was identified to be the single product of DMDSe trapping. These oxidized derivatives have a high stability and low volatility, which makes nitric acid a highly attractive trapping liquid for volatile Se species and enables reconstruction of the speciation of those species. The presented trapping method is simple, quantifiable, reproducible, and robust and can potentially be applied to qualitatively and quantitatively study Se volatilization in a wide range of natural environments.

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We explore the potential of data from EU-SILC (Statistics on Income and Living Conditions) for the enlarged European Union for the study of low pay and its relationship to household poverty and vulnerability. Limitations of the earnings data currently available mean the analysis covers only 14 of these countries. For employees who are not low paid, income poverty is seen to be rare. The low paid face a much higher risk of being in a household below relative income poverty thresholds, ranging from 7 per cent in Belgium and the Netherlands up to 1718 per cent in Austria, Estonia and Lithuania. The likelihood of their being in a poor household is clearly linked to gender, age and social class. In most of the countries only a minority of low-paid individuals are in vulnerable households.

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In this paper we seek to shed light on the mismatch between income poverty and deprivation through a comparative and dynamic analysis of both forms of disadvantage. By extending analysis over five waves of the ECHP we are able to take into account the key dimensions characterizing poverty profiles overtime. Our conclusions turn out to be remarkably stable across countries. While persistent income poverty measures are systematically related to both cross-sectional and longitudinal measures of deprivation, the scale of mismatch is no less at the latter than at the former level. There is some evidence that although rates of volatility for income and deprivation measures are roughly similar, the processes of change themselves are somewhat different. Further light is shed on the underlying processes by cross-classifying the forms of deprivation. Those exposed to both types of deprivation are differentiated from others in terms of need and resource variables. Conclusions relating to the socio-demographic influences on risk levels are influenced by choice and combination of indicators. The results of our analysis confirm the need to devote considerably more attention than heretofore to the analysis of multi-dimensional poverty dynamics.