Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets

We examine the spillovers of the US subprime crisis to Asian and European economies and in particular to what extent currency and stock markets have been affected by the crisis. Linear and nonlinear dependencies are detected after pairwise and system-wise causality analysis. A new stepwise multivariate filtering approach is implemented after controlling for conditional heteroskedasticity in the raw data and in VAR/VECM residuals using multivariate GARCH models. Significant nonlinear causal linkages persisted even after the application of GARCH-BEKK, CCC-GARCH and DCC-GARCH modelling. This indicates that volatility effects might partly induce nonlinear causality. Perhaps new short-term asset-pricing models could be developed to explain this stylized fact. These results might also have important implications for hedging, trading strategies and financial market regulation.     

Has market concentration fostered on-time performance? A case study of seventy-two U.S. airports

The study compares a multivariate with a quantile regression model to determine whether utilized airport capacity, departure and airborne delays, departure and arrival demand, and market structure explained variations in on-time gate arrivals and arrival delays. In both models, airport departure delays, arrival and departure demand explained variations in the two response variables in prioritized and non-prioritized metroplexes, holding other variables constant. After 2008, the consolidation of the airline industry through mergers coincided with the implementation of NextGen programs, which may have contributed to improvements in on-time performance, especially at prioritized metroplexes where airspace was redesigned.     

An Empirical Investigation of the Effects of Rounding on the SPF Probabilities of Decline and Output Growth Histograms

I consider the possibility that respondents to the Survey of Professional Forecasters round their probability forecasts of the event that real output will decline in the future, as well as their reported output growth probability distributions. I make various plausible assumptions about respondents’ rounding practices, and show how these impinge upon the apparent mismatch between probability forecasts of a decline in output and the probabilities of this event implied by the annual output growth histograms. I find that rounding accounts for about a quarter of the inconsistent pairs of forecasts.     

Too Good to be True? An Analysis of the Options Market's Reactions to Earnings Releases

Using option implied risk neutral return distributions before and after earnings announcements, we study the option market's reaction to extreme events over earnings announcements. While earnings announcements generally reduce short‐term uncertainty about the stock price, very good news does not reduce uncertainty and slightly bad news actually increases uncertainty. We also find that left tail probabilities decrease over earnings releases while right tail probabilities increase. We interpret these findings as evidence of maintained investor expectations that very good news is generally not released during earnings announcements, combined with skepticism in the form of lingering uncertainty at the release of such very good news.     

European farmers and participatory rural appraisal: A systematic literature review on experiences to optimize rural development

Farmers are those who daily supervise and manage rural areas, but still their collaborations with those institutions entitled to decide the transformation of these territories are not managed properly. The experiences of participatory processes with the involvement of farmers are analyzed in many agricultural studies. A systematic review has allowed us to analyse experiences related to 35 participation paths aimed at rural regions’ development. The analysis has been made on the basis of 14 variables describing the path followed and its purpose, the agricultural holding involved and the areas surveyed.The work has the objectives to identify some strengths and weaknesses in the involvement of farmers in decision-making and the strengths and weaknesses of the processes themselves. The review has shown that too often in participatory processes farmers are considered only as a source of information to be used by researchers rather than as active participants in the choices for the protection, management and transformation of the rural territory. An effective participatory rural appraisal requires greater empowerment of farmers. In general, compared to the methods and tools used, farmers are wary of paths that are too complex and prefer the use of low-tech tools. This result can be attributed to the farmers’ demand of direct contact with the researchers to build trust and also to the average age of European farmers, which is pretty high.In participation contexts, it is not possible to establish standardized methods and tools, because each process should be tailored for the community that expresses it. Nevertheless, the work has highlighted the need to establish some minimum principles to avoid considering unsuccessful some participation paths which, in reality, have been only scarcely participated. In the work, these principles have been presented through the development of key questions, to which those who design the path for an effective engagement of agricultural stakeholder must respond: representativeness, empowerment, empirical knowledge, relationships, group type, numerosity and involvement stage.     

An alternative interpretation of the discontinuity in earnings distributions

We show that the asymmetric effects of income taxes and special items for profit and loss firms contribute to a discontinuity at zero in the distribution of earnings. Income taxes draw profit observations towards zero while negative special items pull loss observations away from zero. These earnings components are thus expected to contribute to a discontinuity even in the absence of discretion. We show our results are not an artifact of deflation and that other common components of earnings do not have similar effects on the earnings distribution around zero.

The tactical and strategic value of hedge fund strategies: a cointegration approach

This paper analyzes long-term comovements between hedge fund strategies and traditional asset classes using multivariate cointegration methodology. Since cointegrated assets are tied together over the long run, a portfolio consisting of these assets will have lower long-term volatility. Thus, if the presence of cointegration lowers uncertainty, risk-averse investors should prefer assets that are cointegrated. Long-term (passive) investors can benefit from the knowledge of cointegrating relationships, while the built-in error correction mechanism allows active asset managers to anticipate short-run price movements. The empirical results indicate there is a long-run relationship between specific hedge fund strategies and traditional financial assets. Thus, the benefits of different hedge fund strategies are much less than suggested by correlation analysis and portfolio optimization. However, certain strategies combined with specific stock market segments offer portfolio managers adequate diversification potential, especially in the framework of tactical asset allocation.

The perception of biotechnology in agro-forestry: The opinion of undergraduates and researchers

Genetically modified organisms (GMOs) cropping promoted by different researchers, and the subsequent crisis regarding the safety of food derived from them, has resulted in strong public mistrust towards the authorities, both scientific and political. The aim of this work is to investigate the perception of Italian undergraduates and researchers towards the introduction of GMOs in agro-forestry. The factors determining attitudes towards GMOs were examined by means of 66 questions divided into three units: Knowledge, Opinon, Trust. Anagrafic and socio-cultural information were also analyzed. Data was processed through a multivariate analysis approach. The hierarchical clustering on undergraduates and researchers allowed to distinguish clusters of respondents skilled in biotechnology from those skilled in off-topic disciplines. Principal component analysis and K-means demonstrated that the positive or negative opinion toward GMOs, as for undergraduates, does not depend on their knowledge, but it is associated with the level of trust in the institutions. On the contrary, for researchers, it is related to their expertise level, without any linkage to trust in the institutions. This type of study may represent a key step for understanding the social, economic and scientific components underlying the choices of citizens, communities and society about GMOs.     

Forward-neutral valuation relationships for options on zero coupon bonds

This paper extends the literature on Risk-Neutral Valuation Relationships (RNVRs) to derive valuation formulae for options on zero coupon bonds when interest rates are stochastic. We develop Forward-Neutral Valuation Relationships (FNVRs) for the transformed-bounded random walk class. Our transformed-bounded random walk family of forward bond price processes implies that (i) the prices of the zero coupon bonds are bounded below at zero and above at one, and (ii) negative continuously compounded interest rates are ruled out. FNVRs are frameworks for option pricing, where the forward prices of the options are martingales independent of the market prices of risk. We illustrate the generality and flexibility of our approach with models that yield several new closed-form solutions for call and put options on discount bonds.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.