LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.     

Stjepan Metrović and Michel Maffesoli's 'implosive' defence of the Durkheimian tradition: theoretical convergences around Baudrillard's thesis on the 'end' of the social

This paper critically examines Metrovi? and Maffesoli's attempt to understand postmodernity through Émile Durkheim's nonrational link between society, religion and morality. Metrovi? (1991, 1997) and Maffesoli's (1996) work draws upon this emotional element when attempting to refute Baudrillard's (1983) cognitively focused, if implicit, critique of the Durkheimian tradition. Despite their best intentions, Metrovi? and Maffesoli still fail to exploit the partialities of Baudrillard's critique to the full. While both have some appreciation of the link between emotion and religion as found in Durkheim's The Elementary Forms of Religious Life (1912) they, nevertheless, fall short of grasping its full conceptual importance. This leads them to an implicit acceptance of Baudrillard's thesis on the ‘end’ of the social. This pitfall could have been avoided if Metrovi? and Maffesoli had built their respective analyses of the postmodern condition on a closer reading of The Elementary Forms. Reading this text alongside those other insights on emotion and social life as contained within Durkheim and Mauss's Primitive Classification (1903) and Talcott Parsons's subsequent writings on the sociological problem of religion, would have helped to distance the work of Metrovi? and Maffesoli from that of Baudrillard, and allowed them to offer a stronger and more comprehensive defence of the said tradition.     

A semi-parametric approach to robust parameter design

Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic. An essential component of RPD involves the assumption of well estimated models for the process mean and variance. Traditionally, the modeling of the mean and variance has been done parametrically. It is often the case, particularly when modeling the variance, that nonparametric techniques are more appropriate due to the nature of the curvature in the underlying function. Most response surface experiments involve sparse data. In sparse data situations with unusual curvature in the underlying function, nonparametric techniques often result in estimates with problematic variation whereas their parametric counterparts may result in estimates with problematic bias. We propose the use of semi-parametric modeling within the robust design setting, combining parametric and nonparametric functions to improve the quality of both mean and variance model estimation. The proposed method will be illustrated with an example and simulations.     

Refugee Children in Wales: Coping and Adaptation in the Face of Adversity

This article aims to makes a contribution to redressing a methodological and theoretical imbalance in existing research on refugee and asylum‐seeking children. It draws on two qualitative studies from Wales with children and young people. The samples include unaccompanied minors and children living with families as well as both children who are supported in the asylum system and those who have been granted refugee status. The focus on ecological post‐migratory stressors and coping processes that young people identify as being integral to their well‐being and, once granted status, to how they adapt to settlement includes a selective study of some of the sources of resilience referred to in the children's talk. Recognising the interplay between individual and environment leads to a discussion of both personal attributes and collective cultural identities.     

Refined Inference on Long Memory in Realized Volatility

There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter (d) around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about d by higher order theory. Standard asymptotic theory has an O(n^-1/2) error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of o(n^-1/2). The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary (d = 0.5) of nonstationary long memory, and generally confirms earlier findings.     

Consumption and Saving Behavior of Older and Younger Baby Boomers in Korea

The 1998 Korean Survey of Family Income and Expenditures was used to examine the overall consumption and saving behavior of Korean baby boomers and compared the differences in consumption and saving behavior between older and younger boomers. The t -test results indicated that the younger boomers allocated a significantly higher percentage of their expenditures on food away from home, household appliances, transportation and communication than did the older boomers, whereas the older boomers spent higher amounts and allocated larger budget shares on their children's education than did the younger boomers. The results of Ordinary Least-Squares (OLS) regression analysis showed that, holding other factors constant, older boomers not only spent significantly more in the total consumption expenditures and education expenditures, but older boomers also saved significantly less than did younger boomers.     

Diagnostics for dependence within time series extremes

Summary. The analysis of extreme values within a stationary time series entails various assumptions concerning its long- and short-range dependence. We present a range of new diagnostic tools for assessing whether these assumptions are appropriate and for identifying structure within extreme events. These tools are based on tail characteristics of joint survivor functions but can be implemented by using existing estimation methods for extremes of univariate independent and identically distributed variables. Our diagnostic aids are illustrated through theoretical examples, simulation studies and by application to rainfall and exchange rate data. On the basis of these diagnostics we can explain characteristics that are found in the observed extreme events of these series and also gain insight into the properties of events that are more extreme than those observed.     

On the Evolution of Competitive Balance: The Impact of an Increasing Global Search

The Coase theorem maintains that where free-market precepts exist, the allocation of property rights does not impact the distribution of resources. An application to Major League Baseball suggests that institutions such as free agency and the reverse-order amateur draft would not impact player distributions and therefore would not impact competitive balance. The present study finds that the distribution of wins is generally consistent with the precepts of the Coase theorem and therefore suggests a course for those who wish to alter the level of competitive balance: Major League Baseball should increase its focus on expanding the size of its labor pool. (JEL O15 , L83 , C22 )     

UNDERSTANDING THE DECISION TO PARTICIPATE IN A SURVEY

The lack of full participation in sample surveys threatens theinferential value of the survey method. We review a set of conceptualdevelopments and experimental findings that appear to be informativeabout causes of survey participation; offer an integration ofthat work with findings from the more traditional statisticaland survey methodological literature on nonresponse; and, giventhe theoretical structure, deduce potentially promising pathsof research toward the understanding of survey participation.