A Comparative Note about Estimation of the Fractional Parameter under Additive Outliers

In recent articles, Fajardo et al. (2009 Fajardo Molinares, F., Reisen, V.A., Cribari-Neto, F. (2009). Robust estimation in long-memory processes under additive outliers. Journal of Statistical Planning and Inference 139:2511–2525.[Crossref], [Web of Science ®] , [Google Scholar]) and Reisen and Fajardo (2012) propose an alternative semiparametric estimator of the fractional parameter in ARFIMA models which is robust to the presence of additive outliers. The results are very interesting, however, they use samples of 300 or 800 observations which are rarely found in macroeconomics. In order to perform a comparison, I estimate the fractional parameter using the procedure of Geweke and Porter-Hudak (1983 Geweke, J., Porter-Hudak, S. (1983). The estimation and application of long memory time series model. Journal of Time Series Analysis 4:221–238.[Crossref] , [Google Scholar]) augmented with dummy variables associated with the (previously) detected outliers using the statistic τ_d suggested by Perron and Rodríguez (2003 Perron, P., Rodríguez, G. (2003). Searching for additive outliers in nonstationary time series. Journal of Time Series Analysis 24(2):193–220.[Crossref], [Web of Science ®] , [Google Scholar]). Comparing with Fajardo et al. (2009 Fajardo Molinares, F., Reisen, V.A., Cribari-Neto, F. (2009). Robust estimation in long-memory processes under additive outliers. Journal of Statistical Planning and Inference 139:2511–2525.[Crossref], [Web of Science ®] , [Google Scholar]) and Reisen and Fajardo (2012), I found better results for the mean and bias of the fractional parameter when T = 100 and the results in terms of the standard deviation and the MSE are very similar. However, for higher sample sizes such as 300 or 800, the robust procedure performs better. Empirical applications for seven monthly Latin-American inflation series with very small sample sizes contaminated by additive outliers are discussed.     

On the functional form of temporal discounting: An optimized adaptive test

The tendency to discount the value of future rewards has become one of the best-studied constructs in the behavioral sciences. Although hyperbolic discounting remains the dominant quantitative characterization of this phenomenon, a variety of models have been proposed and consensus around the one that most accurately describes behavior has been elusive. To help bring some clarity to this issue, we propose an Adaptive Design Optimization (ADO) method for fitting and comparing models of temporal discounting. We then conduct an ADO experiment aimed at discriminating among six popular models of temporal discounting. Rather than supporting a single underlying model, our results show that each model is inadequate in some way to describe the full range of behavior exhibited across subjects. The precision of results provided by ADO further identify specific properties of models, such as accommodating both increasing and decreasing impatience, that are mandatory to describe temporal discounting broadly.     

Markov Perfect Industry Dynamics With Many Firms

We propose an approximation method for analyzing Ericson and Pakes (1995)‐style dynamic models of imperfect competition. We define a new equilibrium concept that we call oblivious equilibrium, in which each firm is assumed to make decisions based only on its own state and knowledge of the long‐run average industry state, but where firms ignore current information about competitors' states. The great advantage of oblivious equilibria is that they are much easier to compute than are Markov perfect equilibria. Moreover, we show that, as the market becomes large, if the equilibrium distribution of firm states obeys a certain “light‐tail” condition, then oblivious equilibria closely approximate Markov perfect equilibria. This theorem justifies using oblivious equilibria to analyze Markov perfect industry dynamics in Ericson and Pakes (1995)‐style models with many firms.     

What cultural values influence American public relations practitioners?

This paper advances a cultural approach to public relations research and practice through the extension of Hofstede’s cultural dimensions to Grunig’s models of public relations. This study tested a quantitative instrument that links societal culture, corporate culture, and the public relations communication of American practitioners. Two findings emerged from this study. First, American practitioners continue to practice one-way models of public relations even when their organizations may not dictate one-way communication with publics. And second, public relations practitioners who have collectivistic values tend to practice two-way models of public relations.Gabriel Vasquez is an assistant professor in the School of Communication, University of Houston, TX. Maureen Taylor is an assistant professor in the School of Communication, Information, and Library Studies at Rutgers University, NJ.     

Fitting a Semi-Parametric Mixture Model for Competing Risks in Survival Data

A model for survival analysis is studied that is relevant for samples which are subject to multiple types of failure. In comparison with a more standard approach, through the appropriate use of hazard functions and transition probabilities, the model allows for a more accurate study of cause-specific failure with regard to both the timing and type of failure. A semiparametric specification of a mixture model is employed that is able to adjust for concomitant variables and allows for the assessment of their effects on the probabilities of eventual causes of failure through a generalized logistic model, and their effects on the corresponding conditional hazard functions by employing the Cox proportional hazards model. A carefully formulated estimation procedure is presented that uses an EM algorithm based on a profile likelihood construction. The methods discussed, which could also be used for reliability analysis, are applied to a prostate cancer data set.     

ARE THE DISABLED LESS LOSS AVERSE? EVIDENCE FROM A NATURAL POLICY EXPERIMENT

Research findings show that disabled persons often develop physical and psychological mechanisms to compensate for disabilities. Coping mechanisms may not be limited to the psychophysiological domain and may extend to cognitive bias and loss aversion. In this study, we apply unique microdata from a natural policy experiment to assess the role of loss aversion in home purchase among nondisabled and disabled households. Results of survival analysis indicate that the physically disabled are substantially less loss averse in home purchase. Furthermore, loss aversion varies with other population characteristics and attenuates with degree of disability. Findings provide new evidence of diminished cognitive bias and more rational economic decision‐making among the physically disabled. (JEL D03, C9, R38)     

An empirical assessment of the wage premium for American veterans of World War II

This paper examines U.S. census data from 1960 to 1980 to assess the relative wages of WWII veteran and non-veteran men. Our analysis reveals that a significant portion wage gap between veterans and non-veterans (the “veteran wage premium”) is due primarily to differences in education, work experience and other socioeconomic characteristics. Our findings are consistent with the notion that greater human capital, due perhaps to the selection process for military service, or to the post-war benefits provided by the GI Bill, helped contribute to the remarkable post-war labor market success of American veterans. To a lesser extent, veterans may also have benefited from preferential labor market treatment, or from intangible aspects of military experience that enhanced their returns to earnings-related characteristics.     

The variability of individual charitable giving in the US

Using five-year panel data, this study examines the various dimensions of the variability of individual charitable contributions at all income levels: the variation in the generosity of individuals and the variability of the individuals' giving over a five-year period. The study finds considerable variability of both kinds. One finding is that the variability of generosity is substantially greater at the higher income levels. Another finding is that variability is substantially less pronounced by observing a five-year period of an individual's generosity than by observing annual behaviour. One consequence is that a relatively small proportion of donors account for a large proportion of total giving. The popular reputation of the wealthy for generosity is actually due to the exceptional generosity of a minority rather than widespread generosity among the wealthy. Differences in generosity and variability of giving over time are both more pronounced among high-income donors. Results of the study have implications for research on charitable giving, for predicting the effects of tax policy changes on giving, and for fund-raising.The authors wish to acknowledge the valuable comments of Charles Clotfelter, Susan Rose-Ackerman, Jerry Schiff, Eugene Steuerle and participants in a conference on the non-profit sector at the Center for the Study of Philanthropy and Voluntarism at Duke University. The research was supported in part by Yale University's Institution for Social and Policy Studies (Program on Non-Profit Organisations). The views expressed are those of the authors alone and do not represent the views or policies of the above institutions or individuals.     

A spatiotemporal model for Mexico City ozone levels

Summary.  We consider hourly readings of concentrations of ozone over Mexico City and propose a model for spatial as well as temporal interpolation and prediction. The model is based on a time-varying regression of the observed readings on air temperature. Such a regression requires interpolated values of temperature at locations and times where readings are not available. These are obtained from a time-varying spatiotemporal model that is coupled to the model for the ozone readings. Two location-dependent harmonic components are added to account for the main periodicities that ozone presents during a given day and that are not explained through the covariate. The model incorporates spatial covariance structure for the observations and the parameters that define the harmonic components. Using the dynamic linear model framework, we show how to compute smoothed means and predictive values for ozone. We illustrate the methodology on data from September 1997.