The Unemployment Volatility Puzzle: Is Wage Stickiness the Answer?

I discuss the failure of the canonical search and matching model to match the cyclical volatility in the job finding rate. I show that job creation in the model is influenced by wages in new matches. I summarize microeconometric evidence and find that wages in new matches are volatile and consistent with the model's key predictions. Therefore, explanations of the unemployment volatility puzzle have to preserve the cyclical volatility of wages. I discuss a modification of the model, based on fixed matching costs, that can increase cyclical unemployment volatility and is consistent with wage flexibility in new matches.     

Variational Bayes with synthetic likelihood

Synthetic likelihood is an attractive approach to likelihood-free inference when an approximately Gaussian summary statistic for the data, informative for inference about the parameters, is available. The synthetic likelihood method derives an approximate likelihood function from a plug-in normal density estimate for the summary statistic, with plug-in mean and covariance matrix obtained by Monte Carlo simulation from the model. In this article, we develop alternatives to Markov chain Monte Carlo implementations of Bayesian synthetic likelihoods with reduced computational overheads. Our approach uses stochastic gradient variational inference methods for posterior approximation in the synthetic likelihood context, employing unbiased estimates of the log likelihood. We compare the new method with a related likelihood-free variational inference technique in the literature, while at the same time improving the implementation of that approach in a number of ways. These new algorithms are feasible to implement in situations which are challenging for conventional approximate Bayesian computation methods, in terms of the dimensionality of the parameter and summary statistic.     

Group Training in Family Therapy—The Student's Perspective*

This paper examines the experience of learning family therapy in a group training model from the trainees perspective. Five significant aspects of this learning experience are discussed. Supervision of family therapy and training within a group setting, multiple supervision, training with a peer co-therapist, using audio-visual feedback in group supervision of family therapy, and the impact on the trainee of doing family therapy for the first time. The trainees found that their learning experience was enhanced by this training approach. (Editors Note: The program referred to in this paper was described in Stier, Serena & Goldenberg, Irene, Training Issues in Family Therapy, Journal of Marriage and Family Counseling, 1975, 1, 63–68.     

Likely (and Unlikely) Voters and the Assessment of Campaign Dynamics

Only in recent years has the "likely voter" technology beenextended to polls well in advance of an election. In the caseof the 2000 U.S. presidential election, CNN/USA Today/Galluptracking polls indicated considerable fluctuations in likelyvoter preferences, greater than among the larger pool of registeredvoters surveyed. This article explores how Gallup’s likelyvoter model exaggerates the reported volatility of voter preferencesduring the campaign. Much of the reported variation in candidatepreference reported by Gallup in that election is not due toactual voter shifts in preference but rather to changes in thecomposition of Gallup’s likely voter pool. The findingshighlight dangers of relying on samples of likely voters whenpolling well before Election Day.     

The influence of gender and ethnicity on judgments of culpability in a domestic violence scenario

Using an experimental analog design, in this study we examined 503 European American, African American, and Latino undergraduate students' responses to a domestic violence scenario in which the ethnicity and gender of the perpetrator were manipulated. Results indicated that participants perceived perpetration of domestic assault significantly more criminal when committed by a man than when committed by a woman. That finding was robust across European Americans, African Americans, and Latinos and was expressed by both genders. Also, European American participants expressed significantly more criticism toward African American perpetrators of assault than they did toward European American and Latino perpetrators of the exact offense, suggestive of racial bias consistent with stereotypes about African Americans being excessively aggressive. Finally, Latino participants expressed significantly more sympathy toward women who assault their husbands than toward assaulting husbands. Implications of the findings are discussed.     

Implementierung von organisationsinternen Coaching-Programmen

Implementation of internal coaching programs in organizationsThe implementation of internal coaching in organizations requires a long-term preparation. A short-term realization and prompt outcomes of such large programs are not to be expected. The best qualifications of an internal coach is unprofitable, if the conditions of an implementation of such coaching programs are not prepared exactly. Further more, the coach has to make a lot of preparing work, e.g. to organize information meetings, to establish and to co-ordinate a pool of internal and external coaches. There are extensive requirements of an internal coaching, and before an implementation it is to calculate, whether the necessary structures are given or may be established.     

Quantitative Analysis of Variability and Uncertainty with Known Measurement Error: Methodology and Case Study

The appearance of measurement error in exposure and risk factor data potentially affects any inferences regarding variability and uncertainty because the distribution representing the observed data set deviates from the distribution that represents an error-free data set. A methodology for improving the characterization of variability and uncertainty with known measurement errors in data is demonstrated in this article based on an observed data set, known measurement error, and a measurement-error model. A practical method for constructing an error-free data set is presented and a numerical method based upon bootstrap pairs, incorporating two-dimensional Monte Carlo simulation, is introduced to address uncertainty arising from measurement error in selected statistics. When measurement error is a large source of uncertainty, substantial differences between the distribution representing variability of the observed data set and the distribution representing variability of the error-free data set will occur. Furthermore, the shape and range of the probability bands for uncertainty differ between the observed and error-free data set. Failure to separately characterize contributions from random sampling error and measurement error will lead to bias in the variability and uncertainty estimates. However, a key finding is that total uncertainty in mean can be properly quantified even if measurement and random sampling errors cannot be separated. An empirical case study is used to illustrate the application of the methodology.     

An analysis of females convicted of sex crime in the state of Florida

The phenomenon of female sex offenders has been poorly explored in the scientific literature. In particular, little exploration of possible subtypes of female offenders has been conducted. In the current study, 279 female sexual offenders convicted of a total of 940 separate criminal offenses were examined using hierarchical cluster analysis. Results indicated that female sexual offenders tended to engage in behaviors that fell within three distinct patterns differing according to perpetrator characteristics, victim age, and the use of force. These results suggest that female sexual offenders are a heterogeneous population and a more in-depth investigation may be necessary.