Non-profit institutions in an input-output framework

This paper discusses the conceptual treatment of non-profit institutions in the US input-output (I-O) accounts prepared by the Bureau of Economic Analysis, describes the sources and methods used to identify and measure the output of non-profits by I-O industry, and analyses the published benchmark I-O data for 1982 identifying output attributable to non-profits. In the context of the I-O framework, which is detailed and comprehensive, some conceptual and statistical questions associated with the treatment of non-profits are identified and discussed. These issues of definition, scope and measurement are particularly pertinent in light of the recommendations in the 1993 international System of National Accounts on sectoring and on presentation of flows.The author wishes to acknowledge the helpful comments of colleagues at the Bureau of Economic Analysis and other participants in the Workshop, as well as those of two anonymous reviewers. The views expressed in this paper are those of the author's own. They do not necessarily represent the views of the Bureau of Economic Analysis and the US Department of Commerce.     

The Effect of Neglecting Correlations When Propagating Uncertainty and Estimating the Population Distribution of Risk

Interest in examining both the uncertainty and variability in environmental health risk assessments has led to increased use of methods for propagating uncertainty. While a variety of approaches have been described, the advent of both powerful personal computers and commercially available simulation software have led to increased use of Monte Carlo simulation. Although most analysts and regulators are encouraged by these developments, some are concerned that Monte Carlo analysis is being applied uncritically. The validity of any analysis is contingent on the validity of the inputs to the analysis. In the propagation of uncertainty or variability, it is essential that the statistical distribution of input variables are properly specified. Furthermore, any dependencies among the input variables must be considered in the analysis. In light of the potential difficulty in specifying dependencies among input variables, it is useful to consider whether there exist rules of thumb as to when correlations can be safely ignored (i.e., when little overall precision is gained by an additional effort to improve upon an estimation of correlation). We make use of well-known error propagation formulas to develop expressions intended to aid the analyst in situations wherein normally and lognormally distributed variables are linearly correlated.     

Recycling in multi-family dwellings: Increasing participation and decreasing contamination

This study explored the promotion of recycling in multi-family dwellings. An experimental design investigated four behavior change techniques: biweekly postcards giving specific feedback to each dwelling unit as to quantity and contamination of the recyclables, newsletters giving general information on recycling and the amount recycled by the city as a whole, written pledges committing households to recycle for a specified period, and volunteer coordinators who distributed information and answered questions from residents. The effectiveness of these techniques was compared against that of a control group. The findings suggest that volunteer coordinators are not an effective intervention technique in multi-family dwellings, and that feedback and commitment techniques are useful mainly for managing contamination in medium sized complexes. The data also suggest that the size of a multi-family dwelling complex significantly affects the amount of recyclables collected and the level of contamination. Smaller complexes with less than ten units recycled up to three times the amount on a per unit basis as complexes with more units. Smaller units also had fewer problems with contamination in their recyclables. Several explanations are offered for the poor participation and performance in larger complexes.     

Are Cohort Mortality Rates Autocorrelated?

In this paper the author examines the proposition that heterogeneity in individual frailty leads to autocorrelation in cohort mortality rates. A simple model is used to construct analytic expressions for the covariance of cohort mortality rates at different ages under a number of alternative assumptions about the stochastic process generating shocks in mortality. The model then is used to construct a procedure that uses correlations in cohort mortality rates to estimate the extent of heterogeneity in a population without relying on strong assumptions about the distribution of frailty or the shape of the underlying hazard. The procedure then is used to show that cohort mortality data from France are consistent with a generalized random-effects model in which frailty is gamma-distributed.     

Migration and mortality: the experience of birthplace groups in Australia

"Wide diversity exists in the mortality experience of different birthplace groups in Australia, and this also occurs with respect to their cause of death profiles. Most migrant groups experience lower mortality in Australia than in their country of origin, and most experience lower mortality than the Australian-born population. In the latter case the main [groups] are the Scots, Irish, Poles, South Pacific Islanders, Scandinavian men and North American women. Exceptionally high levels of survival occur among Greeks and Italians in Australia. The lower risk of mortality from heart disease is a principal reason for the deficit between observed and expected deaths of most migrant groups in Australia." The analysis is based on deaths of those aged 15-74 by birthplace, as recorded by the Australian Bureau of Statistics in the years 1980, 1981, and 1982.     

A test of the characteristic function and the Harsanyi function in N-person normal form sidepayment games

This paper reports the results of a laboratory experiment investigating sidepayment games represented in normal form. Attempts to predict payoff allocations via the application of solution concepts (such as the Shapley value or the nucleolus) encounter a problem in games of this form, because the game must first be transformed into some other form. Commonly, this other form is a set function defined over coalitions, such as the von Neumann-Morgenstern characteristic function. Because there are numerous possible transformations, the question arises as to which one provides the most accurate basis for prediction of payoffs.The laboratory experiment tested three such transformations - the mixed strategy characteristic function, the pure strategy characteristic function, and the Harsanyi threat function. Payoff predictions from two solution concepts (Shapley value, nucleolus) were computed on the basis of each of these transformations, making a total of six theories under test.Results of the study show, in general, that payoff predictions based on the Harsanyi threat function and on the mixed strategy characteristic function were more accurate than those based on the pure strategy characteristic function. The most accurate theories were the Shapley value computed from the Harsanyi function, the nucleolus computed from the Harsanyi function, and the Shapley value computed from the mixed strategy characteristic function. Less accurate were the nucleolus computed from the mixed strategy characteristic function and both the nucleolus and the Shapley value computed from the pure strategy characteristic function.This research was supported by grants SOC-7726932 and SES-8319322 from the National Science Foundation. The authors express appreciation to Yat-Tuck See, Jyh-Jen Horng Shiau, and Raymond Wong for assistance in computer programming, and to Jennifer Brandt, Young C. Choi, David C. Dettman, Laurel Dettman, Stephen B. Geisheker, Irving J. Ginsberg, Mike P. Griffin, Kimberly Ihm, Todd Isaacson, Christy Kinney, Mary Kohl, Sue Pope, Tammy Schmieden, Jill Schwarze, Susan Winter, and Kenneth Yuen for assistance in data collection and analysis.     

Spouses as Co-Therapists: “Style” Variables and Implications for Patient-Therapist Matching*

The self-report responses of 24 spouse (M) and 24 non-spouse (NM) professional co-therapist pairs were compared on a variety of in-therapy behaviors. The therapist groups were also divided into experienced (E) and inexperienced (IE) co-therapist pairs. Results indicated that, in general, M co-therapists, and particularly E-M co-therapists, were significantly more alike in self-described in-therapy behaviors than NM co-therapists. M therapists reported significantly more congruence in activity levels and quality of “feeling responsiveness” than NM therapists. These results are discussed in terms of the advantages and disadvantages of the co-therapist “united front” likely to be perceived by patients of spouse co-therapists. General implications for matching patients and co-therapists are considered     

Avoiding the valley of death in educating strategists

Billions of dollars and hundreds of millions of hours are invested every year in executive education. However, much of this investment dies in a familiar “Valley of Death” (VoD) wherein what is learned in the classroom is not applied when the strategist returns back to work. Based on 30 in-depth interviews and live observation, we investigate the architecture of an executive education program designed to avoid the VoD. In the observed program, senior partners of a strategy consulting firm, and their key strategist clients, are brought together to co-learn strategy associated with scenario planning, and, at the same time, improve their ongoing business relations. We find that adopting a “paired learning structure” and utilizing “live case content” results in “group-level co-learning” (or the co-production of knowledge) that, participants report, avoids the VoD. This research contributes to the scholarship on learning architecture in executive education by establishing linkages to the literature on client-partner relationships, modelling the student, and service co-production in knowledge-intensive organizations, and, in the end, provides a blueprint that professional service firms and business schools, seeking to produce more value for their participants, can jointly emulate.     

The Social Networks of Leaders in More or Less Viable Communities Six Years Later: A Research Note1

Abstract Using 1995 data, this study re-examines the social networks of leaders in five more and less viable rural communities in Missouri which were originally studied in 1989 (O'Brien et al. 1991; O'Brien and Hassinger 1992). In the six year period between the 1989 and 1995 surveys, four of the five communities were impacted by major events, including the introduction of corporate hog production in two places and flooding in two others. However, despite these events, there is a high degree of continuity in the relative viability scores of the five places in the two surveys. Leaders in more viable places continue to work with a larger number of fellow leaders and to be more involved in community development organizations than their counterparts in less viable places. These findings show the importance of social capital for rural community viability.