NPO Financial Statement Quality: An Empirical Analysis Based on Benford’s Law

In order to assess the accuracy of the figures reported in NPOs’ financial statements, I perform a digital analysis on Belgian non-profit organizations’ financial statements for accounting years 2007 up to 2012. Specifically, I compare observed frequencies for digits in the second-from-the-left position with expected frequencies based on Benford’s Law. Results based on the full sample indicate that observed frequencies strongly conform to Benford’s Law (and thus suggest a high degree of accuracy of the figures reported in NPOs’ financial statements). Nevertheless, I note statistically significant deviations from Benford’s Law (both for the entire distribution and at the individual digit level). The largest deviation is noted for zeroes in the second position (i.e., a significantly positive deviation), which can be explained based on humans’ reliance upon so-called cognitive reference points. Considering different sub-samples, I note that observed deviations from Benford’s Law are largest for the smallest non-profits and those non-profits that rely most heavily on grants and/or donations.     

Threatened plant species in the river ports of Central Europe: a potential for nature conservation

Industrialized areas represent a special group of urbanized areas, but sufficient attention has not been given to them concerning plant species richness and its importance for biodiversity conservation. These sites are considered the main drivers of biological invasions and biotic homogenization on a global scale, but the question of how and to what degree they contribute to biodiversity has yet to be raised. Data for 62 river ports (16 German, 26 Czech, 7 Hungarian, 4 Slovak, and 9 Austrian) on two important Central European waterways (the Elbe-Vltava and Danube waterways) were gathered for 40 years. In total, 1 240 plant species were found. Of these, 371 were classified as threatened and protected, nearly one third of the total number of species found in all of the studied Elbe, Vltava, and Danube ports. Significant differences in the proportion of threatened species in ports and cities were not found. More threatened species were found in the Danube ports than in the other ports, but their numbers fluctuated depending on the size of the port and the region (country). The results showed that the ports must be regarded as special types of species-rich industrial areas; thus, they should not be considered to be only sources of spreading invasive alien species. When planning port development, uniformity and vegetation management that is too intensive should be avoided. Extensively managed open areas and habitat diversity should be maintained.

     

Social innovation and the autoimmunity of employability

The purpose of this article is to examine social innovation in the field of youth employment. It addresses both the shortcomings of supply-side approaches that are balanced towards issues such as employability and the impact of key demand side issues including low pay and precarity. The empirical analysis is based upon interviews with young people in employment or training with social innovations as well as interviews with senior policymakers and practitioners whose remit covers these issues. The study concludes by reflecting upon how the conduct of employability can operate as an autoimmune function.     

Insights from the Evaluation of Past Local Area Population Forecasts

Local area population forecasts have a wide variety of uses in the public and private sectors. But not enough is known about the errors of such forecasts, particularly over the longer term (20 years or more). Understanding past errors is valuable for both forecast producers and users. This paper (i) evaluates the forecast accuracy of past local area population forecasts published by Australian State and Territory Governments over the last 30 years and (ii) illustrates the ways in which past error distributions can be employed to quantify the uncertainty of current forecasts. Population forecasts from the past 30 years were sourced from State and Territory Governments. Estimated resident populations to which the projections were compared were created for the geographical regions of the past projections. The key features of past forecast error patterns are described. Forecast errors mostly confirm earlier findings with regard to the relationship between error and length of projection horizon and population size. The paper then introduces the concept of a forecast ‘shelf life’, which indicates how far into the future a forecast is likely to remain reliable. It also illustrates how past error distributions can be used to create empirical prediction intervals for current forecasts. These two complementary measures provide a simple way of communicating the likely magnitude of error that can be expected with current local area population forecasts.     

Benefits and costs associated with mutual-help community-based recovery homes: The Oxford House model

We used data from a randomized controlled study of Oxford House (OH), a self-run, self-supporting recovery home, to conduct a cost-benefit analysis of the program. Following substance abuse treatment, individuals that were assigned to an OH condition (n = 68) were compared to individuals assigned to a usual care condition (n = 61). Economic cost measures were derived from length of stay at an Oxford House residence, and derived from self-reported measures of inpatient and outpatient treatment utilization. Economic benefit measures were derived from self-reported information on monthly income, days participating in illegal activities, binary responses of alcohol and drug use, and incarceration. Results suggest that OH compared quite favorably to usual care: the net benefit of an OH stay was estimated to be roughly $29,000 per person on average. Bootstrapped standard errors suggested that the net benefit was statistically significant. Costs were incrementally higher under OH, but the benefits in terms of reduced illegal activity, incarceration and substance use substantially outweighed the costs. The positive net benefit for Oxford House is primarily driven by a large difference in illegal activity between OH and usual care participants. Using sensitivity analyses, under more conservative assumptions we still arrived at a net benefit favorable to OH of $17,830 per person.     

Univariate and multivariate models of positive and negative networks: Liking,disliking, and bully–victim relationships

Three relations between elementary school children were investigated: networks of general dislike and bullying were related to networks of general like. These were modeled using multivariate cross-sectional (statistical) network models. Exponential random graph models for a sample of 18 classrooms, numbering 393 students, were summarized using meta-analyses. Results showed (balanced) network structures with positive ties between those who were structurally equivalent in the negative network. Moreover, essential structural parameters for the univariate network structure of positive (general like) and negative (general dislike and bullying) tie networks were identified. Different structures emerged in positive and negative networks. The results provide a starting point for further theoretical and (multiplex) empirical research about negative ties and their interplay with positive ties.     

Norms,status and the dynamics of advice networks: A case study

The issue of the influence of norms on behavior is as old as sociology itself. This paper explores the effect of normative homophily (i.e. “sharing the same normative choices”) on the evolution of the advice network among lay judges in a courthouse. 0020 and 0025 social exchange theory suggests that members select advisors based on the status of the advisor. Additional research shows that members of an organization use similarities with others in ascribed, achieved or inherited characteristics, as well as other kinds of ties, to mitigate the potentially negative effects of this strong status rule. We elaborate and test these theories using data on advisor choice in the Commercial Court of Paris. We use a jurisprudential case about unfair competition (material and “moral” damages), a case that we submitted to all the judges of this court, to test the effect of normative homophily on the selection of advisors, controlling for status effects. Normative homophily is measured by the extent to which two judges are equally “punitive” in awarding damages to plaintiffs. Statistical analyses combine longitudinal advice network data collected among the judges with their normative dispositions. Contrary to what could be expected from conventional sociological theories, we find no pure effect of normative homophily on the choice of advisors. In this case, therefore, sharing the same norms and values does not have, by itself, a mitigating effect and does not contribute to the evolution of the network. We argue that status effects, conformity and alignments on positions of opinion leaders in controversies still provide the best insights into the relationship between norms, structure and behavior.