Combining Quantitative and Qualitative Measures of Uncertainty in Model-Based Environmental Assessment: The NUSAP System

This article discusses recent experiences with the Numeral Unit Spread Assessment Pedigree (NUSAP) system for multidimensional uncertainty assessment, based on four case studies that vary in complexity. We show that the NUSAP method is applicable not only to relatively simple calculation schemes but also to complex models in a meaningful way and that NUSAP is useful to assess not only parameter uncertainty but also (model) assumptions. A diagnostic diagram can be used to synthesize results of quantitative analysis of parameter sensitivity and qualitative review (pedigree analysis) of parameter strength. It provides an analytic tool to prioritize uncertainties according to quantitative and qualitative insights in the limitations of available knowledge. We show that extension of the pedigree scheme to include societal dimensions of uncertainty, such as problem framing and value-laden assumptions, further promotes reflexivity and collective learning. When used in a deliberative setting, NUSAP pedigree assessment has the potential to foster a deeper social debate and a negotiated management of complex environmental problems.     

MULTIPLE IMPUTATION OF INCOMPLETE CATEGORICAL DATA USING LATENT CLASS ANALYSIS

We propose using latent class analysis as an alternative to log-linear analysis for the multiple imputation of incomplete categorical data. Similar to log-linear models, latent class models can be used to describe complex association structures between the variables used in the imputation model. However, unlike log-linear models, latent class models can be used to build large imputation models containing more than a few categorical variables. To obtain imputations reflecting uncertainty about the unknown model parameters, we use a nonparametric bootstrap procedure as an alternative to the more common full Bayesian approach. The proposed multiple imputation method, which is implemented in Latent GOLD software for latent class analysis, is illustrated with two examples. In a simulated data example, we compare the new method to well-established methods such as maximum likelihood estimation with incomplete data and multiple imputation using a saturated log-linear model. This example shows that the proposed method yields unbiased parameter estimates and standard errors. The second example concerns an application using a typical social sciences data set. It contains 79 variables that are all included in the imputation model. The proposed method is especially useful for such large data sets because standard methods for dealing with missing data in categorical variables break down when the number of variables is so large.     

Social Indicators and Living Conditions in the Netherlands

The Dutch Social en Cultural Planning Office(SCP) monitors social changes and socialservices, evaluates social policies, givesinformation about expected developments in thefuture and gives recommendations for furtherpolicy. Key issues are the assessment ofeconomic, demographic and social changes andthe influence of these factors on the socialand living conditions of the population. TheSCP uses social and economic indicators toexamine these developments. Besidesresearching specific themes (such as socialexclusion, the consequences of long-termunemployment, the social position of theelderly and use, costs and productivity ofsocial services) the SCP has developed anoverall monitoring tool for the livingconditions: the living conditions index (LCI).Nowadays the index is composed of indicatorswhich reflect conditions in eight areas:housing, health, consumer durables, leisureactivity, sport activity, socialparticipation, mobility and holiday. In thefuture, the SCP will attempt to develop aconceptual model that will link the livingconditions index to other social indices likelivability (housing and level of services),poverty and socioeconomic deprivation.     

Log-Multiplicative Association Models As Latent Variable Models For Nominal and/or Ordinal Data

Associations between multiple discrete measures are often due to collapsing over other variables. When the variables collapsed over are unobserved and continuous, log-multiplicative association models, including log-linear models with linear-by-linear interactions for ordinal categorical data and extensions of Goodman's (1979, 1985) RC(M) association model for multiple nominal and/or ordinal categorical variables, can be used to study the relationship between the observed discrete variables and the unobserved continuous ones, and to study the unobserved variables. The derivation and use of log-multiplicative association models as latent variable models for discrete variables are presented in this paper. The models are based on graphical models for discrete and continuous variables where the variables follow a conditional Gaussian distribution. The models have many desirable properties, including having schematic or graphical representations of the system of observed and unobserved variables, the log-multiplicative models can be read from the graphs, and estimates of the means, variances, and covariances of the latent variables given values on the observed variables are a function of the log-multiplicative model parameters. To illustrate some of the advantageous aspects of these models, two examples are presented. In one example, responses to items from the General Social Survey (Davis and Smith 1996) are modeled, and in the other example, panel data from two groups (Coleman 1964) are analyzed.     

Efficiency of Large Double Auctions

We consider large double auctions with private values. Values need be neither symmetric nor independent. Multiple units may be owned or desired. Participation may be stochastic. We introduce a very mild notion of “a little independence.” We prove that all nontrivial equilibria of auctions that satisfy this notion are asymptotically efficient. For any α>0, inefficiency disappears at rate 1/n^2‐α.     

Positive class compromise in globalized production? The Freedom of Association Protocol in the Indonesian sportswear industry

This article investigates the role of voluntary initiatives (VIs) as nongovernmental systems of labour regulation in global value chains (GVCs). To identify the conditions conducive to a more active role for labour in VIs, the authors apply Wright's (2000) theory of the factors enabling positive class compromise to a VI implemented in the Indonesian sportswear industry and extend it to the more complex realities of GVCs. They conclude that if VIs are to create conditions under which decent work can be strengthened, the involvement of strong local labour organizations is required while producers' and/or buyers' dependence on workers' cooperation acts as a catalyst.     

Supply and Demand Factors in the Fertility Decline in Matlab, Bangladesh in 1977–1999

A model family planningprogramme started as a component of areproductive and child health project in partof Matlab (the Intervention area), a rural areaof Bangladesh, in 1977 while another part ofMatlab served as a comparison area. Thepaper analyses data from a vital registrationsystem, censuses and sample surveys, and usesboth cross-sectional and longitudinaltechniques of analysis. The supply factoralone, i.e., the model family planningprogramme, contributes substantially to theobserved decline in fertility in theIntervention area. Of the several demandfactors (indicators of socio-economic status)studied, women's education has the largestimpact on the fertility decline. A veryimportant role in the fertility decline isplayed by changes in attitudes towardsfeasibility and acceptability of birth control.The overall conclusion is that not only thesupply factor, but also demand factorscontribute to the fertility decline observed inthe Intervention area. Due to limitations instudy design and data, we cannot provide aprecise, quantitative answer to the question onthe specific contributions of both types offactors.     

A method for applying cultural theory in the study of organizations

This research note proposes a method for determining the relative intensity of cultural theory's four ways of life within a concrete organization. The development of such a method is useful for the testing of hypotheses concerning concrete organizations that can be derived from cultural theory. The method is illustrated in an empirical test of a hypothesis regarding the occurrence of unethical behaviour within public‐sector organizations.