The link between economic and social upgrading in global supply chains: Experiences from the Southern Cone

This article uses nine case studies of global supply chains (GSCs) in Southern Cone countries to explore the extent to which economic and social upgrading are linked and spread from lead firms to their supply chain. While economic and social upgrading are found in lead firm segments throughout the case studies, the impacts on suppliers are varied. Pattern groupings enable the authors to develop a three‐part typology of development in GSCs, in the light of which they consider the roles of public policies, company behaviour and social actors in addressing developmental outcomes for GSC lead firms and suppliers.     

Nonparametric estimation of the link function including variable selection

Nonparametric methods for the estimation of the link function in generalized linear models are able to avoid bias in the regression parameters. But for the estimation of the link typically the full model, which includes all predictors, has been used. When the number of predictors is large these methods fail since the full model cannot be estimated. In the present article a boosting type method is proposed that simultaneously selects predictors and estimates the link function. The method performs quite well in simulations and real data examples.     

Modelling price paths in on-line auctions: smoothing sparse and unevenly sampled curves by using semiparametric mixed models

Summary.  On-line auctions pose many challenges for the empirical researcher, one of which is the effective and reliable modelling of price paths. We propose a novel way of modelling price paths in eBay's on-line auctions by using functional data analysis. One of the practical challenges is that the functional objects are sampled only very sparsely and unevenly. Most approaches rely on smoothing to recover the underlying functional object from the data, which can be difficult if the data are irregularly distributed. We present a new approach that can overcome this challenge. The approach is based on the ideas of mixed models. Specifically, we propose a semiparametric mixed model with boosting to recover the functional object. As well as being able to handle sparse and unevenly distributed data, the model also results in conceptually more meaningful functional objects. In particular, we motivate our method within the framework of eBay's on-line auctions. On-line auctions produce monotonic increasing price curves that are often correlated across auctions. The semiparametric mixed model accounts for this correlation in a parsimonious way. It also manages to capture the underlying monotonic trend in the data without imposing model constraints. Our application shows that the resulting functional objects are conceptually more appealing. Moreover, when used to forecast the outcome of an on-line auction, our approach also results in more accurate price predictions compared with standard approaches. We illustrate our model on a set of 183 closed auctions for Palm M515 personal digital assistants.     

Disclosure Risk and Disclosure Avoidance for Microdata

Under given concrete exogenous conditions, the fraction of identifiable records in a microdata file without positive identifiers such as name and address is estimated. The effect of possible noise in the data, as well as the sample property of microdata files, is taken into account. Using real microdata files, it is shown that there is no risk of disclosure if the information content of characteristics known to the investigator (additional knowledge) is limited. Files with additional knowledge of large information content yield a high risk of disclosure. This can be eliminated only by massive modifications of the data records, which, however, involve large biases for complex statistical evaluations. In this case, the requirement for privacy protection and high-quality data perhaps may be fulfilled only if the linkage of such files with extensive additional knowledge is prevented by appropriate organizational and legal restrictions.     

Using Analysis of Variance and Factor Analysis for the Reduction of High Dimensional Variation in Time Series of Energy Consumption

Summary: In this paper the complexity of high dimensional data with cyclical variation is reduced using analysis of variance and factor analysis. It is shown that the prediction of a small number of main cyclical factors is more useful than forecasting all the time-points separately as it is usually done by seasonal time series models. To give an example for this approach we analyze the electricity demand per quarter of an hour of industrial customers in Germany. The necessity of such predictions results from the liberalization of the German electricity market in 1998 due to legal requirements of the EC in 1996.     

Casino Self- and Forced Excluders’ Gambling Behavior Before and After Exclusion

Casino exclusion programs are intended to prevent or limit gambling-related harm. Although previous research showed that self-exclusion is associated with reduced gambling, it remains unknown whether self- and forced excluded subjects show different patterns of gambling behavior and if exclusion from casino gambling affects all gambling activities. The present study retrospectively investigated (1) the role of voluntariness of exclusion for the first time, and (2) general gambling behavior of excluded individuals before and after exclusion. A total of N = 215 casino excluders (self-excluders: n = 187, forced excluders: n = 28) completed an online survey or a face-to-face interview up to 8 years after enrollment. Self- and forced excluders showed similar rates of abstinence (self-excluders: 19.3%, forced excluders: 28.6%) and reduction (self-excluders: 67.4%, forced excluders: 60.7%), even though forced excluders reported a significantly greater initial gambling intensity compared to self-excluders (e.g., pre-exclusion gambling time; self-excluders: 3.2 days/week, forced excluders: 4.3 days/week). Overall, results indicated that 20.5% of excluders stopped all gambling activities and another 66.5% reduced their gambling. Those who continued gambling significantly reduced this behavior in every segment, except for gambling halls. Findings indicate that self- and forced exclusion are associated with similarly reduced gambling behavior, even in non-excluded segments. However, unchanged gambling in gambling halls emphasizes the importance to implement consistent exclusion programs over all gambling segments.     

Paradoxe Folgen finanzieller Anreize zur Arbeitsaufnahme für die Beschäftigungsstabilität

Financial incentives to work (in-work benefits) are an instrument of labour market policy to motivate the unemployed to re-enter employment. Following neoclassical economic reasoning, such financial incentives should be effective, since the unemployed are expected to maximize financial utility. However, one common empirical finding is that such wage-subsidized employment is rather unstable. Applying Boudons cognitivist model to the ending of wage-subsidized employment the hypotheses are derived that firstly the in-work benefit is interpreted by the employee as a signal for the firm’s violation of the norm of reciprocity and secondly that the employee’s resulting sanctioning behaviour can raise the probability for job terminations. Survey data on in-work benefit recipients is used to test the hypotheses, performing ordered logit and event history analysis in combination with propensity score matching. Results from the empirical analysis support the hypotheses. It is concluded that labour market policy should be based not only on the assumption of economically rational behaviour, if labour market programmes are to be effective.