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Being Good Parents or Being Good Citizens: Dilemmas and Contradictions of Urban Families in Middle‐Class Enclaves and Mixed Neighbourhoods in Germany

In recent years, cities have become ever more attractive to middle‐class families. On the one hand, middle‐class families tend to withdraw into (often newly built) socially homogeneous middle‐class neighbourhoods. On the other hand, they are also known to move into inner‐city and socially mixed areas, thus triggering processes of gentrification. Academic literature has often denounced these housing choices as being either ‘separatist’ or ‘revanchist’, more broadly categorized as strategies of ‘middle‐class disaffiliation’. Although there is a grain of truth in these interpretations, the reality is certainly more complicated. In our research on middle‐class parents’ housing and neighbourhood choices as well as their patterns of neighbourhood use, carried out in each of the two types of residential area mentioned above, we have only very rarely found an explicit desire to draw boundaries that exclude those ‘beneath’ them. We rather argue that the housing choices and neighbourhood‐related activities of middle‐class family households are heavily influenced by the specific dilemmas the interviewees face as (working) urban parents. While a significant number of respondents worry about the social sustainability, justice and cohesion of urban society, they are also concerned about the future prospects of their children. Many find it difficult to reconcile these conflicting normative demands under the prevailing circumstances.     

Improving the performance of random coefficients demand models: The role of optimal instruments

We shed new light on the performance of Berry, Levinsohn and Pakes’ (1995) GMM estimator of the aggregate random coefficient logit model. Based on an extensive Monte Carlo study, we show that the use of Chamberlain’s (1987) optimal instruments overcomes many problems that have recently been documented with standard, non-optimal instruments. Optimal instruments reduce small sample bias, but they prove even more powerful in increasing the estimator’s efficiency and stability. We consider a wide variety of data-generating processes and an empirical application to the automobile market. We also consider the gains of other recent methodological advances when combined with optimal instruments.     

The Economics of Farm Fragmentation: Evidence from Ghana and Rwanda

Farm fragmentation, in which a household operates more thanone separate parcel of land, is a common phenomenon in Sub-SaharanAfrica. Concerned by the perceived costs of fragmented as opposedto consolidated holdings, several countries have implementedland consolidation programs. But these interventions overlookthe benefits that land fragmentation can offer farmers in managingrisk, in overcoming seasonal labor bottlenecks, and in bettermatching soil types with necessary food crops. This articleuses household data from Ghana and Rwanda to discuss the incidenceand causes of fragmentation. It then formally tests the relationbetween fragmentation and land productivity and risk reduction.The conclusion is that consolidation programs are unlikely tolead to significant increases in land productivity and may actuallymake farmers worse off. Policymakers should focus instead onreducing the root causes of fragmentation: inefficiencies inland, labor, credit, and food markets.     

Low price equilibrium in multi-unit auctions: the GSM spectrum auction in Germany

The second–generation (GSM) spectrum auction in Germany is probably the most clear cut example of a low price outcome in a simultaneous ascending-bid multi-unit auction. The present paper gives an account of the events, describes the auction rules and market conditions, and provides a game theoretic explanation of low price equilibrium in simultaneous, ascending-bid multi-unit auctions. In particular, it is shown that in the unique equilibrium that survives iterated elimination of dominated strategies, the efficient allocation is reached at minimum bids.     

Firm heterogeneity, productivity and spatially bounded knowledge externalities

In this paper, we argue that conceptually disentangling the ‘context versus composition’ aspects of regional growth is a multilevel issue. By applying multilevel models (also called random-effects models), we show (1) the importance of considering firm-specific characteristics simultaneously with region-specific characteristics, as we find that a large part of what is traditionally assigned to the impact of the region should be assigned to firm-specific characteristics and (2) that existing single-level methodologies can be problematic, as they are vulnerable to the charge of estimating significance levels that are too liberally assigned and promote exaggerations. This is illustrated empirically by showing that single-level approaches would lead to the conclusion that innovation spillovers are highly significant in a setting of Dutch urban growth differentials, while multilevel analyses shows less liberally assigned significance levels. We conclude that multilevel-effect models better fit research questions that combine firm and spatial characteristics simultaneously, especially because they allow firm-specific characteristics to be differently linked to their regional contexts.     

An Empirical Comparison of the Four Channel Flow Model and Adventure Experience Paradigm

The objective of this study was to conduct empirical comparisons between two models of optimal experience within an on-site whitewater kayaking setting using a modification of the Experience Sampling Method. Four concerns are examined: (1) differences in explanatory power between the four channel flow model and the Adventure Experience Paradigm, (2) convergent validity among measures used to determine conditions within these models, (3) differences among measures of perceived challenge and risk between test times of Class I-V river difficulty, and (4) differences among measures of perceived skill and competence between test times of Class I-V river difficulty. Questionnaires were administered in the Cheat River Canyon in West Virginia to 52 whitewater kayakers at eight sites of various levels of river difficulty. Data were analyzed at the experience level, rather than between subjects, using 409 experience sampling observations. Hypothesis testing, performed with statistical analyses (stepwise regression, correlations, and repeated measures ANOVA), suggested that the explanatory powers of the four channel flow model and Adventure Experience Paradigm were similar and indicated support for convergent and ecological validity of measures used to determine conditions within each of the two models.