Fiscal decentralisation, efficiency, and growth

Much of the recent worldwide trend towards devolution has been driven by the belief that fiscal decentralization is likely to have a positive effect on government efficiency and economic growth. It is generally assumed that the transfer of powers and resources to lower tiers of government allows for a better matching of public policies to local needs and thus for a better allocation of resources. These factors, in turn, are expected to lead to an improvement in regional economic performance, if subnational authorities shift resources from current to capital expenditures in search of a better response to local needs. This paper tests these assumptions empirically by analysing the evolution of subnational expenditure categories and regional growth in Germany, India, Mexico, Spain, and the USA. We find that, contrary to expectations, decentralisation has coincided in the sample countries with a relative increase in current expenditures at the expense of capital expenditures, which has been associated with lower levels of economic growth in countries where devolution has been driven from above (India and Mexico), but not in those where it has been driven from below (Spain). The paper hypothesises that the differences in legitimacy between the central or federal government and subnational governments in top-down and bottom-up processes of devolution may be at the origin of the diverse capacity to deliver greater allocative and productive efficiency and, eventually, greater economic growth by devolved governments.devolution; fiscal decentralisation; subnational expenditure; economic growth; Germany; India; Mexico; Spain; United States

Bayes factors for evaluating latent monotonicity in polytomous Item response theory models

The assumption of latent monotonicity is made by all common parametric and nonparametric polytomous item response theory models and is crucial for establishing an ordinal level of measurement of the item score. Three forms of latent monotonicity can be distinguished: monotonicity of the cumulative probabilities, of the continuation ratios, and of the adjacent-category ratios. Observable consequences of these different forms of latent monotonicity are derived, and Bayes factor methods for testing these consequences are proposed. These methods allow for the quantification of the evidence both in favor and against the tested property. Both item-level and category-level Bayes factors are considered, and their performance is evaluated using a simulation study. The methods are applied to an empirical example consisting of a 10-item Likert scale to investigate whether a polytomous item scoring rule results in item scores that are of ordinal level measurement

Accounting for individual differences in speed in the discretized signed residual time model

With advances in computerized tests, it has become commonplace to register not just the accuracy of the responses provided to the items, but also the response time. The idea that for each response both response accuracy and response time are indicative of ability has explicitly been incorporated in the signed residual time (SRT) model (Maris & van der Maas, 2012, Psychometrika, 77, 615-633), which assumes that fast correct responses are indicative of a higher level of ability than slow correct responses. While the SRT model allows one to gain more information about ability than is possible based on considering only response accuracy, measurement may be confounded if persons show differences in their response speed that cannot be explained by ability, for example due to differences in response caution. In this paper we propose an adapted version of the SRT model that makes it possible to model person differences in overall speed, while maintaining the idea of the SRT model that the speed at which individual responses are given may be indicative of ability. We propose a two-dimensional SRT model that considers dichotomized response time, which allows one to model differences between fast and slow responses. The model includes both an ability and a speed parameter, and allows one to correct the estimates of ability for possible differences in overall speed. The performance of the model is evaluated through simulation, and the relevance of including the speed parameter is studied in the context of an empirical example from formative educational assessment

Spaces of regionalism and the rescaling of government: a theoretical framework with British cases

In recent decades, regional pressures for stronger autonomy have encouraged a number of central and federal governments around the world to devolve powers and resources downwards to the regional level. The contemporary revival of regionalist movements and the simultaneous tendency towards greater government decentralisation have received considerable academic attention. Most of these contributions present detailed accounts of the processes of regional mobilisation and devolution in a specific region or set of regions. Although these analytical stories tell us a lot about the distinctive aspects of a particular case, they do not, in general, present a coherent theoretical account that would allow us to study the origins of these two interrelated but distinctive trends in a structured way. This thesis aims to make a contribution towards such an account. Building on the literature on political legitimacy and social movements, this study develops a tripartite typology of regionalisms which allows us to analyse and compare the origins of regional autonomy movements across different contexts. In addition, it seeks to show that an actor1based rational choice approach to the process of regionalist accommodation and non1accommodation can help us gain a better understanding of the mechanisms through which such demands influence the shape of the government system. The usefulness of the resulting theoretical framework is demonstrated by applying it to the contemporary history of regionalism and devolution in mainland Britain

Evaluating manifest monotonicity using Bayes factors

The assumption of latent monotonicity in item response theory models for dichotomous data cannot be evaluated directly, but observable consequences such as manifest monotonicity facilitate the assessment of latent monotonicity in real data. Standard methods for evaluating manifest monotonicity typically produce a test statistic that is geared toward falsification, which can only provide indirect support in favor of manifest monotonicity. We propose the use of Bayes factors to quantify the degree of support available in the data in favor of manifest monotonicity or against manifest monotonicity. Through the use of informative hypotheses, this procedure can also be used to determine the support for manifest monotonicity over substantively or statistically relevant alternatives to manifest monotonicity, rendering the procedure highly flexible. The performance of the procedure is evaluated using a simulation study, and the application of the procedure is illustrated using empirical data. Keywords: Bayes factor, essential monotonicity, item response theory, latent monotonicity, manifest monotonicit

Psychometric modelling of longitudinal genetically informative twin data

The often-used A(C)E model that decomposes phenotypic variance into parts due to additive genetic and environmental influences can be extended to a longitudinal model when the trait has been assessed at multiple occasions. This enables inference about the nature (e.g., genetic or environmental) of the covariance among the different measurement points. In the case that the measurement of the phenotype relies on self-report data (e.g., questionnaire data), often, aggregated scores (e.g., sum–scores) are used as a proxy for the phenotype. However, earlier research based on the univariate ACE model that concerns a single measurement occasion has shown that this can lead to an underestimation of heritability and that instead, one should prefer to model the raw item data by integrating an explicit measurement model into the analysis. This has, however, not been translated to the more complex longitudinal case. In this paper, we first present a latent state twin A(C)E model that combines the genetic twin model with an item response theory (IRT) model as well as its specification in a Bayesian framework. Two simulation studies were conducted to investigate 1) how large the bias is when sum–scores are used in the longitudinal A(C)E model and 2) if using the latent twin model can overcome the potential bias. Results of the first simulation study (e.g., AE model) demonstrated that using a sum–score approach leads to underestimated heritability estimates and biased covariance estimates. Surprisingly, the IRT approach also lead to bias, but to a much lesser degree. The amount of bias increased in the second simulation study (e.g., ACE model) under both frameworks, with the IRT approach still being the less biased approach. Since the bias was less severe under the IRT approach than under the sum–score approach and due to other advantages of latent variable modelling, we still advise researcher to adopt the IRT approach. We further illustrate differences between the traditional sum–score approach and the latent state twin A(C)E model by analyzing data of a two-wave twin study, consisting of the answers of 8,016 twins on a scale developed to measure social attitudes related to conservatism

Sociologie en tandheelkunde.

Aan de sociologische aspecten van gebitsgezondheid, gebitsziekten en tandheelkundige gezondheidszorg is tot dusver weinig aandacht besteed. Dit proefschrift is een poging om bij te dragen aan de ontwikkeling van een 'tandheelkundige sociologie'. Bij een groep 14-15-jarige Leeuwarder scholieren en hun moeders werd informatie verzameld over houdingen, kennis en gedrag op het gebied van tandheelkundige zaken; de bevindingen uit dit onderzoek worden in dit proefschrift beschreven. Omdat er bij de scholieren tevens een tandheelkundig onderzoek plaats vond, konden de sociaal-culturele variabelen en de gebitsgegevens aan elkaar worden gekoppeld. ... Zie: Samenvattin