WEIGHTED‐AVERAGE LEAST SQUARES (WALS): A SURVEY

Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted‐average least squares (WALS) is a recent model‐average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications.     

Mining big data in tourism

Quality & Quantity - Knowledge discovery from various sources of information based on different data types for decision and accurate prediction can be rather complex and costly without a...     

Tax havens compliance with international standards: A temporal perspective

This paper contributes to the debate centering on the fight against aggressive tax avoidance practices through the release of international standards. We develop a model in which identical tax havens decide upon their compliance date while competing for onshore capital. The timing of these decisions depends on the effects of two opposing forces. One force is linked to the tax sensitivity of international capital and the other to the reaction of nearby potential capital. When the former force dominates, asynchronous compliance arises, which occurs even with identical tax havens and perfect information. However, when the latter force dominates, tax havens comply simultaneously. In any case, the loss of tax base within the onshore region is minimized when compliance is simultaneous and occurs at the earliest possible date. Surprisingly, compliance of just one tax haven is not necessarily better than no compliance at all.     

Random Recursive Partitioning: a matching method for the estimation of the average treatment effect

In this paper we introduce the Random Recursive Partitioning (RRP) matching method. RRP generates a proximity matrix which might be useful in econometric applications like average treatment effect estimation. RRP is a Monte Carlo method that randomly generates non‐empty recursive partitions of the data and evaluates the proximity between two observations as the empirical frequency they fall in a same cell of these random partitions over all Monte Carlo replications. From the proximity matrix it is possible to derive both graphical and analytical tools to evaluate the extent of the common support between data sets. The RRP method is “honest” in that it does not match observations “at any cost”: if data sets are separated, the method clearly states it. The match obtained with RRP is invariant under monotonic transformation of the data. Average treatment effect estimators derived from the proximity matrix seem to be competitive compared to more commonly used estimators. RRP method does not require a particular structure of the data and for this reason it can be applied when distances like Mahalanobis or Euclidean are not suitable, in the presence of missing data or when the estimated propensity score is too sensitive to model specifications. Copyright © 2008 John Wiley & Sons, Ltd.     

HUMAN CAPITAL MEASUREMENT: A SURVEY

Abstract After a short history of the concept of human capital (henceforth HC) in economic thought ( Section 1 ), this study presents the two main methods for estimating the value of the stock of HC – the retrospective and prospective one – with a review of the models proposed ( Section 2 ). These methods are linked both to the theory of HC investment as a rational choice ( Section 3 ), the literature analysing the contribution of HC investment to economic growth and the HC estimating method through educational attainment ( Section 4 ). The more recent literature on HC as a latent variable is also assessed ( Section 5 ) and a new method of estimation where HC is seen both as an unknown function of formative indicators and as a ‘latent effect’ underlying earned income is proposed ( Section 6 ). Section 7 concludes.     

Early stage SME bankruptcy: does the local banking market matter?

Small Business Economics - This paper investigates the role of local context, with regard to the effect of local financial development and banking concentration, on a firm’s probability of...     

The new public corruption: Old questions for new challenges

This paper focuses on corruption in public procurement. It describes the contemporary face of corruption by investigating the role of public accountability in the fight against corruption. The paper describes a specific episode of corruption relative to the awarding of government contracts for big events, such as the celebration of the 150th anniversary of Italian unification. Relying on the philosophical insights of Rousseau, Popper, Kant and others, the study suggests the need for enabling a democratic control and constructing a public ethics for the common good.     

Consolidation in the public sector: a cross-country comparison

This article analyses consolidated annual accounts in the public sector in six countries (Sweden, the UK, the USA, Canada, New Zealand and Australia) highlighting the differences and similarities in approaches. The authors also examine international trends and take an in-depth look at the International Public Sector Accounting Standards Board (IPSASB).