Daylight saving effect

Kamstra et al. [Kamstra, M.J., Kramer, L.A., Levi, M.D., 2000. Losing sleep at the market: the daylight saving anomaly. The American Economic Review 90, 1005–1011] argue that the mean weekend return following the changes in daylight saving time is less than the mean weekend return throughout the rest of the year. Opposing studies, such as Pinegar [Pinegar, J.M., 2002. Losing sleep at the market: comment. The American Economic Review 92, 1251–1256), reason that the observed results depend upon methodology. We extend the ongoing discussions by providing further evidence for equity markets and bond markets in Germany and across Europe. We further demonstrate that the daylight saving effect does not serve as a potential rationale for the weekend effect.     

The Effects of Screening and Monitoring on Credit Rationing of SMEs

In this paper, we seek to empirically assess which determinants of the capability and incentives of banks to screen and monitor firms are significant in explaining credit rationing to Italian SMEs. After testing for the presence of non‐random selection bias and the potential endogeneity of some determinants of interest, the probit model results we obtain suggest that the average banking size and the multiple banking relationship phenomenon are statistically significant factors affecting credit rationing, presumably through their impact on the aforementioned banks' capability and incentives. Other potential determinants of banks' incentives to monitor and screen, such as local banking competition and firm' capacity to collateralize, are never significant. However, when we split the sample according to the level of competition in credit markets, we find that the estimated marginal effects of all significant determinants of interest are larger in absolute value than those obtained when using the whole sample.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

Soziale Kollektiva

Ohne ZusammenfassungDer vorliegende Aufsatz ist aus einem Vortrag, gehalten in der Nationalökonomischen Gesellschaft, Wien, im Juli 1928, entstanden.     

Issues Facing Small Accounting Practices in Regional North Queensland: An Exploratory Study

Small accounting practices (SAP), most of which are sole principals, are an important part of the accounting profession and the Australian economy. This exploratory study identifies issues and challenges experienced by small accounting principals in Far North Queensland, Australia. The findings generally correspond with previous research, ranking staffing and keeping up to date through professional development as key areas of concern, and also highlighting the expectation gap between SAP principals and their clients. Stress emerged as a major concern for principals, and new areas of possible conflict of interests were uncovered. A number of potential areas for future research, including comparative studies in city and suburban areas, have been identified.     

The welfare effects of disclosure under cognitive dissonance

Atlantic Economic Journal -     

Projecting the future size and health status of the U.S. elderly population

"A projection model based on a multivariate continuous state, stochastic process is presented. The model allows multiple time-varying covariates to be used so parameters can be estimated from time series information on health changes and mortality, and their interaction. Health changes are simulated by altering parameters controlling the age trajectory and diffusion of risk factor means, variances, and covariances....By increasing the information used in projections it may be possible to better (a) anticipate the state of health at extreme ages, (b) forecast changes in health at specific ages over time, (c) stimulate the effects of specific interventions, and (d) determine the sensitivity of outcomes to a range of interventions."