Why consumers buy lottery tickets when the sun goes down on them. The depleting nature of weather-induced bad moods.

We propose that weather conditions can influence consumers' engagement in lottery play. A longitudinal study on the extent of lottery play in Belgium shows that lottery expenditures are indeed higher after reduced exposure to sunshine, even after controlling for people's inertia, time-varying characteristics of the game, and deterministic seasonal components. The results of a first laboratory study are consistent with these findings, and establish a link between lottery play and negative mood. Subsequent experiments provide evidence that depletion due to active mood regulation attempts, rather than mood repair, is the underlying process for the link between bad weather and lottery play.Belgium; Characteristics; Laboratories; Processes; Regulation; Research; Studies;

Corruption and inequality of wealth amongst the very rich

Corruption may lead to tax evasion and unbalanced favors and this may lead to extraordinary wealth amongst a few. We study for 13 countries 6 years of Forbes rankings data and we examine whether corruption leads to more inequality amongst the wealthiest. When we correct in our panel model for current and one-year lagged competitiveness and GDP growth rates, we find no such effect. In fact, we find that more competitiveness decreases inequality amongst the wealthiest

Trends in de links-rechts oriëntatie van de Nederlandse kiezers 1978-1995

Contains fulltext : 3293.pdf (publisher's version ) (Open Access

Методи оцінки ризиків в інформаційній системі аналізу екологічного стану басейну малої ріки

В інформаційній системі аналізу стану басейну малої ріки запропоновано методи оцінки ризиків на основі імовірнісних та статистичних оцінок, формалізації моделі гри з природою, прогнозування процесів підтоплення земель з використанням ланцюгів Маркова, розглянуто багато критеріальні моделі ризиків.In informational and analytical system of the small rivers’ ecological condition estimation the methods of risks modelling on the basis of likelihood and statistical estimations, formalization of models of game with nature, risk modelling and forecasting processes flooded lands using Markov chains are offered, multicriteria models of risks are considered

Quarterly U.S. unemployment: cycles, seasons and asymmetries

This paper documents three stylized facts for the quarterly unemployment rate in the United States. Firstly, unemployment is asymmetric over the business cycle, i.e. it rises sharply in recessions and it falls slowly in expansions. Secondly, its seasonal fluctuations are not constant across the two business cycle stages in the sense that there is less seasonality in recession periods. Thirdly, the effect of shocks to the unemployment rate in expansions seem transitory, while this effect is permanent in recessions. Some implications of these stylized facts for empirical macroeconomics and seasonal adjustment are discussed

A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces

Background: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term "rebuild" means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders' performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. Methods: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. Results: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. Conclusions: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions

Proof over promise: towards a more inclusive ranking of Dutch academics in Economics & Business

The Dutch Economics top-40, based on publications in ISI listed journals, is - to the best of our knowledge - the oldest ranking of individual academics in Economics and is well accepted in the Dutch academic community. However, this ranking is based on publication volume, rather than on the actual impact of the publications in question. This paper therefore uses two relatively new metrics, the citations per author per year (CAY) metric and the individual annual h-index (hIa) to provide two alternative, citation-based, rankings of Dutch academics in Economics & Business. As a data source, we use Google Scholar instead of ISI to provide a more comprehensive measure of impact, including citations to and from publications in non-ISI listed journals, books, working and conference papers. The resulting rankings are shown to be substantially different from the original ranking based on publications. Just like other research metrics, the CAY or hIa-index should never be used as the sole criterion to evaluate academics. However, we do argue that the hIa-index and the related citations per author per year metric provide an important additional perspective over and above a ranking based on publications in high impact journals alone. Citation-based rankings are also shown to inject a higher level of diversity in terms of age, gender, discipline and academic affiliation and thus appear to be more inclusive of a wider range of scholarship

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases

Forecasting prices of dairy commodities – a comparison of linear and nonlinear models

peer reviewedDairy commodity prices have become more volatile over the last 10–11 yr. The aim of this paper was to produce reliable price forecasts for the most frequently traded dairy commodities. Altogether five linear and nonlinear time series models were applied. The analysis reveals that prices of dairy commodities reached a structural breakpoint in 2006/2007. The results also show that a combination of linear and nonlinear models is useful in forecasting commodity prices. In this study, the price of cheese is the most difficult to forecast, but a simple autoregressive (AR) model performs reasonably well after 12 mo. Similarly, for butter the AR model performs the best, while for skimmed milk powder (Smp), whole milk powder (Wmp) and whey powder (Whp) the nonlinear methods are the most accurate. However, few of the differences between models are significant according to the Diebold–Mariano (DM) test. The findings could be of interest to the whole dairy industry