Association between gambling harms and game types: Finnish population study

Understanding of the harmfulness of game types is needed when planning harm minimization and prevention strategies. Adult data (N = 3555) from the Finnish Gambling 2015 survey was used to investigate the associations between different game types and gambling-related harms. A negative binomial regression model was used to analyse the effects of demographics, gambling involvement factors, and engaging in different game types on the number of gambling-related harms, which were evaluated by PGSI and SOGS. Age of 18–24, gambling several times a week, high relative expenditure, online gambling and engaging weekly either in scratch games, betting games or slot machine gambling were associated with a higher number of gambling harms. Chasing losses was the most typical harm among online poker players and fast-paced daily lottery game players, while poor self-control was the most typical harm with other game types, although some of the results were not statistically significant. Multiple factors were associated with gambling harms, including young age and gambling intensity. Games that provide a possibility for high-frequency gambling are more linked to harms. Recommendations should be implemented to incorporate effective harm-minimizing strategies in the regulation of specific game types both at the legislative level (provision and supply) and at the public health level.     

Institutions,Incentives and Trade Union Membership

The study investigates the determinants of unionization in a country — Finland — where union density, defined as the number of unionized members divided by the labour force, has risen 60 percentage points in 32 years, from 22 percent in 1960 to 82 percent in 1992. The theoretical framework of the study is based on the background information obtained from surveys inquiring why individuals join a union. The empirical analysis for the period 1962–92 shows that the model is capable of explaining long-run trends in union density in a very satisfactory manner. The results imply that institutional features of the labour market, characterized by the benefit mark-up variable and a dummy variable capturing labour legislation and public policy toward unionization, play an important role in the development of union density. An interesting policy implication of the study is the prediction that union density would fall considerably if earnings-related unemployment allowances were to be cut to the level of the basic unemployment allowances.     

An axiomatic analysis of the Nash equilibrium concept

The purpose of this paper is to analyze axiomatically the Nash equilibrium concept. The class of games under study is a (relatively large) subclass of n-person normal form games. Solutions are correspondences which associate to each game a non empty set of strategy vectors of this game. It is shown that if a solution satisfies the axioms Independence of irrelevant alternatives (IIA) and Individual rationality (IR), then all the strategy vectors in this solution are Nash equilibria. This result holds good also if IR is replaced by Strong individual monotonicity (SIM) or Weak principle of fair compromise (WPFC).     

Study on a resource allocation formula for social services in Finland

This article considers how a specific need-based resource allocation formula for children's day care, income support, child welfare and other social services was developed. The formula is needed for the municipal allocation of state subsidies for social services, and the work was performed for the Ministry of Social Welfare and Health. Cross-sectional data were collected from the 436 Finnish municipalities and 37 small areas within the six largest cities. Because of the simultaneous relationship between supply and demand of services, two-stage least-square estimation and structural equations models were used in the analysis. After the effect of supply was removed from the service utilisation data, group-need factors (municipal variables) were found for these services. The new formula is financially and administratively feasible, transparent and reasonably simple.     

Tests of multinormality based on location vectors and scatter matrices

Classical univariate measures of asymmetry such as Pearson’s (mean-median)/σ or (mean-mode)/σ often measure the standardized distance between two separate location parameters and have been widely used in assessing univariate normality. Similarly, measures of univariate kurtosis are often just ratios of two scale measures. The classical standardized fourth moment and the ratio of the mean deviation to the standard deviation serve as examples. In this paper we consider tests of multinormality which are based on the Mahalanobis distance between two multivariate location vector estimates or on the (matrix) distance between two scatter matrix estimates, respectively. Asymptotic theory is developed to provide approximate null distributions as well as to consider asymptotic efficiencies. Limiting Pitman efficiencies for contiguous sequences of contaminated normal distributions are calculated and the efficiencies are compared to those of the classical tests by Mardia. Simulations are used to compare finite sample efficiencies. The theory is also illustrated by an example.     

Nash implementation and the bargaining problem

We study Nash implementation of the bargaining solutions in a cake sharing set up. We argue that the minimal Pareto optimal, symmetric and Nash implementable SBS is the one inducing all Pareto optimal and midpoint-dominating utility vectors in each state.     

Estimates of regression coefficients based on the sign covariance matrix

Summary. A new estimator of the regression parameters is introduced in a multivariate multiple-regression model in which both the vector of explanatory variables and the vector of response variables are assumed to be random. The affine equivariant estimate matrix is constructed using the sign covariance matrix (SCM) where the sign concept is based on Oja's criterion function. The influence function and asymptotic theory are developed to consider robustness and limiting efficiencies of the SCM regression estimate. The estimate is shown to be consistent with a limiting multinormal distribution. The influence function, as a function of the length of the contamination vector, is shown to be linear in elliptic cases; for the least squares (LS) estimate it is quadratic. The asymptotic relative efficiencies with respect to the LS estimate are given in the multivariate normal as well as the t -distribution cases. The SCM regression estimate is highly efficient in the multivariate normal case and, for heavy-tailed distributions, it performs better than the LS estimate. Simulations are used to consider finite sample efficiencies with similar results. The theory is illustrated with an example.