Economic and Sociological Theories of Individual Charitable Giving: Complementary or Contradictory?

This article first sets out the principles of neoclassical microeconomic analysis and examines the advances in our understanding of individual giving to charitable organizations achieved within this framework of analysis. It then turns to sociology and considers alternative conceptions of sociological analysis, especially rational-action theories and the qualitative tradition. The contribution of these to our understanding of charitable giving is explored. The article concludes that rational-choice sociology can complement economic analyses in two ways but that qualitative sociology is contradictory to the economic approach.     

Flexible regression modeling

The author proposes a new method for flexible regression modeling of multi‐dimensional data, where the regression function is approximated by a linear combination of logistic basis functions. The method is adaptive, selecting simple or more complex models as appropriate. The number, location, and (to some extent) shape of the basis functions are automatically determined from the data. The method is also affine invariant, so accuracy of the fit is not affected by rotation or scaling of the covariates. Squared error and absolute error criteria are both available for estimation. The latter provides a robust estimator of the conditional median function. Computation is relatively fast, particularly for large data sets, so the method is well suited for data mining applications.     

Directional mixture models and optimal estimation of the mixing density

The authors develop consistent nonparametric estimation techniques for the directional mixing density. Classical spherical harmonics are used to adapt Euclidean techniques to this directional environment. Minimax rates of convergence are obtained for rotation ally invariant densities verifying various smoothness conditions. It is found that the differences in smoothness between the Laplace, the Gaussian and the von Mises‐Fisher distributions lead to contrasting inferential conclusions.     

Splines for financial volatility

Summary.  We propose a flexible generalized auto-regressive conditional heteroscedasticity type of model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B -splines of lagged observations and volatilities. Estimation of such a B -spline basis expansion is constructed within the likelihood framework for non-Gaussian observations. As the dimension of the B -spline basis is large, i.e. many parameters, we use regularized and sparse model fitting with a boosting algorithm. Our method is computationally attractive and feasible for large dimensions. We demonstrate its strong predictive potential for financial volatility on simulated and real data, and also in comparison with other approaches, and we present some supporting asymptotic arguments.     

On a paper by kageyama and mohan

Kageyama Mohan (1984) have presented three methods of constructing new incomplete block designs from balanced incomplete block designs, They raise questions about the designs which come from each of their methods, These questions are answered, Another series of group divisible designs is derived as a special case of their second method.     

Is regression adjustment supported by the Neyman model for causal inference?

This paper examines both theoretically and empirically whether the common practice of using OLS multivariate regression models to estimate average treatment effects (ATEs) under experimental designs is justified by the Neyman model for causal inference. Using data from eight large U.S. social policy experiments, the paper finds that estimated standard errors and significance levels for ATE estimators are similar under the OLS and Neyman models when baseline covariates are included in the models, even though theory suggests that this may not have been the case. This occurs primarily because treatment effects do not appear to vary substantially across study subjects.     

Discount-neutral utility models for denumerable time streams

This paper formulates and axiomatizes utility models for denumerable time streams that make no commitment in regard to discounting future outcomes. The models address decision under certainty and decision under risk. Independence assumptions in both contexts lead to additive or multiplicative utilities over time periods that allow unambiguous comparisons of the relative importance of different periods. The models accommodate all patterns of future valuation. This discount-neutral feature is attained by restricting preference comparisons to outcome streams or probability distributions on outcome streams that differ in at most a finite number of periods.     

Simulation model of a predator-prey system comprised ofPhytoseiulus persimilis andTetranychus urticae. II. Model sensitivity to variations in the life history parameters of both species and to variations in the functional response and components of the numerical response

Summary A detailed sensitivity analysis of a model of a predator-prey system comprised ofTetranychus urticae andPhytoseiulus persimilis was performed. The aim was to assess the relative importance of the life history parameters of both species, the functional response, and the components of the numerical response. In addition, the impact of the initial predator-prey ratio and the timing of predator introduction were tested. Results indicated that the most important factors in the system were relative rates of predator and prey development, the time of onset of predator oviposition, and the mode of the predator's oviposition curve. The total oviposition of the predator, the effect of prey consumption on predator oviposition, and predator searching were important under some conditions. Factors of moderate importance were the adult female predator's functional response, total prey oviposition, the mode of the prey's oviposition curve, abiotic mortality of the pre-adult predator, and the effect of prey consumption on predator development and on the immature predator's mortality. Factors of least importance were the variances of the predator's and prey's oviposition curves, the abiotic mortality of the adult predator, the abiotic mortality of the pre-adult and adult prey, the functional response of the nymphal and adult male predators, and the effect of prey consumption on adult predator mortality. The sex ratios had little effect, except when the proportion of female predators was very low. The initial predator-prey ratio and time of predator introduction had significant impacts on system behavior, though the patterns of impact were different.