The marginal propensity to spend on adult children

We examine how much of an extra dollar of parental lifetime resources willultimately be passed on to adult children in the form of inter vivostransfers and bequests. We infer bequests from the stock of wealth late inlife. We use mortality rates and age specific estimates of the response oftransfers and wealth to permanent income to compute the expected presentdiscounted values of these responses to permanent income. Our estimatesimply parents pass on between 2 and 3 cents out of an extra dollar ofexpected lifetime resources in bequests and about 2 cents in transfers.The estimates increase with parental income and are smaller for nonwhites.They imply that about 15 percent of the effect of parental income onlifetime resources of adult children is through transfers and bequestsand about 85 percent is through the intergenerational correlation inearnings, although these estimates are sensitive to assumptions about theintergenerational earnings correlation, taxes, and the number of children.We compare our estimates to the implications of alternative computablebenchmark models of savings behavior in order to assess the likelyimportance of intended bequests for the wealth/income relationship.

Hierarchical location-allocation models for congested systems

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and theirlocations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.

Experiments on substratum roughness, grainsize and volume influence on the motion and spreading of rock avalanches

The main objective of the research is to link granular physics with the modelling of rock avalanches. Laboratory experiments consist to find a convenient granular material, i.e. grainsize and physical behaviour, and testing it on simple slope geometry. When the appropriate sliding material is selected, we attempted to model the debris avalanche and the spreading on a slope with different substratum to understand the relationship between the volume and the reach angle, i.e. angle of the line joining the top of the scar and the end of the deposit. For a better understanding of the mass spreading, the deposits are scanned with a laser scanner. Datasets are compared to see how the grain size and volume influence a debris avalanche. The relationship between the roughness and grainsize of the substratum shows that the spreading of the sliding mass is increased when the roughness of the substratum starts to be equivalent or greater than the grainsize of the flowing mass. The runout distance displays a more complex relationship, because a long runout distance implies that grains are less spread. This means that if the substratum is too rough the distance diminishes, as well if it is too smooth because the effect on the apparent friction decreases. Up to now our findings do not permit to validate any previous model (Melosh, 1987; Bagnold 1956).

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Asset prices and the measurement of wealth and saving

The paper defines concepts of real wealth and saving which take into account the intertemporal index number problem that results from changing interest rates. Unlike conventional measures of real wealth, which are based on the market value of assets and ignore the index number problem, the new measure correctly reflects the changes in the welfare of households over time. An empirically operational approximation to the theoretical measure is provided and applied to US data. A major empirical finding is that US real financial wealth increased strongly in the 1980s, much more than is revealed by the market value of assets.

Eliciting consumers preferences using stated preference discrete choice models: Contingent ranking versus choice experiment

The aim of this paper is twofold: firstly, to carry out a theoreticalreview of the most recent stated preference techniques used foreliciting consumers preferences and, secondly, to compare the empiricalresults of two dierent stated preference discrete choice approaches.They dier in the measurement scale for the dependent variable and,therefore, in the estimation method, despite both using a multinomiallogit. One of the approaches uses a complete ranking of full-profiles(contingent ranking), that is, individuals must rank a set ofalternatives from the most to the least preferred, and the other usesa first-choice rule in which individuals must select the most preferredoption from a choice set (choice experiment). From the results werealize how important the measurement scale for the dependent variablebecomes and, to what extent, procedure invariance is satisfied.

Estimating cross-industry cross-country models using benchmark industry characteristics

International industry data permits testing whether the industry-specific impact of cross-countrydifferences in institutions or policies is consistent with economic theory. Empirical implementationrequires specifying the industry characteristics that determine impact strength. Most of the literature has been using US proxies of the relevant industry characteristics. We show that usingindustry characteristics in a benchmark country as a proxy of the relevant industry characteristicscan result in an attenuation bias or an amplification bias. We also describe circumstances allowingfor an alternative approach that yields consistent estimates. As an application, we reexamine theinfluential conjecture that financial development facilitates the reallocation of capital from decliningto expanding industries.