6,141 research outputs found
Very simple marginal effects in some discrete choice models
I show a simple back-of-the-envelope method for calculating marginal effects in binary choice and count data models. The approach suggested here focuses attention on marginal effects at different points in the distribution of the dependent variable rather than representative points in the joint distribution of the explanatory variables. For binary models, if the mean of the dependent variable is between 0.4 and 0.6 then dividing the logit coefficient by 4 or multiplying the probit coefficient by 0.4 should be moderately accurate.marginal effects, binary choice, count data
Very simple marginal effects in some discrete choice models
I show a simple back-of-the-envelope method for calculating marginal effects in binary choice and count data models. The approach suggested here focuses attention on marginal effects at different points in the distribution of the dependent variable rather than representative points in the joint distribution of the explanatory variables. For binary models, if the mean of the dependent variable is between 0.4 and 0.6 then dividing the logit coefficient by 4 or multiplying the probit coefficient by 0.4 should be moderately accurate.marginal effects, binary choice, count data
The Effect of Payroll Taxes in the Monopoly Union Model - Four Lemmas and a Corollary
This paper models the effect of a simple linear payroll tax in a monopoly union model. Previously derived ambiguous results are given a more intuitive interpretation and conditions under which the effect on wages is unambiguously positive are given. It is shown that after tax wages are invariant to changes in the tax rate.Trade union, wages, payroll tax
Remarks of James E. Denny before the Study Group on Legal Remedies, Commission on Government Procurement
Legalities of patent infringements resulting from government procurement policie
Rating Forecasts for Television Programs
This paper investigates the effect of aggregation and non-linearity in relation to television rating forecasts. Several linear models for aggregated and disaggregated television viewing have appeared in the literature. The current analysis extends this work using an empirical approach. We compare the accuracy of population rating models, segment rating models and individual viewing behaviour models. Linear and non-linear models are fitted using regression, decision trees and neural networks, with a two-stage procedure being used to model network choice and viewing time for the individual viewing behaviour model. The most accurate forecast results are obtained from the non-linear segment rating models.Decision Trees, Disaggregation, Discrete Choice Models, Neural Networks, Rating Benchmarks
ROC and the bounds on tail probabilities via theorems of Dubins and F. Riesz
For independent and in the inequality , we give sharp
lower bounds for unimodal distributions having finite variance, and sharp upper
bounds assuming symmetric densities bounded by a finite constant. The lower
bounds depend on a result of Dubins about extreme points and the upper bounds
depend on a symmetric rearrangement theorem of F. Riesz. The inequality was
motivated by medical imaging: find bounds on the area under the Receiver
Operating Characteristic curve (ROC).Comment: Published in at http://dx.doi.org/10.1214/08-AAP536 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Education Policy Reform and the Return to Schooling from Instrumental Variabes
We exploit an unusual policy reform which had the effect of reducing the direct cost of schooling in Ireland in the early 1970's. This gave rise to an increased level of schooling but with effects that vary across family background. This interaction generates a set of instrumental variables which we use to estimate the return to schooling allowing for the endogeneity of schooling. We find a large and well determined in the rate of return of the order of 11 or 12% substantially higher than the OLS estimates of around 7%.
Bench-to-bedside review: Dealing with increased intensive care unit staff turnover: a leadership challenge
Critical care leaders frequently must face challenging situations requiring specific leadership and management skills for which they are, not uncommonly, poorly prepared. Such a fictitious scenario was discussed at a Canadian interdisciplinary critical care leadership meeting, whereby increasing intensive care unit (ICU) staff turnover had led to problems with staff recruitment. Participants discussed and proposed solutions to the scenario in a structured format. The results of the discussion are presented. In situations such as this, the ICU leader should first define the core problem, its complexity, its duration and its potential for reversibility. These factors often reside within workload and staff support issues. Some examples of core problems discussed that are frequently associated with poor retention and recruitment are a lack of a positive team culture, a lack of a favorable ICU image, a lack of good working relationships between staff and disciplines, and a lack of specific supportive resources. Several tools or individuals (typically outside the ICU environment) are available to help determine the core problem. Once the core problem is identified, specific solutions can be developed. Such solutions often require originality and flexibility, and must be planned, with specific short-term, medium-term and long-term goals. The ICU leader will need to develop an implementation strategy for these solutions, in which partners who can assist are identified from within the ICU and from outside the ICU. It is important that the leader communicates to all stakeholders frequently as the process moves forward
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