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on Discrete Choice Models |
| By: | Mishra, SK |
| Abstract: | In this paper we have proposed a method to conduct the ordinal canonical correlation analysis (OCCA) that yields ordinal canonical variates and the coefficient of correlation between them, which is analogous to (and a generalization of) the rank correlation coefficient of Spearman. The ordinal canonical variates are themselves analogous to the canonical variates obtained by the conventional canonical correlation analysis (CCCA). Our proposed method is suitable to deal with the multivariable ordinal data arrays. Our examples have shown that in finding canonical rank scores and canonical correlation from an ordinal dataset, the CCCA is suboptimal. The OCCA suggested by us outperforms the conventional method. Moreover, our method can take care of any of the five different schemes of rank ordering. It uses the Particle Swarm Optimizer which is one of the recent and prized meta-heuristics for global optimization. The computer program developed by us is fast and accurate. It has worked very well to conduct the OCCA. |
| Keywords: | Ordinal; Canonical correlation; rank order; rankings; scores; standard competition; modified competition; fractional; dense; Repulsive Particle Swarm; global optimization; computer program; FORTRAN |
| JEL: | C13 C43 C63 C14 C88 C61 |
| Date: | 2009–01–16 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:12796&r=dcm |
| By: | David E. Giles (Department of Economics, University of Victoria) |
| Abstract: | We derive an analytic expression for the bias, to O(n-1) of the maximum likelihood estimator of the scale parameter in the half-logistic distribution. Using this expression to bias-correct the estimator is shown to be very effective in terms of bias reduction, without adverse consequences for the estimator’s precision. The analytic bias-corrected estimator is also shown to be dramatically superior to the alternative of bootstrap-bias-correction. |
| Keywords: | Half-logistic distribution, Life testing, Bias reduction |
| JEL: | C13 C16 C41 C46 |
| Date: | 2009–01–20 |
| URL: | http://d.repec.org/n?u=RePEc:vic:vicewp:0901&r=dcm |
| By: | Sundström, Kristian (Swedish Institute for Food and Agricultural Economics (SLI)); Andersson, Henrik (VTI) |
| Abstract: | This paper examines the value to Swedish citizens of reducing the risk for salmonella bacteria in chicken filet. The contingent valuation (CV) study is based on the results of a postal questionnaire that was distributed to 2 000 randomly selected Swedish citizens aged 18-74. The valuation format used is a stated preference double bounded dichotomous choice. We employ the non-parametric Turnbull Lower Bound method in combination with Monte Carlo simulations to obtain lower bound estimates of the mean and median values of expected willingness-to-pay (WTP) for reducing the risk for salmonellosis, as well as values of a statistical case (VSC) and a statistical life (VSL). We find a VSC of between SEK 121 045 (110 297–131 814) and SEK 182 966 (167 915–197 896) depending on the format used (values in parentheses constitute a 90 percent confidence interval). VSL values of SEK 13.3 million and 48.3 million are estimated using different formats, but neither estimation is statistically significant. Since this is the first Swedish study on WTP for food safety, mean and median values of VSL and VSC cannot be directly compared with previous results, but the values obtained are in line with comparable Swedish studies on WTP for traffic safety as well as with international studies related to food safety. We do not find any strong linkage between WTP and income, age or gender. Scale sensitivity seems to depend on which model is chosen, while household size, risk perception ability and perceived Quality Adjusted Life Years (QALY:s) lost seem to be strong predictors of WTP. |
| Keywords: | Contingent valuation; Food safety; Health risk; Salmonellosis |
| JEL: | C14 D12 Q18 |
| Date: | 2009–01–15 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:vtiwps:2009_002&r=dcm |
| By: | Antonio Merlo (Department of Economics, University of Pennsylvania); Kenneth I. Wolpin (Department of Economics, University of Pennsylvania) |
| Abstract: | In this paper, we study the relationship among schooling, youth employment and youth crime. The framework, a multinomial discrete choice vector autoregression, provides a comprehensive analysis of the dynamic interactions among a youth’s schooling, work and crime decisions and arrest and incarceration outcomes. We allow for observable initial conditions, unobserved heterogeneity, measurement error and missing data. We use data from the NLSY97 on black male youths starting from age 14. The estimates indicate important roles both for heterogeneity in initial conditions and for stochastic events that arise during one’s youth in determining outcomes as young adults. |
| Keywords: | crime, schooling, work, VAR |
| JEL: | K42 J24 J15 |
| Date: | 2008–09–02 |
| URL: | http://d.repec.org/n?u=RePEc:pen:papers:09-002&r=dcm |