We estimate the effect of changes in incarceration rates on changes in crime rates using state-level panel data. We develop an instrument for future changes in incarceration rates based on the theoretically predicted dynamic adjustment path of the aggregate incarceration rate in response to a shock to prison entrance or exit transition probabilities. Given that incarceration rates adjust to per...

Prostate Cancer Trial Data Testing Assumptions. We test the validity of the simplifying assumption of no association between the distributions of the PDGFR values X and Y and the other covariates Z in the PFS model, by regressing the individual preand posttreatment mean values on hemoglobin levels and increase in prostate antigen levels. No significant association was revealed by such analysis....

This paper presents an overview of the most powerful universal methods. These are based on acceptance/rejection techniques where hat and squeezes are constructed automatically. Although originally motivated to sample from non-standard distributions these methods have advantages that make them attractive even for sampling from standard distributions and thus are an alternative to special generat...

This paper examines whether growth regressions should incorporate dualism and structural change. If there is a differential across sectors in the marginal product of labour, changes in the structure of employment can raise aggregate total factor productivity. The paper develops empirical growth models that allow for this effect in a more flexible way than previous work. Estimates of the models ...

Estimating joint probabilities plays an important role in many data mining and machine learning tasks. In this paper we introduce two methods, minAB and prodAB, to estimate joint probabilities. Both methods are based on a light-weight structure, partition support . The core idea is to maintain the partition support of itemsets over logically disjoint partitions and then use it to estimate joint...

This paper investigates factors likely to increase a person’s risk of social exclusion, drawing on survey data specifically framed for this purpose. We use a generalised ordered logit model that accounts for observed and unobserved heterogeneity and derive the marginal effects for each influencing attribute. We find that people are less likely to be at risk of social exclusion if they have regu...

This paper identifies the key causal factors behind farmers’ marketing decisions in Mozambique. A two-step decision making process is modelled. Farmers decide, first, whether or not to participate in the market and, second, how much to market. The model is estimated using a Heckman switching regression approach. Marginal effects are calculated for the poor and the nonpoor and broken down into a...

For longitudinal binary data with non-monotone non-ignorable missing outcomes over time, a full likelihood approach is complicated algebraically, and maximum likelihood estimation can be computationally prohibitive with many times of follow-up. We propose pseudo-likelihoods to estimate the covariate effects on the marginal probabilities of the outcomes, in addition to the association parameters...

Arange of approximatemethods have been proposed formodel choice based onBayesian principles, given the problems involved in multiple integration in multi-parameter problems. Formal Bayesian model assessment is based on prior model probabilities P(M = j) and posterior model probabilities P(M = j |Y ) after observing the data. An approach is outlined here that produces posterior model probabiliti...

We obtain sufficient and/or necessary conditions for global/local error bounds for the distances to some sets appeared in set optimization studied with both the set approach and vector approach (sublevel sets, constraint sets, sets of all Pareto efficient/ Henig proper efficient/super efficient solutions, sets of solutions corresponding to one Pareto efficient/Henig proper efficient/super effic...