|
on Discrete Choice Models |
| By: | Tibor Besedes (Georgia Institute of Technology); Cary Deck (University of Arkansas); Sudipta Sarangi (Louisiana State University and DIW Berlin); Mikhael Shor (University of Connecticut) |
| Abstract: | Previous studies have demonstrated that a multitude of options can lead to choice overload, reducing decision quality. Through controlled experiments, we examine sequential choice architectures that enable the choice set to remain large while potentially reducing the effect of choice overload. A specific tournament-style architecture achieves this goal. An alternate architecture in which subjects compare each subset of options to the most preferred option encountered thus far fails to improve performance due to the status quo bias. Subject preferences over different choice architectures are negatively correlated with performance, suggesting that providing choice over architectures might reduce the quality of decisions. JEL Classification: C91, D03 Key words: choice architecture, choice overload, status quo bias, self-sorting, decision making, experiments |
| Date: | 2012–04 |
| URL: | http://d.repec.org/n?u=RePEc:uct:uconnp:2012-24&r=dcm |
| By: | Rendon, Silvio (Stony Brook University) |
| Abstract: | I discuss the application of capture-recapture methods to estimating the total number of deaths in armed conflicts, and propose an alternative method based on a trivariate discrete choice model. Data come from the 'Truth and Reconciliation Commission' (TRC) of Peru, around 25000 deaths, classified by three sources of information, geographical strata, and perpetrator: the State and the Shining Path. In these data many killings have been only documented by one source, which makes a projection of killings unfeasible. TRC consultants Ball et al. (2003) tried to overcome this problem by means of a 'residual estimation,' consisting of merging data for different perpetrators. I show theoretically and empirically that this method over-estimates the number of deaths. Using a conditional trivariate Probit I estimate the total number of deaths in around 28000, 60% by the State, 40% by the Shining Path. This number is substantially lower and has a different composition than the around 69000 deaths, 30% by the State, 46% by the Shining Path, and 24% by 'other perpetrators,' calculated by Ball et al. |
| Keywords: | armed conflict, capture-recapture, count data, discrete choice, human rights, maximum-likelihood estimation, Poisson regression |
| JEL: | D74 C35 C4 O54 P16 |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp6827&r=dcm |
| By: | Pronzato, Chiara (University of Turin) |
| Abstract: | This paper compares two different ways of doing policy evaluation: on the one hand, quasi-experimental methods (or "ex-post" evaluations) which exploit the introduction of a reform and identify its effect by comparing treated and untreated individuals; on the other hand, structural models (or "ex-ante" evaluations) which are based on economic theory and predict the effect of potential reforms by using the estimates of behavioural parameters. The comparison is carried out using an empirical case. In 1998, in Norway, a major welfare reform changed the rules of the most generous benefit for lone parents: it increased the amount of the benefit and introduced working requirements. Using a quasi-experimental evaluation approach, it is found a positive effect of the reform on lone mothers' employment. In this paper, I estimate a static structural model of work and welfare participation decisions and compare the results using the two different approaches. Despite the differences in the assumptions I make for the two models, results are fairly comparable. |
| Keywords: | lone mothers, in-work benefits, quasi-experimental evaluation designs, discrete choice modelling, ex-ante and ex-post evaluation |
| JEL: | I38 J22 C25 |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp6803&r=dcm |