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Essays on Social Interactions and Policy Evaluation
Pertold, Filip ; Jurajda, Štěpán (advisor) ; Buonanno, Paolo (referee) ; Martins, Pedro S. (referee)
In the first part, I explore the start of daily smoking, which is often after the re-sorting of students between elementary and secondary education. I employ a novel identification strategy based on this re-sorting, in order to estimate peer effects in youth smoking. The reflection problem is addressed by peers' pre-secondary-school smoking, which is not influenced by the current interaction. The self-selection is minimized by one's own presecondary school behavior and the pre-existing smoking prevalence among older schoolmates. The empirical findings from the Czech Republic, where the prevalence of youth smoking has recently reached high levels, suggest that male youth smoking is affected by classmates, while female smoking is not. In the second part, I estimate the effect of opposite-gender peer drinking on individual risky sexual behavior among Czech youth. The identification strategy relies on two main controls for individual and group-specific unobservables. First, younger schoolmates' sexual behavior is a control for school-specific attitudes toward sexual behavior. Second, predetermined individual pre-secondary-school alcohol consumption is used to control for selfselection into schools of individuals with specific attitudes toward alcohol. As opposed to Waddell (2010), I find that female drinking...
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Model predicting the evolution of the prison population (PRISMOD)
Dušek, Libor ; Buonanno, Paolo ; Vávra, Jan
The certified methodology describes the newly developed PRISMOD simulation model and the software that implements it. The main purpose of the model is to project the evolution of the sentenced prison population in the Czech Republic over the next 10 years. The model adopts the inflow-outflow approach and models the prison population as a function of the underlying parameters that are estimated from statistical data. The key parameters are the number of crimes recorded, the probability of charges and conviction, probability of a prison sentences, the sentence length, and the probability of parole release from prison. The model also takes into account the prisoners that enter prison upon the probation, parole, or community service violations. The prison population is modeled separately by nine crime categories and by high-security and low-security prisons.
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