Research Fellow in Criminology


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Biography

Babak is a research fellow on the Understanding Inequalities project. He is an expert in implementing econometric and statistical analysis methods such as instrument variable, triple differences analysis, synthetic control method and regression discontinuity design for attempting to draw causal inference from observational data.
 
Babak was a post-doctoral researcher at the University of Pavia where his work focussed on understanding the impact of organized crime on society, specifically around innovation, technology and human capital. He was a visiting scholar at the University of Cambridge to study the effect of the drugs market on public corruption. Babak completed his PhD in 2014 at the University of Bologna.

Biography

Babak is a research fellow on the Understanding Inequalities project. He is an expert in implementing econometric and statistical analysis methods such as instrument variable, triple differences analysis, synthetic control method and regression discontinuity design for attempting to draw causal inference from observational data.
 
Babak was a post-doctoral researcher at the University of Pavia where his work focussed on understanding the impact of organized crime on society, specifically around innovation, technology and human capital. He was a visiting scholar at the University of Cambridge to study the effect of the drugs market on public corruption. Babak completed his PhD in 2014 at the University of Bologna.

Articles

Babak Jahanshahi, Arash Naghavi, 'Education reform and education gaps ', (2017), Applied Economics Letters, Vol 24, pp 1385-1388
Abstract: We estimate the causal effect of the Italian 2009 “Gelmini” education reform on four academic performance gaps relating to immigration status, gender, parental social status, and parental education. The reform led to a reduction in the number of teachers and an increase in class size. Lags in implementing the reform for different grades is used to specify a difference-in-difference identification strategy. We find that the reform had a statistically and economically significant effect on the immigrant-native gap and on the gender gap, but not on the gap between students with more and less favourable family background. Particularly, our findings show that students with an immigration background were the main losers from the Gelmini reform.

Babak Jahanshahi, 'Separating gender composition effects from peer effects in education ', (2016), Education Economics, Vol 25, pp 112-126
Abstract: This paper aims to demonstrate the importance of controlling for endogenous peer effects in estimating the influence of gender peer effects on educational outcomes. Using Manski's linear-in-means model, this paper illustrates that the estimation of gender peer effects is potentially biased in the presence of endogenous peer effect in education. The appropriate gender peer effect is estimated after identifying and controlling for the endogenous effect through the use of Graham's variance-restriction method.

Working Papers

Alessandro Flamini, Babak Jahanshahi, Kamiar Mohaddes, 'Illegal Drugs and Public Corruption: Crack Based Evidence from California' 2018
Abstract: Do illegal drugs foster public corruption? To estimate the causal effect of drugs on public corruption in California, we adopt the synthetic control method and exploit the fact that crack cocaine markets emerged asynchronously across the United States. We focus on California because crack arrived here in 1981, before reaching any other state. Our results show that public corruption more than tripled in California in the first three years following the arrival of crack cocaine. We argue that this resulted from the particular characteristics of illegal drugs: a large trade-off between profits and law enforcement, due to a cheap technology and rigid demand. Such a trade-off fosters a convergence of interests between criminals and corrupted public officials resulting in a positive causal impact of illegal drugs on corruption.

Mustafa Caglayan, Alessandro Flamini, Babak Jahanshahi, 'Organized Crime and Technology ' 2017
Abstract: This paper investigates the relation between the presence of organized crime and the technology level in north Italy. Our analysis proposes two provincial indexes. The first portrays technology at a fine-grained industrial sector level. The second describes mafia-type organizations in line with the investigation approach currently used by Italian National Antimafia Directorate (DNA) and Antimafia District Directorates (DDAs). With these indexes, we provide empirical evidence that in north Italy, the larger the presence of organized crime, the less innovation and the technological level of the industrial fabric. Our reading of this finding is that without organized crime, Nature selects agents according to their capacity to innovate. Instead, with organized crime, agents can choose an alternative strategy: relate with organized crime, which hinders innovation. Modelling the interaction innovation - relation with mafias by evolutionary game theory, we show that the presence of organized crime, through natural selection, leads to low levels of technology. Our model also shows how to use sanctions and indemnities to address the problem.