By Tatiana Zárate-Barrera

This paper estimates the non-monotonic effects of air pollution on criminal activity in a developing country setting and provides empirical evidence on the potential behavioral responses mediating this relationship. To do so, I combine daily administrative data on crime, air pollution, and sentiment polarity from millions of social media posts in Mexico City between January 2017 and March 2020. The identification strategy relies on highly dimensional fixed-effect models, non-parametric estimations of dose-response functions, and an instrumental variable approach that employs wind speed and wind direction as instruments for air pollution. My results suggest a causal and inverted U-shape relationship between air pollution and crime. Specifically, there is an inflection point after which marginal increases in air pollution negatively affect criminal activity. Exploring the mechanisms behind this relationship, I find that air pollution has the power to shape people’s emotional states and mobility patterns. These results provide important insights for developing countries where pollution levels are dangerously high, and crime is still one of the most pressing issues. In particular, under certain circumstances, environmental regulation tailored to reduce air pollution must consider the presence of behavioral responses and these non-linear interactions with criminal activity in their design. 

Unpublished paper, 2021. 48p.

By Jo‑Anne Kramer,  Arjan A. J. Blokland, ·Edward R. Kleemans, Melvin R. J. Soudijn

In order to launder large amounts of money, (drug) criminals can seek help from financial facilitators. According to the FATF, these facilitators are operating increasingly business like and even participate in professional money laundering networks. This study examines the extent to which financial facilitators in the Netherlands exhibit business-like charac teristics and the extent to which they organize themselves in money laundering networks. We further examine the relationship between business-like behavior and individual money launderers’ position in the social network. Using police intelligence data, we were able to analyze the contacts of 198 financial facilitators who were active in the Netherlands in the period 2016–2020, all having worked for drug criminals. Based on social network analysis, this research shows that financial facilitators in the Netherlands can be linked in extensive money laundering networks. Based on the facilitators’ area of expertise, roughly two main types of professional money laundering networks can be discerned. Some subnetworks operate in the real estate sector, while others primarily engage in underground banking. Furthermore, the application of regression models to predict business-like behavior using individual network measures shows that facilitators with more central positions in the net work and those who collaborate with financial facilitators from varying expertise groups tend to behave more business-like than other financial facilitators

Kramer JA, Blokland AAJ, Kleemans ER & Soudijn MRJ 2023. Money laundering as a service: Investigating business-like behavior in money laundering networks in the Netherlands. Trends in Organized Crime.

By Osborne Jackson and Thu Tran

The “hidden tax” resulting from larceny crime refers to the higher prices paid by consumers to producers who raise prices in order to pass on some of the associated cost of such theft. In the same vein, consumers who are victimized by larceny theft could pass along some of the associated cost that they bear by spending less. This study analyzes larceny crime as a hidden tax in order to examine its welfare implications. Using traditional tax theory, the authors first characterize how larceny crime might create distortions in a given product market. Employing a sample covering 17 US states during the 2000–2015 period, they then use the enactment of higher felony larceny thresholds to generate exogenous variation in larceny crime by product market. A felony larceny threshold is the dollar value of stolen property at or above which a larceny offense may be charged in court as a felony rather than a misdemeanor. Focusing on the subset of larceny crime that is likely most affected by raising the larceny threshold, the authors calculate baseline hidden tax rates and then examine how changes in larceny rates related to higher thresholds affect this tax. They use these estimated changes in the hidden tax rates to compare the associated welfare costs of larceny crime across product markets.''

Boston: Federal Reserve Bank of Boston, Research Department. 2020, 33