J.J. Naddeo
I received my Ph.D. in Economics from Georgetown University in May 2022 and my B.S. in Physics and B.A. in Economics from Rutgers University Camden.
I am an Economist with the Center for Economic Studies at the U.S. Census Bureau. I am also a researcher at the Justice Innovation Lab and economist/data analyst at Free Our Vote.
Table of Contents
Peer Reviewed Papers
De-prosecution and death: A comment on the fatal flaws in Hogan (2022)
(joint with Jacob Kaplan and Tom Scott)
Abstract:
In a manuscript recently accepted for publication in Criminology & Public Policy, Hogan (2022) presents results from a synthetic control method analysis that suggests de-prosecution in Philadelphia in the mid to late 2010s resulted in a large increase in the number of homicides that occurred in the city. In this comment, we point out several critical errors in the analysis that when corrected flip the direction of the effect and render the author’s estimated effect null. Our primary concerns include the short pre-intervention period, a failure to correct for imbalance over covariates in the synthetic control models, the use of homicide counts instead of rates as an outcome, an inaccurate description of the data used, and an inadequate explanation of data cleaning procedures including missing data. We reproduce the author’s results after correcting for these issues and find no effect of de-prosecution on homicide. Thus, these flaws are fatal to the author’s findings and therefore the study should not be used to inform criminal justice policy. Considering the author’s unwillingness to share their data and code, we call for a greater dedication to open science and reproduction/replication in criminology.
Working Papers
The Effects of Reducing Pretextual Stops: Evidence from Saint Paul Minnesota
(joint with Rory Pulvino)
Abstract:
Traffic stops make up the vast majority of law enforcement-initiated contact with the public in the United States. As such, it is an important gateway into the criminal legal system. Elected prosecutors---from across the political spectrum---are currently grappling with the growing consensus that the cost of bringing marginal individuals into the criminal legal system likely outweighs the benefits. An important question is how policymakers can reduce intake into the system while maintaining---or even improving---public safety. This article investigates the effectiveness of a policy by the Ramsey County Attorney's Office (RCAO) in conjunction with the Saint Paul Police Department (SPPD) to decrease the number of traffic stops for minor equipment violations. Using an interrupted time series (ITS) framework, we find that the policy met its goal of virtually eliminating traffic stops for vehicle violations, a common source of police-citizen interactions. Furthermore, we show that the policy reduced stops for Black motorists more relative to White motorists. Finally, we utilize ITS to also document changes in short- and long-term crime trends, the number of gun seizures, the number of victims of gun violence, traffic incidents, and response times to 911 calls. The results suggest that the policy was effective in reducing contact between law enforcement and the public---in a way that reduced racial disparities---without adversely affecting long-term public safety.
Race, Criminal History, and Prosecutor Case Selection: Evidence from a Southern U.S. Jurisdiction
Abstract:
State prosecutors are powerful actors who handle the vast majority of criminal cases in the United States. Furthermore, they are located at the core of the criminal justice pipeline, which runs from arrest to sentencing, and produces large persistent racial disparities. Given their centrality and influence, it is important to understand how prosecutors exacerbate or mitigate these disparities. This paper uses administrative data developed in collaboration with a prosecutor’s office located in a medium-sized jurisdiction in the southern United States. Using both descriptive and causal methods, I find that prosecutors are complex actors that are aware of upstream biases that taint signals they receive and act to reduce racial disparities. Specifically, after controlling for a rich set of covariates, I find that Black individuals receive shorter sentences and are more likely to have their charges dismissed relative to similarly situated White individuals. To learn more about what is happening at the margin, I leverage quasi-random assignment of cases to prosecutors and a simple—yet novel—model to show that prosecutors discount how prior convictions map into punishment for Black individuals relative to White individuals. My results suggest policies aimed at removing prosecutorial discretion or “blinding” prosecutors from knowing the race of an individual may have unintended consequences.
How Do Students Value an Elite Education? Evidence from NYC Specialized High Schools
(joint with Lawrence Costa)
Abstract:
Are students willing to endure long commutes for access to good schools? Using New York City Department of Education administrative data matched with Google transit directions, we find that longer commutes from home markedly deter students from applying to even the most elite high schools. For the top public school in New York State, a student with a 20 minute commute is 74% more likely to apply than one who lives 40 minutes away. For two other schools above the 99th percentile of performance, the differences are 234% and 137%. We also find that eighth grade exam scores relate to how well students understand the admissions process. As far as we are aware, we are the first to have the required location precision to track specific commutes for individual high school students. From a policy perspective, our findings imply that – while expanded school choice may be desirable – housing access near good schools is quite important.
What Encourages Returning Citizens to Vote? Measuring the Impact of Different Forms of Voter Outreach in Iowa
(joint with Alexander Billy and Neel U. Sukhatme)
AEA RCT Registry Entry: AEARCTR-0010141
Abstract:
Currently, twenty-six states bar individuals from voting, simply on the basis of convictions in their past. On August 5, 2020, Governor Kim Reynolds of Iowa issued Executive Order 7 which fully restored voting rights to Iowans with past convictions once the terms of incarceration, probation, parole, or special sentence were completed. Despite this recent change in law, uncertainty for many potential beneficiaries about eligibility, paired with the fact that voting illegally in Iowa can carry a punishment of up to 5 years of imprisonment, may cause many individuals with prior felonies to not embrace their newly obtained opportunity to vote. Accordingly, voter turnout among this population can likely be bolstered by targeted information campaigns. This paper aims to measure the impact of such an outreach effort. Specifically, we seek to measure how outreach using traditional mailers—a commonly used but expensive method for voter outreach—compares with outreach using social media and mixed social media/opt-in SMS campaigns.
Figure visualizing minimum detectable effects of a binary variable given a certain sample size and compliance rate, used in power analysis
It's Always Sunny in Politics
Abstract:
A desirable property of democratic elections is that they should not be influenced by forces that reveal no information about the candidate. However, the extant literature suggests that precipitation has a significant impact on electoral outcomes. This paper investigates an understudied dimension of weather—sunshine. Using novel daily weather measurements from satellites, linked to county level U.S. Presidential electoral returns from 19482016, we document how sunshine affects the decision making of voters. We find that election day exposure to sunshine increases support for the Democratic party on average. Additionally, we show that—contrary to prior findings that do not control for sunshine—precipitation has no detectable impact on partisan support, but universally depresses turnout. To rationalize our results we propose a mechanism whereby sunshine modulates voter mood which causes a change in voter choice, while precipitation only impacts turnout through increasing the cost of voting. We then build a theoretical model, which features this mechanism, and generates additional tests that find support in the data. Our main result—that election day sunshine noticeably impacts voter choice—highlights the need to reduce the effect of election day shocks (e.g. by allowing early voting). Furthermore, our results regarding precipitation suggest that reducing costs to voting does not confer partisan benefits—a potentially policy relevant finding for the current vote by mail discussion.
Using Rain for Electoral Gain: Evidence from FEMA’s Public Assistance Program
Abstract:
Distributive politics is the study of “who gets what, when, and how”. In this paper I find empirical support for predictions produced by a model of political competition at the state-level. To perform my analysis, I construct a novel county level dataset that merges fine-grain physical measures of large destructive storms, satellite data on existing infrastructure, demographic information from Census, and multiple types of relief spending. I find robust evidence that political parties target public spending to counties with higher historic turnout relative to their political neighbors. To give more credence to these results I confirm that each model passes multiple placebo tests. Additionally, to reduce the possibility that my results are driven by some systematic bias, I propose two credible instrumental variables and explicitly model the selection process that determines a counties eligibility for relief aid.
Works in Progress
Impact of Screening On Early Dismissals
Leverage variation generated by pilot screening unit in medium sized southern jurisdiction
Find screening increases early dismissal rates for Black defendants, while not impacting rates for White defendants
Developing RCT to scale up
Ranking Crime Types Using Combinatorial Hodge Theory and Survey Data
(joint with Kevin Himberger)
Developed and implemented a survey to approximately 30 assistant prosecutors in medium-sized jurisdiction regarding the prioritization of crime types
Coded HodgeRank algorithm to get back global consistent ranking
Built python package rankpy to implement HodgeRank algorithm
Peer Effects in Jail
(joint with Angelo Diaz-Reyes)
Use random cell assignment of individuals detained in jail to measure how exposure to different types of cellmates impacts future criminal activity as well as labor market outcomes
Unionization, Labor Market Power, and Wage Inequality
Reports
The Case for Screening
Justice Innovation Lab, after analyzing data provided by the Ninth Circuit Solicitor’s Office in Charleston, South Carolina (SOL 9), released its findings in The Case for Screening report. JIL and SOL9 worked together to analyze case trends and develop a data-informed approach to improving outcomes through prosecutorial screening. This report summarizes major findings from JIL’s analyses, discusses results from a pilot screening process, and provides recommendations for future case screening work.
Disparity and Prosecution in Charleston, SC
Press Coverage [1] [2] [3] [4]
This report was prepared for the Ninth Circuit Solicitor’s Office (SOL9) in Charleston County, South Carolina. It focuses on the outcomes of prosecutorial decision-making for felony and misdemeanor offenses in SOL9. It assesses the existence and extent of racial and ethnic disparities across the following four decision points: (1) Complete case dismissals; (2) Plea negotiations; (3) Changes in charges from referral to disposition; and (4) Sentencing.
Aging and the Labor Market in Thailand
In this project:
Assisted Harry Moroz in cleaning, harmonizing, and analyzing Thailand's Labor Force Survey
Produced a report on the effects of an aging labor market on the economy in Thailand
