metadata: authors: 0: author: Ibáñez,Ana María
1: author: Rozo Villarraga,Sandra Viviana
2: author: Bahar,Dany
count: Venezuela, Republica Bolivariana de,Colombia
docna: 0: docna: Empowering Migrant Women : Regularization
            Programs and Crime
docty: Policy Research Working Paper
subtopic: Crime and Society,Social Cohesion,International Migration,Migration and Development,Human Migrations & Resettlements,Gender and Development
teratopic: Social Development,International Economics and Trade,Poverty Reduction,Gender,Communities and Human Settlements
abstracts: cdata!: Do undocumented forced migrants change
            their propensity to report or commit a crime when they are
            granted proper documentation, a job permit, and access to
            social services? This paper examines the impacts of a
            regularization program that granted temporary economic
            rights to over 281,000 undocumented Venezuelan forced
            migrants in Colombia. The program resulted in a general
            reduction in crimes committed by forced migrants, also while
            increasing the number of domestic abuse and sex crimes
            female migrants reported. These findings suggest that
            empowerment and greater trust in local authorities are key
            mechanisms driving the behavioral changes for females, while
            proper enforcement facilitated by adequate documentation and
            the positive income effects of the program reduced the
            general propensity for migrants to commit crimes.
geo_reg_key: 119228,517191
repnme: repnme: Empowering Migrant Women : Impacts of
            Amnesties on Crime Reports
display_title: Empowering Migrant Women : Impacts
            of Amnesties on Crime Reports : Empowering Migrant Women :
            Regularization Programs and Crime
listing_relative_url: /research/2021/11/33576620/empowering-migrant-women-impacts-amnesties-crime-reports-empowering-migrant-women-regularization-programs-crime
topicv3: Domestic Violence m1326034 2441,Gender m1327621 615,Crime m1439217 3041,Homicide m1439222 HOM-3046,Immigration m1504162 2837
publishtoextweb_dt: 2021-11-03T00:00:00Z
dois: 10.1596/1813-9450-9833
historic_topic: Social Development,International Economics and Trade,Poverty Reduction,Gender,Communities and Human Settlements
origu: DECRG: Poverty & Inequality (DECPI)
no_of_pages: 56
author_keys: 0: author_key: NA
1: author_key: 1932755
2: author_key: 1113293
model_extractions: Policy Research Working Paper 9833 Empowering Migrant Women Regularization Programs and Crime _Ana María Ibáñez Sandra V. Rozo Dany Bahar_ Development Economics Development Research Group November 2021
Policy Research Working Paper 9833

# **Abstract**

Do undocumented forced migrants change their propensity to report or commit a crime when they are granted proper documentation, a job permit, and access to social services? This paper examines the impacts of a regularization program that granted temporary economic rights to over 281,000 undocumented Venezuelan forced migrants in Colombia. The program resulted in a general reduction in crimes committed by forced migrants, also while increasing the number of domestic abuse and sex crimes female migrants reported. These findings suggest that empowerment and greater trust in local authorities are key mechanisms driving the behavioral changes for females, while proper enforcement facilitated by adequate documentation and the positive income effects of the program reduced the general propensity for migrants to commit crimes.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at anaib@iadb.org, srozovillarraga@worldbank.org, and dany_bahar@brown.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **EMPOWERING MIGRANT WOMEN:**

# **REGULARIZATION PROGRAMS AND CRIME**<sup>*</sup>

Ana Mar ́ıa Ib ́a ̃nez<sup>†</sup> _⃝_ r Sandra V. Rozo<sup>‡</sup> _⃝_ r Dany Bahar<sup>§</sup> Originally published in the Policy Research Working Paper Series on _November 2021._ This version is updated on _January 2025._ To obtain the originally published version, please email prwp@worldbank.org.

## **JEL Classification:** D72, F2, O15, R23

## **Keywords:** Migration, Crime, Amnesty, Empowerment

*We are grateful for comments from Matt Notowidigdo, Giovanni Peri, Nathan Nunn, Ana Mar ́ıa Tribin, Brian Knight, Catalina Amuendo-Dorantes, Felipe Mu ̃noz, and Berk Ozler and for suggestions received from audiences at seminars at the University of Southern California and the Southern Economic Association. We are grateful to Maria Jos ́e Urbina and Andr ́es Barinas for their excellent research assistance. Bahar thanks the Conrad N. Hilton Foundation for their support. Rozo is grateful for financial support from the Research Support Budget of the World Bank. The order in which authors’ names appear has been randomized using the AEA Author Randomization Tool (#C5TaE0I ~~h~~ dF5), denoted by _⃝_ r . The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and/or the Inter-American Development Bank, and their affiliated organizations, or those of the Executive Directors of the World Bank and/or the Inter American Development Bank or the governments they represent.

> †Inter-American Development Bank, email: anaib@iadb.org

> ‡Development Research Group, World Bank, email: sandrarozo@worldbank.org

> §Center for Global Development and Harvard Growth Lab. email: dany ~~b~~ ahar@brown.edu.
# **I INTRODUCTION**

The popular perception about crime and immigration is that they often move in the same direction (Butcher and Piehl 1998a; Bianchi et al. 2012; Spenkuch 2014a; Fasani et al. 2019; Bahar et al. 2020; Pinotti and Rozo 2022).<sup>1</sup> Additionally, research suggests that during episodes of forced immigration, migrants themselves tend to be victims of crime.<sup>2</sup> In these contexts, it is likely that the most vulnerable migrants, e.g., those who are undocumented and female, might not report crimes against them for fear that interactions with local authorities could result in punishment, discrimination, or deportation.<sup>3</sup> As such, a relevant question points to the effects of facilitating proper documentation and economic integration on undocumented forced migrant’s propensity to commit and report crimes.

We address this question by studying whether a large regularization program of undocumented forced migrants prompted a change of migrant’s behaviors in _reporting_ or _committing_ crimes. Our case study is Colombia, the current largest host of Venezuelan forced migrants.<sup>4</sup> The vast majority of them arrived in Colombia after 2016 as a result of Venezuela’s political, economic, and humanitarian crises. In July 2018, Colombian President Juan Manuel Santos ordered the issuance of a regular migratory status known as Permiso Especial de Permanencia (henceforth PEP for brevity).

The PEP granted regular migratory status for two years to about 281,000 undocumented Venezuelan forced migrants in Colombia. It not only provided these immigrants with proper documentation and a job permit but also gave them the opportunity to receive a score on SISBEN, the mean proxy test used to award social support in Colombia. As such, the PEP enabled undocumented migrants to work in the formal sector and to access social services (including complete health services through the subsidized health regime).

> 1For instance, at least 74 percent of Colombian natives believes that Venezuelan forced immigration exacerbates crime and insecurity (LAPOP, 2021; OXFAM, 2023).

> 2See recent evidence from Colombia by Knight and Tribin (2020) and Mexico by Rozo et al. (2021). 3See evidence by Horn (2010); Calder ́on et al. (2011); Wirtz et al. (2014); Kelly et al. (2199).

> 4According to the latest data from Colombian migration authorities, by 2022 the number of Venezuelans there numbered approximately 2.5 million people, or about 5% of Colombia’s population.

2
We combine data from multiple sources to create a monthly-city level panel of _crime reports from migrant and host victims_ and _crimes committed by migrants_ for the largest urban centers in Colombia. To examine the effects of the PEP we use a difference-in- program differences specification, which compares crime in cities with different program take-up rates, before and after the program roll-out in August, 2018. We complement our analysis with event studies that examine the evolution of quarter-by-quarter crime outcomes in the main urban centers with different program take-up rates. The event studies support the validity of our identification strategy since we observe parallel trends before program implementation.

As a robustness test, we complement the difference-in-difference estimates exploiting the fact that each undocumented migrant eligible for the permit received a registry number exogenously allocated during registration. Based on this number, migrants could apply for (and subsequently get) the PEP migratory status in one of 22 time windows in late 2018. We use these assignments to estimate the average number of registration days available to undocumented immigrants in each city and use it as an instrumental variable for the program take-up rates. Our estimates are similar when employing the instrumental variables, reinforcing the validity of the difference-in-difference results. Additionally, our results are robust to multiple hypothesis testing, changes in geographic aggregation level (e.g., department-month aggregation instead of city-month aggregation), controls choice (e.g., dropping total crime controls), corrections on inference to a low number of clusters, and potential violations to the parallel trend assumption (Bilinski and Hatfield, 2018).

Our main analysis points to two key findings. First, places where more undocumented Venezuelan migrants applied for the PEP permit experienced an increase in total crime reports by Venezuelan migrants. These effects are explained by increments in reports of sex crimes and domestic violence, and they are entirely driven by female Venezuelans migrants, an especially vulnerable population. Notably, we find that Colombian cities 3
that had twice as many Venezuelan immigrants receiving a regular migratory status experienced an increase of 25 percent more crime reports. These effects are not explained by higher domestic violence caused by the PEP program. In fact, the improvements in economic and mental health conditions observed among PEP participants (Ib ́a ̃nez et al., 2024) are inconsistent with patterns typically associated with increased domestic violence. Additionally, the program did not disproportionately increase female income relative to male income.

Particularly, a twofold increase in the number of Venezuelan migrants who received regular migratory status (relative to population) explains an increase of 40 percent and 70 percent in reports of sexual crimes and domestic violence, respectively. Given that the effects stem mostly from female Venezuelan migrant victims of crimes, it is plausible to conclude that these women felt more empowered to report such abuses without fear of deportation or other penalty. We support this hypothesis with data from a representative survey of Venezuelan refugees with and without the PEP that was collected as part of the Venezuelan Refugee Panel Study (VenRePs).<sup>5</sup> As we demonstrate, female migrants with the PEP increased the rate at which they filed complaints with the police and other institutions relative to their peers without the PEP. Additionally, and consistent with our main estimates, there was a mechanical increase in convictions and trials of male Venezuelan perpetrators of these crimes, who were likely partners of the victims.

Second,the program led to a reduction in total crime reports by Colombian natives and a decline in crimes committed by Venezuelans, excluding domestic and sexual crimes (which might be higher mechanically due to the increased reports). The results aligns with qualitative evidence from local officers suggesting that undocumented migrants were previously difficult to apprehend and prosecute due to legislative loopholes in the Colombian law. The regularization program addressed this gap, ensuring better enforcement of criminal laws. Moreover, documented increments in migrants’ income and con5Ib ́a ̃nez et al. (2024) collected the data in 2021.

4
sumption caused by the program (Ib ́a ̃nez et al., 2024) might have reduced crimes by improving economic opportunities. Together, these findings highlight the critical role of regularization programs like PEP in enhancing legal protections, reducing social tensions, and improving safety for both migrants and host communities. Our results are in line with declines in the crime rates of newly documented migrants in Italy, as shown by Pinotti (2017a).

Our results suggest that facilitating forced migrant’s economic integration has powerful impacts that go beyond labor markets. For one, they affect migrant’s willingness to cooperate with governments and make their basic human rights be respected. Such policies seem to be particularly relevant for vulnerable groups such as women who may be facing disproportionate domestic and sexual violence by staying undocumented. Moreover, ensuring proper documentations facilitates enforcement and increases income resulting in lower crime rates.

This study contributes to work examining the relationship between immigration and crime (Butcher and Piehl, 1998b; Borjas et al., 2010; Bianchi et al., 2012; Alonso-Borrego et al., 2012; Bell et al., 2013; Spenkuch, 2014b; Baker, 2017; Pinotti, 2017b; Freedman et al., 2018; Fasani, 2018; Fasani et al., 2019; Ajzenman et al., 2020; Knight and Tribin, 2020). Specifically, for Colombia, Knight and Tribin, 2020 investigate the connection between violent crime and immigration, using data from Colombian municipalities during the recent wave of immigration from Venezuela. The authors find that after the ColombianVenezuelan border was closed and later re-opened in 2016—triggering a large influx of migrants—homicides in Colombia increased in areas near the Venezuelan border. This rise, however, was primarily driven by homicides involving Venezuelan victims, with no statistically significant increase in homicides targeting Colombians. While our study examines a related outcome, it departs from this body of work by focusing on the effects of a policy that improved the rights of undocumented migrants already residing in Colombia.

5
Rather than analyzing the impact of migrants arrival on crime rates, we explore how the enactment of a migration reform influenced migrants’ behavior, particularly their willingness to commit and report crimes.

The papers most closely related to our work are Comino et al. (2020), J ́acome (2022), and Pearson (2024), which analyze changes in crime reporting behaviors following programs that enhanced the rights of undocumented migrants in the United States.<sup>6</sup> Consistent with our findings, these studies show that improving rights for undocumented migrants increases their trust in and cooperation with local authorities, leading to higher rates of crime reporting. This effect is partly driven by a reduction in victims’ fear of deportation (Comino et al., 2020 and Pearson, 2024) and greater trust in law enforcement (J ́acome, 2022).

Our study complements this literature in two important ways. First, while we also examine the effects of a regularization program that enhanced undocumented migrants’ rights, our focus is on a developing country context, characterized by high levels of informality, widespread crime, and relatively low deportation rates. Unlike in the United States, undocumented in Colombia are less to fear as migrants likely deportation, they typically work in the informal sector with minimal detection risk. Since over 75 percent of forced migrants reside in developing countries, this context provides a critical perspective and highlights dynamics that may not translate directly from high-income countries.

Second, our analysis emphasizes gender dynamics and provides a more detailed view of the types of crimes affected by these programs—not only aggregated or property crime. We find that women, particularly victims of sexual crimes and domestic violence, are key drivers of the observed increase in crime reporting in developing countries. This insight is essential for understanding the victimization of vulnerable populations and for

> 6Comino et al. (2020) examines the effects of the 1986 migratory amnesty, J ́acome (2022) the effects of the 2015 Priority Enforcement Program, and Pearson (2024) the effects of the 2012 Deferred Action for Early Childhood Arrivals. Another close contribution is Xie and Baumer (2021), who offer a descriptive study using data from the National Crime Victimization Survey.

6
designing effective policy interventions. Similar increases in reporting among immigrant victims of domestic violence have been documented by Amuedo-Dorantes and ArenasArroyo (2022) and Amuedo-Dorantes and Deza (2022) in the United States following the implementation of sanctuary policies, which reduce local law enforcement’s cooperation with federal immigration authorities and limit deportation enforcement. Our findings demonstrate that granting rights, even in contexts where deportation risks are low, can foster institutional trust and improve reporting behaviors.

Our work also contributes to studies that explore the impacts of migration reforms in hosting countries (Kossoudji and Cobb-Clark, 2002; Bratsberg et al., 2002; Orrenius and Zavodny, 2003; Kaushal, 2006; Amuedo-Dorantes et al., 2007; Chassamboulli and Peri, 2015; Devillanova et al., 2018; Bahar et al., 2021). While most of these papers assess the impacts of migration reforms on labor or political outcomes<sup>7</sup> , we focus on the behavior of the immigrants themselves as measured by crime reports. To some extent, crime reporting proxies the subsequent social empowerment of vulnerable migrant populations that results from receiving regular migratory status. In this context, our results have key policy implications by documenting large social benefits to such populations following a migratory amnesty, which in itself—according to previous literature—poses negligible costs to labor market outcomes for natives.

We also add to research on the assimilation and integration of migrants (Abramitzky et al., 2014; Bratsberg et al., 2014; Abramitzky et al., 2199; Harder et al., 2018; Hainmueller et al., 2019; Abramitzky et al., 2020; Brell et al., 2020; P ́erez, 2021; Ib ́a ̃nez et al., 2024). These studies mostly explore the assimilation of migrants into labor markets by estimating the convergence of wages, occupational sector, and education levels between first-generation and second-generation migrants and the local population. Although recent papers have identified mediating factors such as marriage decisions, language ability, and cultural

> 7See Bahar et al. (2023) and Rozo et al. (2023) who examine the effects of the same program on firm development and electoral outcomes.

7
integration, the success of migrants also depends on trust in state institutions to which they apply for social services or to seek protection. We document that regularization empower migrants to request state action against crime, an important step toward social integration in receiving countries.

# **II THE PROGRAM: THE PEP REGULARIZATION**

Colombia has led regional efforts to regularize the status of Venezuelan forced migrants. As is typical in crisis-driven migration, a large share of Venezuelans who migrated to Colombia did so without a formal migratory process. Between April and June 2018, Colombian authorities at 1,109 authorized points in 413 municipalities registered undocumented Venezuelan immigrants (see Figure A1 in the Appendix). This registry, the _Registro Administrativo de Migrantes Venezolanos_ or RAMV, conducted a massive public campaign to attract Venezuelan immigrants to register and self-report personal information such as name, date of birth, current address, municipality of origin in Venezuela, date of entry, education level, and job status, among others. It succeeded in registering 442,617 undocumented Venezuelans from 253,575 different households.

It is important to note that in advertising the RAMV, the government explicitly stated that registration would not result in deportations or other negative legal consequences. Yet, it did not promote the RAMV either as a path to work permits or other legal benefits to enhance the migrant experience. The program was advertised simply as a registry to count and identify migrants.<sup>8</sup> However, in July 2018, just days before leaving office, outgoing President Juan Manuel Santos decreed that all Venezuelans who registered in the RAMV would be eligible for regular migratory status that would let them stay in Colombia and join the workforce. In particular, previously undocumented migrants who registered in RAMV could apply for the _Permiso Especial de Permanencia_ , or PEP, a comprehensive two-year regular migra-

> 8We subsequently spoke with government officials and confirmed that these were, in fact, their intentions at the time.

8
tory status that Colombia had previously granted to Venezuelan migrants. The difference between previous waves of PEP and this one (PEP) was that the latter was explicitly created for Venezuelans registered in the RAMV, and as such, focused on undocumented immigrants. According to the decree, these immigrants could request the PEP migratory status during the third quarter of 2018. Each migrant had a window of time in which to apply based on their RAMV registration number, which they received as their record was entered into the system in real time. This number was exogenously allocated to each immigrant across all the authorized points. By the end of that year, 281,307 of the 442,617 eligible individuals had applied for and received one.

According to the RAMV data described in Table 1, the migrants under consideration were young and had low levels of education: less than 10 percent of RAMV migrants were older than 60 years, and over 50 percent of this group had completed at least secondary education. This group was younger but slightly less educated than the Colombian labor force. According to 2018 population estimates, approximately 13.5 percent of the Colombian population was older than 60 years, and 61.5 percent of the active labor force in 2017 had completed at least basic secondary education. At the time of the RAMV survey, 46.3 percent of working-age migrants had some level of employment in the informal sector.

# **III DATA**

We exploit monthly and city variation in our estimates. The data we use can be grouped as follows:

1. . _Crime reports by migrant victims_ We use individual level reports from victims from the Colombian National Police that include reports on all crimes denounced in Colombia between January 2017 and December 2019 (one year before and after the regularization program). They include information on the type of crime, the municipality of reporting, and the nationality and the gender of the individual who reported it. We construct crime counts on a monthly basis for each main city in

9
Table 1. Sociodemographic Characteristics of Migrants Who Registered in the RAMV

|_Panel A. Age Groups_||||||
|---|---|---|---|---|---|
|Variable|Total Obs.|Observations|Percentage|Average|STD|
|0-18 years|440,869|116,529|26.43%|7.64|4.94|
|18 - 30 years|440,869|167,743|38.05%|24.23|3.51|
|31 - 40 years|440,869|88,392|20.05%|35.07|2.84|
|41 - 50 years|440,869|44,568|10.11%|44.91|2.83|
|51 - 60 years|440,869|17,602|3.99%|54.6|2.76|
|61 - 70 years|440,869|4,948|1.12%|64.34|2.66|
|71 - 80 years|440,869|880|0.20%|74.2|2.7|
|_≥_80years|440,869|207|0.05%|87.27|8.9|
|_Panel B. Individual Covariates_||||||
|Variable|Total Obs.|Observations|Percentage|95%|CI|
|_Gender_||||||
|Female|442,616|219,847|49.67%|49.52%|49.82%|
|Male|442,616|222,435|50.25%|50.11%|50.40%|
|Transgender|442,616|334|0.08%|0.07%|0.08%|
|_Household role_||||||
|Head of Household|442,616|231,915|52.40%|52.25%|52.54%|
|_Marital Status_||||||
|Single|442,617|279,956|63.25%|63.11%|63.39%|
|Married / Cohabitating|442,617|153,659|34.72%|34.58%|34.86|
|Divorced / Separated / Widowed|442,617|9,002|2.03%|1.99%|2.08%|
|_Level of Education_||||||
|Preschool / Primary|442,617|150,884|34.09%|33.95%|34.23%|
|Secondary|442,617|221,319|50.00%|49.86%|50.15%|
|Tech School / University/ Post Grad|442,617|70,414|15.91%|15.80%|16.02%|
|_Panel C. Household Covariates_||||||
|Variable|Observations|Mean|STD|Min|Max|
|Number of family members|437,059|3.51|2.06|0|10|
|Number of relatives in Venezuela|435,758|2.56|2.72|0|14|

_Notes:_ The table depicts the descriptive statistics of Venezuelan migrants who registered in the Registro Administrativo de Migrantes Venezolanos (RAMV) Census.

10
the country. We aggregate data at the city-month level. By limiting crime reports to Venezuelans, we attempt to capture the effect of the regularization on the propensity of Venezuelan migrants to report crimes.

2. _Crimes perpetrated by migrants._ To examine changes in crime perpetrated by migrants we use data from the _Fiscal ́ıa General de la Naci ́on_ , Colombia’s Office of the Attorney General. The data set includes all criminal cases in Colombia that are in trial or have yielded convictions, including information on the year the crime occurred, the type of crime, and the gender, age, and nationality of the indicted individual between 2017 and 2021.<sup>9</sup> In the data, 97.11 percent of crimes (178 _,_ 483) were committed by Colombian nationals and 2.8 percent (5 _,_ 312) were committed by Venezuelan migrants.

3. _Registro Administrativo de Migrantes Venezolanos (RAMV)_ . We use administrative data sourced from the RAMV survey to compute the number of people eligible for the PEP migratory status and the actual number of individuals who applied for (and received) the PEP migratory status. Using individual records, we compute the allocated time window each individual had to register in the PEP (based on the registration number), which we use for our identification strategy.

4. _Municipality Controls_ . We control for a rich set of baseline municipal covariates including night light density, variables related to internal conflict, GDP municipal composition, distance to the Venezuelan border, and number of Venezuelans with previous rollouts of PEP migratory status (particularly the PEP1 and PEP2), as well as proxies for government activity. Administrative information at the municipal level comes from the CEDE municipal panel, the Ministry of Defense, the National Planning Department, and DANE (Colombia’s national statistical agency). Night

> 9The original data set had more information that we do not use in our effort to measure actual crimes. Thus, we exclude cases that were found not guilty, were in pretrial investigation (i.e., not enough evidence had been compiled to go to trial), were closed by the prosecutor, or suffered “procedural rupture” (according to Article 53 of the Code of Criminal Procedure).

11
light density comes from the National Oceanic and Atmospheric Administration.

Table 2 presents descriptive statistics for all the main variables in our analysis. Our sample includes 1,080 observations that correspond to the 30 municipalities that represent cities of most in Colombia and 36 months.<sup>10</sup> We focus on capital departments capital cities that host about two-thirds of all Venezuelans in our sample (e.g., using the locations reported in the RAMV data) in order to reduce possible biases in crime reporting due to internal conflict that still persists in rural areas (Iba ̃nez et al., 2017). Yet, as a robustness test we also show that our main results hold for different levels of geographic aggregation B. A. (such as aggregating the data by department-month level) in Appendix Panel A of Table 2 illustrates the total number of crimes B the ones re- reported; panel ported _by Venezuelans_ in rates per 100,000 individuals. The rate of all crimes reported by Venezuelan migrants in our sample is 0.79 per 100,000 individuals (panel B). The most common crimes reported by Venezuelans is theft (0.44 per 100,000 individuals). These numbers are quite low, as expected—at the time, Venezuelans represented at most three percent of Colombia’s population, with heterogeneity in terms of locations, naturally. Yet, they have enough variation to exploit for our exercise. Indeed, given the high standard deviations relative to the mean, significant variation is evident across crime reports, cities, and months. Similar trends are observed for crimes perpetrated by Venezuelans (Panel C), where theft is also the most common crime.

In terms of the treatment variable, panel D of Table 2 shows that for the average city in our sample, there were 4,839 Venezuelans who received the PEP migratory status. That number, however, ranged between 13 and 35,729 across all cities in the sample. In proportion to the local population, the number of PEP migratory status awarded was, on average, 217.98 per 100,000 inhabitants. While the number of observations in this table is 10Colombia has 32 departments; the panel only includes those 30 cities for which there were consistent monthly crime reports and control variables. The cities excluded did not had available data for all periods and the data was of low quality.

12
Table 2. Descriptive Statistics

|Variable|Obs.|Average|SD|Min|Max|
|---|---|---|---|---|---|
|_Panel A: Total Crime Reports (ratesper 100,000)_||||||
|Homicides (per 100K)|1,080|1.99|1.81|0.00|18.97|
|Threats (per 100K)|1,080|12.00|8.46|0.00|52.82|
|<br>Domestic Violence (per 100K)|1,080|20.82|13.42|0.00|98.67|
|<br>Thefts (per 100K)|1,080|83.80|30.95|12.69|193.44|
|Sex Crimes (per 100K)|1,080|7.95|4.61|0.00|31.16|
|<br>Total Crimes(per 100K)|1,080|127.17|40.56|40.49|266.15|
|_Panel B: Crime Reports by Venezuelan Victims (ratesper 10_|_0,000)_|||||
|Homicides (per 100K)|1,080|0.08|0.42|0.00|4.88|
|Threats (per 100K)|1,080|0.04|0.24|0.00|3.07|
|<br>Domestic Violence (per 100K)|1,080|0.15|0.49|0.00|9.18|
|<br>Thefts (per 100K)|1,080|0.44|0.90|0.00|14.65|
|Sex Crimes (per 100K)|1,080|0.08|0.42|0.00|6.12|
|Total Crimes(per 100K)|1,080|0.79|1.63|0.00|19.59|
|_Panel C. Crimes Perpetrated by Venezuelans (ratesper 100,_|_000)_|||||
|Homicides (per 100K)|150|0.46|0.92|0.00|5.94|
|<br>Threats (per 100K)|150|0.26|1.02|0.00|9.48|
|Domestic Violence (per 100K)|150|1.39|4.47|0.00|48.84|
|<br>Theft (per 100K)|150|3.71|7.12|0.00|37.23|
|Sex Crimes (per 100K)|150|0.66|2.48|0.00|19.54|
|Total Crimes(per 100K)|150|6.48|11.65|0.00|78.15|
|_Panel E: Treatment and Other Migration Variables_||||||
|PEP-RAMV holders|1,080|4,839.60|7,686.24|13.00|35,729|
|PEP holders per 100K (ages 10-64)|1,080|217.98|375.02|3.33|1,767.00|
|Venezuelan population 2005|1,080|676.83|1,171.58|0.00|4,578|
|<br>Totalpopulation 2005|1,080|644,783|1,252,964|12,897|6,778,691|
|_Panel F: Control Variables (at baseline)_||||||
|Night Light Density (2009)|30|12.73|14.47|0.03|53.98|
|Total Mun. Income (COP, Billions) (2009)|30|628.79|1,513.32|9.06|8,131.36|
|<br>Mun. Public Expenditures (COP, Billions) (2009)|30|617.83|1,434.27|10.52|7,553.10|
|<br>Total Central Gov. Transfers (COP, Billions) (2009)|30|222.60|381.46|4.98|2,048.44|
|Number of Financial Institutions (1995)|30|24.23|47.62|1.00|252.00|
|Number of Tax Collection Offces(1995)|30|8.87|18.93|1.00|99.00|
|<br>Homicide Rate (Per 100,000 Indv.) (2009)|30|34.88|21.45|7.00|109.91|
|<br>N. of Terrorist Attacks (1995)|30|0.07|0.37|0.00|2.00|
|Unsatisfed Basic Needs (UBN % Households) (2005)|30|27.46|17.76|9.16|89.51|
|<br>Informal Labor* (% Households) (2005)|30|88.33|5.54|77.16|96.51|
|<br>GDP Agriculture (COP, Billions) (2009)|30|53.79|42.21|4.50|145.92|
|<br>GDP Industry (COP, Billions) (2009)|30|2,138.95|4,368.66|8.44|22,970.06|
|<br>GDP Services (COP, Billions) (2009)|30|4,444.15|13,266.97|87.69|72,695.80|
|<br>PEP1 (August 2017-October 2017)|30|1,777.50|5,133.56|0.00|27,703.00|
|<br>PEP2 (February 2018-June 2018)|30|2,880.43|8,737.14|0.00|47,389.00|
|Inverse Distance to Closest Border Crossing|30|0.13|0.35|0.00|1.00|

_Notes:_ The table depicts the summary statistics of the main variables used in our study.

13
1,080, since this is the treatment variable, there is no across-time variation (as will be clear when we describe our empirical strategy).

Panel E presents summary statistics for all the different controls in our specifications for the 30 cities in our sample at baseline.<sup>11</sup> Figure 1 visually represents these data on a map of Colombia. For each capital city, the figure plots the number of PEP holders per 100,000 inhabitants via the scale of the markers (circles). Using a light-to-dark color scale, it also shows the total crimes reported (per 100,000 inhabitants, for consistency) in the different cities. For visualization purposes, the color scale is represented in the departments where the capital cities are located. This graph shows a great deal of variation for both the treatment variable and the outcome under consideration. Figure 2 also illustrates a scatter plot in which each dot represents an urban centers in our sample. The scatter plot shows that there is a positive correlation between the PEP program take-up and the change in crime reports by Venezuelan migrants, before and after the PEP implementation. For completeness we also replicate the B1. same Figure aggregating the data at the department level in Figure

# **IV EMPIRICAL STRATEGY**

Our main goal is to establish whether provision of the PEP program to previously undocumented migrants change crime reported or committed by Venezuelans. To do so, we compare cities with different PEP take-up rates, before and after they received this status. Effectively, we estimate a difference-in-differences specification as follows:

> where _c_ indexes city and _t_ indexes time (month-year). Our main outcome variable is Crime _ct_ ,

> 11All controls are measured at the municipality level.

14
<!-- Start of picture text --> \ ha<br>ams Marta<br>Barranqyflla (5)(<br>Cartagena de rig 7,<br>4 @fedupar<br>UO) , José de Cucuta<br>manga<br>Qui\ to Carrenho<br>Perei‘ anizales<br>A ogota,<br>Wank Qiillavicencio Gis Legend<br>Neiva PEP holders per 100K<br>Gopayan san Jose del Guaviare ° 1.5101 - 19.3515<br>ia O 19.3515 - 45.9371<br>Pasto V9 © 45.9371- 83.6226<br>(_) 83.6226 - 226.8864<br>C) 226.8864 - 1767.005<br>Crime Reports by Venezuelans per 100K<br>0-0<br>0-0.38<br>MM 0.38 - 0.62<br>Leticia MM 0.62 -1.19<br>HM 1.19 - 4.78<br><!-- End of picture text -->
Figure 2. Change in Crime Reports before and after PEP Implementation <!-- Start of picture text --> 0 100 200 300 400 500 600<br>PEP−RAMV holders per 100,000 inhabitants<br>Change in Crime Reports Linear Fitted Values<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>Change in Crime Reports by Venezuelans<br>0<br><!-- End of picture text --> _Notes:_ The figure shows the change in the average crime reports by Venezuelan migrants one year before, and after the PEP implementation by capital cities.

16
which is the rate of committed or reported crimes by Venezuelans in city _c_ and month-year _t_ per 100,000 inhabitants. _PEPc_ is the number of Venezuelans with the PEP migratory status per city _c_ per 100,000 inhabitants,<sup>12</sup> interacted with a dummy that takes the value of one for all time periods after August 2018, when the PEP roll-out began. Our estimator of interest is _βDID_ . Concerning the time dimension, the coefficient can be interpreted as the average effect of the PEP program for all months in the sample after August 2018 (included) versus all the months before August 2018.

All continuous variables on the right-hand side, including the treatment variable, were transformed using the inverse hyperbolic sine transformation.<sup>13</sup> Thus we interpret _βDID_ as a semielasticity of crime reports with respect to the share of the population that received regular migratory status.

We also include a full set of predetermined municipal characteristics measured before the beginning of our period of analysis (to reduce endogeneity concerns), represented by the set _Z_ . We interact these control variables with year dummies (denoted by _yeart_ ) to flexibly account for potential differential non-parametric trends for each city _c_ that could emerge from these variables as they explain crime reports by Venezuelans in ways that are correlated with the treatment. The variables included in _Z_ are (1) percentage of households in Colombia in 2005 with at least one unsatisfied basic need; (2) percentage of households in Colombia the same year with at least one informal worker; (3) the number of terrorist attacks in 1995 (to proxy for the internal conflict); (4) night light density in 2009; (5) the number of financial institutions in 1995; (6) the number of tax collection offices in 1995; (7) agriculture, (8) industry, and (9) services GDP in 2009; (10) central government transfers in 2009; (11) total municipal expenditures in 2009; (12 and 13) the number of Venezuelans who received the two previous rounds of the PEP migratory status; and (14) the inverse distance to the closest of the five authorized crossing points between Venezuela and Colombia. The specification also includes fixed effects for city ( _γc_ ) and month-year ( _ηt_ ). Unless indicated, we cluster our standard errors at the city level to account for geographic serial correlation. Since we have a low number of clusters we also correct the standard errors using wild

> 12Specifically, it corresponds to the number of PEP holders (between 10 and 64 years old) divided by the population between 10 and 64 years old, multiplied by 100,000.

> 13See Burbidge et al. 1988 and MacKinnon and Magee 1990 for more details on this transformation.

17
bootstrapping.

As a robustness test we also present results _controlling_ for the total reports of crimes in that city and period. The idea behind including this control is that we want to estimate the effects of the program on the _crime report by migrants_ , keeping constant the _overall number of crime reports_ . Reassuringly our results remain robust with and without this control.

# **IV. A Addressing potential dynamic endogeneity**

The validity of the main estimates described in equation 1 rests on the parallel dynamic behavior on the outcomes we examine for municipalities that had higher and lower PEP program take-up. Although evidence on the validity of this assumption will be illustrated in the next section, we also estimate a specification that was robust to dynamic individual responses to the program as a robustness test.

For this purpose, we follow our approach in Bahar et al. (2021). In particular, we employ an instrumental variable approach and estimate specification (1) through two-stages least squares (2SLS).<sup>14</sup> Our instrument is the average number of days undocumented Venezuelan migrants had to register for the PEP program in the last quarter of 2018. The number of days was defined randomly at the individual level by the form number of the registration in the RAMV survey. According to the government officials who oversaw this process, the local registration point gave this number to migrants in the order they arrived and registered. More importantly for us, the numbers did not correspond to any particular geographic or socioeconomic characteristics of the municipalities. The officials said they took this approach to scatter the applications to manage the administrative load and distribute it more evenly across locations. Based on the individual numbers for all PEP holders at the time of registration in a given municipality, we estimate the average registration days per municipality as: Reg. Days _c_ = � RAMV registrants assigned to time window j _<u>c</u> ×_ [Days in time window j] (2) _jεK_ Total RAMV registrants _c_

> 14It is common in the economics literature to apply instrumental variables in a difference-in-differences setting. As a pioneering example of combining these methods, see the seminal study by Duflo (2001).

18
where _K_ represents each of the 22 possible individual time windows assigned to migrants in the RAMV to request a PEP migratory status, which ranged between 78 and 141 days.<sup>15</sup> Therefore, _Reg.Daysc_ represents the average number of registration days available for the eligible population to receive the PEP in that city. Our identification strategy relies on the strong correlation between the length of the window to apply for the PEP amnesty and the number of people who actually applied (and received it). This is the case, as can be seen in a simple plot in Appendix Figure A3.

In addition, the exclusion restriction needs to hold in order for our instrument to be valid and to interpret our results as causal. That is, the effect of the time windows available to register for the PEP program in each municipality (exogenously assigned to migrants as they registered) affected crime reports by Venezuelans only through the actual number of Venezuelans who received the PEP migratory status. We believe this is a very reasonable assumption. Although the allocation of times to register was exogenous to the migrant, our identification relies on geographic variation of registration times across municipalities. Such variation exists due to the higher concentration of Venezuelans near the border, which means higher average registration times in border municipalities compared to areas further away with fewer migrants. This would threaten our identification strategy if there were other aspects of border proximity that could affect crime reports by Venezuelans through channels other than the regularization itself. Given the characteristics of the natural experiment we utilize, as well as all the controls in our specifications—including proxies for economic activity, sectoral distribution, public income and expenditures, governmental presence, crime, conflict, population poverty and vulnerability, informality, and distance to the border—it is reasonable to assume the exclusion restriction holds, especially since we control for distance to the border and the vast set of variables outlined above. Reassuringly, all our results are extremely similar when we use the 2SLS estimation suggesting that endogeneity was not biasing our coefficients in a substantial way.

# **V IMPACTS OF THE PEP ON CRIME REPORTS**

Our main results are in Table 3, which presents the OLS (panel A and C) and 2SLS (panel B and D) estimation of Equation (1). Panels And B include controls for total crime and Panels C and 15See Figure A2 in the Appendix for its distribution.

19
D exclude this control. All panels use as dependent variable the number of crime reports by Venezuelans per 100,000 inhabitants. Each column presents results for different types of crimes, which include homicides, threats, domestic violence, thefts, and sex crimes. Column (6) presents results for the aggregate of all crime reports by Venezuelans. The main variable of interest is in the first row, which corresponds to _β_<sup>_DID_</sup> of specification (1). Standard errors clustered by city level are in parentheses and False Discovery Rates (FDR) q-values that correct for multiple hypothesis testing as well as p-values that correct for a small number of clusters obtained using wild bootstrapping are presented in brackets. To maximize statistical rigor, we only consider a coefficient statistically significant only if they remain valid in the 2SLS estimates after adjusting for multiple hypothesis testing and accounting for the small number of clusters.

20
Table 3. Impacts of the PEP Program on Crime Reports by Migrants

||Homicides<br>(1)|Threats<br>(2)|Domestic Viol.<br>(3)|Thefts<br>(4)|Sex Crimes<br>(5)|Total Crimes<br>(6)|
|---|---|---|---|---|---|---|
|_Panel A. OLS - Crime Reports b_|_y Venezuelans_|_(ratesper_|_100,000)_||||
|_PEPc × I_[_PostAugust_2018]|0.040***|0.018|0.034|0.043|0.021**|0.087***|
||(0.014)|(0.015)|(0.020)|(0.024)|(0.008)|(0.024)|
|FDR q-values|[0.016]|[0.141]|[0.068]|[0.066]|[0.019]|[0.007]|
|bootstrap p-val.|[0.004]|[0.423]|[0.131]|[0.133]|[0.015]|[0.000]|
|Crime Reports Tot|0.071***|0.042**|0.069***|0.189***|0.058|0.442***|
||(0.024)|(0.018)|(0.023)|(0.057)|(0.038)|(0.084)|
|AdjR-squared|0.319|0.244|0.423|0.575|0.370|0.653|
|_Panel B. 2SLS - Crime Reports b_|_y Venezuelans_|_(ratesper_|_100,000)_||||
|_PEPc × I_[_PostAugust_2018]|0.033|0.024|0.078**|0.036|0.051**|0.105**|
||(0.017)|(0.016)|(0.033)|(0.035)|(0.017)|(0.041)|
|FDR q-values|[0.040]|[0.078]|[0.031]|[0.113]|[0.019]|[0.026]|
|bootstrap p-val.|[0.134]|[0.264]|[0.019]|[0.418]|[0.001]|[0.032]|
|Crime Reports Tot|0.072***|0.042**|0.075***|0.186***|0.059|0.450***|
||(0.023)|(0.017)|(0.024)|(0.052)|(0.037)|(0.082)|
|Adj R-squared|0.319|0.244|0.418|0.575|0.366|0.653|
|KP F Stat|20.29|21.11|21.27|21.88|21.16|21.46|
|_Panel C. OLS - Crime Reports b_|_y Venezuelans_|_(ratesper 1_|_00,000) - Excluding_|_Controls_|_for Total Crime_||
|_PEPc × I_[_PostAugust_2018]|0.052***|0.018|0.028|0.035|0.020***|0.073***|
||(0.015)|(0.016)|(0.020)|(0.023)|(0.007)|(0.026)|
|FDR q-values|[0.007]|[0.151]|[0.115]|[0.115]|[0.017]|[0.017]|
|bootstrap p-val.|[0.000]|[0.421]|[0.213]|[0.185]|[0.004]|[0.012]|
|AdjR-squared|0.298|0.231|0.416|0.572|0.362|0.646|
|_Panel D. 2SLS - Crime Reports_|_by Venezuelans_|_(ratesper_|_100,000) - Excludin_|_g Controls_|_for Total Crime_||
|_PEPc × I_[_PostAugust_2018]|0.049***|0.025|0.075**|0.032|0.050***|0.094**|
||(0.016)|(0.016)|(0.034)|(0.034)|(0.016)|(0.044)|
|FDR q-values|[0.007]|[0.049]|[0.032]|[0.128]|[0.007]|[0.032]|
|bootstrap p-val.|[0.018]|[0.229]|[0.040]|[0.472]|[0.004]|[0.065]|
|Adj R-squared|0.298|0.231|0.411|0.572|0.358|0.646|
|KP F Stat|21.21|21.21|21.21|21.21|21.21|21.21|
|Observations (All Panels)|1,080|1,080|1,080|1,080|1,080|1,080|

_Notes:_ The table presents the OLS and 2SLS estimations of specification (1). All columns include city and month-year fixed effects as well as the set of controls described in section IV. Standard errors are clustered at the city level. Cluster-robust wild-bootstrap p-values, and FDR q-values are presented in square brackets. To ensure statistical rigor, we consider a coefficient statistically significant only if it remains valid after adjusting for multiple hypothesis testing and accounting for the small number of clusters.

First of all, regardless of the specification choice the program resulted in higher reports in total 21
and sex crime. Second, in Panels B and D, the first-stage Kleibergen-Paap F statistic is large, eliminating concerns about weak instrumentation. For brevity, we focus on the 2SLS (panel B) results, since those estimates control for total crime and robust to endogeneity concerns. As such they are, in our view, the most robust results. In particular, the results of column (6) show that in the months after the roll-out of the PEP program, municipalities that had double the number of PEP holders (per 100,000 inhabitants) saw an increase of 0.1 in the rate of crimes reported by Venezuelans, on average. Considering that the rate of total crimes reported by Venezuelans is 0.79 (as documented in Table 2), this constitutes an increase of 12.5 percent, a sizable effect. In terms of specific types of crimes, we observe statistically significant effects of the program on reports of domestic violence, and sex crimes. Considering the point estimates for the outcome of reports by Venezuelans, the results are also economically significant. For example, a city with double the number of Venezuelan migrants who received the PEP program compared to the mean (relative to the local population), experienced an increase in the rate of sex crime reports by Venezuelans of 0.05. Since the average rate of reports by Venezuelans of these types of crimes is 0.08, this corresponds to more than an 62.5 percent increase in reporting after Venezuelans received regular migratory status. The same number for domestic violence crime reports is about 53 percent.

Note that the purpose of controlling the total number of reports _CrimeReports_<sup>_TOT_</sup> _ct_ —a proxy for _all_ crimes committed in that municipality every month—implies that our main estimator in this specification, when positive, does not represent an _increase in crimes_ but rather an increase in crime reports by Venezuelans. Naturally, the estimators for _CrimeReports_<sup>_TOT_</sup> _ct_ are all positive and statistically significant, since this variable explains a huge deal of variation of the dependent variable: the more crimes there were, the more crime reports Venezuelans made. Reasuringly, the results in Panel D are similar to the ones presented in Panels B. Yet, in those estimates we not only document increments on migrants reports of domestic violence and sex crimes but also homicides. Since the effects in homicide rates are not consistently observed in the 2SLS squares estimates we only see them as suggestive evidence.

As an additional robustness test we also estimate the effects of the program by aggregating the national data at the department-month level. We initially decided to only account for cities as rural 22
areas have high violence due to the presence of illegal armed groups and illegal crops, and hence, violent crime may be inflated. Yet, including the whole department is also a relevant exercise to test the validity of our main estimates. The results of this exercise are presented in Tables B1 and B2. They are qualitatively robust to our main results for sex crime and domestic violence. However, in these estimates we also document an increment of homicide rate reports, which as discussed earlier may be driven by the different context of Colombian rural areas.

The most obvious interpretation of these results is that the receipt of regular migratory status empowered previously undocumented Venezuelans to report crimes without fear of deportation or other legal repercussions. As such they might have increased trust from newly documented migrants in public institutions. If this is the case, we would expect this effect to be stronger among more vulnerable Venezuelan populations before they received the PEP migratory status. One dimension to test this hypothesis is gender, which is important because the results above concern crimes such as domestic violence and sex crimes, for which women have much higher rates of victimization. As expected, Venezuelan women reported such abuses at a much higher rate than A1. men, as we show in Appendix Table Table 4 replicates the main estimation using total reports by Venezuelan men (column 1) and women (column 2) as the dependent variable. The results show reports by women drive the overall patterns. When focusing on the 2SLS estimates (panel B), we find a 0.16 points increase in the rate of crime reports by female Venezuelan migrants in municipalities with twofold more PEP holders per 100,000 inhabitants. Again, since the share of crime reports by Venezuelans on average is one percent, this corresponds to an increase of about 30 percent.

Results when using reports by male Venezuelan migrants are statistically insignificant and the magnitude of the coefficient estimates is smaller, hinting that the totality of the effect in Table 3 is driven by female migrants. We focus on total crime reports given the challenges of focusing on reports by gender and by type simultaneously, since the number of crimes within each cell becomes much smaller and thereby significantly reduces our ability to estimate with enough precision.

23
Table 4. Impacts of the PEP Program on Crime Reports by Migrant’s Gender

|Male Total Crimes|Female Total Crimes|
|---|---|
|(1)|(2)|
|_Panel A. OLS - Crime Reports by Venezuelans (ratesper 100,000)_||
|_PEPc × I_[_PostAugust_2018]<br>0.023|0.109***|
|(0.020)|(0.026)|
|FDR q-values<br>[0.143]|[0.001]|
|bootstrap p-val.<br>[0.314]|[0.000]|
|Crime Reports Tot<br>0.089|0.407***|
|(0.069)|(0.088)|
|AdjR-squared<br>0.526|0.553|
|_Panel B. 2SLS - Crime Reports by Venezuelans (ratesper 100,000)_||
|_PEPc × I_[_PostAugust_2018]<br>0.014|0.159***|
|(0.029)|(0.042)|
|FDR q-values<br>[0.442]|[0.001]|
|bootstrap p-val.<br>[0.716]|[0.002]|
|Crime Reports Tot<br>0.085|0.430***|
|(0.067)|(0.088)|
|Adj R-squared<br>0.526|0.550|
|KP F Stat<br>21.46|21.46|
|_Panel C. OLS - Crime Reports by Venezuelans (ratesper 100,000) -_|_Excluding Controlsfor Total Crime_|
|_PEPc × I_[_PostAugust_2018]<br>0.020|0.096***|
|(0.019)|(0.027)|
|FDR q-values<br>[0.168]|[0.003]|
|bootstrap p-val.<br>[0.345]|[0.000]|
|AdjR-squared<br>0.525|0.543|
|_Panel C. 2SLS - Crime Reports by Venezuelans (ratesper 100,000)_|_- Excluding Controlsfor Total Crime_|
|_PEPc × I_[_PostAugust_2018]<br>0.012|0.149***|
|(0.028)|(0.044)|
|FDR q-values<br>[0.484]|[0.003]|
|bootstrap p-val.<br>[0.709]|[0.005]|
|Adj R-squared<br>0.525|0.541|
|KP F Stat<br>21.21|21.21|
|Observations (All Panels)<br>1,080|1,080|

_Notes:_ The table presents the OLS and 2SLS estimation of specification (1). All columns include city and month-year fixed effects as well as the set of controls described in section IV. Standard errors are clustered at the city level. Cluster-robust wild-bootstrap p-values, and FDR q-values are presented in square brackets. To ensure statistical rigor, we consider a coefficient statistically significant only if it remains valid after adjusting for multiple hypothesis testing and accounting for the small number of clusters.

Finally, we estimate the program’s effects on crimes reported by victims of Colombian nationality.

24
Our analysis reveals a reduction in all reported crimes (Table 5). These findings are consistent with reductions in overall crime rates and in line with the the significant improvements in migrants’ income and consumption following the regularization program, which may have reduced the likelihood of committing crimes for migrants in Colombia (Ib ́a ̃nez et al., 2024). Moreover, qualitative reports from local authorities indicate that undocumented migrants could not be convicted due to a loophole in Colombian legislation, whereas regularized migrants are subject to prosecution. Therefore, having proper documentation also increased the cost of committing crimes for migrants.

25
Table 5. Impacts of the PEP on Crime Reports by Colombians

||Homicides<br>(1)|Threats<br>(2)|Domestic Viol.<br>(3)|Thefts<br>(4)|Sex Crimes<br>(5)|Total Crimes<br>(6)|
|---|---|---|---|---|---|---|
|_Panel A. OLS - Crime Reports b_|_y Colombians_|_(ratesper 10_|_0,000)_||||
|_PEPc × I_[_PostAugust_2018]|-0.037**|-0.083*|-0.102**|-0.011|-0.111**|-0.024**|
||(0.017)|(0.055)|(0.033)|(0.007)|(0.048)|(0.007)|
|FDR q-values|[0.044]|[0.068]|[0.013]|[0.068]|[0.038]|[0.013]|
|Crime Reports Tot|0.931***|0.877***|1.068***|1.011***|0.783***|1.021***|
||(0.021)|(0.126)|(0.056)|(0.034)|(0.108)|(0.040)|
|AdjR-squared|0.928|0.773|0.827|0.973|0.784|0.954|
|_Panel B. 2SLS - Crime Reports b_|_y Colombians_|_(ratesper 10_|_0,000)_||||
|_PEPc × I_[_PostAugust_2018]|-0.049*|-0.186*|-0.130*|-0.016*|-0.166*|-0.044**|
||(0.022)|(0.096)|(0.072)|(0.010)|(0.098)|(0.015)|
|FDR q-values|[0.062]|[0.078]|[0.078]|[0.084]|[0.080]|[0.025]|
|Crime Reports Tot|0.933***|0.877***|1.063***|1.009***|0.782***|1.011***|
||(0.020)|(0.120)|(0.054)|(0.031)|(0.101)|(0.038)|
|Adj R-squared|0.928|0.770|0.826|0.973|0.783|0.953|
|KP F Stat|20.29|21.11|21.27|21.88|21.16|21.46|
|_Panel C. OLS - Crime Reports b_|_y Colombians_|_(ratesper 10_|_0,000) - Excluding_|_Controlsfo_|_r Total Crime_||
|_PEPc × I_[_PostAugust_2018]|0.116***|-0.085*|-0.190***|-0.049**|-0.120**|-0.056***|
||(0.032)|(0.064)|(0.065)|(0.018)|(0.056)|(0.011)|
|FDR q-values|[0.003]|[0.051]|[0.010]|[0.014]|[0.020]|[0.001]|
|AdjR-squared|0.444|0.641|0.657|0.857|0.668|0.833|
|_Panel D. 2SLS - Crime Reports_|_by Colombians_|_(ratesper 10_|_0,000) - Excludin_|_g Controls_|_for Total Crime_||
|_PEPc × I_[_PostAugust_2018]|0.161**|-0.154|-0.177*|-0.036|-0.177*|-0.068**|
||(0.065)|(0.120)|(0.100)|(0.031)|(0.100)|(0.023)|
|FDR q-values|[0.034]|[0.133]|[0.085]|[0.133]|[0.085]|[0.019]|
|Adj R-squared|0.443|0.640|0.657|0.857|0.667|0.833|
|KP F Stat|21.21|21.21|21.21|21.21|21.21|21.21|
|Observations (All Panels)|1,080|1,080|1,080|1,080|1,080|1,080|

_Notes:_ The table presents the results of the OLS and 2SLS estimations of specification (1). All columns include city as well as the set of controls described in section IV. Standard errors are clustered at the city level. False Discovery Rate q-values are presented in square brackets are presented in brackets. To ensure statistical rigor, we consider a coefficient statistically significant only if it remains valid after adjusting for multiple hypothesis testing and accounting for the small number of clusters.

# **V. A Assessing the validity of the identification strategy**

We also present our results in an event study format to measure the effect across time averaged by quarter and by gender. The benefit of this complementary result is twofold. First, since our sample includes many months before the rollout of the PEP regularization program, we can test 26
for pre-trends that would threaten the validity of our results. Second, it also enables us to see the evolution of crime reports over time after the program rollout. The results are illustrated in Figure 3.

The figure illustrates the results of specification (1), with the difference that the treatment is interacted with 12 indicator variables representing quarters (i.e., three-month periods) from Q1 of 2017 to Q4 of 2019 (instead of the _I_ [ _PostAugust_ 2018] _t_ dummy). Each marker represents the average effect of the treatment on crime reports for the three-month period that corresponds to each quarter. The upper, middle, and lower panels present results using total crime reports by all Venezuelan migrants, male migrants, and female migrants, respectively. The gray vertical line represents the start of the rollout of the PEP program in August 2018.<sup>16</sup> The whiskers represent 95 percent confidence intervals, based on standard errors clustered at the city level.

Figure 3 suggests no evidence of pre-trends, as all estimators before the grey line—which symbolizes the roll-out of the treatment—are not statistically distinguishable from zero, relative to the base period.<sup>17</sup> This is encouraging as it reduces possible endogeneity concerns. Consistent with Table 4 (which measures the differences on average between “before” months and “after” months), we distinguish a stronger effect in crime reports by female migrants, whereas we barely distinguish any robust effect in such reports by male migrants. (This occurred only in the last few months of 2019, more than a year after the program rollout). As such, the positive coefficients in the post-August 2018 period for all Venezuelans (upper panel) stem almost entirely from female migrants. In addition, the uptake in crime reports by female migrants seems to continue for more than a year after the amnesty, implying that it is not an immediate effect that subsequently reverts to pre-trend levels.

To complement this evidence and further support the validity of our results we also estimate a test of non-inferiority (Bilinski and Hatfield, 2018). These estimators are robust to violations on the parallel trend assumption. Our main results remain unchanged even after using this estimator 16Results are based on OLS estimates due to the limitation of having only one instrument.

> 17When limiting the dependent variable to reports by male Venezuelan migrants, there are instances before the treatment where the estimator suggests there is a statistically significant difference between localities for different levels of treatment. However, the point estimates in those instances are very small.

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Figure 3. Event Studies, Total Crime Reports <!-- Start of picture text --> All<br>Quarter<br>Male<br>Quarter<br>Female<br>Quarter<br>2017−Q1 2017−Q2 2017−Q3 2017−Q4 2018−Q1 2018−Q2 2018−Q3 2018−Q4 2019−Q1 2019−Q2 2019−Q3 2019−Q4<br>2017−Q1 2017−Q2 2017−Q3 2017−Q4 2018−Q1 2018−Q2 2018−Q3 2018−Q4 2019−Q1 2019−Q2 2019−Q3 2019−Q4<br>2017−Q1 2017−Q2 2017−Q3 2017−Q4 2018−Q1 2018−Q2 2018−Q3 2018−Q4 2019−Q1 2019−Q2 2019−Q3 2019−Q4<br>.015<br>.01<br>.005<br> (95% CI)<br>β<br>0<br>−.005<br>.015<br>.01<br>.005<br> (95% CI)<br>β<br>0<br>−.005<br>PEP−RAMV Roll−out<br>PEP−RAMV Roll−out<br>.015<br>.01<br>.005<br> (95% CI)<br>β PEP−RAMV Roll−out<br>0<br>−.005<br><!-- End of picture text --> _Notes:_ The figure presents the estimation of an event study based on specification (1). It estimates the effect of the treatment interacted with 12 quarter dummies from Q1 of 2017 to Q4 of 2019. The gray vertical line represents the beginning of the rollout of the PEP amnesty program in August 2018. The results are based on OLS estimates. The whiskers represent 95 percent confidence intervals based on standard errors clustered at the city level.

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(Tables B3 and B4).

As shown by Ib ́a ̃nez et al. (2024), the regularization program led to improvements in household consumption, income, and overall health, including mental health for adults who participated. These positive changes in economic and health conditions are inconsistent with any potential increase in domestic violence. Additionally, the program did not result in a disproportionate increase in female income compared to male income. Our analysis found no evidence of genderbased differences in the program’s effects on either income or consumption. Therefore, we can confidently rule out higher domestic violence as a factor underlying the observed effects.

These results reinforce our interpretation that empowerment—especially female empowerment— propels the patterns. Once their fear of deportation and other repercussions drops significantly, these migrants report more crimes to the police. This is particularly true for crimes such as domestic violence and sex crimes that disproportionately affect women. Qualitative interviews with Venezuelan migrants reinforced our sense that having the PEP migratory status empowered them to report human rights abuses without fearing punishment.

# **V. B What do PEP holders say about filing crime reports?**

We also leverage data from the Venezuelan Refugee Panel Study (VenRePs) that interviewed a representative sample of Venezuelan PEP holders and non-holders in 2021 to examine the PEP’s effects on migrant welfare.<sup>18</sup> One survey question asked respondents if they had reported being a victim of a crime to the police or any other institution. The responses are in Figure 4. Results for the full sample are in the left panel and by gender in the right panel. First, the results show strikingly low reporting rates across the board for migrants who were victims of a crime. Second, they confirm that migrants with the PEP reported crimes at higher rates than migrants without the PEP. In fact, 9.9 percent of household heads with PEP reported a crime; this number is lower for those without PEP (8.7 percent).

Third, the results by gender confirm our main conclusions by showing small differences between men with and without the PEP (of less than one percent) and more substantial differences for 18See Ib ́a ̃nez et al. (2024) for details of the sampling strategy.

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Figure 4. Has Filed a Complaint for Any Reason with the Police or Any Institution <!-- Start of picture text --> β<br>0.118<br>0.099<br>0.094<br>0.087 0.088<br>0.08<br>N = 1481 N = 1369 N = 965 N = 710 N = 516 N = 659<br>Full Sample Male Female<br>Has PEP−RAMV Doesn’t have PEP−RAMV<br>.14 .14<br>.13 .13<br>.12 .12<br>.11 .11<br>.1 .1<br>.09 .09<br>.08 .08<br>.07 .07<br>.06 .06<br>.05 .05<br><!-- End of picture text --> _Notes:_ The figure presents the propensity to file a complaint with the police or any official body. We present results for all, male, and female heads of households using the VenRePs Survey collected by Ib ́a ̃nez et al. (2024).

women. Particularly, female victims of a crime reported the event 11.8 percent of the time if they had the PEP but only 9.4 percent of the time if they did not have the PEP. The difference in reporting rates between PEP holders and nonholders is only statistically significant for women, as documented in Appendix Table C1.

# **VI IMPACTS OF THE PEP ON CRIMES COMMITTED**

To complement our main results, we also study the effects of the PEP on crimes committed by Venezuelan migrants. For this purpose, we employ data from Colombia’s Office of the Attorney General as described in the data section. We use the same 2SLS specification described in section IV to evaluate the effects of the regularization on the rate of total crimes directly committed by 30
Venezuelan migrants. We focus on crimes committed in capital cities after 2017 and before 2021.

The results in Table 6 are estimates for total crime rates as well as for crimes committed by men and women, separately. The estimates are in line with our main results suggesting actual reductions in almost all crime rates, although the estimated effects are imprecise. Moreover, we only observe increments in sex crimes committed by men, in line with the story that more reports are being made by females against potential partners of the same nationality. The estimated effects are robust to the exclusion of the control for total crime (Table B5). Moreover, the event studies across all outcomes show increases only in domestic and sexual crimes committed by Venezuelan migrants, as would be mechanically expected based on the results presented in the previous section (Figure B2).

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Table 6. Impacts of the Amnesty on Crimes Committed by Venezuelan Migrants

||Homicides|Threats|Domestic Vio.|Thefts|Sex Crimes|Total Crimes|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|_Panel A. All Venezuelans (ratesp_|_er 100,000)_||||||
|_PEPc × I_[_PostAugust_2018]_t_|-0.146|-0.098|-0.217|0.274|0.219*|-0.151|
||(0.123)|(0.071)|(0.183)|(0.189)|(0.128)|(0.244)|
|_CrimeReports_<sup>_T OT_</sup><br>_ct_|0.033|0.102***|0.334***|0.257**|0.340***|0.886***|
||(0.066)|(0.022)|(0.062)|(0.106)|(0.111)|(0.218)|
|R-squared|0.835|0.801|0.844|0.923|0.902|0.936|
|KP F Stat|7.730|8.544|7.754|8.359|9.255|7.532|
|_Panel B: Male Venezuelans (rates_|_per 100,000)_||||||
|_PEPc × I_[_PostAugust_2018]_t_|-0.194**|-0.053|-0.187|0.238|0.229*|-0.230|
||(0.092)|(0.052)|(0.176)|(0.173)|(0.123)|(0.237)|
|_CrimeReports_<sup>_T OT_</sup><br>_ct_|0.079|0.095***|0.342***|0.207**|0.364***|0.919***|
||(0.072)|(0.020)|(0.061)|(0.098)|(0.106)|(0.180)|
|R-squared|0.837|0.822|0.854|0.916|0.905|0.935|
|KP F Stat|7.730|8.544|7.754|8.359|9.255|7.532|
|_Panel C: Female Venezuelans (ra_|_tesper 100,000_|_)_|||||
|_PEPc × I_[_PostAugust_2018]_t_|0.023|-0.081|-0.015|-0.011|-0.001|-0.125|
||(0.050)|(0.057)|(0.057)|-0.09|(0.014)|(0.126)|
|_CrimeReports_<sup>_T OT_</sup><br>_ct_|-0.044|0.014|0.038|0.063|-0.047*|0.263*|
||(0.046)|(0.011)|(0.034)|(0.047)|(0.025)|(0.148)|
|R-squared|0.716|0.737|0.695|0.755|0.730|0.808|
|KP F Stat|7.730|8.544|7.754|8.359|9.255|7.532|
|Observations (All Panels)|150|150|150|150|150|150|

_Notes:_ The table presents estimates for the identification strategy described in section IV, using crimes rates per 100,000 inhabitants committed by Venezuelan migrants as the dependent variable. Panel A presents results for the full samples. Panel B presents results for men and panel C for women. The variable _Crime_<sup>_T ot_</sup> _ct_ is the inverse hyperbolic sine of the total crimes for the same type of crime per 100,000 inhabitants. All columns include city and year fixed effects as well as the set of controls described in section IV. Standard errors are clustered at the city level.

# **VII CONCLUDING REMARKS**

This study examines the crime effects of a migration reform that granted regular migratory status to approximately 281,000 Venezuelan migrants in Colombia. We document two key findings. First, we find that cities where more Venezuelans received regular migratory status experienced an increase in crime reports by these migrants. These reports are primarily related to domestic violence and sexual crimes and are predominantly filed by female migrants. Consistent with these findings, we observe a corresponding increase in convictions and trials of male Venezuelan per32
petrators of domestic and sexual crimes, which is intuitive since these individuals are likely the partners of the victims. By focusing on crime reports to local authorities, we capture a behavioral change reflecting the empowerment of a highly vulnerable population. These findings are significant because they highlight the social benefits of regularization programs—benefits that are often overlooked due to their difficulty to measure. The regularization program empowered women to report violations of their human rights, underscoring its importance.

Second, we observe a reduction in total crime reports by Colombian natives and a decrease in crimes committed by Venezuelans, excluding sexual and domestic crimes (which increased mechanically due to the increment in reports). This aligns with qualitative evidence suggesting that undocumented migrants who were reported or detained could not be prosecuted due to a loophole in Colombian legislation. Proper documentation ensures the enforcement of criminal laws. Additionally, the program’s documented increases in income and consumption (Ib ́a ̃nez et al., 2024) likely reduced petty crime by improving the economic opportunities of Venezuelan migrants, thereby lowering their propensity to commit crimes.

The evidence on the impacts of the PEP regularization program underscores the critical role of proper identification and registration of undocumented forced migrants in effective migration management and in ensuring the safety and security of both migrants and host communities. Many migrants arrive without formal documentation, complicating efforts to monitor and address criminal activities. A robust identification system, coupled with enhanced access to services, allows authorities to process individuals effectively, ensuring accountability for serious crimes while protecting the rights of innocent migrants.

Programs like PEP, which enhance access to social services, legal protections, and labor markets (as shown in Ib ́a ̃nez et al., 2024), also reduce risks of exploitation and criminal behavior. Furthermore, such programs enable law enforcement to monitor migration flows more effectively, reduce social tensions, and prevent wrongful deportations, all while safeguarding human rights.

A promising avenue for future research is to explore whether these effects remain consistent in the long term or diminish after the implementation of the treatment. Moreover, in the future, as the criminal trials resolve, it would also be extremely interesting to understand what are the long-term 33