Current Research Teams (2022-2023)
Banking Bad
Team Lead: Eoin Power
Faculty Lead: Mike Findley & Dan Nielson
Preventing, punishing, and prosecuting money laundering, and stopping global flows of illicit cash, have taken on increased importance for global policymakers over the last decade. Investigative reporting, like the Panama Papers, the Pandora Papers, and other exposés, has revealed how easy it can be for criminals, terrorists, and other bad actors to access the financial system while hiding behind the facades of seemingly legitimate enterprises and business partners. For years, the world has known little about the mechanics that underpin the global transfer of crooks’ ill-gotten gains, which has made it challenging to measure the scope of illegal behavior, identify risk factors and regulatory blind spots, and drive regulatory change. Building on prior work led by senior IPD investigators, which focused on the international legal regime governing access to shell companies, and which has already catalyzed meaningful reform in the United States, the Banking Bad team has turned to address compliance with global KYC/AML regulations in the banking sector. Working from the observation that de jure country-level compliance with the international regulatory regime is de facto implemented at the level of individual firms and financial institutions, we use experimental research methods to electronically contact banks and corporate service providers worldwide, to generate an as-if-real test of access to basic financial services, and adherence to global KYC/AML requirements.
Corruption
Team Leads: Regina Cruz, Augustine D'Eramo, Ansh Samdaria
Faculty Lead: Mike Denly
For about 25 years, empirical scholarship on corruption has primarily relied on perceptions data, but the drawbacks of these measures are ample and well-known. More recently, analyses centered on Brazil have showcased the utility of randomly assigned audits as a more objective alternative to perception-based measures. However, Brazil discontinued the program in 2015, and the country has many unique institutional features that limit the broader applicability of the numerous studies using the Brazil data. To address these limitations, in this project we will (1) collect and clean new audit data from Honduras, Guatemala, Mexico, India, and the Philippines; and (2) provide a framework for analyzing these new corruption data, which we will release to the public once they are fully cleaned. In the process, researchers participating on this team will improve their technical knowledge of corruption, researchers working on Latin American countries’ audits will improve their Spanish, and researchers working on the Philippines’ audits will learn how to scrape the audit data from a Python tool developed for this project. The Corruption team will work remotely with Professor Denly, who is a postdoctoral Research Fellow at the Institute for Advanced Study in Toulouse, France, this academic year.
Data4Defense
Team Lead: Eoin Power
If you know what to look for, you can head over to Google Maps, zoom in on the Saudi coastline about sixty miles from the Yemeni border, and find the remains of a shrimp farm. But what you would not guess from glancing at the satellite imagery is that its construction was partially funded by Raytheon, a company more widely known for manufacturing Patriot missile systems than prawns. Welcome to the weird world of defense offsets. Under the terms of these arrangements, aerospace and defense suppliers are required to offset some percentage of the value of their contracts with activities and investments that will benefit the acquiring country’s domestic economy. Estimates suggest the global value of these agreements will approach $400B by 2026, and more than 60 countries engage in some kind of offset policy, but publicly available data on these opaque and complex transactions is generally rare and low quality. With IPD’s new project, Data for Defense Offsets (informally known as Missile Shrimps), we aim to answer questions like: How, why, and when do states use offsets? Why and when do states change their offset strategies? When do they punish contractors for breaking offset requirements, and when do they let them off the hook? What kinds of companies benefit from offsets?
Data4Peace - Afghanistan
Team Lead: Jiseon Chang & Briana Villarreal
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Afghanistan team aims to produce zones of territorial control in order to understand who is most at risk during civil war conflicts. This project entails gathering qualitative information from news sources to code points of attack and control for non-state actors, such as the Taliban. This year, which coincided with the takeover by the Taliban in Afghanistan, the team focused on understanding humanitarian, political, and security risks.
Data4Peace - Colombia Ex-combatant Reintegration Experiment
Team Lead: Paul Orszag
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Colombia ex-combatant reintegration project is carrying out a resume experiment to learn what factors make it more difficult (or easy) for ex-combatants and victims to reintegrate into society after the peace agreement with the FARC. In official partnership with the Colombian government’s Agency for Reincorporation and Normalization (ARN), we are sending out actual ex-combatant resumes to thousands of employers and then engaging with the employers to learn about their interest, how interviews proceed, and whether jobs are offered. The team will be assisting ex-combatants in sending out resumes, coding employer responses, and analyzing the results.
Data4Peace - Policing & Urban Security
Team Lead: Jiseon Chang & Shannon Miller
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Policing Project under Data4Peace is a new team that started in Fall 2021. We have partnered with the Politics of Race and Ethnicity lab in the Government Department to analyze the extent to which policing is used as a boundary maintenance strategy between predominantly white and predominantly black/latino/asian or other minority areas. This is important because it could suggest that standard crime-based expectations are not accurate. But it would also suggest that existing race/ethnicity based expectations are also not accurate. Additionally, we are looking at patterns in the neighborhood geography of policing for as many cities as possible, linking to broader theories of state population control. We will be using GIS data on policing, race, ethnicity, and gentrification in city neighborhoods to address this and other questions. The team cleans, compiles, and codes policing data from major police departments in the US from 2012-2014, specifically working with arrest, race, ethnicity, and geocoding data to seek our question on whether geography affects civilian and policing behavior. As part of this project, we will also be analyzing historical data on how transportation networks in Austin, Dallas, and Houston may have exacerbated security and socio-economic challenges, and further contributed to discriminatory patterns of policing.
Exiting Russia
Team Lead: Rachel Jeon
Faculty Lead: Rachel Wellhausen
Russia’s invasion of Ukraine massively disrupted international business and raised the risks of operating there. All multinational corporations (MNCs) that were doing business in Russia found themselves operating in a jurisdiction now engaged in an aggressive interstate war. A bloc of Western states has imposed increasingly harsh sanctions on Russia and restricted the ability of MNCs from their jurisdictions to do business in Russia. Another set of states, including China and other emerging markets that are increasingly home to MNCs, have not. Against this backdrop, MNCs have also faced an unprecedented amount of worldwide attention in their decisions over whether to continue investing in Russia after 24 February 2022. All of this raises a critical question: under what conditions do MNCs divest, and how? Or, from the point of view of MNC home states: under what conditions can home states can rely on MNCs as tools of economic statecraft? In this project, we are building an original data set on the universe of tens of thousands of MNC subsidiaries operating in Russia and their actions regarding their Russian investments since the invasion of Ukraine by analyzing media reports, industry publications, and corporate press releases. This is a joint project with Professor Boliang Zhu at Penn State, so UT Austin IPD members have the opportunity to collaborate with Penn State student researchers as well.
Garbage IR
Team Leads: Marley O'Brien & Vilasini Nayar
Faculty Lead: Rachel Wellhausen
In the global waste trade, importing firms buy foreign-origin waste and scrap. Firms recycle some into inputs for new goods, while the rest is end-of-life (EOL) waste that has no further useful purpose – foreigners’ garbage that overwhelms waste management systems in developing states and causes environmental and social harm. The “Garbage IR” team will look into the most international organization in this issue area, the Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and their Disposal. Nearly every country in the world is a member of the Basel Convention – with the very notable exception of the United States. We will collect and code data on the history and day-to-day operations of the Basel Convention to understand how effectively it manages the international relations around garbage, and we will collect and code data on US garbage to understand the consequences of the US not being a member. (This research team is the next generation of the previous “Weaponizing Waste” IPD team, who helped build a dataset of hundreds of national-level laws that restrict waste imports.)
Governance - Government Responsiveness
Team Lead: Danny Cowser
Faculty Lead: Dan Nielson
Discrimination towards citizens based on ethnicity and socioeconomic inequality have been analyzed extensively at the level of elected politicians, but much less at the level of bureaucrats, whose mission requires prima facie impartiality towards citizens. In this paper, we examine whether government agencies discriminate (according to gender, race or ethnicity, immigration status, partisanship, religion, and/or socioeconomic status) in communication with their constituencies by conducting an array of correspondence-audit field experiments in which actual citizens contact bureaucrats to request information on public services in five countries (the U.S, South Korea, South Africa, Turkey, and Argentina). Benefitting from the variation within confederates in terms of their gender, race or ethnicity, immigration, political, religious, and socioeconomic background, we match them on covariates and statistically maximize differences on the key dimensions between individuals in pairs. Afterwards, we will randomly assign individuals from the pairs as treatments to government agencies. Our main outcome variable is responsiveness, particularly whether the agency responds, how helpful the response is, and how much time elapses for the response to be received. To analyze the data on how long it takes our confederates to get a response, we use survival analysis techniques (also known as time-to-event analysis). We anticipate that women, racial or ethnic minorities, immigrants, political affiliates, religious minorities, and economically disadvantaged individuals will be subject to more discrimination, manifested by a decreased likelihood in response, poorer quality responses, and increased length of response time.
Governance - Trade War
Team Lead: Danny Cowser
Faculty Lead: Dan Nielson
President Trump’s trade war with China proved to be detrimental to a wide swatch of US companies, yet resistance to the trade war remained limited to a handful of well-connected firms. To better understand the constraints to corporate political action, we are implementing a series of field experiments targeted at chambers of commerce and managers of US-based firms in which we are randomly providing different prompts. These include new information with original estimates of the costs of the trade war to their industry, a charge to bring down inflation, and a prompt that the tariffs are from Trump or Biden to activate political partisanship. Outcomes measure the chambers’ or firms’ willingness to take political action to oppose the trade war, such as organizing other firms, signing petitions, sending messages to members of Congress, or donating to advocacy groups.
Peacebuilding
Team Lead: Jiseon Chang & Danny Cowser
Faculty Lead: Mike Findley
For the past 30 years, International Non-Governmental Organizations (INGOS), the United Nations, the African Union, ECOWAS, governments, and private citizens have expended billions of dollars on peacebuilding initiatives. However, collectively we do not know the extent of success of these efforts in preventing the onset, continuation, and repetition of violence and civil war in countries around the globe. One of the enduring challenges of building sustainable peace in conflict ridden regions is the lack of systematic evidence about what works and what does not work in conflict prevention and peacebuilding. Our team is collecting data on all peacebuilding projects in the past 30 years (the novel dataset we call PeaDa 1.0) to provide the academic, policy, and peacebuilding sectors with the ability to analyze the overall effects of peacebuilding. Our tasks include coding peacebuilding reports, data analysis, data visualization, and geocoding.
Renewable Energy
Team Lead: Isabella Steinhauer
Faculty Lead: Nate Jensen
The recent passage of the U.S. Inflation Reduction Act (IRA) is one the most ambitious Federal programs that encourages renewable energy use, green consumer purchases, and funding for climate justice. Less well documented are fights across states on environmental policies. In this pilot project, we will collect data on proposed environmental legislation across a number of large states in the United States for the past five years. We are particularly interested in bills related to energy production, including subsidies for renewable energy and regulations of emissions from fossil fuels. Our goal is to identify the companies and interest groups supporting and opposing major energy legislation across states. Research assistants will be assigned as a state expert, by first documenting the major environmental legislation from 2018-2022 for the 10 largest US states (California, Texas, Florida, New York, Pennsylvania, Illinois, Ohio, Georgia, North Carolina, and Michigan).
Sweetheart Tax Deals
Team Lead: Zhizhen Lu
Faculty Leads: Nate Jensen & Dan Nielson
Thousands of cities, counties, and school districts give companies big tax breaks to relocate to their area. These “sweetheart” tax deals are generally bad for the economy, and they gobble up tax revenue that might otherwise be used for roads, water, parks, internet access, and schools. Local governments have a professional obligation to disclose these tax abatements in annual audit reports. But do they? And are they more likely to disclose if they are reminded of the disclosure standard or actual laws that require transparency? This is contacting thousands of local U.S. government offices and asking about their tax abatements. Will they come clean and admit to the sweetheart deals? This team will get answers through contacting the government offices directly. This project welcomes help in learning where all the local tax dollars go and who gets the tax breaks.
Team Lead: Eoin Power
Faculty Lead: Mike Findley & Dan Nielson
Preventing, punishing, and prosecuting money laundering, and stopping global flows of illicit cash, have taken on increased importance for global policymakers over the last decade. Investigative reporting, like the Panama Papers, the Pandora Papers, and other exposés, has revealed how easy it can be for criminals, terrorists, and other bad actors to access the financial system while hiding behind the facades of seemingly legitimate enterprises and business partners. For years, the world has known little about the mechanics that underpin the global transfer of crooks’ ill-gotten gains, which has made it challenging to measure the scope of illegal behavior, identify risk factors and regulatory blind spots, and drive regulatory change. Building on prior work led by senior IPD investigators, which focused on the international legal regime governing access to shell companies, and which has already catalyzed meaningful reform in the United States, the Banking Bad team has turned to address compliance with global KYC/AML regulations in the banking sector. Working from the observation that de jure country-level compliance with the international regulatory regime is de facto implemented at the level of individual firms and financial institutions, we use experimental research methods to electronically contact banks and corporate service providers worldwide, to generate an as-if-real test of access to basic financial services, and adherence to global KYC/AML requirements.
Corruption
Team Leads: Regina Cruz, Augustine D'Eramo, Ansh Samdaria
Faculty Lead: Mike Denly
For about 25 years, empirical scholarship on corruption has primarily relied on perceptions data, but the drawbacks of these measures are ample and well-known. More recently, analyses centered on Brazil have showcased the utility of randomly assigned audits as a more objective alternative to perception-based measures. However, Brazil discontinued the program in 2015, and the country has many unique institutional features that limit the broader applicability of the numerous studies using the Brazil data. To address these limitations, in this project we will (1) collect and clean new audit data from Honduras, Guatemala, Mexico, India, and the Philippines; and (2) provide a framework for analyzing these new corruption data, which we will release to the public once they are fully cleaned. In the process, researchers participating on this team will improve their technical knowledge of corruption, researchers working on Latin American countries’ audits will improve their Spanish, and researchers working on the Philippines’ audits will learn how to scrape the audit data from a Python tool developed for this project. The Corruption team will work remotely with Professor Denly, who is a postdoctoral Research Fellow at the Institute for Advanced Study in Toulouse, France, this academic year.
Data4Defense
Team Lead: Eoin Power
If you know what to look for, you can head over to Google Maps, zoom in on the Saudi coastline about sixty miles from the Yemeni border, and find the remains of a shrimp farm. But what you would not guess from glancing at the satellite imagery is that its construction was partially funded by Raytheon, a company more widely known for manufacturing Patriot missile systems than prawns. Welcome to the weird world of defense offsets. Under the terms of these arrangements, aerospace and defense suppliers are required to offset some percentage of the value of their contracts with activities and investments that will benefit the acquiring country’s domestic economy. Estimates suggest the global value of these agreements will approach $400B by 2026, and more than 60 countries engage in some kind of offset policy, but publicly available data on these opaque and complex transactions is generally rare and low quality. With IPD’s new project, Data for Defense Offsets (informally known as Missile Shrimps), we aim to answer questions like: How, why, and when do states use offsets? Why and when do states change their offset strategies? When do they punish contractors for breaking offset requirements, and when do they let them off the hook? What kinds of companies benefit from offsets?
Data4Peace - Afghanistan
Team Lead: Jiseon Chang & Briana Villarreal
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Afghanistan team aims to produce zones of territorial control in order to understand who is most at risk during civil war conflicts. This project entails gathering qualitative information from news sources to code points of attack and control for non-state actors, such as the Taliban. This year, which coincided with the takeover by the Taliban in Afghanistan, the team focused on understanding humanitarian, political, and security risks.
Data4Peace - Colombia Ex-combatant Reintegration Experiment
Team Lead: Paul Orszag
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Colombia ex-combatant reintegration project is carrying out a resume experiment to learn what factors make it more difficult (or easy) for ex-combatants and victims to reintegrate into society after the peace agreement with the FARC. In official partnership with the Colombian government’s Agency for Reincorporation and Normalization (ARN), we are sending out actual ex-combatant resumes to thousands of employers and then engaging with the employers to learn about their interest, how interviews proceed, and whether jobs are offered. The team will be assisting ex-combatants in sending out resumes, coding employer responses, and analyzing the results.
Data4Peace - Policing & Urban Security
Team Lead: Jiseon Chang & Shannon Miller
Faculty Lead: Mike Findley
The Data for Peace team is conducting research on various questions related to peace and conflict globally. The Policing Project under Data4Peace is a new team that started in Fall 2021. We have partnered with the Politics of Race and Ethnicity lab in the Government Department to analyze the extent to which policing is used as a boundary maintenance strategy between predominantly white and predominantly black/latino/asian or other minority areas. This is important because it could suggest that standard crime-based expectations are not accurate. But it would also suggest that existing race/ethnicity based expectations are also not accurate. Additionally, we are looking at patterns in the neighborhood geography of policing for as many cities as possible, linking to broader theories of state population control. We will be using GIS data on policing, race, ethnicity, and gentrification in city neighborhoods to address this and other questions. The team cleans, compiles, and codes policing data from major police departments in the US from 2012-2014, specifically working with arrest, race, ethnicity, and geocoding data to seek our question on whether geography affects civilian and policing behavior. As part of this project, we will also be analyzing historical data on how transportation networks in Austin, Dallas, and Houston may have exacerbated security and socio-economic challenges, and further contributed to discriminatory patterns of policing.
Exiting Russia
Team Lead: Rachel Jeon
Faculty Lead: Rachel Wellhausen
Russia’s invasion of Ukraine massively disrupted international business and raised the risks of operating there. All multinational corporations (MNCs) that were doing business in Russia found themselves operating in a jurisdiction now engaged in an aggressive interstate war. A bloc of Western states has imposed increasingly harsh sanctions on Russia and restricted the ability of MNCs from their jurisdictions to do business in Russia. Another set of states, including China and other emerging markets that are increasingly home to MNCs, have not. Against this backdrop, MNCs have also faced an unprecedented amount of worldwide attention in their decisions over whether to continue investing in Russia after 24 February 2022. All of this raises a critical question: under what conditions do MNCs divest, and how? Or, from the point of view of MNC home states: under what conditions can home states can rely on MNCs as tools of economic statecraft? In this project, we are building an original data set on the universe of tens of thousands of MNC subsidiaries operating in Russia and their actions regarding their Russian investments since the invasion of Ukraine by analyzing media reports, industry publications, and corporate press releases. This is a joint project with Professor Boliang Zhu at Penn State, so UT Austin IPD members have the opportunity to collaborate with Penn State student researchers as well.
Garbage IR
Team Leads: Marley O'Brien & Vilasini Nayar
Faculty Lead: Rachel Wellhausen
In the global waste trade, importing firms buy foreign-origin waste and scrap. Firms recycle some into inputs for new goods, while the rest is end-of-life (EOL) waste that has no further useful purpose – foreigners’ garbage that overwhelms waste management systems in developing states and causes environmental and social harm. The “Garbage IR” team will look into the most international organization in this issue area, the Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and their Disposal. Nearly every country in the world is a member of the Basel Convention – with the very notable exception of the United States. We will collect and code data on the history and day-to-day operations of the Basel Convention to understand how effectively it manages the international relations around garbage, and we will collect and code data on US garbage to understand the consequences of the US not being a member. (This research team is the next generation of the previous “Weaponizing Waste” IPD team, who helped build a dataset of hundreds of national-level laws that restrict waste imports.)
Governance - Government Responsiveness
Team Lead: Danny Cowser
Faculty Lead: Dan Nielson
Discrimination towards citizens based on ethnicity and socioeconomic inequality have been analyzed extensively at the level of elected politicians, but much less at the level of bureaucrats, whose mission requires prima facie impartiality towards citizens. In this paper, we examine whether government agencies discriminate (according to gender, race or ethnicity, immigration status, partisanship, religion, and/or socioeconomic status) in communication with their constituencies by conducting an array of correspondence-audit field experiments in which actual citizens contact bureaucrats to request information on public services in five countries (the U.S, South Korea, South Africa, Turkey, and Argentina). Benefitting from the variation within confederates in terms of their gender, race or ethnicity, immigration, political, religious, and socioeconomic background, we match them on covariates and statistically maximize differences on the key dimensions between individuals in pairs. Afterwards, we will randomly assign individuals from the pairs as treatments to government agencies. Our main outcome variable is responsiveness, particularly whether the agency responds, how helpful the response is, and how much time elapses for the response to be received. To analyze the data on how long it takes our confederates to get a response, we use survival analysis techniques (also known as time-to-event analysis). We anticipate that women, racial or ethnic minorities, immigrants, political affiliates, religious minorities, and economically disadvantaged individuals will be subject to more discrimination, manifested by a decreased likelihood in response, poorer quality responses, and increased length of response time.
Governance - Trade War
Team Lead: Danny Cowser
Faculty Lead: Dan Nielson
President Trump’s trade war with China proved to be detrimental to a wide swatch of US companies, yet resistance to the trade war remained limited to a handful of well-connected firms. To better understand the constraints to corporate political action, we are implementing a series of field experiments targeted at chambers of commerce and managers of US-based firms in which we are randomly providing different prompts. These include new information with original estimates of the costs of the trade war to their industry, a charge to bring down inflation, and a prompt that the tariffs are from Trump or Biden to activate political partisanship. Outcomes measure the chambers’ or firms’ willingness to take political action to oppose the trade war, such as organizing other firms, signing petitions, sending messages to members of Congress, or donating to advocacy groups.
Peacebuilding
Team Lead: Jiseon Chang & Danny Cowser
Faculty Lead: Mike Findley
For the past 30 years, International Non-Governmental Organizations (INGOS), the United Nations, the African Union, ECOWAS, governments, and private citizens have expended billions of dollars on peacebuilding initiatives. However, collectively we do not know the extent of success of these efforts in preventing the onset, continuation, and repetition of violence and civil war in countries around the globe. One of the enduring challenges of building sustainable peace in conflict ridden regions is the lack of systematic evidence about what works and what does not work in conflict prevention and peacebuilding. Our team is collecting data on all peacebuilding projects in the past 30 years (the novel dataset we call PeaDa 1.0) to provide the academic, policy, and peacebuilding sectors with the ability to analyze the overall effects of peacebuilding. Our tasks include coding peacebuilding reports, data analysis, data visualization, and geocoding.
Renewable Energy
Team Lead: Isabella Steinhauer
Faculty Lead: Nate Jensen
The recent passage of the U.S. Inflation Reduction Act (IRA) is one the most ambitious Federal programs that encourages renewable energy use, green consumer purchases, and funding for climate justice. Less well documented are fights across states on environmental policies. In this pilot project, we will collect data on proposed environmental legislation across a number of large states in the United States for the past five years. We are particularly interested in bills related to energy production, including subsidies for renewable energy and regulations of emissions from fossil fuels. Our goal is to identify the companies and interest groups supporting and opposing major energy legislation across states. Research assistants will be assigned as a state expert, by first documenting the major environmental legislation from 2018-2022 for the 10 largest US states (California, Texas, Florida, New York, Pennsylvania, Illinois, Ohio, Georgia, North Carolina, and Michigan).
Sweetheart Tax Deals
Team Lead: Zhizhen Lu
Faculty Leads: Nate Jensen & Dan Nielson
Thousands of cities, counties, and school districts give companies big tax breaks to relocate to their area. These “sweetheart” tax deals are generally bad for the economy, and they gobble up tax revenue that might otherwise be used for roads, water, parks, internet access, and schools. Local governments have a professional obligation to disclose these tax abatements in annual audit reports. But do they? And are they more likely to disclose if they are reminded of the disclosure standard or actual laws that require transparency? This is contacting thousands of local U.S. government offices and asking about their tax abatements. Will they come clean and admit to the sweetheart deals? This team will get answers through contacting the government offices directly. This project welcomes help in learning where all the local tax dollars go and who gets the tax breaks.