Economic gains from global cooperation in fulfilling climate pledges

Publication in Energy Policy by Sneha Thube ’16 (Economics) et al

Co2, Carbon Dioxide, Carbon, Oxygen, The Atmosphere
Image by Gerd Altmann from Pixabay

My paper “Economic gains from global cooperation in fulfilling climate pledges” (with Ruth Delzeitab and Christian H.C.A. Henning) is now available online.

Paper Abstract

Mitigation of CO2 emissions is a global public good that imposes different regional economic costs. We assess the distributional effects of cooperative versus non-cooperative CO2 markets to fulfil the Nationally Determined Contributions (NDCs), considering different CO2 permit allocation rules in cooperative markets. We employ a global computable general equilibrium model based on the GTAP-9 database and the add-on GTAP-Power database. Our results show the resulting winners and losers under different policy scenarios with different permit allocation rules. We see that in 2030, we can obtain gains as high as $106 billion from global cooperation in CO2 markets. A cooperative CO2 permit market with equal per capita allowances results in considerable monetary transfers from high per capita emission regions to low per capita emission regions. In per capita terms, these transfers are comparable to the Official Development Assistance (ODA) transfers. We also disaggregate the mitigation costs into direct and indirect shares. For the energy-exporting regions, the largest cost component is unambiguously the indirect mitigation costs.


With regard to the initial NDCs, aggregate economic gains from jointly achieving the NDCs are $106bn (i.e. 60% of costs with unilateral action) in 2030. Mobilizing cooperation via Article 6 is important.

When the costs are disaggregated into direct (i.e. domestic mitigation) and indirect (i.e. due to changes in international markets) within the energy-exporters (e.g., Russia, Canada, Middle East and North Africa) the dominant cost share arises from indirect costs.

We also model a scenario using where regional allowances allocated in proportion to the regional population (aka Carbon Egalitarianism) within a global ETS. This approach addresses global equity issues, aligns incentives of all countries & eliminates free-riding problem.

Large financial transfers (~$114bn in 2030) are generated via the carbon markets are leads to welfare improvements in the developing regions. These transfers are comparable to the per capita ODA received by some countries esp. in Sub-Saharan Africa.

The approach based on per capita emission benchmarking has also been suggested by Dr. Raghuram Rajan

If global justice is considered as a global public good, which similar to GHG mitigation, is underprovided, then the principle of carbon egalitarianism could promisingly combine an additional aspect to welfare, giving an important message for policymakers.

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Sneha Thube ’16 is a researcher at the Kiel Institute for World Economy. She is an alum of the Barcelona GSE Master’s in Economics.

Save The Euro Policy: European Debt Crisis and Covid-19 Pandemic

Economics master project by Kadir Özen and Hirotaka Ito ’21

Euro bills and face masks

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.


The 2008-2009 Global Financial Crisis led to European debt crisis leaving the periphery of euro zone with very high borrowing costs compared to core countries. When Covid-19 Pandemic Crisis hit the economies, monetary policy tools of European Central Bank prevented a similar debt crisis. We identify the underlying factor of the ECB monetary policy that is active during the 2011-2012 debt crisis and Covid-19 Pandemic periods operated through sovereign spreads preventing the contagion of fragmentation risk of euro area. We call this new factor, save-the-euro with which we shed light on the monetary policies of this unusual periods.


  • Identified the new dimension of the ECB Policy, save-the-euro policy, that captures stabilization policy of ECB that works through euro zone sovereign yields
  • This policy addresses euro area fragmentation risk 
  • An expansionary save-the-euro policy leads to a highly statistically significant appreciation of Euro against US dollar: Sharp contrast with the standard textbook treatment
  • Document the reversal of flight-to-safety flows in the euro area

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About the BSE Master’s Program in Economics

Wealth Inequality in the US: the Role of Heterogeneous Returns

Best paper award for Inês Xavier (Economics ’15, UPF PhD ’21)

Paper abstract

Why is wealth so concentrated in the United States? In this paper, I investigate the role of return heterogeneity as a source of wealth inequality. Using household-level data from the Survey of Consumer Finances (1989-2019), I provide new empirical evidence on returns to wealth in the United States, and find that wealthier households earn, on average, higher returns: moving from the 20th to the 99th percentile of the wealth distribution raises the average yearly return from 3.6% to 8.3%. To understand how these return differences shape the distribution of wealth, I introduce realistic return heterogeneity in a partial equilibrium model of household saving behavior. This exercise suggests that considering both earnings and return heterogeneity can fully account for the top 10% wealth share observed in the data (76%), which cannot be explained by earnings differences alone.

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Inês Xavier ’15 (PhD, UPF and BSE) is an Economist at the U.S. Federal Reserve Board of Governors. She is an alum of the BSE Master’s in Economics.

On the Effects of Sovereign Debt Volatility: a Theoretical Model

Economics master project by Oscar Fernández, Sergio Fonseca, Gino Magnini, Riccardo Marcelli Fabiani, and Claudia Nobile

Two pairs of hands exchange euro bills
Photo by cottonbro on Pexels

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.


We construct a theoretical Overlapping Generations (OLG) model to describe how sovereign debt crises can propagate in the economy under certain financial constraints.

In the model, households work when young and deposit their savings in exchange for a dividend, banks invest deposits in assets and government bonds. Banks, subject to legal and market requirements, invest a fixed fraction of deposits and own equity in assets. When prices of bonds fall due to perceived sovereign debt risks, banks can invest less on capital goods directly affecting the business cycle. This paper simulates the deviations from steady-state produced by a shock to government securities and provides insights into macro-prudential policy implications.

We find that a sovereign debt crisis affects young and old generations differently, with the latter facing higher fluctuations in consumption. We also find that the macro-prudential policy can be effective only at very high levels on the old, but ineffective for the younger generation.


This paper draws three main conclusions about the impact of a sovereign debt crisis on the business cycle within the proposed OLG theoretical framework:

  1. A decline in government bond prices leads to lower output, wages and dividend negatively affecting present and future consumption. However, this effect is different for young and old generations. In particular, the old seem to face more sudden changes and higher deviations from steady-state values when a sovereign debt crisis takes place.
  2. The proposed macro-prudential policy does not seem to offset the impact of a fall in government bonds prices on the business cycle. In fact, almost all the macroeconomic variables of interest in our theoretical model do not change significantly, relative to their steady-state values, when the supervising authority modifies the capital requirements for banks.
  3. A very aggressive policy on capital requirements (i.e. x=0.9 for the whole period) can compensate for the negative shock bonds prices have on dividends and, therefore, consumption for the old.

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About the BSE Master’s Program in Economics

How COVID-19 affected the Catalan regional elections

Analysis by Iván Auciello Estévez ’21 and Pau Jovell Codina ’21 (Economics)

Editor’s note: this article was originaly published in the popular economics blog, Nada es Gratis (in Spanish).

In the Catalan elections held on 14 February 2021, just a few weeks after the peak of the third wave of COVID-19, voter turnout was significantly lower than in 2017 (51.3% compared to 79.1%) and the lowest in history. Despite the political context being different compared to 2017, in the run-up to the election predicted turnout remained at similar levels until the emergence of Covid-19 – whereupon it dropped sharply. In these extraordinary elections, the vote share of the parties changed which shifted the Catalan political spectrum.

We study this relationship between Covid-19 and electoral results in Catalonia. To estimate the effect of the pandemic we explore the differences in cumulative Covid-19 incidence at the municipal level and compare it with electoral outcomes controlling for economic and demographic variables (population density, percentage of over-65 years old, share of foreign population and the unemployment rate).

The most widely used model of electoral participation, that of Riker and Ordeshook (1968), considers that the decision to participate is based on a cost-benefit trade-off between the expressed benefit of voting (feeling fulfilled, considering that civic duty is fulfilled, etc.) and the cost that individuals associate with participation. This cost rose sharply, because voting implied a higher risk of contracting the disease and the inconvenience caused by anti-covid measures. Therefore, higher costs would imply lower turnout as shown by several empirical studies, which find that with small increases in cost turnout drops significantly (eg. Aldrich, 1993). We assume that the increase in cost is the same for all (although there could be differences by age, and so we control for the most vulnerable group, the over-65s), which would imply a fall in participation, but could also induce changes in the outcome. This change may be due to differences in the “sentimental” benefit of voting between voters of different parties.

Economic theory also indicates who voters choose, conditional on voting. According to “retrospective” voting theory, voters support or punish parties in government in response to their performance in a crisis such as Key (1966). In contrast, according to “prospective” voting theory, the individual votes for the party that he believes will do better or, as Leininger and Schaub (2020) argue, seeks to match the party in regional and national government for more optimal crisis management.

Effect on participation

As seen in the maps above, the areas with the highest cumulative Covid incidence also have a lower percentage of participation, especially the Barcelona metropolitan area. Our analysis shows that an increase of 100 points in cumulative incidence in the last 14 days is related to a drop of 2.6 percentage points in turnout. To understand the magnitude, this is equivalent to one extra Covid case in a municipality of 1,000 inhabitants, so we estimate that the effect of the pandemic is quite high. To understand the impact of the second and third waves of Covid-19, we have conducted the analysis with cumulative incidence measures in the last month and in the last 4 months prior to the elections. However, as the period lengthens, the effect on turnout decreases (1.3 and 0.4 percentage points respectively).

However, the political context also changed: while in 2017 the voting framework was centred on the independence process (which led to the historical record turnout); in 2021 it was the pandemic that defined the elections. However, the trigger for this change of context (and the neglect of the independence process) was the eruption of the virus. As can be seen in the graph below showing the predicted turnout for the elections to the Parliament of Catalonia. Since Covid-19 appears to be the only element of exogenous variation between municipalities when comparing the 2017 and 2021 elections, we can infer causality.

These results are in line with the theory of the myopic voter who takes into account episodes closer to the election when voting. In this case, the myopic voter is acting rationally, as they account for the actual risk at the time of the vote rather than the risk of the past few months.

Effect on results

Secondly, the elections brought a major shift in the political spectrum, as can be seen in the bar charts above. For this reason, we have not been able to include other elections, as they were not comparable with each other. We have grouped the political parties into the following ideological and identity groups:

  • Pro-independence left: ERC and CUP.
  • Pro-independence right-wing: JUNTSXCAT and PDECAT
  • Non-independence left-wing: PSC and PODEMOS
  • Non-independence right: PP, Cs, and VOX

First, we respectively analyse the pro-independence and non-independence groups, the victors (the pro-independence coalition), and the opposition. The results show that the pandemic has a positive effect on the percentage of the vote of the pro-independence parties and a negative effect on the non-independence group. This effect can be seen as a retrospective vote, showing a certain approval by pro-independence voters of how the regional government has handled the pandemic.

On the other hand, in the analysis of the groups divided into identity and ideological groups, we find that the group with the highest positive coefficient is the non-independence left – the coalition in charge of the central government at the time of the elections. This behaviour is associated with the prospective vote. With the arrival of Salvador Illa (The Spanish Minister of Health during the pandemic) as the PSC candidate, the party was reinforced and ends up as the winner of the elections. This positive effect can be seen as an attempt to align the post-pandemic recovery strategy in Catalonia with that of the rest of Spain.

In conclusion, our results suggest that COVID-19 had a significant outcome in the Catalan elections that translated into a negative relationship between the virus and turnout. In contrast, the relationship is positive between cumulative incidence and the vote of pro-independence parties and the non-independence left-wing group. At the same time, the retrospective theory seems to hold true as there has been strong support for the government in office based on their management of the pandemic.

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Iván Auciello Estévez ’21 is a student in the Barcelona GSE Master’s in Economics. After graduating he plans to work as a Research Assistant at Banco de España.

Pau Jovell Codina ’21 is a student in the Barcelona GSE Master’s in Economics. After graduating he plans to work as a Research Assistant at Banco de España.

This post was edited by Ashok Manandhar ’21 (Economics).

What is the effect of Long-Term Care (LTC) benefits on healthcare use?

Helena Hernández-Pizarro ’12 is part of a research team that uses administrative data to estimate quality of life and health.

person holding a stress ball
Photo by Matthias Zomer on

This post is based on the article Ayudas a la dependencia y uso de los servicios sanitarios, ¿qué nos dicen los datos administrativos? (Nada Es Gratis, April 2021) by Helena Hernández-PizarroGuillem López CasasnovasCatia Nicodemo, and Manuel Serrano Alarcón.

Since the 2007 implementation of the “Dependency Act”, people with functional limitations in Spain can request Long-Term Care (LTC) benefits. The Act’s main objective is to improve the care and quality of life of people who have lost their autonomy. Fourteen years later, evidence on the impact of the Dependency Act in Spain on its beneficiaries remains scarce. This is partly because we need data on the quality of life of this population in order to fully evaluate its impact and we still don’t gather a suitable indicator. However, we can assess the impact of benefits by utilising data on the use of healthcare services as a proxy to estimate quality of life and health, and that is the approach we have taken in our research.

The relationship between LTC benefits and healthcare use

The effect of LTC benefits on healthcare use is not trivial and may have implications not just for the quality of life of recipients, but also for the management of healthcare services.

If access to LTC improves the health status of dependent people (for example through better treatment management, better nutrition or avoiding domestic accidents), investments in the LTC system could save healthcare providers money in the future. On the other hand, LTC benefits might increase the demand for healthcare, for example through greater health-monitoring by caregivers.

Using data on the type of healthcare service, type of admission and diagnoses, we can better understand the relationship between benefits and healthcare use, and therefore increase the efficiency in the allocation of social care and healthcare resources to design a better integrated care system.

The data

To study the effects of LTC benefits on healthcare use, we needed to gain access to data from social services and healthcare providers and then link it. As others have shown, this was not easy, but fortunately, the interest of the institutions involved in this research —CatSalut, AQuAS, the Departament de Treball, Afers socials i Famílies de la Generalitat de Catalunya (DTASF) (Labour, Family and Social services department) and CRES (UPF) — helped to facilitate this process.

Even with access to the data, measuring the effect of LTC benefits on the health system is not straightforward. Those who qualify for benefits will by definition have worse health and, regardless of the new policy, will probably make greater use of the healthcare system than those who don’t qualify for benefits. Therefore, simply comparing those applicants who receive LTC benefits with those who don’t would not help us to identify the effects of the Dependency Act.

To deal with this, we use an instrumental variable technique based on the “leniency” of the evaluators. The idea is as follows. When there is an evaluation guided by objective criteria such as when grading an exam, imposing a judicial sentence or assigning the severity of a medical case, there is always a degree of subjectivity from the person performing the assessment. It is common in research literature to consider this as a source of exogenous variation, because there is no predictable basis by which assessors should differ. This allows us to use traditional statistical methods that can identify any consequences associated with new policies. In our context, despite the fact that the assessment is based on the Dependency Assessment Scale, each examiner has a small margin of subjective interpretation. Thus, there are examiners who, on average, tend to provide slightly higher scores, so that their applicants qualify for greater LTC benefits. Since the applicant cannot choose his/her examiner, being assessed by one examiner or another affects the probability of receiving a benefit which is exogenous to the assessment process.

The results

In the two graphs below, we summarize the most important results from our research.

Figure 1 shows that access to LTC benefits decreases by 7 percentage points the probability of a group of hospitalizations considered by the medical literature as avoidable with continuous care for the elderly (such as hospitalizations for injuries, ulcers and nutritional deficiencies). This represents a 60% reduction in this type of hospitalization.

Figure 1. Effect of LTC benefits on the probability of avoidable hospitalizations

Figure 2 shows that unscheduled visits to primary care decrease by almost 10 visits two years after receiving LTC benefits, a 50% reduction with respect to the mean. Our analysis by diagnosis indicates that this reduction is explained by a sharp drop in visits caused by the economic and family situation of the individual.

Figure 2. Effect of LTC benefits on visits to primary care. Scheduled vs Unscheduled


Our results show that LTC benefits can mitigate the use of healthcare services, in line with the conclusions of previous research. Additionally, our data allows us to go one step further, identifying in detail the types of services which are the most affected.

Particularly interesting are the results relating to primary care, where LTC benefits strongly reduce visits not strictly related to health causes. It seems that reinforcing the LTC system will not only improve the quality of life of dependents and caregivers, but may also reduce the pressure on the healthcare system.

Undoubtedly, these results are important given the chronic under-financing of the LTC system, especially in a context where COVID-19 has highlighted a need for real integration between social and health care. This is just one example of how access to, and analysis of administrative data can contribute to the evaluation of public policies, facilitating better informed decision making. 

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Helena Hernández-Pizarro (ECON ’11, HEP ’12, GPEFM ’17) is a Research Fellow at the Centre for Research in Health and Economics (CRES-UPF).

International cooperation on carbon pricing

OECD working paper by Sneha Thube ’16 (Economics)

Photo by Markus Spiske on Pexels

As we are approaching the COP26 meeting to be held in Glasgow later this year, a highly anticipated milestone that is to be expected is the finalization of the rulebook for Article 6 of the Paris Agreement. Article 6 calls for ‘voluntary cooperation’ between public and private actors in carbon markets and other forms of international cooperation to meet the climate goals.

Ex-ante policy modelling assessments have shown that international cooperation on carbon pricing can result in economic and environmental gains that potentially could be used to boost the ambition of the climate targets. In our OECD working paper (jointly with Sonja Peterson, Daniel Nachtigall and Jane Ellis) we present a review of the literature on ex-ante policy modelling studies that examine the economic and environmental gains that could be realised if nations cooperate on climate action. Ex-ante modelling studies usually use Computable General Equilibrium (CGE) models or Integrated Assessment Models (IAM) to understand the socio-economic and environmental impacts of climate policies. We group the research articles into the following five types of cooperative actions that could be realised between countries – carbon price harmonization, extending the coverage of carbon pricing systems, implementing a multilateral fossil fuel subsidy reform, establishing international sectoral agreements and, mitigating carbon-leakage through strategic climate coalitions and border carbon adjustment.

The literature shows that all forms of international cooperation could potentially deliver economic and environmental benefits. Extending carbon markets to include new regions would reduce the aggregate mitigation costs but would not lead to unanimous gains for each of the participating countries and thus compensation mechanisms would be needed to incentivize participation from countries that would face costs. Sectoral agreements have a limited impact but could help in the reduction of GHG emissions though not cost-effectively. All of the studies unambiguously show that removal of fossil fuel subsidies would lead to an improvement in aggregate global welfare.

Further details about the results and individual papers can be found here:

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Sneha Thube ’16 is a researcher at the Kiel Institute for World Economy. She is an alum of the Barcelona GSE Master’s in Economics.

The Poor and the Rich: Preferences over Inflation and Unemployment

Paper in the Journal of Money, Credit and Banking by José Nicolás Rosas ’20 (Economics) and Marc Hofstetter

Photo by olia danilevich on Pexels

Our paper “The Poor and the Rich: Preferences over Inflation and Unemployment”, written jointly with Marc Hofstetter, has now been published in the Journal of Money, Credit and Banking (JMCB). Here is a summary of our work:

Strong Central Bank’s anti-inflationary postures are often viewed as a way to implement policies consistent with the preferences of the poor. Five examples:

  1. Mankiw (2006): inflation “is not a tax on all assets but only on non-interest-bearing assets, such as cash. The rich are able to keep most of their wealth in forms that can avoid the inflation tax”.
  2. FED Kansas City President, George (2017): “not as enthusiastic or encouraged as some when I see inflation moving higher,” because “inflation is a tax and those least able to afford it generally suffer the most.”
  3. Cœuré, ECB (2012): “inflation is also particularly harmful to the poorest parts of the population”; “poorer households tend to hold a larger fraction of their financial wealth in cash, implying that both expected and unexpected increases in inflation make them even poorer.”
  4. Central Bank of Colombia: low & stable inflation is important because “increasing inflation means a redistribution of income against the poor.” 
  5. Central Bank of Chile: inflation tends to hurt those who have a greater proportion of their wealth in money, that is, the poorest.

But do the poor prefer stronger anti-inflationary policies than the rich? 

This is not obvious: anti-inflationary policies often come at the cost of less economic activity and higher unemployment rates, and these side effects of contractionary monetary policies are not necessarily evenly spread across the income distribution. 

Accordingly, preferences vis-à-vis inflation versus unemployment might also not be evenly distributed across income groups. We study these relative preferences across the income distribution.

We find that:

  1. Both the poor and the rich dislike inflation and unemployment and they both dislike extra points of unemployment more than extra points of inflation. 
  2. The aversion to unemployment relative to inflation is higher in Latin America than in Europe.
  3. Our main point: the poor have a higher aversion to unemployment relative to inflation than the rich. This finding is at odds with the commonly held view by Central Banks that hawkish monetary policies line up with the poor’s preferences.

The idea that a compassionate Central Bank should fight inflation strongly notwithstanding the consequences on unemployment is at odds with the preferences along the income distribution estimated in our paper.


José Nicolás Rosas G. ’20 is an MRes/PhD student at UPF and Barcelona GSE. He is an alum of the Barcelona GSE Master’s in Economics.

New evidence of granular business cycles from German cities

Federica Daniele ’13 shares a paper accepted to Review of Economics and Statistics.

journal cover

My paper “The Micro-Origins of Business Cycles: Evidence from German Metropolitan Areas” joint with Heiko Stueber has been accepted to the Review of Economics and Statistics. Here is a summary of our work:

Cities compete to attract large firms. When Amazon announced in 2017 the opening of its second headquarters, 238 US cities signed up for it. Large firms bring jobs and can boost local productivity through spillovers. However, the downside is that they generate excessive local volatility.

We leverage quarterly data on size of all German establishments from 1990 to 2014 to show that a buildup of concentration of economic activity in the hands of few sizable firms is systematically associated with higher volatility in local labor markets in subsequent months.

The reason is granularity. When concentration is high, shocks to large firms do not average out with shocks to smaller ones and the evolution of local employment ends up mimicking the evolution of employment in the large firm. The economy experiences “granular” business cycles.

Our paper is the first to provide solid time-series support to granular business cycles as in Carvalho and Grassi. However, we show that large firms do not seem capable to trigger both booms and busts alike. Our evidence points in favor of granularity-driven recessions only.

Finally, we calibrate the parameters governing local firm dynamics to match the local employment law of motion, because we want to see what are the causes of the disproportionate presence of large firms in big cities. We find that it’s because of higher growth opportunities in big cities.

Bottom line: the volatility externality imposed by large firms encourages short-time work schemes as opposed to layoffs and may justify using size-dependent forms of public support for crisis management, but the benefit might have to be weighed against potential moral hazard.

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Federica Daniele ’13 is an economist at the Bank of Italy. She holds a PhD from UPF and Barcelona GSE and is an alum of the Barcelona GSE Master’s in Economics.

Tackling domestic violence using large-scale empirical analysis

New paper in Journal of Empirical Legal Studies co-authored by Ria Ivandić ’13 (Economics)

A woman holds a sign in front of her face that reads, "Love shouldn't hurt."
Photo by Anete Lusina from Pexels

In England, domestic violence accounts for one-third of all assaults involving injury. A crucial part of tackling this abuse is risk assessment – determining what level of danger someone may be in so that they can receive the appropriate help as quickly as possible. It also helps to set priorities for police resources in responding to domestic abuse calls in times when their resources are severely constrained. In this research, we asked how we can improve on existing risk assessment, a research question that arose from discussions with policy makers who questioned the lack of systematic evidence on this.

Currently, the risk assessment is done through a standardised list of questions – the so-called DASH form (Domestic Abuse, Stalking and Harassment and Honour- Based Violence) – which consists of 27 questions that are used to categorise a case as standard, medium or high risk. The resulting DASH risk scores have limited power in predicting which cases will result in violence in the future.  Following this research, we suggest that a two-part procedure would do better both in prioritising calls for service and in providing protective resources to victims with the greatest need. 

In our predictive models, we use individual-level records on domestic abuse calls, crimes, victim and perpetrator data from the Greater Manchester Police to construct the criminal and domestic abuse history variables of the victim and perpetrator. We combine this with DASH questionnaire data in order to forecast reported violent recidivism for victim-perpetrator pairs.  Our predictive models are random forests, which are a machine-learning method consisting of a large number of classification trees that individually classify each observation as a predicted failure or non-failure. Importantly, we take the different costs of misclassification into account.  Predicting no recidivism when it actually happens (a false negative) is far worse in terms of social costs than predicting recidivism when it does not happen (a false positive). While we set the cost of incurring a false negative versus a false positive at 10:1, this is a parameter that can be adjusted by stakeholders. 

We show that machine-learning methods are far more effective at assessing which victims of domestic violence are most at risk of further abuse than conventional risk assessments. The random forest model based on the criminal history variables together with the DASH responses significantly outperforms the models based on DASH alone. The negative prediction error – that is, the share of cases that would be predicted not to have violence yet violence occurs in the future – is low at 6.3% as compared with an officer’s DASH risk score alone where the negative prediction error is 11.5%.  We also examine how much each feature contributes to the model performance. There is no single feature that clearly outranks all others in importance, but it is the combination of a wide variety of predictors, each contributing their own ‘insight’, which makes the model so powerful.

Following this research, we have been in discussion with police forces across the United Kingdom and policy makers working on the Domestic Abuse Bill to think how our findings could be incorporated in the response to domestic abuse. We hope this research acts as a building block to increasing the use of administrative datasets and empirical analysis to improve domestic violence prevention.

This post is based on the following article:

Grogger, J., Gupta, S., Ivandic, R. and Kirchmaier, T. (2021), Comparing Conventional and Machine-Learning Approaches to Risk Assessment in Domestic Abuse Cases. Journal of Empirical Legal Studies, 18: 90-130. 

Media coverage

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Ria Ivandić ’13 is a Researcher at LSE’s Centre for Economic Performance (CEP). She is an alum of the Barcelona GSE Master’s in Economics.