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.

Conclusions

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.

Two Macro alumni publish in the same volume of European Economic Review

Publications by Nicolò Maffei-Faccioli ’15 and Alessandro Ruggieri ’12

The September 2021 volume of the journal European Economic Review includes two publications by alumni of the BSE Macroeconomic Policy and Financial Markets Program:

Does immigration grow the pie? Asymmetric evidence from Germany

by Nicolò Maffei-Faccioli ’15 (with Eugenia Vella)

We provide empirical evidence suggesting that net migration shocks can have substantial demand effects, potentially acting like positive Keynesian supply shocks. Using monthly administrative data (2006–2019) for Germany in a structural VAR, we show that the shocks stimulate vacancies, wages, house prices, consumption, investment, net exports, and output. Unemployment falls for natives (dominant job-creation effect), driving a decline in total unemployment, while rising for foreigners (dominant job-competition effect). The geographic origin of migrants and the education level of residents matter crucially for the transmission. Overall, the evidence implies that the policy debate should focus on redistributive strategies between natives and foreigners.

(Featured on this blog as a working paper last year)


Twin Peaks: Covid-19 and the labor market

by Alessandro Ruggieri ’12 (with Jake Bradley and Adam Hal Spencer)

This paper develops a choice-theoretic equilibrium model of the labor market in the presence of a pandemic. It includes heterogeneity in productivity, age and the ability to work from home. Worker and firm behavior changes in the presence of the virus, which itself has equilibrium consequences for the infection rate. The model is calibrated to the UK and counterfactual lockdown measures are evaluated. We find a different response in both the evolution of the virus and the labor market with different lockdown policies. A laissez-faire approach results in lives lost and acts as negative shock to the economy. A lockdown policy, absent any other intervention, will reduce the lives lost but increase the economic burden. Consistent with recent evidence, we find that the economic costs from lockdown are most felt by those earning the least. Finally, we introduce a job retention scheme as implemented by the UK Government and find that it spreads the economic hardship more equitably.


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Nicolò and Alessandro are both alumni of the Barcelona School of Economics Master’s Program in Macroeconomic Policy and Financial Markets. They both got their PhDs from the IDEA Program (UAB and BSE).

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Nicolò Maffei-Faccioli ’15 is a Senior Economist at Norges Bank.

 
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Alessandro Ruggieri ’12 is an Assistant Professor at the University of Nottingham.

The additional costs of living with a disability in the UK

Publication in the European Journal of Health Economics by Lukas Schuelke ’21 (ITFD)

A woman in a wheelchair around Camden street market
Photo: iStock.com/VictorHuang

Last year I worked on the article, “Estimating the additional costs of living with a disability in the United Kingdom between 2013 and 2016,” which was based on my undergraduate dissertation and which just got published in the European Journal of Health Economics.

My co-authors Luke Munford and Marcello Morciano are affiliated with the School of Health Sciences at the University of Manchester.

Abstract

In the United Kingdom, more than 20% of the population live with a disability. Past evidence shows that being disabled is associated with functional limitations that often cause social exclusion and poverty. Therefore, it is necessary to analyse the connection between disability and poverty. This paper examines whether households with disabled members face extra costs of living to attain the same standard of living as their peers without disabled members. The modelling framework is based on the standard of living approach which estimates the extra income required to close the gap between households with and without disabled members. We apply an ordered logit regression to data from the Family Resources Survey between 2013 and 2016 to analyse the relationship between standard of living, income, and disability, conditional on other explanatory variables. We find that households with disabled members face considerable extra costs that go beyond the transfer payment of the government. The average household with disabled members saw their weekly extra costs continually increase from £293 in 2013 to £326 in 2016 [2020 prices]. Therefore, the government needs to adjust welfare policies to address the problem of extra costs faced by households with disabled members.

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Lukas Schuelke ’21 is a Planning Analyst at Amazon in London, UK. He is an alum of the BSE Master’s in International Trade, Finance, and Development.

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.

How has public discourse on marriage equality affected change in US institutions?

Giulia Mariani ’12 (International Trade, Finance, and Development)

Gradual institutional change analyses have allowed drawing a more flexible line between stability and transformation when examining how institutions evolve over time, particularly in the absence of major critical junctures or exogenous shocks. Yet, the explanatory power of the theory has been undermined by a lack of attention to the overlapping boundaries of the modes of gradual institutional change, a relatively static model of agency, and conceptual confusion regarding what the modes of change exactly are.

In our recent article “Discursive Strategies and Sequenced Institutional Change: The Case of Marriage Equality in the United States” published in Political Studies, Tània Verge and I argue that addressing these shortcomings requires investigating the agent-based dynamics underpinning gradual institutional change and bringing to the fore the role of ideas. Indeed, ideas and discourses can have a constitutive impact in the creation, maintenance and reform of institutions, and actors strategically reframe problems and redirect solutions to influence both the process and the outcome of policy reforms.

Employing marriage equality in the United States as a case study, we show that the modes of gradual institutional change can be studied simultaneously as processes that unfold over time, often in a sequential fashion, as outcomes of these processes, and as strategies pursued by actors to steer, impede or undermine policy change.

Our results reveal that proponents and opponents of marriage equality have deployed discursive frames to legitimize institutional change to take off sequentially in a progressive direction — through the modes of “layering“ and “displacement“ — and in a regressive direction — through the mode of “conversion“.

Throughout this sequenced process, opposing actors have not only adjusted their discursive strategies to both their rivals and the targeted institutional venues, but have also shifted roles as change and status quo agents. Indeed, our study shows that the actors contesting the institutional status quo in one stage may become the actors defending it in a subsequent phase of the institutional change process, and vice versa. Thus, we argue that traditional, static conceptualizations of agency should be problematized and, rather than as resistance to gender-friendly reforms, opposition to marriage equality should be understood as a proactive mobilization to transform existing institutions.

The recent US Supreme Court decision in Fulton v. City of Philadelphia (2021) in favor of a Catholic foster care agency that refuses to work with same-sex couples, should then be understood as a victory of the years-long conservative strategy to undermine LGBT couples’ newly recognized right to marry.

Lastly, our study highlights the role of private actors as ideational entrepreneurs in the adoption and implementation of “morality policies,“ such as marriage equality. While morality policy scholars have so far predominantly examined how governmental actors shape policymaking, we show that the discursive strategies deployed by LGBT advocates, religious-conservative organizations and other private actors, such as foster care agencies, florists, and bakers, created new opportunities to influence policy debates and tip the scales to their preferred policy outcome.

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Giulia Mariani ’12 is a postdoctoral researcher in Political Science at Uppsala University. She is an alum of the Barcelona GSE Master’s in International Trade, Finance and Development.

How can we rethink our economy for a more sustainable future?

Nils Handler ’18 presents the D\carb Future Economy Forum

I recently founded the D\carb Future Economy Forum with the goal of better informing the public debate on climate change on topics such as green growth, green macroeconomics and green innovation.

D\carb is strongly inspired by my Master’s studies at Barcelona GSE such as Antonio Ciccone’s class on Economic Growth and Albert Bravo-Biosca’s course on innovation policy.

Last week we held our virtual kick-off event, “Green Growth: Technological Innovation, Market Incentives and Investments for a Green Economy” to discuss the opportunities and risks of transitioning our economy into a sustainable future.

Our speakers were Prof. Ottmar Edenhofer, Director and Chief Economist of the Potsdam Institute for Climate Impact Research, and Prof. Cameron Hepburn, Director of the Economics of Sustainability Programme and Professor of Environmental Economics at the University of Oxford. Johanna Schiele, McCloy-fellow at the Harvard Kennedy School, moderated the event.

The event was organized jointly with the Mercator Research Institute on Global Commons and Climate Change and the Sustainability Centre of the Hertie School of Governance.

Upcoming events and more information about these topics is available on our website:

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Nils Handler ’18 is a PhD Student at DIW Berlin. He is an alum of the Barcelona GSE Master’s in International Trade, Finance, and Development.

How we used Bayesian models to balance customer experience and courier earnings at Glovo

Javier Mas Adell ’17 (Data Science)

Neon sign depicts Bayes' Theorem

Glovo is a three-sided marketplace composed of couriers, customers, and partners. Balancing the interests of all sides of our platform is at the core of most strategic decisions taken at Glovo. To balance those interests optimally, we need to understand quantitatively the relationship between the main KPIs that represent the interests of each side.

I recently published an article on Glovo’s Engineering blog where I explain how we used Bayesian modeling to help us tackle the modeling problems we were facing due to the inherent heterogeneity and volatility of Glovo’s operations. The example in the article talks about balancing interests on two of the three sides of our marketplace: the customer experience and courier earnings.

The skillset I developed during the Barcelona GSE Master’s in Data Science is what’s enabled me to do work like this that requires knowledge of machine learning and other fields like Bayesian statistics and optimization.

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Javier Mas Adell ’17 is Lead Data Scientist at Kannact. He is an alum of the Barcelona GSE Master’s in Data Science.

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.

References

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.

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. https://doi.org/10.1111/jels.12276 

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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.