The Wisdom of the Crowd: Using ensemble machine learning techniques as an early warning indicator for systemic banking crises

Finance master project by Gabriela Lavagna, Helena Patterson, and Robizon Razmadze ’21

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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.

Abstract

We develop early warning models for systemic crisis prediction using machine learning techniques on macrofinancial data for 36 countries for quarterly data spanning 1970-2013. Machine learning models outperform logistic regression in out-of-sample predictions under the recursive window forecasting mechanism. In particular, using the ensemble random forest algorithm for both feature selection and prediction substantially outperforms the logit models. We identify the key economic and financial drivers of our models using the random forest framework by extracting each feature’s Gini impurity and corresponding information gain. Throughout the time period, the most important predictors are credit, foreign liabilities, asset prices and foreign currency reserves. 

Conclusions

  • The aim of the study was to construct a machine learning methodology to improve the predictive ability of systemic crises models. We applied these algorithms on macrofinancial data for 36 countries for quarterly data spanning 1970-2013. The results of the paper show that predictions of financial crises are more accurately obtained via machine learning algorithms as opposed to logit regression models in out-of-sample predictions (obtaining an AUC score of 0.77-0.81).
  • During the analysis, our goal was not only to be able to improve the predictive power of the models, but also to be able to select the most relevant and concise predictor variables. We applied the random forest ensemble algorithm to undertake feature selection and concluded that, over the years, the variables credit, foreign liabilities, asset prices and currency reserves were most important in predicting systemic crises.
  • The value-add derived from the models developed by us can be viewed in two main directions: Firstly, the need to use time series data as a means of predicting crises has meant many authors in the past have been unable to avoid the ‘looking to the future’ issue. We managed to alleviate this risk by using a recursive window estimation mechanism. The main benefit of this methodology is that it would allow policymakers to observe the predictors in real-time. Second, by being able to rank variables in order of importance, we were able to reveal the key economic and financial drivers which should be used by policymakers in evaluating any pressing risk of systemic crises. 
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Gender Gap and Retirement Decisions: the Maternity Pension Supplement in Spain

Economics master project by Jorge Casanova, Horia Guias, Carlos Javier López, Andrea Salvanti, and Patrick Sewell ’21

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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.

Abstract

Embedded in the growing governmental efforts to reduce the gender income gap, in 2016 a retirement pension supplement for mothers of at least two children was introduced in Spain. Through an Oaxaca-Blinder decomposition analysis, we find that the policy had a smaller-than-expected shrinking effect in the gender gap in retirement pensions. Using a difference-in-differences approach, we identify that the trade-off between the supplement incentivizing early retirement and the penalty this retirement modality entails in Spain is the mechanism driving this result. Finally, we developed a dynamic choice model to simulate women’s behavior under alternative versions of the policy.

Summary

Our main motivation was to analyse whether the maternity supplement proposed by the Spanish government in 2016 fostered gender equality through a reduction of the gender gap in retirement income. We decompose the average monthly retirement income for both men and women into its determinants and estimate how the gender difference in returns on pension of having two or more children changes after the policy is introduced. Our result is that the policy had a smaller-than-expected shrinking effect in the gender gap in retirement pensions, as the gender gap for regular retirement closes but the gap conditional on early retirement (i.e. below 65 years) remains unaffected.

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Figure 1: Time Series of Average Monthly Retirement Income: negative trend reverted for women retiring at 65 after the introduction of the policy but not for women retiring at an earlier age.

Using a difference-in-differences approach, we observe that the policy has a positive effect on all retirement hazard rates – i.e. the probability of retiring at a certain age, conditional on not having done so before.

One reason for the lower income effect is due to the trade-off that women face when they consider retiring before reaching the age at which they would start receiving their full retirement pension. On the one hand, early retirement increases the value of leisure, which could be especially beneficial for women with difficult working biographies. On the other hand, early retirement entails a penalty on the pension. For this group of women, early retirement reduces this penalty and hence, changes the trade-off in favour of early retirement, making the substitution of retirement income for more leisure more appealing.

Finally, we develop a dynamic choice model that depicts the trade-off between income and leisure that women face in retirement decisions, which can be used in a next step to simulate different retirement policies and compare their outcomes.

Future research on the maternity benefit ought to shed light on the different effects it produced between women who were and were not in a couple, and how much agents value leisure relative to money.

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The role of pensions: Exploring the link between pension funds, monetary policy and economic performance

Macroeconomic Policy and Financial Markets master project by Diljá Matthíasardóttir and Lara Zarges ’21

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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.

Abstract

Shocks to the European Central bank’s unconventional monetary policy trigger Dutch pension funds to search for yield: A structural VAR analysis shows that the pension funds reallocate their asset holdings from bonds towards equity and alternatives. The latter suggests the existence of a portfolio-rebalancing channel through institutional investors in the euro area. Moreover, we emphasize that the portfolio reallocation induced by monetary policy has increased the overall riskiness of the funds’ investments, which has potentially systemic risk implications. As the pension sector has evolved into a key player in the Dutch financial market, we additionally investigate the domestic real effects of a further increase in its size. In this context, a second SVAR approach shows that an expansive shock to total asset holdings boosts economic growth. As this link also works in the reverse direction, we point out the potential problems of a sudden dissaving of pension funds. Our results are of general interest for the aging societies in Europe as they improve the understanding of pension funds’ potential importance for economic policy in a period of demographic change. This paper hence urges future research to contribute to a better understanding of the link between demographic change, growing pension systems and central bank policies.

Conclusions

We infer that the change in the portfolio composition following a monetary shock to the ECB shadow rate after 2008 is driven by unconventional monetary policy succeeding in lowering the long-term interest rates. The resulting rise in equity and alternatives in the pension fund’s asset holdings can therefore be interpreted as evidence for the existence of a portfolio rebalancing transmission channel of quantitative easing in the euro area.

These findings also imply that due to unconventional monetary policy the riskiness of Dutch pension funds’ portfolios has been increasing gradually. Together with the sheer size of the Dutch pension sector and the funds’ tendency to herd-behavior this might be affecting local financial stability and with it the safety of Dutch pensions.

We further show that the size of the pension sector is a factor influencing economic growth and unemployment in the Netherlands.

Due to structural drivers such as demographic change, interest rates are likely to be lower for longer. We therefore stress the importance of future research on demographic effects such as the evolution of the size of funded pension systems on monetary policy conduction. This is e.g. important considering that the change of the Dutch pension system towards a full DC system in 2027 will most likely alter the consumption and saving patterns of citizens. The importance of bank deposits could shrink, impeding the supply of bank loans to the corporate sector. Firms would then likely turn towards financial securities to finance their operations. This would imply an overall decline in the importance of the credit channel for monetary policy transmission regardless of unconventional times. Therefore, a deeper understanding of the influence of central bank policies on institutional investors and insurers is required. This is especially important since the number of private, complementary pension schemes has been growing in many member states following the European Directive 2003/41/EC.

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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.

Extreme Weather and Health Outcomes in Women: Evidence from Colombia and Peru

Economics of Public Policy master project by Melina Aliayi, Manohar Gannavarapu, and André López ’21

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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.

Abstract

This paper investigates the relationship between health outcomes during delivery and extreme temperatures in Colombia and Peru. 

We used geo-coded household survey data from the Demographic and Health Survey Program (DHS), allowing us to construct an index accounting for the incidence of pregnancy complications in women during labor. Matching these health outcomes indicators with monthly-temperature data at a grid-cell level, we find that experiencing extreme temperatures during pregnancy, particularly cold temperatures, increases the probability of suffering pregnancy complications in the case of Colombia. Contrary to majority of the literature on health outcomes and temperature, we find no effect of experiencing extreme high temperatures. Interestingly, we find no significant effects in Peru.

Conclusions

  • We identify that experiencing at least one month of extreme cold temperatures during pregnancy increases the incidence of pregnancy complications by 2.5%.  
  • Shifting the analysis to the trimester level, we find that experiencing extreme cold temperatures during the first and third trimester of pregnancy increases the probability of pregnancy complications. 
  • Furthermore, we find an additional effect by wealth. Being poor increases the probability of experiencing pregnancy complications due to extreme cold temperatures by an additional 5%.
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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.

Abstract

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.

Conclusions

  • 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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Green Agreement in the Electricity Market

An ex-post evaluation of the 2013 Dutch Coal Power Plants Closure Agreement by Ilaria Noviello and Shaun Tey ’21

Smoke stacks
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The full title of this project is “Green Agreement in the Electricity Market: An ex-post evaluation of the 2013 Dutch Coal Power Plants Closure Agreement.”

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.

Abstract

There has been much theoretical discussion on whether Green Agreements can be a cost efficient means of improving the sustainability of products, but no empirical studies have been done on what the cost and benefits of past Green Agreements have been. 

In order to provide a substantive contribution to this discussion, we have undertaken an ex-post analysis of an agreement in the Netherlands to close five aging coal power plants in 2016 and 2017. First, we evaluated the ACM’s assumption that the plant closures would result in an increase of the Dutch wholesale electricity price in the Netherlands by undertaking a before-and-after analysis. Second, we examined how the ACM quantification of the benefits deriving from emissions reductions would have changed if it used its same methodology a year after the plants closed (in mid-2018). Third, we considered how the quantification of the benefits would have changed if the ACM used an alternative evaluation technique based on estimating consumers’ willingness to pay for Green Electricity.

Our findings indicate that the ACM was likely incorrect to oppose the agreement to close the coal power plants.

Conclusions

  • The before-and-after analysis indicates that the agreement to close the coal power plants did not result in any increase in the wholesale price of electricity in the Netherlands. This implies that this Green Agreement had no cost, while still producing a benefit of reduced emissions.
  • Our examination of the ACM’s method for quantifying the benefits derived from reduced emissions finds it to be volatile. In particular, due to subsequent changes to the methods used by the Dutch Government for valuing reduced emissions, the benefit of the Closure Agreement would be regarded as far higher if evaluated today. 
  • We find that it is unviable to use an alternative evaluation technique based on estimating consumers’ willingness to pay for Green Electricity.

Our conclusion suggests that those working on ex-ante assessments of Green Agreements should recognise that the volatility of their government’s approach to environmental policy can alter the accuracy of their assessments. As a result of this, regulators should coordinate better across government departments, in order to understand which methodologies are currently subject to scrutiny and could possibly change in the future.

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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.

Understanding Latent Vector Arithmetic for Attribute Manipulation in Normalizing Flows

Data Science master project by Eduard Gimenez Funes ’21

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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.

Abstract

Normalizing flows are an elegant approximation to generative modelling. It can be shown that learning a probability distribution of a continuous variable X is equivalent to learning a mapping f from the domain where X is defined to Rn is such that the final distribution is a Gaussian. In “Glow: Generative flow with invertible 1×1 convolutions,” Kingma et al introduced the Glow model. Normalizing flows arrange the latent space in such a way that feature additivity is possible, allowing synthetic image generation. For example, it is possible to take the image of a person not smiling, add a smile, and obtain the image of the same person smiling. Using the CelebA dataset we report new experimental properties of the latent space such as specular images and linear discrimination. Finally, we propose a mathematical framework that helps to understand why feature additivity works.

Conclusions

Generative Models for Deep Fake generation sit in between Engineering, Mathematics and Art. Trial and error is key to finding solutions to these types of problems. Theoretical grounding might only come afterwards. But when it does, it is simply amazing. By experimenting with normalizing flows we found properties of the latent space that have helped us create a mathematical model that explains why feature additivity works.

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The Macroeconomics of Fighting Climate Change

Macroeconomic Policy and Financial Markets master project by Astrid Esparza Sánchez, Benedikt J. F. Höcherl, and Wei Liam Yap ’21

Photo by Nicholas Doherty on Unsplash

The full title of this project is “The Macroeconomics of Fighting Climate Change: Estimating the Impact of Carbon Taxes, Public and Private R&D Investment in Low-Carbon Technologies on the Scandinavian Economy.”

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.

Abstract

The worldwide lockdowns and slowdown of the global economy in the past two years induced a significant overall decrease in CO2 emissions by 8.8% – the largest observed decrease since World War II. In that sense, COVID-19 emphasized the important trade-off between the emissions reductions necessary to fight climate change and economic welfare, which also constitutes a major political stumbling block to introducing policies aimed at halting climate change in normal times.

In order to further our understanding of this trade-off, we evaluate the macroeconomic impact of three policies that are commonly regarded as crucial to meeting national emissions targets:

  • Carbon taxes
  • Public Investment in low-carbon R&D
  • Private Investment in the R&D of low-carbon technologies, proxied by the number of patents for environmentally friendly applications 

In our paper, we develop a novel approach to identifying the long-term impact of these policies using an Structural Vector Autoregression (SVAR) model. We use a Blanchard-Quah long-run identification scheme and a Cholesky short-run identification respectively to  recover a one-standard deviation shock of carbon tax and low-carbon R&D, and investigate their impact on the evolution of GDP, employment and CO2 emissions. In an extension, we include both public and private low-carbon R&D in an SVAR to uncover how public and low-carbon R&D incentivize and complement each other.

Conclusions

We evaluate the effect of carbon taxes, public low-carbon R&D and private low-carbon R&D on GDP, employment and CO2 emissions in Finland, Norway, Denmark and Sweden. We find that carbon taxes do not significantly affect GDP and employment in the long run, but we also do not observe a significant reduction in CO2 emissions. Our results might be shaped by the fact that the first carbon taxes were introduced in 1990 and consequently data is still relatively limited.

Furthermore, our results indicate a significant negative effect of public and private low-carbon R&D on emissions in Denmark and Finland. However, the effect on GDP and employment is ambiguous and depends on the individual country. 

To the best of our knowledge, this is a first empirical indication of the relevance of R&D into low-carbon technologies in reducing CO2 emissions in Northern Europe. 

The implications of our result can fruitfully contribute to the debate about the adequate policy instruments for fighting climate change on at least three dimensions:

  • We find no evidence supporting the political concern that carbon taxes might negatively impact jobs and growth.
  • We provide evidence for the effectiveness of low-carbon R&D – public and private – in reducing CO2 emissions. However, country specific crowding in and crowding out effects of public and private investment in low-carbon technologies should be taken into account when deciding for example on appropriate innovation policies.
  • Our paper underlines the idea that revenues from carbon taxes might potentially be employed for financing low-carbon R&D which in turn could spur long-run, emission free economic growth.

In any case, as for the planet time is of the essence, the Economics profession should focus ever more efforts on understanding the macroeconomics of climate change.

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