In his own narrative: an interview with Robert Shiller
"Loi travail" un réel changement
by José M. Álvarez and Marina Sánchez del Villar
par Mariam Aounallah
7 Talking about depressions: an
interview with Tim Kehoe
62 Le "Burkini" Un maillot de
bain ou plus que ça ?
by Kristina Hagen
par Mai Wang
10 Faculty Article On the econometrics of matching by Shruti Sinha
13 What caused the Spanish
housing bubble? by Alea Muñoz Guisande
15 PhD Research God insures those who pay? by Eva Raiber and Julie Lassebie
Professional On Campus
64 Internship Reports 68 Alumni Testimony
69 Business Talk Big time for smart data by Lisa Degalle
70 Distinguished Lectures Series
18 About the absence of pluralism
in economics by Manon Schuegraf
Narrative Economics. Robert J. Shiller
by Alfonso Muñoz
71 Mens sana in corpore sano
20 A Farewell to Arms?
An everlasting illness: violence throughout Colombia's history
by Nicolas Martinez
"No": Colombia's risky bet
by Oscar Diaz
Price shocks and armed conflict in Colombia
by Isabella Medina
Participation on the European Doctoral Olympics Sports competition in ClermontFerrand 2016. Our quest for the medals
by Rodrigo Arnabal
73 Coffee Talks Charter cities and governance of megacities
by Mahi ElAttar
74 Integration Weekend
No Economics in the Title
32 Egypt: back to square one? by Omar Dogheim, Mahi ElAttar, Farah Hathout and Moheb Said
36 Five huge lessons of the US
elections by Mahi ElAttar and Friedrich Lucke
40 So long and thanks for all the fish by Tristan Salmon
by Fernando Stipaniccic and Lars Nordgreen
75 BDE Note 76 Junior Etudes Note
77 Say It Aloud! Note 78 Meet the TSEconomist Team! 79 Picture Quiz
The power of the right: The rise of Trump in American politics
by Carlos Francisco Restituyo Vassallo
48 Socialismo o Muerte by Friedrich Lucke
Why should we go to Mars? An argument for space exploration
by Olivier Ferrage
55 Brazil: Impeachment and the day
All the writings in this issue remain the strict responsibility of their authors and in no way represent the opinions of TSE and its members. Article refrences are available upon request. The online version contains modifications. Contact us: email@example.com www.tseconomist.com
by Alipio Ferreira Cantisani and Gabriela Miyazato Szini
New office: MD303
The Team Editorial Board
Mariam Aounallah Alicia Bassière Gregory Beaumont Nicola Benigni Sai Bravo
Pauline de Villèle Lisa Degalle Oscar Mauricio Diaz Omar Doghiem Mahi ElAttar
Olivier Ferrage Selin Goksel Kristina Hagen Farah Hathout Arthur Hill
Annie Krautkraemer Victoire Lamarca Max Langer Zhuxi Li Vincent Lim
Moritz Loewenfeld Friedrich Lucke Gosia Majewska Nicolas Martinez Rose Mebiame
Paul Montesinos David Montoya Jose Alfonso Muñoz Lars F. Nordgreen Valeria Plata Franco
Roxana Pozo Aurelie Prefumo Linda Punt Tristan Salmon Manon Schuegraf
Anna Schulze Tilling Fernando Stipanicic Andres Villarreal Lee Tyrrell-Hendry Joaquin Urgel Mai Wang
Moheb Said Photographer
Marina Sánchez del Villar Editor-in-Chief
José M. Álvarez Deputy Editor
Maria Teresa Aguilar Rojas Head of Design
Philip Hanspach Head of Organization
Catalina Salas Head of Communications
The times, they are changing
Come gather around readers, wherever you roam, and welcome to the 14th issue of The TSEconomist. The new editorial board is thrilled to present to you the first number of the academic year. This semester we welcomed a significant inflow of new students who quickly set to the task of producing a high quality and ambitious issue. Like the times, TSE is also changing and we are changing with it. After almost five years on the market, it is safe to say that we are just getting started. Returning readers may notice that we have restructured the sections of the magazine. We are now casting a “Spotlight” on the armed conflict in Colombia. This semester’s Spotlight team reflects on the background and reasons they believe pushed Colombians to the rejection of the peace agreement. I strongly encourage you to read their pieces, which hopefully will shed some understanding to a problem that sometimes feels distant in Europe. In addition, to resonate with the student community, we included a “French Corner”. We inaugurate this section with two timely articles: one on the French labour law and one on the burkini affair that shook France during the summer. Moreover, we continue the line of previous publications by featuring interviews with prominent economists and a Nobel Prize winner, a faculty article and a PhD contribution. In these pages you will also find numerous articles written by the new figure of in-house writers. The ambition of our projects is growing as well. We have just started collaborating with the institutional magazine of the school, the TSE Mag, which will give our members a wider access to interviewees. Next semester, we will host the fourth TSEconomist Public Lecture, where The Economist’s correspondent Adam Roberts will speak on “A changing media landscape: social, political and economic consequences”. Do not miss this event on February 23rd. In addition, we are working on the third edition of our successful Writing Workshop to share with the TSE community the writing mechanisms we have learnt over the years. We will, of course, continue to hold our monthly Coffee Talks, which have seen a significant increase in popularity thanks to the moderators and topics discussed this semester. Finally, to celebrate our fifth-year anniversary, we are organizing a get-together of old and new members in March. The TSEconomist is growing quickly and adapting to the changing times. If there is one thing 2016 has shown us is that of the importance of factual, well written, and well-presented information. This is a fascinating time to be in a studentmagazine. Do not hesitate and come to meet us. In the words of 2016’s Nobel Prize in Literature Bob Dylan: “Come writers and critics who prophesize with your pen, and keep your eyes wide the chance won’t come again.” Marina Sanchez del Villar Editor-in-Chief
Cover painting: El presidente by Fernando Botero.
Fernando Botero is a figurative artist and sculptor from Colombia. His work focuses on people and figures in large, exaggerated volume, which can represent political criticism or humor, depending on the piece. This painting belongs to the Colombia's central bank art colection.
References: El presidente. Fernando Botero, 1997. Colección de Arte Banco de la República. Recuperado de http://banrepcultural.org/coleccion-dearte-banco-de-la-republica/artista/fernando-botero Manuel Marulanda “Tiro Fijo”, 1999. Colección de Arte Banco de la República. Recuperado de http://banrepcultural.org/coleccion-dearte-banco-de-la-republica/artista/fernando-botero
In his own narrative: An interview with Nobel Laureate Robert Shiller
by José M. Álvarez and Marina Sánchez del Villar
Robert Shiller with Marina Sánchez del Villar and José M. Álvarez. . Credit to Gosia Majewska.
It is not every day that two master students interview a Nobel Prize Laureate in Economics. Understandably, we were nervous, overprepared, and excited. We had done our homework, but we did not expect to be interviewing the Laureate in what can only be described as a TV newsroom. The cameras, the lights, the equipment, and only five people in the room. We had no idea TSE even had such a room. We hope the reader will enjoy the interview as much as the two of us did when preparing and conducting it. Robert Shiller does not need an introduction. A simple Google search would suffice to show how vast and influential his work has been. Professor Shiller won the Nobel in 2013, is the current Sterling Professor in Economics at Yale University, and is one of the most cited and influential economists on IDEAS ranking. He graduated from the University of Michigan in 1967 and obtained his Ph.D. from the Massachusetts Institute of Technology (MIT) in 1972 under the guidance of Franco Modigliani. He famously opposed the common belief that markets aggregate information efficiently, going against the predominant view in financial economics at the time and challenging none other than University of Chicago’s Eugene Fama—a heavyweight of the field with whom he and Lars Peter Hansen later shared the Nobel Prize. His latest research has focused around how narrative shapes decision-making and consequently the economy. We met with Professor Shiller after his IAST Distinguished Lecture to talk about the influence of narrative on decision-making, the rise of Donald Trump in the United States, and Eugene Fama. The following is an edited version of that talk.
*This interview was conducted alongside James Nash, who works as a freelance journalist for TSE Mag and IAST Connect. We hope that this will be the first of many more collaborations between TSE’s magazines.
6. A narrative of panic inspired by the possibility of leaving the EU - promoted, for example, by the Bank of England - preceded the months before the EU Referendum. Should the Bank of England, as well as other institutions and experts, have taken their roles as narrators more cautiously prior to the vote? I think that people really didn’t believe Britain would exit. It was a surprise. And so maybe people didn’t do enough to combat that. Personally, I think it’s a tragedy. The European Union has many advantages for everyone and it’s a community and the sense of community was damaged by this. Unfortunately, it was also a campaign for Brexit that exaggerated fears about immigrants or [fears about] domination by Europe. So it was a bit of a misinformation campaign. I’m hopeful, though, that Europe and the UK will stay united in some spiritual sense despite this.
7. From Brexit to the current U.S. presidential race, disruptive political narratives are playing an important role. We have seen Donald Trump, for example, running on a political platform mostly based on his own narrative rather than on facts. What does the rise of Trump say about the importance of narrative on elections or on markets overall? The Donald Trump phenomenon is a beautiful example of the importance of narrative. In the primaries leading up to his nomination as the Republican Party candidate, there were many other candidates who looked perfectly plausible—in fact, more plausible in my opinion. And they just faded away. It was his showmanship and the stories that he generated. The narratives that would be spread then by word of mouth about Trump that powerfully swayed voters in the primaries and continues to do so today. The problem is that you cannot argue against a narrative with statistics. So if Donald Trump tells a story about Mexican immigrants committing crimes in America, you might try countering it by saying that actually their crime rate is actually no higher. That’s the statistic. But Trump just ignores that and continues to tell stories as if they were a danger. In order to counter that you have to form a narrative, another story, that outperforms his narrative. That’s a challenge for Hillary Clinton and she’s trying to do that. I think he’s a tough man to beat on narrative. He has a sense of story quality and a sense on how to do it.
Robert Shiller. Credit to Gosia Majewska.
make a country prosperous and have shared prosperity are problems of risk and incentivisation. We can diminish the impact of economic risks if we have plans to share the risks and we can help incentivize people if people are given a share in the benefits or profits that an enterprise makes. So I’m sounding traditional as a finance professor, but I think that finance needs to also take into account human behaviour, incorporate that into a broader vision for finance, and it will make for a better world.
9. What is your reading of the IAST story? What is the narrative of your visit to Toulouse? Well, my visit to Toulouse involved speaking to people with many different perspectives. And I found it very instructive for me. You have some very smart people here working in different traditions and coming together. At least I saw them coming together. And I think that is extremely important for research. When research is narrowly defined, then it can become repetitive. The interdisciplinary cross-fertilization is, I believe, extremely important. And I saw it happening here.
8. Now let’s talk about the future of the financial markets. In particular, how do you think that the emergence of FinTech firms (financial firms relying in technological innovation), with their optimistic and easygoing narrative, will have an impact on consumer’s investment decisions? I feel positive about financial innovation. It has a very important role in our society because it brings a real technology to solving real problems. The fundamental problems that help
“When research is narrowly defined, then it can become repetitive. The interdisciplinary cross-fertilization is, I believe, extremely important.”
10. Professor Shiller, for the final and million-dollar question: who’s right, Eugene Fama or yourself? [Laughs] Eugene Fama and I won the Nobel Prize on the same year but we have often been described as opposites. I actually am a big admirer of Eugene Fama. And I do not think he’s opposite. He’s not opposite me. I think we agree on basic facts. And I think, though, that there’s a different rhetoric. I think we belong to different parties. I don’t actually belong to a party, and maybe he doesn’t either. But he has a different way of summarizing and he has a different policy prescription. I’m sure he’s less sympathetic to government intervention. But these are judgment matters. I think it’s ok. I think people in disciplines have opposite views, but as long as they are respectful of the facts, their research is useful. And so I have used Eugene Fama’s research and I’ve read it carefully and I think it’s basically right if you can get away from the politics.
like Spain, Italy, and Portugal are close to that. It looked like they were starting to grow the past two years, but now I have doubts whether that’s going to keep up.
2. How can we explain an economic crisis with macroeconomic theory? There is something called business cycles, and business cycles are small deviations around the growth path. They occur mainly because of shocks—such as shocks in the terms of trade for a small open economy or interest rate shock. Great depressions are something much worse. They last for a longer period and are much deeper. Prescott and I found from the cases we looked at that the depressions were a result of bad government policy. We tried to identify what that policy was. Sometimes we could just say what policy was not. The big question is: What kind of mistakes can a government make that leads to 10 years of falling output? I specifically worked on comparing Mexico and Chile. Both Chile and Mexico started the 1980s with very large economic downturns, but then Chile righted itself and started growing very vigorously. After 4 years of severe contraction they just started growing. This continued for 15 years and was one of the best periods of economic growth in the world. Chile used the opportunity to make reforms, to clean up the banking sector, and to get growing—whereas Mexico did not. Instead they nationalised the banks, which then operated inefficiently. They had bad bankruptcy procedures. Mexico also had companies that were hiring a lot of workers, but that were not growing or innovating. They were doing nothing better than surviving. The companies were zombie institutions. This went on in Mexico for about 10 years and it killed the economic progress in the country during the 1980s.
3. What are often the causes of great depressions? External shocks can cause temporary downturns, but it is mistakes in government policy that turn these downturns into great depressions. Government behaviour is the main cause. For example, Finland was in a severe economic downturn because people make mistakes. This lead to the Scandinavian banking crisis in the early 1990s. But if there is a reform you can get out of this situation. Finland nationalised half of the banks and within two years they had either gotten rid of the
Flags of Scandinavia. Source: wikimedia.org.
banks or reprivatized them. This is similar to what happened in Chile.
The 2008-2009 financial crisis in the US was not that severe and so it didn’t lead to a great depression, but it was government policy that deregulated financial markets without thinking of the consequences. Actually when the financial market was failing due to activities that should have been judged as criminal for the people in the financial sector, the US decided it was more important to get growing again, and they didn’t prosecute many of these cases.
“The 2008-2009 financial crisis in the US was not that severe and so it didn’t lead to a great depression, but it was government policy that deregulated financial markets without thinking of the consequences.”
Pamphlet for the Chilean consitutional referendum, 1980.
4. Which structural reforms have most commonly been used to escape a recession? It depends on what goes wrong. Great depressions can be caused by a lot of things, so what you should do is fix what goes wrong. In most cases the financial system failed. In other cases, there may be big problems in the labour market, and so there is need for reforms in the labour market. Often it is a financial problem, but whether the financial system is the cause of the crisis or that it just collapses under the weight of crisis, we cannot always tell. It might not be the shock that causes the crisis, but if you let it collapse and do nothing to fix it then you are going to have a problem and a great depression. This is what happened also in Japan. When Japan found out that
On the econometrics of matching
by Shruti Sinha
Al Roth, in his 2012 Nobel speech, noted that matching markets are some of the most important types of markets that we are involved in— in fact, matching markets can determine what schools we go to, what jobs we get, and maybe who we marry. Both, Al Roth and Lloyd Shapley, who jointly won the 2012 Nobel Prize in Economics, have worked extensively on the fundamental problem of market design in such markets. Most notably, their research has led to many improvements in the National Resident Matching Program in the US hospitals, and to the creation of a matching program that matches kidney donors to patients. Early works in this area were mainly concerned with developing the theoretical tools to understand the allocation mechanism in such markets. In fact, the economic theory of matching models has been around for more than five decades. However, it is only recently that there has been a surging interest in taking these theoretical matching models to the data. One reason for this has been the easier availability of datasets that are observed at the level of the matches, be it men/women matching with spouses; students matching with schools and colleges; residents matching with hospital residency programs; and many more. This has posed a set of new questions and challenges for the econometricians and empirical economists alike. The econometric challenges lie in finding the right set of conditions given the features and limitations of the dataset, under which we can formulate credible strategies to estimate the agent preferences for matching.
Simply put, a matching market is a two-sided market with disjoint sets of agents on the two sides. Agents on both sides have a say in forming a match or remaining unmatched according to some innate preferences. These matching preferences are usually what we want to estimate from the data. As empiricists, we assume that the match allocations observed in the data are generated in equilibrium, or according to some stability criterion. Broadly, this literature on matching can be classified into two strands—one where transfers or prices play a role as a mechanism to clear markets (transferable utility models, or TU), and the other where transfers do not play a role (non-transferable utility models, or NTU). Each of these can be further classified
“Matching markets can determine what schools we go to, what jobs we get, and maybe who we marry.”
based on how many matches agents on each side are allowed to make. For example, in a school choice problem, one school can match with multiple students but one student can match with at most one school. This is called one-to-many matching. In a traditional marriage market, one man can match with at most one woman and vice-versa. This is called one-to-one matching. We can also have the case where, say, an upstream firm can choose to match with many downstream firms and vice-versa. This is called many-to-many matching. Depending on the setting of our application—whether it is TU or NTU, and how many matches an agent can form—the matching model can have different implications on the number of stable allocations, whether the stable allocations are efficient, etc. For concreteness, let us look at the questions and challenges posed to empirical research in a couple of these models.
Alvin E. Roth. Source: wikimedia.org.
Marriage Markets A widely studied case of matching in the empirical literature is that of the marriage market. A major question often posed in this literature is how a policy or technology shock affects the matching patterns or the agents’ preferences to match? For example, what is the impact of improved birth control technologies and/or abortion laws on the matching patterns?
incentive to misreport their preferences, and the Deferred Acceptance (DA) algorithm where truth-telling is a weakly dominant strategy. Theoretically, it has been argued that the BM can give unfair advantage to students with sophisticated parents whereas DA is strategy-proof. The Boston School Committee voted in 2005 to replace the BM with a DA mechanism, based on such theoretical discourse.
“Thus, for the estimation of preference parameters, we can only rely on the moment inequalities that are implied by the condition of “stable matching.”
To test this empirically, we need to understand what drives these match allocations. In other words, we need to find a way of estimating agent preferences. We can use these to perform counterfactual analyses that involve computing the welfare gains/losses under different equilibriums in a given market. In fact, He (2014) shows that even under DA algorithm, students with naïve parents enjoy a utility gain only if the true population has a sufficiently small percentage of naïve parents. And, sophisticated parents always lose. This suggests a more mixed verdict that does not always favour the DA mechanism.
What is Next? The empirical literature on matching has made many leaps in recent years, but much remains to be done. The focus has primarily been on one-to-one matching models. These models have so far considered matching on observed and perhaps unobserved characteristics, which are exogenously given. But in reality, it might be the case that the covariates that agents
match on are in fact endogenous. For instance, it might be the case that our marital prospects affect our decision to invest in our human capital. What implications can this have for estimating the preference parameters in such models?
Apart from a few exceptions, we still need to make methodological advances in estimating decentralized one-to-many and many-to-many matching models. That is, there is scope to study these models with the supply side preferences endogenised. In the school choice example, there are markets where the match allocation is not centralized. Here modelling the supply side becomes important, so we can study it as a true two-sided matching problem.
“The focus has primarily been on one-to-one matching models. These models have so far considered matching on observed and perhaps unobserved characteristics, which are exogenously given. But in reality, it might be the case that the covariates that agents match on are in fact endogenous.”
Finally, it should be noted that most of the empirical literature has been performed assuming frictionless matching. One way of interpreting this is to say searching for a match is costless. However, there is a large theory of search models. A fruitful area of research for the future can be to do empirical work in matching models incorporating search frictions.
Source: García Montalvo J. and Raya Vilchez J. “What is the right price of Spanish residential real estate?”.
20% of the value of the house has already been paid. However, the closer an LTV is to 100% the riskier the mortgage is, and the higher the probability of not paying back the debt. If the bank was facing a mortgage with an LTV higher than 80% it was unlikely that the Bank of Spain would accept it. In a recent working paper titled “What is the right price of Spanish residential real estate?” published by two professors from Pompeu Fabra University, Jose María Raya and Jose García Moltavo, the conclusion is that banks actually managed to give mortgages that were not following the policies of the Bank of Spain. Here is what happened: if a worker in a financial institution was in front of a family whose LTV was equal to 100%, they called to the appraisal company and asked it to change the price of the house in order to get a lower LTV. Consequently, the appraisal company raised the price of the house, the bank could then give the mortgage, the buyer could happily enjoy his new home and the Bank of Spain was none the wiser. The two professors got to this conclusion by calculating the LTV with the market prices instead of the appraisal value. They observed that all real LTV were greater than 100%. This shows that banks gave mortgages to insolvent clients and prices were extremely high because of the distortions between appraisal firms and financial institutions. However, as the institutions did not notice, financial firms continued to give mortgages to insolvent clients. This lending practice led to the so-called Spanish bubble, which burst as thousands of families were unable to pay back their debts. Another important estimator that contributed to the increase of the bubble was the poor data for housing prices. The Department of Work used the appraisal prices, which, as mentioned above, were not a good reflection of the real housing prices. First of all, they were not connected with market fluctuations. Another important fact to remember is how financial entities had high incentives to tell the appraisal companies to distort prices. What is even worse was how this housing price index was computed by the administration. The housing price index was calculated by taking the average. There is a popular Spanish saying that “you cannot compare apples with pears.” It is quite obvious that housing prices should be compared according to certain characteristics. Fortunately, in
2008 the Spanish National Institute of Statistics of Spain (INE) elaborated another index that takes into account the critiques exposed above.
The Spanish housing bubble is a clear example of the consequences that bad incentives, interferences on price formation, and poor statistics can have in the economy of a country. We can understand what happened like a series of distorted behaviours. That is, agents were buying houses according to some “beliefs” that were not rational, financial institutions and appraisal companies were manipulating prices in order to get more profits, and the administration was computing a price index that was far from reflecting real house prices. But behind this economic reasoning, there were thousands of Spanish households.
“The Spanish housing bubble is a clear example of the consequences that bad incentives, interferences on price formation, and poor statistics can have in the economy of a country.”
The Spanish housing bubble has devastated families: people committed suicide because of evictions, elderly ladies were forced to leave their homes, and children have suffered from poverty. This is why it is important to know if something has been done in order to give the appropriate incentives to all agents. The Bank of Spain, for instance, no longer computes the LTV with the appraisal value but with the price that is registered in the notary. In this context, appraisal companies would not raise the price of the house in order to help buyers get a lower LTV. If they did, buyers would have to pay more taxes to the Government. However, the construction industry has been growing since 2013 and recent news has shown this sector will keep growing in 2017. Could Spain make the same mistake again? Have all the bad incentives been removed?