Category Archives: Visiting Lecturers

What’s a Good Teacher Worth? A CERGE-EI Public Lecture by Eric Hanushek

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“Economic growth is a function of education, period.”  During his public lecture at CERGE-EI, Professor Eric Hanushek emphasized the enormous impact that human capital (i.e. education) has on long-term economic development.  A renowned scholar in educational research, Professor Hanushek (Stanford University) used this link between education and development to make a compelling argument for improving the quality of instructors.

Prof. Hanushek began his lecture from a distance and gradually brought the audience ‘closer to earth.’ From the furthest vantage point, he established the unambiguous link between economic growth and test scores (i.e. what students know). A graph plotting test scores and economic growth revealed a nearly perfect correlation for a wide sample of countries over the past five decades. To Prof. Hanushek, the data screams loud and clear that imparting knowledge and skills through the educational system is the most potent means by which countries successfully grow.

Growth and test scores

Unfortunately, raising test scores is not so simple. Students may be required to attend school, and governments spend a great deal to make this happen, but merely sitting in a classroom with a teacher is not enough to guarantee meaningful learning. The question, then, is how to ensure that students learn while they sit in those classrooms.

According to Prof. Hanushek, research on student achievement has identified that good teachers play the essential role. In economic terms, how much can a good teacher contribute to economic growth? He showed that a top teacher with a class of 30 students will boost the cumulative lifetime income of that classroom group by over $800,000. Of course the inverse of this relationship also exists: lousy instruction from the worst teachers will damage their students’ earnings by a similar magnitude.

Removing the worst teachers and replacing them with average ones could contribute to large gains in test scores—and as Hanushek already demonstrated, higher test scores should directly contribute to long-term economic growth. Analyzing the Czech Republic and making conservative assumptions about teacher quality, he showed that removing the bottom 5% of teachers and replacing them with average instructors could lift the country’s test scores to the level of Finland. This in turn would add 110 trillion euros to the Czech Republic’s GDP over the next 80 years (in present value worth).

Eric Hanushek Lecture

Considering the enormous impact that good teachers can have on student achievement and economic growth, the focus on improving teacher quality should be paramount. Unfortunately, solutions to improve teacher quality are often misguided and ineffective.

Rather than focus on a teacher’s educational credentials, experience, or training, Prof. Hanushek proposed solutions that work with incentives and focus on outcomes.  He suggested methodically measuring testing outcomes and rewarding teachers for achieving defined objectives. He was also dismissive of those who see technology as a silver bullet. Accountability and performance rewards can be far more effective than giving students iPads.

Check out the full lecture below:

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Nobel Prize Laureate Eric Maskin Visits CERGE-EI

At the end of April 2013, we had the honor to welcome Prof. Eric Maskin (Harvard University) to CERGE-EI in Prague. On April 29, Prof. Maskin gave a public lecture titled “How to Make the Right Decisions without Knowing People’s Preferences: An Introduction to Mechanism Design”.

To begin his lecture, Prof. Maskin contrasted the field of ‘mechanism design’ with other more familiar parts of economic theory. Whereas the bulk of economics takes existing institutions as a given and aims to understand and explain outcomes delivered by those institutions, mechanism design reverses the direction. It starts by identifying outcomes one wishes to achieve and asks whether institutions are able to be designed to achieve the desired outcome(s) and, if so, what these institutions ought to look like. In this sense, mechanism design can be called an “engineering” component of economic theory.

To further illustrate the concept, Professor Maskin offered three concrete applications of mechanism design theory. They were, in the order presented, (1) how can you divide a plot between two people in a way that neither of them envies the share of the other?, (2) how can a government sell a license to allow transmission over a band of radio frequencies to a company which values it most?, and (3) how to choose a public energy source when individual preferences are different and optimal choice depends on the unknown state of the world? Professor Maskin explained how insights from mechanism design theory can provide answers to these intractable questions.

Simple as they are, these examples illustrate key features of mechanism design. First, a designer of the mechanism does not know what the optimal outcomes should be. Secondly, the designer must proceed to indirectly convince participants to reveal necessary information. Finally, participants have their own goals and motivations which may not coincide with those of the designer. Therefore, the mechanism must be ‘incentive compatible’—in other words, it should recognize those goals and reconcile them with those of the designer.

The examples presented during the lecture displayed transparent mechanisms that are implemented to achieve the designer’s goals. For those interested in a general way to understand whether a goal is implementable and, if it is, how to find a mechanism to implement it, Professor Maskin referred to his seminal paper, “Nash Equilibrium and Welfare Optimality.” Professor Maskin concluded with some further examples of possible future applications of mechanism design theory, namely the development of an international treaty on greenhouse gas emissions and the design of policies to prevent financial crises.

While here, Professor Maskin also sat down with CERGE-EI student Maxim Guryunov for a brief interview. Check out the highlights on our CERGE-EI Youtube Channel:

httpv://www.youtube.com/watch?v=zaC4Z2JFWB4&feature=youtu.be

Find the full list of Distinguished Speaker Series at CERGE-EI here

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VIDEO INTERVIEW: Media Economics with Professor Simon Anderson

Media economics, the study of the macro and microeconomic aspects of media companies and industries, is an ever-changing field. With new mediums of consumption, new audiences, and changing forms of entertainment, the research agenda is constantly expanding. Professor Anderson (University of Virginia) researches many aspects of media economics. He recently visited CERGE-EI to present his most recent paper, Media Market Concentration, Advertising Levels, and Ad Prices.

While at CERGE-EI, Professor Anderson sat down for a brief interview with PhD student Liyou G. Borga. Check it out in HD on the CERGE-EI youtube channel:

httpv://youtu.be/6nEi2tDwpvU

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African Development and Social Capital with Professor Marcel Fafchamps

Professor Marcel Fafchamps (Oxford University) researches development economics, with a particular interest in social networks, risk-coping strategies, and market institutions. With advanced degrees in law and economics, Professor Fafchamps is fascinated by the role of institutions (both formal and informal) in the development of productive economic exchange. His recent papers include work on markets, political economy, social networks, and link formation. He also serves as deputy director for the Center for the Study of African Economies.

Professor Fafchamps visited CERGE-EI recently to present a paper titled “Networks and Manufacturing Firms in Africa”. While here, he sat down for an interesting interview with two CERGE-EI PhD students, Liyou G. Borga and Dejan Kovac.

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Before you began doing economic research, you did some development work. Why did you choose to go back and get your PhD?

That’s correct. After completing my military service I went to work for the ILO in Ethiopia. I initially went for a year but ended up staying for four and a half years, and I even met my wife there. I became interested in research at that point, and I noticed that everyone around me who was doing interesting research already had a PhD… so I thought, I better get one of those!

You work on research and you design some policy recommendations for developing countries, but these countries and their government are not always fond of these recommendations and may not put them in to practice. Is it frustrating to do this kind of work?

I find it very rewarding. Even though I started in policy, over time I moved away from pure policy-oriented work and more into behavioral work, because I think that if you can understand some of the main drivers of human behavior, you can try to anticipate how they will respond to various policies, even policies we haven’t tested yet. That’s always been my personal approach.

So I don’t try to come to the government of Ghana and say ‘You should do X’. I never could see myself in that role.  For several reasons: One is that I don’t think I should be advising the government of Ghana. I don’t know enough about Ghana. They should be listening to their own people, they should have their own local capacity. I train people from a whole series of developing countries, and a lot of them go back to their country. So I try to give them the best possible grounding and training. In my view teaching is my most important policy work.

And the second is that politicians are on a different clock than we are. They are subject to pressure; they deal with crises and emergencies all the time. If the prime minister wants me to advise on what to do, they want an answer now. But research takes time—it will take at least two years before you get a meaningful result.  Politicians never have time to wait that long.

And the third thing is that policy research is impossible in the following sense: You can never do research on something that has not happened yet. Hence you cannot give a definitive answer to someone who wants to know the future effect a proposed policy. You can offer a prediction based on your understanding of the processes at work, and hopefully this opinion is an informed one so you can give a better prediction than other people. But at the end of the day it’s only a prediction. The politician should blend this prediction to their own predictions based on their own understanding of the various political dynamics at work, which they understand way better than you ever will. And of course, as a policy advisor I am not really responsible for my actions as an advisor. I can say ‘well you should do X, Y, and Z’— and then what? What if it costs millions, or kills people?  I think they should be the ones who make the decisions, not outsiders who are ultimately not responsible for the consequences of their advice.

You are involved in the Center for the Study of African Economics. Do you see a reason to be an optimist about African development? Are they on the right track?

You know the answer to that question is yes. There will be hiccups along the way, just like in Latin America (and if you want to find a part of the world that is most comparable, in terms of population pressure, types of resources, geographical location, and to some extent history, it’s Latin America). The way I see it, the main historical difference between Latin America and Africa is the pattern of colonization and pattern of settlement. America was colonized very early, from 1500 onward, and ended in the 1820s, roughly. And because the Europeans brought many diseases which the Native Americans were not immune to, there was a very large depopulation on the continent. So you have a lot of Latin American countries where big native populations were largely marginalized, and only now are they politically emerging after 200 years of independence.

That’s very different in Africa where it was the opposite. The settlers didn’t survive very well, and the native Africans were much better at surviving, so colonization started very late and lasted for a very short period of time. And it did not, except in South Africa,  generate a settler population. Whatever settler population was introduced as a result of colonization, a lot of them have left.

So then if you compare Latin America to Africa, you see that these settlers bring with them a lot of talent and human capital. They bring familiarity with business practices, with modes of contracting, and these get transplanted nearly immediately. You don’t have to wait for the local population to learn how to take advantage of innovations like supplier credit, banking, etc.

This explains why it took longer in Africa.  But now it’s happening ! I’m very optimistic. There’s no reason why it shouldn’t continue. It could have happened faster if there were more settlers, but then you would have the same problem we see in Latin America, where the native population gets side-lined. In Africa that is not taking place.

So in a sense, in a bizarre way, I am more optimistic for Africa; it was a bit harder to get started because there was a lot of learning to do about modern business practices and institutions, but once they have learned it, they’ll be in charge.

A lot of your research is based on Social Capital. So what is social capital, and how does it influence economic outcomes?

The way I think of social capital, the way the word is useful, is that it’s a flag behind a research agenda which looks at certain phenomena. There are three components: norms, networks, and outcomes (for example, the provision of public goods).

It’s funny that sometimes researchers will only look at the first and the third. For example, they look at certain types of social norms and how they influence outcomes, but do not focus on the networks, or do not even require network dimensions. Other researchers focus on networks and outcomes, but not on the norms. So in the first case, social capital will be the norms people have internalized, and in the second case social capital will be their networks, for example  how many friends they have, what kind of friends they have. In this sense it is a strange research agenda, because it doesn’t always use this phrase with the same meaning.

I think the provision of local public goods is absolutely essential for communities, and also for business communities. And this is what has particularly interested me. Because you don’t get very effective business communities without them using up-to-date organization forms and contractual forms between themselves. When you think about growth and development, if you try to explain the last two hundred years and the rapid increase in standards of living across much of the world, what you see is the spread of innovation. If you learn something about knowledge in one particular area it can spread and help you innovate in another area. But the innovations people typically focus on are things, like the steam engine or electrical power, or consumer goods like the computer and the telephone. But they forget about institutions and forms of organization. Yet that’s what we economists do. This is the kind of thing we study and where we offer innovations. For example: independent central banks, auction for cellphone airwaves, conditional cash transfers. We offer research on innovations in organizational forms and institutions.

But the thing is: if we discover that a computer is useful, you buy a computer. However, if you discover that trade credit is useful, it’s not so easy to introduce that on your own.  Everyone is going to suck you up, take your credit, and not pay you. It has to be a collective decision. So you get into this issue: how to respect other people’s trade credit practice so it becomes like a local public good within your community. But how do you generate that? That’s pretty interesting. It involves social norms, respect for social norms, it involves networking, coordination. Basically it involves the provision of local public goods.

What do you think of bonding capital becoming a negative influence, for example the Mafia in Southern Italy? Is this type of thing possible to empirically investigate?

I think this point has been made before. I would say it’s worse than that, in the following sense: if you tell me that people with a bigger interpersonal network derive advantages from it (e.g. getting a job, doing more business, easier access to credit, ability to deliver public goods within their group), then by definition you are saying there are other people out there who don’t have these benefits. So I would say that every time that interpersonal social capital is helpful, it is also creating inequality. For that reason, I am very skeptical of interpersonal social capital, and why I prefer generalized trust and generalized norms; I prefer things that are the same for everyone and don’t exclude anyone.

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VIDEO INTERVIEW: Monetary-Fiscal Interaction, the Euro Crisis, and More with Dr. Jan Libich

What is the connection between monetary and fiscal policy? How do the interactions between them explain the global financial crisis and its aftermath? Dr. Jan Libich, senior lecturer at La Trobe University in Melbourne, is deeply interested in questions of monetary and fiscal interaction and how an understanding of them may provide solutions to today’s difficult global economic problems.

Dr. Libich visited CERGE-EI in January to discuss his paper, ‘Monetary Exit Strategy and Fiscal Spillovers’. While here in Prague, Dr. Libich sat down for an interview with CERGE-EI student Dejan Kovac to discuss his economic research and policy suggestions. Topics of discussion included: interactions between government’s fiscal policy, the central bank’s monetary policy, the prospects of the European monetary union, sustainability of public finances, the global financial crisis, the future of inflation targeting, and aging populations.Watch the full video interview (in HD) here!:

httpv://www.youtube.com/watch?v=eCOZQWOTd3o

Dr. Jan Libich is a senior lecturer at La Trobe University in Melbourne and the School of Economics, VŠB-TU Ostrava.

 

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An Interview with Dr. Ferre de Graeve, Researcher at Sweden’s Central Bank

Dr. Ferre de Graeve, a researcher at  Sveriges Riksban (Sweden’s central bank), visited CERGE-EI back in November to discuss fiscal policy in contemporary DSGE models. Check out the hitherto unpublished interview between Dr. de Graeve and CERGE-EI PhD student Liyou G. Borga

Why did you choose to study economics? What motivates you?

At the age of 18, going out of school, I didn’t really know what I wanted to do. I decided to study but I pretty much eliminated subject after subject, and what was left was economics. After about three or four months of studying economics, I knew I wanted to do research in the field. And here I am. No regrets so far.

How do you approach your research interests?

I tend to not take advantage of economies of scale. I switch topics a lot. And that’s essentially because I want to learn more. Certainly there are disadvantages to that. But it’s so easy to get excited by something entirely new. I just pursue ideas that I find interesting.

At any point in time I have a couple ideas that I don’t pursue but I think about. But if let’s say a year later they’re still in my head, chances are I start working on them.

What are you working on now?

Essentially I am presenting at CERGE-EI an old paper of mine in which we were concerned with the term structure of interest rates. Now I am revamping that paper from a different angle. There has been a lot of discussion lately about fiscal policies, for obvious reasons. What we realized is that, although the paper has nothing to do with fiscal policy, essentially it turns out to be quite informative about what people call ‘fiscal inflation’. This is the probability that inflation is going to be driven by fiscal policy in the near future. So we basically estimated the model, and it turns out that the model immediately speaks to this issue. It was only two weeks of research, and all the results are already there. That’s definitely not my usual experience.

How did that happen? Is it just that you got lucky? Why did you decide to go back and look?

In terms of work, we got lucky, because we didn’t have to do much. There are a couple of people these days who warn us about fiscal inflation, and perhaps it’s the sense in their arguments that made us go back and look.

One big area for our students is macro models. This DSGE model comes up often in macro issues. Can you tell us in laymen-terms what this model is and why it is different from traditional models? 

DSGE models are essentially models that describe business cycle fluctuations and are built from what we call “micro foundations”; deep structural parameters that determine economic agents’ behavior.

Let me distinguish DSGE models from reduced form forecasting models on the one hand, and old-style structural models on the other. DSGE models complement both. Regarding the first set of models, the important part is that the DSGE models allow us to understand something that the forecasting models don’t necessarily do. Both models will produce forecasts. But DSGE models build on mechanisms that have an economic interpretation. The big advantage that implies for example for central banks is that they allow storytelling. You can think about policies and how they will work. You can create forecasts conditional on policies and that’s a lot harder to do in traditional reduced-form models.

The old-style structural models had the same objective as DSGE models. However, the way they were constructed was rather ad hoc, often inconsistent with theoretical models. They therefore produced answers to policy questions that were hard to put faith in.

How risky is it for central banks to adopt this model and base their forecasts on it, if we base our micro-foundations on some assumptions that don’t work?

I think the main risk is over-estimating the value of a model. I mean as soon as you have a model that you can use to tell stories, you may have too much attention for that model and you may stop thinking about model uncertainty. Because there are other models out there we are not studying. The current crisis is hopefully teaching us that we should think about other models too. In building a model and using it for policy analysis, there are a lot of steps we take that involve assumptions that won’t do well in the current state. We often fail to generate crises in these models of the type we see in reality. That said, I think there is a lot of value in being able to communicate clearly through a model. I definitely think there is value in DSGE models and how they are constructed, but we shouldn’t think that we’ve solved everything here.

As students, we always want to know advice about how to pursue research.  Do you have any advice?

I ask myself that question everyday, and I don’t know. The most important factor, I think is this: pursue your interest. In research you never know where you’re going to end up. You’ll always find out that things don’t work out. So you better have inherent motivation to get you going, even when you face those stages of research.

If it’s your interest, you’re kind of blessed to have the opportunity. For me, it’s certainly better than a lot of alternatives. The fact that I can think of something I find interesting and follow up on it—the average job doesn’t necessarily give you that.

Following the literature might give you more of a probability of getting publication success, but maybe there is value in thinking completely differently and pursuing it.

What is economics now, in terms of importance and relevance, compared to the past?

Well the field is getting so big now. When I started, I had the impression that everyone was doing macro and everyone was discussing with everyone. Now it seems there are so many fields, and they have all developed so much, so it’s hard to know about everything.

So is that a good thing? 

Perhaps with more fields we are inclined to go deep in every particular field, but then you can easily lose track of the bigger picture. It’s important that at least some people keep a bird’s eye view of all the fields, and question whether we are focusing on the right questions. Of course sometimes reality does it for us, such as with this recent crisis.  Afterwards, a lot of researchers I know thought ‘am I working on the right topic, given that current events are so massively important?’. Of course having many different fields can help people learn from each other and build.

Economics is indeed very diversified now, but there are some important questions unanswered. What research questions should be best pursued today by students?

Although we have models that have evolved to understand crises, we’re not there yet. I’m sure there are a lot of questions that are unanswered relating to all aspects of the financial crisis: both what’s happening in the financial sector, how it related to what’s happening in the real economy, and feedback between the two. There are a lot of things we don’t know in this area.

Mostly our students are from transition and developing countries.  In terms of research, what is the comparative advantage of a student coming from one of these countries?

Well for one thing, they probably have more observations and experiences with crises than Western Europeans have. I see that roots are important in research. But having had a good education will basically allow you to do anything. So then it comes back to interest. I don’t necessarily see a comparative advantage, it’s just that there is some correlation about what you think is important and where you come from. But given a good education, you’re basically going to be able to do whatever you want, because you have a wide understanding of issues and the ability to learn.

Author: Liyousew G. Borga, 2nd Year PhD Student

9 November 2012

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Searching for Answers with Dr. Adam Sanjurjo

Dr. Adam Sanjurjo (University of Alicante) researches search behavior in ‘rich search environments.’ As he writes in a recent paper, “we consider much more than wage when choosing a job, and much more than price when purchasing a home.” How to optimize the way we search and the ultimate decisions we make is still not well understood, but Dr. Sanjurjo is searching for answers. Check out Dr. Sanjurjo’s brief interview during his visit to CERGE-EI in Prague:

Who is someone who influenced your decision to become an economist?

Well maybe I shouldn’t say this, but I think it was more of a compromise. For a lot of people who do economics, it’s a compromise, because they like math and they also like psychology. And that was the case for me. As an undergrad I wasn’t as enthusiastic about my economics classes as my math classes. But economics allows the whole continuum between pure math and pure psychology. I felt that I could have that whole continuum to work with, and I think it was a pretty good strategy.

What are you working on now?

Many things, but my main line of research is search behavior in rich search environments. So for example you want to choose a house, so you’re going to evaluate a bunch of different houses on a bunch of different dimensions.  How do you search that information, what information do you search, and in what order do you search that information? And how does the order that you search in affect the choices you are going to make?

I’d say a lot of my work falls under the veil of heuristics and biases, relating to the original work of Kahneman and Tversky in their 1973 paper. It has a lot to do with how people think about probabilities, and how they have systematic biases in the way they evaluate subjective probability.

Where do you get inspiration to start doing your research?

Well that’s pretty clear. The reason I went to do PhD in economics is because I was kind of obsessed with the idea of modeling first impressions. Somehow that quickly turned into the study of information overload.  I felt like information overload was affecting me in my life and a lot of people around me. It was very salient for me. And actually the rich search stuff I’m doing now stays true to that. I think I’m approaching it in a slightly more responsible way than when I first started. So now I’m trying to find concrete mechanisms that cause people to get confused or overwhelmed in complicated decisions, and even in decisions that aren’t so complicated.  We get confused.

So this research can be applied quite generally?

With the multiple attribute search stuff, I think this is a framework that applies to all decision making. So we’re not aware of the fact that we’re evaluating choices on multiple dimensions, and yet we’re doing it all the time. We’re integrating multiple dimensions in evaluating what decision to make, for every decision we make, and we’re making decisions constantly. I’m making decisions right now; I’m choosing which words to use, which sentences to string together, which topics to talk about

And what are your main concerns?

Sometimes I get the feeling when I present this material that it’s very interesting, but it’s also very eclectic for many economists. I personally don’t think it’s eclectic at all, because I think it applies to all decision making. But it’s eclectic in the sense that not much formal work has been done on it, because they’re very rich search problems and thus hard to study. So people have steered away from them because they’re hard problems to work with. But that doesn’t mean they’re not important problems to study.

How do you think your field will look in ten years?

I don’t think it will look very different. There’s kind of a ‘holy grail’ in my field, which is to be able to analytically solve what’s the best way of searching in these rich search problems. I don’t think that’s going to happen any time soon. However I think the ability to numerically solve for what’s the best way to search in these environments is going to get better. People are going to do impressive things in terms of having these very rich search problems that are similar to the way that people search for information on the internet. So you’re not only going to be able to see how people search, but also ‘how they ought to search’. I think that will be an exciting advancement.

What do you think of CERGE-EI?

From what I’ve seen, it’s a beautiful place, and I’m very excited with the faculty here. There are a lot of people who are interested in search and bounded rationality. I’m looking forward to meeting everyone else.

Interviewer: Tamta Bakhtadze

21 January 2013

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The Rich and the Rest: Dr. Martí Mestieri Discusses Income Disparity

Dr. Martí Mestieri (Toulouse School of Economics) researches the dynamics of new technology adoption in developing countries in order to explore the patterns of convergence and divergence between rich and poor countries. The models he uses show that changes in the pattern of technology diffusion account for at least two thirds of the Great Income Divergence between rich and poor countries since 1800. During his visit to CERGE-EI in December, we sat down with him for a brief chat.

Tell us about the paper you are presenting at CERGE-EI

Before the industrial revolution, the income disparity between countries was not that high. The richest country was maybe twice as rich as the poorest. Now there are much great magnitudes of difference between rich and poor countries. With the industrial revolution, growth has become very uneven. Some countries have experienced sustained growth while others have stagnated. Economists of course have been puzzling with this question for a very long time.

What we do in this project is we try to isolate the channel of technology adoption. Even though there are methods of production that make labor much more productive, it seems that many countries are not adopting the best technologies that are out there. So we collect data for many technologies and many countries and we are trying to understand how much technology adoption (or lack thereof) explains the differences between growth performances in the last 200 years.

This is what they call the ‘Great Divergence’, right?

Exactly. Especially in the 19th century you observed a handful of western countries starting to take off, while others didn’t grow at all. So over 100 years, you develop a huge gap in income per capita.

So how much does this technology adoption channel explain differences?

I wouldn’t say ‘explain’, I would say ‘account’, because we don’t have a fundamental theory for why these differences in technology adoption exist. But we find it accounts for a lot, almost 70%. Indeed the question that lies ahead is what are the drivers of technology adoption. In order to explain this, you have to confront a couple of facts. The first is that adoption lags have been declining over time—poor countries are adopting new technologies relatively faster over time. This means the poor countries are relatively more productive because they are catching up.

But what we find as well is that the rate at which technology diffuses within poor countries is actually slower. So even though they are importing technology faster, they are not diffusing it well within their borders. I think this is a set of interesting facts, and if you want to have a big theory, you need to have a theory that predicts these two things, and this is not entirely obvious.

Can you try to explain some reasons why?

This is the most interesting question, and the one we are after. But just building a consistent methodology to assess differences in technology adoption has been keeping us busy. We have some theories that we are exploring. One idea is that some of the early technologies that were produced in the industrial revolution are important inputs for future technology. We see that emerging economies have been lagging behind because they lack this ‘infrastructure technology.’ We think that the diffusion of new technologies is actually being prevented in these emerging economies because perhaps they don’t have the stock of old technology infrastructure necessary for the new technology. So these lack of old technologies are a bottleneck for the new technologies to diffuse.

Another idea is that income inequality may play a role. This means that new technologies are only adopted by a small and elite fraction of the population, and this fraction is not enough to generate spillover to the wider public. But these are only partial explanations. To get more depth, we have to dig much deeper.

Interviewer: Liyousew G. Borga

7 December 2012

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Talking Politics with Dr. Milan Svolík

CERGE-EI isn’t just for economists. Dr. Milan Svolík, a political scientist at the University of Illinois,  visited CERGE-EI recently to discuss his research on election outcomes. We sat down with him for a chat:

Tell us about what influenced your decision to become a political scientist.

When I applying for PhD programs, I got accepted to both economics and political science programs. At the time, I was so bored of interest rates and unemployment levels, I thought it would be much more interesting to know why people vote, why we fight wars, why we have some countries that are dictatorships and others that are democracies. So I intentionally decided that I wanted to study political science. That decision was primarily based on the idea that most mainstream economic topics are not as exciting as political topics. I didn’t know at the time that you can actually study most of these topics within the field of economics. Now I know it, but I didn’t at the time!

So what are your research interests?

I study what would be called political economics. I study several things.I’m interested in why some countries are dictatorships and others are democracies. I study transitions to and from democracy. I study the politics of new democracies, why some survive, while others are more or less corrupt or more or less functioning. I also study political accountability—why elections sometimes work as a way of keeping politicians in line, and why they sometimes don’t work.

Why does this research interest you?

I think it has to do with the fact that I’m from Eastern Europe. Because all of these things you can see here. Some countries are dictatorships, some are democracies. Some are more authoritarian, some are more democratic. Why is Russia governed by somebody who looks like a  new dictator, and Czech Republic is not? I think those are basic questions that we should be able to answer, and they have been around for quite a long time.

What insights do you think are the most influential in your work?

I am too young to have produced influential and important things yet (laughs). I don’t think I have any great answers, but I think some of the questions I ask are very very important. If you look at the 20th century, you see there are great economic questions: why and when do we have recessions, why do we have enormous growth in some places and not in others. But I think there are also incredibly interesting political questions. Why are some regimes ‘persistent democracies’ while others are changing from democracy to dictatorship. The changes you can observe in the 20th century provoke as many political questions as economic questions. And many of these questions are poorly understand but deeply fundamental. Why is China still a dictatorship, but managed to quadruple its GDP/cap in the last 20 years? We need to understand what will happen in North Africa. Is being a democracy important for economic growth, or is it ultimately irrelevant? There are so many questions.

How do you think your field will develop and change in the next 10 years?

It’s hard to say. Some of the big questions will remain the same. Even in the politics I’m interested in, the questions are as important today as they were 100 years ago, and we still don’t have completely satisfactory answers. One thing that is changing is the methodology. Very few economists and fewer political scientists were doing experiments even 20 years ago. And now field experiments are becoming very popular. In ten years we will see what we learn from the wave of experimental economics that is being produced right now. I am very interested to see how people digest evidence coming from these experiments.

What do you think of CERGE-EI?

I think it’s an incredible institution. It has an incredible collection of young economists, and these are some of the most talented people from the region. I hope CERGE-EI will be able to keep them here. It’s very hard to find such a number of high quality people in one place.

What advice do you have for new PhD students? 

I would give two types of advice. When I speak to political scientist grad students, I give them the absolute opposite advice as economics students. When I speak to them, I tell them to learn as much technical methodology as they can—to study econometrics, game theory, and formal theory. Because they don’t get enough of it. But for economics students, there is so much technical stuff already forced on you. So for economic students, I would advise them not to forget to always ask, ‘Why? What is the basic economic question here. What is the big question I want to understand?’

The second piece of advice is to be very cautious about ‘fashionable topics’ or ‘fashionable methodology’, because those change very quickly. If something is fashionable in year 1, it may not be fashionable five years later when the student is graduating. I think it’s important to follow gut-feelings about what is important, rather than any particular fashion.

Interviewer: Tamta Bakhtadze

3 December, 2012

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A Brief Chat with Professor Andreas Ortmann

CERGE-EI discussed lab rats and experimental economics, among other things, with visiting senior lecturer Andreas Ortmann:

You are interested in experimental and behavioral economics. Why did you choose this field and who influenced your decision?

It’s a funny story. To earn my Ph.D., I went to Texas A&M University where one of the first and prominent experimentalists in the US was working. But I didn’t go there to study experimental economics, I went to study industrial organization and public finance. In fact, I never heard about experimental  economics. But …  I needed to earn money and so I started working for this professor called Ray Battalio – a brilliant guy and real mensch – who conducted experiments with animals (I was a rat-lab technician!) and humans. Even though I was very skeptical at first, experimental economics grew on me and I became interested in it as one way of understand economic problems.

But it’s only one way.  It’s not the only way. I also do theory, I do history of thought, and even empirical work if I have to.  I don’t believe in one method alone. You take what’s appropriate to understand and solve the problem .

Today a lot of people are doing these types of experiments. How do you see the field changing in the future?

There are lots of issues that experimental economists need to address. For example, there is always the question of external validity of experiments, i.e., the question to what extent laboratory results tell us anything about the real world.

There are also all kinds of issues of how to do the econometrics, and how to evaluate the evidence that is being produced in experiments. Experimental economists mostly talk about statistical significance, but this is really not that interesting if the effect size turns out to be miniscule. You want to talk about economic significance, which is a different concept. We may actually have the wrong tools for understanding these experiments, at least for some of the big issues which we need to address.

What are your current research interests?

Which of my 273 would you like me to talk about? (laughs) Well I’m working on, among other things, evidence production and evaluation. I’m working obviously on what I talked about in my seminar at CERGE-EI: social-impact bonds, which is a recent addition to  my  research agenda .  I’m also working on simple heuristics. Fast and frugal ways of making decisions which contradict some of the basic ideas that economists have on how we make decisions. We usually assume common and full knowledge and rationality when actors make decisions, and I think the evidence shows that under time-constraints and uncertainty we don’t have a lot of time to make decisions and we don’t have full information. We make decisions on incomplete information, and this is one of the big issues I am focusing on.

How do you get inspiration from your research?

It’s a difficult question because I think there is no algorithm for it. You just have to run through the world with open eyes. And sometimes you have to dive very deeply into a particular topic to understand what kind of open questions there are. Sometimes it just hits you—you say ‘why?’ and then you just go for it.

I think it is fair to say that it has to do, for the most part, with knowing a field well and reading thoroughly. Of course it helps if you read broadly and don’t just focus on one particular topic. And it always is useful to talk and work with different people with different experiences. There are various strategies to get inspirations and they can all be equally valuable.

Do you usually find unexpected results from your studies?

At my age, little surprises me (laughs). But of course, that’s why we do experiments. You do it because you have a theory and you do an experiment to understand if your theory predicts properly. And sometimes the evidence seems to reject the theory that you tested.

Much of laboratory research is being done precisely because theories didn’t predict properly, and then you try to understand what’s going on. You essentially give theorists more grist for the mill to come up with better theories to explain lab results. Of course there are often situations where a theory doesn’t predict well, and it’s a big surprise. Then you have to go on and try to do better. Write better theories, do new experiments. This is the cycle: theory, experiments, theory, evidence, theory, more evidence, more theory, and so on.

You have written many papers, so you may be the right person to ask the burning question of all young PhD students: where do you see the research gap?

You are asking for the low-hanging fruit, yes? (laughs). It’s an interesting question. It’s a little like the famous efficient market argument: there can’t be money on the street, because if there were, someone would already have picked it up. But that’s not true, because there is always new money being dropped, essentially.  There are always new research opportunities. The world is changing and there are always new ideas being generated. In order to understand what’s a new idea, typically it takes some experience and some feeling for what constitutes a good story.

But there are many situations where you come up with something new to the field because you are not caught in this paradigm. So you might see that something is interesting where mainstream economists would never see it. There are so many examples of this.

What is the competitive advantage of CERGE-EI students in choosing a research topic? Since most of the student body is from post-socialist regions, is this the area where they should focus their research?

There shouldn’t be a ‘should’ here. In the first place you must try to become a good economist. After that, if you want to go back to your country, I’m sure you will have plenty of questions and problems to deal with. Just become the best economist you can be, and there will be plenty of opportunities to apply your knowledge.

I can say that good economists are badly needed in the region. Many of the policy decisions are not informed properly by good economics, and that’s a real problem.

How do you perceive the evolution of CERGE-EI?

I think it’s a major success story. It has shown in the region that economics today is very different than the economics practiced here in the past. The way we do and apply economics, and in terms of our ambition, we set a very good example at CERGE-EI. If you look at the rankings of institutions in the Czech Republic, you find CERGE-EI always in the top. I think CERGE-EI has done a lot of good, in the Czech Republic and beyond. You need only look at the career paths of the graduates to see just how successful CERGE-EI has been.

Andreas Ortmann is a professor of experimental and behavioural economics at the Australian Business School at UNSW, Sydney, Australia. He was a professor and senior researcher at CERGE-EI until summer 2009, and he remains affiliated with the Economics Institute of the Academy of Sciences as a visiting senior researcher.

Interviewer: Sophio Khozrevanidz

9 November 2012

 

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