timag20-fall2009

tinbergen�institutetinbergentinbergentinbergentinbergentinbergen�institute�institute

magazine

Column:�A�more�plausible�story

by Eric Bartelsman

Development economics and poverty mapping

An�interview�with�Chris�Elbers

Econometrics and marketing

An�interview�with�Dennis�Fok

Fiat Lex: Law, Economics and (Roman) History

Tinbergen Institute Medal

Fall 2009

�Tinbergen�Magazine�is�published�

by�Tinbergen�Institute,�the�Institute�

for�economic�research�of�Erasmus�

Universiteit�Rotterdam,�Universiteit�

van�Amsterdam�and�Vrije�

Universiteit�Amsterdam.

magazinemagazine20

Column

Up close

In depth

NewLetters from Alumni

In short

References3

tinbergen magazine 20, fall 2009

tinbergen institute

magazine

Column: A more plausible story

by Eric Bartelsman


An interview with Chris Elbers


An interview with Dennis Fok



Fall 2009

Tinbergen Magazine is published

by Tinbergen Institute, the Institute

for economic research of Erasmus

Universiteit Rotterdam, Universiteit

van Amsterdam and Vrije

Universiteit Amsterdam.

20

Highlighting ongoing research at Tinbergen Institute for policymakers and scientists.

In this issueColumn

A more plausible story

� Eric Bartelsman

Up close


� An�interview�with�Chris�Elbers

Nick Vikander

� Econometrics and marketing�� An�interview�with�Dennis�Fok Nalan Basturk

In depth


Giuseppe Dari-Mattiacci

New

Introducing the Tinbergen Institute Medal

Letters from Alumni

Ronald Wolthoff , University of Chicago

In short

Papers in journals

Discussion papers

Theses

References

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9

13

17

18

19

21

22

16

TI Magazine’s column highlights a current news topic.

By Eric Bartelsmanl

l Eric Bartelsman is professor

of economics at VU University

Amsterdam. His research

interests focus on the sources

of productivity growth, both

from a micro and macro point

of view. Recently, his work is

on international comparisons

of productivity and resource

reallocation at the firm level.

Will the recovery lead us to the same level of output we would have achieved, had the global financial crisis not occurred? Or, will we converge to the same growth rate of potential GDP, but with a permanent gap? The questions are important for policymakers in countries such as the US, where projected increases in the debt-to-GDP ratio leave the country vulnerable to foreign creditors, or in our own European lowlands, where we are faced with the long-run challenge of an aging population.

The current debate is about how to forecast long-run GDP (growth) following a downturn. In practice, such forecasts are made by Central Banks, government budget offices, or international organizations such as the IMF and the OECD. I agree with the main tenets of a recent working paper by Cai and Den Haan (2009): the official macro forecasts leave much to be desired, and academic economists should provide the methods to improve this state of affairs.

My purpose in this short column is to complement Cai and Den Haan by suggesting a research agenda for improving our ability to forecast long-run growth. The workhorse method of forecasting continues to be extrapolation of time-series data by assuming that they are generated by identifiable stochastic processes. The art of macroeconometrics should be to find the appropriate disaggregation, such that the component time series are indeed the outcome of discernable ‘data-generating processes’.

My first suggestion is for researchers to gain a better understanding of the system of national accounts (SNA). While for current GDP estimates the US Bureau of Economic Analysis places most weight on data from the expenditure side, the bookkeeping system also builds up GDP from the income side and the production side. For tracking the cyclical movements around a Keynesian recession, it does seem sensible to analyse the time paths of final expenditure components that add up to

GDP. For understanding the effects of structural policies on GDP, or for understanding issues related to long-run growth, the expenditure-side disaggregation of GDP may not be the most illuminating.

The income-side components of GDP provide a different view of the underlying economic processes. The rapid rise of labour income in the financial sector in recent years may or may not have raised some eyebrows. But, if national accountants had adjusted their measures— in accordance with the spirit of the SNA— to account for the changes in riskiness on the balance sheets of banks, then measured GDP may well have been one percentage point lower. I expect this loss to be permanent.

For long-run GDP forecasting, the

production-side approach seems more relevant. In a recent working paper with Z. Wolf, we assess the forecasting power of multivariate time-series models of GDP, factor inputs and productivity. In general, the forecast for productivity is extremely poor— even over relatively short horizons. My next suggestion is therefore for macro forecasters to find data that better match theoretical models of productivity and income growth. In my view, relevant components include time series of the productivity frontier, movements of firms towards the frontier, and reallocation of resources between firms with differing productivity. I think that the financial crisis will leave a permanent mark by reducing risky investment needed for growth of the productivity frontier. Further, I fear that the current neglect of structural policy reform may reduce the contribution of reallocation to long-run growth for some time to come. While I presently have no metric with which to judge my wild guess that these impacts of the crisis will reduce long-run growth by 1/2 percentage point, at least I have a more plausible story than claiming that GDP evolves according to a process that can be identified by looking at its own history.

A More Plausible Story

4

References

Bartelsman, E, and Z. Wolf,

(2009), Forecasting aggregate

productivity using

information from firm-level

data, TI discussion paper TI

2009-043/3.

Cai, X., and W. den Haan, 2009,

Predicting recoveries and the

importance of using enough

information, CEPR working

paper 7508.

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Up

cl

se

Development economics and poverty mapping�An�interview�with�Chris�Elbers

�Chris�Elbers�is�Desmond�Tutu�Chair�Holder�of�the�Faculty�of�Economics�and�Business�

Administration�of�the�VU�University�Amsterdam.�The�chair�is�part�of�the�Desmond�Tutu�

program�on�Youth,�Sports�and�Reconciliation,�which�aims�to�strengthen�cooperation�

between�the�VU�University�and�partner�institutions�in�South�Africa.�Elbers�has�been�with�

the�VU�University�Development�Economics�group�since�1994,�where�his�work�has�focused�

on�impact�evaluation�and�poverty�measurement.�TI�Magazine�sat�down�with�him�shortly�

after�his�inaugural�lecture�on�October�14.1��Chris�Elber

1 Inaugural lecture, Op zoek naar

de juste maat, 14 October 2009.

Available in Dutch at

www.fsw.vu.nl/en/Images/

Oratie %20Chris%20Elbers_tcm31-

110868.pdf

By Nick Vikander


You began your inaugural lecture as Desmond Tutu Chair by criticizing what you called typical economic reasoning when giving policy advice: relying only on theoretical ideas, and being uninterested in empirically testing hypotheses. How big of a problem is this?

I think that the problem is widespread. People have called it the Ricardian vice, the idea of ruthlessly applying some kind of equilibrium, rational behaviour concept and arguing to a certain outcome. It basically says that we are always very close to an equilibrium state. For instance, there cannot be any large bills left on the sidewalk because they would have been picked up. Or there can be no serious misalignment of expectations with true distributions, because people would milk the suckers who are wrong.

While I think that the arguments are often elegant and rather appealing— especially to economists who are trained in looking at equilibrium phenomenon— they still have to be tested. In the inaugural lecture I mentioned Jacobs and de Mooij (2009), who argue that the marginal cost of public funds exactly equals one. Their reasoning is that if it were not so, politicians would adjust the tax level to perfectly balance the inefficiency of tax collection with the advantages of income redistribution. While that is an interesting idea,

�Chris�Elbers

6


6


it’s not enough if the issue is really going to be important. In that case, you have to set up a program to test it properly and find out whether it’s true.

Early in your career you also did quite a bit of theoretical work. Were you more interested in theory back then?

Yes, very much. I have always enjoyed digging into theory, and it’s still intellectually pleasing to discover some insight that is not directly presented to you from a textbook or an article. How relevant that is, I don’t know.

Here’s an example: A couple of years ago I was working on a joint paper on environmental policy and trade. We were able to apply an existing model to this case, and by basically changing some names we obtained a particular result. Yes well, what does it mean? At best, it means that this is a point that needs some attention from policymakers or researchers.

Theory can lead to certain conclusions or ideas— but they’re just ideas. Most economic theory turns out in the end to be irrelevant— but this is probably true for theory in most disciplines.

Did you decide to move to the Economic and Social Institute (ESI) of the VU University in 1984 because the position gave you the chance to do more applied work?

The move was partly due to the fact that I had been working for quite a while at the institute where I was at the time, so I felt the need to move on. It was also a nice switch to a more relevant kind of research, where I needed to link my technical skills to real applications. At the time, doing applied general equilibrium analysis was very popular as an alternative to macroeconomic models for policy evaluation. I have never regretted this step; it was really a good thing to do.

Was there a particular reason why you later moved to the VU economics department?

Jan Willem Gunning, who recruited me to the institute, moved to the faculty to become Professor of Development Economics, and he was building the staff around him. The move was attractive for me, because it meant going a little bit more into academia. There had been quite some room at the institute to do research that was funded by the faculty, rather than by some external source. At a given point, much of that work was shifting back to the faculty itself.

You mentioned in your inaugural lecture that your success is linked directly to that of the poverty-mapping project. Could you explain what poverty mapping is?

Basically, the challenge is to come up with more detailed statistics than the data would normally allow. It’s a bit of magic that is possible only if you combine several sources of data.

In development economics, you have something called Living Standards Surveys, which allow for a detailed look at the goings-on in a household— what they consume, very often what they earn, and all kinds of household characteristics. These are small surveys because of cost and logistic limitations, and they give a picture at a rather high level of aggregation. But policymakers would really like to have more detailed information with which to build their policy.

What people started to do is to use census data to paint a detailed picture of local standards of living. Census data does not contain direct information on consumption, but some countries started playing with “rule-of-thumb indicators” of living standards: how big the house is, for example, and how many rooms there are, what kind of material is used and so on. This gave them a wonderfully detailed picture of the population— if you would believe the index they were using. That happened in Ecuador. At that point, awareness began to grow about how completely artificial such an index is.

7


variables. We model these differences as random effects, which we usually apply at the level of the census enumeration area, which is, say, a group of 100-200 households. If you want to predict poverty for a group of 10,000 households, that gives, say, 50 independent random effects— and they cancel out a little bit.

The obvious objection made by Deaton and Tarozzi is that you have only thinly sampled clusters in your survey, and each location effect could just be representative of the effect of a bigger area. Say, for instance, that you didn’t use 50 random effects to build up your district estimate, but five; that would certainly increase the standard error of your prediction.

It is basically an empirical matter. The difficulty is that you don’t often have observations where you can check— although in some rare cases you do. We have a really nice data set from Brazil that can be used to check whether this makes a lot of difference. Fortunately, we were vindicated in that particular case, but that is just one case.

My position is that the only way we can resolve this is by knowing the correlation of location effects of two contiguous enumeration areas. Say we made a double selection of clusters— so that every time we draw an enumeration area, we could also pick a neighbouring one as well. Then we could study the degree of correlation that exists between the location effects of two neighbours, and easily fit that into the whole procedure.

What is the objection to doing so?It’s funding. You would still want to have

a picture of the whole country, so it would amount to doubling the number of clusters, which would basically double the cost of the survey. I’ve been pushing for this— so far, unsuccessfully. But perhaps one of these years I will succeed.

Do you expect a change in the focus of your work as a result of receiving the Desmond Tutu Chair?

One thing is that I’ll be working more in the area of program evaluation. I’m currently involved in a project measuring the impact of budget support in Zambia. The idea of budget support is that donor funds go directly to the recipient government, without many strings attached. There is some monitoring of the budget process, but essentially the funds just go into the government’s general budget. People want to know how effective this is, and Jan Willem Gunning and I have elaborated a proposal for the evaluation of budget support. It’s a bit scary, in the sense that it is certainly not clear yet whether this is a feasible approach that will yield credible results.

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Poverty mapping allows us to do better by combining both types of data. Census data from a typical developing country contain many things we know are intimately correlated with consumption levels, such as housing characteristics and so on. The Living Standards Surveys have information about the correlation between these core variables and consumption for the sampled households. We use the variables in the census as predictors, to come up with predicted consumption for households not covered in the Living Standards survey.

It is a nice invention. When it comes to doing relevant work, I think that this is the most relevant thing I have done and will probably do in my life.

Your work was published in Econometrica (Elbers et al. 2003), and poverty mapping has been widely used by the World Bank. But there has also been criticism. An independent review on World Bank research (Banerjee, Deaton et al. 2006), and also Deaton and Tarozzi (2009), argue that standard errors are in fact larger than those the World Bank presents. How do you view this criticism?

Deaton clearly dislikes poverty mapping, and was extremely critical in this World Bank independent review. This is remarkable, really, because he was consulted very often during the development of the details of the poverty-mapping procedure. But it has to be said that there are others who are very positive about poverty mapping. The statistical community has been very positive, as has Martin Ravallion, who is I think the most influential researcher working at the World Bank.

The serious issue here is that with poverty mapping, you are applying patterns in the data to domains where you have no direct observation. You are basically assuming that the residual in your survey is more or less distributed similarly in the other non-surveyed parts of the countries.

Data from a Living Standards Survey are clustered, meaning you have a group of ten households interviewed in one place, ten interviewed in another, and so on. That helps, because it gives you an idea about the differences that exist between locations— even after you control for many observable

When it comes to doing relevant

work, I think that poverty

mapping is the most relevant

thing I have done and will probably

do in my life.

I also plan to do some more work on risk, growth and the role of insurance with Jan Willem Gunning. That’s an area in which there is a nice interplay between economic theory and empirics.

As for South Africa, I’ll be working with a number of South African PhD students. One has begun already; she is a brilliant student and will be looking at the effi ciency and eff ectiveness of the education system in South Africa. She has been working with Servaas van der Berg, a famous South African economist. So far, she’s mainly been doing regression-based analysis, and I’d like to also get her started using project evaluation techniques.

South Africa is a middle-income country, but with such terrible inequality. Every time you see it in the data, you can hardly believe it. I think that reducing this inequality is intimately connected to reconciliation, and that the education system can play a major role. It is of course also directly relevant for youth.

Have you any plans for the Sports aspect of the Chair?

Well, in a few weeks I’ll be sitting in a forum for the upcoming football World Cup. I guess I’ll have to become an expert very fast.

No plans for sports yet, but there are sports-related questions I could work on. For instance, one big issue is how to get important information to children— say, about gender equality or about HIV prevention. This is not going to work through handing out pamphlets, or sending letters home from school. But if kids have played football for an hour or so, and are a bit tired— and perhaps are happy because they’ve won— well, the coach may then have an opening to talk to these kids in a context where they will listen. Several initiatives are actively trying out this approach, and I would very much like to be involved in the evaluation of that kind of activity.

My work on poverty mapping is also going to continue. I’m now involved in a project applying poverty-mapping techniques to South Africa. The South Africa Living Conditions Survey from 2008-2009 contains new and detailed data, and that should give us the chance to dive in for more empirical work.


8

Reducing the inequality in South Africa is intimately

connected to reconciliation, and the education system

can play a major role.

There should also be an opportunity to work with the South African government, which is now in the process of setting a new poverty line. Martin Ravallion has done a lot of work looking at the theoretical underpinnings of poverty lines, and this could be a chance to apply certain aspects of his approach to the case of South Africa.

Just one last question. Quality Assurance Netherlands Universities (QANU) recently carried out an evaluation of economics research groups in the Netherlands. Do you know how the VU Development group did?

No, well ..

I’ve heard you received a 4.5/5 for quality, which is very good.

Okay, yes… Well, we jokingly refer to ourselves around here as the best development economics group in the Netherlands. Seriously, we are a big group and I think that most economists would consider us to be somewhere near the top in the country. There seems to be renewed interest in development economics these days among students.

Something slightly strange is that many students who are interested in development economics courses at the VU are actually UvA students. We have the advantage of being able to pick out the best students. Our department has lots of room for research assistants, so you grab these students and keep them. Some of them go on to enrol in high-profi le PhD programs— and although we’re happy for them, and proud, it’s also a bit sad to see them go.

Many PhD students have come directly from the TI MPhil program— four in just the past two years. As I also mentioned in my inaugural lecture, our department is a great environment to work in, being surrounded by many bright people.

References

Banerjee, A., A. Deaton, N. Lustig and K. Rogoff

(2006) An Evaluation of World Bank Research,

1998-2005, independent panel evaluation,

http://go.worldbank.org/45WXOK0OQ1.

Deaton, A. and A. Tarozzi (2009), Using census and

survey data to estimate poverty and inequality for

small areas. Review of Economics and Statistics,

forthcoming.

Elbers, C., J. Lanjouw and P. Lanjouw (2003)

Micro-level estimation of poverty and inequality.

Econometrica, 71(1).

Jacobs, B. and R. de Mooij (2009) De marginale

kosten van publieke fondsen zijn gelijk aan één.

ESB, 94(4567), 532-535.


You are an econometrician doing applied work in marketing; can you explain what led you to apply econometric methods to marketing questions? How did your research evolve over time?

What attracted me mainly was the detail that is available in marketing data. The detail can be found in having information on many different households making decisions, or having low-level sales data (that is, at the actual product level). Having such a rich dataset compels you to use more complicated models. Furthermore, the models that you work on have applied value— the analysis you do really answers a particular question. So I can work on several models and techniques without losing sight of possible applications. My research started at the Econometric Institute at Erasmus University.

As part of my Master’s thesis I did an internship at ROBECO. I had a marketing topic for my research there, where we determined the risk profile of people. My colleagues at ROBECO were not really used to using econometric techniques on the information in their client database. This was my first encounter with marketing econometrics. While working on this project, I became interested in “quantitative marketing models”. During this period, my thesis supervisor, Philip Hans Franses, suggested that I become a PhD student. I had to think about it a little bit, because I did not know if academics was something for me. Actually, at the time I thought I was relatively young to go into business— and there was too much I did not know about— and decided to do a PhD. During my PhD I liked the field so much that I

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Up

clo

se

Econometrics and marketingAn�interview�with�Dennis�Fok

Dennis�Fok�is�an�associate�professor�at��Erasmus�University�Rotterdam�since�2008.�He

is�a�member�of�Erasmus�Research�Institute�of�Management�(ERIM)�and�is�a�TI�research�

fellow.�His�research�interests�include�applied�econometrics�in�general,�with�a�particular�

focus�on�combining�new�econometric�methods�with�marketing.�TI�Magazine�interviewed�

him�about�the�relevance�of�marketing�and�econometrics.


�Dennis�Fok

By Nalan Basturk

What are the particular demands of marketing scholars, compared with other scholars in economics and management science? And, in terms of approaching problems, what do you think are the major differences between marketing and other fields?

These differ according to the scientist’s perspective, which can be methodological or more theoretical. I can say something only about the methodological part. In terms of methodology, a marketing scholar needs to be creative in finding the question that is interesting to study and identifying what kind of modelling techniques should be developed to answer the particular question. Apart from that, there is a need to combine different subfields of econometrics. The question of interest can involve many issues at the same time— for example, endogeneity, a panel model, and a dynamic structure that you want to describe. In this sense, a marketing scholar needs to know about all of these different aspects. A second challenge facing a marketing researcher is not to get too focused on the technical matters. You have to be able to also explain things in a relatively less technical manner than you would have to do for a study in an econometrics journal, for instance. So you could say that being able to sell your method is an important skill of a marketing scholar. In the recent years, the marketing field has become more and more quantitative, and the models in marketing have become increasingly complex. This means that there is more interest in technical matters— although the practical side of things is important. If you develop a new technique, you need to explain it well enough to reach the entire audience of the marketing field.

How wide is the field of marketing? Although people traditionally think of supermarkets, many other players— such as insurance companies, funds with ‘good targets’, political campaigns, pension funds with early retirement decisions— use advanced marketing strategies based on individual decision making. Is there a common element in all of these subfields?

The field of marketing is really broad. It is not very easy for me to define marketing, but all of the studies that we carry out deal with the choices that people make. The data we use for this purpose can be aggregated data for a particular region, or it can be household-level data. But in the end it is always some sort of consumer behaviour that we model. This behaviour could be the choice to buy a product, or the choice to vote for a particular party. Hence, the behaviour could be influenced through price or promotion— or through political campaigns. Similar kinds

decided to stay in academia afterwards as well. My PhD thesis contains only econometric marketing models. However, next to the papers that I wrote for my thesis, I also worked on some more general econometric models. Over time, my research has evolved more and more into marketing applications. One of the reasons that I am still in the econometrics department, and not in a marketing department, is that my main focus is still the methodology that can be applied to marketing questions— as well as other types of problems, such as those in macroeconomics.


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of methods and techniques can be applied to both of these problems. In this sense, marketing may not be the correct label for the research I do.

How valuable do you think econometric and statistical models are for marketing managers in the field? Do they use these models (or at least the results from the application of such models), or is such use mainly confined to academia? How strong do you think the link is between marketing scholars and practitioners?

Models are important for managers, but academics are always ahead of the applied work in the field. We see managers using some applied models, but not the most advanced ones. What is often important for managers is to be able to understand the models themselves. So they need to understand how the models work, and some of these models are just too complicated for them. However, this does not mean that managers are not interested in the things we do. In fact, we have many contacts with firms. These contacts give us access to the data of firms, which enables us to apply our methods to interesting questions— and we can then answer the questions of these managers using new methods.

To what extent do you think that marketing and economics influence each other— for instance, with insights from behavioural models and firm/consumer multiproduct decision models?

The link between marketing and economics goes both ways. Economics influences marketing, in the sense that marketing models mainly start with some form of economic model. Economic models have become increasingly realistic, and they oftentimes provide the basis for econometric models. For example, when we observe a market and a new development happens in the market— perhaps a firm changes its policy or a new brand is introduced— you need the economic models to assess the effect of it on what the competitors will do. Marketing, however, also influences economics. Understanding and describing decision-making is, after all, a large part of economics. Marketing is an area in which we

can observe many decisions being made. Such observations allow us to test theories, and to say something about how people arrive at their decisions. I think that marketing is a good field in which to apply economic models— and developments in the marketing field influence economics.

Do you think that marketing research also contributes to modelling innovations such as those in econometrics and statistics, or are marketing scholars more empirically driven— i.e. interested mainly in applying econometric models to study specific research questions?

The questions we study in marketing lead to a demand for models with specific features— models that can, for example, deal with differences between individuals, or that can be used to define groups of similar individuals. Next, we often want to tie such differences to some observable variables. This aspect is rather unique to marketing, since data is usually available for many individuals. We see that the tools to deal with these kinds of problems, such as Hierarchical Bayes models, are growing in popularity. Many developments in this sense actually come from a marketing application— where people are dealing with an empirical question, but at the same time they need to develop some specialized technique for the question at hand.

Do you think that econometric models are able to replace managers for some decision-making tasks, or would you say that it is the manager (with his or her managerial intuition and experience) that, in the end, makes the difference between a good or a bad decision?

It is not going to happen soon. I think we are at the point where we have to convince managers that it is good to get advice based on models. Next, they can use their own knowledge to adjust this advice, if necessary. The main reason for this is that the decisions that the managers make are on a rather high and general level. For instance, decisions about a product introduction are not made on a daily basis. In a firm, such decisions are taken after many meetings, and the decision-making process takes a long time. Only when each decision is not extremely important can you rely on an automated system. One situation in which the replacement you mentioned is possible (and necessary) is the online world. For example, websites like Amazon apply techniques to process the search and clicking behaviour of consumers in order to target special offers through email or to suggest products to buy. This is all automated, and is done using econometric models. But in general, automated systems are not applicable to many managerial decisions.

You could say that being able to

sell your method is an important

skill of a marketing scholar


11

How do you think that the advancements in information technology affect econometricians— particularly those in marketing science? For example, the availability of large databases, as well as advances in computer technologies, especially for the researchers using Bayesian methods— how did all these achievements affect marketing research? How do you see this progress?

One aspect of information technology relates to the development of online applications. I think we will see more websites that are adaptive. The behaviour of the consumer will be recorded, and the suggestions made by the website, or the way in which the site can be viewed, will be updated according to this information. Apart from that, we have larger databases. Nowadays, every company collects data about everything. In some cases they have millions of records. The companies often do not differentiate what part of this data is useful; they simply collect all data available. The challenge for marketing people is to do something useful with this huge dataset. While such databases are often large, they frequently do not contain enough information on each individual. In order to say something about a particular person, we also need to use the information about the other individuals. Bayesian methods are ideally suited to problems like this. A second aspect of information technologies is the increasing computing power needed to apply these methods. Most of the time, the models we make are just small enough to get results in a couple of hours or a couple of days. Every time the computers become faster, we come up with more complicated models that are more detailed and involve more individuals. In that sense, computing power is still a limit on the things we are capable of doing. With more powerful computers we can also make the analysis more general.

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What lines of research in quantitative marketing do you think will be more pronounced in upcoming years? Can you envision relatively more promising research lines in marketing that will attract significant attention? Which of the newly emerging fields particularly interests you?

Many different marketing subfields should become more important in the future. The analysis of online behaviour is one of these. There is also a trend to generalize findings. People used to study one set of products in one area or in one country. The tendency nowadays is to, for example, analyse multiple products over several countries in order to be able to assess the results for a new product, or a different country. The challenge is to make a general model that can explain the differences between the regions, which places higher demands on the techniques that are used. A final thing is the goal of being able to say something about a new situation. This could be a new product in the market or changes in the structure of the market, such as new competitors. In order to explain the results of this change, we need a rather strict connection to economic theories. We need to use the econometric model on this data and extrapolate it for the future event. This cannot be done by regressing sales on prices, as this does not provide advice for something that happens outside the scope of the data.

The tendency nowadays is to analyse multiple

products over several countries in order to be

able to assess the results for a new product,

or in a different country.

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I n d e p t h

Fiat Lex:Law, Economics and (Roman) History

Any novel combination of otherwise independent research lines raises the question whether the new, interdisciplinary approach yields insights that could not otherwise be obtained using existing methodologies.

Law (L), Economics (E) and History (H) have a long history of fruitful interconnection. By performing some combinatorics on L, E and H, one obtains a large set of possible interdisciplinary approaches. To keep the exposition compact, let us use XàY to indicate the study of Y using methods borrowed from X. Legal History (including both HàL and LàH), Economic History (EàH)

and History of Economic Thought (HàE) are three well-established disciplines. More recently, the Economic Analysis of Law (EàL) has applied methods borrowed from economics to unveil the behavioural effects of legal rules; vice versa, Law and Finance (LàE) has looked at (company) law as a way to explain the economic performance of (financial) markets.

All of these areas of research are now an integral part of the curriculum of lawyers, historians or economists, and their role in bringing novel ideas into the social sciences is beyond question. Therefore, it seems desirable to perform some additional combinatorics: that is, to explore further possibilities for interdisciplinary research. This contribution sketches the importance of research combining Law, Economics and History—with specific reference to the Fiat Lex Vidi-project.

The Fiat Lex projectThis project aims to take account of

theories developed in the fields of legal scholarship, history and economics when addressing questions concerning the evolution of law and lawmaking institutions. Research by Douglas North (North 1990) and Avner Greif (González de Lara, Greif and Jha 2008) first aroused interest for the effects and determinants of institutional change. Bringing in methodology and results from legal history enables us to shift the core of the research slightly— from institutions in general to the specific institutions that make law (courts, assemblies, customs) and to the law itself.

Giuseppe Dari-Mattiaccil

l Giuseppe Dari-Mattiacci

is professor of law and

economics at the University

of Amsterdam, co-director

of the Amsterdam Center for

Law and Economics and

research fellow at the

Tinbergen Institute and

the Centre for the Study

of European Contract Law

The goal of the Fiat Lex

project is to understand

why lawmaking institutions

change over time and what

effect these changes have had

on the laws created by them.

L

H

E

14


lawmaking institutions— and then to investigate what impact this in turn has on the legal system. Although such questions have been put on the world’s research agenda by the Legal Origins project (La Porta, López de Silanes and Shleifer 2008), a comprehensive answer is still missing.

The fact that the law evolves in reaction to both external events and internal dynamics (see, for instance, Greif and Laitin 2004, and Roe 1996) is now generally accepted; yet, the exact nature of the dynamics of legal change remains elusive. One question that remains is whether one can compare different lawmaking institutions (say, courts and assemblies). In other words, can we confirm that one lawmaking institution is in some way better than another— and if so, according to which benchmark(s)? Addressing these questions means investigating whether lawmaking institutions have a systematic, predictable effect on the product of the law— and if so, what effect. Looking at a past where different types of lawmaking institutions were simultaneously present might shed some light on these modern conundrums.

Case law vs. legislationMost commonly, the relevant economic

literature considers two modes of lawmaking: case law versus legislation. This approach naturally brings to mind the dichotomy between common law and civil law jurisdictions, but to limit the analysis to this dichotomy would not do justice to the complexity of the reality. Rather, both common law and civil law countries adopt a mix of case law and legislation.

Roman law cannot be classified according to modern criteria as a common law or civil law jurisdiction (this distinction emerged much later); rather, the Roman legal system relied on both case law and legislation.

A teaser of the resultsIn a study on the emergence of the

corporate form (Abatino et al. 2009), we examine the legal framework that made depersonalisation of business in ancient Rome possible, and we compare it with the modern corporate form. Depersonalisation of business (that is, the possibility for an enterprise to operate as a separate entity from its owners and managers) is a crucial step in economic development. The Roman legal system developed an early form of de facto depersonalised business entity— exhibiting all of the distinctive features of modern corporations (continuity, direct agency, limited liability, and entity shielding)— by means of the judicial evolution of specific remedies in favour of

The goal of the Fiat Lex project is to understand why lawmaking institutions change over time and what effect these changes have had on the laws created by them. Roman law is still considered to be an important (at times, the most important) building block of western legal systems—within both the civil law and the common law tradition. Roman law spans a period of over a thousand years, and its study relies on a centuries-long tradition of scholarly attention. It is by far the most studied and best-documented ancient legal system.

By looking at the evolution of Roman lawmaking institutions and tracking their effects on the final product of the law, one can learn much about the present. On the one hand (learning about the past: L,E,HàH), the economic study of Roman law caters to the demand of historians for a clarification of the legal-economic mechanisms operating within the ancient world (Frier and Kehoe 2007), an endeavour that has already proven to be able to produce remarkable results (for instance, Parisi 2001 and Temin 2001). In this sense, legal scholarship and economics are used alongside other modern disciplines, such as physics, chemistry or archaeology, in order to shed light on the past.

On the other hand (learning from the past: L,E,HàL,E), Roman law can be used—with some caution, due to the lack of econometrically tractable data—as a natural experiment about different modes of lawmaking. The existing literature has shown that there is both a demand and a potential for research that draws lessons from the past in order to understand the complex interaction between legal and economic principles (for instance, Hansmann, Kraakman and Squire 2006, Levmore 1986 and Malmendier (forthcoming)). The important next step, which is the aim of this line of research, is to examine the essence of the lawmaking process and to understand what determines the emergence of certain

By looking at the evolution

of Roman lawmaking

institutions and tracking their

effects on the final product

of the law, one can learn much

about the present.

15


Republic. In this case, the focus of the analysis is on the influence that the distribution of political and economic power has on the functioning of a lawmaking institution.

While still a great deal of work has to be done in order to better understand the institutional dynamics governing lawmaking, there is a clear convergence of interests among legal scholars, economists and historians. It is at the intersection of these disciplines that breakthroughs may be expected.

creditors. Paradoxically, these remedies expanded the liability of the pater familias for contracts entered into by his slaves.

In contrast, the modern version of the corporate form emerged as a result of a series of legislative acts in the period between the 17th and 19th centuries. Moreover, the corporate form emerged by limiting the liability of owners and managers. A comparison of ancient (de facto) and modern (de iure) versions of the corporate form sheds some light on the relationship between a lawmaking institution and the legal rules produced. In particular, the analysis indicates that case law was able to produce an expansion of liability (at the core of de facto depersonalisation), but could not bring about a reduction of liability (de iure depersonalisation), which was to be implemented much later through legislation.

Another study on Roman sumptuary laws regulating banquet expenditures (Dari-Mattiacci and Plisecka 2009) grounds the analysis in the observation that luxury is a signal of wealth. We show that the senatorial class, holding political power, enacted or supported sumptuary laws in order to restrict signalling when there were individuals wealthier than they were. The historical pattern of sumptuary legislation between 182 BC and 18 BC follows, and can be accurately explained by, the shifts in the balance of power between the senatorial class and the emerging equestrian class at the end of the

There is a clear convergence

of interests among legal

scholars, economists and

historians. It is at the

intersection of these disciplines

that breakthroughs may be

expected.

References

Abat ino, B., G. Dari-Mattiacci and E. Perotti (2009),

Early elements of the corporate form:

Depersonalization of business in ancient Rome,

working paper.

Dari -Mattiacci, G. and A. Plisecka (2009), Luxury in

ancient Rome: Scope, timing and enforcement of

sumptuary laws, working paper.

Frier, B.W. and D.P. Kehoe (2007), Law and economic

institutions, in W. Scheidel, I. Morris and R. Saller,

eds., The Cambridge Economic History of the Greco-

Roman World, Cambridge: Cambridge University

Press, p. 113-143.

Gonz ález de Lara, Y., A. Greif and S. Jha (2008),

The administrative foundations of self-enforcing

constitutions, American Economic Review, 98,

105-9.

Greif , A. and D.D. Laitin (2004), A theory of

endogenous institutional change, American Political

Science Review, 98, 14-48.

Hansm an, H., R. Kraakman and R. Squire (2006),

Law and the rise of the fi rm, Harvard Law Review,

119, 1333-403.


16

La Po rta, R.F. López de Silanes and A. Shleifer

(2008), The economic consequences of legal

origins, Journal of Economic Literature, 46,

285-332.

Levmor e, S. (1986), Rethinking comparative law:

Variety and uniformity in ancient and modern tort

law, Tulane Law Review, 61, 235-87.

Malmen dier, U. (forthcoming), Law and fi nance at

the origin, Journal of Economic Literature.

North, D.C. (1990), Institutions, Institutional Change

and Economic Performance, Cambridge: Cambridge

University Press.

Parisi , F. (2001), The genesis of liability in ancient

law, American Law and Economics Review, 3, 82-14.

Roe, M .J. (1996), Chaos and evolution in law and

economics, Harvard Law Review, 109, 641-668.

Temin, P. (2001), A market economy in the early

Roman Empire, Journal of Roman Studies,

91, 169-81.

The�Board�of�Tinbergen�Institute�established�in�2008�the�‘Tinbergen�

Institute�Medal’.�The�Chairperson�of�the�Board,�Jeroen�Kremers,�

announced�that�this�medal�would�be�awarded�to�honour�those�

persons�who�are�or�have�been�of�great�service�to�the�Institute.�

The�medal�is�round�in�form,�and�cast�in�bronze.�The�fi�rst�TI�

Medal�was�awarded�to�professor�Maarten�Janssen,�director�of�

the�Institute�from�2004�until�2008,�and�the�second�to�professor�

Jaap�Abbring,�Director�of�Graduate�Studies�from�2004�until�2008.


1616




persons�who�are�or�have�been�of�great�service�to�the�Institute.�

The�medal�is�round�in�form,�and�cast�in�bronze.�The�fi�rst�TI�











Letters�from�Alumnilife after the PhD thesis defense

l Ronald Wolthoff graduated

in 2008 with a thesis entitled

“Essays on Simultaneous

Search Equilibrium”

A lot less remoteRonald Wolthoff l, University of Chicago

When University of Chicago professor Roger Myerson was awarded the Nobel Prize in October 2007, I had just entered my fi nal year as a PhD student at the VU University Amsterdam. Although I was more familiar with his work than with the work of his co-winners, I did not know much about him. Chicago seemed like a remote place.

Around the same time I had to start thinking about my future. My advisor, Pieter Gautier, encouraged me to go to the international job market. I applied to several places and decided to go to the meetings in New Orleans. It was defi nitely a fascinating experience: the desperate attempts around mid-December to fi nd a hotel room (still many thanks to the unknown person who suddenly cancelled his online reservation); the four days in a city invaded by 9000 economists; the interviews with four people around a bed, while the fi fth one tries to convince the cleaning lady that they will really need only two more minutes to kick me out.

In the end, I got a fantastic off er: a two-year postdoc position at the University of Chicago. The Windy City suddenly seemed a lot less remote. I’ve been here for a bit more than a year now, and have enjoyed every second. The academic environment is truly amazing, with seminars at virtually any moment of the day and opportunities to speak with an impressive number of prominent economists. Of course it is typically harder to arrange a meeting with somebody here than it was in Amsterdam, but often the intensity of the discussion is compensation enough for this drawback.

The main lesson that I have learned in Chicago is that the research question and the motivation are crucial. Everybody here can do IV, solve Bellman equations and program complicated models. What distinguishes the best from the rest is the question they answer and the way they sell it in their paper and presentation. Hopefully, I am slowly developing some intuition for that as well.

What’s up next? I’ve come full circle now, and fi nd myself again on the job market. Although many things now are quite diff erent than they were two years ago (this year the meetings are in Atlanta), some things have hardly changed. As before, I seem to be endlessly polishing my paper and presentation— and again I have no idea where I will end up next year. One thing I know for sure, though: if the cleaning lady comes again, she will have to wait at least another 15 minutes this time!


intuition for that as well.

17

18


The structure of dynamic correlations in multivariate stochastic volatility models

Static and dynamic covariance and correlation structures are used routinely for optimal portfolio choice, risk management, obtaining Value-at-Risk (VaR) forecasts, and determining optimal capital charges under the Basel Accord. Although the conditional volatility literature has examined the theoretical development of alternative dynamic covariance and correlation structures, this issue has not been examined in detail in the Multivariate Stochastic Volatility (MSV) literature.For multivariate GARCH models, the most general expression is called the ‘vec’ model, which parameterises the vector of the conditional covariance matrix of the returns vector, as determined by its lags and the vector of outer products of the lagged-returns vector. A serious issue with the vec model is that it has many parameters to be estimated, and will not guarantee positive definiteness of the conditional covariance matrix without further restrictions. The diagonal GARCH model restricts the off-diagonal elements of the parameter matrices to be zero, and also reduces the number of parameters drastically in computing the conditional

covariance matrix. The BEKK specification guarantees positive definiteness of the conditional covariance matrix, which is essential for obtaining sensible VaR forecasts.In the context of modelling conditional correlations rather than conditional covariances, the Constant Conditional Correlation (CCC) model assumes that the time-varying covariances are proportional to the conditional standard deviation derived from univariate GARCH processes. This specification also guarantees positive definiteness of the conditional covariance matrix. As an extension of the CCC model, the Dynamic Conditional Correlation (DCC) model allows the conditional correlation matrix to vary parsimoniously over time.The development of dynamic correlation and covariance models has proceeded at a faster pace in the conditional volatility literature than in its stochastic volatility counterpart. Two reasons for this would seem to be the development of parsimonious multivariate dynamic conditional correlation models and their relative ease in estimation. As a contribution to the development of parsimonious dynamic correlation MSV models that can be estimated with relative ease, the paper proposes two types of stochastic correlation structures for MSV models: namely, the constant correlation (CC) MSV and the dynamic correlation (DC) MSV models. The dynamic stochastic covariance matrices may be obtained easily from the dynamic stochastic correlation matrices. The structures can be used for purposes of determining optimal portfolio and risk management strategies through the use of dynamic correlations, and for calculating Value-at-Risk (VaR) forecasts and optimal capital charges under the Basel

Accord through the use of dynamic covariances. A technique is developed for estimating the DC MSV model using the Markov Chain Monte Carlo (MCMC) procedure. The properties of the estimation method are examined using simulated data, and various multivariate conditional volatility and MSV models are compared via simulation, including an evaluation of alternative VaR estimators. It is found in an empirical example that MSV models that allow for time-varying correlations generally fit the data better.

l l l l l l

Manabu Asai and Michael

McAleer (EUR), 2009.

The structure of dynamic

correlations in multivariate

stochastic volatility models,

Journal of Econometrics,

150(2), 182-192.

l l l l l l

Non-hyperbolic time inconsistency

Stationarity concerns a rationality assumption for intertemporal choice. It means that indifference between a small outcome received soon and a large outcome received later is preserved if both outcomes are equally delayed. Stationarity reflects constant impatience, and is equivalent to time consistency under common assumptions (“stopwatch time,” resetting the zero of time to the moment of decision). Empirical studies have found that stationarity is usually violated (Frederick et al., 2002), with impatience mostly decreasing and not constant. That is, delaying the aforementioned outcomes makes the decision-maker less impatient and more willing to wait for the large (and late) outcome. Thus, the indifference turns into a preference for the late

outcome, and stationarity is violated.The most popular discount functions today, the generalized hyperbolic (Loewenstein and Prelec, 1992) and quasi-hyperbolic (Phelps and Pollak, 1968; Laibson, 1997) discount functions, were introduced so as to accommodate decreasing impatience. A drawback is that they do not have enough flexibility to accommodate increasing or strongly decreasing impatience. These restrictions make it impossible to fit data at the individual level because there will always be significant fractions of subjects with increasing or strongly decreasing impatience (Abdellaoui et al., 2007; Harrison et al., 2002; Barsky et al., 1997). The impossibility to fit data at the individual level is particularly disconcerting in view of recent advances in neuroeconomics, where typically only a few individuals can be analysed.This paper introduces two classes of discount functions that can accommodate any degree of increasing impatience, and also any degree of decreasing impatience. Hence, they cover all degrees covered by hyperbolic discounting and allow additional degrees on top of those, giving increased flexibility at no cost (no more parameters used). The classes are the intertemporal counterparts of the CARA and CRRA utility functions from decision under risk. They generalize classes of discount functions introduced by Prelec (1989) and Ebert and Prelec (2007). Thus, it becomes possible to analyse data at the individual level. In particular, it is possible to analyse which subjects are most prone to time inconsistencies and, hence, to irrationalities in their intertemporal preferences.

papers in�journals

19


ReferencesBarsky, R.B., F.T. Juster, M.S.

Kimball and M.D. Shapiro, 1997.

Preference parameters and

behavioral heterogeneity: An

experimental approach in the

health and retirement study.

Quarterly Journal of Economics.

112, 537–579.

Ebert, J.E.J., and D. Prelec, 2007.

The fragility of time: Time-

insensitivity and valuation of

the near and far future.

Management Science. 53:9,

1423–1438.

Laibson, D.I., 1997. Golden eggs

and hyperbolic discounting.

Quarterly Journal of Economics.

112, 443–477.

Loewenstein, G.F., and D. Prelec,

1992. Anomalies in

intertemporal choice: Evidence

and an interpretation. Quarterly

Journal of Economics. 107,

573–597.

Phelps, E.S., and R.A. Pollak,

1968. On second-best national

saving and game-equilibrium

growth. Review of Economics

Studies. 35, 185–199.

Prelec, D., 1989. Decreasing

impatience. Mimeo.

Prelec, D., 2004. Decreasing

impatience: A criterion for

non-stationary time preference

and ‘hyperbolic’ discounting.

Scandinavian Journal of

Economics. 106, 511–532.

Harrison, G.W., M.I. Lau and M.B.

Williams, 2002. Estimating

individual discount rates in

Denmark: A field experiment.

American Economic Review 92,

1606–1617.

l l l l l l

Bleichrodt, H., K.I.M. Rohde

and P.P. Wakker, 2009,

Non-hyperbolic time

inconsistency, Games and

Economic Behavior, 66(1), 27-38.

l l l l l l

Retirement, pensions, and ageing

Population ageing is wreaking havoc with the public pension schemes of many western countries. For most developed countries, the

pension system includes promises that cannot be kept without significant system reforms.This paper constructs a model that helps to understand the macroeconomic effects of reforms that would restore the sustainability of the pension systems. Although the resulting model is simple enough to obtain analytical results, and hence provides better insight into the forces at play, it is also general enough to incorporate four main features of the data. (1) Until the mid 1990s, people tended to leave the labour force at an ever-younger age. (2) Most people retire at the earliest age at which retirement benefits are available (typically 60-62), or at least before the normal retirement age (usually 65). (3) Most social security programs (still) contain strong incentives for older workers to leave the labour force. (4) In many European countries disability programs and age-related unemployment provisions essentially provide early retirement benefits.The analysis makes use of modelling insights from two branches of the literature. First, the paper employs the generalized Blanchard-Yaari model developed in earlier papers by the authors. In this model, individual agents face an age-dependent probability of death. By allowing the mortality rate to depend on age, the model can be used to investigate the effects of a reduction in adult mortality— one of the main forces behind the ageing problem. A time-varying fertility rate allows us to also focus on the other two forces— the baby boom and baby bust.The second building block of the analysis concerns the labour market participation decision of individual agents. Following much of the literature, this study assumes

that agents either work full time or not at all— and that the retirement decision is irreversible. Workers choose the optimal retirement age, taking as given the time- and age profiles of wages, the fiscal parameters, and the public pension system.From a policy perspective, the main finding is that most existing pension systems induce a kink in the lifetime income function that acts as an early retirement trap. Fiscal changes are not potent enough to get individuals out of the trap. Increasing the early entitlement age appears to be a low-cost policy measure to counteract the adverse effects of longevity and the changing demographic composition.

l l l l l l

Ben J. Heijdra (RuG) and

Ward E. Romp (UvA), 2009,

Journal of Public Economics,

vol. 93, pp. 568-604.

l l l l l l

Inciting protocols – How international environmental agreements trigger knowledge transfers

This paper offers a new perspective on the currently dominant view that international environmental agreements (IEAs) have little impact on local efforts to reduce international environmental spillovers. Even though IEAs in general may not be indicative of the ability to induce emission reductions directly, clear evidence is presented that the Helsinki and Oslo protocols on reducing sulfur (SO2) emissions have played a prominent role on their own. The paper explores the conjecture that innovating firms consider an IEA as a

signal that their product market expands, and therefore are strongly inclined to designate patent protection of technologies employed for reducing SO2 emissions in countries that consider signing the protocol. The timing of (new) inventions and their diffusion are studied in detail by means of a uniquely constructed patent dataset on SO2 abatement technologies filed in 15 signatory and non-signatory countries between 1970-1997. The paper looks specifically at the protection behaviour of firms by means of so-called intended knowledge flows, or transfers through ‘family’ patents (see Lanjouw and Mody, 1996). A distinction is made between ‘mother’ and ‘family’ patents, as well as the panel characteristics of our dataset, to identify differences in patenting behaviour as induced by local and international regulatory interventions in both signatory and non-signatory countries. It turns out that innovating firms indeed exploit the signal provided by the protocols and designate mother and family patent applications before the protocols are actually implemented. Moreover, that these effects are found to be particularly strong in countries that cooperate through the IEAs (i.e. the signatory countries). The results in this paper suggest that firms are aware of the potential private benefits of such international agreements and exploit potential advantages of larger product markets by seeking protection in countries that participate in the protocols.

ReferencesLanjouw, J.O. and A. Mody, 1996.

Innovation and the international

diffusion of environmentally

responsive technology, Research

Policy 25: 549-571.

discussion�papers

l l l l l l

By Thijs Dekker (VU), Herman

R.J. Vollebergh (Netherlands

Assessment Agency), Frans P. de

Vries (Stichting Management

School, Division of Economics,

University of Stirling), Cees A.

Withagen (VU and CentER,

Tilburg University), Inciting

protocols – How international

environmental agreements

trigger knowledge transfers

TI 09-060/3

l l l l l l

Starting an R&D project under uncertainty

The decision to start a Research and Development (R&D) project is one of the most challenging firm decision problems. R&D projects usually take time to complete, their investments are irreversible (and therefore represent sunk costs) and above all, they are highly uncertain. This paper contributes to the theoretical as well as the empirical literature on R&D decisions under uncertainty. From a theoretical point of view, the paper studies a two-stage R&D project with an abandonment option. Two types of uncertainty influence the decision to start R&D. Demand uncertainty is modelled as a lottery between a proportional increase and decrease in demand. Technical uncertainty is modelled as a lottery between a decrease and increase in the cost to continue R&D. Both lotteries become more divergent when the difference between the outcomes of the lottery increases. We relate differences in uncertainty to differences in risk premia. This makes it possible to consider a broader set of demand and supply lotteries than only the subset of lotteries that preserves the mean, as previously studied in the literature. A potential entrant is endowed with a superior

technology and threatens to drive the incumbent out of the market. The incumbent has a time lead over the entrant and can obtain the same superior technology by completing the R&D project before the entrant can enter the market. The presence of the entrant in our model provides the incumbent with additional benefits from investing in the superior technology, a strategic effect known as Arrow’s replacement effect. In order to deduct testable hypotheses, we derive under which lottery probabilities more divergent demand and supply lotteries positively or negatively affect the decision to start R&D. For empirical testing, data are used from the fourth Community Innovation Survey (CIS IV) in Germany for about 4000 firms to explain actual and planned R&D investments. Our main results, strongly confirming our model predictions, are that for firms facing lotteries where the good state is more likely to prevail (i) a 10% increase in the degree of divergence of the demand lottery increases the likelihood of undertaking R&D by 1.4% and (ii) a change from a low- to a high degree of divergence of the supply lottery increases the likelihood of undertaking R&D by 23.3%. For firms facing a demand lottery where the bad state is more likely to prevail, an increase in the degree of divergence of the demand lottery decreases significantly the probability of undertaking R&D.

l l l l l l

By Sabien Dobbelaere (VU),

Roland Iwan Luttens (SHERPPA,

Ghent University, and CORE,

Université Catholique de

Louvain), Bettina Peters

(Centre for European

Economic Research (ZEW)),

Starting an R&D project

under uncertainty

TI 09-044/3

l l l l l l

Why are residents reluctant to consult attending physicians? Suppose you go to a hospital because you’ve been under the weather for a couple of days. A medical resident examines you thoroughly and diagnoses that you suffer from a rare, exotic disease. He proposes a heavy treatment that may lead to problems of infections and depressions. How would you react? As the disease is rare and the treatment is heavy, it is likely that you would want the resident to ask a more senior physician to have a look at you. One good reason to ask for a second opinion is that physicians themselves are reluctant to consult other physicians in case of uncertainty. This typically applies to residents. Most hospitals have protocols describing the circumstances under which residents should call the attending physician. However, there is strong evidence that residents do not always follow protocols.This paper examines a resident’s incentives to consult an attending physician when the resident is uncertain about the diagnosis. The paper distinguishes between two motives that may drive consulting behaviour: the instrumental motive and the image-based motive. The idea behind the instrumental motive is that a resident seeks feedback to better select the proper treatment for his or her patient. The first part of the paper shows that (i) more uncertainty leads to more consulting; (ii) a resident should call the attending physician if the resident’s diagnosis suggests a relatively extreme situation; and (iii) highly able residents seek confirmation from their superiors out of fear of being wrong, whereas less-able residents seek feedback out of

fear of being right. These results explain why many hospitals use protocols to guide the consulting behaviour of residents.Consulting behaviour is also influenced by how residents believe it affects their image: that is, how their superiors see them. Using a model in which residents are concerned with their image, this paper shows that protocols that dictate consulting behaviour do not always work. Fear of negative feedback seems to discourage employees from seeking feedback. On the flip side of the coin, hope for positive feedback is a stimulus for seeking feedback. Moreover, the paper shows that the act of seeking feedback and the content of feedback have separate impacts on employees’ images. Finally, whether it is strength or weakness to seek feedback varies from situation to situation.The second part of the paper shows that residents may shy away from consulting in order to conceal their shortcomings from the eyes of others. Abstaining from asking advice increases the likelihood of poor task performance, and may lead to complaints. The third part of the paper examines whether monitoring through investigation of complaints alleviates the distortion in the consulting decisions of medical residents. Monitoring is shown to weaken the incentives of less-able juniors to distort their consulting decisions. However, monitoring leads to another distortion: It induces residents to give too much weight to their own information.

l l l l l l

By Otto H. Swank (EUR),

Why are residents reluctant to

consult attending physicians?

TI 09-042/1

l l l l l l

:

20


21

Kahneman and Tversky and the making of behavioural economics

Over the past two decades, behavioural economics has emerged as a dominant new research program in the economic discipline. The history of behavioural economics can be traced back to the faculty of psychology of the University of Michigan during the 1950s, where psychologists such as Clyde Coombs and Ward Edwards developed a new scientific approach to human decision behaviour: behavioural decision research. The focus of this new psychological discipline was the empirical question of if (and if so, when) individuals make mistakes in their decision behaviour. For instance, whether an individual taking part in a lottery always chooses the option with the highest expected value. In this approach, the rules of expected utility, Bayesian statistics and logic defined the normative benchmarks by which the experimental behaviour was compared.Contrary to his thesis supervisor Edwards, Amos Tversky became increasingly convinced during the second half of the 1960s that the behavioural decision research approach had a serious problem— because his experimental results showed individuals deviating systematically from the normative benchmarks, instead of deviating from them randomly, as Edwards thought. As the normative benchmarks were understood as being devised by (and hence as applicable to) normal healthy individuals, this implied that either something was wrong with the

experimental methodology, or that something was wrong with the normative benchmarks. Daniel Kahneman, who had a different background in psychology, offered Tversky an ingenious, conceptual solution for his problem in 1969. If the normative benchmarks are not thought of as being made by ordinary, normal healthy adults, but instead are conceived of as universal rules of rational decision-making, then both the normative benchmarks and the experimental results can be maintained by understanding human behaviour as systematically and predictably deviating from the rational choice, as determined by the universal benchmarks. This new approach formed the basis of Kahneman and Tversky’s famous research, including Heuristics and Biases (1974) and Prospect Theory (1979). Starting in the early 1980s, Kahneman and Tversky’s work was introduced first into financial economics, and later into economics generally. In particular, it offered a useful explanation for observed irrational behaviour in financial markets. On the basis of the research of the two psychologists, behavioural economics has produced a fundamental reorientation of economics. This dissertation shows that this reorientation can only be understood on the basis of an appreciation of a specific psychological research program that emerged in the 1950s.

ReferencesKahneman, D. and A. Tversky,

1979. Prospect theory: An

analysis of decision under risk.

Econometrica 47: 313-327.

Tversky, A. and D. Kahneman,

1974. Judgment under

uncertainty: Heuristics and

biases. Science 185: 1124-1131.

l l l l l l

Thesis: ‘Kahneman and Tversky

and the making of behavioural

economics’ by Floris Heukelom.

Published in the Tinbergen

Institute Research Series #455

l l l l l l

Rationalised panics: The consequences of strategic uncertainty during financial crises

Like many international economic crises, the 2008 financial crisis materialized abruptly, after a protracted period of economic optimism. Financial crises often appear to be panic-like “swings in sentiment” on markets, against a backdrop of essentially unchanged macroeconomic indicators, and negligible changes in economic conditions. Even in cases where crises are blamed on deteriorated economic conditions, imbalances are allowed to persist at length until a panic ultimately erupts. In sum, crises are driven by sudden turbulence on markets, not by unstable economic fundamentals. This dissertation argues that “strategic uncertainty”— doubt in the minds of market participants about the intentions and actions of other agents— is key to understanding such sudden turbulence on markets. Strategic uncertainty arises from the interdependent nature of choices made by agents on financial markets, and has a decisive influence on the choices of agents. It may arise abruptly, even while economic fundamentals remain largely unchanged. Using epistemic game theory (in particular, the theory of global games), this dissertation investigates the consequences of this strategic uncertainty. It develops new models that explain many aspects of financial crises.

Consider, for instance, the question of why a country is more crisis-prone if it has more short-term debt. This maturity structure makes investors more dependent on each other, and thus aggravates strategic uncertainty. Therefore, more short-term debt increases the probability of a panic on financial markets.Or consider the question of why markets tend to allow a misaligned currency peg to survive for a length of time, and then suddenly punish— late and harshly. Currency pegs are associated with political prestige, and governments take great pains defending them, typically by raising the costs for speculators. Speculators depend on each other to bring down the peg. Since they may expect a defence, they postpone attacking until the expected devaluation compensates for both the costs and strategic uncertainty they face. The more vigorous the expected defence, the longer they postpone— and the harsher the ultimate collapse. These two examples demonstrate the dissertation’s message that the risk of a financial crisis originates not from shocks to economic fundamentals, but from the different ways in which strategic uncertainty facilitates a change of sentiment. A study of the determinants of strategic uncertainty deserves a prominent place in the analysis of financial risk. Unfortunately, recent experience shows that this message has yet to be internalised by policymakers and the financial sector.

l l l l l l

Thesis: ‘Rationalised panics:

The consequences of strategic

uncertainty during financial

crises’ by Tijmen Daniëls.

Published in the Tinbergen

Institute Research Series #457

l l l l l l

theses


Theses

458 BRAM VAN DIJK (2-7-2009), Essays on Finite

Mixture Models

459 CHRIS VAN KLAVEREN (2-7-2009),

The Intra-household Allocation of Time

460 OLAF JONKEREN (29-10-2009), Adaption to

Climate Change in Inland Waterway Transport

461 SABINE GO (10-12-2009) Marine Insurance

in The Netherlands 1600-1870, A Comparative

Institutional Approach

462 JERZY NIEMCZYK (13-10-2009) Consequences

and Detection of Invalid Exogeneity Conditions

463 IWAN BOS (20-11-2009), Incomplete Cartels

and Antitrust Policy – Incidence and Detection

464 MICHAL KRAWCZYK (28-10-2009), Experiments

in Decision-Making under Risk

465 TSE-CHUN LIN (17-12-2009), Three Essays on

Empirical Finance

Papers in TI-ranked journals by TI fellows

AA-ranked journalsDittmann, I., E.G. Maug, O.G. Spalt, 2009, Sticks or

carrots? Optimal CEO compensation when

managers are loss-averse, Journal of Finance,

forthcoming.

Offerman, T.J.S., J. Sonnemans, G. van de Kuilen,

P.P. Wakker, 2009, A truth serum for non-Bayesians:

Correcting proper scoring rules for risk

attitudes, The Review of Economic Studies, 76(4),

1461-89.

A-ranked journalsArguedas, C., D.P. van Soest, 2009, On reducing the

windfall profits in environmental subsidy

programs, Journal of Environmental Economics and

Management, 58(2), 192-205.

Asai, M., M. McAleer, 2009, The structure of

dynamic correlations in multivariate stochastic

volatility models, Journal of Econometrics, 150(2),

182-192.

Bleichrodt, H., K.I.M. Rohde, P.P. Wakker, 2009,

Non-hyperbolic time inconsistency, Games and

Economic Behavior, 66(1), 27-38.

Bleichrodt, H., U. Schmidt, H. Zank, 2009, Additive

utility in prospect theory, Management Science,

55(5), 863-73.

Borm, P., M.A. Estévez-Fernández, M.G. Fiestras-

Janeiro, 2009, Competitive environments and

protective behavior, Games and Economic Behavior,

67(1), 245-52.

Brandts, J., A. Riedl, F.A.A.M. van Winden, 2009,

Competitive rivalry, social disposition, and

subjective well-being: An experiment, Journal of

Public Economics, 93(11-12), 1158-67.

Crépon, B., M. Ferracci, G. Jolivet, G.J. van den Berg,

2009, Active labor market policy effects in a

dynamic setting, Journal of the European Economic

Association, 7(2/3), 595-605.

Den Haan, W.J., G. Kaltenbrunner, 2009, Anticipated

growth and business cycles in matching models,

Journal of Monetary Economics, 56(3), 309-27.

Doctor, J.N., J. Miyamoto, H. Bleichrodt, 2009, When

are person tradeoffs valid?, Journal of Health

Economics, 28(5), 1018-27.

Dominguez-Martinez, S., O.H. Swank, 2009, A

simple model of self-assessment, The Economic

Journal, 119(539), 1225-41.

Dur, R.A.J., 2009, Gift exchange in the workplace:

Money or attention? Journal of the European

Economic Association, 7(2/3), 550-60.

Facchini, G., Testa, C., 2009, Who is against a

common market? Journal of the European Economic

Association, 7(5), 1068-1100.

Facchini, G., A.M. Mayda, 2009, Does the welfare

state affect individual attitudes toward immigrants?

Evidence across countries, Review of Economics and

Statistics, 91(2), 295-314.

Gillet, J., A.J.H.C. Schram, J.H. Sonnemans, 2009,

The tragedy of the commons revisited: The

importance of group decision-making, Journal of

Public Economics, 93(5-6), 785-97.

Granger, C.W.J.†, S.J. Leybourne, 2009, The research

interests of Paul Newbold, Econometric Theory, 25,

Special Issue 06, 2009, 1460-65.

22


Onderstal, A.M., 2009, Bidding for the unemployed:

An application of mechanism design to welfare-to-

work, European Economic Review, 53(6), 715-22.

Perotti, E.C., A. Schwienbacher, 2009, The political

origin of pension funding, Journal of Financial

Intermediation, 18(3), 384-404.

Schluter, C., K.J. van Garderen, 2009, Edgeworth

expansions and normalizing transforms for

inequality measures, Journal of Econometrics,

150(1), 16-29.

Schram, A.J.H.C., A.M. Onderstal, 2009, Bidding to

give: An experimental comparison of auctions for

charity, International Economic Review, 50(2), 431-57.

Stremersch, S., A. Lemmens, 2009, Sales growth of

new pharmaceuticals across the globe: The role of

regulatory regimes, Marketing Science, 28(4), 690-

708.

Van den Berg, G.J., A.H. Bergemann, M. Caliendo,

2009, The effect of active labor market programs

on not-yet treated unemployed individuals, Journal

of the European Economic Association, 7(2/3), 606-16.

Van Everdingen, Y., D. Fok, S. Stremersch, 2009,

Modeling global spillover of new product takeoff,

Journal of Marketing Research, 46(5), 637-52.

Van Kippersluis, J.L.W., T.G.M. van Ourti, O.

O’Donnell, E.K.A. van Doorslaer, 2009, Health and

income across the life cycle and generations in

Europe, Journal of Health Economics, 28(4), 818-30.

Van Ommeren, J.N., M. Fosgerau, 2009, Workers’

marginal costs of commuting, Journal of Urban

Economics, 65(1), 38-47.

Van Ourti, T.G.M., E.K.A. van Doorslaer, X. Koolman,

2009, The effect of income growth and inequality

on health inequality: Theory and empirical

evidence from the European Panel, Journal of Health

Economics, 28(3), 525-39.

Vis, I.F.A., K.J. Roodbergen, 2009, Scheduling of

container storage and retrieval, Operations

Research, 57(2), 456-67.

Vollebergh, H.R.J., B. Melenberg, E. Dijkgraaf, 2009,

Identifying reduced-form relations with panel data:

The case of pollution and income, Journal of

Environmental Economics and Management, 58(1),

27-42.

B-ranked journalsAlbrecht, J., A.P. van Vuuren, S. Vroman, 2009,

Counterfactual distributions with sample selection

adjustments: Econometric theory and an

application to the Netherlands, Labour Economics,

16(4), 383-396.

Algan, Y., O. Allais, W.J. den Haan, 2010, Solving

the incomplete markets model with aggregate

uncertainty using parameterized cross-sectional

distributions, Journal of Economic Dynamics and

Control, 34(1), 59-68.

Anufriev, M., G. Bottazzi, F. Pancotto, 2009,

Equilibria, stability and asymptotic dominance in a

speculative market with heterogeneous agents,

Journal of Economic Dynamics and Control, 30(9-10),

1787-1835.

Anufriev, M., V. Panchenko, 2009, Asset prices,

traders’ behavior and market design, Journal of

Economic Dynamics and Control, 33(5), 1073-90.

Beetsma, R., M. Giuliodori, F. Klaassen, 2009,

Temporal aggregation and SVAR identification, with

an application to fiscal policy, Economics Letters,

105(3), 253-55.

Benchekroun, H., A. Halsema, C.A.A.M. Withagen,

2009, On nonrenewable resource oligopolies: The

asymmetric case, Journal of Economic Dynamics and

Control, 33(11), 1867-79.

Bettendorf, L., A. van der Horst, R.A. de Mooij,

2009, Corporate tax policy and unemployment in

Europe: An applied general equilibrium analysis,

World Economy, 32(9), 1319-47.

Bleichrodt, H., J.L. Pinto Prades, 2009, New

evidence of preference reversals in health utility

measurement, Health Economics, 18(6), 713-26.

Booij, A.S., B.M.S. van Praag, 2009, A simultaneous

approach to the estimation of risk aversion and the

subjective time discount rate, Journal of Economic

Behavior & Organization, 70(1), 374-88.

Boucherie, R.J., N.M. van Dijk, 2009, Monotonicity

and error bounds for networks of Erlang loss

queues, Queuing Systems, 62(1-2), 159-93.

Boulaksil, Y., P.H.B.F. Franses, 2009, Experts’ stated

behavior, Interfaces, 39(2), 168-71.

Calleja, P., M.A. Estévez-Fernández, P. Borm,

H. Hamers, 2009, Job scheduling, cooperation, and

control, Operations Research Letters, 34(1), 22-28.

De Vries, J.J., P. Nijkamp, P. Rietveld, 2009,

Exponential or power distance-decay for

commuting? An alternative specification,

Environment and Planning A, 41(2), 461-80.

De Zwart, G., T. Markwat, L. Swinkels, D.J.C. van

Dijk, 2009, The economic value of fundamental

and technical information in emerging currency

markets, Journal of International Money and Finance,

28(4), 581-604.

23


24

Herings, P.J.-J., K.I.M. Rohde, 2009, On the

completeness of complete markets, Economic

Theory, 37, 171-201.

Heijdra, B.J. W.E. Romp, 2009, Human capital

formation and macroeconomic performance in an

ageing small open economy, Journal of Economic

Dynamics and Control, 33(3), 725-44.

Hochguertel, S., H. Ohlsson, 2009, Compensatory

inter vivos gifts, Journal of Applied Econometrics,

24(6), 993-1023.

Karamychev, V.A., 2009, Preference for flexibility in

the absence of learning: the risk attitude effect,

Economic Theory, 40(3), 405-26.

Karamychev, V.A., P.A., van Reeven, 2009, Why fuel

surcharges may be anticompetitive, Journal of

Transport Economics and Policy, 43(2), 141-55.

Koetse, M.J., H.L.F. de Groot, R.J.G.M. Florax, 2009,

A meta-analysis of the investment-uncertainty

relationship, Southern Economic Journal, 76(1),

283-306.

Koopman, S.J., M. Ooms, I. Hindrayanto, 2009,

Periodic unobserved cycles in seasonal time series

with an application to US unemployment, Oxford

Bulletin of Economics and Statistics, 71(5), 683-713).

O’Donnell, O., Á.L. Nicolás, E.K.A. van Doorslaer,

Growing richer and taller: Explaining change in the

distribution of child nutritional status, Journal of

Development Economics, 88(1), 45-58.

Poelhekke, S., F. van der Ploeg, 2009, Foreign direct

investment and urban concentrations: Unbundling

spatial lags, Journal of Regional Science, 49(3),

749-75.

Qiao, Z., M. McAleer, W.-K. Wong, 2009, Linear and

nonlinear causality between changes in

consumption and consumer attitudes, Economics

Letters, 102(3), 161.

Roodbergen, K.J., I.F.A. Vis, 2009, A survey of

literature on automated storage and retrieval

systems, European Journal of Operational Research,

194(2), 343-62.

Ross, S.M., H.C. Tijms, S. Wu, 2009, A model for

locking in gains with an application to clinical

trials, Probablity in the Engineering and

Informational Sciences, 23(4), 637-47.

Rouwendal, J., J. Boter, 2009, Assessing the value of

museums with a combined discrete choice/count

data model, Applied Economics, 41(11), 1417-36,

Stremersch, S., W. van Dyck, 2009, Marketing of the

life sciences: A new framework and research

agenda for a nascent field, Journal of Marketing,

73(4) 4-30.

Delfgaauw, J., R.A.J. Dur, 2009, From public

monopsony to competitive market: more efficiency

but higher prices, Oxford Economic Papers, 61(3),

586-602.

Den Haan, W.J., forthcoming, Assessing the

accuracy of the aggregate law of motion in models

with heterogeneous agents, Journal of Economic


Den Haan, W.J., forthcoming, Comparison of

solutions to the incomplete markets model with

aggregate uncertainty, Journal of Economic


Den Haan, W.J., K.L. Judd, M. Juillard, forthcoming,

Computational suite of models with heterogeneous

agents: Incomplete markets and aggregate

uncertainty, Journal of Economic Dynamics and

Control, 34(1), 1-3.

Den Haan, W.J., P. Rendahl, forthcoming, Solving

the incomplete markets model with aggregate

uncertainty using explicit aggregation, Journal of

Economic Dynamics and Control, 34(1), 69-78.

Den Haan, W.J., S.W. Sumner, G.M. Yamashiro, 2009,

Bank loan portfolios and the Canadian monetary

transmission mechanism, Canadian Journal of

Economics, 42(3), 1150-75.

Elbers, C., Gunning, J.W., Pan, L., 2009, Insurance

and rural welfare: what can panel data tell us?

Applied Economics, 41(24), 3093-101.

Ellman, M.J., 2009, Economics in Russia: Studies in

intellectual history, Economic History Review, 62(3),

764-65.

Englmaier, F., P. Guillén, L. Llorente, A.M. Onderstal,

R. Sausgruber, 2009, The chopstick auction: A

study of the exposure problem in multi-unit

auctions, International Journal of Industrial

Organization, 27(2), 286-91.

Estévez-Fernández, M.A., P. Borm, M. Meertens, H.

Reijnierse, 2009, On the core of routing games with

revenues, International Journal of Game Theory,

38(2), 291-304.

Ficco, S., V.A. Karamychev, 2009, Preference for

flexibility in the absence of learning: The risk

attitude effect, Economic Theory, 40(3), 405-26.

Gardini, L., C.H. Hommes, F. Tramontana, R. de

Vilder, 2009, Forward and backward dynamics in

implicitly defined overlapping generations models,

Journal of Economic Behavior & Organization,

(71(2), 110-29.

Gautier, P.A., M. Svarer, C.N. Teulings, 2009, Sin

City? Why is the divorce rate higher in urban

areas?, Scandinavian Journal of Economics, 111(3),

439-56.


Van den Brink, J.R., Y. Funaki, 2009, Axiomatizations

of a class of equal surplus sharing solutions for

TU-Games, Theory and Decision, 67(3), 303-40.

Van den Brink, J.R., R.P. Gilles, 2009, The outflow

ranking method for weighted directed graphs,

European Journal of Operational Research, 192(2),

484-91.

Van der Ploeg, F., 2009, Prudent monetary policy

and prediction of the output gap, Journal of

Macroeconomics, 31(2), 217-30.

Van der Ploeg, F., S. Poelhekke, 2009, Volatility and

the natural resource curse, Oxford Economic

Papers, 61(4), 727-60.

Van Diepen, M., B. Donkers, P.H.B.F. Franses, 2009,

Does irritation induced by charitable direct

mailings reduce donations?, International Journal

of Research in Marketing, 26(3), 180-88.

Verheul, I., M. Carree, A.R. Thurik, 2009, Allocation

and productivity of time in new ventures of female

and male entrepreneurs, Small Business Economics,

33(3), 273-91.

Viaene, J.-M., I. Zilcha, 2009, Human capital

and inequality dynamics: The role of education

technology, Economica, 76(304), 760-78.

(Chapters in) TI-ranked books

Batabyal, A.A., P. Nijkamp, Sustainable development

and regional growth, 282-301, ch. 15 in:

(R. Capello, P. Nijkamp, eds.) Handbook of Regional

Growth and Development, Edward Elgar, 2009.

Bröcker, J., P. Rietveld, Infrastructure and regional

development, 152-81, ch. 9 in: (R. Capello,

P. Nijkamp, eds.) Handbook of Regional Growth and

Development Theories, Edward Elgar, 2009.

Davis, J.B., Individualism, 261-66, ch. 35 in: (J. Pell

and I. van Staveren, eds.) Handbook of Economics

and Ethics, Edward Elgar, 2009.

De Groot, H.L.F., J. Poot, M.J. Smit, Agglomeration

externalities, innovation and regional growth:

theoretical perspectives and meta-analysis, 256-81,

ch. 14 in: (R. Capello, P. Nijkamp, eds.) Handbook of

Regional Growth and Development Theories, Edward

Elgar, 2009.

Fischer, M.M., P. Nijkamp, Entrepreneurship and

regional development, 182-98, ch. 10 in:

(R. Capello, P. Nijkamp, eds.) Handbook of Regional

Growth and Development, Edward Elgar, 2009.

Hartog, J., On returns to education: Wandering

along the hills of ORU land, 3-45, in: (H. Heijke,

J. Muysken, eds.) Education and Training in a

Knowledge-Based Economy, MacMillan, 2009.

Hommes, C.H., F.O.O. Wagener, Complex

evolutionary systems in behavioral finance, 217-

276, ch. 4 in: (T. Hens, K.R. Schenk-Hoppé, eds.),

Handbook of Financial Markets: Dynamics and

Evolution, Elsevier, 2009.

Hommes, C.H., Complexity, evolution and learning

– Empirical and experimental validation of

heterogeneous expectations, 91-104, ch. 7 in: (A.

Reggiani, P. Nijkamp, eds.) Complexity and Spatial

Networks, Springer, 2009.

Jungbacker, B., S.J. Koopman, Parameter estimation

and practical aspect of modeling stochastic

volatility, in: 313-44, (T. Mikosch, J.-P. Kreiß,

R.A. Davis, T.G. Andersen, eds.) Handbook of

Financial Time Series, Springer, 2009.

Masurel, E., P. Nijkamp, The low participation of

urban migrant entrepreneurs: Reasons and

perceptions of weak institutional embeddedness,

247-65, in: (C. Karlsson, A.E. Andersson,

P.C. Cheshire, R.R. Stough, eds.) New Directions in

Regional Economic Development, Springer, 2009.

Patuelli, R. A. Reggiani, P. Nijkamp, F.-J. Bade,

Spatial and commuting networks, A unifying

perspective, 257-71, in: (A. Reggiani, P. Nijkamp,

eds.) Complexity and Spatial Networks, Springer,

2009.

Reggiani, A., S. Signoretti, P. Nijkamp, A. Cento,

Network measures in civil air transport: A case

study of Lufthansa, 257-82, in: (A.K. Naimzada,

S. Stefani, A. Torriero, eds.) Networks, Topology

and Dynamics – Theory and Applications to

Economic and Social Systems, Springer, 2009.

Van Veelen, C.M., Does it pay to be good?

Competing evolutionary explanations of pro-social

behaviour, 182-200, in: (J. Verplaetse, J. Schrijver,

S. Venneste, J. Braeckman, eds.) The Moral Brain -

Essays on the Evolutionary and Neuroscientific

Aspects of Morality, Springer, 2009.

A.P. van Vuuren, The impact of homeownership on

unemployment in The Netherlands, 113-35, in:

(C. van Ewijk, M. van Leuvensteijn, eds.) Home

Ownership and the Labour Market in Europe,

Oxford University Press US, 2009.

25

09-072/1

Andrei Dubovik, Alexei Parakhonyak, EUR,

Selective Competition

09-075/1

Te Bao, CeNDEF, UvA, Yongqin Wang, CCES and

School of Economics, Fudan University,

Incomplete Contract and Divisional Structures

09-077/1

Vladimir A. Karamychev, Peran van Reeven, EUR,

A Monopolist in Public Transport: Undersupply or

Oversupply?

09-081/1

Harold Houba, Evgenia Motchenkova, VU,

Quan Wen, Vanderbilt University, The Effects of

Leniency on Maximal Cartel Pricing

09-085/1

Jeroen Hinloopen, Sander Onderstal, UvA, Going

Once, Going Twice, Reported! Cartel Activity and the

Effectiveness of Leniency Programs in Experimental

Auctions

09-087/1

Alexei Parakhonyak, EUR, On the Relevance of

Irrelevant Information

09-089/1

Maarten Janssen, University of Vienna, and EUR,

Alexei Parakhonyak, EUR, Minimum Price

Guarantees in a Consumer Search Model

09-090/1

Arantza Estévez-Fernández, VU, A Game Theoretical

Approach to Sharing Penalties and Rewards in Projects

09-092/1

Harold Houba, VU, Hans-Peter Weikard, Wageningen

University, and Mansholt Graduate School,

Stone Age Equilibrium

09-095/1

Vjollca Sadiraj, Georgia State University,

Jan Tuinstra, Frans van Winden, UvA, Identification

of Voters with Interest Groups improves the Electoral

Chances of the Challenger

09-097/1

Jona Linde, Joep Sonnemans, UvA, Social

Comparison and Risky Choices

Financial and International Markets

09-036/2

Stefan Arping, UvA, Sonia Falconieri, Brunel

University, Strategic versus Financial Investors: The

Role of Strategic Objectives in Financial Contracting

09-049/2

Saul Lach, The Hebrew University, and CEPR,

José Luis Moraga-González, University of

Groningen, Asymmetric Price Effects of Competition

Discussion papers

Institutions and Decision Processes

09-033/1

Florian Wagener, UvA, Shallow Lake Economics Run

Deep: Nonlinear Aspects of an Economic-Ecological

Interest Conflict

09-038/1

René van den Brink, Gerard van der Laan, VU, Valeri

Vasil’ev, Sobolev Institute of Mathematics, Russia,

The Restricted Core for Totally Positive Games with

Ordered Players

09-040/1

Mikhail Anufriev, UvA, Tiziana Assenza, ITEMQ,

Catholic University of Milan, Cars Hommes,

Domenico Massaro, UvA, Interest Rate Rules and

Macroeconomic Stability under Heterogeneous

Expectations

09-042/1

Otto H. Swank, EUR, Why are Residents Reluctant

to Consult Attending Physicians?

09-052/1

René van den Brink, VU, Agnieszka Rusinowska,

Université Lumière Lyon, Frank Steffen, University

of Liverpool Management School (ULMS), Measuring

Power and Satisfaction in Societies with Opinion

Leaders: Dictator and Opinion Leader Properties

09-062/1

Gerard van der Laan, VU, Dolf Talman, Tilburg

University, Zaifu Yang, Yokohama National

University, Solving Discrete Systems of Nonlinear

Equations

09-064/1

René van den Brink, VU, Ilya Katsev, Russian

Academy of Sciences, Gerard van der Laan, VU,

Axiomatizations of Two Types of Shapley Values for

Games on Union Closed Systems

09-065/1

René van den Brink, VU, Efficiency and Collusion

Neutrality of Solutions for Cooperative TU-Games

09-067/1

Margaretha Buurman, Robert Dur, EUR, Seth Van

den Bossche, TNO Work and Employment, Public

Sector Employees: Risk Averse and Altruistic?

09-068/1

Matthias Dahm, Universitat Rovira i Virgili, Robert

Dur, EUR, CESifo, IZA, Amihai Glazer, University of

California, Irvine, Lobbying of Firms by Voters

09-069/1

Josse Delfgaauw, Robert Dur, Joeri Sol, Willem

Verbeke, EUR, Tournament Incentives in the Field:

Gender Differences in the Workplace


26

09-076/2

Ingolf Dittmann, Ko-Chia Yu, EUR, How Important are

Risk-Taking Incentives in Executive Compensation?

09-093/2

Andreas Schabert, UvA, and TU Dortmund

University, Monetary Policy under a Fiscal Theory

of Sovereign Default

09-094/2

Samuel Reynard, Swiss National Bank, Andreas

Schabert, UvA, Modeling Monetary Policy

Labor, Region and Environment09-032/3

P.D. Koellinger, A.R. Thurik, EUR, Entrepreneurship

and the Business Cycle

09-034/3

Hugo Erken, Piet Donselaar, Ministry of Economic

Affairs, The Hague, Roy Thurik, EUR, EIM Business

and Policy Research, Zoetermeer, Total Factor

Productivity and the Role of Entrepreneurship

09-035/3

Friso de Vor, Henri L.F. de Groot, VU, The Impact

of Industrial Sites on Residential Property Values

09-037/3

Hans van Kippersluis, EUR, Owen O’Donnell,

University of Macedonia, Thessaloniki, Eddy van

Doorslaer, EUR, Long Run Returns to Education:

Does Schooling Lead to an Extended Old Age?

09-053/2

Julia Swart, EUR, Charles van Marrewijk, Utrecht

University, Cross-Border Mergers and Acquisitions:

A Piece of the Natural Resource Curse Puzzle

09-054/2

Chris Elbers, Jan Willem Gunning, Melinda Vigh, VU,

Investment under Risk with Discrete and Continuous

Assets

09-057/2

Stefan Arping, UvA, The Pricing of Bank Debt

Guarantees

09-063/2

Tim Willems, Sweder van Wijnbergen, UvA,

Imperfect Information, Lagged Labor Adjustment

and the Great Moderation

09-066/2

Michael R. Baye, Indiana University, Dan Kovenock,

University of Iowa, Casper G. de Vries, EUR,

Contests with Rank-Order Spillovers

09-073/2

Chris Elbers, Jan Willem Gunning, VU, Evaluation

of Development Policy: Treatment versus Program

Effects

09-074/2

Tim Willems, UvA, Visualizing the Invisible:

Estimating the New Keynesian Output Gap via

a Bayesian Approach


27

09-043/3

Eric J. Bartelsman, Zoltán Wolf, VU, Forecasting

Productivity using Information from Firm-Level Data

09-044/3

Sabien Dobbelaere, VU, Roland Iwan Luttens,

SHERPPA, Ghent University, and CORE, Université

Cath. de Louvain, Bettina Peters, Centre for

European Economic Research (ZEW), Starting

an R&D Project under Uncertainty

09-045/3

Shunli Wang, Henri L.F. de Groot, Peter Nijkamp,

Erik T. Verhoef, Global and Regional Impacts of

the Clean Development Mechanism

09-046/3

Michel van der Wel, EUR, CREATES, ERIM, Albert

Menkveld, VU, Asani Sarkar, Federal Reserve Bank

of New York, Are Market Makers Uninformed and

Passive? Signing Trades in the Absence of Quotes

09-047/3

Simonetta Longhi, Institute for Social and Economic

Research, University of Essex, Peter Nijkamp, VU,

Jacques Poot, Population Studies Centre, University

of Waikato, Hamilton, Regional Economic Impacts of

Immigration: A Review

09-048/3

Aura Reggiani, Sara Signoretti, University of

Bologna, Peter Nijkamp, VU, Alessandro Cento, KLM

Royal Dutch Airlines, Milan, Network Measures in

Civil Air Transport: A Case Study of Lufthansa

09-050/3

Maureen Lankhuizen, Henri L.F. de Groot,

Gert-Jan M. Linders, VU, The Trade-Off between

Foreign Direct Investments and Exports: The Role

of Multiple Dimensions of Distance

09-051/3

Christiaan Behrens, Eric Pels, VU, Intermodal

Competition in the London-Paris Passenger Market:

High-Speed Rail and Air Transport

09-055/3

Robin Douhan, Research Institute of Industrial

Economics (IFN), and Uppsala University,

Mirjam van Praag, UvA, Amsterdam Center for

Entrepreneurship, Max Planck Institute of Economics,

IZA, Entrepreneurship, Wage Employment and

Control in an Occupational Choice Framework

09-056/3

Mirjam van Praag, UvA, Amsterdam Center for

Entrepreneurship, Max Planck Institute of

Economics IZA, Who Values the Status of the

Entrepreneur?


09-058/3

Aliye Ahu Gulumser, VU, Istanbul Technical

University, Peter Nijkamp, VU, Tüzin Baycan-

Levent, Istanbul Technical University, Martijn

Brons, VU, Embeddedness of Entrepreneurs in Rural

Areas: A Comparative Rough Set Data Analysis

09-059/3

Roberta Capello, Andrea Caragliu, Politecnico di

Milano, Peter Nijkamp, VU, Territorial Capital and

Regional Growth: Increasing Returns in Cognitive

Knowledge Use

09-060/3

Thijs Dekker, Institute for Environmental Studies,

VU, Herman R.J. Vollebergh, Netherlands

Assessment Agency, Frans P. de Vries, Stichting

Management School, Division of Economics,

University of Stirling, Cees A. Withagen, VU,

CentER, Inciting Protocols – How International

Environmental Agreements trigger Knowledge

Transfers

09-070/3

Peter van der Zwan, EUR, Ingrid Verheul, EUR and

EIM, Zoetermeer, Roy Thurik, EUR, EIM, Max Planck

Institute of Economics, and VU, Isabel Grilo,

DG Enterprise, European Commission, Brussels,

GREMARS, Université de Lille 3, CORE, Université

de Louvain, Entrepreneurial Progress: Climbing

the Entrepreneurial Ladder in Europe and the US

09-071/3

Peter Berkhout, EIB Amsterdam, Joop Hartog,

Hans van Ophem, UvA, Starting Wages respond to

Employer’s Risk

09-078/3

Mildred E. Warner, Cornell University, Raymond

Gradus, VU, The Consequences of Implementing a

Child Care Voucher: Evidence from Australia, the

Netherlands and USA

09-079/3

Elbert Dijkgraaf, EUR, Maarten C.W. Janssen,

University of Vienna, and EUR, Defining European

Wholesale Electricity Market: An “And/Or” Approach

09-080/3

Andrea Ghermandi, Zuckerberg Institute for Water

Research, Ben-Gurion University of the Negev,

Israel, Jeroen C.J.M. van den Bergh, Universitat

Autonoma de Barcelona, Luke M. Brander, Institute

for Environmental Studies, Henri L.F. de Groot, VU,

Paulo A.L.D. Nunes, Fondazione Eni Enrico Mattei,

The Values of Natural and Constructed Wetlands:

A Meta-Analysis

09-082/3

Thomas Buser, UvA, The Impact of Female Sex

Hormones on Competitiveness

28


09-083/3

Jos van Ommeren, Derk Wentink, Jasper Dekkers,

VU, The Real Price of Parking Policy

09-091/3

Teresa Bago d’Uva, EUR, and Netspar, Maarten

Lindeboom, VU, and Netspar, Owen O’Donnell,

University of Macedonia, University of Lausanne,

and Netspar, Eddy van Doorslaer, EUR, Slipping

Anchor? Testing the Vignettes Approach to

Identification and Correction of Reporting

Heterogeneity

09-100/3

Elbert Dijkgraaf, EUR, Raymond H.J.M. Gradus, VU,

and EUR, Matthijs de Jong, EUR, Competition and

Educational Quality: Evidence from the Netherlands

Econometrics09-039/4

Michael McAleer, EUR, National Chung Hsing

University, Taiwan, Juan-Angel Jimenez-Martin,

Teodosio Pérez-Amaral, Complutense University of

Madrid, Has the Basel II Accord encouraged Risk

Management during the 2008-09 Financial Crisis?

09-041/4

Borus Jungbacker, Siem Jan Koopman, VU,

Michel van der Wel, EUR, ERIM, CREATES, Dynamic

Factor Models with Smooth Loadings for Analyzing

the Term Structure of Interest Rates

09-084/4

Bahar Kaynar, Ad Ridder, VU, The Cross-Entropy

Method with Patching for Rare-Event Simulation of

Large Markov Chains

09-086/4

Maurice J.G. Bun, UvA, Frank Windmeijer,

University of Bristol, The Weak Instrument Problem

of the System GMM Estimator in Dynamic Panel

Data Models

09-088/4

Jörn H. Block, EUR, Technische Universität München,

Lennart Hoogerheide, EUR, Roy Thurik, EUR, EIM

Business and Policy Research, Max Planck Institute

of Economics, Jena, Education and Entrepreneurial

Choice: An Instrumental Variables Analysis

09-096/4

Michel Beine, University of Luxembourg, CESifo,

Charles S. Bos, VU, Serge Coulombe, University of

Ottawa, Does the Canadian Economy suffer from

Dutch Disease?

29

30


Colophon

Tinbergen�Magazine�is�published�by�

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31


Column: A�more�plausible�story

by Eric Bartelsman


An�interview�with�Chris�Elbers


An�interview�with�Dennis�Fok


Letters from Alumni


Publications and References

In this issue

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timag20-fall2009

Documents

professor of economics

gdp growth

research agenda

research interests

vrije universiteit amsterdam

universiteit van amsterdam

sources of productivity

growth rate of potential