Foto: Maurice van den Bosch
Email: T.J.Klein at uvt.nl
phone: +31 13 466-8233
fax: +31 13 466-3280
Department of Econometrics and OR
PO Box 90153
5000 LE Tilburg
Tobias Klein studied economics at the University of Mannheim, the University of California at Berkeley, and University College London. He joined Tilburg University's faculty in 2007 after obtaining a Ph.D. from the University of Mannheim.
He is deputy managing editor of the Econometrics Journal, associate editor of Empirical Economics and the Review of Economics, and was editor of a special issue of Information Economics and Policy on current regulatory issues in media and entertainment markets.
His research is in health economics, empirical industrial organization, and econometrics. Among other things he currently works on the design of health insurance, the effects of patient cost sharing, consumer behavior, the effects of advertising, competition between online platforms, two-sided markets, and rating systems in online markets.
Tobias Klein's research interests are more broadly related to the idea that recent developments in information and communication technologies together with the availability of big data can help us to address research questions in a novel way if we combine data with tractable models of individual behavior. Insights gained in this way then gives rise to the opportunity to implement welfare-improving policies that are at the same time in the interest of the firms offering a service. This can even lead to the creation of new markets. Examples are the online rating mechanisms used by eBay, Airbnb, Tripadvisor, Yelp, Uber and others, which discipline market participants via online ratings that lead to more transparency. Another example is well-targeted advertising that reminds consumers of making a purchase if they intended to do so.
A recurrent theme in his research is that seemingly small details may have economically important effects. In a recent paper he and his co-authors quantify the effect of framing patient cost sharing incentives in a different way. They find that this can affect yearly health care spending by as much as 8.6 percent.
He is co-organizer of the structural econometrics group and teaches econometrics and structural empirical organization at Tilburg University.
Bernal, Noelia, M.A. Carpio, and T.J. Klein (2017): "The effects of access to health insurance for informally employed individuals in Peru," Journal of Public Economics, 154, pp. 122-136.
French, E. with many others including T.J. Klein (2017): "End-Of-Life Medical Spending In Last Twelve Months Of Life Is Lower Than Previously Reported," Health Affairs, 36(7), pp. 1211-1217.
Klein, T.J., C. Lambertz and K.O. Stahl (2016): “Market Transparency, Adverse Selection, and Moral Hazard,” Journal of Political Economy, 124(6), pp. 1677-1713.
Karlsson, M., T.J. Klein, and N. Ziebarth (2016): “Skewed, Persistent and High before Death: Medical Spending in Germany,” Fiscal Studies, 37(3-4), pp. 527-559. This article is part of a special issue of Fiscal Studies with the title "Medical Spending around the Developed World". See French and Kelly (2016) for an overview.
van Dalen, R. and Klein, T. J. (2014): “Mededingingsbeleid voor internetmarkten met netwerkeffecten," Economisch Statistische Berichten, p. 44-49.
Klein, T.J. (2013): “College Education and Wages in the U.K.: Estimating Conditional Average Structural Functions in Nonadditive Models with Binary Endogenous Variables,” Empirical Economics, 44(1), 135-161.
van der Heijden, E., T.J. Klein, W. Müller, and Jan Potters (2012): “Framing Effects and Impatience: Evidence from a Large Scale Experiment,” Journal of Economic Behavior and Organization, 84(2), pp. 701-711.
Bonsang, E. and T.J. Klein (2012): “Retirement and Subjective Well-Being,” Journal of Economic Behavior and Organization, 83(3), pp. 311-329.
Filistrucchi, L., T.J. Klein, and T.O. Michielsen (2012): Assessing Unilateral Merger Effects in a Two-Sided Market: An Application to the Dutch Daily Newspaper Market, Journal of Competition Law and Economics, 8(1), pp. 1-33. A shorter and less technical version with a slightly different focus appeared as: Filistrucchi, L., T.J. Klein, and T.O. Michielsen (2012): Assessing Unilateral Merger Effects in the Daily Newspaper Market, in: J. Harrington and Y. Katsoulakos (eds.): Advances in the Analysis of Competition Policy and Regulation, Edward Elgar Publishing.
Amann, R. and T.J. Klein (2012): Returns to Type or Tenure?, Journal of the Royal Statistical Society, Series A, 175(1), pp. 153-166.
Filistrucchi, L., D. Geradin, E. van Damme, S. Keunen, T.J. Klein, T. Michielsen, and J. Wileur (2010): “Mergers in Two-Sided Markets—A Report to the NMa,” Nederlandse Mededingingsautoriteit, The Hague, Netherlands.
Hullegie, P. and . Klein (2010): The Effect of Private Health Insurance on Medical Care Utilization and Self-Assessed Health in Germany, Health Economics, 19(9), pp. 1048-1062. A shorter version with additional results appeared as: Hullegie, P. and T.J. Klein (2011): “The effect of private health insurance on doctor visits, hospital nights and self-assessed health: Evidence from the German Socio-Economic Panel,” Schmollers Jahrbuch, 131(2), pp. 395-407.
Klein, T.J. (2010): Heterogeneous Treatment Effects: Instrumental Variables without Monotonicity?, Journal of Econometrics, 155(2), pp. 99-116.
Klein, T.J., C. Lambertz, G. Spagnolo, and K.O. Stahl (2009): The Actual Structure of eBays Feedback Mechanism and Early Evidence on the Effect of Recent Changes, International Journal of Electronic Business, 7(3), pp. 301-320.
SELECTED WORKING PAPERS
The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Discontinuities Design
This figure shows how the change in care consumption around the change of the year depends on dynamic incentives at the beginning of the year.
We develop a new approach to quantify how patients respond to dynamic incentives in health insurance contracts with a deductible. Our approach exploits two sources of variation in a differences-in-regression-discontinuities design: deductible contracts reset at the beginning of the year, and cost-sharing limits change over the years. Using rich claims-level data from a large Dutch health insurer we find that individuals are forward-looking. Changing dynamic incentives by increasing the deductible by 100 euros leads to a reduction in healthcare spending of around 3% on the first days of the year and 6% at the annual level. The response to dynamic incentives is an important part of the overall effect of cost-sharing schemes on healthcare expenditures—much more so than what the previous literature has suggested.
Does the framing of patient cost-sharing incentives matter? The effects of deductibles vs. no-claim refunds
This figure shows, for each risk score decile, the simulated effect of framing cost-sharing incentives as a deductible instead of a no-claim refund (dots). Numbers next to the dots are the percentage changes. Absolute values are given on the right axis. The solid line is the effect on out-of-pocket payments. The simulation is done for 2015.
Understanding how health care utilization responds to cost-sharing incentives is of central importance for providing high quality care and limiting the growth of costs. While there is compelling evidence that patients react to financial incentives, it is less well understood how and why specific aspects of the design of contracts shape the size of this reaction. In this paper, we focus on the question whether the framing of cost-sharing incentives has an effect on health care utilization. To study this we make use of a policy change that occurred in the Netherlands. Until 2007, patients received a no-claim refund if they consumed little or no health care; from 2008 onward there was a deductible instead. This means that very similar economic incentives were first framed in terms of smaller gains and later as losses. We use claims-level data for a broad sample from the Dutch population to estimate whether the reaction to economic incentives was affected by this. Our empirical approach exploits within-year variation using an instrumental variables approach while controlling for differences across years. Our central finding is that patients react to incentives much more strongly when they are framed in terms of losses. Simulations based on our estimates show that the effect on yearly spending is 8.6 percent. This suggests that discussions on the optimal design of cost-sharing incentives should not only involve coinsurance rates and cost-sharing limits, but also how these are presented to patients.
Consumer Time Budgets and Grocery Shopping Behavior
This figure shows that households with at least one retired individual spend more on grocery goods.
Using a novel household panel data set that combines purchase records with information on labor market status and other demographics, this paper reports that the availability of more discretionary time, due to, e.g., retirement, leads to additional shopping trips across a more diverse set of stores, increased spending on groceries, more diversity in products chosen, and less visits to restaurants. This confirms earlier findings in the literature, which mainly used cross-sectional variation and related shopping behaviors to the age of the household head. Our main results revolve around the question whether the availability of time also changes the types of products households buy. To answer this question we develop an approach to classify products according to the time it takes to turn them into consumption experiences and an empirical approach that builds on this classification. We find that the availability of additional time shifts a household’s shopping bundle towards more time intensive market goods. This novel finding implies that product- and retail-innovations aimed at forward-integrating into household production are important drivers of demand in CPG industries.
Advertising as a reminder: Evidence from the Dutch State Lottery
Our minute-level data allow us to nonparametrically estimate the effect of an advertisement on online sales. Here we see that the effect of advertisements reaching many people lasts for about 30 minutes.
Consumers who intend to buy a product may forget to do so. Therefore, they may value being reminded by an advertisement. This phenomenon could be important in many markets, but is usually difficult to document. We study it in the context of buying a product that has existed for almost 300 years: a ticket for the Dutch State Lottery. This context is particularly suitable for our analysis, because the product is simple, it is very well-known, and there are multiple fixed and known purchase cycles per year. Moreover, TV and radio advertisements are designed to explicitly remind consumers to buy a lottery ticket before the draw. This can conveniently be done online. We use high frequency advertising and online sales data to measure the effects of TV and radio advertising. We show that advertising effects are short-lived and the bigger the less time there is until the draw. This is consistent with the predictions of a simple model in which consumers suffer from limited attention and advertising affects the probability that consumers think about buying a lottery ticket and otherwise value buying it as late as possible. We provide direct evidence that advertising does not only affect the timing of purchases, but also leads to market expansion. Finally, we estimate a dynamic structural model of consumer behavior and simulate the effects of a number of counterfactual dynamic advertising strategies. We find that total sales would be 35 percent lower without advertising and that shifting advertising to the week of the draw would lead to a 16 percent increase in sales. This means that consumers react strongly to reminder advertising and wish to be reminded late, when their intention to buy is higher.
Price Competition in Two-Sided Markets with Heterogeneous Consumers and Network Effects
NET Institute Working Paper #13-20
We model a two-sided market with heterogeneous customers and two heterogeneous network effects. In our model, customers on each market side care differently about both the number and the type of customers on the other side. Examples of two-sided markets are online platforms or daily newspapers. In the latter case, for instance, readership demand depends on the amount and the type of advertisements. Also, advertising demand depends on the number of readers and the distribution of readers across demographic groups. There are feedback loops because advertising demand depends on the numbers of readers, which again depends on the amount of advertising, and so on. Due to the difficulty in dealing with such feedback loops when publishers set prices on both sides of the market, most of the literature has avoided models with Bertrand competition on both sides or has resorted to simplifying assumptions such as linear demands or the presence of only one network effect. We address this issue by first presenting intuitive sufficient conditions for demand on each side to be unique given prices on both sides. We then derive sufficient conditions for the existence and uniqueness of an equilibrium in prices. For merger analysis, or any other policy simulation in the context of competition policy, it is important that equilibria exist and are unique. Otherwise, one cannot predict prices or welfare effects after a merger or a policy change. The conditions are related to the own- and cross-price effects, as well as the strength of the own and cross network effects. We show that most functional forms used in empirical work, such as logit type demand functions, tend to satisfy these conditions for realistic values of the respective parameters. Finally, using data on the Dutch daily newspaper industry, we estimate a flexible model of demand which satisfies the above conditions and evaluate the effects of a hypothetical merger and study the effects of a shrinking market for offline newspapers.
Skewed, Persistent and High before Death: Medical Spending in Germany
The horizontal axis in this picture is the time until death. We see that medical spending sharply increases in the two years before death.
We use claims panel data from a big German private health insurer to provide detailed individual-level evidence on medical spending between 2005 and 2011. This includes evi- dence on the distribution of medical spending, the dependence of medical spending on age and other demographic characteristics, its persistence, and how medical spending evolves in the years before death. Our main findings are that health care spending more than dou- bles between ages 50 and 80 and that spending is very concentrated: the top 10% of all spenders are responsible for 53% of all medical spending in a given year. There is a fifty percent probability that individual expenditures lie in the same quintile of the distribution after five years, both for very high and very low cost individuals. Medical spending in the year before death is six times higher for the deceased, as compared to spending of every- body else, and accounts for 5.6% of lifetime spending. Females use more outpatient care and have higher spending in younger ages, whereas males have higher spending in older ages, particularly for inpatient care, and die younger. The presentation of these empirical facts is framed by an institutional discussion of the German health care system, a compari- son between publicly and privately insured, and a discussion of medical spending trends in aggregate-level data.
The effects of access to health insurance for informally employed individuals in Peru
This figure shows a measure of health care utilization against an eligibility index. Individuals are eligible for free health insurance if the index is negative. This suggests that the effect of free health insurance on utilization is positive.
In many countries large parts of the population do not have access to health insurance. Peru has made an effort to change this in the early 2000's. The institutional setup gives rise to the rare opportunity to study the effects of health insurance coverage exploiting a sharp regression discontinuity design. We find large effects on utilization that are most pronounced for the provision of curative care. Individuals seeing a doctor leads to increased awareness about health problems and generates a potentially desirable form of supplier-induced demand: they decide to pay themselves for services that are in short supply.
Dynamic Discrete Choice Models: Methods, Matlab Code, and Exercises
This document supports the first Matlab computing sessions in our PhD elective course Empirical Industrial Organization II in CentER Tilburg's Research Master in Economics program (230323) and in the Finnish Doctoral Programme in Economics (SEIO11). It contains some notes on the theory of dynamic discrete choice models and on methods for their computation and estimation. It is centered around some basic Matlab code for solving, simulating, and empirically analyzing a simple dynamic discrete choice model. Student exercises ask students to extend this code to apply different and more advanced computational and econometric methods to a wider range of models.
We present a simple example of a two-sided market in Matlab. There are logit models on either side of the market. We generate data from that model and then proceed as if one could in a structural empirical study. In particular, we recover marginal cost, conduct a SSNIP test, calculate UPP, and finally conduct a merger simulation. The zip file contains a document with a detailed explanation of the setup, slides that have been used for teaching, as well as Matlab code.