Behavioral and Experimental Economics

Summer School Experimental Economics

The Behavioral and Experimental Economics group has an influential position in this field in the Netherlands and Europe. CREED, the Amsterdam-based group, focuses particularly on three main projects: economics of political decision making; bounded rationality and institutions and experimental economics. The research of the Rotterdam-based group focuses on two broad themes: decision under risk and uncertainty and intertemporal choice.

Cooperative Behavior, Strategic Interaction and Complex Systems

This research group focuses on: (non-)cooperative game theory; nonlinear dynamics and complex systems; bounded rationality, learning and heterogenous expectations; dynamic models of collective behavior and social networks & dynamic optimization.

Econometrics and Operations Research

Research themes: time series econometrics, panel data, Bayesian econometrics, applied econometrics and econometric methodology. Applications can be found in areas as diverse as monetary economics, labor economics, marketing and asset pricing. Some fellows in this group focus on operations research.


The Finance group at TI spans many of the core fields in finance: asset pricing, corporate finance, financial econometrics, market microstructure, and financial institutions.

Labor, Health, Education and Development

At TI, a large group of fellows works in different areas of labour, health, education and development.

Macroeconomics and International Economics

Fellows in the Macroeconomics and International Economics group carry out research on growth, innovation, international trade and factor mobility, the role of economic geography, banking and monetary economics, and fiscal policy.

Organizations and Markets

The Organizations and Markets (OM) group spans many areas in (applied) microeconomics, including the economics of organizations, industrial organization, entrepreneurship, innovation, and auctions.

Spatial, Transport and Environmental Economics

The STEE group addresses four themes: urban and regional dynamics, land use, transportation, and environment and resources. Many fellows combine policy research with fundamental research.

Journal of Econometrics, August 2016, 193(2), 405-417

For the purpose of forecasting key macroeconomic or financial variables from a panel of time series variables, we adopt the dynamic factor model and propose a weighted likelihood-based method for parameter estimation. The loglikelihood function is split into two parts that are weighted differently. The first part is associated with the key variables while the second part is associated with the related variables which may contribute to the forecasting of key variables. We derive asymptotic properties, including consistency and asymptotic normality, of the weighted maximum likelihood estimator. We show that this estimator outperforms the standard likelihood-based estimator in approximating the true unknown distribution of the data as well as in out-of-sample forecasting accuracy. We verify the new estimation method in a Monte Carlo study and investigate the role of different weights in different settings. In the context of forecasting gross domestic product growth, this key variable is typically observed at a low (quarterly) frequency while the supporting variables are observed at a high (monthly) frequency. We adopt a low frequency representation of the mixed frequency dynamic factor model and discuss the computational efficiencies of this approach. In our empirical study for the U.S. economy, we present improvements in nowcasting and forecasting accuracy when the weighted likelihood-based estimation procedure is adopted.

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