My z-Tree online course is a self-paced, fully online course teaching you how to program and run experiments using the z-Tree programming environment for economic experiments. The course consists of a series of video chapters, augmented by exercises and other resources.
Watch the course on YouTube, and download the accompanying resource package.
The Bubble Measure database was published in Palan, S., 2013. A Review of Research into Smith, Suchanek and Williams Markets, Working Paper Series of the Faculty of Social and Economics Sciences, Karl-Franzens-University Graz 2013-04. The database and accompanying material is available from http://dx.doi.org/10.17632/fypc7g44xc.3 and can be cited as Palan, Stefan (2016), “Bubble Measure Database”, Mendeley Data, v3, DOI 10.17632/fypc7g44xc.3.
zTools is an add-in for Microsoft Excel™, designed to facilitate work with z-Tree, the Zurich Toolbox for Readymade Economic Experiments. Feedback – including, but not limited to, suggestions for new functionality – is appreciated and should be directed to uni@palan.biz.
There is also one video explaining the concepts of tables and scope in z-Tree:
Slides of a comprehensive introduction to z-Tree, v2.9.0:
Various z-Tree resources used alongside the lecture (demo treatments, batch files, tools, etc.):
A number of batch files to quickly open and close z-leafs, to close z-Tree when its process is still running even after the program has been closed, or to delete the temporary files generated while testing in z-Tree. Also included: an Excel sheet for calculating color codes for use in z-Tree, and a tutorial for reading z-Tree output data into R for analysis.
Definition file to enable z-Tree code highlighting in Notepad++.
GIMS is a software for asset market experiments, based on the z-Tree software platform. Feedback – including, but not limited to, suggestions for new functionality – is appreciated and should be directed to stefan.palan@uni-graz.at.
If you use GIMS, please cite the corresponding paper: Palan, S., 2015. “GIMS – Software for Asset Market Experiments”, Journal of Behavioral and Experimental Finance 5, 1-14, DOI: 10.1016/j.jbef.2015.02.001.
Download the latest version, including full documentation, from Zenodo or clone the repository from GitLab or GitHub.
Camerer, C. F., Dreber, A., Forsell, E., Ho, T.-H., Huber, J., Johannesson, M., Kirchler, M., Almenberg, J., Altmejd, A., Chan, T., Heikensten, E., Holzmeister, F., Imai, T., Isaksson, S., Nave, G., Pfeiffer, T., Razen, M., Wu, H., 2016. Evaluating replicability of laboratory experiments in economics, Science 351(6280), 1433-1436.
Deck, C., Hao, L., Xu, W., Yeager, T. J., 2021. Social Comparison and Wealth Inequality in a Leveraged Asset Market, Journal of Behavioral Finance 22(4), 382-402.
Duch, M. L., Grossmann, M. R.P., Lauer, T., 2020. z-Tree unleashed: A novel client-integrating architecture for conducting z-Tree experiments over the Internet, Journal of Behavioral and Experimental Finance, 100400.
Giamattei, M., Huber, J., Lambsdorff, J. G., Nicklisch, A., Palan, S., 2020. Who inflates the bubble? Forecasters and traders in experimental asset markets, Journal of Economic Dynamics and Control 110, 103718.
Hefti, A., Heinke, S., and Schneider, F., 2016. Mental Capabilities, Trading Styles, and Asset Market Bubbles. Theory and Experiment.
Huber, C., Bindra, P. C., Kleinlercher, D., 2019. Design-features of bubble-prone experimental asset markets with a constant FV, Journal of the Economic Science Association 73(2), 419.
Huber, J., Palan, S., Zeisberger, S., 2019. Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence, Journal of Banking and Finance 108(105635).
Marquardt, P., Noussair, C. N., Weber, M., 2019. Rational expectations in an experimental asset market with shocks to market trends, European Economic Review 114, 116-140.
Palan, S., Huber, J., Senninger, L., 2020. Aggregation mechanisms for crowd predictions, Experimental Economics 23, 788-814.
Razen, M., Kupfer, Al, 2023. The effect of tax transparency on consumer and firm behavior: Experimental evidence, Journal of Behavioral and Experimental Economics, 101990.
Weitzel, U., Huber, C., Huber, J., Kirchler, M., Lindner, F., Rose, J., 2020. Bubbles and Financial Professionals, The Review of Financial Studies 33(6), 2659-2696.