Randomization to treatment failure in experimental auctions: The value of data from training rounds

Briz, Teresa and Drichoutis, Andreas C. and Nayga, Rodolfo M. (2014): Randomization to treatment failure in experimental auctions: The value of data from training rounds.

Abstract

In the experimental auctions literature it is common practice to train the potentially unfamiliar subjects in the auction procedure by conducting a few training (often hypothetical) auctions. Data from these practice auctions are rarely reported in scientific papers. We argue that valuable information can be conveyed by looking at data coming from the training rounds of experimental auctions. As a case study, we use data from an experiment that seeks to elaborate on the mediating role of mood states on projection bias. Following a mood induction procedure, subjects are found to bid more under negative mood (as compared to positive mood) for products that are delivered in the future but bid less under negative mood for products that are delivered in present time. We show that if we had neglected insights gained from the training auction data, we would not have been able to detect a failure of randomization to treatment.

• Item Type: MPRA Paper
• Language: English
• Keywords: projection bias; mood induction; experimental auctions; randomization to treatment
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C90 - General

References

Briz, T., A. C. Drichoutis, and L. House (2015). Examining projection bias in experimental auctions: The role of hunger and immediate gratification. Agricultural and Food Economics 3 (22).

Brodeur, A., M. Le, M. Sangnier, and Y. Zylberberg (2016). Star wars: The empirics strike back. American Economic Journal: Applied Economics 8 (1), 1-32.

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ, USA: Lawrence Erlbaum Associates.

Corrigan, J. R., A. C. Drichoutis, J. L. Lusk, J. R.M. Nayga, and M. C. Rousu (2012). Repeated rounds with price feedback in experimental auction valuation: An adversarial collaboration. American Journal of Agricultural Economics 94 (1), 97-115.

Corrigan, J. R., M. C. Rousu, and D. P. T. Depositario (2014). Do practice rounds affect experimental auction results? Economics Letters 123 (1), 42-44.

Demont, M., P. Rutsaert, M. Ndour, W. Verbeke, P. A. Seck, and E. Tollens (2013). Experimental auctions, collective induction and choice shift: willingness-to-pay for rice quality in Senegal. European Review of Agricultural Economics 40 (2), 261-286.

Demont, M., E. Zossou, P. Rutsaert, M. Ndour, P. Van Mele, and W. Verbeke (2012). Consumer valuation of improved rice parboiling technologies in Benin. Food Quality and Preference 23 (1), 63-70.

Diggle, P. J., P. Heagerty, K.-Y. Liang, and S. L. Zeger (2002). Analysis of Longitudinal Data (2nd ed.). New York, USA: Oxford University Press Inc.

Drichoutis, A. C., J. L. Lusk, and R. M. Nayga (2015). The veil of experimental currency units in second price auctions. Journal of the Economic Science Association 1 (2), 182-196.

Drichoutis, A. C., J. Rodolfo M. Nayga, and P. Lazaridis (2011). The role of training in experimental auctions. American Journal of Agricultural Economics 93 (2), 521-527.

Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.

Ho, D. E., K. Imai, G. King, and E. A. Stuart (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis 15 (3), 199-236.

Hoffman, E., D. J. Menkhaus, D. Chakravarti, R. A. Field, and G. D. Whipple (1993). Using laboratory experimental auctions in marketing research: A case study of new packaging for fresh beef. Marketing Science 12 (3), 318-338.

Isoni, A., G. Loomes, and R. Sugden (2010). The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations: Comment. American Economic Review 101 (2), 991-1011.

Kahneman, D. and R. H. Thaler (2006). Anomalies: Utility maximization and experienced utility. Journal of Economic Perspectives 20 (1), 221-234.

Kessler, J. B. and S. Meier (2014). Learning from (failed) replications: Cognitive load manipulations and charitable giving. Journal of Economic Behavior & Organization 102 (0), 10-13.

Lang, P. J., M. M. Bradley, and B. N. Cuthbert (2008). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical report A-8, University of Florida, Gainesville, FL.

Lee, J. Y., D. B. Han, R. M. Nayga, and S. S. Lim (2011). Valuing traceability of imported beef in Korea: an experimental auction approach*. Australian Journal of Agricultural and Resource Economics 55 (3), 360-373.

Liu, H. and T. Wu (2005). Sample size calculation and power analysis of time-averaged difference. Journal of Modern Applied Statistical Methods 4 (2), 434-445.

Loewenstein, G., T. O'Donoghue, and M. Rabin (2003). Projection bias in predicting future utility. The Quarterly Journal of Economics 118 (4), 1209-1248.

Lusk, J. L., M. S. Daniel, D. R. Mark, and C. L. Lusk (2001). Alternative calibration and auction institutions for predicting consumer willingness to pay for nongenetically modified corn chips. Journal of Agricultural and Resource Economics 26 (1), 40-57.

Lusk, J. L. and J. F. Shogren (2007). Experimental auctions, Methods and applications in economic and marketing research. Cambridge, UK: Cambridge University Press.

Madeira, T. (2015). Weather, mood, and use of antidepressants: The role of projection bias in mental health care decisions. Working paper.

Mehra, R. and R. Sah (2002). Mood fluctuations, projection bias, and volatility of equity prices. Journal of Economic Dynamics and Control 26 (5), 869-887.

Menkhaus, D. J., G. W. Borden, G. D. Whipple, E. Hoffman, and R. A. Field (1992). An empirical application of laboratory experimental auctions in marketing research. Journal of Agricultural and Resource Economics 17 (1), 44-55.

Morawetz, U. B., H. De Groote, and S. C. Kimenju (2011). Improving the use of experimental auctions in Africa: Theory and evidence. Journal of Agricultural and Resource Economics 36 (2), 263-279.

Mutz, D. C. and R. Pemantle (2015). Standards for experimental research: Encouraging a better understanding of experimental methods. Journal of Experimental Political Science 2 (2), 192-215.

Neugebauer, T. and J. Perote (2007). Bidding as if risk neutral in experimental first price auctions without information feedback. Experimental Economics 11 (2), 190-202.

Newson, R. and the ALSPAC Study Team (2003). Multiple-test procedures and smile plots. Stata Journal 3 (2), 109-132.

Olivola, C. Y. and S. W. Wang (2015). Patience auctions: the impact of time vs. money bidding on elicited discount rates. Experimental Economics, 1-22.

Peirce, C. S. and J. Jastrow (1885). On small differences in sensation. Memoirs of the National Academy of Sciences 3, 73-83.

Plott, C. R. and K. Zeiler (2005). The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations. The American Economic Review 95 (3), 530-545.

Plott, C. R. and K. Zeiler (2011). The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations: Reply. American Economic Review 101 (2), 1012-28.

Robles, R. and F. Paez (2003). Estudio sobre la traduccion al espa~nol y las propiedades psicometricas de las escalas de afecto positivo y negativo (PANAS). Salud Mental 26 (1), 69-75.

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology 66 (5), 688-701.

Rubin, D. B. (1990). [On the application of probability theory to agricultural experiments. Essay on principles. Section 9.] Comment: Neyman (1923) and causal inference in experiments and observational studies. Statistical Science 5 (4), 472-480.

Selya, A. S., J. S. Rose, L. C. Dierker, D. Hedeker, and R. J. Mermelstein (2012). A practical guide to calculating Cohen's f2, a measure of local effect size, from PROC MIXED. Frontiers in Psychology 3, 111.

Shogren, J. F., M. Margolis, C. Koo, and J. A. List (2001). A random nth-price auction. Journal of Economic Behavior and Organization 46 (4), 409-421.

Siegel, A. E. (1964). Sidney Siegel: a memoir. In S. Messick and A. H. Brayeld (Eds.), Decision and Choice. Contributions of Sidney Siegel. New York: McGraw-Hill Book Co.

Simmons, J. P., L. D. Nelson, and U. Simonsohn (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science 22 (11), 1359-1366.

Simonsohn, U., L. D. Nelson, and J. P. Simmons (2014). P-curve: A key to the file-drawer. Journal of Experimental Psychology: General 143 (2), 534-547.

Smithson, M. (2001). Correct confidence intervals for various regression effect sizes and parameters: The importance of noncentral distributions in computing intervals. Educational and Psychological Measurement 61 (4), 605-632.

Snijders, T. A. and R. J. Bosker (1999). Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modeling. London: Sage publications Ltd.

Speed, T. P. (1990). Introductory remarks on Neyman (1923). Statistical Science 5 (4), 463-464.

Splawa-Neyman, J., D. M. Dabrowska, and T. P. Speed (1990). On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Statistical Science 5 (4), 465-472.

Svorencik, A. (2015). The experimental turn in Economics: A history of Experimental Economics. University of Utrecht, Utrecht school of economics, Dissertation series #29.

Vickrey, W. (1961). Counterspeculation, auctions, and competitive sealed tenders. Journal of Finance 16 (1), 8-37.

Watson, D., L. A. Clark, and A. Tellegen (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology 54 (6), 1063-1070.

Wilson, T. D. and D. T. Gilbert (2003). Afective Forecasting, Volume Volume 35, pp. 345-411. Academic Press.

Zhang, L. and A. Ortmann (2013). Exploring the meaning of signficance in experimental economics. Australian School of Business Research Paper No. 2013 ECON 32.