Which performs better under trader settings, double auction or uniform price auction?


A marketable permit system (MPS) has been suggested as a solution to environmental problems. Although the properties of MPSs under non-trader settings, in which each player is exclusively either a seller or a buyer, are well documented, little research has explored how MPSs perform under trader settings, in which each player can be both a seller and a buyer. We institute two auctions of trader settings in MPS experiments: a double auction (DA) and a uniform price auction (UPA). We then evaluate and compare their performances both with each other and with those under non-trader settings. The main results are as follows: DAs under trader settings perform much worse than do DAs under non-trader settings, whereas UPAs perform well, regardless of the trader and non-trader settings. UPAs are more efficient and generate more stable prices than do DAs under trader settings, and a considerable proportion of trades in DAs under trader settings consist of “flips” that could be considered speculation or errors. Thus, UPAs are likely to work better than DAs under trader settings.

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  1. 1.

    The trader or non-trader setting is determined by whether each agent in a permit market can be both a seller and a buyer during trading periods or whether each agent can be only one or the other. If the agents can take on both roles, we denote the environment as a “trader setting,” otherwise, the environment is called a “non-trader setting” (see Ledyard and Szakaly-Moore 1994).

  2. 2.

    For instance, Anderson and Sutinen (2005) clearly demonstrate an event of “bubbles” in the laboratory experiments of tradable fishing allowances with DAs under trader settings.

  3. 3.

    Anderson and Sutinen (2006) implement laboratory experiments of tradable fishing allowance markets employing UPA and DA. However, their UPA is a “continuous uniform double auction,” which is fundamentally different from the UPA we use in our experiment. Our UPA is a sealed-bid uniform price auction, which is the same as that adopted by Smith et al. (1982) and Cason and Plott (1996), except we use trader settings. In addition, Anderson and Sutinen (2006) focus on the price discovery of fishing allowance markets and thus use different experimental parameters for UPAs and DAs. A direct comparison between the auctions cannot be made on the same ground, which is also noted by the authors. In finance, Boening et al. (1993) compare the price dynamics under DA and UPA, showing that a UPA institution reduces price bubbles.

  4. 4.

    The UPA under non-trader settings in our experiments follows the call market or uniform price auction introduced by Davis and Holt (1992), in which bids to buy from buyers and offers to sell from sellers are first collected and all trades are effected at a uniform price. Such UPAs have been employed for real-world trades such as in financial markets in the European, New York, American and Tokyo stock exchanges.

  5. 5.

    This feature is adopted to avoid “end effects,” following Cason and Gangadharan (2006).

  6. 6.

    For instance, a subject of \(T1\) firm is asked to submit 8 bids to buy and 2 offers to sell. Since two subjects are assigned to one type of firm among 4 types, as shown in Table 1, in total, 32 offers to sell and 48 bids to buy are submitted from 8 subjects in a period.

  7. 7.

    Fixed revenue was included in the payoff calculation for adjustment purposes.

  8. 8.

    Note that there has been no research that employs UPAs under trader settings for marketable permit experiments.

  9. 9.

    There are possible 6 pairs of treatments: (“\(\text {T}\_\text {DA}\) versus \(\text {T}\_\text {UPA}\),” “\(\text {T}\_\text {DA}\) versus \(\text {NT}\_\text {DA}\),” “\(\text {T}\_\text {DA}\) versus \(\text {NT}\_\text {UPA}\),” “\(\text {T}\_\text {UPA}\) versus \(\text {NT}\_\text {DA}\),” “\(\text {T}\_\text {UPA}\) versus \(\text {NT}\_\text {UPA}\)” and “\(\text {NT}\_\text {DA}\) versus \(\text {NT}\_\text {UPA}\)”). For each pair, we have run a Mann-Whitney test.

  10. 10.

    The Mann-Whitney test for the pair of \(\text {NT}\_\text {UPA}\) versus \(\text {T}\_\text {UPA}\) does not exhibit any statistical significance, implying that non-trader or trader settings do not affect the efficiency of UPAs.

  11. 11.

    In \(\text {T}\_\text {UPA}\) and \(\text {NT}\_\text {UPA}\), the average trading price and the last trading price in a period are identical.

  12. 12.

    There is one outlying observation of 166 at period 1 in \(\text {NT}\_\text {DA}\) for Figs. 3a and 5a. This is due to the fact that a trading price of 866 is observed at period 1 in session 4 of \(\text {NT}\_\text {DA}\) and the trade is considered an error (For the reference, all the trading prices in session 4 of \(\text {NT}\_\text {DA}\) including the outlier are shown in Fig. 8 at the “Appendix”). In Figs. 3a and 5a, we do not include the outlier to ensure the clearer visibility.

  13. 13.

    As was done with efficiency data in the previous subsection, we have six sessions per treatment. Therefore, we have six independent observations of average prices and the average last trading prices over 10 periods per treatment.

  14. 14.

    We could separately show the same figure by each period from 1 to 10. However, what we can illustrate in Fig. 6a, b is the same as the figure per period in DAs. Therefore, we decided to show only the two figures. For readers to see how trading patterns occur, especially for DAs, all the prices over 10 periods in some sessions of \(\text {NT}\_\text {DA}\) and \(\text {T}\_\text {DA}\) are shown in Fig. 9 at the appendix.

  15. 15.

    For robustness check, we run the regression model of Eq. (1) using the average trading prices per session in each period. The results are almost the same as that shown in Table 4. The estimated convergent average price in \(\text {T}\_\text {DA}\) is 95, which is outside the equilibrium price range. The estimated convergent average prices in other treatments are within the equilibrium price range or sufficiently close to it.

  16. 16.

    Godby (2002) conducts various treatments of market power experiments for emission permit trading. Among them, treatment 5 is the closest to the experiments in our research, generating a TR of 1.9. Because the TR in our experiments is 1.8, the TR result seems to be plausible and consistent with Godby (2002).

  17. 17.

    In asset market experiments, Lei et al. (2001) demonstrate that the occurrences of bubbles and poor performances in DAs are not due to speculative trades. There are two differences between our results and those of Lei et al. (2001). One difference is that each permit in our experiment is a single period-lived asset and possesses a clear underlying value of MACs, whereas a commodity in the asset market is a multiple period-lived asset, and its underlying value depends on subjects’ future expectations of dividends or returns. Therefore, the underlying value of multiple period-lived assets changes in a more complex manner than that of permits in the MPS experiments. The other difference is that the non-trader settings in this research can be considered to give information about which side (buyers or sellers) of markets each subject is on, whereas the “no-resale” treatment in Lei et al. (2001) does not give such information.

  18. 18.

    Jamison and Plott (1997) demonstrate that bids and asks in the closing moments of a continuous double auction play a fundamental role in price discovery. Easley and Ledyard (1993) develop a theoretical model of double auctions by assuming that the last trading price for a period in a continuous time double auction contains key information for price adjustment in the next period.


  1. Anderson, C. M., & Sutinen, J. G. (2005). A laboratory assessment of tradable fishing allowances. Marince Resource Economics, 20, 1–20.

    Article  Google Scholar 

  2. Anderson, C. M., & Sutinen, J. G. (2006). The effect of initial lease periods on price discovery in laboratory tradable fishing allowance markets. Journal of Economic Behavior and Organization, 61, 164–180.

    Article  Google Scholar 

  3. Cason, T. N. (2010). What can laboratory experiments teach us about emissions permit market design? Agricultural and Resource Economics Review, 39, 151–161.

    Article  Google Scholar 

  4. Cason, T. N., & Friedman, D. (1999). Learning in a laboratory market with random supply and demand. Experimental Economics, 2, 77–98.

    Article  Google Scholar 

  5. Cason, T. N., & Gangadharan, L. (2005). A laboratory comparison of uniform and discriminative price auctions for reducing non-point source pollution. Land Economics, 81, 51–70.

    Article  Google Scholar 

  6. Cason, T. N., & Gangadharan, L. (2006). Emissions variability in tradable permit markets with imperfect enforcement and banking. Journal of Economic Behavior and Organization, 61, 199–216.

    Article  Google Scholar 

  7. Cason, T. N., Gangadharan, L., & Duke, C. (2003). Market power in tradable emission markets: A laboatory testbed for emission trading in Port Phillip Bay, Victoria. Journal of Environmental Economics and Management, 46, 469–491.

    Article  Google Scholar 

  8. Cason, T. N., & Plott, C. R. (1996). EPA’s new emission trading mechanism: A laboratory evaluation. Journal of Environmental Economics and Management, 30, 133–160.

    Article  Google Scholar 

  9. Conover, W. J. (1999). Practical nonparametric statistics. New York: Wiley.

    Google Scholar 

  10. Davis, D. D., & Holt, C. A. (1992). Experimental economics. Princeton: Princeton University Press.

    Google Scholar 

  11. Easley, D., & Ledyard, J. (1993). Theories of price formation and exchange in double oral auction. In D. Friedman & J. Rust (Eds.), The double auction market: Institutions, theories and evidence, chapter 3 (pp. 253–283). Boulder: Westview press.

    Google Scholar 

  12. Farrell, M. J. (1966). Profitable speculation. Economica, 33, 183–193.

    Article  Google Scholar 

  13. Field, B. C., & Field, M. K. (2006). Environmental economics. New York: McGraw-Hill/Irwin.

    Google Scholar 

  14. Fischbacher, U. (2007). Z-tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10, 171–178.

    Article  Google Scholar 

  15. Godby, R. (2002). Market power in laboratory emission permit markets. Environmental and Resource Economics, 23, 279–318.

    Article  Google Scholar 

  16. Godby, R. W., Mestelman, S., Muller, R. A., & Welland, J. D. (1997). Emissions trading with shares and coupons when control over discharges is uncertain. Journal of Environmental Economics and Management, 32, 359–381.

    Article  Google Scholar 

  17. Goeree, J. K., Holt, C. A., Palmer, K., Shobe, W., & Burtraw, D. (2010). An experimental study of auctions versus grandfathering to assign pollution permits. Journal of the European Economic Association, 8, 514–525.

    Article  Google Scholar 

  18. Hahn, R. W. (1989). Economic prescriptions for environmental problems: How the patient followed the doctor’s orders. Journal of Economic Perspectives, 3, 95–114.

    Article  Google Scholar 

  19. Hahn, R. W., & Stavins, R. N. (2011). The effect of allowance allocations on cap-and-trade system performance. Journal of Law and Economics, 54, 267–294.

    Article  Google Scholar 

  20. Jamison, J. C., & Plott, C. R. (1997). Costly offers and the equilibration properties of the multiple unit double auction under conditions of unpredictable shifts of demand and supply. Journal of Economic Behavior and Organization, 32, 591–612.

    Article  Google Scholar 

  21. Kilian, L., & Murphy, D. P. (2014). The role of inventories and speculative trading in the global market for crude oil. Journal of Applied Econometrics, 29, 454–478.

    Article  Google Scholar 

  22. Kilkenny, M. (2000). A classroom experiment about tradable permits. Review of Agricultural Economics, 22, 586–606.

    Article  Google Scholar 

  23. Kolstad, C. C. (2010). Environmental economics (2nd ed.). Oxford: Oxford University Press.

    Google Scholar 

  24. Ledyard, J. O., & Szakaly-Moore, K. (1994). Designing organizations for trading pollution rights. Journal of Economic Behavior and Organization, 25, 167–196.

    Article  Google Scholar 

  25. Lei, V., Noussair, C. N., & Plott, C. R. (2001). Nonspeculative bubbles in experimental asset markets: Lack of common knowledge of rationality vs. actual irrationality. Economica, 69, 831–859.

    Google Scholar 

  26. Muller, R., & Mestelman, S. (1998). What have we learned from emissions trading experiments? Managerial and Decision Economics, 19, 225–238.

    Article  Google Scholar 

  27. Muller, R., Mestelman, S., Spraggon, J., & Godby, R. (2002). Can double auctions control monopoly and monopsony power in emissions trading markets? Journal of Environmental Economics and Management, 44, 70–92.

    Article  Google Scholar 

  28. Myagkov, M., & Plott, C. (1997). Exchange economies and loss exposure: Experiments exploring prospect theory and competitive equilibria in market environments. American Economic Review, 87, 801–828.

    Google Scholar 

  29. Noussair, C. N., Plott, C., & Riezman, R. (1995). An experimental investigation of the patterns of international trade. American Economic Review, 85, 462–491.

    Google Scholar 

  30. Plott, C. R. (1983). Externalities and correctives policies in experimental markets. Economic Journal, 93, 106–127.

    Article  Google Scholar 

  31. Plott, C. R., & Gray, P. (1990). The multiple unit double auction. Journal of Economic Behavior and Organization, 13, 245–258.

    Article  Google Scholar 

  32. Plott, C. R., & Pogorelskiy, K. (2017). Call market experiments: Efficiency and price discovery through multiple calls and emergent Newton adjustments. American Economic Journal: Microeconomics, 9, 1–41.

    Google Scholar 

  33. Smith, V. L., Williams, A. W., Bratton, W., & Vannoni, M. G. (1982). Market institutions: Double auctions vs. sealed bid-offer auctions. American Economic Review, 72, 58–77.

    Google Scholar 

  34. Tietenberg, T. H. (2006). Emissions trading: Principles and practice. Washington: RFF Press.

    Google Scholar 

  35. Van Boening, M. V., & Wilcox, N. T. (1996). Avoidable cost: Ride a double auction roller coaster. American Economic Review, 86, 461–477.

    Google Scholar 

  36. Van Boening, M. V., Williams, A. W., & LaMaster, S. (1993). Price bubbles and crashes in experimental call markets. Economics Letters, 41, 179–185.

    Article  Google Scholar 

  37. Williams, A. W. (1980). Computerized double-auction markets: Some initial experimental results. Journal of Business, 53, 235–258.

    Article  Google Scholar 

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The authors thank anonymous referees, Makoto Kakinaka and Hiroaki Miyamoto for their helpful comments, advice and supports. We are also grateful to the financial supports from the Japan Society for the Promotion of Science (JSPS) as the Grant-in-Aid for Scientific Research B (16H03621), JSPS Specially Promoted Research and Ministry of Environment, Japan (S-16) and Kochi University of Technology.

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Correspondence to Koji Kotani.



In this appendix, all the trading prices over 10 periods in some sessions of \(\text {T}\_\text {DA}\) and \(\text {NT}\_\text {DA}\) are shown in Figs. 8 and 9 as samples for readers to see how trading patterns occur, especially for DAs.

Fig. 8

All the trading prices over 10 periods in session 4 of \(\text {NT}\_\text {DA}\)

Fig. 9

Samples of all the trading prices over 10 periods in some sessions of \(\text {NT}\_\text {DA}\) and \(\text {T}\_\text {DA}\). a All the trading prices over 10 periods in session 4 of \(\text {NT}\_\text {DA}\), b all the trading prices over 10 periods in session 1 of \(\text {T}\_\text {DA}\)

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Kotani, K., Tanaka, K. & Managi, S. Which performs better under trader settings, double auction or uniform price auction?. Exp Econ 22, 247–267 (2019). https://doi.org/10.1007/s10683-018-9585-0

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  • Marketable permits
  • Economic experiments
  • Double auction
  • Uniform price auction
  • Non-trader settings
  • Trader settings

JEL Classification

  • D44
  • Q50
  • C91