Market versus Residence Principle: Experimental Evidence on the Effects of a Financial Transaction Tax

The effects of a financial transaction tax (FTT) are scientifically disputed, as seemingly small details of its implementation may matter a lot. In this article, we provide experimental evidence on the different effects of an FTT, depending on whether it is implemented as a tax on markets, on residents, or a combination of both. We find that a tax on markets has negative effects on volatility and trading volume, whereas a tax on residents shows none of these undesired effects. Additionally, we observe that individual risk attitude is not related to traders’ reaction to the different forms of an FTT.

y s is a generic placeholder for the dependent variables explained below, i stands for subject. The interacted binary dummy variables for each treatmente.g. M 9 LOSSmeasure the impact of subjects' loss aversion in each treatment. LOSS stands for the individual loss aversion parameter k (G€ achter et al., 2007) ranging from larger than 2.5 in case of rejecting all lotteries to smaller than 0.83 in case of accepting all lotteries. The higher the individual loss parameter k, the more loss averse a subject is. The intercept a represents the average of all treatments. Again, we apply clustered standard errors on a session level to allow for correlation within sessions and independence between sessions. It is important to mention that as all dependent variables are normalised the interacted binary dummies only measure the impact of the loss aversion coefficient. Table A1 shows that loss aversion has an effect on trading volume in the expected direction. More loss averse subjects trade less. Adding the coefficient of RISK to the specification in Table A1, we see from Table A2 that the significance of loss aversion gets weaker and partly insignificant, when we control for RISK. In fact, the best model fit (according to BIC and AIC) is given when we only control for RISK, as has been done in the main text in Table 8.

Appendix B. Interaction of FTT with Loss Aversion
We apply the following regression model to explore whether subjects with different levels of loss aversion react differently to the imposition of an FTT: Here, y m,p is a generic placeholder for the dependent variables and LOSS i stands for the loss aversion coefficient of subject i. 1 Table B1 shows that loss aversion is never significant. This remains true if one adds RISK to the specification. Table B2 shows that loss aversion remains insignificant when risk aversion is controlled for. Again, the best model fit (according to BIC and AIC) is given when we only control for RISK, as has been done in the main text in Table 10.    Notes. Treatments: M: market tax on market LEFT. R: residence tax for residents of market LEFT. MR SAME : residence tax for residents of market LEFT and corresponding market tax on market LEFT. MR DIFF : residence tax for residents of market LEFT and corresponding market tax on market RIGHT. Variables: SUMTAX: normalised sum of all tax payments per subject. MARKETSHARE: subject i's ratio between the trading volume on the left market and on the right market when a tax is levied. DVOLLEFT and DVOLRIGHT: subject i's change in trading volume prior and after an FTT is applied on both markets. RISK: amount X invested in the risky lottery in the risk aversion task (Gneezy and Potters, 1997). LOSS: individual loss aversion parameter k. *, ** and *** represent the 10%, 5% and the 1% significance levels of a double-sided test. Coefficient values with corresponding z-values (in parentheses) are provided. C.6. Calculating Wealth during the Experiment Your wealth (expressed in cash) during the experiment comprised the value of your holdings in the asset (units of the asset multiplied by the last price) plus the holdings in cash. For valuing the asset the last price is used: Wealth ¼ ðunits of the asset Â price of the assetÞ þ cash: If prices in the two markets deviate, the current price with the higher trading volume is used.

C.7. Payout in EUR in the End of the Experiment
Your payment in euro depends on your total wealth at the end of the experiment. Your holdings of the asset will be valued at their fundamental value (not price!) of the last period. The final payment is calculated as follows: Final wealth ¼ ðunits of the asset Â fundamental valueÞ þ cash; Price-Chartof the current period.

Orderbook -list of all
offers to buy of all traders -your own offers to buy are written in blue. The offer with blue background is always the best, i.e., it is the one with the highest price for the seller.

Orderbook -list of all
offers to sell of all traders -your own offers to sell are written in blue. The offer with blue background is always the best, i.e., it is the cheapest one for the buyer.
Overview of your offers to buy and your offers to sell of the current period (offered prices and quantities). With the "DELETE…" buttons own offers can be deleted and so they disappear from the orderbook.
Your signal on the fundamental value of the asset (in cash).
Market LEFT is your HOME MARKET.
© 2017 The Authors. The Economic Journal published by John Wiley & Sons Ltd on behalf of Royal Economic Society.
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