Working Paper: CEPR ID: DP17238
Authors: Marco Cipriani; Antonio Guarino; Andreas Uthemann
Abstract: We develop a new methodology to estimate the impact of a financial transaction tax (FTT) on financial market outcomes. In our sequential trading model, there are price-elastic noise and informed traders. We estimate the model through maximum likelihood for a sample of sixty New York Stock Exchange (NYSE) stocks in 2017. We quantify the effect of introducing an FTT given the parameter estimates. An FTT increases the proportion of informed trading, improves information aggregation, but lowers trading volume and welfare. For some less liquid stocks, however, an FTT blocks private information aggregation.
Keywords: financial transaction tax; market microstructure; structural estimation
JEL Codes: G14; D82; C13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| increase in informed trading (G14) | improved information aggregation (D83) |
| increase in informed trading (G14) | inefficiencies in price discovery (G14) |
| financial transaction tax (FTT) (F38) | blocks private information aggregation (D82) |
| financial transaction tax (FTT) (F38) | increase in informed trading (G14) |
| financial transaction tax (FTT) (F38) | decrease in trading volume (G14) |
| financial transaction tax (FTT) (F38) | decrease in welfare for less liquid stocks (G19) |