Security Returns and Tax Aversion Bias: Behavioral Responses to Tax Labels (Digest Summary)

The authors attempt to test empirically the extent to which debt investors (issuers) will accept lower (pay higher) effective returns on debt purchases (sales) simply to avoid paying taxes (maintain a tax deduction). They find that study participants acting as investors as well as those assuming the role of corporate issuers tend to value tax avoidance beyond what the math would predict. Learning diminishes this bias, but the rate of learning varies based on feedback quality. The authors believe that their findings are most relevant for unfamiliar financial decisions and inexperienced players but that the impact of labels may have broader implications.

The authors refer to Ang, Bhansali, and Xing (Journal of Finance 2010), who observed larger-than-expected spreads between taxable and tax-exempt municipal bonds. The authors consider a behavioral explanation (emotional aversion to paying taxes) that is more compelling than a rational market–based explanation (compensation for taking on the burden of having to calculate and pay taxes). They build their study considering the existing tax aversion literature, including the issue of labels; for example, calling a cost a “tax” rather than a “surcharge” or “fee” actually seems to increase investors’ aversion to paying it. Carefully constructing the study to control for possible rational explanations, the authors provide empirical support for a behavioral bias that leads to higher debt returns than expected.

Accepting the authors’ conclusions about behavioral biases, a financial planner helping clients through a new, tax-sensitive transaction should keep in mind investors’ tendency to make wealth-reducing decisions because of tax aversion and take the time required to thoroughly analyze costs and benefits. Conversely, a corporate finance professional arranging new financing should exercise care not to assume that professional status exempts investors from this sort of bias; the authors also refer to a bias among finance professionals.

Finally, governments or companies looking to pass on a tax to consumers may want to use another label to avoid unnecessary resistance at the outset, although that strategy may not remain beneficial once payers become familiar with whatever label is used.

In addition, political actors could choose tax incentives that allow taxpayers to take a greater deduction (i.e., tax avoidance) rather than offering an incentive free from tax to increase the measure’s incentive power.

The authors perform two experiments where participants trade taxable “debt” under different circumstances to test the following hypotheses:

• Tax aversion increases the debt return.
• The effect of tax aversion is higher for a tax deduction of expenses than for a tax exemption of earnings.
• With sufficient opportunity for investors to learn, the effect of tax aversion diminishes with increasing experience.

Participants include undergraduate students at a German university who earn real-money rewards for trading “profits.” Participants may act either as investors or issuers of debt (including issuers allows testing of the second hypothesis because issuers can deduct interest expense). To avoid label problems because of the investment types, debt and equity investments carry the names “yellow” and “blue.” Investor participants are assigned one of three tax rates.

In the first experiment, participants unknowingly trade against a computer algorithm, and in the second, the investor group trades against the issuer group. The traders may either set a debt return or take the default tax-exempt equity return. After each round, traders receive personalized feedback describing profit and loss so that they remain fully aware of tax impact. The results support the first and second hypotheses for the early trades because debt returns on trades significantly exceed the rational rate.

In the second experiment, investors trade against issuers and not only receive personalized feedback but also observe the market level of prices. The additional data enhance feedback quality and provide a reference point for pricing. Results generally support the third hypothesis, but feedback quality affects how quickly participants learn.

Using a student population and a simplified capital market admittedly limits the study’s applicability to the real world. The authors address these limitations by referencing other published research, and they emphasize that the study best addresses one-time transactions by inexperienced players (e.g., life insurance).

One would not expect tax aversion among inexperienced investors to explain municipal bond market spreads because new investors would likely use a bond fund or hire a professional to trade for them. Arbitrageurs probably eliminate such opportunities as they arise. But in the context of one-time transactions—especially complex ones that do not lend themselves to easy calculations—a behavioral bias can lead to mistakes. Financial advisers have a duty to help clients analyze the quantitative and qualitative impact of major transactions to limit these mistakes. Researchers might also develop analytical tools to help the public with this process.