New Approaches to the Economics of Tax Evasion

1. New Approaches to the Economics of Tax Evasion Nigar Hashimzade University of Reading Gareth D. Myles University of Exeter and Institute for Fiscal Studies Binh-Tran Nam University of New South Wales

2. Introduction • The paper considers the analysis of the individual tax compliance decision • This is an area where orthodox analysis has been challenged by behavioural economics • The purposes of economic analysis are to understand and to predict • Results can then be applied for policy purposes to design policy instruments

3. Introduction • The presentation presents a brief discussion of the assessment of economic models • The “standard model” of the compliance decision is then reviewed • This reveals its limitations • Contributions based on behavioural economics are then considered • Forms of non-expected utility • Alternative payoff structures

4. Assessing Models • The purposes of a model are to explore, understand, and predict • Friedman argued that predictions matter not assumptions • But there cannot be understanding if the assumptions are wrong • It is often proposed that a model can be tested by confronting predictions with data • But many models make only weak predictions

5. Assessing Models • But what if a model makes numerous clear predictions • Some of which are correct • But some of which may be wrong? • Especially if the logic for the wrong result is compelling and the evidence is mixed • But intuitively we are convinced it is wrong • This is the situation for the “standard model”

6. Standard Model • The compliance decision is a gamble • Failure to declare correctly may be detected • The taxpayer has a fixed income level Y but declares income X where X ≤ Y • Income when not caught is Ync = Y – tX • If caught a fine at rate F is levied on the tax that has been evaded • Income level when caught is Yc = [1 – t]Y – Ft[Y – X]

7. Standard Model • If income is understated the probability of being caught is p • Applying expected utility theory implies the optimal declaration X solves max{X} E[U(X)] = [1 – p]U(Ync) + pU(Yc) • The model predicts: • Less than full compliance ifp < 1/[1 + F] • Greater compliance if p or F increase • Greater compliance if t increases

8. Standard Model • These results can be obtained from the diagram displaying the decision problem • For example an increase in F reduces Yc • This increases the (absolute) gradient of the trade-off • X* must rise

9. Standard Model • For observed values p < 1/[1 + F]which implies no taxpayer will be fully compliant • This does not match data • The conclusion that compliance rises as t increases runs counter to “intuition” and has mixed empirical support • Problem of separating aggregate and individual effects • Weakness of experimental evidence • The failure of these predictions has lead to a search for alternative models

10. Alternative Approaches • Behavioural economics can be seen as a loosening of modelling restrictions • Two different directions can be taken: (i) Move away from expected utility theory (ii) Modify the terms that enter the utility functions • The consequences of making such changes are now considered

11. Non-Expected Utility • Expected utility theory is based on a set of axioms • Preferences are defined over lotteries • The axioms impose consistency conditions over combinations of lotteries • Experimental evidence reveals the violation of these axioms • The best-known example of violation is the Allais paradox

12. Non-Expected Utility • Most people choose 1A over 1B • And choose 2B over 2A • Extract the “sure thing” of $1 million with 89% • Or cancel from both sides of additive EU • Residual gamble is the same

13. Non-Expected Utility • There are several non-expected utility models • These have the general form V(X) = w1(p, 1 – p)v(Yc) + w2(p, 1 – p)v(Ync) • w1(p, 1 – p) and w2(p, 1 – p) are translations of p and 1 – p • v(.) is some translation of u(.) • Different representations are special cases of this general form

14. Non-Expected Utility • Some of the alternatives that have been applied to the compliance decision are: • Rank Dependent Expected Utility imposes structure on the translation of probabilities • Prospect Theory translates probabilities, changes payoff functions, and uses a reference point • Non-Additive Probabilities do not require the normal consistency of aggregation for probabilities • Ambiguity permits uncertainty over the probability of outcomes

15. Non-Expected Utility • Adopting non-expected utility can solve one problem • The transformation of probabilities can raise the rate of compliance • Non-expected utility does not change the tax effect • Recall Ync = Y –tX and Yc = [1 –t]Y–Ft[Y–X] • What matters is tX so the solution always has X = [1/t]f( . )

16. Prospect Theory • Use this as an example • Prospect theory does three things • Translate the probabilities • Convex losses and concave gains • Payoffs are measured relative to a reference point • These changes create additional problems

17. Prospect Theory • The figure represents one parameterization of Yaniv’s (1999) application of prospect theory • The solid line is the payoff given by prospect theory • The two dashed lines represent the two component payoffs X/Y

18. Modified Payoffs • Alternatively the arguments of the payoff functions can be changed • This can change the results by breaking the dominance of the tX term • This can be achieved through adopting convexity of cost in evasion • Or through including additional terms in the payoff

19. Modified Payoffs • The simplest change is to have punishment convex in evasion • But does this represent tax law? • Or a dynamic model so that cost increases with the number of years on non-compliance • But limitations on discovery • Can also have additional costs of evasion • Psychic costs • Social custom costs • Tax morale

20. Additional Costs • Social customs explain links between taxpayers and differences between countries • Psychic costs can be “guilty conscience” and “public disgrace” • These changes can reverse the tax effect when the cost is determined by the level of evasion • They can also be combined with the non-expected utility models

21. Conclusions • Non-expected utility delivers nothing that is not given by adopting subjective probabilities in the EU model • It requires some modification of the payoff to reverse the tax result • So the non-expected utility models are not in themselves the solution • A possible solution is to reflect more carefully on what taxpayers care about