Understanding Individual Tax Compliance

1. Understanding Individual Tax Compliance Gareth D. Myles University of Exeter and Tax Administration Research Centre In collaboration with Miguel Fonseca Exeter and TARC Shaun Grimshaw Exeter and TARC Nigar Hashimzade Durham and TARC Tim Miller Exeter and TARC Matthew Rablen Brunel and TARC The financial support of ESRC/HMRC/HMT is gratefully acknowledged.

2. Introduction • An understanding of the individual tax compliance decision is important for revenue services • It is necessary for designing good policy interventions that reduce the tax gap • Tax compliance is an area where orthodox analysis has been challenged by behavioural economics • This talk explores the limitations of the orthodox analysis and suggests improvements

3. Starting Point • A natural starting point is to consider non-compliance as a gamble • A non-compliant taxpayer is gambling on not being audited and discovered • Let the taxpayer have income Y and declare income X, with 0 ≤ X ≤ Y • Income when not caught is Ync = Y – tX • If the fine is F then income when caught is Yc = [1 – t]Y – Ft[Y – X]

4. Orthodox Analysis • 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) • There are two states of the world: • In one state the taxpayer is not caught evading and income is Ync • In the other state they are caught and income is Yc

5. Evasion Decision • The choice problem is shown in Figure 1 • The optimal declaration achieves the highest indifference curve • The taxpayer chooses to locate at the point with declaration X* • This is an interior point with 0 < X*< Y • Some tax is evaded but some income is declared Figure 1: Interior choice: 0 < X* < Y

6. Non-Compliance • Non-compliance occurs when the indifference curve is steeper than the budget constraint at X = Y • This is true when p < 1/[1 + F] • If this condition is satisfied the taxpayer should be non-compliant • It is independent of preferences • When F = 1 the taxpayer will evade if p < ½ • The model predicts that for realistic parameter values every taxpayer should be non-compliant

7. Tax Effect • An increase in the tax rate moves the budget constraint inward as in Figure 2 • The outcome is not clear-cut • If taxpayers are more willing to take on a fixed gamble as income increases then a tax increase reduces tax evasion • This is because the fine is Ft so an increase in the t raises the penalty Figure 2: Tax rate increase

8. Testing the Results • The model could be tested by comparing its predictions against data • The publicly available data is very limited and has not been adequate to test the model • An alternative strategy has been to use experiments to test the model • How does the behaviour of experimental subjects compare to the predictions?

9. Experiments • Most experiments have been run in experimental labs using students as subjects • TARC has gone beyond this by using online experiments with large numbers of actual taxpayers • The results of the experiments are not supportive of the orthodox analysis • The experiment in which you participated will illustrate this

10. Winner • The lowest payoff was 122700 • The highest payoff in the experiment was 215000 • The winner of the prize is: Mark Phillips University of Southern California

11. Structure • You were enrolled randomly in one of two experiments • In one experiment Part A involved tax compliance • In the other experiment Part A involved an investment decision • For both experiments Part B tested attitude to risk • The tax experiment will be discussed first

12. Compliance Experiment • What does the model predict about behaviour? • For all sets of parameter it was the case that p < 1/(1 + F) • So the model predicts every participant should have been non-compliant • Non-compliance might vary between participants • But the optimal strategy to maximise expected income is to declarenothing

13. Compliance Experiment • The data do not match these predictions • 10 participants out of 50 declared honestly • Only 4 declared nothing every time (including me!) • Some participants were partially non-compliant • The choices are summarised in the histograms that follow

14. Compliance Experiment

15. Compliance Experiment

16. Investment Experiment • The investment experiment involved the allocation of saving • There was a risky asset and a safe asset • The payoffs were structured so that the risky asset was a better-than-fair bet • The optimal strategy to maximise expected income is to put everything into the risky asset • The histograms summarise the responses

17. Investment Experiment

18. Investment Experiment

19. Combination • Why did we run two versions of Part A? • The compliance experiment and the investment decision had the same payoffs • If tax compliance were just a gamble then the experiments should have the same choices • This was the reason for randomising participants and experiments • The comparison of histograms shows the pattern of choices are very different

20. Combination

21. Observations • These results are not explained by attitudes to risk

22. Observations • This experiment was first reported by Baldry in 1986 • It always works! • He concluded that tax compliance was not just a gamble • The comparison shows that the orthodox analysis is not correct • Recent research has explored how it should be revised • Some of this research is now reviewed

23. Opportunities Not all taxpayers have an opportunity to be non-compliant Employment income is usually subject to third-party reporting or withholding Self-employment opens the opportunity for non-compliance Occupational choice should be modelled The potentially non-compliant self-select into occupations where non-compliance is possible

24. Occupational Choice Self-employment can be successful (S) or unsuccessful (U) For optimal evasion, Ei*, the payoff from self-employment is EU = (1–q) EUu (Eu*) + qEUs (Es*) The choice of occupation is determined (partly) by risk aversion Low risk aversion implies self-employment and significant non-compliance

25. Behavioural Approach • The next issue is why be honest if it does not pay? • The problem that confronts modelling is how to maintain rationality but reach different conclusions • This issue has had to be addressed in many areas of economics • “Anomalies” are observed decisions that do not fit theoretical predictions • These have lead to the development of behavioural economics

26. Behavioural Approach • Behavioural economics can be seen as a loosening of modelling restrictions • Two different directions can be taken: (i) Revise the assumption about information underlying the decision (ii) Reconsider the private nature of the compliance decision • This allows additional factors to be incorporated in the evasion decision

27. Information • In the orthodox model the taxpayers use the objective probability of audit and know the fine • Two criticisms • The probability is not public information • The fine is not widely known • There is evidence that subjective beliefs about unknown variables inflate the probability of bad events

28. Non-Expected Utility • Let w1(p, 1 – p) and w2(p, 1 – p) be weighting functions that depend on p and 1 – p • More weight is given to the bad outcome so w1(p, 1 – p) > p • The general form of non-expected utility is V = w1(p, 1 – p)U(Yc) + w2(p, 1 – p)U(Ync) • The inflation of the probability will raise the rate of compliance

29. Alternatives • 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 focuses on uncertainty over the probability of outcomes

30. Social Customs Attitudes to compliance also matter Some taxpayers will always be fully compliant This can be explained by a social custom (an informal rule on behaviour) If the social custom is broken there is an additional loss of utility U if followed, U – S if broken S can also be interpreted as a psychological cost of non-compliance

31. Social Customs • Let S = mciEi where m is the proportion of population who are compliant • Choose either to be compliant with payoff UNE = U(Y[1– t]) • Or to be non-compliant with payoff UE = E[U] – mciEi • People with high ci (individual concern about custom) will be compliant Non-Compliant Compliant c 0

32. Social Interaction • How can we explain the formation of attitudes and beliefs? • Both can be the outcome of social interaction • This can be modelled using a social network that governs the interaction between individuals • Individuals meet with their contacts in the network and exchange information • Information affects compliance

33. Social Network A network is a symmetric matrix A of 0s and 1s (bi-directional links) The network shown is described by 1 2 3 4

34. Social Network Social networks can be studied using agent-based models We have done this to look at audit rules and predictive analytics Information transmission can sustain a subjective probability above the objective probability Attitudes can differ among occupational groups Compliance can be increased by fostering attitudes

35. Conclusions The talk was titled “Understanding individual tax compliance” When viewed as an individual decision the orthodox model makes incorrect predictions More accurate predictions can be made by understanding compliance as a social decision We need to take into account attitudes, beliefs, and opportunities

36. Conclusions Occupational choice links with risk aversion to self-select those willing to be non-compliant into a position where non-compliance is possible The process of social interaction is central to the formation of attitudes and beliefs A stronger social custom can give higher compliance Unknown audit rules force the formation of a subjective probability