Fiscal anarchy in the UK: Modelling poll tax noncompliance

Journal of Public Economics 64 (1997) 137–152

Fiscal anarchy in the UK: Modelling poll taxnoncompliance

a,b,c, c , d c , e*Timothy Besley , Ian Preston , Michael RidgeaLondon School of Economics, Houghton Street, London WC2A 2AE, UK

bNBER, Cambridge, MA 02138-5398, USAcInstitute for Fiscal Studies, London, UKdUniversity College London, London, UK

eBrunel University, London, UK

Received 1 July 1995; accepted 1 July 1996

Abstract

The UK’s experience with the poll tax reminds us that even in an economy with arelatively well developed detection and legal system, one cannot take tax compliance forgranted. The experience of the poll tax provides a unique opportunity to study manydimensions of tax compliance. We model nonpayment rates in a short panel of data on theEnglish local authorities. The transparent observability of liabilities makes reliablemeasurement of rates of nonpayment possible. Moreover, these rates rose to unprecedentedlevels as well as exhibiting considerable variation across authorities. This, together with thevariation in local taxes both between districts and over time, creates an ideal opportunity forempirical investigation. Our empirical specification allows us to investigate the determinantsof compliance as a function of authority characteristics using socioeconomic and othergeographical data. Moreover, the analysis takes seriously the possibility of neighbourhoodinfluences across authority boundaries. Our empirical results confirm the idea that highertaxes lead to larger nonpayment problems and that attempts to enforce compliance can havea positive effect. Political variables are also found to be associated with nonpayment rates.Evidence of influence from neighbouring jurisdictions is also found.

1. Introduction

In most modern fiscal systems, the problem of tax compliance is considered to

*Corresponding author.

0047-2727/97/$17.00 1997 Published by Elsevier Science S.A. All rights reservedPII S0047-2727( 96 )01625-8

138 T. Besley et al. / Journal of Public Economics 64 (1997) 137 –152

be a minor, albeit painful, source of irritation to tax authorities. On this count, theBritish public have historically been reasonably law abiding. However, after theThatcher government in the UK introduced a poll tax to replace a long-standingsystem of local property taxation, this ceased to be the case. A combination ofpolitical protest, perceptions of unfairness and substantial increases in average taxrates in the year of introduction undermined willingness to pay, with nonpaymentrising to well above fifty per cent in a number of areas. In fact the problem becameso severe, along with the social unrest manifested in the poll tax riots of 1990, thatabandonment of the tax was promised within the first year of its operation,following the replacement of Mrs. Thatcher as Prime Minister.

The poll tax (or ‘‘community charge’’, as it was formally known) wasintroduced in Scotland in 1989 and a year later in England and Wales, replacing a600 year old system of property taxation. The latter suffered from very littlenon-compliance. Poll tax payments were to be at a flat rate within each district,except for a limited number of income support recipients and special groups. Theunpopularity of the poll tax was aggravated by increases in average local tax ratesin the year of its introduction (Ridge and Smith, 1990). A widespread campaign ofnonpayment was initiated with the support of certain opposition Members ofParliament (one of whom served a jail sentence for nonpayment). There were riotsin central London in 1990 and by the end of the year opinion polls showed over

190% expressing discontent with the tax. A challenge to the Prime Minister inOctober 1990 led to an internal leadership election in which all candidatespromised abolition, at which point the demise of the tax was assured. Furthermore,the budget of April 1991 announced a shift in the burden of local finance fromlocal to central taxation, allowing a general reduction in the second years’ poll tax

2levels. Noncompliance with the discredited tax however continued to rise and itwas eventually replaced by a return to property taxation in April 1993.

This paper studies compliance with the UK poll tax. In light of the experience,this is the most striking dimension to understand. We model nonpayment rates in ashort panel of data on the English local authorities, each of which set its own polltax level. The transparent observability of liabilities makes reliable measurementof rates of nonpayment possible. Moreover, these rates rose to unprecedentedlevels as well as exhibiting considerable variation across authorities. This, togetherwith the variation in local taxes both between districts and over time, creates aninteresting opportunity for empirical investigation. We investigate the determinantsof compliance as a function of authority characteristics from census and othergeographical data.

1Market and Opinion Research International, 26 November 1990.2More precisely Value Added Tax was increased from 15% to 17.5% allowing an average cut of over

£110 in observed poll tax payments.

T. Besley et al. / Journal of Public Economics 64 (1997) 137 –152 139

We test a number of hypotheses concerning non-compliance. The first twofollow from standard economic reasoning. First, higher tax burdens should lead togreater non-compliance. Second, government activity to detect and sanctionnon-payers should reduce non-compliance. We also consider whether the extremeregressivity of the system led to greater non-compliance with the poll tax. Thisargument is based on inability rather than unwillingness to pay, and is tested byincluding the unemployment rate and other measures of economic hardship in thenon-compliance equation. Since the poll tax was a politically charged issue, wealso investigate the link between economics and politics in compliance. As Fig. 1shows, regions to the North and London to the South-East consistently showedgreatest non-compliance. It is in these areas that authorities controlled by theLabour Party are concentrated. Since poll tax non-compliance may have reflectedpolitical protest, we investigate the link between compliance and voting patterns.

3Finally, we test for the importance of neighbourhood effects on tax-compliance.This allows the non-compliance rate of geographically contiguous areas toinfluence the level of non-compliance. This is motivated empirically by the

4pronounced geographical patterns in the data as shown in Fig. 1. We argue belowthat such links can arise either because of regionally varying information about

Fig. 1. Poll tax noncompliance in England 1990/93.

3For recent applications of such models, see Case and Katz (1991) Case, Hines and Rosen (Case etal., 1993) and Besley and Case (1995).

4This choropleth map divides England into its shire counties, metropolitan counties and GreaterLondon.


costs and benefits of non-compliance, or by social attitudes reflecting guilt, shameand stigma having a spatially correlated component.

The UK poll tax experience is unique in many ways and, given the outcome, isunlikely to be repeated. However, while this paper might already be regarded aslargely a piece of economic history, there are some general lessons to be learned.First, our paper confirms that in spite of the turmoil created by the new system,predictions of the economic theory of tax compliance (and of crime moregenerally) are sustained. The results on neighbourhood effects reinforce thepotential importance of such issues in studying patterns of behaviour in crime anddelinquency (as originally argued by Case and Katz (1991)). The importance of thepolitical variables reminds us that understanding public attitudes is crucial tomodelling tax compliance.

The remainder of the paper is organized as follows. Section 2 develops thetheoretical and empirical framework for the analysis. Results are presented inSection 3, while Section 4 concludes.

2. Framework

This section develops relevant theoretical insights and uses these to suggest anempirical specification.

2.1. Theoretical models

The standard economic theory of tax compliance posits that individuals weighup the gamble of sanction for non-payment against the benefit from not paying the

5tax. In the case of the poll tax, the main difference is that poll tax nonpayment isan act of defiance rather than deceit. Taxpayers could not hide their liability exceptby hiding their existence or migrating to another authority. It is true that notregistering to vote in order to avoid payment of the tax became a stock anecdote

6during this period. Sanctions were probabilistic because the efficacy of andwillingness to invoke sanctions were uncertain. Non-compliance for those thatregistered was thus a gamble on prosecution rather than on detection, which oughtto have been close to automatic for most people.

Our first two testable hypotheses follow more or less automatically from a

5See the initial investigations of Allingham and Sandmo (1972) and Srinivasan (1973). The literaturein this spirit is nicely summarised in Cowell (1990).

6Smith and McLean (1994) provide evidence that this sort of behaviour was a reality.


7simple economic model of poll tax compliance —(a) that an increase in the tax tobe paid increases non-compliance and (b) increases in sanctions and/or penaltiesreduce non-compliance. These are core implications of the economic approach andhave been tested empirically by Clotfelter (1983), Witte and Woodbury (1983) andDubin and Wilde (1988) among others. We discuss some of their results in relationto ours below.

Our analysis goes beyond the standard framework by positing that individualsmay be influenced by others. There is a small literature which has considered thispreviously. For example, Cowell (1990) posits that individuals care about thestigma of non-compliance. In similar vein Erard and Feinstein (1994) haveconsidered the effect of guilt and shame on compliance. Pommerehne et al. (1994)also consider the importance of attitudes. In all of these cases, we would argue thattax compliance is susceptible to social influence. The amount of stigma that I feelif I do not comply may depend upon what my friends and neighbours think.Moreover, whether they also cheat on their tax payments may determine how I feelif I do not comply. Similar things are likely to be true of guilt and shame.

From a behavioural point of view, this can imply that individuals care about theamount of non-compliance in the community at large when choosing whether tocomply themselves. Our empirical analysis allows for spatial patterns in thenon-compliance data reflecting spatially correlated attitudes towards tax com-pliance. It also permits behavioural influence across geographical areas.

Individuals must also get their information about the consequences of notcomplying from somewhere. This is particularly true of the poll tax which was a

8new tax with a broader base of tax payers than previously. Erard and Feinstein(1994) have suggested that individuals may have different perceptions about thesanctions that they face which is consistent with individuals using differentinformation sets to make this judgment. We suppose that individuals can learn

7Consider a risk neutral individual who decides whether or not to comply with a poll tax demand. Hestands to gain t from non-compliance and will lose f if pursued for non-payment, where f .0incorporates any penalties for not paying on demand. Let q denote the probability of being prosecutedand forced to pay. To mirror the empirical reality that some fraction of individuals pay, while others donot, let u be the ‘‘cost’’ of behaving dishonestly which is assumed to be distributed in the populationaccording to the distribution function F(?). Then the extent of non-compliance is given by F(t2qf ). Itis very easy to see that non-compliance in the population is increasing in t and decreasing in f and q.While this model is only illustrative, similar results emerge under a broad range of assumptions. Inmodels with risk averse preferences changes in tax rates have income effects which can result inambiguous compliance responses, although the empirical results below suggest that we do not need toworry about this ambiguity in the present context. The structure of penalties can also be important butthe simplifying assumption of fixity seems reasonable for this case.

8Domestic rates were levied on the occupying head of household, while the poll tax demands weresent directly to all occupiers over the age of 18 (except for a small number of exempted groups).


about sanctions from others. This could be through media sources to whicheveryone has access, or else other sources of sharing information, such as casualcontact in pubs, work places etc.

The standard model of tax compliance would suggest estimating the relationshipbetween individual compliance behaviour, the level of the tax paid, measures ofthe government’s attempt to sanction non-compliance, and other relevant in-dividual characteristics, such as income, education etc. There is a literature whichhas done this, for the US income tax, to which we referred above.

There are two reasons to depart from this here. First, this model takes noaccount of the kind of interdependent behaviour due to social phenomena orlearning about sanctions. Second, we do not have access to data on individualnon-compliance. All of our data is at the level of the local authority. We treat eachof these issues in turn.

To model interdependent behaviour, we permit the level of non-compliance todepend upon others’ behaviour within a region. This raises issues of appropriatemethods of econometric analysis, which we will discuss below. For example, ifinfluence is mutual, then the amount of non-compliance of others is determinedsimultaneously with your own non-compliance. There is also a fundamentalidentification problem—if behaviour is similar in localities, then it could reflectgenuine behavioural interdependence or could just reflect omitted factors that are acommon influence on all individuals in the locality. We discuss some possibleprocedures for dealing with this below in the context of the model developed here.

The nature of our data forces us to work with decisions to comply aggregated atthe district level. Thus our left hand side variable is the mean rate of non-compliance in a district at a particular date. As in the canonical model of taxcompliance, we make this a function of the poll tax level and various measures ofpolicy towards non-compliers, detailed below. Interdependence in non-compliancebehaviour within districts cannot be captured given the aggregate data. However, itis possible that some of the neighbourhood effects spill over district boundaries.This seems particularly plausible in some of the more densely populated urbanareas where geographical districts are relatively small. However, if access tocommon media sources is important, this could also result in geographical effectsin the data across other districts. Thus, we posit a model in which non-compliancein an area can be a function of non-compliance in geographically contiguous areasas well as other ‘‘more standard’’ variables. The econometric problems that wediscussed above will still arise if interdependent behaviour is determined in somegrand social equilibrium where neighbours behaviour is endogenous. Geographic-ally correlated district level shocks will also be an issue, as discussed above.

The basic theory of tax compliance takes government behaviour as given.However, this is unreasonable. The level of taxation and policing activity are allparts of conscious government policy decisions. High rates of non-compliancemay necessitate high revenues to offset lower tax take and increased levels ofgovernment activity to police non-compliance. This has implications for empirical


studies like ours and was recognised in previous empirical work by Dubin andWilde (1988). We discuss our own procedure for dealing with this below.

2.2. Empirical specification

The model is estimated using aggregate data on the local authorities in England,which include the London Boroughs, metropolitan districts and shire districts inEngland. The data are derived from a number of official sources, full details ofwhich are available in Appendix A.

The theory suggested that important variables would be local authorities’non-compliance rates, levels of the poll tax, levels of collection effort, fines andauthority characteristics including incomes. To define compliance rates empirical-ly, we use the ratio of revenues received within the year of demand to total

9collectable revenue . Subtracting this from one gives a measure for which highervalues represent a greater extent of noncompliance. There are two possible sourcesof deviation of this from the theoretical ideal. First, some individuals not havingpaid at the year end may still intend paying, and secondly, some individualsincluded as non-delinquent may have paid only because they were successfullyprosecuted within the year. Notwithstanding, our measure is sufficiently close tothe theory to make studying it worthwhile. Data on poll tax levels are readilyavailable.

10Enforcement of payment for delinquents was a lengthy procedure and gives avariety of data on collection effort. We make use of the numbers of reminders,summonses and calls for bailiffs within the year. Including enforcement in theanalysis reduces the sample considerably, since some authorities failed to respondto the data collecting agency’s requests on this point. This may generate a sampleselection bias which we discuss further below. Fines were equal to the cost of thesummons and therefore varied little across authorities and are excluded from ourempirical analysis.

Our basic empirical specification for poll tax non-compliance within anauthority is

X ; b 1 b X 1 b t 1 b e 1 b z 1 b z 1 n 1 n (1)jt 0t 1 2jt 2 jt 3 jt 4 1jt 5 2j j jt

Here X denotes the ln odds transformation of the noncompliance rate in authorityjt

9The measure of collectable revenue allows exemptions due to low income, incarceration,membership of a religious order and so on.

10The sequence of enforcement was as follows. Initially reminders were sent. If these were ignorednoncompliers were summonsed to appear in court, and if individuals did not then make payment in full(plus the cost of the summons) they then received a liability order forcing them to pay their arrears in aprescribed form. This could be a monthly arrangement, an attachment of earnings or benefits, or so on.If any of these methods failed then bailiffs were called upon to visit and recover property equal to thevalue of the arrears.


j in period t, chosen to allow the dependent variable to vary across the whole realline. The poll tax level is t and the enforcement effort is e . Authorityjt jt

characteristics are divided into a set z which vary over time and a set z which1jt 2j

do not (at least in the available data). The former comprise district levelunemployment rate and political variables, including both shares of local votes anddummies for party control. The latter include data on demographic and housingcharacteristics. The basic theory of tax compliance outlined above suggests thatb , b .0. Note that since there is no observed variation over time or authorities in2 3

the level of fines, we have therefore absorbed them into the intercept term. Thevariable X denotes the geographically contiguous neighbours’ non-compliance2jt

rate (again in ln odds transformation). We argued above that we would expectb .0. The effects of unobserved authority characteristics enter through the final1

terms v and n . The first of these, v , is treated as an authority specific fixed effectj jt j

and the second, n , as a time-varying authority specific shock that is uncorrelatedjt

over time. It is possible that n is correlated across jurisdictions to reflect commonjt

economic and attitudinal shocks which are spatially specific.The major problem with the above specification is that the right hand side

variables may be jointly determined with non-compliance. For example, au-thorities’ need to balance their budgets implies that the level of the poll tax isinfluenced by both past and anticipated noncompliance. In this case, the poll taxlevel is endogenous. Similarly, enforcement is also a policy instrument which will

11be affected by the extent of noncompliance. There are also good reasons tosuppose that the neighbours’ non-compliance rate is endogenous since anyinfluence ought to be reciprocal. The existence of spatially correlated shocks to theerrors would also imply that X were correlated with n . In both of these cases,2jt jt

neighbours’ exogenous right-hand side variables should serve as convenientinstruments (see, for example, Case and Katz, 1991). All of these result incorrelation between the fixed effects y and right-hand side variables in Eq. (1),j

leading to bias in OLS estimates.To deal with this problem we use instrumental variables. Taking first differences

in Eq. (1) eliminates the fixed effects together with all time-invariant variables,yielding an equation

DX 5 Db 1 b DX 1 b Dt 1 b De 1 b Dz 1 Dn (2)jt 0t 1 2jt 2 jt 3 jt 4 1jt jt

This equation can be estimated allowing for simultaneity by using the momentrestrictions

E(Dn W ) 5 0 (3)jt jt2k

for appropriate instruments W , weighting the instruments to give the GMMjt2k

11One could even argue that political outcomes could be endogenous.


12estimator suggested by Arellano and Bond (1991) . To do so requires choice ofinstruments W and lag length k. We believe that good candidates are the fixedjt

13socioeconomic characteristics , and lagged and current values of unemployment14rates and political variables . Sufficiently lagged values of endogenous variables

can also be used and twice-lagged values are admissible under the assumption that15

n is uncorrelated over time. Variables treated as potentially endogenous are polljt

tax rates, enforcement variables and neighbours’ nonpayment rates.

3. Results

OLS estimates of Eq. (1) in Table 1 provide a useful benchmark, andforeshadow the later results. The first columns contain poll tax, unemployment and

16political variables as regressors . There is a strong correlation of nonpaymentrates with the poll tax as predicted above, a basic precept of a simple economic

17model. The strong correlation with unemployment may be taken as an indicationof the possible payment difficulties that some individuals faced. It also mirrors aresult for US compliance with the income tax due to Dubin and Wilde (1988).

The pattern of signs on electoral variables is a consistent feature of these andlater regressions. Nonpayment is negatively associated with Conservative share ofvotes, given control of the authority. However, for a given voting pattern,Conservative control appears to encourage noncompliance. While at first sight,these results might appear contradictory, there is a straightforward and plausibleinterpretation. A greater Conservative vote being associated with lower non-compliance reflects a less negative attitude towards the poll tax among thesevoters. Greater non-compliance in Conservative-controlled authorities may arise

12We report the one step rather than two step GMM estimates because of the greater reliability ofstandard errors in small samples-see Arellano and Bond (1991).

13These are described in full in Appendix A and include indicators of housing quality, urbanisation,long-term unemployment, mortality, age and class structure.

14We have also calculated estimates, not reported here, treating political variables as endogenousalong with tax levels and enforcement variables. The main consequence is a weakening of thesignificance of the poll tax variable.

15One could even use once-lagged values of variables for which any feedback from n happens onlyjt

with a lag.16This and all subsequent regressions are estimated using year dummies.17Given the average non-compliance, multiplication of these coefficients by 0.2 gives a rough

estimate of marginal effects on the untransformed nonpayment rate. For example, a coefficient of 3.517implies that a 100 increase in poll tax would lead to about a 7% rise in nonpayment. The existingempirical literature on tax compliance has studied how reporting of income varies with tax ratescontrolling for other influences. In this spirit, Poterba (1987) studies the response of capital gains taxesto changes in tax rates using US data from 1965–82, finding an elasticity of evasion of about 0.37. Thisis similar to findings of other studies of the US such as Clotfelter (1983).


Table 1OLS on Levels. Dependent variable: Nonpayment rate (ln odds)

Poll Tax 3.517 3.798 4.305(14.92) (13.00) (16.50)

Unemployment 22.62 23.32 6.49rate (27.33) (19.37) (3.45)Conservative 0.046 0.073 0.091control (1.36) (1.88) (2.81)Conservative 20.537 20.533 20.263seat share (7.45) (5.80) (3.25)Reminders 20.169 20.154per person (3.17) (3.12)Summonses 0.645 0.062per person (3.20) (0.34)Calls to bailiffs 20.646 20.582per person (2.04) (2.23)Accommodation 5.542not self- (3.14)containedAccommodation 1.154crowded (1.84)Priority need 34.08cases (3.07)Urbanisation 20.001

(3.38)Mortality ratio 0.007

(5.02)Under 30 3.45

(4.67)Over 60 2.57

(3.92)Professional or -1.457clerical (6.831)Long term 0.803unemployment (2.19)

2R 0.701 0.693 0.779Standard error 0.295 0.289 0.247Sample size 1055 706 706

Standard errors corrected for heteroscedasticity. Year dummies included in all equations.

from greater use of non-compliance in such cases as a means of political protestagainst the Conservative party who introduced the tax.

Later columns also include enforcement variables, with a consequent fall in18sample size. The number of reminders does seem to affect the non-compliance

18We have checked for evidence of any sample selection bias by re-estimating equations excludingenforcement variables on the smaller sample. Results, available on request, are not sufficiently differentto cause concern.


rate in the direction suggested by the theory. Summonses enter perversely in thesecond column but insignificantly in the final column. There is some evidence ofan effect from calls to bailiffs.

The final column adds available (fixed) socioeconomic characteristics in anattempt to correct as far as possible for any fixed effects. Characteristics reflectinglocal deprivation, such as the amount of non-self contained and crowdedaccommodation, are associated with nonpayment, further underlining the possiblepayment difficulties that the unemployment variable represents.

Within-groups estimates allow for a complete set of authority fixed effects andare reported in Table 2. Estimated tax and unemployment effects remainsignificant as do the political variables. We now obtain stronger evidence thatenforcement is important, with summonses now having the expected sign.

Table 3 reports instrumented estimates and incorporates neighbourhood effectsby adding the average values of non-compliance rates from neighbouring localauthorities. The first column uses only the instruments regarded as strictlyexogenous. Strong effects continue to come through from poll tax level and issueof reminders. The size of the poll tax coefficient falls somewhat while that onreminders increases. However the broad pattern of effects is similar to the previousresults. There is also some weaker evidence of a role for political variables. Inboth columns neighbours’ non-compliance rates are positively associated with ownnon-compliance rate. Thus the empirical results confirm the view that neigh-bouring authorities exercise influence on non-compliance. The second columnadds twice-lagged values of own and neighbours’ potentially endogenous variables

Table 2Within-Groups Estimates. Dependent variable: Nonpayment rate (ln odds)

Poll Tax 3.441(9.68)

Unemployment 6.51rate (2.99)Conservative 0.121control (3.12)Conservative 20.501seat share (3.29)Reminders 20.138per person (3.62)Summonses 20.210per person (1.40)Calls to bailiffs 20.331per person (1.78)

2R 0.943Standard error 0.165Sample size 706

Standard errors corrected for heteroscedasticity. Year dummies included in all equations.


Table 3IV, First Differences with Neighbourhood Effects. Dependent variable: Change in nonpayment rate (lnodds)

Poll Tax 2.486 2.418(3.80) (3.85)

Neighbours 0.590 0.599nonpayment (5.06) (5.34)Unemployment 5.529 5.505rate (1.64) (1.65)Conservative 0.085 0.088control (1.55) (1.60)Conservative 20.450 20.454seat share (2.04) (2.08)Reminders 20.269 20.269per person (2.42) (2.51)Summonses 0.232 0.271per person (0.76) (0.93)Calls to bailiffs 20.200 0.095per person (0.43) (0.21)Sargan test 99.79 (94 df) 114.04 (104 df)

p50.322 p50.235Sample size 306 306

Instruments used:Nonpayment rate, poll tax Not used Lagged twiceand enforcement variablesUnemployment, politics and Current and Current andsocioeconomic variables lagged lagged

Year dummies included in all equations.

to the instruments. The results in this case are broadly similar. Moreover Sargan’s19test of the over-identifying restrictions fails to reject at the 5% level in either

20column.To summarise: these results indicate robust effects on non-compliance of (i) the

poll tax level, (ii) compliance effort measured by reminders per person, (iii)various measures of economic hardship such as the unemployment rate and (iv)geographical neighbours’ non-compliance rates. These findings appear robust to

19See Sargan (Sargan, 1958, 1988) or Arellano and Bond (1991) for a description of the test. Wereport the two step Sargan test since ‘‘no robust chi-square Sargan test based on one-step estimates isavailable (Arellano and Bond, op cit, p. 282)’’.

20F-tests for the significance of the identifying instruments in the first stage regressions are reportedin Appendix B. The instruments are at their weakest in predicting reminders but even there the F test isabove unity (see Bound, Jaeger and Baker (Bound et al., 1995)).


concerns about some of these variables being endogenous, with our instrumentspassing Sargan’s overidentification test for this model.

4. Conclusion

This paper has exploited the UK poll tax experience to investigate a number oftax-compliance issues. The empirical results suggest four main determinants ofnon-compliance. Higher taxing authorities did face higher rates of non-compliance.In addition, the effect of enforcement also appears as the economic theory of taxcompliance would suggest. Thus our paper adds to the body of evidence thateconomic models of crime have value in understanding real world decisions.

The results also emphasise that economic hardship may have been a factor inpoll tax non-compliance, with indicators of unemployment having a consistentlypositive effect on non-compliance. This confirms a standard view of the difficultyof using a head tax to raise revenues.

The results on political control are consistent with the story that political protestcoloured the response to the poll tax. The act of defiance involved in non-paymentwas a kind of civil disobedience response to the unfairness of the tax. In areas witha high Conservative vote we find evidence that such acts were less widespread.Conditional on the size of vote, we find however that Conservative control mayhave encouraged protest. This is an interesting political economy issue, whichreminds us of the difficulties of getting individuals to comply with a tax that isdeemed to be unjust.

Finally, we found evidence of influence from neighbouring jurisdictions. This isconsonant with models of learning and social influences such as guilt, shame andstigma. While, the UK poll tax experience was an extreme case, such effects maywell be present in many other settings where tax compliance is an issue.

Acknowledgments

We are grateful for comments from Richard Blundell, Stephen Bond, KevinDenny, Richard Disney, Roger Gordon, Edward Gramlich, Michael Keen, CostasMeghir, Wallace Oates, Michael Rothschild, Stephen Smith, Tony Travers,numerous seminar participants and two anonymous referees. Martin O’Hare andDamon Clark both provided research assistance. The research was carried out aspart of the Economic and Social Research Council Research Centre for theMicroeconomic Analysis of Fiscal Policy at IFS. Responsibility for any opinionsexpressed rests solely with the authors.


Appendix A

Data

We are grateful to the following for access to data: Department of theEnvironment (DoE), Chartered Institute of Professional Finance Accountants(CIPFA), Office of Population Census Surveys (OPCS), Local GovernmentChronicle Elections Centre (LGCEC), Ordnance Survey (OS).

• Non-payment rates: (DoE, CIPFA) Our measures of non-payment rates takethe ratios of revenues received within the year of demand (DoE) to collectionfund income (CIPFA). Collection fund income is a measure of collectablerevenue based on the number of individuals registered by the local authority.Our measure therefore fails to pick up non-compliance through non-registra-tion. Other weaknesses are discussed in the main text.

• Poll tax levels: (DoE) These are actual poll tax levels set by local authorities.• Enforcement effort: (CIPFA) We have good data on enforcement effort for

some authorities only. The gaps could be endogenous (in that those authoritiesnot responding to CIPFA might be atypical in terms of non-payment rates) butwe have found little evidence that this is so. The sequence of enforcement isissue of reminder, followed by summons to attend at court. Conviction leads toa liability order. A call to bailiffs is a final option for recalcitrant nonpayers.

• Politics: (LGCEC) Data on voting and on political control come from the LocalGovernment Election Centre at the University of Plymouth to whom we aregrateful.

• Socioeconomic and Other Characteristics: (OPCS, DoE) ‘‘Accommodationnot self-contained’’ is the proportion of 1992 household residents living inaccommodation which is not self-contained or is not permanent. ‘‘Accommoda-tion crowded’’ is the proportion of 1992 household residents living inaccommodation with more than one person per room. ‘‘Priority need cases’’ isthe average number of households of more than one person accepted as inpriority need for securing permanent accommodation under the 1985 HousingAct divided by the total 1992 resident population, averaged over the years1990/91 to 1992/93. ‘‘Mortality ratio’’ is for persons under 75 years of ageand is averaged over the period 1990 to 1992. ‘‘Long term unemployment’’ isproportion of persons unemployed who have been unemployed for more thanone year, averaged over July 1990 to April 1993. ‘‘Unemployment rate’’ isproportion of the resident population unemployed. ‘‘Under 30’’ and ‘‘Over 60’’are proportions of persons in those age ranges in the 1991 Census. ‘‘Profession-al and clerical’’ is the proportion of households headed by persons in Registrar


General’s classes I and II in the 1991 Census. ‘‘Urbanisation’’ is proportion ofpersons living in towns of population greater than 20000 in the 1991 Census.

• Neighbourhood effects: (OS) Authorities are treated as neighbouring if sharinga boundary.

• Exclusions: Our data initially cover the 366 English local authorities. Weexclude as evidently idiosyncratic the City of London and Isles of Scilly (ongrounds of small size of resident population) and Wandsworth (which set a zeropoll tax in 1991 and 1992, financing all spending through central grants).Authorities are also dropped where data is missing or obviously outlying andthere is doubt as to the veracity of the data.

Appendix B

Table A.1 Means of variables

Variable Sample Mean Standardsize Deviation

Nonpayment rate 1055 0.280 0.106Poll tax 1077 0.280 0.071Unemployment rate 1077 0.033 0.016Reminders per person 745 0.583 0.264Summonses per person 756 0.152 0.074Calls to bailiffs per person 732 0.038 0.038Conservative control 1080 0.275 0.447Conservative seatshare 1077 0.371 0.217Accommodation not self-contained 365 0.010 0.008Accommodation crowded 365 0.039 0.026Priority need cases 365 0.002 0.001Urbanisation 364 64.7 34.3Mortality ratio 365 95.53- 14.274

7

Under 30 365 0.407 .038Over 60 365 0.213 .038Professional and Clerical 365 0.400 .088Long term unemployment 365 0.247 0.058

Table A.2 First stage F-tests

Variable F(99, 202) F(109, 192)

Poll tax 2.193 2.223p50.000 p50.000

Neighbours nonpayment rate 3.773 3.607


p50.000 p50.000Reminders per person 1.097 1.121

p50.248 p50.245Summonses per person 1.241 1.126

p50.240 p50.236Calls to bailiffs per person 1.282 1.450

p50.014 p50.013

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Documents

Fiscal anarchy in the UK: Modelling poll tax noncompliance