WHO PAYS THE GASOLINE TAX?

WHO PAYS THE GASOLINE TAX?

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WHO PAYS THEGASOLINE TAX?HOWARD CHERNICK * &ANDREW RESCHOVSKY **

Abstract - The regressivity of thegasoline tax and other consumptiontaxes has been challenged on thegrounds that the use of annual asopposed to lifetime income andconsumption data leads to a substantialoverestimate of regressivity. Rather thanrely on proxies for lifetime income, inthis paper panel data on gasolineconsumption and income are used tomeasure incidence over an intermediatetime period. When people are groupedinto 11-year average income deciles,average gasoline tax burdens are onlyslightly less regressive than annualburdens. The main reason for thesimilarity of annual and intermediate-run burdens is the limited degree ofincome mobility over an 11-year period.

INTRODUCTION

The taxation of gasoline is a highlycontentious issue in the United States.Despite the fact that the combinedfederal and state tax rate on gasoline in

the United States is approximately one-fifth of the average rate in WesternEurope, any attempt to increase the taxrate is met with strong opposition. In1993, a grueling political battle had tobe fought in order to raise the federalgasoline excise tax rate by four cents pergallon.

The fierce opposition to gas taxes existsdespite the view held by many econo-mists and policy analysts that theexpanded use of gasoline excise taxes isan appropriate response to automobilecongestion and a suitable tool forreducing air pollution and alleviatingglobal warming attributable to vehicularcarbon emissions. The opposition to thegas tax on the part of politicians and thegeneral public appears to arise from thewidely held perception that the tax isunfair because it is regressive, imposinga greater economic burden on the poorthan on higher-income families, andhorizontally inequitable, unduly penaliz-ing some regions of the country overothers.

The evidence for the regressivity ofexcise taxes comes primarily from cross-sectional surveys, which show that low-income families spend a larger propor-tion of their annual income on gasolinethan do high-income families. Recently,

*Department of Economics, Hunter College and

the Graduate Center, City University of New York,

New York, NY 10021.**Robert M. La Follette Institute of Public Affairs and

Department of Agricultural and Applied Economics,

University of Wisconsin–Madison, Madison, WI 53706.

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the regressivity of the gasoline tax hasbeen challenged by a number ofeconomists who have argued that it isinappropriate to determine tax incidenceon the basis of income data from asingle year.1 Their argument, which isbased on Friedman’s (1957) permanentincome theory of consumption and thecompanion life-cycle model of saving(Ando and Modigliani, 1963), is that, ifmost people with low incomes are onlytemporarily poor and if gasolineconsumption decisions tend to be madeon the basis of lifetime incomes,calculating tax burdens based on datafrom a single year will yield tax burdensfor low-income people that are substan-tially higher than burdens calculated onthe basis of lifetime or permanentincome.

Although the argument that theregressivity of consumption taxes isoverstated when incidence calculationsare based on annual income is widelyaccepted, until recently it has comeunder little empirical scrutiny. Therehave been only a handful of studies thathave employed alternative measures ofincome in calculating the incidence ofconsumption taxes. Almost all of thesestudies have approached the question oftax incidence from a lifetime perspec-tive, employing various approaches forthe calculation of lifetime income.

One approach, employed by Davies,St.-Hilaire, and Whalley (1991), usescross-sectional data and imposesassumptions about income mobility tosimulate lifetime income. A secondapproach, exemplified by Lyon andSchwab (1995), Caspersen and Metcalf(1994), and Rogers (1995), uses limitedpanel data to estimate lifetime income.Lyon and Schwab combine theseestimates with panel data on alcoholand cigarette consumption, in order tocalculate long-run excise tax burdens.

Caspersen and Metcalf, and Rogers, useconsumption data for a single year tocalculate annual tax burdens relative tolifetime income, for the value-added taxand for gasoline, alcohol, and tobaccotaxes, respectively.

Yet another approach, taken by Poterba(1989, 1991a), Metcalf (1994), and theU.S. Congressional Budget Office(1990), is based on the argument that,as long as consumption is a constantfraction of lifetime income, annualconsumption expenditures provide agood proxy for lifetime income. Thesestudies, consequently, use total con-sumption data in a single year as a basisfor their tax incidence calculations.Finally, Fullerton and Rogers (1991,1993) calculate lifetime tax burdens byestimating lifetime income in thecontext of a large overlapping-genera-tions computable general-equilibriummodel.

A general conclusion that arises fromthese empirical studies is that consump-tion-based taxes are less regressivewhen incidence calculations are basedon lifetime as opposed to annualincome. In his studies of the gasolinetax, Poterba (1989, 1991a) concludesthat the gasoline tax is actually slightlyprogressive over the bottom half of theincome distribution. Rogers (1995) findsthat relative to lifetime income, gasolinetax burdens rise over the bottom threelifetime income quintiles and fallthereafter. Finally, the U.S. Congres-sional Budget Office (1990) finds that atax on motor fuels, while regressiverelative to annual income, is generallyproportional relative to total expendi-tures. We can thus summarize theliterature to date as concluding that theuse of annual income in the calculationof gasoline tax burdens creates asubstantial annual income bias in thedirection of increased regressivity.


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While, on theoretical grounds, the useof lifetime incidence is highly appealing,there are a number of quite seriouspractical and conceptual problems withthis approach to tax incidence. Theseproblems diminish the usefulness of thelifetime approach and suggest thatpolicy conclusions based on the analysisof lifetime tax burdens should betreated with great caution. The basicproblem is that we cannot directlyobserve an individual’s lifetime income.Any estimation of lifetime income isthus, by necessity, difficult to carry outand requires a large number of restric-tive assumptions. To illustrate, thefoundation for Fullerton and Rogers’measure of lifetime income (Fullertonand Rogers, 1993) is an estimated age-earnings profile for a sample of house-holds from the Panel Study of IncomeDynamics (PSID). One problem with thisapproach is that forecasting lifetimeincome based on incomplete earningsexperience can lead to substantialerrors. As discussed by Moss (1978), anyobserved age-earnings profile representsa combination of a cohort effect, anaggregate growth effect, and anindividual age-earnings profile. Forecasterrors for any of these three compo-nents can lead to a substantial error inpredicting lifetime income. For example,Barthold (1993) points out that if age-earning profiles had been based on datafrom the 1960s, one would haveprojected rapidly rising real wages foryoung workers throughout the 1970sand 1980s, while in fact, real wagesgrew very slowly during this period.

Another problem with existing estimatesof lifetime income is that they tend torely on data from quite restricted sets ofhouseholds. For example, both Fullertonand Rogers (1991, 1993) and Lyon andSchwab (1995) base their incomeestimates on a sample of individualsfrom the PSID who were continuously

heads of households over 18- and 20-year periods, respectively. By excludingfemale-headed households, in the caseof Lyon and Schwab, and maritallyunstable households, in the case ofFullerton and Rogers, these sampleselection rules result in samples that arenot representative of the U.S. popula-tion. This is not a minor problem,because nearly 40 percent of thewomen in the first wave of the PSIDlived in a female-headed household inone or more years of the sample period,and the average income of thesewomen was about one-half of theincome of the women who were inmale-headed families. Moreover, divorceor separation is a primary route intopoverty for many women and children.Thus, this type of sample selection rulemay bias estimates of lifetime income,because individuals included in thesample are likely to have steeper age-earnings profiles than those who areexcluded.

The use of total annual expenditures asa proxy for lifetime income is alsoseriously flawed. Like annual income,consumption expenditures vary overtime for transitory reasons. Just as anegative transitory component ofincome could bias upward the measureof tax burdens relative to annualincome, the presence of a positivetransitory component of consumptioncould bias tax burdens downward. Forexample, an unexpected illness thatrequires substantial out-of-pocketmedical expenses will inappropriately bereflected in the measure of lifetimeincome, resulting in a downward bias inmeasured tax burdens. Liquidityconstraints are another factor that mayweaken the link between annualconsumption expenditures and lifetimeincome. For those who are unable toborrow against future income, changesin consumption are more likely to track


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changes in annual income than changesin lifetime income. Zeldes (1989)identifies those with low levels of liquidassets as most likely to be liquidityconstrained, and finds that this grouptends to consume more food in re-sponse to increases in income thanwould be predicted by the permanentincome–life-cycle model. Wilcox (1989)presents aggregate evidence that evenwell-publicized increases in socialsecurity benefits lead to greater in-creases in consumption at the time theyare received than one would expectfrom the life-cycle model. Conceptually,those with borrowing constraints couldstill smooth consumption out of savings.However, the identification of liquidity-constrained consumption behavior withthe lack of fungible wealth suggeststhat such individuals have been unableto save out of past income. If liquidityconstraints affected only a small portionof the population, they might not beimportant to the consumption-lifetimeincome issue. However, the low level ofwealth in at least the bottom twoquintiles of the income distributionsuggests that substantial numbers ofpeople are likely to face such constraints(Wolff, 1994). In sum, for a substantialfraction of the population, annualconsumption is likely to be a poor proxyfor lifetime income.

The use of lifetime income as a founda-tion for tax incidence analysis implicitlyminimizes the difficulties some individu-als face in consumption smoothing. Onthe other hand, the use of annualincome as the basis for tax incidencecalculations tends to overstate the taxburdens faced by some taxpayers withlow annual incomes, because it fails toaccount for the ability of many taxpay-ers to augment current income bydissaving or by borrowing. One reasonwhy policymakers may reject measuresof lifetime tax incidence is that they

recognize that many taxpayers, especiallythose with low and moderate incomes,face substantial liquidity constraints, andthus find it impossible to use expectedhigher incomes as a basis for borrowingmoney to pay current taxes.

Finally, the assertion that total consump-tion is a good proxy for lifetime income,and hence a good measure of ability topay, is predicated on the assumptionthat, over the course of a lifetime, allincome is consumed. This assumptionwill hold, however, only if individualsmake no bequests. Although researchon bequests is limited, a careful study byMenchik and David (1982) providesevidence that bequests are a rising shareof lifetime income as income rises. Thus,the failure to categorize bequests andgifts as consumption expenditure willoverstate the measured progressivity ofconsumption taxes.

In this paper, we propose an alternativemeasure of tax incidence that provides apractical compromise between twoextremes—the use of annual incomeand lifetime income. Our approachrecognizes both the potential problemsinherent in the use of data from a singleyear and the difficulties in developingaccurate estimates of lifetime income.We calculate intermediate-run taxburdens based on 11 years of data onboth income and gasoline consumption.The choice of 11, instead of an alterna-tive number of years, is attributableprimarily to the fact that 11 years is themaximum period over which high-quality longitudinal data are available onboth income and gasoline consumption.Nevertheless, we shall argue that thisintermediate-run period provides apractical compromise between annualand lifetime tax incidence measures.

Individuals who have low incomes inany given year fall into one of three


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groups: those with persistently lowincomes over a substantial number ofyears; those who have temporarily lowincomes for transitory reasons, such asunemployment or illness; and thosewho have temporarily low incomes forlife-cycle reasons, for example, becausethey are students or retired elderly. As aconsequence, classification on the basisof 11 years of income will provide amore accurate picture of long-termincome for some groups than for others.

Only for the first group, the persistentlypoor, will tax burdens calculated usingannual income and consumption dataprovide a reasonably accurate indicatorof longer-run burdens. For all those whodo not have persistently low incomes,tax burdens based on annual incomeand consumption data will be biased inthe direction of regressivity.

Calculating intermediate-run taxburdens should eliminate any annualincome bias in the burden calculationsfor those who have low incomesbecause of transitory variations inincome. Whether the use of 11 years ofdata is sufficient to eliminate bias in thecalculation of tax burdens for individualswhose income varies over time for life-cycle reasons is open to question.Although 11 years will span about aquarter of an individual’s working life,this period may not be sufficient to fullycapture changes in economic statusresulting from movements along someindividuals’ age-earnings profiles.However, recent evidence on growingwage inequality and stagnant real wagegrowth for many Americans suggeststhat, for many individuals, especiallythose with a low level of education andtraining, age-earning profiles may bequite flat. For example, the median realearnings of all men who were 30 yearsold in 1972 rose by only 11 percent inthe following 20 years, with most of

that growth occurring in the first decade(Levy, 1995). Thus, for an increasinglylarge number of individuals who haverelatively flat age-earnings profiles, 11years of income data may well provide agood estimate of their longer-runincome.

However, for those with high lifetimeearnings, age-earnings trajectories havebeen rather steep (Fullerton and Rogers,1993). For some, especially those withgraduate and professional degrees, theslope of the age-income profile mayhave actually increased. While a decadeor so of income information will providean appropriate foundation for calculat-ing intermediate-run tax burdens, forthese individuals, a longer period of in-come data would be required to providean accurate estimate of lifetime income.

This discussion suggests that incomemobility, broadly defined to include bothtemporary changes in economic positionand longer-run movements along age-income profiles, will be crucial toassessing the bias toward regressivityoccurring because of the use of annualincome data.

In this paper, we explore the relationshipbetween income mobility and taxincidence. We examine both theproportion of individuals who areeconomically mobile and the differencesin tax burdens calculated using annualand 11-year income data, for bothmobile and immobile individuals. Thenext section of the paper describes thedata and methodology used in thisstudy. We then present the gasoline taxincidence results for alternate incomemeasures and provide an interpretationof the results, focusing on the impor-tance of income mobility in determiningtax incidence. We also briefly addressthe issue of compensating low-incomefamilies for gasoline tax increases.


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METHODOLOGY

The primary source of data for comput-ing the intermediate-run burden of thegasoline tax is the PSID. The PSID is alarge longitudinal survey that hasfollowed the members of over 5,000families since 1968. The high quality ofthe income data and the availability ofsome longitudinal consumption datamake the PSID the best available dataset for examining long-term tax bur-dens.2 Our sampling frame consists ofall family heads and spouses who werein the PSID in 1982. For most of ouranalysis, the sample is an 11-year panelconstructed by following the 1982sample backward to 1976 and forwardto 1986. The sample consists of 10,906individuals. Making the individual theunit of analysis avoids severe sampleselection problems inherent in thechoice of a sample based on headshipor on marital status. Because changes infamily composition are major determi-nants of changes in income (Bane andEllwood, 1986), it is important thatinclusion or exclusion from the samplenot be conditional on such changes.3

Our sampling strategy is designed tomake our results comparable to annualincidence studies based on cross-sectional data sets such as the CurrentPopulation Survey. It duplicates theannual approach by choosing a sampleat a point in time, computing annualincidence in that year, and then compar-ing the results to a measure of interme-diate-run incidence by following thesample backward and forward overtime. This approach contrasts with thestrategy followed by a number of otherincidence studies, which compareindividuals’ economic positions in aninitial period to their economic positionsin some future year or years.4 We choseour approach because, from a tax-incidence perspective, we want the best

possible measure of longer-run ability topay for a given annual distribution ofincome. Particularly for those individualswho are liquidity constrained in theirability to consume, a measure of longer-run income based on expected (oractual) future income does not provideas good an estimate of the ability to paytaxes as a measure that combines pastand future income.

Although tax burdens are calculatedover an entire income distribution, mostpolitical discussions of consumptiontaxes focus on the degree of regressivityat the bottom end of the distribution. Ifa family is poor in the current year andin the midst of an extended spell ofpoverty, its economic well-being and itsability to pay taxes are presumed to belower than the well-being and tax-paying ability of a family that hasrecently fallen into poverty. The litera-ture on spells of poverty has emphasizedthe distinction between those who arepoor at a given point in time and thosewho ever become poor (Bane andEllwood, 1986). While many of thosewho will ever become poor will experi-ence only a short spell of poverty, ofthose in poverty in any given year, asubstantial fraction (over 50 percent inBane and Ellwood’s work) are in themidst of a long spell of poverty. Censor-ing of the sample, either from the left(prior to the observation period) or theright, can give a misleading picture ofthe persistence of poverty. Thus, thepermanence of low-income status willbe understated if we look only at thelength of time in poverty of those whoare currently poor, ignoring futureincome levels, or look only at povertystatus in the future, ignoring incomelevels in previous years.5

Because the public finance literaturedoes not typically calculate tax burdensaccording to arbitrary thresholds such as


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the poverty line, the results of researchon spells of poverty cannot be applieddirectly to quantile divisions (e.g.,deciles) of the population. Nonetheless,the general point about sample trunca-tion applies. The closer we come toexamining completed periods at anygiven income level, the more accuratethe picture of long-run income statuswe will get for a given annual distribu-tion. Our approach is thus to compareannual burdens for a centered year toaverage burdens for periods surround-ing that year.

The basic unit of analysis for intermedi-ate-term incidence is the individual.6 Weassume that income and expendituresare pooled among all members of thefamily unit. Therefore, at any point intime, the resources available to anindividual equal the total resources ofthe family unit in which the individualresides, and consumption tax burdensdepend on family expenditures relativeto family income. Our measure ofintermediate-run income is the averageincome of the family (or families) inwhich an individual lives over the 11-year period covered by our sample. Ifthe individual stays in the same familyunit over the sample period, then familyand individual incidence are the same. Ifthe individual passes through differentfamily units, intermediate-run incidenceis the average of family incidence ateach point in time.

Due to missing data, it was not possibleto calculate average incomes and taxburdens over the full 11-year period forevery individual in the 1982 sample.However, the full 11 years of data areavailable for a third of the sample, anddata are available for eight or moreyears for fully 83 percent of the sample.The implications of the missing data arediscussed in a data appendix availablefrom the authors. On the whole, our tax

incidence results remain largely un-changed when burden calculations arebased on a subsample of individualswith no missing data.

Although the PSID provides considerabledata on sources of income, it providesonly limited information on consump-tion expenditures of individuals in thesample. In order to develop an estimateof expenditures on gasoline, we rely ondata available on the PSID on the annualnumber of miles driven by the membersof each family.7 Indirect consumption ofgasoline through public transportationand reflected in the shipping cost ofgoods is not considered in this analysis.Gasoline expenditures are imputed tothe sample using a three-step proce-dure. First, miles driven are divided byan imputed measure of the fuelefficiency (miles per gallon) for eachfamily’s vehicles. Our miles-per-gallonestimates are based on methodologydeveloped by Kayser (1994) thatcombines data from the 1983 Survey ofConsumer Finances on the make,model, and year of cars owned by eachfamily with data on the averagegasoline mileage of each type of car.8

These data are used to estimate aregression of the assigned fuel efficiencyon a number of household-specificsocioeconomic and locational variables.9

The coefficients from this regression arethen used to calculate fuel efficienciesfor each individual in the PSID.

As the data needed to estimate theregression were only available for 1983,we had to assume that the structuralrelationship that existed in 1983between individual characteristics(including income) and fuel efficiencyalso held true in the other ten years ofour sample period. Miles-per-gallon datafor 1979, 1985, and 1988 from theResidential Energy Consumption Survey(U.S. Energy Information Administration,


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various years) suggest, however, thatthe relationship between income andfuel efficiency was weaker in theperiod prior to 1980 than in the periodafter 1980. Although this suggests thatour use of the 1983 structural relation-ship between income and fuel efficien-cy may be overestimating theregressivity of gasoline expenditures, atest of this proposition (described in thedata appendix) indicates that themagnitude of this overestimate is quitesmall.10

The final step in estimating gasolineexpenditures is to multiply the numberof gallons consumed by each individualby the price per gallon of gasoline. Thedata on gasoline prices are inclusive offederal excise taxes and state excise andsales taxes. The gasoline price data,which were provided by the Bureau ofLabor Statistics, are disaggregated byregion and for a number of majormetropolitan areas. Individuals livingoutside the major metropolitan areaswere assigned the average price for theregion of the country and the size of thejurisdiction in which they lived.

The data indicate that poorer familiestend to drive older and less fuel efficientcars than families with higher incomes.This implies that an imputation ofgasoline expenditures based on nationalaverage fuel efficiency would result in aless regressive pattern of gasolineexpenditure burden than we observeusing our more elaborate imputationprocedure.11

There was a considerable amount ofvolatility in the price of gasoline duringour sample period. The real price ofgasoline was stable from 1976 to 1979,increased by 56 percent between 1980and 1982, and then fell steadily from1983 through 1986. In real terms,

however, prices at the beginning andthe end of our sample period wereapproximately the same. Consumerresponses to price changes can occuralong two margins, adjustments in milesdriven and adjustments in the fuelefficiency of cars. The latter can beaccomplished by replacement of fuel-inefficient cars, or, in multicar families,by substituting away from the lessefficient car(s). In any given year, themiles driven variable reflects the neteffect of price adjustments along bothof these margins. Miles driven declinedin 1980 and 1981 but started toincrease again in 1982. Meanwhile,gallons of gasoline consumeddecreased continuously until 1985(Kayser, 1994). This suggests that bothtypes of price responses did, in fact,occur.

If the price elasticity of demand varies byincome level, then volatility in gasolineprices may influence our tax incidenceresults. The fact that, during the 11-yearperiod between 1976 and 1986, realgasoline prices were highest in 1982,the base year of our study, suggeststhat, if gasoline consumption is at allresponsive to the level of gasolineprices, our results may overstate theregressivity of the gasoline tax. Al-though we cannot precisely quantify themagnitude of any overestimate ofregressivity, we have used data from theU.S. Department of Energy on fuelefficiency by income class for the year1979 to make a rough adjustment forany overestimate of fuel efficiency forhigh-income individuals. The results ofthis adjustment to the data suggest thatthe methodology we employ forestimating fuel efficiency does not resultin either a significant increase in theregressivity of gasoline expenditures or asubstantial underestimate of the annualincome bias.12


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TAX INCIDENCE RESULTS

Gasoline Expenditures as a Percentageof Income

To allow easier comparison to otherstudies and because the incidence ofgasoline taxes is quite similar to theincidence of gasoline expenditures, mostof our analysis will focus on gasolineexpenditures rather than gasoline taxes.We begin with the traditional approachused in tax incidence analysis, namely,comparing gasoline consumption in asingle year with income in that year. Inthe left panel of Table 1, we order oursample of individuals by deciles of 1982income 13 and calculate average gasolineexpenditure burdens by decile (definedas gasoline expenditures by 1982 annualincome). The data indicate that, asexpected, annual gasoline expenditureburdens are regressive, with burdensfalling from 7.3 percent of income inthe second decile of 1982 annualincome to 3.1 percent in the top decile.To be sure that 1982 was not an atypicalyear, we also computed annual gasolineexpenditure burdens for each yearbetween 1976 and 1986. Averageburdens are lower in nine of the tenother years, reflecting lower real pricesof gasoline relative to 1982. The

incidence of expenditure burdens,however, is similar to the patternobserved in 1982. We also averaged theannual expenditure burdens for eachdecile over the 11 years and found theresulting distribution of burdens to besimilar to, although slightly moreregressive than, the annual incidencepattern in 1982.

Our finding that gasoline expendituresare regressive when measured usingannual data on income and expendi-tures is consistent with the findings ofother recent studies. Poterba (1991a)reports a similar regressive pattern forgasoline and motor oil expendituresrelative to annual income. Using 1985expenditure and income data from theConsumer Expenditure Survey, he findsthat the average burden falls from 6.5percent in decile 2 to 2.4 percent indecile 10. The U.S. CongressionalBudget Office (1990) reports thatgasoline expenditures as a percent of“post-tax family income” decline from6.9 percent in the bottom annualincome quintile to 1.5 percent in the topquintile. Rogers (1995) finds an evenmore highly regressive pattern of annualgasoline expenditure burdens. Hermeasure of annual burden falls from

TABLE 1GASOLINE EXPENDITURE BURDENS

1 (lowest)

Source: Authors’ tablulations based on data from the PSID.

Gasoline Expendituresas a Percentage ofAnnual Income:1982 Data from PSID

1976–86Average FamilyIncome Decile

Average Family Gasoline ExpendituresDuring the Period from 1976 to 1986 asa Percentage of Average Family IncomeDuring the Period from 1976 to 1986

1982 FamilyIncome Decile

10 (highest) 10 (highest)

23456789

23456789

7.36.75.85.75.25.04.63.93.1

5.35.15.04.64.34.03.83.42.5

6.4 % 1 (lowest) 3.9 %


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0.19 in the bottom annual incomequintile to 0.02 in the top quintile.

Calculating average burdens for thebottom decile is complicated by the factthat a number of individuals reportnegative, zero, or very small incomes.The standard response to this problem isto exclude individuals with very lowincomes from the analysis. In their well-known study of the distribution of taxburdens, Pechman and Okner (1974)excluded those in the bottom fivepercent of the income distribution fromthe bottom decile. In this paper, wehave excluded all individuals in thelowest one percent of the incomedistribution from the average burdencalculations for the lowest decile.Although we have excluded as fewindividuals as possible, any exclusionrule is, by definition, arbitrary. A closelook at the pattern of income over timeof the excluded individuals shows verylarge year-to-year income swings,suggesting that many excluded indi-viduals are self-employed and comfort-ably middle class, yet suffer occasionalbusiness losses. Similar conclusions arereached by Slemrod (1992), who,drawing on a panel of tax return data,reports that those with negativeadjusted gross incomes in a given yearhave relatively high seven-year averageincomes. The numbers reported in thetables for the lowest decile also reflectthe fact that a substantial portion of theindividuals in the lowest decile do nothave access to a car and, hence, have azero burden. If we exclude nondriversfrom our calculations, the distribution ofburdens is regressive starting with thelowest decile.

We expect that the use of annualincome in calculating expenditure or taxburdens will result in a more regressivepattern of burdens than if income ismeasured over a period of years (up to a

lifetime). Because measured annualincome contains a transitory componentthat by assumption, is weakly correlatedwith total consumption, the elasticity ofgasoline consumption with respect toannual income should also be smallerthan the elasticity with respect tolonger-run income. Since the fraction ofmeasured income, which is transitory,should decline as the time period islengthened, expenditures on any givenitem, in this case, gasoline, should beless regressive when compared to long-run income than when compared toannual income.

Consumption as well as income has along-run component and a transitorycomponent. Therefore, basing calcula-tions of gasoline tax burdens on datafrom a single year of gasoline consump-tion may give a misleading picture ofthe long-run burden of the gasoline tax.Assuming that the ratio of transitory tolong-run consumption declines as themeasurement period increases, averagegasoline expenditures over 11 years willprovide a better approximation of long-run expenditure patterns. Therefore, amore precise measure of the interme-diate-run burden of gasoline taxes isgiven by comparing the average amountof money spent on gasoline during eachyear of the 1976 to1986 period withthe average amount of real incomeearned during each year of that sameperiod.

The right panel of Table 1 presents ourintermediate-run incidence results. Aswe believe that intermediate-run incomeprovides a better measure of taxpayerability to pay than annual income, werank individuals by their 11-year averageincome and assign them to average-income deciles. Expenditure burdens aredefined as average family gasolineexpenditures over the 11-year periodfrom 1976 to 1986 divided by average


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family income over the same 11-yearperiod.11

The results indicate that intermediate-run burdens decline monotonically from5.3 percent in the second decile to 2.5percent in the highest decile. If wecharacterize individuals in the lowestseveral deciles as “persistently” poor,where persistence is defined as lowaverage income over an 11-year period,then an ad valorem tax on gasolinewould impose an economic burden onthe persistently poor that is nearly twiceas high as the burden placed on thepersistently rich.

Although intermediate-run burdensremain regressive, they appear to be lessregressive than annual burdens. Tosummarize and compare progressivityunder different measures of income andconsumption, we use the Suits index oftax progressivity, which ranges from –1(most regressive) to +1 (most progres-sive).15 The Suits index for gasolineexpenditures using annual data is–0.173. The index drops to –0.153when 11-year average income andexpenditure data are used. A criticismsometimes levied against the Suits indexis that it is sensitive to the distribution ofincome (Kiefer, 1984). For our purposes,however, the fact that the incomedistribution tends to become moreequal when income is measured overlonger periods of time is an importantfactor in explaining the annual incomebias. It is, thus, appropriate that theSuits index indicates decreased regres-sivity as we move to longer timeperiods.

To examine the relationship between thelength of the accounting period andmeasured incidence, we also calculateaverage gasoline expenditure burdensfor the five-year period from 1980 to1984. The value of the Suits index for

five-year average income and expendi-ture is –0.165. As a percentage of theone-year Suits index, the differencebetween the one-year and the 11-yearindex represents an 11.5 percent declinein the regressivity of gasoline expendi-ture burdens. The decline in regressivityis fairly uniform over the 11-yearobservation period, with a 4.6 percentchange in the first five years.

The incidence pattern indicated by theSuits indexes is illustrated in Figure 1,which plots one-year, five-year, and 11-year gasoline expenditure burdens bydecile of income. For comparability,individuals are ranked according to theirincome position over the relevantaccounting period. Thus, for 11-yearburdens, individuals are ranked by 11-year average income position, while forthe five-year period, they are ranked byfive-year income deciles. Figure 1 showsthat, although the average burden fallsas the accounting period is lengthenedand regressivity is somewhat reduced bynot relying on annual income andconsumption data, the overall regressivepattern of the gasoline tax remainsregardless of time period.

Lyon and Schwab (1995), in a study ofalcohol and cigarette tax incidence,arrive at results that are similar to ourresults for gasoline consumption. Theyfind that taxes on cigarette and alcoholconsumption are only slightly lessregressive when incidence is measuredwith respect to both five-year andlifetime incomes than when it ismeasured with respect to annualincome.

Our results, however, contrast withthose of several other recent studies ofgasoline expenditure incidence. Poterba(1991a) calculates expenditure burdensby dividing 1985 gasoline and motor oilexpenditures by total 1985 expenditures


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for families ranked by expendituredeciles. He finds that the pattern ofexpenditure burdens is progressivethrough the bottom four deciles beforeturning regressive over higher deciles.16

The U.S. Congressional Budget Office(1990) also uses total expenditures as ameasure of ability to pay. They calculatemotor fuel expenditures relative to totalexpenditures using annual data, butrank families by their post-tax annualincome.17 They find that spending onmotor fuels is proportional to totalexpenditures over the bottom fourincome quintiles and regressive over thetop income quintile.

Rogers (1995) uses gasoline expendi-tures in a single year and a proxy for

lifetime income to calculate gasolineexpenditure burdens. Ranking individu-als by her lifetime income measure, shefinds that gasoline expenditure burdensfollow a hump-shaped pattern, with thehighest burdens in the middle lifetimeincome quintile.

Gasoline Tax Burdens

If the only tax on gasoline was in theform of a national ad valorem excisetax, then the gasoline expenditureincidence displayed in Table 1 would beproportional to the incidence of thegasoline tax. In fact, about two-thirds ofthe total gasoline excise tax rate facedby the average American consumer iscomposed of state excise taxes. In 1982,

FIGURE 1. Three Measures of Gasoline Expenditure Burdens as a Percentage of Income: Single Year,Five-Year Averages, and 11-Year Averages


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these state taxes ranged from 8 to 22cents per gallon. In addition, nine statesincluded gasoline consumption in theirsales tax base during some or all of the11-year period between 1976 and1986.

To determine whether the incidence ofthe gasoline tax is identical to that ofgasoline expenditures, we calculatedgasoline tax burdens by assuming thatgasoline taxes are shifted fully forwardto consumers and by applying state-specific total gasoline excise tax rates togasoline consumption (in gallons) and,where appropriate, state sales tax ratesto gasoline expenditures. The resultsshow that the incidence of tax burdensis very similar to the incidence ofgasoline expenditure burdens displayedin Table 1. The average intermediate-rungasoline tax burden is 0.90 percent inthe second average income decile, 0.77percent in the fifth decile, and 0.43percent in the top decile.

To determine whether the variationamong states in excise tax burdenscontributes to the overall regressivity ofthe tax, we simulated a revenue-neutraluniform national gasoline excise taxrate. The results of the simulationindicate that the variation in ratesacross the states actually contributes toa slight reduction in regressivity. Thisoccurs because states with a highconcentration of residents with rela-tively low intermediate-run incomestend to have below-average gasolinetax rates.

INTERPRETATION OF THE RESULTS

The purpose of this section is to explorethe reasons why the intermediate-runincidence of gasoline expenditures (andtaxation) is quite similar to the annualincidence. Following Poterba, we refer

to the differences between these twomeasures of incidence as annual incomebias. The bias from using annual data toconduct tax incidence analysis occursfor two reasons. First, annual incomebias will be larger to the extent thatannual income differs from longer-runincome. If, over time, most individualsexperience limited changes in their realincome (for either transitory or life-cyclereasons), the measurement of taxincidence will be quite insensitive tothe length of time over which incomeis measured. Second, given that annualincome differs from longer-run income,the annual income bias will be largerto the extent that individuals’ gasolineconsumption depends on theirlonger-run rather than their annualincome.

To help us analyze the annual incomebias, it is useful to write out a simplemodel of gasoline consumptionbehavior. Let us assume that annualgasoline expenditures in year t (Gt)depend on longer-run income (Yl) andon the difference (Y dt ) between annualincome in year t (Yt) and longer-runincome.18 This relationship can beexpressed as

If α2 = 0, then annual gasoline expendi-tures depend only on longer-runincome. In that case, the consumptionmodel in equation 1 is in the spirit ofthe permanent income model. If α2 > 0,then positive deviations of annualincome from longer-run income wouldlead to an increase in annual gasolineexpenditures. Defining Yl as equal to Yt

1

Gt = α0 + α1Yl + α2Y d.

t


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minus Y dt , substituting into equation 1,and dividing by annual income, weobtain the following expression for theannual gasoline expenditure burden (Bt):

If Y dt equals zero, annual income equalslonger-run income in year t, and theannual burden (the first term in equa-tion 2) is equal to the longer-runburden. If Y dt is not equal to zero, thenthe first term represents the longer-runcomponent of the measured annualburden. Labeling this term Bl, we candefine the annual income bias in yeart (βt) as

From equation 3, we can see that theannual income bias depends on the re-sponsiveness of gasoline consumptionto changes in both annual and longer-run income and to income mobility, wheremobility is measured as the differencebetween annual and longer-run incomerelative to annual income (Y dt /Yt).

In this section, we analyze the rolesincome mobility and gasoline consump-tion behavior play in determining theincidence of gasoline expenditures. Thediscussion will help explain our inci-dence results and will explore thereasons our results differ from those ofother studies. As will be explainedbelow, our ability to look separately atthe impact of income mobility andgasoline consumption behavior on taxincidence will be enhanced by separat-

ing the calculation of intermediate-runincidence into two parts. The first is thecalculation of annual, five-year average,and 11-year average expenditureburdens for each individual. The secondis the ranking of individuals by alterna-tive measures of their ability to paytaxes, namely, annual, five-year, and 11-year average incomes.

Summary statistics generated from thistwo-step procedure are presented inTable 2, which displays two measures ofthe incidence of gasoline expenditureburdens using three alternative mea-sures of burden and three alternativeincome rankings. For each expenditureburden measure, horizontal movementsin Table 2 represent alternative rankingsof individuals by annual, five-year, and11-year average incomes. Verticalmovements (down the columns)represent the use of different burdenmeasures under a constant incomeranking.

The Suits indexes presented in theprevious section of the paper aredisplayed in the upper-left to lower-rightdiagonal cells of Table 2. Thus, in theupper-left cell (which we will call cella11), burdens are calculated using 1982annual income and gasoline expendituredata and individuals are ranked by their1982 annual incomes. In the bottom-right cell (cell a33), burdens are calcu-lated using 11-year average gasolineexpenditures and income and individualsare ranked by their 11-year averageincomes. As discussed previously, theobserved decline in the Suits index from–0.173 to –0.153 indicates a modestreduction in regressivity as we movefrom annual to intermediate-runincidence.

As Suits indexes can only be calculatedwhen expenditures (or taxes) andincome are ranked according to the

3

2

Yt

Bt = Gt =

α0 + α1Yt + (α2 – α1) Yt .

Yt Yt

d

d

βt = Bt – Bl = (α2 – α1)Yt

Yt .


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same criterion, we must use an alterna-tive summary measure to determineincidence in the off-diagonal cells ofTable 2. As an alternative incidencemeasure, we take the ratio of theaverage burden in the top part of theincome distribution (deciles 7 through 9)to the average burden in the bottompart (deciles 2 through 4). For conve-nience, we will call this measure theratio index of tax progressivity.19 Thelarger the value of the index, the greaterthe progressivity of the underlyingdistribution. A value of one indicatesproportionality.

The Role of Economic Mobility

We consider first the role of economicmobility in explaining the magnitude ofthe annual income bias. At the outset, itis important to emphasize that incomemobility is a particularly elusive concept,and any conclusions about the extent ofmobility are highly sensitive to the wayin which it is measured. As Fields andOk (1996) point out, “...the very notionof income mobility is rather a multi-

faceted one, and any attempt to devisea measure that aims to incorporate allaspects of income mobility is thereforedestined for failure” (p. 4). Results maydiffer depending on whether economicmovement is defined in relative orabsolute terms and depending on thetime frame for measurement.

Defining Mobility

For any given year t, we define incomemobility in terms of the differencebetween an individual’s annual incomedecile and his or her 11-year averageincome decile. Average income isdefined in terms of an income periodcentered on year t. As discussedpreviously, defining average income inthis way, rather than as average incomein a period starting in year t, provides abetter measure of ability to pay becauseit considers both past and future incomelevels and tends to reduce the impact ofsample truncation. We refer to individu-als whose annual income position in agiven year is close to their intermediate-run income position as economically

TABLE 2DISTRIBUTIONAL INDICES FOR GASOLINE TAX INCIDENCE: SUITS INDEX (IN BOLD) AND

RATIO PROGRESSIVITY INDEX* (IN SQUARE BRACKETS)

*The ratio progressivity index is defined as the average burden in deciles 7 through 9, divided by the averageburden in deciles 2 through 4.Source: Authors’ calculations.

Ranking of Individuals by Alternate Ability to Pay Measures

(3)11-yearaverage

(2)Five-yearaverage

(3)11-YearAverageIncome

Alternative gasolineexpenditure burdens

(2)Five-YearAverageIncome

(1)

AnnualIncome

(1)annual [0.68]

[0.75]

[0.78]

[0.72]

[0.72]

[0.73]

[0.76]

[0.73]

[0.73]

–0.173

–0.165

–0.153


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immobile and individuals whose annualposition differs substantially from theirintermediate-run position economicallymobile. This definition of mobilityemphasizes changes in relative incomeposition and makes no distinctionbetween mobility that occurs fortransitory reasons and that which takesplace for life-cycle reasons.

To calculate the number of individuals inour PSID sample whose relative incomeposition remain unchanged over a periodof 11 years, we calculate the proportionof individuals who are in the same or anadjacent decile of 1982 annual incomeand 11-year average income.20 A U-shaped pattern that is characteristic oftransition matrix measures of incomemobility emerges, with a higher propor-tion immobile in the tails of the distribu-tion than in the middle (Atkinson,Bourguignon, and Morrisson, 1992).Overall, nearly 85 percent of individualsremained in the same or an adjacentaverage-income decile and, thus, areclassified as immobile. Among house-holds whose incomes are in the bottomtwo deciles in 1982, 87 percent had low11-year average incomes.21 And even inthe middle-income deciles, whereeconomic mobility is greatest, we classifyover 75 percent of households aseconomically immobile.

It should be pointed out that otherstudies that have reported larger annualincome biases than we do, for example,Fullerton and Rogers (1993), Caspersenand Metcalf (1994), and Davies,St.-Hilaire, and Whalley (1991), alsotend to find a substantial amount ofincome mobility. These differences inreported income mobility stem from twosources. The first is that most otherstudies rely on restricted samples,generally household heads. Theseindividuals tend to experience moreeconomic mobility than the population

as a whole.22 The second is that, for thereasons articulated earlier, we use acentered measure of mobility, whereasmost other studies use a prospectivemeasure of mobility—comparing incomein year t to income in a period followingyear t. Furthermore, other studies tend toestimate income over a longer time pe-riod, generally a lifetime. For those in-dividuals whose real income follows alinear time trend over the observation pe-riod, the interior year will be a better pre-dictor of average income than the initialyear. Hence, centered measures of mo-bility are more likely to reflect transitorychanges in income while minimizing theimpact of life-cycle changes (movementsalong an age-earnings profile).23

We are now ready to use the ratioprogressivity indices presented in Table 2to help us look more closely at thequestion of why annual gasolineexpenditure incidence differs fromintermediate-run incidence. We start byasking what happens to the distributionof annual expenditure burdens ifindividuals are ranked by their averageincome. The answer to this question canbe seen by looking at the first row ofTable 2 and comparing the value of theratio progressivity index in cell a11 (0.68)to the value of the index in cell a31

(0.76). As burden measures remainunchanged for all horizontal moveswithin Table 2, any changes in the valueof the index must be due entirely tochanges in relative income. The changein the ratio index from 0.68 to 0.76indicates that income reranking reducesregressivity. Recall that reranking ofindividuals from their annual to their 11-year average income position results inlittle change in the relative incomepositions for most individuals. Thus, thereduction in regressivity indicated by amove from cell a11 to a13 reflects theincome mobility of a relatively smallnumber of individuals. Many of these


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individuals have high annual gasolineexpenditure burdens. The incomereranking moves them up the average-income distribution. The movement ofindividuals with high burdens from thebottom of the annual income distribu-tion to a higher position in the average-income distribution results in theobserved reduction in measuredregressivity.

A different story can be told by lookingat horizontal movements in the thirdrow of Table 2. Again, we are isolatingthe impact of income mobility, but herewe look at the distribution of averageexpenditure burdens as individuals movefrom a ranking by annual income to aranking by average income. In cell a31,average expenditure burdens arearrayed by 1982 annual incomes.24 Byreranking these individuals by theiraverage incomes, the ratio progressivityindex is reduced from 0.78 to 0.73,indicating an increase in regressivity or,alternatively stated, a reduction in themagnitude of the annual income bias.To understand this change, rememberthat the very process of calculatingintermediate-run burdens has tended toreduce burdens for those with unusuallyhigh annual burdens (and low annualincomes) and increase burdens for thosewith unusually low annual burdens (andhigh annual incomes). The reorderingfrom annual to intermediate-run incomeposition (represented by the move fromcell a31 to a33) takes mobile individualswith low annual incomes and what arenow relatively low average burdens andmoves them up the income distribution.Conversely, mobile individuals with highannual incomes and moderate or highaverage burdens tend to move downthe income distribution. The result is anincrease in measured regressivity. Thissuggests that using measures of long-run tax burdens, but failing to rankindividuals by the corresponding mea-

sure of ability to pay, will overstate themagnitude of the annual incomebias.

The Role of Gasoline ConsumptionBehavior

The importance of intermediate-runincome as opposed to annual income indetermining annual gasoline expendi-tures depends on the magnitude of α1

relative to α2 (see equation 3). Theannual income bias will be larger to theextent that gasoline consumptiondecisions are made on the basis oflonger-run income rather than on thebasis of annual income. To help isolatethe relationship between income andgasoline expenditures from the impactsof income mobility, we move downcolumn 1 of Table 2. The movementfrom cell a11 (annual burdens ranked by1982 annual income) to cell a31 (11-year average burdens for individualsranked by 1982 annual income)indicates a substantial reduction inregressivity, with the ratio index goingfrom 0.68 to 0.78. In terms of the ratioindex of progressivity, this reduction inregressivity is twice as large as thereduction in regressivity that we observewhen we calculate intermediate-runburdens and rank individuals by theirintermediate-run incomes. The conclu-sion we draw is that the annual incomebias is substantially overstated if wecalculate average expenditure burdensbut continue to rank individuals by theirannual incomes.

To help us understand the reasons forthis reduction in regressivity, we divideour sample into three groups accordingto their magnitude and direction ofincome mobility. Individuals are definedas upwardly mobile if their 11-yearaverage income decile is more than onedecile higher than their 1982 annualincome decile, downwardly mobile if


250

their average income decile is more thanone decile lower than their annualincome decile, and immobile if theyremain in the same or an adjacentaverage and annual income decile. Foreach of these three groups, we calculateannual and 11-year average gasolineexpenditure burdens. Figure 2 illustratesthe results of these calculations forindividuals in each group ranked by their1982 annual incomes.25

The top panel of Figure 2 demonstratesthat, for those who are upwardlymobile, the use of annual data incalculating gasoline tax burdens willsubstantially overestimate the regres-sivity of the gasoline tax. For the lowestthree deciles of the 1982 annual incomedistribution, annual burdens are abouteight percentage points higher thanaverage burdens. The annual incomebias is especially high in the lowestannual income decile, equalling almostten percent of income. By contrast, forthose who are classified as immobile ordownwardly mobile, the annual incomebias appears to be negligible. Theseresults suggest that, for the relativelysmall number of individuals who areupwardly mobile, gasoline consumptiondecisions are primarily influenced byintermediate-run incomes rather than by(temporarily) low annual incomes.

Just as income mobility reduces theannual income bias (increasesregressivity) once we have replacedannual by intermediate-run burdens(represented by horizontal movement inTable 2 from a31 to a33), so replacingannual by intermediate-run burdens,after we have taken into accounteconomic mobility (represented byvertical movement from a13 to a33), alsodecreases the annual income bias. Inthis case, some high intermediate-runincome individuals with high annualburdens are assigned lower intermedi-

ate-run burdens, leading to greaterregressivity.

To summarize the results of this section,we argue that the magnitude of theannual income bias depends on theextent of economic mobility and thedifference in consumption behavior withregard to longer-run income and annualincome. When we compare annual to11-year incidence for gasoline expendi-tures, we find that the annual incomebias is relatively modest. Looking first atmobility, we find limited economicmobility in our 11-year sample. Only asmall proportion of the sample havemore than one decile differencebetween their annual and intermediate-income positions. Comparing gasolineexpenditure burdens for those who aremobile and those who are not showsthat the annual income bias is substan-tial only for the small percentage of thesample who are upwardly mobile.

Though mobility in our sample islimited, the annual income bias is stilloverstated if we take into account onlyeconomic mobility. The bias is similarlyoverstated if we take into account onlythe difference between annual andintermediate-run burdens. The bias iscorrectly measured by comparingintermediate-run incidence to annualincidence, in other words, by substitut-ing intermediate-run for annual expen-diture burdens and reranking individ-uals according to longer-run ability topay.

The discussion in this section shouldhelp clarify why a number of otherstudies of the incidence of the con-sumption-based taxes conclude that theuse of annual data leads to a substantialoverestimate of regressivity. As pointedout previously, the U.S. CongressionalBudget Office (1990) study of excisetaxes calculated expenditure burdens


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FIGURE 2. Annual and 11-Year Average Gasoline Expenditure Burdens for Individuals Classified by Income Mobility


252

using a single year of consumption dataand used total consumption expendi-tures in the same year as a measure ofability to pay. We have argued in theIntroduction that annual expendituresare likely to be a poor proxy for thelong-run ability to pay taxes. In addition,the Congressional Budget Office drawsconclusions about long-run incidencebased on the distribution of expenditureburdens for individuals ranked by theirannual income. As demonstrated above,the failure to rank individuals by ameasure of long-run ability to payresults in an overestimate of the annualincome bias.

In his study of gasoline tax incidence,Poterba (1991a) also uses annualexpenditures as a proxy for lifetimeincome. He uses annual gasolineexpenditures to calculate burdens, andthen ranks individuals by decile on thebasis of their total annual expenditures.We calculated that Poterba’s resultsimply a ratio progressivity index forgasoline expenditure burdens of 0.84.This number compares with the ratioindex values for annual burdens of 0.68and for 11-year average burdens of0.73, and, hence, indicates that the useof total expenditure data as a measureof lifetime income results in a substan-tially larger annual income bias than thebias relative to intermediate-run income.

The difference between Poterba and ourgasoline incidence results demonstratesthat total annual expenditures provide apoor proxy for intermediate-run income.One possible explanation for this resultis that, while the 11 years over whichintermediate-run income is measured islong enough to eliminate the bias fromtransitory income variations, the use ofannual expenditures may serve toremove the annual income bias attribut-able to both transitory and life-cycleeffects. If this were so, annual expendi-

tures would indeed be a good proxy forlifetime income. It seems unlikely,however, that annual expenditures aredevoid of both transitory and life-cycleeffects. Annual consumption almostcertainly has a transitory componentand a permanent component. As sug-gested by Caspersen and Metcalf (1994),to the extent that transitory consump-tion expenditures are constant acrossincome classes, the use of annualexpenditure data will lead to a down-ward bias in tax (or expenditures) bur-dens at lower income levels. In terms oflife-cycle measurement, because annualexpenditures exclude bequests, and be-quests are a larger proportion of lifetimeincome for individuals with higherlifetime incomes, the use of annualexpenditures as a measure of ability topay will bias tax burdens upward at thetop of the income distribution.

Davies, St.-Hilaire, and Whalley (1991)report that the lifetime incidence ofsales and excise taxes, while remainingregressive over the entire incomedistribution, is substantially less regres-sive than the annual incidence. The ratioindex of progressivity for sales andexcise taxes, calculated from their Table2, increases from 0.78 for annualincidence to 0.94 for lifetime inci-dence—an increase of 22 percent. Thiscontrasts with our results, whichindicate that the ratio index increases byonly seven percent as we move fromannual to intermediate-run incidence. Intheir study, Davies, St.-Hilaire, andWhalley use Lillard’s (1977) results onearnings mobility to construct theirestimates of lifetime income. Byparameterizing a mobility probabilitythat is greater than that for the entirepopulation, and that does not reflectdifferences in mobility across the annualincome distribution, Davies, St.-Hilaire,and Whalley impose unrepresentativemobility on the sample. Our longitudinal


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data from the PSID indicate thatsubstantial income mobility, at least overan 11-year period, tends to be limited toa relatively small proportion of thepopulation. This result suggests that theearnings mobility assumptions used byDavies, St.-Hilaire, and Whalley mayresult in an overestimate of the biascreated by using annual data for taxincidence analyses.

COMPENSATION FOR EXCISE TAXINCREASES

As a way of countering claims thatincreases in regressive consumptiontaxes will create hardships for individualswith low incomes, economists fre-quently propose coupling a tax increasewith an offsetting compensationscheme designed to neutralize anyadverse distributional impacts of theinitial tax increase. An important issue inthe design of such schemes is to targetcompensatory payments as effectively aspossible to those most in need ofassistance. If one of the reasons forincreasing gasoline taxes is to dis-courage the consumption of gasoline,compensatory payments should betargeted as closely as possible to thosefacing increased burdens, yet beindependent of individual gasolineconsumption decisions. A sensiblestrategy would be to limit eligibility forcompensation to those in the weakesteconomic position. In principle,compensation payments could be paidonly to those with persistently lowincomes, defined, for example, asindividuals in the bottom of the inter-mediate-income distribution. In practice,it would be almost impossible toimplement any scheme based onaverage incomes. Practical consider-ations would probably require that anycompensation scheme be based on aneasily observable characteristic, such asannual income.

The cost of any compensation schemerises and its effectiveness declines to theextent that “undeserving” individualsreceive payments or “deserving”individuals are not compensated. Theuse of annual income instead ofintermediate-run income in a compen-sation scheme would result in somedegree of “mispayment.” In any givenyear, some middle-income familieswould qualify for compensation,because their incomes are temporarilylow, and some persistently low-incomefamilies would not be eligible forcompensation, because their incomethis year is too high.

To illustrate the consequences ofdesigning a compensation scheme usingannual income instead of some measureof longer-run income, we consider a$100 per ton carbon tax analyzed byPoterba (1991b). Based on projectedretail energy prices in the United States,Poterba estimates that a fully forward-shifted tax of this magnitude wouldcause a 25 percent increase in the retailprice of gasoline. We adopt the follow-ing simple compensation scheme:

Compensatory payments are restricted tothose in the lowest three deciles of theannual income distribution, and theamount of compensation is determinedby using a “circuit breaker” type of for-mula that limits the average eligibleperson’s increase in gasoline tax burdento one-half of one percent of annualincome.

Our discussion in the last sectionsuggests that if a large portion of low-income individuals in any given year areonly temporarily poor, any compensa-tion scheme will be characterized bysubstantial mispayments. Given therelatively low level of income mobilityreported in the Interpretation of theResults section it is not surprising that asimulation of the compensation scheme


254

outlined above reveals that only about18 percent of those in the lowest threeannual income deciles (based on their1982 income) would be ineligible forcompensation if compensation werebased on 11-year average income.Conversely, about six percent of thoseineligible for compensation becausetheir 1982 income places them abovethe third income decile would be eligibleif compensation had been based onaverage income.

Under the assumption of a long-rungasoline price elasticity of -0.5, wecalculate that a $100 per ton carbon taxwould have raised $9.8 billion in 1982.26

The implementation of the compensa-tion scheme outlined above would havecost $692 million, which equals sevenpercent of the tax revenue raised.Furthermore, we estimate that signifi-cantly less than 18 percent of totalcompensation would have been paid“incorrectly” to persons who wereabove the third average income decile.The amount of misallocated compensa-tion is relatively small, because most ofthe families with intermediate-runincomes above the third decile, butannual incomes in the lowest threedeciles, have incomes in the third annualincome decile and, therefore, would tendto receive lower payments than those inthe first two annual income deciles. Weconclude that, although there is no wayto design a completely target effectivescheme to compensate low-incomeindividuals for increases in consumptiontax burdens, schemes that rely on annualincome to determine eligibility andpayment levels would be quite effectivein targeting payments to the mosteconomically vulnerable individuals.

Conclusions

Attention has focused on the gasolinetax as an efficient way of simultaneously

addressing a number of major problems:the threat of global warming, ourcongested highways, and the largefederal budget deficit. A frequentlyheard political objection to increasingthe gasoline tax is its alleged regressivity.Empirical support for the view that thetax imposes a much higher burden onthe poor than on the affluent comesprimarily from studies that utilize annualdata on gasoline consumption andincome. Recently, however, theregressivity of the gasoline tax, as wellas other consumption taxes, has beenchallenged by a number of economists.They argue, primarily on the basis ofMilton Friedman’s permanent incomehypothesis, that the use of annual dataas opposed to lifetime income andconsumption data leads to a substantialoverestimate of the regressivity of thetax.

In this paper, we argue that, while alifetime perspective is conceptuallyattractive, a series of problems with theapproach, including the difficult task ofmeasuring lifetime income andconsumption and explaining the resultsto policymakers, preclude the wide-spread use of the approach in analyzingconsumption tax incidence. To addressthe issue of the bias toward regressivitywhen annual data are used in distribu-tional analyses, we propose an alterna-tive to both the annual and the lifetimeapproaches that is based on data for anintermediate time period.

Using longitudinal data on income andgasoline expenditures, we show that,when people are grouped into 11-yearaverage income deciles, intermediate-run average gasoline tax burdens areonly slightly less regressive than annualburdens. The main reason for thesimilarity of annual and intermediate-run burdens is the limited degree ofincome mobility over an 11-year period.


255

We find that most persons who werepoor (or rich) in 1982 were in a similarrelative income position over the periodfrom 1976 to 1986. This lack of incomemobility means that, for most people,annual spending patterns are replicatedover a longer time period. The specialstrength of our analysis is that wecombine income and expenditure datain a single panel. We exploit this data toexamine directly the proportion of thesample for whom the annual incomebias is important. We find that, in agiven year, substantial overestimates ofthe regressivity of gas expendituresoccur only among the small proportionof individuals who were only temporarilypoor in 1982.

One criticism of our approach is that, bydefining intermediate-run income asaverage income over 11 years, wesubstantially underestimate the degreeof income mobility that occurs asindividuals move up their age-earningsprofile. Lack of data availability pre-vented us from testing this propositiondirectly with linked expenditure andincome data. However, we note thatLyon and Schwab (1995) find no changein the incidence of cigarette consump-tion when cigarette burdens arecalculated using income over a five-yearperiod and lifetime income. A similarcomparison for alcohol consumptionindicates only a relatively small decreasein regressivity when lifetime burdens arecompared to five-year burdens. TheLyon and Schwab results taken togetherwith ours suggest that, while the annualincome bias is a real phenomenon, itsmagnitude is insufficient to overturn thegeneral proposition that consumptiontaxes are regressive.

With regard to the gasoline tax itself,we conclude that, in assessing theadvantages and disadvantages ofincreased reliance on gasoline taxation,

concerns about the burdens placed onthose with low incomes cannot bedismissed. Persons in the bottom half ofthe income distribution face 11-yearaverage gasoline tax burdens thataverage 0.85 percent of income. Ourmobility findings indicate that, of thosewith low incomes in a given year, a largemajority are in the midst of an extendedperiod of low incomes. For people withlow incomes, burdens of this magnitudeand duration can create substantialeconomic hardships. Nevertheless, webelieve that the magnitude of the taxburdens (especially when compared toother taxes) is moderate enough sothat, when combined with a reasonablysimple compensation scheme, gasolinetax increases could be implemented thatwould generate substantial revenuesand provide efficiency benefits, yetprotect the poor from undue hardship.

ENDNOTES

We would like to thank the seminar participants atNorthwestern University, Hunter College, and theUniversity of Wisconsin–Madison and GregDuncan, James Poterba, Cordelia Reimers, JohnKarl Scholz, and three anonymous referees for veryhelpful comments on a previous draft. We areindebted to Dietrich Earnhart, Hilke Kayser, andJohn Pepper for exceptionally able researchassistance. Financial support was provided by theRussell Sage Foundation and the Robert M. LaFollette Institute of Public Affairs at the Universityof Wisconsin–Madison.

1 See Poterba (1989, 1991a), U.S. CongressionalBudget Office (1990), and Charles River Associates(1991).

2 Duncan and Hill (1989) report that total incomereported by the PSID accounts for about 95percent of income as measured by aggregatenational statistics, and Duncan, Smeeding, andRodgers (1991) find that family income trendsfound in the PSID are exceedingly close to thosefound in the Current Population Survey. Bycontrast, Clayton-Matthews and Kazarosian (1988)report that income measured by the ConsumerExpenditure Survey, is lower than income asreported on the Current Population Survey.Furthermore, even after accounting for differencesin definition, they find total consumptionexpenditures as reported on the Consumer


256

Expenditure Survey are considerably lower thanaggregate estimates of consumption from theNational Income and Product Accounts. In previouswork, we have found that estimates of sales andexcise tax revenues made using consumption datafrom the Consumer Expenditure Survey aregenerally substantially below actual tax collections,even after subtracting taxes paid on interfirmtransactions (Chernick and Reschovsky, 1990).

3 Considerable uncertainty exists with respect to thereported household income when the head of thehousehold changes. A family member leaving ahousehold to become head of a new family unitmay, for example, report zero income for theprevious year that was spent mainly as part of theoriginal family unit. The original family’s incomemay be a more accurate measure of the individual’sfinancial situation. The PSID deals with theallocation issue by prorating the mover’s income tothe family of origin and attributing the income tothat family. The entire calendar year income is alsoattributed to the new family. This techniqueproduces some double counting in the aggregate.To avoid any incorrect assignment that may resultfrom the proration method, in calculating averageincomes, we excluded reported income for eachyear in which a change in the head of the familyunit occurred. This is equivalent to assuming thatthe income in the year a family change occurredwas equal to the average income over the rest ofthe 11-year period. For the reference year 1982,average income from the remaining years is usedto replace the self-reported income.

4 For examples, see Fullerton and Rogers (1993) orDavies, St.-Hilaire, and Whalley (1991).

5 For example, Bane and Ellwood (1986) show thatonly a quarter of those who are poor in a givenyear have been poor for more than nine years. Bynot following those who are currently poor intothe future, 25 percent of the sample are incorrectlyassigned a long-term poverty status of less thannine years.

6 Each adult is assigned the weight of the family ofwhich he or she is a member in 1982. However,because family weights in the PSID do not varywith family size, the weight will be the sameregardless of the number of children in a family.

7 Each year about 3.2 percent of the automobileowners in our PSID sample responded to thequestion asking for the number of miles driven byanswering “do not know.” Because the number ofmiles driven is a crucial variable in the analysis, wehave used an ordinary least-squares regression toimpute miles for individuals with missing data.Included in the regression as explanatory variablesfor miles driven are family income, number ofadults in the family unit, number of children,number of cars, average miles driven over theprevious three years (or the previous two years for1976 because miles were not reported in 1973),

distance to the city center, and state dummies. Thesample for the regression includes only the headsof family units.

8 Data on fuel efficiency come from gasoline mileageguides published annually by the U.S. Environ-mental Protection Agency (various years).

9 To impute fuel efficiency for years other than 1983,we simply adjust the constant term of the miles-per-gallon regression to reflect increasing fuelefficiency over the sample period. The imputationequation is

According to this equation, each household’s fuelefficiency differs from the national average by theway in which the household’s characteristics differfrom the average values for the characteristics inthe sample.

10 It is interesting to note that recent data indicatethat the fuel efficiency to income relationship isnow weaker than it was during our sample period.Increases in the number of vans and light truckspurchased by households have actually invertedthe relationship, with higher-income families morelikely to drive less fuel efficient vehicles than lower-income families. These changes in vehiclepurchasing habits clearly have the effect ofsomewhat reducing the regressivity of the gasolinetax.

11 Earlier studies of gasoline demand using data fromthe PSID by Holmes (1976) and Hill (1980)assumed that all drivers experienced the same fuelefficiency.

12 Details about the procedure we followed todetermine the magnitude of any underestimate ofthe annual income bias attributable to our fuelefficiency imputations are provided in a dataappendix available from the authors.

13 For expositional clarity, we refer to the income ofindividuals interviewed in 1982 as 1982 annualincome. It should be understood, however, that inthe PSID, as in most sample surveys, individuals areasked to provide income in the previous year. Thus,references in this paper to “1982 annual income”actually represent income in 1981.

14 This is equivalent to a weighted average of annualburdens, where the weights represent annualincome relative to average income.

15 The Suits index is similar to the well-known Ginicoefficient, except that it compares a cumulativefrequency distribution of tax liabilities with asimilar distribution of household income. For aregressive tax, the resulting Lorenz curve lies abovethe diagonal, and the Suits index takes on negativevalues.

16 Poterba’s (1991a) results are taken from column 3of his Table 2.

17 In the next section, we argue that it is inappropri-ate to make normative judgments about long-run

mpgt = mpgt + β 83,SCF [Xt,PSID – Xt,PSID] .


257

tax incidence on the basis of a ranking of taxburdens by annual income.

18 Annual income can differ from longer-run incomefor both transitory and life-cycle reasons.

19 It should be noted that the ratio progressivity indexassigns identical weights to, for example, thesecond and the fourth decile of income. Anincrease in the burden in the second decile coupledwith an equal-value decrease in the fourth decilewould leave the index unchanged. We recognizethat this is not acceptable as a social welfare index.For this reason, we use the index as a convenientsummary for a number of different distributions,while also explicitly noting any changes inincidence patterns that occur in smaller slices ofthe income distribution.

20 Lillard and Willis (1978) and Gottschalk (1978)used this type of mobility measure to examineearnings mobility.

21 Additional evidence of the relatively low level ofeconomic mobility among low-income individualsis provided by Stevens (1995), who shows that, forpersons just beginning a spell of poverty, persistentpoverty is quite common if we account for theprobability of multiple spells of poverty. She reportsthat, of persons who fall into poverty, the averageperson will spend more than four of the next tenyears in poverty. Furthermore, over this period,more than 50 percent of all blacks and one-third ofall whites will spend five or more years in poverty.

22 Bane and Ellwood (1986) make a similar criticismof studies of income dynamics, which use samplesof prime age males, arguing that the patterns ofincome mobility for this group are inadequate forunderstanding the dynamics of poverty for theentire population.

23 When we calculate mobility prospectively, bycomparing annual-income positions in 1976 toaverage-income positions from 1976 to 1986, wefind that the proportion of the sample classified asimmobile drops from 85 to 69 percent. Comparingthe initial and final years of the period, theproportion who are immobile drops to 49 percent.In spite of this overall increase in measuredmobility, over 80 percent of those in the bottomtwo deciles of the 1976 income distribution wouldbe classified as immobile over the period coveringthe 11 years from 1976 to 1986. In the bottomdecile of the annual income distribution, mobility isthe same whether measured prospectively or usingthe centered approach. For deciles 4 and above,some 20 percent of the sample who are immobilebased on their 1982 income positions are classifiedas mobile when mobility is measured prospectively.

24 In their study of excise tax burdens, the U.S.Congressional Budget Office (1990) displays theirlonger-run burden measures by annual income. Weshall argue below that this asymmetry betweenburden measure and ranking is inappropriate fortax incidence analysis and results in an over-

estimate of the magnitude of the annual incomebias.

25 This is equivalent to a movement down the firstcolumn of Table 2 for three subsamples.

26 Our choice of gas price elasticity reflects anaverage of estimated price elasticities in studies ofgasoline demand surveyed in Dahl (1986).

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WHO PAYS THE GASOLINE TAX?