Referee Report:

The Internet as a Tax Haven?

The E↵ect of the Internet on Tax Competition

David R. Agrawal, 2014

Melika Liporace

November 17, 2014

1 Summary

The aforementioned paper investigates the e↵ect of e-commerce availability on tax competition be-tween localities in the U.S., examining both the theoretical predictions and the empirical results. Todo so, the author uses the U.S. sales tax system that interestingly relies on a decentralized multi-layerssetup - state, county, municipal and sub-municipal levels. To research the main question, whether in-ternet constitutes a tax haven or actually helps enforcing taxes, he distinguishes two types of e-shops:websites without nexus - that are not required to pay sales tax to localities - or with nexus - thatmust then collect local sales taxes given the location of their consumers. It follows that two competinge↵ects are at stake: either Internet creates a way for consumer to escape local taxes, constituting avirtual tax haven, that will lead to an ine�ciently low tax rates, as suggested by tax competitiontheory; or Internet gives the possibility to jurisdictions to collect taxes on firms that are not physicallyimplemented, retains consumer that would have crossed border and hence could reduce competitivepressure between localities.

Both of these hypotheses rely on a theoretical analysis, based on a similar model, in which twoborder towns that are 1 unit long and 1 unit populated are located in di↵erent states, with di↵erentstate sales tax rate - relatively, high and low. The consumers have inelastic demand and can obviouslycross-border (mobile tax base). The two towns compete in a Nash game and want to maximize localtax revenue. When solving the model as such - no internet, benchmark solution - the author findsa Nash equilibrium in which the high-tax state town sets a lower local sales tax than the low-taxstate town. To account for the tax haven hypothesis, Agrawal introduces a fraction of population tohave access to the untaxed online commodity - hence escape from taxes revenue - and thus createsa downward pressure on tax rates. The high-tax state locality will however lowers its tax rate rel-atively less, as it was already pressured by lower prices outside. Unsurprisingly, two notable factorsmodulate this asymmetry in response: the magnitude of the tax di↵erence between states and thecost of cross-bording. Finally, the author proposes a model for the anti-haven e↵ect of internet, byassuming that online shopping, even taxed, can be preferred by consumers because of their intrinsicpreferences. Hence, consumers that would have crossed the border previously now shop online, whichcreates an upward pressure on tax rates, which is similar across localities. In a last theoretical step,Agrawal examines the asymmetrical e↵ect of internet on taxes with regard to town size; to isolatethis e↵ect, he assumes similar state tax rates between towns and find that untaxed online purchaseaccess lowers local tax rates in small localities less than in large ones, as its tax base is relatively small.

To test which hypothesis is better-suited, the author confronts the predictions to empirical data.Concerning taxes, the Pro Sales Tax’s national database records sales tax rates at town, county, dataand district level. Agrawal restricts the sample to states with municipal sales taxes, identified in Cen-sus Places from 2010 American Community Survey (ACS), and as cross-section from 2011. Concerning

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Internet penetration, he obtains data from July 2011, using the National Broadband Map, collected bythe National Telecommunications and Information Administration (NTIA) and the Federal Commu-nication Commission. As robustness check, he instruments Internet through lightning density, whichis measured by flash density using the National Oceanic and Atmospheric Administration’s SevereWeather Database, from 1996 to 2011.

The empirical methodology follows two steps. A baseline specification is first conducted as a cross-sectional OLS regression of tax rates on Internet usage - as such and interacted with town size -,geographic, political and demographic controls, and including state fixed e↵ects; the Internet usage isbest (highest R2 in univariate regression) proxied by access to � 4 providers , but alternative measure,such as a combination of Internet related variables, are used as robustness checks. The first results areconsistent with a downward pressure on tax rates, as ”a one standard deviation increase in Internet

penetration lowers local tax rates by 6% of average rate”. To correct for the constraints on the taxrates (between 0 and 1), the author implements a fractional response model, which leads to similarresults and is preferred for subsequent analysis. As verification, he runs a Tobit setup - as long asdi↵erent response functions specification, e.g. Cauchy distribution - and finds consistent estimates.Extra robustness checks include di↵erent sets of controls and county fixed e↵ects; the significance ofthe coe�cient indicates that results are not driven by omitted variables common to counties. Finally,as an alternative to the population x Internet penetration interaction term, and to account for theasymmetry in response depending on the size, Agrawal splits the sample between small and largejurisdictions (divided w.r.t median, alternatively mean). As predicted, the response in small towns isnot significantly di↵erent from zero, while the response in large localities is of greater magnitude.

The second step of identification focuses on a discontinuity approach, as the state sales tax ratediscontinuously changes at the border. Hence, the only omitted spatial threat to identification wouldnow require to have asymmetric e↵ects on local tax rates depending on the locality state. The speci-fication now includes distance to the border, as such, interacted with a high-tax state dummy - whichallows the e↵ect of distance to vary asymmetrically between high and low tax state localities - in-teracted with the internet variable and with both the internet variable and high-tax state dummy -which once more allows the e↵ect of distance to vary not only w.r.t distance to the border but alsoasymmetrically between high and low tax state juridictions. For all of these terms, a cubic polynomialis included rather than the usual linear term. Note that the author verifies that the observable controlvariables do not change at borders; almost none of them do. The results are once more consistentwith theory: Internet e↵ect is mainly significantly negative for low-tax state; the results are strongerwhen focusing only on large towns; the closer to the border, the bigger the asymmetry of the response;the smaller the state tax di↵erence, the smaller the response. The analysis is reproduced at a countylevel - as well as inside metropolitan statistical areas (MSA) - and finds similar results. To check thatthe e↵ect is driven by di↵erence in Internet penetration rather than a border e↵ect, a placebo test isperformed for towns in di↵erent counties but find similar e↵ect of Internet on tax. As a final step, hecreates a dummy for states that have above average firms with nexus - using (partial) data from Bruce,Fox and Luna (2014) -, which he interacts with all the Internet terms in the discontinuity design; hefinds that for towns with above average e-firms with nexus, a positive e↵ect of internet on tax ratescan be observed. Hence, the empirical findings seem to be in accordance with the theoretical predic-tion, with the haven e↵ect to be prevalent on average, but the anti-haven e↵ect to be observable as well.

2 Contribution to Literature

Tax competition is not a new topic in public finance and economics literature. An arguably first modelof tax related migration dates back to 1956, with Tiebout theory of the welfare enhancing auto-sortinghouseholds mobility. More critical on tax competition, Oates (1972) properly opens up the way to taxcompetition theory, modeling a Nash equilibrium resulting in a suboptimal tax rates because of in-tergovernmental competition - finding still used as an argument against tax havens. Many theoretical

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papers followed, including Nielsen (2001) on which Agrawal bases his model. He adds the tax evasionpossibility o↵ered by e-shopping. Although standard literature models behavior of contributors andadds costs of tax avoidance, as proposed by Slemrod (1994) for instance, demand is simply inelastic inthis model. In that sense, Agrawal takes a step backward from literature. One could argue the reasonto be avoiding unnecessary complexification of the model. We will however discuss that element inthe following section. As a result, only the revenue leakage function is modeled, and specified as analready used specification forms. Maybe a more daring contribution in the theoretical part concernsthe anti-haven e↵ect, for which Agrawal assumes preferences to shop online. Nevertheless, once more,no micro-based model is set to describe the consumer preferences or choices.

The article tackles another sensitive issue, that is tax avoidance. Tax havens are a well-knowntopic in public finance literature, but their e↵ects are still discussed. If tax havens are generally viewedas bad, since they increase tax competition, which leads to a decrease in welfare (see e.g. Slemrodand Wilson, 2009). Other scholars modulate this results, like Johannesen (2010) that argues thattax havens diminish attractiveness of the competed prize and hence could lead to an increase in taxrevenues. Further empirical evidence from Desaia, Foleyb and Hines (2006) would indicate that taxhaven stimulate investments, promoting in fine growth; this positive enlightement on tax havens isdeveloped further by Hines (2010). The paper relates largely on that literature by its setup, as e-commerce can be viewed as a tax-leakage, hence becoming virtually and practically a tax haven.

Arguably, the contribution is more empirical than theoretical. If tax competition is quite an oldissue, both theoretically and empirically, e-commerce is not. Yet, many empirical papers already triedto tackle this issue, by linking internet and tax. However, the recent literature emphasized the e↵ectof tax on internet purchase, studying the change in consumer behavior under these new technologyopportunities. We could for instance cite Goolsbee (2000), Ballard and Lee (2007) or Einav et al.(2014). Some other papers investigate the revenue consequences of the aforementioned e↵ect, such asBruce and Fox (2000) or Alm and Melnik (2012). However, none of them studies the e↵ect of onlineshopping on taxes.

This issue is nonetheless central in both media and academic world. Notably, taxation debates areand always have been a sensitive topic in media, as it constitutes more than an economical question, apolitical issue and concerns every citizen (and non-citizen). The debate on technology and its influenceon growth, employment and poverty is also famous - or maybe infamous. Dating back to industrialrevolution, the place of technology in the economical development has aroused passions for a longtime. Quite naturally, the mixed issue of tax and technology surely interests media.

Even more light has been shed on this issue recently in U.S. media, as the Marketplace Fairness

Act was discussed. This bill would require online firms that have no physical presence in any state (nonexus) to still pay the sales and use1 taxes to states in which they provide consumers. If the debatedates back to 2013, the news page of the o�cial website2 indicates that the question is still actual -and that tweets about it are still trending and numerous.

More than the popular and trending topic examined, the tax policy implications of the paper canbe underlined. As the paper does not rely on empirical evidence only, but is backed up by theory, themechanisms at stake are salient, meaning that not only do we know what e↵ect internet penetrationhave on taxes, but also we have an insight on how it is a↵ected. As the relation is complex - dependson the relative quantity of firms with or without nexus in the state, the size of the town, its locationand its neighbors - the reliance on theory seems necessary; it does contribute to validate the theoret-ical framework as each mechanism at stake seems to be validated by one or the other specifications.Hence, one could argue that Internet is not necessarily a tax haven, as anti-haven e↵ects are empiri-

1although discussed in the paper, this tax was not explained in the above summary, as it is indicated that it is largely

under enforced, leading to practically no e↵ect, for our analysis at least

2see http://marketplacefairness.org/news/

last consultation on the November 16, 2014

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cally observable as well. Overall, general conclusion can be drawn as the dominant e↵ect depends onthe nature of the locality - its size, state, firms composition, etc. We note the tax haven e↵ects seemshowever dominant in most of the cases; yet, even as such, conclusions from former empirical workdiscussed above could be recovered.

The magnitude are also of similar size throughout the paper, which reassure the faith in theirconsistency and relevance. All and all, the paper is quite strong in addressing a new issue by using oldmethods and theories. If nothing is really revolutionary in methodological matters - no breakthroughon instrumental variables or never-used-before specification and econometrical methods - the findingsare still relevant to both social and academic interests.

3 Weaknesses and Main Issues

Overall, both theoretical and empirical procedures are well rooted and strongly backed up by previousanalysis. However, some elements can be qualified as missing or not very convincing. In a theoreticalmatter first, it is interesting to note once more that behavior of consumer is not properly modeled.Although the indi↵erent consumer is properly defined, and implicit micro-based theory is used, con-sumer preferences are not specified.

Specifically, inelastic demand is assumed; as the results concern tax variations, a price variationmay occur, leading the inelastic demand assumption to be used. It is nevertheless not really credible,especially when the author cites Einav et al. (2014) contribution to the field. Einav et al. (2014)indeed measures the online shopper sensitivity to sales taxes and find ”a price elasticity of around -2

for interested buyers”, which is a substantial value. At first glance, it would be particularly interestingto conduct an analysis of elastic demand of consumers - at least online shoppers - in the anti-havensetup. As we expect an increase in tax rates, prices are expected to raise, and the beneficial e↵ectsfrom more local buyers through online shopping (less cross bording) could be o↵set by the decrease indemand due to the increase in prices. Potentially, local jurisdictions could endogenize that responseand potentially not increase their tax rates, or at least not as much as predicted by the theory exposedin the paper.

A second concern could raise from the measure of internet penetration. Let us recall that both thebaseline and discontinuity specification include internet penetration - that is an indication of onlinepurchases, that cannot be included as such on pain of endogeneity - this measure has to be proxied.As explained previously, given the di↵erent variables of his database (any access to internet, speed ofconnexion, number of providers) the author first uses the variable that maximizes the univariate re-gression R

2 when regressed on state-level Internet usage from the Consumer Population Survey (CPS).His second measure is a combination of available mentioned data, following Lubotsky and Wittenberg(2006). His final strategy is to IV internet usage from a weather based variable, that is, lightningstrikes, arguing that ”power disturbances increase the cost of investing in IT, which then lowers IT

investment and Internet usage”.

If all the methods have precedents in literature, their relevance is here arguable. The first univari-ate R2 argument is convincing, although it relies on pure empirics and no real theory: why would fouror more providers be a better measure than three or more providers? - the argument of competition toexplain quality, price and in fine access to internet is strong, but the exact variable chosen could justbe a matter of sample, for which the R

2 was by chance maximized. Still, the method has precedentand the argument stays somewhat valid.

The same cannot be said concerning the IV used. The author acknowledges that ”lightning may

be correlated with weather conditions or topographical features, which are unlikely to be correlated with

tax rates unless weather related amenities influence public good preferences”. Yet, it seems logical for

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the weather condition to be directly correlated to public good demand! Indeed, when a town is subjectto more lightning strikes, more public investment should be made in infrastructure that could bothprevent or stand lighting strike damages. This requires more taxes. Hence, the instrument used doesnot fulfill the exclusion condition and should not be implemented. Even though it merely reflects onemore robustness check, it should not have any value on the consistency of the results and should notbe accounted for.

The main issue - that is usually corrected by IV - is simultaneity in the specification. It is indeedprobable that the sales tax rates influences the quantity of internet providers, as well as the otherInternet related variables. Competition is likely to be fiercer in low-tax environment; even if the In-ternet providers were not to be levied directly according the sales tax rates, the general fiscal systemof the state would be correlated to the sales rate, and which would influence the quantity of Internetproviders. Hence, the dependent variable would have an e↵ect on the independent variable, whosecoe�cient is of interest; i.e. reverse causality bias. Let us note that he argument that makes otherinternet related variables relevant for the co-proxying in the second measure of Internet penetration,also discredit them as exogenous. As explained above, the IV methodology used here is not a viablesolution to this issue, as the exclusion restriction could be not met.

Another minor issue could also arise from the ”split sample” analysis. As described previously,Agrawal argues that the ”split sample approach is preferable to interacting I with the log of popula-

tion” and divides the sample above and below the median of the population by localities. He thenassesses that: ”the sub-sample of “large” towns contains 97% of the population from the full sample;

this suggests this subsample analysis is still economically meaningful and applicable”. However, theanalysis is conducted on both sub sample: small and large towns. The e↵ect from small towns istheoretically predicted to be negligible, and the empirics indeed find insignificant coe�cients. Yet, thesize of the sample let us doubt whether the sub-sample of small towns is representative. It follows that,even if it is true that the results are not inconsistent with the theory, they are not properly consistentwith it neither, as they should not have indicative value because of the small size of the selected sample.

4 Further Research

Although already quite dense, some further analysis could have been, or should be, conducted. Thefirst obvious step forward would be a welfare analysis. As argued before, the issue treated in the pa-per is a peculiar public issue, that relates to multiple social matters, such as inequalities, governmente�ciency or public investments. A welfare analysis could be particularly adapted as the specificationtested relies on a proper theoretical model. The straightforward analysis would simply concern thechange in revenues of localities compared to the change in prices (implicitly, the change in consumersurplus). However, the assumption of preferences for online shopping per se raises the question of otherelement entering the consumer surplus, such as higher diversity of goods, or even higher e�ciency ofpurchasing due to broader availability of information. Furthermore, as discussed above, a behavioralmodel for the consumer could be required. From then, the author could estimate the change in localrevenues due to internet penetration, by identifying change in demand, allocation of demand - foreign,online or local - and change in taxation.

Another interesting factor in the welfare analysis would be the distribution of internet access andits influence on price discrimination. If internet is perceived as a tax havens, which in fine wouldincrease tax rates, and is furthermore accessible to the richer class rather than randomly assigned, itcan become a regressive taxation system and would be socially unacceptable - rich people have accessto tax-free goods whereas poorer consumers deal with sales tax. On the other hand, if tax-free onlineshopping is preferred by consumers that have more time, whereas richer citizens prefer going to anearby store, internet would be seen as a tool towards e�ciency - would tend to equalize marginalcost of time and money for both parties. Finally, no matter the assumptions, e-commerce allows for

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price discrimination - online auctions, or di↵erences in tax rates - which could lead, to some extend,to increased e�ciency. Once more, it could be interesting to model the consumer behavioral maxi-mization, to allow for elastic demand and perform a more relevant welfare analysis.

Another behavioral model could concern the governments. In the paper, the author considers bothlocalities to maximize the tax revenues - in a Nash game setup. It could be interesting to considerother objective, especially for small towns. Agrawal acknowledges this element when referring to”less sophisticated” small jurisdictions, that would then be ”less strategic” in their taxation behavior.Without rushing into the rent-seeking breach of political economy, we could imagine a case wheresmall localities have a fixed revenue they try to achieve. The other analysis, at the other extreme ofrationality, would obviously be the benevolent government that tries to maximize the overall surplusof their town. A final step could be to consider both competition and cooperation equilibrium in theNash game, with or without internet, to make final policy implications.

Finally, regarding the empirics, it could be interesting in future exploitation of data to use a paneldata setup. If at the time of the publication, internet related variables were available only as cross-sectional, future availability could lead to an analysis allowing for town fixed e↵ects, removing almostany risk of omitted variable bias, except time-varying factors that would influence towns asymmetri-cally across border. We could argue that technology-acceptibility as part of the behavioral preferencesof the citizens could constitute such a factor: it depends on the initial levels of technology but is timevarying; it could be regional but evolves di↵erently across border, especially in the case of small vs.large jurisdictions, or as a general trend the would be state specific (but once more time-varying). Inthat case, panel data would not be the perfect solution. It would however reinforces the findings ofthe paper by narrowing the possible biasing unobservables.

References

[1] Alm, James, and Mikhail I. Melnik, 2012, ”Cross-border Shopping and State Use Tax Lia-bilities: Evidence from eBay Transactions”, Public Budgeting and Finance, 32(1): 5–35.

[2] Ballard, Charles L., and Jaimin Lee, 2007, ”Internet Purchases, Cross-Border Shopping, andSales Taxes”, National Tax Journal, 55(4): 711–725.

[3] Bruce, Donald, and William F. Fox, 2000, ”E-Commerce in the Context of Declining StateSales Tax Bases” National Tax Journal, 53(4): 1373–1388.

[4] Bruce, Donald, William F. Fox, and LeAnn Luna, 2014, ”The E↵ect of State Tax Policieson Where E-Tailers Collect Sales Tax”, University of Tenessee Working Paper.

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[9] Johannesen, Niels, 2010, ”Imperfect Tax Competition for Profits, Asymmetric Equilibirum andBeneficial Tax Havens”, Journal of International Economics, 81: 253–264.

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[10] Lubotsky, Darren, and Martin Wittenberg, 2006, ”Interpretation of Regressions with Mul-tiple Proxies”, The Review of Economics and Statistics, 88(3): 549–569.

[11] Nielsen, Søren Bo, 2001, ”A Simple Model of Commodity Taxation and Cross-Border Shop-ping”, The Scandinavian Journal of Economics, 103(4): 599–623.

[12] Oates, Wallace E., 1972, Fiscal Federalism, New York: Harcourt Brace Jovanovich.

[13] Slemrod, Joel, 1994, ”Fixing the Leak in Okun’s Bucket: Optimal Tax Progressivity WhenAvoidance Can Be Controlled”, Journal of Public Economics, 55(1): 41–51.

[14] Slemrod, Joel, and John D. Wilson, 2009, ”Tax Competition with Parasitic Tax Havens”,Journal of Public Economics, 93(11-12): 1261–1270.

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