Munich Personal RePEc Archive
Short and long run income elasticity of gambling tax bases: evidence from Italy
di Bella, Enrico and Gandullia, Luca and Leporatti, Lucia
University of Genova
September 2014
Online at https://mpra.ub.uni-muenchen.de/73757/
MPRA Paper No. 73757, posted 20 Sep 2016 18:29 UTC
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Short and long run income elasticity of gambling tax bases: evidence from Italy
Enrico di Bella - Luca Gandullia - Lucia Leporatti1
Abstract
In periods of econom ic recession and budget const raint s, it becomes essent ial for t he government s t o underst and w hich t ax revenues are more likely t o guarant ee a st able or increasing amount of revenues able t o support t he provision of main public services w it hout depending t oo much on variat ion in Gross Domest ic Product (GDP).
The aim of t his paper is t o analyze a part icular source of t ax revenues in It aly, namely gambling t ax revenue split by game t ype (i.e. Lot t o; Lot t eries; Ent ert ainment machines), in order t o underst and how t ax bases react t o changes in income, providing a measure of short run (variabilit y over t he business cycle) and long run (grow t h) income elast icit y of different gambling t ax revenues. Result s show t hat gambling act ivit ies t end t o be im pressively react ive t o variat ion in income in t he long run, and, on t he cont rary, not part icularly volat ile in t he short run.
Keyw ords: dynamic ordinary least squares, error correct ion models, excise t axat ion, gambling t ax revenue, income elast icit y of t ax base.
JEL Classification: H21, H27, H60, C10
1. Introduction
M ost of w est ern count ries are facing dramat ic economic problems, mainly caused by t he economic recession of current years w hich has seriously reduced t he Gross Domest ic Product (GDP) grow t h levels and increased unemployment and povert y. This fact is rising t he effort s of government s t o find out addit ional financial resources t o cope w it h t he increasing social cost s of economic crisis (e.g. subsidies t o w orkers and firms) and t o guarant ee t he provision of necessary services (e.g. educat ion, healt h care).
1 Enrico di Bella, Universit y of Genoa, It aly: edibella@econom ia.unige.it Luca Gandullia, Universit y of Genoa, Italy: luca.gandullia@unige.it Lucia Leporat ti, Universit y of Genoa, It aly: lucia.leporat t i@unige.it
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In addit ion t o t his phenomenon, in Europe, count ries belonging t o t he Economic and M onet ary Union (EM U) are subject ed t o st rict budget const raint s im posed by t he St abilit y and Grow t h Pact2 (SGP) w hich limit s t he decision possibilit ies for government s in t he field of fiscal policies, reducing t he opport unit ies of resort ing t o public debt and fiscal deficit as means of financing.
In addit ion t o t hese t w o phenomena, several European count ries are already subject ed t o high level of fiscal pressure especially on income and general consumpt ion; t his fact makes impract icable a furt her increase in t ax rat es. Therefore, government s are t rying t o find addit ional financial resources from t axes ot her t han income and sales ones. Among alt ernat ive sources of t ax revenues, sin t axes (i.e. t axes levied on socially proscribed goods and services, as alcohol, t obacco, candies, soft drinks, fast foods, gambling) are looked w it h int erest by government s as t hey are usually perceived by t he populat ion as " volunt ary t axes" due t o t he fact t hat t hey w eight only on consumers of sin goods and t hus t hey are more accept able t han t axes on w idely consumed goods (Fox, 2010; Clot felt er and Cook, 1991).
In t he macro-economic environment , It aly does not make except ion, recording impressively low GDP grow t h level, high level of public debt (alm ost 130% of GDP in 2012) and dramat ically high fiscal pressure (in 2012 fiscal pressure in It aly account ed t o 55% for each euro). As a consequence, like ot hers European count ries, It alian government st art ed t o look for alt ernat ive t ax revenues and it ident ified gambling as a possible precious source of resources.
As a result , during t he last t en years (2003-2013), It aly experienced a big promot ion of gambling act ivit ies by means of t he government w ho has t he monopoly of t he sect or. Generally, t he st rat egy of t he government w as t o increase gambling possibilit ies t hrough t he int roduct ion of new t ypes of games subject ed t o low t ax rat es in order t o boost demand for gambling and t o rise t ax revenues.
Before 2003, t he number of legalized games in It aly w as st ill limit ed3: in addit ion t o t he 4 casinos present in It aly (i.e. Venice,Sanremo,Campione d'It alia , Saint -Vincent ) popular games included Lot t o, a lim it ed number of lot t eries, Sport Bet t ing, Superenalot t o and Bingo. How ever, in 2003, Law 269/ 2003 legalized a new t ype of gambling act ivit y dest ined t o gain great success: slot machines. The int roduct ion of slot machines represent ed a great innovat ion in gam bling market as it brought gambling among ordinary people, due t o t he fact t hat , aft er 2003, slot machines can be placed in cafe, t obacco shop, st at ions and supermarket s w it hout being confined t o casinos;
2 The SGP is represented by a set of rules in t erm s of fiscal deficit and public debt t hat should be sat isfied for all M em ber St ates and t hat have been est ablished in order t o m ake public finances sust ainable over t he cycle.
3 For a short descript ion of t he games see Appendix 1.
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t herefore, gambling consumpt ion became a const ant presence in rout ine life for m ore and more people.
Aft er 2003, t he great expansion of gambling cont inued, w it h t he progressive legalizat ion of ot her gambling product s: on-line games have been progressively liberalized in t he period 2008-2011, several inst ant lot t eries have been int roduced in 2009, Video-Lot t eries in 2010, Online Poker in 2011.
It is t hus evident t hat , in Italy, t he government obt ained a huge development of gambling indust ry t hrough an increase in gambling t ax base: t his t arget w as pursued t hrough a massive increase in available games and operat ors in t he market and t hrough a sim ult aneous reduct ion in t ax rat es on recent ly int roduced games.
How ever t he huge development of gambling market inflamed t he debat e on moralit y of gambling promot ion by t he government. Indeed, even if gambling is not coercive, t he gains in t ax revenues are not devoid of social cost s: t he number of people devot ing a significant amount of money in gam bling product s is increasing w it h t he amount of available public games: t hus t he issue of problemat ic gamblers is becoming a more and more serious problem. In addit ion, many st udies showed t hat gambling t ends t o be more problemat ic am ong poorer individuals w ho are more fascinat ed by t he hope of a life change (e.g. Clot felt er, 1979; Kit chen and Pow ells, 1991; Combs et al., 2008 Beckert and Lut t er, 2009). All t he aforesaid issues gave rise t o a debat e on t he moralit y of st at e in t he legalizat ion and, above all, prom ot ion of gambling (Smit h, 2000); Vit i de M arco et al. (1936), already in 1930s, invest igat ed t he inconsist ent role of t he government in gambling market , st at ing that t he st at e has, at t he same t ime, t he dut y t o fight against t he vice from w hich it can derive a big profit .
Despit e t he rapid development of gambling m arket , in It aly t he lit erat ure on gambling fiscal syst em is st ill lacking. To t he best of our know ledge only one st udy (Sart i and Trivent i, 2012) focused t he at t ent ion on It alian gambling fiscal syst em st udying t he pot ent ial regressivit y of gambling t axat ion; how ever, no st udies have been developed on t he specific charact erist ics of fiscal syst em spit by game t ypology.
The aim of t his paper is t o t ry t o fill t his gap, t hrough t he st udy of t he evolut ion of gambling market in It aly, analyzing some charact erist ics of gambling fiscal syst em in t his cont ext of market development . In part icular w e w ill focus t he at t ent ion on t he charact erist ics of gambling t ax revenues in t erms of grow t h and variabilit y over t he business cycle, t rying t o underst and if gambling t ax revenue represent s a significant alt ernat ive source of t ax revenue for t he government and if it is a st able and predict able source of revenue in t he short and long run. In order t o do so, w e w ill comput e some measures of income elast icit y of different cat egories of gambling t ax revenues (i.e Lot t o, Inst ant Lot t eries, Ent ert ainment M achines) using dat a of t he It alian M inist ry of Economy and Finance (M EF) under a short and long run perspect ive.
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The paper is organized in 6 sect ions; aft er t he int roduct ion, t he second sect ion review s t he lit erat ure on t he t opic; t he t hird one analyzes t he evolut ion of gambling market in It aly; t he fourt h and t he fift h provide t he met hod and t he empirical result s of our m odeling. The paper ends w it h conclusions and policy implicat ions.
2. Literature Background
Tradit ionally t w o element s are considered in t he evaluat ion of a t ax syst em:
efficiency and equit y. How ever, in addit ion t o t he t w o aforesaid element s, Clot felt er (2005) ident ifies adequacy and st abilit y as import ant issues t o be considered by pract ical-minded t ax analyst s. A t ax sat isfies adequacy principle if t ax revenues collect ed are relevant w it h respect of t ot al am ount of t ax revenues. When considering gambling t ax revenue t his is a difficult condit ion t o be sat isfied as generally gambling revenues represent a definit ely small amount of t ot al t ax revenues; how ever, Clot felt er (2005) show s t hat It aly and Aust ralia make except ion as gambling t ax revenues, in 1999, account ed t o m ore t han 1.5% of t ot al t ax revenue (in det ail t o 2.4%
for It aly), and t hus t hey w ere a relevant source of t ax revenue. According t o our est imat ion based on dat a provided by t he It alian M inist ry of Economy and Finance (M EF) t he percent age of gambling t ax revenues (Lot t o + Inst ant Lott eries + Ent ert ainment M achines + Ot her Games) over t he t ot al amount of t ax revenues in It aly is increasing over t ime and, in 2013, it account ed t o 2.87% making gambling a more and more import ant source of revenue for t he It alian government .
In addit ion t o adequacy, government s are oft en int erest ed in t he long and short t erm variabilit y of different t ax bases and in how t hey are affect ed by variat ion in income. Indeed, in periods of financial dist ress, it is import ant t o underst and on w hich resources t he government can rely in t he short run (cyclical variabilit y of t ax revenues) and on w hich it can rely under a long run perspect ive (t rend grow t h rat e of t ax revenues). From a short run perspect ive, government s are int erest ed in guarant eeing t he qualit y and quant it y of public services offered, and, in order t o do so, t hey need a st able amount of t ax revenues able t o finance properly fundament al public services.
On t he ot her side, w hen focusing on long run purposes, government s aim at maximizing t ax revenue grow t h in order t o improve t he public services provision and qualit y.
How ever, st abilit y of revenue and grow t h are not alw ays compat ible; some aut hors (e.g. Fox and Campbell, 1984) point ed out t hat t here is a t rade-off bet w een t ax revenue grow t h in t he long run and st abilit y of t ax revenues in t he short run, w hile ot hers (Dye and M cGuire, 1991) find t hat somet imes grow t h and st abilit y can be direct ly correlat ed; indeed in principle, high long t erm grow t h can be compat ible w it h
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short -t erm st abilit y (W olsw ijk, 2009). As st at ed by Groves and Kahn (1952) a fair t axat ion system is one t hat ensures t o t he government an approximat ely const ant amount of revenue over a t ime period and t hat t hus permit s t o finance major public services w it hout depending t oo much on t he business cycle condit ions.
In order t o measure t he impact of variat ion in income on gambling t ax base a commonly used approach is by t he use of t w o measures (one for t he short run and one for t he long run) of income elast icit y. In part icular, more income elast ic t ax bases are more likely t o grow fast in t he long t erm because, as income increases, t he t ax base w ould increase more t han income (Groves and Kahn, 1952). In addit ion, high incom e elast ic t axes in t he short run w ould experience fluct uat ions of t ax base over t he business cycle, making t he t ax base, and consequent ly t he t ax revenues, unst able and uncert ain. Different measures and economet ric t echniques have been proposed in t he lit erat ure t o est imat e t he short and long run income elast icit y of several t ax bases.
The first st udy in t his direct ion w as proposed by Groves and Kahn (1952) w ho comput ed a measure of income elast icit y for local t axes for several USA st at es. If w e consider a t ime period bet w een and , income elast icit y of a t ax base is defined as t he rat io bet w een t he percent age change over t he period of t ime in t ax yield T and t he percent age change in income Y during t he same period of t ime:
= (
−
) [ (⁄
+ ) / 2](
−
) [ (⁄
+ ) / 2] (1)w here t he numerat or of equat ion 1 represent s t he rat io bet w een change in t ax yield bet w een and and t he average t ax yields bet w een t he t w o periods, w hereas t he denominat or represent s t he rat io bet w een change in income bet w een and and t he average income of t he t w o periods.
Using t he value of income elast icit y as a benchmark, Groves and Kahn (1952) ident ified t hree t ypes of t axes depending on income elast icit y value:
1. income elast icit y less t han one: t hese t axes are the most st able as an elast icit y smaller t han unit y guarant ees t hat t ax bases fluct uat e less t han income.
According t o Groves and Kahn (1952) licences, propert y t axes and pool t axes belong t o t his cat egory;
2. income elast icit y close t o one: t hese t axes vary proport ionally w it h income, meaning t hat t hey are roughly unst able. Sales t axes are oft en considered in t his cat egory;
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3. income elast icit y bigger t han one: t hese t axes vary more t han proport ionally t o income. This means t hat t hey are st rongly unst able over t he business cycle.
Corporat e net income t axes usually have an income elast icit y bigger t han one.
Applications to general sales and income tax base
St udies based on t he Groves and Kahn (1952) approach have been developed, among t he ot hers, by Fox and Campbell (1984), Dye and M cGuire (1991), Sobel and Holcom be (1996), Bruce et al. (2006). M any aut hors focus t he analysis on different cat egories of sales t axes, finding out how income elast icit y varies over different goods.
Fox and Campbell (1984) analyze t he income elast icit y of t en t axable sales groups, finding out t hat differences exist over different groups. The main differences are observed among durable and nondurable goods; in part icular durable goods t ax base declines during economic recession and boost s in expansion period, w hile t he cont rary is t rue for nondurable goods. Ot her aut hors (Dye and M cGuire, 1991; Bruce et al., 2006) analyze t he elast icit y of income t axes in different USA st at es. Bruce et al., 2006 find out t hat flat and progressive income t ax base t end t o be more elast ic t han sales t ax bases, and t hus more unst able. How ever, not all t he st udies agree on t his conclusion; among t he ot hers, Fox and Campbell (1984) find out t hat cert ain income t ax bases can be more st able t han sales t ax bases. In addit ion, t he aut hors observe t hat income t ax bases t end t o fluct uat e less t han sales t ax bases over t he business cycle in t he short run. Bruce et al. (2006) perform a similar analysis on short and long run income elast icit y of sales t ax bases and incom e t ax bases, finding out t hat , overall, long run income elast icit y for personal income t ax base is more t han double t he one for sales t axes.
Research on t his t opic in Europe are lacking; Wolsw ijk (2009) proposes a st udy in t his direct ion applied t o t hree t ax cat egories (i.e. value-added t ax, personal income t ax and corporat e income t ax) in t he Net herlands. Result s show t hat short run elast icit y est imat es t end t o be different from long run ones, especially w hen t ax bases are below t he long run equilibrium. This means t hat economic agent s t end t o react slow ly t o variat ion in income, as responses are lagged and smaller in t he short run. In part icular , for w hat concerns value-added t ax (VAT) t he aut hor find out a long run elast icit y of 0.9, and t w o short run elast icit y est imat es (w hen t ax base are respect ively below and above t he equilibrium) of 0.64 and 1.10. This fact can be explained by a change in consumpt ion habit s t ow ards more basic (less taxed) goods during recession, and, conversely, by a shift t ow ards t he consumpt ion of m ore luxurious (and t hus t axed) goods during economic expansion. Different conclusions emerge for income t ax bases.
Personal income t ax (PIT) has been found t o have a symmet ric short run response and t o be more react ive in t he short run, experiencing a short run elast icit y bigger t han t he
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long run one (1.89 versus 1.57); t his can be explained by t he slow ness in employment adjust ment s. Last ly, corporat e income t axes (CIT) t end t o be more react ive in t he long run, recording a long run elast icit y bigger t han one (1.07) versus t w o short run est imat es of 0.12 (w hen t ax base is below long run equilibrium ) and 0.90 (w hen t ax base is above long run equilibrium).
Applications to gambling tax base
As w e already said, t he vast majorit y of st udies focusing on income elast icit y of t ax base focused t he analysis on sales and income taxes. How ever, t heoret ically, similar approaches can be applied t o any t ypes of t ax bases, including t he gambling t ax base.
Some previous researches focus t he at t ent ion on gambling t axat ion. In part icular, t he first st udy in t his direct ion has been proposed by Cargill and Eadingt on (1978) w ho analyze t he income elast icit y of casino gambling revenues in t hree regions of Nevada, finding out t hat gross casino gambling revenue is fairly elast ic and t hat t he est imat es vary across regions from 1.05 t o 1.75. A similar study has been performed for Brazil by Babbel and St aking (1983). A more recent research has been proposed by Nichols and Tosun (2008), w ho analyze t he long and short run income elast icit y of casino gambling revenues using quart erly dat a of 11 USA st at es and observing how gambling revenues differ from ot her t ypes of t ax bases (i.e. sales taxes and income t axes). The aut hors improve on previous st udies: indeed t hey use quart erly dat a as in Fox and Campbell (1984) but t hey ext end t he analysis t o more t han one st at e using a panel dat aset . In addit ion t hey use act ual t ax base rat her t han a proxy for it as in previous researches and t hey int roduced in t he model t hree variables t hat describe t he supply-side of casino gambling indust ry (i.e. number of slot s machines lagged t w o quart ers, num ber of t able games lagged t w o quart ers, seasonal dummies) t o t ake int o account t he specific charact erist ics of t he sect or. Nichols and Tosun (2008) find out t hat , in t he long run, gross casino revenues generally grow fast er t han ot her sales t ax bases but slow er t han income t ax base. For w hat concern t he short run, t heir est imat es on gambling elast icit y are usually low er t han est imat es for sales and income t ax base, meaning t hat gambling revenues t end t o fluct uat e less t han ot her t ax bases over t he business cycle.
3. Gambling in Italy: data and recent development of the market The development of gambling market
During t he last decade in It aly gambling market experienced a dramat ic boost : aft er t he liberalizat ion of 2003 w hich legalized new forms of gambling (i.e. slot s machines) t he amount of money devot ed t o gambling significant ly increased, leading t o an explosion of t he market .
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In It aly t hree main measures are used t o evaluat e gambling market : gross expendit ure, net expendit ure and t ax revenue. The gross expendit ure represent s t he t ot al amount of money t hat is devot ed t o gambling, w hich means t he t ot al amount of money bet , w hereas t he net expendit ure is t he net amount of money spent in gambling aft er subt ract ing t he payout (i.e. money t hat goes back t o t he consumer t hrough w innings). Thus:
= (2)
= (
−
) (3)It is evident t hat t hese tw o measures, even t hough highly correlat ed, provide different informat ion: t he first is a measure of t he global gambling market , w hile t he lat t er is a measure of t he im pact of gambling on households budget . In addit ion, for t he vast majorit y of games, gross expendit ure represent s t he t ax base on w hich t ax rat es are applied t o get t ax revenue.
The amount of t ax revenue is a furt her measure t hat should be considered w hen analyzing gambling market from t he government point of view as it represent s t he t ot al amount of econom ic resources t hat t he government gets from gambling act ivit ies. It has been show ed t hat t he dynamics of gambling t ax revenue is generally different from t he dynamics of gambling expendit ure due t o t he different t ax syst ems applied t o different games.
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Table 1: Gross Expenditure and its variation (2003-2012) split by game -dat a in millions of euro- (source: It alian Cust oms and M onopolies Agency)-
Table 1 and Figure 1 show how gross expendit ure evolved during t he last t en years: overall, t ot al gross expendit ure increased by 481% recording, in 2012, a t ot al amount of gross expendit ure of more t han 80 billions of euro; t his phenomenon w as mainly caused by t he change in t he government at t it ude t ow ards gambling, namely by t he int roduct ion of new games (e.g. slot machines) w hich boost gambling opport unit ies during everyday life. If w e analyze t he evolut ion of gross expendit ure split by game t ypology w e can see t hat t he games more responsible for gambling grow t h are t he m ost modern ones: in part icular slot s machines (slot s) and video- lot t eries (vlt s) (w hich w e w ill referred t o as " Ent ert ainment M achines" ) w hich have
Year Variable Lotto Superena
lotto Lottery Sport Betting
Horse
racing Bingo Slots and Vlt
Skill Games –
Online Poker
Total
2003
Total 6,938 2,066 282 1,123 2,974 1,257 367 - 15,007
% of total 46% 14% 2% 7% 20% 8% 2% - 100%
%∆( , − ) - - - - - - - - -
2004
Total 11,689 1,836 594 1,300 2,908 1,542 4,474 - 24,343
% of total 48% 8% 2% 5% 12% 6% 18% - 100%
%∆( , − ) +68% -11% +111% +16% -2% +23% +1,119% - +62%
2005
Total 7,315 1,981 1,546 1,488 2,820 1,553 11,470 - 28,173
% of total 26% 7% 5% 5% 10% 6% 41% - 100%
%∆( , − ) -37% +8% +160% +14% -3% +1% +156% - +16%
2006
Total 6,588 2,000 3,970 2,281 2,912 1,755 15,436 - 34,942
% of total 19% 6% 11% 7% 8% 5% 44% - 100%
%∆( , − ) -10% +1% +157% +53% +3% +13% +35% - +24%
2007
Total 6,177 1,940 7,955 2,591 2,748 1,726 18,827 - 41,964
% of total 15% 5% 19% 6% 7% 4% 45% - 100%
%∆( , − ) -6% -3% +100% +14% -6% -2% +22% - +20%
2008
Total 5,852 2,509 9,274 3,909 2,272 1,636 21,685 242 47,379
% of total 12% 5% 20% 8% 5% 3% 46% 1% 100%
%∆( , − ) -5% +29% +17% +51% -17% -5% +15% - +13%
2009
Total 5,664 3,782 9,434 4,026 1,981 1,512 25,525 2,348 54,272
% of total 10% 7% 17% 7% 4% 3% 47% 4% 100%
%∆( , − ) -3% +51% +2% +3% -13% -8% +18% +870% +15%
2010
Total 5,231 3,525 9,367 4,396 1,729 1,954 32,000 3,145 61,347
% of total 9% 6% 15% 7% 3% 3% 52% 5% 100%
%∆( , − ) -8% -7% -1% +9% -13% +29% +25% +34% +13%
2011
Total 6,800 2,400 10,200 3,910 1,370 1,850 44,900 8,420 79,850
% of total 9% 3% 13% 5% 2% 2% 56% 11% 100%
%∆( , − ) +30% -32% +9% -11% -21% -5% +40% +168% +30%
2012
Total 6,215 1,800 9,800 3,980 1,010 1,655 48,700 13,980 87,140
% of total 7% 2% 11% 5% 1% 2% 56% 16% 100%
%∆( , − ) -9% -25% -4% 2% -26% -11% +8% +66% +9%
Total
%Variation
(2003-2012) -10% -13% +3,375% +254% -66% +32% 13,170% +495% +481%
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been legalized respect ively in 2003 and 2010 and w hich experienced an average increase of 72% a year: t he gross expendit ure connect ed t o ent ert ainment machines (i.e. slot s + vlt s) became a more and more relevant percent age of t ot al gross expendit ure, moving from 2% in 2003t o 56% of t ot al gross expendit ure in 2012.
Figure 1: Gross Expenditure ( billions of euro) , Tax Revenues ( billions of euro),
% of Gambling tax on total Tax Revenues, Average Tax Rate - source: It alian Cust oms and M onopolies Agency -
On t he ot her side, expendit ure in games t hat have been int roduced earlier (i.e.
Lot t o, Superenalot t o) remained quit e const ant during t he last 10 years and became a less relevant percent age of t ot al gross expendit ure; gross expendit ure in Lot t o moved from 46% of t ot al expendit ure in 2003 t o 7% in 2012; in addit ion, expendit ure in horse relat ed games declined (-66%). The expendit ure in lot t ery t icket s increased t hanks t o t he great increase in inst ant aneous lot t ery t icket s available. Also online skills games and online poker, w hich have been legalized respect ively in 2008 and 2011 experienced a great expansion, w it h a t ot al increase of 495% in only 5 years.
The main reason for t he government t o promot e gambling is econom ic: t ax revenues deriving from gambling guarant ee t o the government a precious source of funds t hat can be used t o finance several public needs.
20406080100Gross Expenditure
2002 2004 2006 2008 2010 2012 Year
46810Tax Revenues
2002 2004 2006 2008 2010 2012 Year
11.522.5% of Total Tax Revenues
2002 2004 2006 2008 2010 2012 Year
1015202530Average Tax Rate
2002 2004 2006 2008 2010 2012 Year
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Table 2 and Figure 1 show some figures on gambling t ax revenue evolut ion. Tax revenues increased significant ly during t he t ime period (2003-2012) m oving from 3,5 billions of euro in 2003 t o more t han 8 billions in 2012 (+135%). If w e split t he analysis by game t ype w e can see (Table 2) t hat a big part of t he increase in t ax revenues derives from lot t eries, slot s and video-lot t eries. How ever, t he increase in t ax revenues is much low er t han t he increase in gross gambling expendit ure (overall, +135% t ax revenues versus +481% of gross expendit ure), and t ot al t ax revenues experience a reduct ion aft er 2010.
This phenomenon can be explained analyzing t he gambling t ax syst em (Giuricin, 2013). In It aly t he gambling t axat ion syst em is not homogeneous as different games have different t ax syst ems and t ax rat es (Table 3); for some games (i.e. Lot t o and Inst ant lot t eries) t ax revenues are derived from t he different ial bet w een t he t ot al amount of money bet by gamblers and t he money ret urned t o players as w inning. For all t he ot her games t he t ax base is represent ed by gross expendit ure; how ever, as it is show ed by Table 3, t ax rat es applied t o different games vary significant ly. In part icular recent ly int roduced games t end t o have low er average rat es t han older games: video- lot t eries have part icularly low t ax rat es (i.e. 4.00 %), w hile for slot s machines t ax rat es for t ax payers decrease if t ot al gross expendit ure is higher t han t he one obt ained t he previous year leading t o an incent ive for t ax payers t o boost demand. On t he ot her hand, older games t end t o be subject t o higher t ax rat es; for example Superenalot t o is subject t o part icularly high t ax rat es, namely 53.62 %.
This phenomenon of decrease in t ax rat es applied t o gambling is a consequence of t he change in t he government at t it ude t ow ards gambling. Fiasco (2011), a sociologist specialized in research on gambling in It aly at t he Nat ional ant i-Usury Council, ident ifies different st eps in government s behaviour on gambling regulat ion. During t he period 1992-2002 t he government w as focused on maximizing t ax revenues (t he so- called period of `generat e t ax revenues`): t herefore t he government t ried t o find t he equilibrium bet w een t axat ion level and demand. On t he cont rary, aft er 2003, t he main aim of t he government became t o increase market value (t he so-called period of
`generat e market value`) and t hus t o decrease tax rat es in order t o boost t he demand for gambling. For t his reason, new games have been subject ed t o low er t ax rat es, in order t o incent ivize demand t hat increases t ax revenues. As a consequence, t he t ot al amount of t ax revenues collect ed increased in absolut e num bers, but t he percent age revenues for each euro decreased.
12
Table 2: Tax Revenue and its variation (2003-2012)
-Dat a in millions of euro (source: It alian Cust oms and M onopolies Agency)-
Game Tax Base Tax Rates
Lot t o - Different ial
Superenalot t o Gross Expendit ure 53.62%
Lot t ery - Different ial
Sport Bet t ing Gross Expendit ure From 2.00% t o 33.84%
Horse racing Gross Expendit ure From 6.00% t o 15.70%
Bingo Gross Expendit ure 11%
Slot - VLT Gross Expendit ure From 4.00% t o 13.00 % Table 3: Tax base and tax rates by game (source: Chamber of Deputies, 2012)
Year Variable Lotto Superen
alotto Lottery Sport Betting
Horse
racing Bingo Slots and Vlt
Skill Games – Online
Poker
Total
2003
Total 1,565 1,100 114 297 144 251 33 - 3,504
% of total 45% 31% 3% 8% 4% 7% 1% - 100%
%∆( , − ) - - - - - - - -
2004
Total 4,919 976 219 222 141 308 513 - 7,298
% of total 67% 13% 3% 3% 2% 4% 7% - 100%
%∆( , − ) +214% -11% +92% -25% -2% +23% +1,455% - +108%
2005
Total 2,425 1,054 426 290 137 311 1,514 - 6,157
% of total 39% 17% 7% 5% 2% 5% 25% - 100%
%∆( , − ) -51% +8% +95% +31% -3% +1% +195% - -16%
2006
Total 1,959 1,013 891 291 141 351 2,072 - 6,718
% of total 29% 15% 13% 4% 2% 5% 31% - 100%
%∆( , − ) -19% -4% +109% +0% +3% +13% +37% - +9%
2007
Total 1,747 962 1,526 230 134 345 2,250 - 7,194
% of total 24% 13% 21% 3% 2% 5% 31% - 1
%∆( , − ) -11% -5% +71% -21% -5% -2% +9% - +7%
2008
Total 1,565 1,235 1,659 249 110 327 2,594 7 7,746
% of total 20% 16% 21% 3% 1% 4% 33% 0% 100%
%∆( , − ) -10% +28% +9% +8% -18% -5% +15% - +8%
2009
Total 1,591 1,736 1,663 218 97 270 3,165 70 8,810
% of total 18% 20% 19% 2% 1% 3% 36% 1% 100%
%∆( , − ) +2% +41% +0% -12% -12% -17% +22% +900% +14%
2010
Total 1,250 1,578 1,545 213 83 214 3,756 94 8,733
% of total 14% 18% 18% 2% 1% 2% 43% 1% 100%
%∆( , − ) -21% -9% -7% -2% -14% -21% +19% +34% -1%
2011
Total 1,737 1,081 1,330 184 66 231 3,916 103 8,648
% of total 20% 13% 15% 2% 1% 3% 45% 1% 100%
%∆( , − ) +39% -31% -14% -14% -20% +8% +4% +10% -1%
2012
Total 1,134 810 1,590 177 48 206 4,154 108 8,227
% of total 14% 10% 19% 2% 1% 3% 50% 1% 100%
%∆( , − ) -35% -25% +20% -4% -27% -11% +6% +5% -5%
Total
%∆
( , ) -28% -26% +1,295% -40% -67% -18% +12,488% +1,443% +135%
13
Therefore, average t ax rat e is significant ly changing due t o t he int roduct ion of new , less t axed, high-demanded games (Figure 1). In det ail, average t ax rat e4 decreased over t ime moving bet w een 2003 and 2013 from 23% t o 9%. Among games, lot t eries experienced a significant negat ive t rend in t he evolut ion of rat es: t ax rat es moved from 40% in 2003 t o 16 % in 2012. Even more int ense is t he drop in average rat e connect ed t o sport bet t ing: it decreases by 83 % in t en years.
Data on gambling in Italy
One of t he main lim it s of developing analysis on gambling in It aly is t he lack of easily available dat a on t he t opic. Different subject s are responsible for t he collect ion and processing of dat a on gambling. The main dat a source is t he It alian Cust oms and M onopolies Agency w hich is t he administ rat ion creat ed t o deal w it h t he responsibilit y of ruling st at e monopolies. In addit ion t o It alian Cust oms and M onopolies Agency ot her inst it ut ions provide dat a on gambling: specialized new s agencies (e.g.
Agipronew s, Agicos, Agimeg, Agicops), gambling aut horit ies, organizat ions dealing w it h pat hological gambling, It alian M inist ry of Econom y and Finance (M EF), It alian Inst it ut e of St at ist ics (ISTAT), It alian Ant i-Drug Depart ment (DPA) and t he Nat ional Research Council (CNR).
For w hat concern dat a useful for our analysis, w e are mainly int erest ed in dat a on gambling t ax revenues and t ax bases. In It aly dat a on gambling t ax revenue can be direct ly obt ained from t he It alian M inist ry of Economy and Finance (M EF) w ebsit e w hich report s, bot h by cash and com pet ence crit eria, t he amount of t ax revenues derived from Lot t o, lot t eries and ent ert ainment machines (i.e. slot s machines and video-lot t eries) at a mont hly level for t he period 1990-2014. In addit ion t o t his dat aset , a mont hly report is published by t he Court of Audit ors w hich permit s t o obt ain annual t ax revenues from 1995 t o 2013 w ell det ailed by game t ypology. The longest t ime series of t ax revenues can be obt ained by ISTAT w hich report s t he t ot al amount of indirect t ax collect ed by t he government split by t ax cat egory. Tax categories include four game t ypologies (i.e. Casino, Lot t o and lot t eries, sport bet t ing, horse racing, skill games and ot her bet s) for t he last 23 years (1990-2012).
On t he ot her side, a proxy for t ax base can be obtained by t he It alian Cust oms and M onopolies Agency w hich provides, on request , dat a on gross expendit ure at a mont hly level for t he last years and by game t ypology (i.e. Ent ert ainment machines, Bingo, Horse racing, sport bet t ing, lot t eries, Lot t o, Superenalot t o, skill games).
In t his paper w e w ill use dat a on t ax revenues provided by t he M EF aggregat ed at a quart erly level: t he dat aset report s, t he inflow s in several t ypes of t axes using cash
4 Average t ax rat e has been com put ed as t he rat io betw een the t otal am ount of t ax revenues and Gross Expendit ure
14
(1990-2001) and compet ence (2002-2014) crit eria. Previous st udies (e.g. Fox and Campbell, 1984) show ed t hat using quart erly dat a inst ead of yearly dat a brings some benefit s as it perm it s t o have more degrees of freedom. How ever, as gambling t ax revenues can be influenced by government decisions on fiscal syst em (e.g. change in t ax rat es, increase in t he number of licences, promot ion of gambling), some cont rol variables connect ed t o t he market should be included.
Table 4: Some descriptives of the variables
We consider t hree cat egories of gambling act ivit ies: lot t o, inst ant lot t eries, ent ert ainment machines5 (Table 4), w hich represent , in 2012, respect ively t he 14%, 19% and 50% of t ot al amount of gambling t ax revenues. Due t o t he lack of available dat a w e are not able t o use t ax bases for all game t ypes. In part icular, t ax revenues have been considered as a good proxy for t ax base for Lot t o as revenues for t he government on t hese game derived from t he difference bet w een money spent and money given back as w inning.
We inst ead use ent ert ainment machines and inst ant lot t eries t ax bases comput ing t hem as t he rat io bet w een t ax revenue and average t ax rat e for each year6: w e believe t hat considering t ax base rat her t han t ax revenue is part icularly import ant for t hese cat egories of gambling act ivit ies due t o t he import ant legislat ive reforms t hat impact on Inst ant Lot t eries and Ent ert ainment machines during t he last years; in addit ion, due t o t he great expansion of inst ant lot t eries aft er 2003 w e select as period of analysis for t his game only dat a relat ed t o t he last decade.
Figure 2 show s t he evolut ion of gambling and GDP t ime series over t he period considered. The t hree gambling series experienced different t rends: w hile lot t o revenues recorded only a minor grow t h over t he 23 year-period considered, ent ert ainment machines t ax base boomed im pressively during t he last t en years; on t he ot her side, inst ant lot t ery t ax base experienced a high grow t h level during t he period (2005-2008), w hile st abilizing in t he follow ing years (2008-2013).
5 Entert ainm ent m achines include slot m achines (slot s) and video-lot t eries (vlt s) revenues.
6 Average t ax rat es have been com puted as t he ratio bet w een t he t ot al am ount of tax revenues and Gross Expendit ure for each year (source of dat a: It alian Custom s and M onopolies Agency)
Tax Time period
considered
Number of observations
M ean per quarter
Standard
deviation Variable Lotto 1990q1-2013q4 96 1.49 billions 1.36e+09 Tax Revenue Instant Lotteries 2005q2-2013q4 35 1.77 billions 6.98e+08 Tax Base Entertainment
M achines 2004q2-2013q4 39 5.94 billions 3.02e+09 Tax Base
15
As measures of income w e used t hree different quart erly variables: market prices GDP, GDP per capit a, available disposal income7. Result s do not differ significant ly;
t herefore w e w ill present t he ones obt ained t hrough t he use of aggregat e GDP.
Figure 2: Yearly gambling time series considered in our models -dat a expressed in billions of euro (source: M EF- Eurost at )-
All variables have been convert ed in const ant euro using t he GDP deflat or and t heir nat ural logs are used in t he regressions.
4. Econometric specification
To empirically comput e t he income elast icit y of t ax bases, most of t he early st udies use a simple double logarit hm regression of t he form (Groves and Kahn, 1952):
ln( ) = + ln( ) + (4)
w here represent s t he t ax yield during t he period t and represent s t he income level during t he period t. Due t o t he logarit hm specificat ion, provides a measure of t he income elast icit y of a t ax yield.
The main limit at ion of such an analysis lays in t he fact t hat t his model does not make a dist inct ion bet w een short run and long run: in part icular, according t o t hese early st udies, provides, at t he same t ime, t he pot ent ial long t erm grow t h and t he short run variabilit y over t he business cycle. As already not iced by Sobel and Holcombe (1996) t his is not alw ays t he case as t w o t axes can share t he same grow t h pat t ern
7 The dat a source of all incom e measures is Eurost at
6008001,0001,2001,4001,600 GDP
01020304050
1990 1995 2000 2005 2010 2015
Year Lotto
Instant Lotteries Entertainment Machines GDP
16
w hile varying different ly over t he business cycle. In addit ion, from a met hodological point of view , t he est imat es comput ed using equat ion 4 are asympt omat ically biased w it h inconsist ent st andard errors. To solve t hese problems, w e decide t o follow an approach already used by ot her aut hors in similar cont ext s (e.g. Sobel and Holcombe, 1996; Bruce et al., 2006; Nichols and Tosun, 2008 ). In part icular Sobel and Holcombe (1996), using USA dat a covering t he period 1951-1991 on different t ypes of t ax bases, analyze precisely t he principal economet ric limit at ions affect ing earlier st udies (e.g.
Groves and Kahn, 1952) and propose some solut ions. First of all, in order t o produce unbiased est imat es of coefficient s t ax and income variables should be st at ionary. A variable follow ing a st at ionary process is one t hat t end t o ret urn t o a cert ain mean value over t ime. This means t hat , if a variable has a decreasing or increasing t rend it cannot be st at ionary and t hus t radit ional regression t echniques cannot be applied.
M ost macroeconomic t ime series are not st at ionary; how ever, w hen convert ed in first differences t hey become st at ionary; if t his is t he case, t he series are defined as co- int egrat ed, w hich means int egrat ed of same order. W it h co-int egrat ed series, economet ric models est imat e t he long and short run est imat es follow ing t he Engle- Granger t w o st ep procedure (1987).
The first st ep of t his approach is t he t est ing for variables st at ionarit y and t herefore for t heir level of coint egrat ion. In general, t o det ermine if a variable is st at ionary, t he Augment ed Dickey-Fuller t est (See Dickey and Fuller, 1979) is performed: a significant t -st at ist ic indicat es t hat t he variable is st at ionary, w hile an insignificant t -st at ist ic indicat es t hat t he variable is non-st at ionary. Several st udies confirm t hat t axes and income variables t end t o be non st at ionary (e.g. Sobel and Holcombe, 1996; Bruce et al., 2006; Nichols and Tosun, 2008). If t his is t he case, some correct ions should be used on t he est imat ion t echnique: first of all it is necessary t o divide t he analysis in short run est imat ion and long run est imat ion. Indeed, an est imat ion of income elast icit y of t ax base based on equat ion 4 w ould not t ake int o account short run fluct uat ions around t he t rend, and it t hus provides only an est imat ion for t he long t ime period. In order t o correct for t he non st at ionarit y of t he variables it is necessary t o t ransform t he variables int o st at ionary ones; t his can be done eit her adjust ing for a const ant t rend or t ransforming t he variables int o t he first difference form. The second approach has been show n t o be more effect ive in t his cont ext (e.g. Sobel and Holcom be, 1996;
Bruce et al., 2006; Nichols and Tosun, 2008).
This means t hat equat ion 4 for t he short run elast icit y, in presence of non st at ionary variables becomes:
∆
ln( ) = +∆
ln( ) + (5)17
w here represent s t he t ax yield during t he period t and t he income level during t he period t. In equat ion 5 all t he variables are expressed in first difference form denot ed by
∆
. In t his case, t he coefficient represent s t he short run income elast icit y of t ax base and it measures t he percent age change in t ax base provoked by a one percent change in income. A coefficient bigger t han one indicat es a t ax base t hat moves more t han income over t he business cycle w hile a coefficient low er t han one indicat es an opposit e sit uat ion. This measure is independent of t he long run elast icit y and it just provides a measure of how t ax base fluct uat es up and dow n due t o t he business cycle adjust ing immediat ely t o income variat ion.The problem of non st at ionarit y of t he variables has consequences also on long run est imat ion as it brings t o biased est imat ions of long run elast icit y w it h inconsist ent st andard errors. The bias in est imat ion derives from t he fact t hat est imat ed error t erms t end t o be correlat ed, leading t o a problem of serial aut o-correlat ion of t he error t erm. To solve t his problem, St ock and Wat son (1993) propose t he use of a dynamic ordinary least squares (DOLS) w hich consist s in t he inclusion in t he m odel of a proper number (usually five) of leads and lags of t he change in t he independent variable:
ln( ) = + ln( ) +
∆
+ (6)The number of leads and lags t o be included is usually select ed looking at t he Bayesian Informat ion Crit erion (BIC). This procedure removes coefficient bias and correct s for serial aut ocorrelat ion by using New ey-West correct ion for t he st andard error (New ey and West , 1986).
Sobel and Holcombe (1996) ident ify one last problem t hat can affect short run elast icit y est imat ion in t his cont est . Under a short run perspect ive, in any period t ax bases can be above or below t he long run equilibrium value. According t o t he aut hors, t w o non st at ionary variables t hat have a long run relat ionship w it h anot her one t end t o move back t oget her w hen t hey deviat e t oo much from each ot her. This means t hat , in any t ime period, t w o short run movement s coexist : on one side t ax base react t o income variat ion, w hile on t he ot her side t ax base adjust t o converge t o t he long run equilibrium value. This phenomenon is usually called error correct ion and it cont ribut es t o make short run est imat ion biased. To solve t he problem, an Error Correct ion M odel (ECM ) can be built t hrough t he inclusion of anot her variable in equat ion 6: t he addit ional variable show s how far w as t he variable from t he long run equilibrium values in t he previous period. The ECM permit s t hus t o capt ure bot h t he aforesaid short run movement s. The ECM equat ion is obt ained using a t w o st ep
18
procedure. First of all, model of equat ion 4 is est imat ed and t he connect ed residuals are comput ed. Than t he lagged once residuals are insert ed as an independent variable in model in order t o obt ain an unbiased short run income elast icit y est imat ion using:
ln( )
−
ln( ) = + ( ln(−
ln( ) ) + + (7)w here represent s t he disequilibrium bet w een short and long run elast icit y value. In equat ion 7 t he paramet er capt ures t he short run income elast icit y of t ax base, w hile measures t he size of adjust ment of tax base t o it s long run equilibrium value: it provides a measure of t he percent age of disequilibrium t hat is correct ed in every t ime period.
Some aut hors (e.g. Bruce et al., 2006) believe t hat a more appropriat e approach should consider an asymmet ric response of t ax base t o income variat ion depending on t he posit ion w it h respect t o long run equilibrium value. To allow for an asymmet ric react ion, Bruce et al. (2006) propose t o insert in equat ion 7 a dummy variable t hat assumes value 0 if t he short run t ax base is below it s long run equilibrium and value 1 if t he cont rary is t rue.
Δ
T = +Δ
+ + (∗ Δ
) + (∗
) + (8)w here
Δ
T andΔ
represent s respect ively t he difference bet w een t he logarit hm of t ax base and income at t ime and t he corresponding value at t ime−
1. Inequat ion 8 short run elast icit y and t he adjust ment paramet ers are est imat ed separat ely depending on t he posit ion respect t o long run equilibrium : in part icular, and represent t he short run income elast icit y w hen t ax base is respect ively below and above t he long run equilibrium. If is st at ist ically different from zero t his means t hat t he upw ard adjust ment w hen t ax base is below equilibrium is different from t he dow nw ard adjust ment w hen t ax base is above equilibrium. In addit ion, and represent t he size and speed of adjust ment t o t he long run equilibrium w hen t ax base is respect ively below and above long run equilibrium value.
5. Results
Table 6 show s long run est imat es of income elasticit y w hile Table 7-8 show s short run elast icit y est imat es.
As w e explained in paragraph 4, in order t o applied t he just described economet ric t echniques, t he first problem t o be analyzed is on t he st at ionarit y of t he variables.
Table 4 report s t he result s of t he Augment ed Dickey-Fuller t est (Dickey and Fuller,
19
1979): a significant value of t he st at ist ic indicat es t hat t he variable is st at ionary.
Result s show t hat Lot t o seems t o be st at ionarit y in level w hile all t he ot her variables are not st at ionarit y in t heir regular form. How ever, if w e consider variables in t heir difference form w e see t hat all variables are st at ionarit y, suggest ing t hat t hey are int egrat ed of order one. Therefore, for Lot t o cat egory w e w ill analyze result s of t radit ional m odels, w hile w e w ill deal w it h non st at ionarit y relat ed issues for Ent ert ainment M achines and Inst ant Lot t eries t ax base.
Variable Test for st at ionarit y in level
Test for difference st at ionarit y
Lot t o -8.914 (* * * ) -16.697 (* * * )
Inst ant Lot t eries -2.831 -5.969 (* * * ) Ent ert aim ent M achines - 1.627 -12.405 (* * * )
GDP -2.067 -10.326 (* * * )
Table 5: Augmented Dickey Fuller (ADF) Stationarity Test (* p<0.05; ** p<0.01; *** p<0.001)
In order t o account for t he great market expansion of gambling market w e decide t o include some cont rol variables in t he m odels follow ing Nichols and Tosun (2008) approach. Omit t ing supply-driven changes may lead t o om it t ed variables bias since gambling revenues can depend on fact ors ot her t han income (e.g. number of licences or machines). Among game cat egories t hat w e select ed w e can divide games in t w o main groups: t he first one composed by Lot t o w hich represent s t he most mat ure gambling market : indeed, Lot t o has been first int roduced in It aly long t ime ago: already during t he XIX cent ury Lot t o w as popular in several cit ies of It aly. Unlikely ot her t ypes of games, during t he last decades, Lot t o has not experienced huge incent ives and legislat ive reforms by t he government and t hus it has not been involved in t he great expansion of t he market . On t he ot her side, Ent ert ainment M achines (w hich include slot s machines and video-lot t eries) and Inst ant Lot t eries represent t w o recent ly int roduced booming market s, highly promot ed by t he government t hrough t he int roduct ion of more and m ore slot s machines, licences and lot t ery t icket s. These dist inct ions among games, make us select different controls variables t o t ake int o account t he single peculiarit ies of t he market s. In part icular w e include in all t he regressions seasonal dummies t o account for pot ent ial seasonal variat ions; in addit ion w e include some variables specific for each market : t o take int o account t he expansion of Ent ert ainment machines and Inst ant Lot t eries market w e include a variable report ing t he number of w orkers employed in Art s, Ent ert ainment , Recreat ion sect or (Eurost at Nace Classificat ion = R) as a measure of t he development of gambling
