The Impact of Unemployment Rate on the Dimension of Shadow Economy in Spain: A Structural Equation Approach

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1 European Research Sudies, Volume II, Issue (4), 2009 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: A Srucural Equaion Approach Ion Dobre, Adriana AnaMaria Alexandru 2 Absrac: The paper uses annual daa for he period in order o esimae he size of Spanish shadow economy. In view o do so, he shadow economy is modelled like a laen variable using he srucural equaion model(sem). The model includes ax burden, social benefis, subsidies, governmen employmen, self-employmen and unemploymen rae as main causes of shadow economy and he resuls indicaes ha he size of informal secor oscillaes beween 22% and 8% of GDP in he las en years. Invesigaing he relaionship beween he shadow economy and unemploymen rae a posiive relaionship is marked ou beween his wo variables. Keywords: Shadow economy, MIMIC mode, unemploymen rae JEL Classificaion: C22, E26, O7 PhD. Prof. Ion Dobre, Deparmen of Economic Cyberneics, Academy of Economic Sudies, Romana Square, no.2, Buchares, Romania, dobrerio@ase.ro, The auhor is vice-dean of he Faculy of Cyberneics, Saisics and Economic Informaics. 2 PhD. Assisan. Adriana AnaMaria Alexandru, Deparmen of Saisics and Economerics, Academy of Economic Sudies, Romana Square, no.2, Buchares, Romania, adrianaalexandru@yahoo.com, The auhor is research assisan a he Naional Scienific Research Insiue in he Field of Labour and Social Proecion (

2 80 European Research Sudies, Volume II, Issue (4), Definiion of he Shadow Economy In he aemp of defining he shadow economy, one commonly used working definiion is: all currenly unregisered economic aciviy which conribues o he officially calculaed (or observed) Gross Naional Produc 3. Smih (994) defines i as marke-based producion of goods and services, wheher legal or illegal ha escapes deecion in he official esimaes of GDP. The Sysem of Naional Accouns (SNA93) and he European Sysem of Naional Accouns (ESA95) define he non observed economy, as all produc aciviies ha can be classified ino he following hree areas: () Underground producion; (2) Informal producion; (3) Illegal producion. The Underground producion represens he area of producion aciviies ha are no direcly observed due o: (.a) Economic reasons (he aciviies carried ou ouside governmen regulaions such as avoiding ax, minimum wages, number of work hours, and working condiions for labourers. (.b) Saisical reasons (producion aciviies ha are no regisered due o failure o fill saisical quesionnaires. Their aciviies go undeeced using radiional survey mehods due o he small naure of he enerprise. The Informal producion refers o producive insiuional unis characerised by: (2.a) a low level of organisaion; (2.b) lile or no division beween work and capial; (2.c) work relaions based on occasional jobs, kinship, or personal relaions. (This conex comprises he aciviy of crafsmen, peddlers wihou licences, farm workers, home workers, and he unregisered aciviies of small merchans). Illegal producion includes he aciviies oriened a he producion of goods and services whose sale, disribuion or possession is prohibied by law. Included in his area are also producive aciviies carried ou by unauhorised operaors. 2. Empirical Sraegy and Daa In he process of economeric modelling of Spanish shadow economy we used a differen ype of models-srucural Equaions Models (SEM).The Srucural Equaion Models (SEM) represens saisical relaionships among laen 3 This definiion is used by Feige (989- economic aciviies include conscious effors o avoid official deecion) and by Schneider and Ense(2000- all economic aciviies which conribue o officially calculaed gross naional produc)

3 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 8 A Srucural Equaion Approach (unobserved) and manifes (observed) variables. A special case of SEM is he Muliple Indicaors and Muliple Causes model. I allows o consider he SE as a laen variable linked, on he one hand, o a number of observable indicaors (reflecing changes in he size of he SE) and on he oher, o a se of observed causal variables, which are regarded as some of he mos imporan deerminans of he unrepored economic aciviy(dell Anno, 2003). Frey and Weck-Hannemann in 984 have been he firs economiss ha consider he dimension of he hidden economy as an unobservable variable. This ype of models is composed by wo sors of equaions, he srucural one and he measuremen equaions sysem. The equaion ha capures he relaionships among he laen variable ( ) and he causes ( q ) is named srucural model and he equaions ha links indicaors (Y p ) wih he laen variable (non-observed economy) is called he measuremen model. So he shadow economy ( ) is linearly deermined, subjec o a disurbance, by a se of observable exogenous causes, 2,... 6 : () The srucural model ies he laen variable [ : shadow economy index] and he causes [ax burden (), social benefis paid by governmen (2), subsidies (3), governmen employmen in civilian labour force (4), self-employmen in civilian labour force (5), unemploymen rae (6)]. The laen variable ( ) deermines, linearly, subjec o disurbances, a se of observable endogenous indicaors Y,Y 2 : (2) Y Y2 2 2 (3) The measuremen model links he indicaors [Yp: real gross domesic produc index ( Y ), civilian labour force paricipaion rae ( Y2 )] and he unobservable variable ( ). The srucural disurbance, and measuremen errors are all normal disribued, muually independen and all variables are aken o have expecaion zero. For he modelling of shadow economy in Spain, we use annual daa from (fig.). Appendix A repors he daa sources for each variable in he empirical model. The series in levels or differences have been esed for he exisence of uni roos using Augmened-Dickey Fuller (ADF) es. All he daa has been differeniaed for he achievemen of he saionariy. While all he variables have been idenified like inegraed on firs order, he laen

4 82 European Research Sudies, Volume II, Issue (4), 2009 variable is esimaed in he same ransformaion of independen variables (firs difference). 3. The Causes of he Shadow Economy Tax burden ( ): The ax burden is considered o be he mos imporan deerminans of SE. Usually an increase in he ax burden offers a srong incenive o work in he unofficial economy, so he expeced sign for his variable is a posiive one. In he model, ax burden is calculaed as raio of oal axes (direc, indirec axes and social securiy conribuions) in gross domesic produc. The second variable in he model are social benefis paid by governmen ( 2 ) ha includes all curren ransfers received by households: unemploymen, reiremen, sickness, housing, educaion. They represens an incenive o paricipae and remain in he irregular marke, by reducing he willingness of he unemployed o work and providing incenives o under-declare official income in order o receive undue social benefis.they have been calculaed by raporing o gross domesic produc. Subsidies ( ): They are curren unrequied paymens ha governmen unis 3 make o enerprises on he basis of heir level of producion or he quaniies or values of he goods or services which hey produce, sell or impor (SNA 993). Subsidies are declared like percenage of GDP. Governmen employmen ( 4 ): This variable quanifies he degree of regulaion in he economy. Regarding he sign of his indicaor, i could be a negaive one, he presence of he sae could disincenive people o incorporae in he shadow economy or posiive one, capuring he fac ha mos regulaed he economy is, firms find more incenive o develop heir aciviies in he underground economy. This cause is measured as raio of governmen employmen in civilian labour force. Self-employmen ( ): The rae of self-employmen as a percenage of he 5 civilian labour force is considered as a deerminan of he informal economy. According o (Bordignon and Zanardi, 997) he significan diffusion of small firms and he large proporion of professionals and self-employed respec o he oal workforce are imporan characerisics ha jusify higher level of he shadow economy. This kind or workers have more possibiliies o evade as hey usually have greaer number of deducions in base and deducions in quoe in personal income axes. Therefore, ceeris paribus, he higher he rae of self-employed, and he larger he shadow economy would be. Unemploymen rae ( ): Regarding he relaionship beween unemploymen 6 rae and shadow economy, an increase in unemploymen could imply a decrease in he black economy as underground economy could be posiively relaed o he

5 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 83 A Srucural Equaion Approach growh rae of GDP and he laer is negaively correlaed o unemploymen. On he oher side some official unemployed spend a par of heir ime working in he black economy, hus we may find a posiive correlaion (Gilles and Tedds, 2002). Therefore, economic heory does no give a clue o deermine wheher he expeced sign of his variable is posiive or negaive, i has o be solved by he empirical analysis in each counry. Indicaors: Index of Real gross domesic produc index ( Y scale variable, base year 990=00). In he problem of idenificaion of he model, his variable is very imporan, mainly because i is chosen as a variable of scale (or reference variable). MIMIC approach suggess he necessiy o fix a scale in order o esimae he res of he parameers as a funcion of his scale variable. The value of fix parameer is arbirary, bu using a posiive (or negaive) uni value is easier o find ou he relaive magniude of he oher indicaor variables. There is no common view abou he sign of he relaionship beween shadow economy and economic growh. Some auhors like Adam and Ginsburgh (985) for Belgium, Giles and Tedds (2002) for Canada, Chaerjee, Chaudhuri and Schneider (2003) for Asian counries, find a posiive relaion beween SE and official GDP, while ohers like Frey and Weck-Hannemann (984) for 7 OECD counries, Loayza (996) for 4 Lain America counries, Kaufmann and Kaliberda (996) for Transiion counries, Eila and Zinnes (2000) for ransiion counries, Schneider and Ense (2000) for 76 Counries, Dell Anno (2003) for Ialy, Dell Anno, Gomez and Alañón (2007) for France, Greece and Spain, find a negaive relaionship. Schneider in 2005 find a negaive sign for ransiion and developing counries and a posiive relaionship for developed ones. If we change he sign of he coefficien of scale ( ), he parameers of he causes became from posiive negaive (keeping he same absolue values. A value (+) is assigned o ( Y ) consequenly, he coefficiens of and 4 are negaive 4, bu his resul compleely diverges from well-known heories and empirical sudies ha assign a posiive link beween underground economy and ax burden and/or governmen employmen. Tha is he reason why we choose in he model he minus sign for he relaionship beween shadow economy and growh rae of GDP. A disadvanage of he MIMIC mehod is he srong dependence of he oucomes by he (exogenous) choice of he coefficien of scale ( ) (Dell Anno, 2003). Civilian labour force paricipaion rae ( Y 2 ): The civilian labour force paricipaion rae is calculaed as he raio of he oal civilian labour force in working age 4 The shadow economy decreases by increasing ax burden and governmen employmen.

6 84 European Research Sudies, Volume II, Issue (4), 2009 populaion (5-64 years old). According o Giles (998) a decrease in his rae over ime may reflec a movemen of he workforce from he measured economy ino hidden aciviies. By including his variable as an indicaor, we invesigae if here is a flow of resources beween official and underground economy. The idenificaion procedure sars from he mos general model specificaion (MIMIC 6--2) presened in figure 2. and coninues removing he variables which have no srucural parameers saisically significan. The following able presens he maximum likelihood esimaed coefficiens of various MIMIC models considered for he informal economy of Spain. The models have been esimaed using LISREL 8.8. The coefficien of he index of real GDP 5 is normalised o - o sufficienly idenify he model ( ).This indicaes an inverse relaionship beween he official and shadow economy. Since he causal variables are expressed all in percenage of gross domesic produc, hey are comparable in order o invesigae relaive weigh o explain he dynamics of SE. For he Spanish case resuls, able poin ou ha unemploymen rae presens a posiive sign according wih he negaive one obained by he indicaor civilian labor force paricipaion rae. I means ha in Spain many workers from he official economy go underground when hey are laid off. The posiive sign of he unemploymen rae indicaes he exisence of a flow of resources from official o shadow economy in recession cycles. The governmen employmen aken like percenage of civilian labor force has a posiive sign meaning ha his variable is acing like a good proxy for he grade of regulaion in he economy. The self employmen variable is always significan in all he models and wih a posiive sign acing a one of he main causes of shadow economy in his counry and one possible cause for his siuaion is ha in he Spanish economy mos of he underground aciviies are developed by his collecive. The indicaor of labor force paricipaion became also significan and negaive, indicaing ha here is a flow of resources beween official economy and hidden economy. As can be seen, he coefficiens of ax burden, subsidies and social benefis measured like pecenage of GDP are no saisically significan. 4. Obaining he Size of he Shadow Economy in Spain Esimaion oupus reveal ha he main causes of shadow economy are: governmen employmen/civilian labour force, unemploymen rae, selfemploymen/civilian labour force, social benefis/gdp. Saring from MIMIC Re al GDP Index real GDP Re al GDP 990

7 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 85 A Srucural Equaion Approach 2(fig.) and removing he variables which have no srucural parameers saisically significan, we obain MIMIC 4--2 as he bes model (fig.2). The choice of he model is based on: he saisical significance of parameers, he parsimony of specificaion, he p-value of chi-square, and he Roo Mean Square Error of Approximaion (RMSEA) es, adjused goodness-of-fi index (AGFI). Taking ino accoun he reference variable ( Y, Re al GDP ) he Re al GDP shadow economy is scaled up o a value in 990, which is our base year, he year in which here are several esimaes of he Spanish shadow economy. Furher, we build an average of hese esimaes (able 2). The index of changes of he shadow economy in Spain measured as percenage of GDP in he 990 is linked o he index of changes of real GDP as follow: Measuremen Equaion: GDP ~ ~ GDP (4) GDP GDP 990 The esimaes of he srucural model are used o obain an ordinal ime series index for laen variable (shadow economy): Srucural Equaion: ~ (5). GDP The index is scaled o ake up o a value of 8.8% in 990 and furher ransformed from changes respec o he GDP in he 990 o he shadow economy as raio of curren GDP.These operaions are show in he benchmark equaion 6 : ~ * GDP ˆ GDP ~ (6) GDP GDP where: 6 As he variables are all differenced o same degree, o calculae he levels of he laen variable muliplying he srucural coefficiens for raw (unfilered) daa, i is equivalen o compue he changes in he index by muliplying coefficiens for he differenced causes and hen o inegrae hem.

8 86 ~ GDP 990 European Research Sudies, Volume II, Issue (4), 2009 is he index of shadow economy calculaed by equaion (5) * 990 GDP % is he exogenous esimae of shadow economy ~ GDP is he value of index esimaed by equaion (5) GDP 990 is o conver he index of changes respec o base year in shadow economy GDP respec o curren GDP ˆ GDP is he esimaed shadow economy as a percenage of official GDP. The shadow economy measured like percenage of official GDP, presened in he figure 3, records he value of 20.7% in 970 and follows an ascendan rend reaching he value of 24.5% in 985. Then i oscillaes beween 20% and 22% of official GDP, wih a slow endency of decreasing in he las five years. The resuls of his esimaion are no far from oher mehod, he currency demand approach applied by Schneider who esimaes he size of shadow economy a he level of 22.5% in 200/02, 2.2% in 2003/04 and 20.5% in 2004/ The Impac of Unemploymen Rae on Shadow Economy Dimension Figure 4 poin ou a direc relaionship beween he size of shadow economy esimaed by MIMIC as % of official GDP and unemploymen rae. The correlaion beween his wo variable [ Corr (, ) 0. 6] confirms a posiive relaionship. UR Giles and Tedds (2002) sae ha he effec of unemploymen on he shadow economy is ambiguous (i.e. boh posiive and negaive). An increase in he number of unemployed increases he number of people who work in he black economy because hey have more ime. On he oher hand, an increase in unemploymen implies a decrease in he shadow economy. In order o invesigae he impac of unemploymen rae on he shadow economy dimension, we develop a srucural relaionship, aking ino accoun also he growh rae of official GDP (able 3):

9 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 87 A Srucural Equaion Approach shad off g g u 7 (7) The parameer of he equaion shows an inverse relaionship beween he off shad growh of he official economy ( g ) and growh of he shadow economy ( ). On he oher-hand, he parameer shows a direc relaionship beween changes in unemploymen and he growh of he shadow economy. The coefficiens are saisically significan(prob.<5%) bu he degree of deerminaion in he model is moderae, only 4% of he variaion of shadow economy is explained by he wo exogenous variables unemploymen rae and growh rae of official GDP. However hese resuls, hough saisically significan, should be inerpreed carefully. The esimaion shows ha he presence of he shadow economy acs as a buffer as i absorbs some of he unemployed workers from he official economy ino he shadow economy. I reduces he impac of higher unemploymen on official oupu. 6. Conclusions The main objecive of his paper is o explain he evoluion of shadow economy in Spain using he srucural equaion models, aking ino accoun he nonsaionariy problems, very usual in he economic ime series. The main conclusions ha can be drawn are he following: ) Unemploymen appears as one of he main causes for he exisence of he shadow economy. This indicaor presens a posiive sign in all he models. This aspec is very imporan if we have ino accoun ha hese workers suppose a double cos for he Sae. In one hand, hey receive moneary percepions from Sae and, in he oher hand, he Sae is losing he axes hey should be paying for heir (hidden) incomes. 2) There is a posiive relaionship beween he size of he non-observed economy and he self-employmen indicaor. I reflecs ha his variable is one of he main conribuors o he growh of he shadow economy irrespecive of he level of developmen of he economy. 3) The governmen employmen aken like percenage of civilian labor force has a posiive sign meaning ha his variable is acing like a good proxy for he grade of regulaion in he economy. g 7 off shad ( g ) is he firs difference of annual growh rae of he official GDP, g is he firs difference of he shadow economy, u is he firs difference of unemploymen rae, residuals;

10 88 European Research Sudies, Volume II, Issue (4), 2009 The resuls indicae ha he Spanish informal secor a he beginning of he 970 s iniially accouned for 20.7 percen of official GDP while slighly increasing o 24.5 percen of GDP in he lae 985 and furher, i oscillaes beween 22% and 8% of GDP unil our days. Regarding he relaionship beween unemploymen rae and he size of shadow economy, he economerical esimaion shows a direc relaionship beween changes in unemploymen and he growh of he shadow economy. We consider like an exogenous variable also he growh rae of official GDP, and he model reveals an inverse relaionship beween his variable and he growh of shadow economy. The main limiaions of he MIMIC approach remains: he difficuly () o calculae of he confidence inervals associaed wih esimaes of he laen variable; (2) o es he hypohesis of independence beween srucural and measuremen errors; (3) arise for underaking a ime-series analysis wih he MIMIC model (o idenify exhausively he properies of he residuals, mehods o perform coinegraion analysis in he conex of SEM); (4) o apply he SEM approach o small sample sizes and ime series analysis and he srong dependence of oucomes by he (exogenous) choice of he coefficien of scale ( ).Alghough hese limiaions, from a mehodological viewpoin, he MIMIC approach is considered helpful because i is based on a srucural approach more appropriae han ohers given he naure of he SE and i provides supplemenary knowledge o undersand he economic phenomenon of shadow aciviies (Dell Anno, 2007). 7. References ) Adam, M. and C.V. Ginsburgh, 985, The Effecs of Irregular Markes on Macroeconomic Policy: Some Esimaes for Belgium, European Economic Review, 29/, ) Bollen, K. A., 989, Srucural equaions wih laen variables, John Wiley & Sons, New York. 3) Bordignon, M., and A. Zanardi, 997, Tax evasion in Ialy, Giornale degli Economisi e Annali di Economia 56, ) Chaerjee, S., K. Chaudhuri, and F. Schneider, 2003, The size and developmen of he Indian shadow economy and a comparison wih oher 8 Asian counries: An empirical invesigaion, Discussion Paper , Deparmen of Economics, Johannes Kepler Universiy of Linz. 5) Dell Anno, R., 2003, Esimaing he shadow economy in Ialy: A srucural equaion approach, Working Paper , Deparmen of Economics, Universiy of Aarhus. 6) Dell Anno, R., M. Gomez, and A. Alañón Pardo, 2007, Shadow economy in hree differen Medierranean counries: France, Spain and Greece. A MIMIC approach, Empirical Economics 33, 5-84.

11 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: A Srucural Equaion Approach 89 7) Dell Anno, R., and F.Schneider, 2004, The Shadow Economy of Ialy and oher OECD Counries: Wha do we know?. Mimeo. 8) Dobre, I., and A.Alexandru, 2007, Scenarii privind evoluia raei somajului in Romania in perioada , Revisa Sudii si Cerceari de Calcul Economic si Ciberneica Economica, 4/2, ) Dobre I., and A. Alexandru, 2007, Posibiliai de esimare a dimensiunii economiei informale, Revisa Sudii si Cerceari de Calcul Economic si Ciberneica Economica, 4/3, ) Dobre I., and A. Alexandru, 2008, Informal economy and USA unemploymen rae. Is here is a srucural relaionship? An empirical analysis, Macroeconomic of E.U. exension and economic growh Secion, Inernaional Conference: Economic growh and E.U. Exension Process, Academy of Economic Sudies, Buchares, Ed.Ase, ISBN , ) Dobre I., and A. Alexandru, 2008, Modelling Unemploymen Rae using Box-Jenkins Procedure, Journal of Applied Quaniaive Mehods, 3/2, ) Eila, Y., and C. Zinnes, 2000, The evoluion of he shadow economy in ransiion counries: Consequences for economic growh and donor assisance, CAER II Discussion Paper 83, Harvard Insiue for Inernaional Developmen. 3) Feige, E. L., 989, The Underground Economies, Tax Evasion and Informaion Disorion, Cambridge, Cambridge Universiy Press. 4) Frey, B. S. and H. Weck-Hannemann, 984 The hidden economy as an unobservable variable, European Economic Review 26, ) Giles, D.E.A., 998, The underground economy: Minimizing he size of governmen, Economerics Working Papers 980, Deparmen of Economics, Universiy of Vicoria. 6) Giles, D. E.A., and L.M. Tedds, 2002, Taxes and he Canadian Underground Economy, Canadian Tax paper 06, Torono, Canadian Tax Foundaion. 7) Johnson, S., D.Kaufmann, and P. Zoido-Lobaón, 998, Regulaory Discreion and he Unofficial Economy, American Economic Review, 88:2, ) Jöreskog, K., and D.Sörbom, 993, LISREL 8, User s Reference Guide, Chicago: Scienific Sofware Inernaional. 9) Loayza, N. V., 996, The economics of he informal secor: A simple model and some empirical evidence from Lain America, Carnegie- Rocheser Conference Series on Public Policy 45, ) [OECD, 2002, Handbook for measuremen of he non-observed economy, Paris, OECD Publishing.

12 90 European Research Sudies, Volume II, Issue (4), ) Schneider, F., 2005, Shadow economies around he world: Wha do we really know, European Journal of Poliical Economy 2, ) Schneider, F., and D. H. Ense, 2000, Shadow economies: size, causes and consequences, Journal of Economic Lieraure 38, ) Schneider, F., 2007, Shadow Economies and Corrupion all over he world: New esimaes for 45 Counries, Economics 2007/9, ) Smih, P., 994, Assessing he size of he underground economy: The saisics Canada perspecives, Canadian Economic Observer, Caalogue -00, , a 3.8.Spiro, P. S. (993): "Evidence of a Pos-GST Increase in he Underground Economy;" Canadian Tax Journal/ Revue Fiscale Canadienne, 4/2, ) Thalassinos, E. J., Hanias, P. M., Curis, G. P., (2007) Non-Linear Dynamics and Chaos: The Case of he Price Indicaor a he Ahens Sock Exchange", Inernaional Research Journal of Finance and Economics, issue, Sepember, pp ) Thalassinos, E., Th. Kiriazidis, 2003, Degrees of Inegraion in Inernaional Porfolio Diversificaion: Effecive Sysemic Risk, European Research Sudies Journal, Vol. VI, issue ) OECD Economic Oulook Saisic and Projecions Daabases. 28) OECD Labour Force Saisics. 29) OECD Naional Accouns. 30) OECD Main Economic Indicaors.

13 European Research Sudies, Volume II, Issue (4), 2009 Appendix A: Analysis of Non-Saionariy In his appendix we display he ess employed o deec he order of inegraion in he ime series. The pioneer in ackling he problem of non-saionariy in he MIMIC models has been (Giles, 2002) ha poin ou o consider he non-saionary elemen is o consider he possibiliy of coinegraion. To discover he uni roos, he Augmened Dickey-Fuller (ADF) Tes are used. In he following able he p-value of ADF es is repored, while he null hypohesis is he presence of he uni roo, and herefore a value greaer han 0.05 Var CAUSES Sources Uni roo Analysis of Non-saionariy (ADF es) analysis Level Firs diff. Second diff. Transf.used. Toal Direc Tax/GDP OECD-Economic Oulook I() T&C * 0.000* 2008 ( ) 2 3 Toal Indirec Tax/GDP Social Securiy Conribuions received by Governmen/GDP Tax_burden/GDP OECD-Economic Oulook 2008 OECD-Economic Oulook Social benefis paid by OECD-Economic Oulook 5 governmen/gdp 2008 Subsidies/GDP OECD-Economic Oulook Governmen employmen/ OECD-Economic Oulook 7 Civilian Labour force 2008 Self-employmen/ OECD-Economic Oulook 8 Civilian Labour force 2008 Unemploymen rae OECD-Economic Oulook INDICATORS Y Index of Real GDP OECD-Economic Oulook 2008 Y2 Civilian labour force paricipaion rae I() T&C * 0.000* ( 2 ) I() T&C * 0.000* ( 3) I() T&C * 0.000* ) OECD-Economic Oulook 2008 I() I() I() I() I() I() I() T&C * 0.000* C * 0.000* T&C * 0.000* T&C * 0.000* T&C * T&C * T&C * 0.000* * Indicaes non-saionary ime series. The economeric sofware Eviews 6.0 was used o perform his analysis. ( 4 ( 5) ( 6) ( 7 ) ( 8) ( 9 ) ( Y ) ( Y 2 )

14 European Research Sudies, Volume II, Issue (4), 2009 Table : Esimaed Coefficiens 8 of he MIMIC Models Mode ls MIM IC 6--2 MIM IC 5-- 2a MIM IC Tax burden/ GDP Social Benefis/ GDP Subsidies/ GDP Bureauc racy Index Selfemploymen/ Civilian Labour Force Unemploym en rae Civilian Paricipaion raio Y (-0.20) 3 (0.26) (-0.) 0.08 (0.9) (0.94).48 (.00).50 (.02) 2.54* (4.28) 2.56* (4.34) 2.6* (4.84) 0.67* (2.39) 0.67* (2.39) 0.6* (2.47) 0.96* (8.28) 0.97* (8.4) 0.98* (.23) -0.26* (-5.7) -0.26* (-5.7) -0.26* (-5.7) Chisquare A RMSE (pvalue) 9 value) ( (p (0.92) (0.63).37+ (0.73) (0.95) (0.7) (0.79) AGF I Df The esimaions has been made wih he sofware LISREL If he srucural equaion model is correc and he populaion parameers are known, hen he marix S(Sample covariance marix) will equal o ( ) (model implied covariance marix) herefore he perfec fiing correspond o p-value=.0.this es has a saisical heory if here are large sample and mulinormal disribuions. 0 P-value for Tes of Close Fi (RMSEA<0.05). + means good fiing (p-value>0.05). Adjused goodness-of-fi index, AGFI.This indicaor akes values ino he inerval [0, ]. 2 The degrees of freedom are deermined by 0.5(q+p)(q+p+)-, where p=number of indicaors, p=numbers of causes, =number of free parameers.. 3 T-saisic is given in parenheses. * means saisic. 96

15 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: A Srucural Equaion Approach b MIM IC 5-- 2c MIM IC 4-- 2a MIM IC 4-- 2b MIM IC 4-- 2c MIM IC (-0.40) 0.22 (0.47) (-0.24) 0.5 (0.34) (.04) * (4.7) 2.60* (4.84) 2.36* (4.9) 2.45* (4.68) 2.44* (4.68) 0.66* (2.33) 0.68* (2.46) 0.66* (2.32) 0.69* (2.43) 0.68* (2.42) 0.97* (8.27) 0.98* (.34) 0.98* (8.45).0* (.89).0* (.93) -0.26* (-5.7) -0.26* (-5.7) -0.26* (-5.7) -0.26* (-5.7) -0.26* (-5.7).34+ (0.73).3+ (0.33).3+ (0.35) (0.5) (0.6) (0.79) (0.4) (0.42) (0.58) 0.2+ (0.2)

16 European Research Sudies, Volume II, Issue (4), 2009 Table 2: Esimaes of he size of Spanish shadow economy (990) Auhor Mehod Size of Shadow Economy Johnson e. Al(998) Currency Demand Approach 6.% Lacko(999) Physical Inpu(Elecriciy) 22.9% Schneider and Ense(2000) Currency Demand Approach 7.3%* Mean % *means for Table 3: Esimaion oupu of regression g shad g off u

17 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 95 A Srucural Equaion Approach GRAPHICS Fig.. Diagram Pah MIMIC 6--2 Tax_burden/G DP 2 Social benefis/gdp 2 Index of Real GDP Y 3 Subsidies/GDP 3 4 Governmen Employmen /Civilian Labour Force 4 Shadow Economy 5 Selfemploymen/ Civilian Labour Force Civilian Labour Force Paricipaion Y 2 6 Unemployme n rae

18 96 European Research Sudies, Volume II, Issue (4), 2009 Fig.2. Pah diagram of 4--2 MIMIC model

19 The Impac of Unemploymen Rae on he Dimension of Shadow Economy in Spain: 97 A Srucural Equaion Approach Fig.3.The size of shadow economy as % of GDP % o f o f f ic ia l G D P Fig.4.Shadow Economy vs.unemploymen rae unemploymen rae shadow economy as % of GDP shadow economy as % of GDP unemploymen rae(%)