Returns to Education <strong>and</strong> ExperienceWith<strong>in</strong> the EU: An Instrumental Variable Approach for Panel Data 87equivalent to runn<strong>in</strong>g 2SLS with [X*, X 1 , Z 1 ] as the set <strong>of</strong> <strong>in</strong>struments. If the model isidentified, <strong>in</strong> the sense that there are at least as many time-vary<strong>in</strong>g exogenous regressors X 1as there are <strong>in</strong>dividual time-<strong>in</strong>variant endogenous regressors Z 2 , i.e. k 1 g 2 , this Hausman-Taylor estimator is more efficient than fixed effects. If the model is under-identified, i.e. k 1
88Advances <strong>in</strong> Econometrics - <strong>The</strong>ory <strong>and</strong> Applicationsmore than 8,000 <strong>in</strong> Germany. For the self-employed, the figures are considerably lower,vary<strong>in</strong>g between less than 1,000 <strong>in</strong> Germany to almost 2,500 <strong>in</strong> Italy. Sample proportions arenot very different from population rates (see Table 1). Bear<strong>in</strong>g <strong>in</strong> m<strong>in</strong>d that self-employedearn<strong>in</strong>gs are commonly believed to be under-reported (Hamilton, 2000), wage earnersappear to earn a little more than the self-employed <strong>in</strong> Italy, whereas the opposite occurs <strong>in</strong>Germany <strong>and</strong> <strong>in</strong> the UK. Note that dispersion <strong>in</strong> earn<strong>in</strong>gs is higher for the self-employed,reflect<strong>in</strong>g a greater heterogeneity <strong>in</strong> these types <strong>of</strong> activities, from low-ability jobs (retailers<strong>and</strong> basic services) to those <strong>of</strong> pr<strong>of</strong>essionals, such as doctors or lawyers. People liv<strong>in</strong>g <strong>in</strong>Germany <strong>and</strong> <strong>in</strong> the UK obta<strong>in</strong> higher earn<strong>in</strong>gs than those resid<strong>in</strong>g <strong>in</strong> Italy.<strong>The</strong> years <strong>of</strong> experience are clearly higher <strong>in</strong> the self-employed sector than <strong>in</strong> that <strong>of</strong> wageearners. <strong>The</strong> majority <strong>of</strong> <strong>in</strong>dividuals <strong>in</strong> Italy present low educational levels, the percentagebe<strong>in</strong>g somewhat higher among the self-employed. By contrast, <strong>in</strong> Germany, workers <strong>in</strong>general are highly educated, with more than 40% <strong>of</strong> the self-employed hav<strong>in</strong>g atta<strong>in</strong>ed atertiary degree. <strong>The</strong> case <strong>of</strong> the UK is especially appeal<strong>in</strong>g s<strong>in</strong>ce workers atta<strong>in</strong><strong>in</strong>g asecondary level are clearly fewer than those <strong>of</strong> primary or higher education, <strong>in</strong>dicat<strong>in</strong>g somek<strong>in</strong>d <strong>of</strong> a bi-modal distribution. Roughly speak<strong>in</strong>g, where self-employment rates are higher,the self-employed themselves are less educated, as aga<strong>in</strong>st countries with low selfemploymentrates, which exhibit a higher proportion <strong>of</strong> workers, either wage earners or theself-employed, who have obta<strong>in</strong>ed at least a secondary level <strong>of</strong> education.GermanyItalyUnitedK<strong>in</strong>gdomSelfemployedWageearnerSelfemployedWageearnerSelfemployedWageearnerEarn<strong>in</strong>gsper hour9.06(8.26)8.48(4.30)6.21(5.31)6.73(3.55)8.71(9.73)7.88(5.59)Exp.22.94(10.98)20.48(11.16)23.69(13.34)18.03(11.07)25.33(13.03)20.02(12.86)Primaryeduc.Secondaryeduc.Highereduc.Obs.peryear12.31 46.19 41.50 84019.48 57.88 22.64 806656.82 31.95 11.23 249444.13 44.63 11.24 786546.48 13.74 39.78 105345.99 13.70 40.31 6433Table 2. Sample averages (ECHP 1994-2000). Note: St<strong>and</strong>ard errors between parentheses.Earn<strong>in</strong>gs are expressed <strong>in</strong> terms <strong>of</strong> the PPP. Observations per year is the average, s<strong>in</strong>cefigures vary from year to year.5. <strong>Estimation</strong> resultsThis section presents the empirical evidence which is then assessed <strong>in</strong> the light <strong>of</strong> the aspectsmentioned <strong>in</strong> Section 2, with the aim <strong>of</strong> provid<strong>in</strong>g some <strong>in</strong>sights <strong>in</strong>to the function<strong>in</strong>g <strong>of</strong> theEuropean labour markets. <strong>The</strong> results from EGIV Hausman-Taylor estimations are shown <strong>in</strong>Table 3, along with the tests for choos<strong>in</strong>g the appropriate <strong>in</strong>struments (Baltagi et al., 2003).In column H1, a st<strong>and</strong>ard Hausman test rejects the r<strong>and</strong>om effects hypotheses <strong>in</strong> favour <strong>of</strong>
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