Now let a denote the vector of parameters<sup>of themodel relatedto theproductionfunction and scaling</sup> factor, that is, a = _(f,_ a,p,a, _,s)._ Suppose<sup>wehada sampleof nhouseholds,andlety,bea zero-</sup> one indicator variable for the observed entrepreneurship<sup>choiceof householdi.Thenwiththenotation</sup> _x'(b, 1, w)_ for the point on the _xe(b,_ w)<sup>curve forhouseholdiwithwealthb,,atparametervector0 with</sup> wage w, we can write the explicit log likelihood<sup>of the entrepreneurshipchoice forthe n householdsas</sup> 1n Ln(9,m) = _-EylnH[xe(btIO,_ w),ml +<sup>(1 -y,)ln{I</sup><sup>_-H[xe(b, 1,w),m]}_</sup> (24) t=1 The parameters over which to search are again<sup>the production parameters(,B, a,p,</sup><sup>_a,(),_the scaling factor</sup> _s_ and the skewness m of H(., m).

Intuitively, however, the production parameters<sup>invector 9cannotbeidentifiedfromapurecross-</sup> section of data at a point in time For if<sup>we</sup> return<sup>tothedecisionproblem ofanentrepreneurfacing</sup> wage w, we recall that the labor hire decision<sup>given by equation(7)is a linear functionof capital</sup><sup>_k._Then</sup> substituting _l (k, w)_ back into the production function<sup>as in equation(8),weobtain a relationship between</sup> output and capital with a constant term, a<sup>linearterm in</sup><sup>_k,_and a quadratic termin</sup><sup>_k._Essentially,then,</sup> only three parameters are determined, not<sup>five.</sup> If data on capital and labor demand at the<sup>firmlevelwereavailable,wecouldsolvethe identification</sup> problem by directly estimating the additional<sup>linearrelation</sup><sup>_l(k)_givenin equation(7).Thiswouldgive</sup> us two more parameters thus obtaining full identification.<sup>Unfortunately, thesedata arenotavailable.</sup> However, equation (8) suggests that we can<sup>fullyidentifythe productionparametersbyexploitingthe</sup> variation in the wages over time observed<sup>inthedata.The Appendixshowsindetailthecoefficients</sup> estimated and how the production parameters<sup>arerecovered.</sup> The derivatives of the likelihood in equation<sup>(24)can be determinedanalytically,andthenwith the</sup> given observations of a database, standard maximization<sup>routinescan be usedto searchforthe maximum</sup> numerically'". The standard errors of the estimated<sup>parameterscanbecomputedby bootstrapmethods</sup> using 100 draws of the original sample with<sup>replacement.</sup> It is worthwhile mentioning that for some<sup>initialpredeterminedguesses,theroutineconvergedto</sup> different local maxima. However, all estimates<sup>usinginitialguessesaroundaneighborhood of anysuch</sup> estimate, converged to the same estimate. The<sup>multiplicityof local maximamaybe due tothe computa-</sup> tional methods available rather than the<sup>non-concavityoftheobjective function in certainregions.See</sup> also the experience of Paulson and Townsend"<sup>6(2001)withLEBandotherstructuralmodels.</sup> We run this maximum hkehhood algorithm with<sup>two differentdata bases.The firstandprimarydata</sup> base is the widely used and highly regarded<sup>Socio-EconomicSurvey'7(SES)conductedbythe National</sup> Statistical Office in Thailand. The sample<sup>isnationallyrepresentative,anditincludeseightrepeated</sup> cross-sections collected between 1976 and<sup>1996.Thesamplesizeineachcrosssection:11,362in1976,</sup> 11,882 in 1981, 10,897 in 1986, 11,046 in<sup>1988,13,177in1990,13,459in1992,25,208in1994and 25,110</sup> in 1996. Unfortunately, the data do not constitute<sup>apanel,butwhenstratifiedbyage ofthehousehold</sup> head, one is left with a substantial sample.<sup>As</sup> in<sup>the complementary work of Jeong and Townsend(2000),</sup> we restrict attention to relatively young households,<sup>aged20-29,whosecurrentassetsmightberegarded</sup> somewhat exogenous to their recent choice of occupation.<sup>Wealsorestrict attentiontohouseholdswho</sup> had no recorded transaction with a financial<sup>institutioninthemonthpriorto theinterview,acrude</sup>

> 1'1n particular, we used the MATLAB routine<sup>fminconstartingfroma variety of predeterminedguesses</sup>

"See their technical appendix for more information<sup>aboutthe estimationtechnique</sup><sup>**and**its drawbacks</sup>

**'**<sup>**7**</sup> **See** Jeong(1999) for details or its use **in**<sup>DeatonandPaxson(2000)or Schultz(1997).</sup>

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