to produce _exports_ is _KE_<sup>_i_=</sup><sup>_KE −K_</sup> _E_<sup>_f×_(1+</sup><sup>_tK_) = 18</sup><sup>_._55</sup><sup>_−_1</sup><sup>_._97</sup><sup>_×_(1+0</sup><sup>_._39) = 16</sup><sup>_._58.</sup> The SAM of Table 2 does not show _leisure_ . The quantity of leisure is determined by the representative consumer’s endowment of time less the sum of formal and informal labor. To enable simple calibration of the elasticity of labor supply, the utility function is specified with unitary (Cobb-Douglas) elasticity of substitution between leisure and all other goods. This implies a labor supply elasticity of _η_ = _<u>T</u> −LL_ where _T_ is the time endowment and _L_ is total labor supply. The value of _L_ is fixed by the data – in the case of Guinea-Bissau _L_ = _L_<sup>_i_</sup> + _L_<sup>_f_</sup> = 9 _._ 45+34 _._ 61 = 44 _._ 06. The calibration approach is to choose a value for the labor supply elasticity, which then fixes the value of _T_ . There appear to be very few published estimates of the elasticity of labor supply in developing countries. For rich countries, estimates of the elasticity of labor supply are close to zero, when estimated for those who are employed. Nevertheless at the extensive margin, the decision whether or not to take a job, the elasticity of labor supply is positive. For our developing countries, we felt that some small responsiveness of labor supply to changes in taxation was appropriate, and thus chose an elasticity of 0.05, implying that _T_ = 1 _._ 05 _× L_ .

National accounts figures represent values: price _×_ quantity. Following the Harberger convention, units of aggregate goods are chosen such that quantities equal values. This implies that for untaxed goods or factors, benchmark prices are equal to one. For taxed goods and factors, we choose quantity units such that either the net of tax price or the gross of tax price is equal to one at the benchmark equilibrium. Specification of the tax rates allows calculation of the missing prices.

With all benchmark prices and quantities determined, calibration finishes with the selection of elasticities for the CES utility and production functions. Our base case uses unitary elasticities: constant returns to scale Cobb-Douglas functions. This appears to be reasonable for the elasticity of demand for imports (Senhadji 1998). But we do not have evidence on the empirical magnitude of other necessary elasticities. Faced with a data vacuum we preferred a simple functional specification, and performed sensitivity checks by changing elasticities.

While this account of the calibration process is straight-forward, it glosses over several problems with the calibration of informal sectors. It is likely that these problems affect all countries to some degree, but the issue is particularly acute in eight countries where, using the procedure described above, the calibrated values of sections of the informal economy are negative. The _untaxed_ good is negative in Equatorial Guinea (-74% of GDP), Gabon (-2 %), Mauritania (-3%), Namibia (-22%), and Swaziland (-3%). In addition, the calibration process gives negative values for _informal labor_ used to produce _domestic_ and _exports_ in Cape Verde (-5%), South Africa (-13%) and Zimbabwe (-13%).

The first problem is a general question about the reliability of GDP data in small developing economies. In particular, statisticians dealing with developing economies make efforts to incorporate the informal economy, but to the extent that some informal activities escape the measure of GDP, our calibrated informal sectors are too small. Data reliability may affect results for all countries, but it 12