where b is the relevant, real economic base of the tax and i,t Z is a vector of other explanatory variables. Data availability restricts the choice of tax bases. The GDP is assumed to be the relevant macroeconomic base for tax categories i = {1, 4, 5}; final household consumption, the base for i = {2} and total imports, for i = {3}. The vector Z includes other determinants of the rate of growth of real tax proceeds such as the inflation rate<sup>3</sup> (in logs or log difference) and terms of trade (in logs or log difference). Unfortunately, due to data limitations on tax law changes over time, the regression does not control for discretionary policy measures thus rendering elasticity estimates not completely reliable.<sup>4</sup> An additional potential source of bias is the use of the OLS estimation technique, which ignores the effect of the fiscal position on the cyclical behavior of macroeconomic aggregates thus yielding biased estimates. To deal with the endogeneity problem, the instrumental variable estimation procedure is used. This uses the U.S. GDP (log difference) and the first lag of the inflation rate and terms of trade variables as instruments.

Annual tax data series generally spanning the period from 1972 to 2000 and generally comprising what the IMF defines as ‘consolidated central government’ come from the Government Finance Statistics database and IMF country reports. The remaining data were retrieved from the World Development Indicators database (World Bank). Output elasticities of various macroeconomic bases were obtained from OLS regressions of d(log(bi,t )) on d(log(Yt )) with no correction for the potential endogeneity of the righthand side variable.<sup>5</sup> In the other methodology, Pechman (1973) estimates the responsiveness of the U.S. tax system to fluctuations in income using a sample of historical individual federal income tax returns to simulate the impact on tax liabilities of a dollar increase in personal income. Pechman refers to this measure as the tax system’s “built-in flexibility” and Auerbach and Feenberg (2000), as the “normalized tax change.” Lacking the specific information needed to perform a similar calculation for LAC countries, an aggregate version of the relationship between tax revenue and income is computed here by defining it as the mean of the yearly ratios of the absolute increase in total tax revenue to the absolute increase in GDP. The PI indicator is computed as where N + 1 is the sample size and Δ(R t ) is the absolute change in total tax revenue between periods t -1 and t . Unfortunately, the PI indicator is also tainted by the problem

> 3 The inflation rate is defined as inflation rate/(1+inflation rate).

> 4 In stricto sensu, this is not a tax elasticity measure but a tax buoyancy measure. The latter incorporates the impact of any discretionary changes in tax rates on revenue collection data. By definition, buoyancy does not control for discretionary changes in the tax structure.

> 5 In some cases the described general methodology to compute SBB did not work satisfactorily. In those cases Hodrick-Prescott filtered (logged) series (budget categories, tax bases and output) are used to estimate elasticities.

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