Suchergebnisse

In theoretical settings, growth rates are generally based on derivatives, which relate infinitesimal changes in time to changes in a variable's value. In applications of theory, growth occurs over discrete intervals, and a variety of discrete growth measures exist. Therefore, a key question is which discrete measure provides estimates most consistent with true parameter values. In estimating elasticity values, results show that the standard growth rate can be highly inaccurate. The average-base and logarithmic growth rates do a much better job. In addition, when the process generating data is unknown, a linear in growth rates regression equation is found to be more accurate than the widely used linear, logarithmic, logarithmic-linear, and linear-logarithmic specifications.

The accuracy of index numbers can be understood by evaluating the consistency of their formulas with the sources of change in total expenditure and by examining their ability to estimate actual price and output changes with precision. In terms of formulas, differences among index numbers can be seen in their treatment of the interaction term, which arises when changes in prices and quantities occur simultaneously over discrete time intervals. This paper evaluates these differences for a number of important indices, including the additive and multiplicative versions of the Fisher. Then, using the growth-rate counterparts of these measures, the accuracy of index numbers is examined in terms of their ability to estimate constant elasticity values for both demand and supply functions. For the indices considered, results show that the additive measures, especially the Additive Fisher, provide superior measurement of price and output growth effects.