By J. M. Bruce

12 pages together with covers, simple and particular info at the airplane and its carrier with bw and colour illustrations

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Bourguignon 1979). The theorem considers only three of the auxiliary requirements listed above. The other three requirements (scale independency. principle of equal additions. and boundedness) are violated by Vf(X) for most strictly convex functions f. This can easily be checked for the nonlinearity bias that corresponds to a quadratic function. that is the variance. Corollary 2: For every continuous and strictly concave function f. Wf(X)- -Vf(X) satisfies the conditions of population size invariance.

Of scale invariance. For other functions f or g, this is usually not the case. 3 Estimation from grouped data: I The remainder of this chapter will be concerned with methods of estimating Vf{Y) from grouped data on income distributions. Income distribution data are often not available in the form of micro-level data for all population members, but only in the form of grouped data. Two major types of grouped data may be distinguished: Data on the percentage shares of income accruing to percentile groups of the population (with the population ranked in ascending order of income), and data on the frequency distribution of incomes.

5 percent higher in absolute value than the estimates of method 1. It can be concluded that, when the lognormal distribution provides an adequate description of the size distribution of incomes (as is commonly believed), the estimates of Vf(Y) that will be obtained by using method 2 will be more precise than the estimates obtained by method 1. This means that, generally spoken, method 2 is to be preferred. When, however, less precision is required, method 1 may be chosen for its simplicity. 4 Estimation from grouped data: II Another often used manner of presenting income distribution data is the frequency distribution.

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Aircraft Profile No. 21: The Bristol Fighter by J. M. Bruce

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