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The Effect of Income Instability on Farmers' Consumption and Investment

The Review of Economics and Statistics 1974 56(2), 141
POLICIES to promote price and income stability in agriculture have often been justified by the belief that stability would help farmers make better consumption and investment decisions. However, review of literature makes it abundantly clear that the consequences of instability are matters of debate among economists. For instance, Caine (1966, p. 16) believes that a main evil resulting from fluctuations in income is lowering of the level of capital expenditure. Others argue that farmers adapt to the exigencies of fluctuating income and that instability, per se, has little influence on consumption and investment (e.g., Campbell, 1964, p. 59).1 In this paper, consumption and investment functions are estimated for two groups of southern Minnesota farmers with contrasting degrees of income stability. Since various hypotheses exist about investment and consumption behavior, alternative models are outlined in the first section. Consequently, this paper provides empirical evidence for evaluating alternative models as well as assessing the effects of instability. The data and the estimation procedures are briefly described in the second section, and the empirical results are presented in the third.

A Convenient Descriptive Model of Income Distribution: The Gamma Density

Econometrica 1974 42(6), 1115
The distribution of personal income is approximated by a two-parameter gamma density function (Pearson Type III). The two parameters may be considered as indicators of scale and of inequality, respectively. Maximum likelihood estimates of the parameters are derived from a random sample using graphical techniques, and a likelihood ratio test for the hypothesis that the inequality parameter is the same for different distributions is presented. The derivation of both the estimates and the test statistic requires computing the arithmetic and geometric means from the sample. An empirical application, including a comparison of the gamma and lognormal distributions to demonstrate the better fit of the gamma, is made to personal income data in the United States for the years 1960 to 1969. Using the gamma density, inequality is shown to decrease when unemployment or inflation decreases, or when the real national product increases.