Note: ME = Median, M = Mean, S.D. = Standard Deviation of the distributions of the estimated parameters, respectively. The parentheses contain the corresponding statistics for the distributions of the t-values, JEP S = as; ?lEP X/X = ax */logsoe = elasticity of EP with respect to X at X, where X = any explanatory variable in equation (I) other than size (S); X = mean value of X; e = 2.718. a Details of the regression results may be obtained from the author upon request.

PpT HE loss of aggregate income due to the 1970 recession in the United States is widely recognized and much decried. How the loss has been distributed in society is not so well known and not extensively researched. This paper is concerned with measuring and describing the incidence of the recession on families, by income level. Historical trends in the size distribution of income have been' analyzed by Budd (1970) and Lampman (1971), and its cyclical variability has been studied by Schultz (1969), Metcalf (1972), Thurow (1970), and Mirer (1972). Most of their results suggest that macro-economic downturns increase income inequality or otherwise bear heavily on the poor and near-poor. This analysis examines micro data from a panel survey to measure the pattern of incidence of the loss of aggregate income in 1970, and finds it to be different from the effects found for past recessions. Toward the end of the 1960's, the economy was experiencing high employment along with increasing inflation. Restrictive monetary and fiscal policies along with changes in the structure of government expenditure brought about a worsening of economic conditions. In February 1969 the civilian unemployment rate stood at 3.3 per cent; it rose above 3.5 per cent in September and above 4.0 per cent in February 1970. By December 1970 the unemployment rate was 6.1 per cent. In 1970 real output declined 0.4 per cent from the 1969 level. In describing the distributional effects of these changes in macro-economic conditions, it is essential to compare what actually occurred to what would have occurred under some specified set of alternative conditions. The analytical framework of this study is a comparative statics model in which families' incomes in 1970 are compared to what their incomes would have been then if the aggregate conditions of 19671969 had continued. This approach is particularly relevant for policy purposes because it allows one to judge the distributional costs of the restrictive anti-inflationary policies of recent years.

Aged people face the problem of allocating over the rest of their lifetimes the wealth that they have accumulated during their working years. This problem is fairly complex, because they are uncertain about the dates of their death and because they may wish to use their wealth to finance general consumption, or hold it to meet emergencies, leave estates, or maintain power or status. Whether skilled at dynamic programming or not, aged people effectively do make these decisions. What are the results? Some studies of the entire lifetime pattern of saving and wealth tend to support the simple life cycle model, in which the aged use up their wealth to help finance consumption. Harold Lydall, for example, found saving rates to increase and then decrease with age in the whole population and to be negative for the group aged 65 and over. Guarded support for the theory was found by Franco Modigliani and Albert Ando in Britain and by Dorothy Projector in the United States. More recently, A.F. Shorrocks examined the lifetime pattern of wealth holding in estate-tax data for a single cohort and found the hump pattern that is characteristic of life cycle saving. Other evidence on wealth holding runs contrary to this, however. In a study of estate-tax returns in Washington, D.C., James D. Smith found that wealth increased with age among the aged, after controlling for other demographic variables. Examining national estate-tax data, John Brittain found wealth to increase with age in the United States and A. B. Atkinson and A. J. Harrison reported the same pattern in England and Wales. In a sample of (TIAA) annuity recipients analyzed by James Mulanaphy, over half reported that their total savings had increased during retirement and another quarter reported that their savings had remained about the same. In this paper, I examine wealth holding patterns among aged married couples, using survey data representing the entire aged population of the United States in 1968. The statistical analysis serves as a test of the hypothesis that emerges from life cycle theory and provides some further exploration into the economic behavior of the aged. I find that the aged tend to increase their wealth over time.

IN A RECENT ARTICLE in Econometrica [1] Barbara Bergmann argues that improvement over the usual regression procedures can be gained by a combination of a very simple do-it-yourself simulation with regression. She asserts that this approach can provide insights which would not be found using a regression approach, and claims that simulation-regression offers a partial solution for the problems of multicollinearity and choice of functional form while economizing on degrees of freedom. These points are illustrated with an application to a simple model determining the incidence of poverty. In this comment we point out an analytic solution to Bergmann's theoretical model and show her simulation to be inefficient. We explore the general properties of prepared regression, arguing that its usefulness is overstated and that it is not more fruitful for scientific investigation than properly performed regression analysis. Bergmann proposes a model of the effects on the incidence of poverty (p) of the unemployment Tate (u), the weekly gross turnover rate (v), and the weekly wage rate relative to the poverty line. In her model, which assumes homogeneous labor force participants who stochastically become employed or unemployed, the probability that a person will be employed next week depends only on his employment status this week. A participant is poor if he is employed no more than a certain number of weeks in the year (c), which number depends on the poverty threshold and the weekly wage. This model can be criticized on many substantive grounds such as its use of a homogeneous labor force, the assumption that accessions and separations are random, the neglect of the labor force participation decision, and the omission of unearned income. Hall [4] has shown that the probability of separation depends importantly on the length of employment. It may also be important to distinguish between quits and layoffs. Our primary purpose, however, is not to offer substantive criticism of the model. We need only emphasize here that the poor in this model are very different from the poor in the real world.2 Bergmann solves the model by computer simulation, but in fact it has an analytic solution. The model is a two state Markov process in equilibrium, with the states defined as employed this week (state 1) and unemployed this week (state 0). The transition probability matrix is as follows: