Although institutional investors have a preference for large capitalization stocks, over time they have shifted their preferences toward smaller, riskier securities. These changes in aggregate preferences have arisen primarily from changes in the preferences of each class of institution, rather than changes in the importance of different classes. Evidence also suggests that recent growth in institutional investment combined with this shift in preferences helps explain why markets in general, and smaller stocks in particular, have exhibited greater firm-specific risk and liquidity in recent years. Additional analyses suggest that institutional investors moved toward smaller securities because such securities offer "greener pastures."

This paper considers a dynamic real exchange model of international trade in commodities and equities. Given “generalized Cobb-Douglas” intraperiod tastes that differ across countries, we find a closed-form solution with properties that are noteworthy, not because they reverse our presumptions, but because they exceed them. A consumption-based model of international equity investment might be expected to have the following properties: (i) The optimal portfolios should reflect the international pattern of commodity expenditure. (ii) A country’s portfolio should be biased toward equities in commodities that attract a large share of its expenditure. (iii) A country would short some equities, given an appropriate structure of equity returns. (iv) Short sales of equities would allow the international economy to move toward the situation that would prevail if risk markets were complete. In our model solution, these properties take strong forms:

our earlier article, we developed model which supported the hypothesis that the proportion of the staff budget which each senator from 48 states returned unspent 1978 was significantly influenced by their political philosophy: conservatives, on average, returned higher proportion than liberals. their comment, Steven Cobb and Robert Hagemann emphasize that some state may have been omitted and, as result, the coefficients estimated from our model may be biased. They develop an approach intended to correct this, that is, a regression estimated on differences between state senators will automatically purge the regression of all state effects (p. 524), and find that the relationship between the proportion returned and political philosophy is statistically significant. Although concern about omitted is justified, there are two shortcomings with the approach that Cobb and Hagemann employ that deserve mention. First, differencing is an appropriate technique to use with cross-section data, as Carl Christ observed, because the cross-section has no analogy to the value the time series case (1966, p. 210).1 time-series, the data are uniquely ordered, but this is true cross section. The data which Cobb and Hagemann difference are cross section of two on senators within each of 48 states. The crux of the issue is which senator is subtracted from which within each state, because in economics there is usually no meaningful way to order ... cross-section observations (p. 209).2 As an illustration, consider three states (A, B, C), each with two senators (denoted by subscripts). Several differencing schemes can be proposed which generate for each state: (A,-A2),(Bj-B2), (Cl-C2); (A1-A2), (B1-B2), (C2-C1); and, (A1-A2), (B2-BB), (C2-C1), among others. Each scheme generates different set of values for the dependent variable and for the independent variable measuring political philosophy. The different data sets will produce confficting estimates of the coefficients their model and choosing among them is necessarily arbitrary. When all permutations and combinations among 48 states are considered, Cobb and Hagemann's approach produces hundreds of different data sets that yield hundreds of conflicting estimates for the same parameters. Of course, the within states can be ordered by some rule (political philosophy, proportion returned unspent, tenure office, age, etc.),3 but the choice of rule is itself arbitrary. Second, for purposes of exposition, consider the where senators are either extreme liberals or conservatives; liberals spend all of their staff budgets, whereas conservatives spend none of their funds; also, every state has two senators with the same political philosophy. this ideal case, our model will verify that political philosophy determines spending behavior, but the model presented by Cobb and Hagemann will not, for when differences are taken, the value of the dependent variable (and the independent variable for political philosophy) for every observation is identically zero and no empirical estimates can be obtained whatsoever. One *George Mason University, Fairfax, VA 22030. Research support provided by the Sarah Scaife Foundation and the Earhart Foundation is gratefully acknowledged. 'In strict sense, Cobb and Hagemann are differencing, employing lagged values. However, Christ explicitly points out that ...using first differences as is equivalent to using variables (p. 177). 2Christ adds that In pure cross-section modelthe typically have no natural order, though certain cases we can imagine putting them the order of size, social status, or distance from some focal point, or what not (p. 209, emphasis added). 3If political philosophy is used, the question then becomes which measure of political philosophy. We used three: the American Conservative Union, the AFLCIO, and the Americans for Democratic Action rankings of senators.

A survey of the empirical work involving interest rates indicates an almost universal use of seasonally unadjusted rates, apparently due to a conviction that seasonal factors are not important in interest rates. Studies by V. Kerry Smith and Richard Marcis (1972), Stanley Diller (1969) and William Gibson (1970), however, provide evidence showing that interest rates exhibit seasonal variation. Seasonality in interest rates merits careful consideration for at least two reasons. First, as noted by Gibson, An aim of the Federal Reserve System is to accommodate seasonal swings in the financial needs of trade, and the system tries to do this by removing seasonal fluctuations from interest rates. The seasonal variations remaining in interest rates suggest that the system is not wholly successful in these efforts. . (Gibson, 1970, p. 442). Second, from an econometric point of view, any model, such as a money demand model, which contains an interest rate as an independent variable should also contain seasonal dummy variables; otherwise, the coefficient of the interest rate variable may be both biased and inconsistent.' These issues underscore the importance of determining whether there is seasonality in interest rates. In this regard, it is interesting to note that the Federal Reserve does not report seasonally adjusted rates, apparently because the Board does not recognize the existence of a seasonal component. The purpose of this paper is to provide additional information regarding seasonality in interest rates. Unlike earlier studies, both daily and monthly data are analyzed. And, whereas Smith and Marcis employed spectral analysis to detect seasonality, ordinary least squares techniques with seasonal dummies are employed here. Using this technique, we find, in contrast to the findings reported by other investigators, no evidence of a significant seasonal component in monthly rates. Seasonality is, however, present in the daily rate. The plan of the remainder of the paper is as follows. In section II, the magnitude and the importance of seasonality in three interest rates are assessed. Section III contains a discussion of seasonal variation in a short-term rate employing daily as opposed to monthly data. A summary and the conclusions are presented in the last section.