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Demand and Supply Functions for Stocks of Euro-Dollar Deposits: An Empirical Study

The Review of Economics and Statistics 1972 54(4), 381
T HIS study considers the market for Eurodollar deposits as a structural system with determinate demand and supply relationships. It is important at the outset to distinguish the stock demand for Euro-dollar deposits, which we shall be investigating here, from the flow demand for Euro-dollar credit. Machlup (1970) points out that the demand for Euro-dollar credit is a demand for a flow of funds to borrowers who, in turn, plan to pay out the funds they have borrowed. The demand for Euro-dollar deposit balances is, on the other hand, a demand for money, or near-money, to hold. We shall be concentrating upon the factors affecting the demand for a stock of Eurodollar deposits to hold.1 Since we shall not be taking the stock of Euro-dollar deposits in existence at a point in time as exogenously given, we shall also be identifying an equation to determine the stock of Euro-dollar balances supplied by Euro-dollar issuing institutions (hereafter Euro-banks). This will be based on an identifiable stock of reserves held by Euro-banks. Briefly, the procedure and results are as follows. Quarterly data from 1964-III through 1970-IV are employed to obtain parameter estimates for scale and substitution arguments in a stock demand function for Euro-dollar deposit balances as well as to obtain an estimated equation for the stock of dollar claims produced by Euro-banks. The empirical results suggest that a stable stock-demand function for Euro-dollar deposit balances exists along with a stable stock-supply function for Eurodollar deposits. The results also suggest that about 40 per cent of the growth of Euro-dollar deposits in the 1964-III 1970-IV period was due to the multiple deposit expansion process.

Corporate Earnings and Tax Shifting in U.S. Manufacturing, 1930-1968

The Review of Economics and Statistics 1972 54(3), 235
FEW economic magnitudes have commanded as much attention from economists as the earnings of capital. Despite this emphasis, it is interesting that there exists scant empirical evidence concerning the determinants of capital income over the relatively long run. This is rather surprising since the short-term behavior of profits has come under considerable scrutiny by econometric model builders. Existing evidence concerning long-run behavior stems primarily from recent studies of the incidence of the corporation income tax.' In order to isolate the effects of the tax, investigators have had to identify and eliminate the effects of the nontax determinants of profit. As would be expected, conclusions regarding tax incidence have turned out to be extremely sensitive to the underlying model of profit. It is the purpose of this paper to ascertain the extent to which a model based upon standard competitive behavior is capable of explaining the time path of corporation earnings over a period of almost forty years. Since most incidence studies have been based upon models which explicitly or implicitly assume nonprofit maximizing behavior, such a study will provide a useful extension of the empirical evidence concerning the behavior of profit as well as a test of the relative efficacy of standard economic theory. Furthermore, unlike existing studies, the model will be tested in such a way that the contribution of such determinants of profit as technological change, capital intensity and aggregate demand can be isolated. Since indirect evidence on such factors exists from studies of aggregate production functions and business cycle behavior, the plausibility of the estimates can be determined. Finally, the model can be used to provide additional evidence concerning the shifting of the corporation income tax. If the model is specified correctly, the introduction of a corporation income tax variable into the estimating equation should have little effect. In what follows, a model of corporation earnings is developed and tested for the manufacturing sector of the United States economy for the period 1930-1968. The model is based upon the hypothesis that the return to capital depends upon its marginal productivity and short-run fluctuations in output. It is found that the model does quite well in explaining the time path of manufacturing earnings over the sample period; all coefficients are statistically significant, have the right sign, and are of reasonable magnitude. These estimates also provide evidence concerning the underlying aggregate production function. Specifically, the estimates imply an elasticity of factor substitution of less than one, and technical progress which is not solely of the Harrod-neutral variety. At this point the question of short-run corporation tax shifting is taken up. A suitably defined tax variable is introduced into the statistical model. It is found that the tax variable does not significantly add to the explanatory power of the model; its coefficient is small in absolute value and is statistically insignificant. It is concluded, therefore, that corporations bear the full burden of the corporation income tax in the short run.

Controls or Competition--What's at Issue?

The Review of Economics and Statistics 1972 54(3), 224
PpT HE issue is stated that after Phase II the United States faces or competition. Leading economists Charls Walker, Charles Schultze, Murray Weidenbaum and others who oppose controls in principle nevertheless caution (forecast?) against expecting an early return to free markets. The general prescription comes to something like Weidenbaum's: Basically, we need to deal with those concentrations of private economic power which have become insulated from the influences of aggregate monetary and fiscal policy. 1 Charls Walker, Undersecretary of the Treasury, recently predicted voluntary controls for Phase III in a talk before the Manufacturing Chemists Association.2 Walker said this will require what Paul McCracken, former Chairman of the President's Council of Economic Advisers, called a 'social compact'a consensus among business and labor that substantial gains in real economic growth must be paid for by wage and price stability. Arguments supporting such a definition of the issue are grounded in believed about concentration of economic power and concern derived from accepted interpretations of these facts. The evidence concerning these facts will be reviewed in a moment.

Real Money Balances: An Omitted Variable from the Production Function?

The Review of Economics and Statistics 1972 54(3), 290
SEVERAL writers have argued that real money balances are a factor of production.1 No one, however, has directly tested the hypothesis that real money balances are a factor input.2 The purpose of our paper is to report the results of such a test. We find that real money balances, regardless of definition, enter significantly in a Cobb-Douglas production function fitted to annual data over the period 1929-1967 for the private domestic sector of the United States economy. Quantity indices of output, capital and labor, published by Christensen and Jorgenson (1970) and adjusted both for quality changes and rates of utilization, are employed to estimate the production function. Data for nominal money balances are taken from Friedman and Schwartz (1970). Our results have important implications for production function analysis, the explanation of total factor productivity, and monetary growth theory. The plan of the paper is as follows. Section II deals with a brief discussion of the rationale for the presence of real balances in the production function. In section III we present the production function used in the study and discuss the data employed. Results are given in section IV. A summary and conclusions follow in the final section.

The Market Price of Risk, Size of Market and Investors' Risk Aversion: A Comment

The Review of Economics and Statistics 1972 54(2), 204
that the ordinary least squares coefficient corresponding to the variable with the error will be biassed downward (in absolute value), and it is also seen that the direction and extent of bias in the other coefficients will depend directly on the covariances between those coefficient estimates and that of the offending variable. In particular, it may be useful to note that the sign of the bias is given by: sgn ( gj 8 *j) = ( l)(sgn cov ,2j,, ) (sgn j,