Knowledge that Transforms

I NTEREST rates on long term United States Federal government bonds stood at 214 per cent as World War II ended in 1946. Now, in 1970, they are 6' 2 per cent. Treasury bill rates have increased from Y8 per cent to as high as 8 per cent. This rise in rates has been shared by all types of securities: corporate bond yields have risen from 23/4 per cent to 8%4 per cent today, state and local government bond yields from 112 per cent to 6X2 per cent, mortgage rates from 4 per cent to over 8 per cent, etc., and the upward trend has been interrupted only for brief periods during these years. Why has this rise in rates occurred? The principal explanation given by the empirical studies and econometric models is that interest rates have risen because liquidity has fallen; investors have relinquished their liquidity only to higher interest rates.' Liquidity is a sufficiently vague term to render the theory highly imprecise. Happily for its proponents, however, it can be defined in a number of ways all of which will show a decline and at least one of the ways should satisfy nearly everyone else. However, I must object for I do not believe that these commonly used ratios measuring liquidity do any more than register certain structural changes in the economy, particularly in the financial intermediary system, and cannot explain the rise in interest rates. My purpose here, therefore, is to argue this point, and secondly, to outline what I regard as a better explanation. My principal contention is that basic demand forces have caused the upward trend: the nortfolio changes are resDonses to. not causes of this trend and, in fact, have helped mitigate it. To document and examine the various hypotheses, data on the financial asset acumulation in the United States since 1945 are collected in tables 1 and 2, giving dollar amounts and percentages of total, respectively. The principal source of this data is the Federal Reserve Flow of Funds Accounts, Year-End Assets and Liabilities [2 ]. Seven basic categories of assets are defined in table 1: currency outside banks, cash reserves of commercial banks, primary bonds, trade credit, financial intermediary bonds, nonfinancial corporate stock and financial intermediary corporate stock. These categories include all of the forms of financial assets available.2 Two categories may not be clear in meaning: primary bonds and financial intermediary bonds. Primary bonds are bonds issued by the ultimate borrowers in the economy, households, business and government. Financial intermediary bonds (see table 3) are claims issued by financial intermediaries against themselves: demand and time deposits, savings and loan shares, insurance and pension reserves, etc. Financial intermediaries are defined in the customary way to include commercial banks. As shown in tables 1 and 2, all of these assets have increased in dollar terms but their relative proportions have changed. Currency, reserves, and primary bonds have not grown as rapidly as trade credit or both nonfinancial and financial corporate stocks. Financial intermediary bonds have maintained a relatively steady share of total financial assets.3' '

Franklin M. Fisher, Peter Temin, Regional Specialization and the Supply of Wheat in the United States, 1867-1914: A Reply, The Review of Economics and Statistics, Vol. 53, No. 1 (Feb., 1971), pp. 102-103

PLANNING for agricultural development usually places primary emphasis on an efficient allocation of resources. Programming models have been used extensively for this purpose in recent years [2, 9, 11, 13]. However, for many developing countries with export oriented agricultures, the problem of agricultural policy formulation is further complicated by uncertain foreign demand. In these cases, policy makers must take into account both international demand factors, such as trade restrictions and block trading agreements, and domestic factors affecting internal resource allocation such as technological innovation and structural changes which may alter relative production costs and supply possibilities. This paper illustrates the use of a programming model as a tool for the evaluation of price policies t necessary to meet alternative hypothesized foreign demand situations for Argentina. The measurement of the resultant interrelated side effects of these policies is also presented. The inclusion of international factors in the analysis is particularly relevant for Argentina given that (1) balance of payments restrictions have been shown to be a major bottleneck to growth [4, 5]; and (2) recent developments in traditional Argentine markets, such as the formation of the European Economic Community (EEC) and the incomplete implementation of the Latin American Common Market, have raised important questions regarding alternative export strategies. If the agricultural producers are reasonably responsive to relative product prices as recent evidence suggests [4, 13, 14], general price policies may be one of the simplest and most effective tools at the disposal of government to manage production to meet expected domestic and foreign demands. But it also must be recognized that price policies have other wide and varied impacts on an agriculturally oriented export economy. Among these are the impact on farm incomes and resource use in agriculture, foreign exchange earnings and government export revenues, consumer prices and agriculture's contribution to national growth. Given these multiple effects, the policy maker is forced to examine trade-offs between the potentially undesirable as well as desirable effects of an agricultural price policy. The approach contained here gives some insights into the trade-off process. Specifically, vectors of demand quantities, representing alternative export strategies in 1975, are introduced into a spatial equilibrium programming model as quantity restraints. The r sults of the analysis are then used to investigate the following series of related questions: (1) What constellation of product prices (minimum price guarantees) would be necessary to induce an efficiently organized Argentine agriculture to produce the alternative quantities once possible technological innovations have been accounted for? (2) How much land would be required for these levels of production? (3) What would be the labor requirements for each strategy? (4) How would each strategy affect consumer food costs? (5) How would each strategy affect agriculture's contribution to national product? (6) What would be the effects on governmental export earnings? Section I of this paper describes the method of analysis and the model used. Section II presents the alternative output specifications. Section III discusses prices required to meet specified demand levels while section IV describes the resulting impact on the agricultural sector with respect to farm incomes, land use, and labor requirements, and the indirect impacts on consumer welfare, net real aggregate value of production, and government export revenues and earnings. Section V draws some tentative conclusions. The major objective of this article is to demonstrate the usefulness of this type of analytical method for the analysis * Research upon which this article is based was supported by the Agricultural Development Council and the University of California. It appeared as Giannini Foundation Research Paper No. 305. 'The use of programming analysis for output price determination has been largely restricted to the United States [9, 101.

W AGE-PRICE guideposts were part of the government's economic policy from 1962 until the close of the Johnson Administration in 1968.' A particular method of policing the guideposts evolved during this period. The Administration sought, through public and private confrontations, to influence the pricing decisions of firms. We shall describe briefly this policy, propose several alternative hypotheses to explain the resultant behavior of firms, and analyze statistically those variables predicted to be associated with government success and failure in influencing firm behavior.

gives opportunity-cost/marginal-product meanings to the factor prices. Unfortunately, this is not good enough. If one wants to compute social costs of a project in terms of the economy's long-run equilibrium, then the project's physical factor requirements should also be computed in this framework, allowing for the factor-substitution possibilities which exist in the long run and which are instrumental in assuring positive marginal products for all the primary resources. To conclude, while we agree with HK that in the presence of unemployed resources money expenditures on a project overestimate social costs, we do not believe (for the reasons given in this note) that the HK model allows computation of the correct adjustments.10

The use of iterative algorithms, based on the Gauss-Seidel method or a similar approach, to solve systems of nonlinear simultaneous equations may lead to problematical situations which in theory are not surprising, but in practice are unexpected by the user. In particular, such situations may arise in the solution of econometric models for simulation purposes. One source of the problem lies in the failure of these algorithms, which repeatedly solve single equations according to some sequential ordering,1 to deal with the interaction properties of specific higher-order subsystems of closely related equations. One illustration of such a subsystem is the set of equations which determines unemployment and labor force in the Wharton Econometric Forecasting Model [1].