Knowledge that Transforms

Using the assumptions of the Capital Asset Pricing Model this paper presents a measure of the effective protection rate which adjusts for the industry's risk. It is shown that if the tariff on the final good is greater (smaller) than the weighted average tariff on the traded inputs, then the effective protection increases (decreases) as one moves from an industry with low risk (low beta) to an industry with high risk (high beta), holding other things constant. The empirical methodology of the new measure is also provided, as well as several illustrations from U.S. industries.

OTTO ECKSTEIN and I founded Data Resources, Inc. in 1968 after working together on Wall Street for several years. We came to know each other during the mid-1960s while I was attempting to build up the institutional stock brokerage business of Mitchell Hutchins and Co. The firm's business was mainly retail in nature, and we needed to distinguish ourselves from the competition in some fundamental way if we were quickly to establish an institutional franchise. I hit upon the idea of developing a consisting of nationally recognized authorities who would give portfolio managers expert insight into both the state of the economy and the larger political and diplomatic environment shaping economic conditions. I therefore put the following question to a number of my colleagues on Wall Street: Who is the best young economist you can think of to fill this role? The most frequent reply was Eckstein, who had just stepped down from the Council of Economic Advisers. I gave Otto a call and laid out my plans. He liked the proposal, and soon we were travelling around the country, meeting with clients and presenting our view of economic conditions. Bright and charismatic, Otto was very popular with clients. The consulting program was a great success and was later expanded with Otto's help to include Henry Kissinger and Bill Moyers. While Otto and I were on the road, we taught each other. He taught me a great deal about economics, and I introduced him to the world of commerce. Otto quickly learned that money managers were intelligent, interesting, and well-informed peoplesomething of a revelation to a long-time denizen of Washington, D. C. and Cambridge, Massachusetts. This was the first of many steps in Otto's business education, an on-the-job MBA that would eventually turn him into an accomplished businessman as well as a respected economist. Travelling was a tedious and time consuming way to impart information to our clients, and some time in 1967 Otto suggested to me that perhaps we could use a computer instead. If we set up a model that clients could access by timesharing they would be able not only to get Otto's most recent forecast when they needed it, but could shift the inputs in the model to reflect their own economic assumptions. If, for example, they thought mortgage rates would be 6% rather than 5% and that consumer spending would slow in the second half of the year rather than hold steady, they could plug these assumptions into the model and see how other variables changed. It struck me as an ambitious but promising project. Otto had formulated his basic view of how the economy worked from his early input-output research in graduate school, and then his extensive studies of the U.S. economy for Congress. Also he had produced a steady flow of micro-macro economic analyses at the Council of Economic Advisers. So, he was well along in his thinking about computer modeling of the economy. We discussed the project at great length, and I asked Otto to write a paper laying out his ideas more fully. The product concept developed by Otto had four basic elements-the model itself, a large data base, a computer, and the software-and each of them posed formidable obstacles for a fledgling enterprise like ours. Rather than use any of the econometric models then available Otto decided to build a new model of his own design-an admirable decision but an onerous task that challenged, I believe, even his formidable knowledge of economics and statistics. In building this model Otto worked with Gary Fromm of the Brookings Institution, who had developed a model of his own and was familiar with the latest advances in econometrics. He also consulted with other leading econometricians, including Martin Feldstein, Lester Thurow, and Dale Jorgenson. Even more important to our efforts was the Brookings database, which consisted not only of a large number of time series, but of subroutines for managing the data. Clearly the prior work of Fromm and his associates enabled Otto to begin much further up on the learning curve than he otherwise could have. Two members of the Brookings staff, James Craig and John Ahlstrom, joined our company and made herculean efforts to build *Paine Webber Group Inc.

Abstrac-t-This paper gathers evidence on the contribution of various techniques of exchange rate management to the output stability of twelve industrial countries. We estimate the distribution of unanticipated disturbances in outputs and the payments balances under pegged exchange rates from the 1955-1971 experience. We use this distribution to characterize the foreign exchange market intervention procedures which simultaneously minimize the output variances of the sample countries. The efficient procedures and the alternatives of managed floats, basket pegs, and the European currency area are compared according to structure and efficacy; and several implications for I.M.F. surveillance of exchange rates are drawn.

The Box-Cox technique has been frequently em- ployed in the estimation of economic models for which theory suggests no a priori appropriate functional form. Typically, an iterative OLS procedure is used to find the maximum likelihood estimates of the regression coefficients. However, Spitzer has demonstrated that biased estimates of the coefficient variances result from the use of the OLS covariance matrix. The purpose of this paper is to investigate the magnitude of the bias for two cases typical of the kind encountered in many empirical studies that employ the iterative OLS approach. The paper finds that hypothesis testing based upon the OLS covariance matrix may be quite misleading since the magnitude of the bias is quite large in one of the cases analyzed.

Conventional empirical studies of money neutrality have focussed on the response of aggregate economic measures to anticipated and unanticipated money supply shocks. The present paper uses data from the U.S. pork industry to test for money neutrality at the microeconomic level. The appeal of the pork industry stems largely from the homogeneity of the product we consider and the fact that the product is traded in what are essentially auction markets. We find that current unanticipated, but not anticipated, money supply shocks have real effects in the industry.