Knowledge that Transforms

OVER the course of the last decade, economists have made increased use of the effective protection framework when analyzing the impact of various restrictions to international trade. A key feature of this measure is that it estimates the protection for value added in a production process rather than for product price.' Thus, while the nominal rate of protection relates solely to the final output, the effective rate accounts for the joint influence of trade restrictions on production inputs as well as on the final product. A primary requirement for estimating effective protection is accurate information on the nature and shares of production process inputs. National input-output tables have frequently served as a source for these data, but due to problems in compilation and processing these tables are generally not available until a considerable period after the date to which they apply. As such, effective protection studies which draw upon this information are frequently based on production coefficients over a decade old.2 If production processes have changed considerably in this interval, there exists the possibility that the effective protection rates may be seriously in error. This paper evaluates the direction and magnitude of bias in effective protection estimates due to the use of production data pertaining to a previous period. A separate analysis also investigates the relative importance of two sources of error (i.e., shifts in factor inputs and changes in the value added coefficient). Further, an attempt is made to assess the effect of variances in the age of the production information on the effective rates. While the analysis is confined to U.S. data, it is expected that the results apply equally to other industrial nations.

S. Schim van der Loeff, R. Harkema, Three Models of Firm Behavior; Theory and Estimation, with an Application to the Dutch Manufacturing Sector, The Review of Economics and Statistics, Vol. 58, No. 1 (Feb., 1976), pp. 13-21

and the less-developed countries. Tower's alternate explanation that A does not differ systematically while (er/f) does is not very appealing. The empirical evidence (p. 453) suggests that r is an external cost and does not vary significantly from nation to nation. Given this, the less-developed countries would have to weight e relatively twice as large as the advanced nations to explain the typical disparity in the estimates of A between the two groups.

Donald H. Straszheim, Mahlon R. Straszheim, An Econometric Analysis of the Determination of Prices in Manufacturing Industries, The Review of Economics and Statistics, Vol. 58, No. 2 (May, 1976), pp. 191-201

recently published works, Michael (1972, 1973) exhibited evidence that offers tentative support for the assertion that education not only affects consumption indirectly by raising productivity at work, but that in addition, education directly affects the consumer's lifetime real income (utility) stream. In Michael's language, education increases nonmarket productivity the efficiency with which the consumer combines market goods and leisure time to generate utility. To obtain his empirical results, Michael assumed that education enters as a parameter in the utility-production functions which characterize the consumption of goods and leisure time. He further assumed that the shifts in these functions caused by education are Hicks' neutral in the sense that both the ratio of marginal products of time and market goods, and the ratio of marginal utilities for any two of the more basic goods produced by combining market goods and time, are independent of attained educational level. These assumptions allowed Michael to conclude that as the consumer's educational level rises, the composition of market purchases will shift toward goods whose income elasticity is greater than one, and away from goods with less than unitary elasticity. A cross-section analysis of consumer expenditures showed that this hypothesis could not be rejected. As Michael himself indicated, the derivation of his test is complex; there is thus a good possibility that a quite different theory could have the same empirical implication. For example, education could affect choices by changing the goods that the consumer considers important in his or her consumption bundle.' This effect would show up as an alteration in the composition of market purchases; it could be quantified as education elasticities for a number of consumer expenditure categories; and the relationships between these elasticities and income elasticities could be just as Michael discovered in his work. Inasmuch as educational attainment tends to be highly correlated with income, other factors not being held constant, it should not be surprising to find that education and income have similar effects on the composition of market purchases. On the other hand, by restricting attention to the choice of spending income on a composite consumption good, or foregoing income to enjoy leisure, it is possible to derive some simpler tests of the direct effects of education on choices. Further, if one is willing to identify changes in the shape of indifference curves as the preference structure effect of education, then nonmarket productivity effects can be distinguished from such lifestyle effects.