This paper uses a unique panel data set of an insurer's transactions with repeat customers. Consistent with the asymmetric learning hypothesis that repeated contracting enables sellers to obtain an informational advantage over their rivals, I find that the insurer makes higher profits in transactions with repeat customers who have a good claims history with the insurer, the insurer reduces the price charged to these repeat customers by less than the reduction in expected costs associated with such customers, and repeat customers with bad claim histories are more likely to flee their record by switching to other insurers.

This paper tests the predictions of adverse-selection models using data from the automobile insurance market. I find that, in contrast to what recent research suggests, the evidence is consistent with the presence of informational asymmetries in this market: new customers choosing higher insurance coverage are associated with more accidents. Consistent with the possibility of policyholders' learning about their risk type, such a coverage-accidents correlation exists only for policyholders with enough years of driving experience. The informational advantage that new customers with driving experience have over the insurer appears to arise in part from customers' underreporting their past claim history: policyholders switching to new insurers are disproportionately ones with a poor claims history, and new customers tend to underreport their past claims history when joining a new insurer.

This paper evaluates the presence of racial disparities in the issuance of consumer credit. Using a database of credit histories, I link location-based information on race with individual credit files. After controlling for place-specific factors such as housing vacancy rates and general population demographics, I find qualitatively large differences in the amount of credit offered to similarly qualified applicants living in black versus white areas. High data quality allows distinguishing between issuer-provision (supply) and utilization of credit (demand). Additional estimates using information on payday lending provide support for idea that issuers condition lending on location.

D ESPITE failure of rich countries to grant any new tariff preferences to less developed countries (LDC's) 1960's, export earnings of manufactures by LDC's grew by more than 10 per cent per year during decade.' This phenomenon seems related to !the expansion of multinational firm. Scattered bits of evidence suggest that a large fraction of exports of manufactures from LDC's are accounted for by such firms. Between 1965 and 1968 annual exports from LDC's by foreign affiliates of United States manufacturing firms rose from 700 million dollars to 1.4 billion dollars.2 Between 1957 and 1966 Latin America's annual exports of manufactures rose from 709 million dollars to 1,613 million dollars, and subsidiaries of United States firms accounted for 65 per cent of this increase of 804 million dollars.3 IBM is said to have been largest single exporter of manufactures from both Argentina and Brazil 1969.4 As is well known, there is a large amount of literature on question of impact on currently less developed countries of large increase their exports of primary products during 19th century. We do not have much evidence on impact of contemporary investment by foreign manufacturing firms LDC's.5 The Pearson Commission (1969, p. 104) said in absence of detailed empirical studies, it is difficult to pass a definitive verdict on precise size of contribution which foreign investment has made to development. 6 Vernon (1971, p. 181), discussing extent to which foreign firms introduce into developing countries production techniques that are excessively capital intensive, says the actual facts are, as usual, obscure. There are no comprehensive data on degree to which multinational enterprises adapt their production processes to conditions of less-developed countries, and scarcely any data on comparative adaptive actions of local competitors. The next two sections present data on a sample of Japanese and United States firms South Korea, and final section discusses benefits and costs to South Korea of these foreign investments.

We do not find the relatively large prediction errors for all the regressions tested in 1965-IV surprising since the HWI rose an unprecedented 40 points from 1965-III to 1966-1, and other measures Rfi p1a1tSin., kbt, 1,,zr -nkaA,t,q npont,d t.0njrwor heating. In this same period, the nonfarm job openings series of the Bureau of Employment Security also increased dramatically, as did new hires in manufacturing. (Possibly there is a greater impact of the industrial cycle on the nonindustrial job market than has been previously recognized.) Moreover, the build-up of conventional type arms for Vietnam which got underway at the same time resulted in a shift of procurements from the West Coast to the Great Lakes and New England regions, which together have a heavier weight in the HWI.8 Tltis inip-esJing, tlit evem cru&de measures of tob vacancies may be quite sensitive indicators of pressures in the labor market. Certainly, job vacancy measures, when analyzed with care, deserve much more attention than they have received in the past.

New indicators, based on technology titles, are used to measure the impact of innovative activity on the U.S. labor market between 1909 and 1949. We find that positive technology shocks raised productivity, employment, vacancies, and labor turnover and lowered unemployment and business failures. Moreover, automotive and electrical innovations (quintessential general-purpose technologies) had a greater positive impact on employment than those in mechanical innovations. The overall results, compatible with the predictions of the real business cycle model, raise questions about the anemic recovery in employment after 1934 since the strong upsurge in technical change failed to be accompanied by vigorous job expansion.

This paper offers a framework for forecasting aggregate sales of new motor vehicles; this framework incorporates separate models for the change in the vehicle stock and for the rate of vehicle scrappage. Because this approach requires only a minimal set of assumptions about demographic trends, the state of the economy, consumer “preferences,” new vehicle prices and repair costs, and vehicle retirements, it is shown to be especially useful as a macroeconomic forecasting tool. In addition, this paper presents a new historical annual time-series estimate of motor vehicle stocks in the United States.

Wesley M. Cohen, Steven Klepper, Firm Size and the Nature of Innovation within Industries: The Case of Process and Product R&D, The Review of Economics and Statistics, Vol. 78, No. 2 (May, 1996), pp. 232-243

A4MONG the many problems raised by the X'Wactual construction of empirical input-output tables two key issues are often singled out: (1) what industrial classification scheme should be adopted and (2) how the data should be structured. Actually, these problems of industry definition and data structuring are two facets of a more fundamental problem: Given external constraints on data gathering (availability and format) which make the industry concept mostly unobservable, how can we best group the available data into an input-output table. Ideally, each industry would be defined by a single well-defined product and a separate industry should be used for different, but possibly 6closely related, products.1 A widely accepted notion of best grouping is one which minimizes the bias, i.e., the difference between the gross output forecast obtained with a disaggregated table and the forecast obtained with an aggregated table, for any final demand bill. Historically, a theoretical condition for zero aggregation bias was first derived by Hatanaka (1952).2 Briefly stated, let A denote the (n x n) disaggregated direct coefficient matrix; x denote the n-dimensional column vector of gross outputs; y denote the n-dimensional column vector of final demands; I denote the (n X n) unit matrix; S denote the aggregation operator where S is (M X n) and reads