Real price variability depreciates the information about future prices contained in current ones. Repeat-purchase customers have, then, less incentive to acquire price information. The fact that consumers are less well informed allows firms to increase their markups and permits inefficient producers to increase their sales. Production gets reallocated toward higher-cost firms. Given the well-documented correlation between inflation and relative price variability, these results help explain some of the costs of inflation. Copyright 1994 by American Economic Association.
In the past ten years, discussions of the system and reform have increasingly been concerned with the extent of welfare dependence. However, while the idea that some individuals may be dependent upon the system for support is intuitively clear, the concept of dependence is rather ill-defined. Our aims in this paper are to clarify what is meant by dependence; to discuss the implications for data handling, measurement, and statistical modeling; and to present new results on the level and trend in dependence in the United States.
Despite recent employment gains of women in many occupations, women continue to be underrepresented in science and engineering jobs in the United States.1 Because the competitiveness of the U.S. economy is linked to the availability of highquality science and engineering professionals, attention has focused on potential educational and labor-market impediments preventing talented women from pursuing careers in science and engineering (Jeannie Oakes, 1990). This study documents another, perhaps surprising, aspect of the low representation of women in science and engineering. Women who have begun work in science and engineering jobs and have therefore cleared any educational and social hurdles impeding entry are much more likely to leave these professions than comparable men. As they leave, these women are forgoing the returns of large social and private investments. This paper documents a twofold difference in aggregate occupational exit rates of male and female scientists and engineers in the 1980's. Decomposing the aggregate exit rate into exit for different reasons, the paper reveals that the biggest differences in male and female exit behavior occur within two categories: exit from the labor force, and exit to other occupations for reasons other than promotion. Because the data also reveal that male and female scientists are different along demographic, human-capital, and occupational dimensions, multivariate models are estimated to determine whether these marked differences account for the large differences in exit rates.
This paper uses a two-good version of Hall's (1978) representative agent, permanent income model to derive a structural import demand equation for nondurable consumer goods. Under the identification restriction that taste shocks are stationary, the model is shown to imply that log imports, log domestic goods, and the log relative price of imports are co-integrated. The data decisively reject the null hypothesis that imports, the relative price of imports, and the consumption of home goods are not co-integrated. We employ the non-linear least squares technique recently proposed by Phillips and Loretan (1990> to estimate the parameters of the import demand equation. The long-run price elasticity of import demand is estimated to be -0.95. The elasticity of import demand with respect to a permanent increase in real spending is estimated to be 2.20. These estimates fall within the range reported in studies by Helkie and Hooper (1986), Cline (1989), and the many studies surveyed by Goldstein and Kahn (1985) The message of this paper is that, at least for non-durable consumer goods, it is possible to interpret the traditional import demand equation as a co-integrating regression, and to interpret the price and expenditure elasticities estimated from such a trade equation as a co-integrating vector. Estimates of the co-integrating vector can be used to recover estimates of the utility parameters of the representative household. The similarity between the OLS and Phillips-Loretan estimates of the parameters suggests that the simultaneous equation bias is not large.(This abstract was borrowed from another version of this item.)
This paper studies trade liberation between a lag country and a small one. We make two key assumptions, suggested by political debates on trade reform in small countries. First, future production requires an irreversible investment now. Second, There is a the possibility of future trade negotiations. Strikingly, anticipated trade negotiations mau make the small country strictly worse off than a fully anticipated trade war, and indeed worse off than autarchy. The reason is a negative strategic externality in the small country conferred by anyone investing in country into trade with the large one, harming its bargaining trade, so that anticipated bargeing benefits the small country on balance only if (i) the two economies are sufficiently different, and (ii) there are sufficient substitutions possibilities in consumption.
Changes in wage inequality have long been a concern of labor economists and public policymakers. When the wage premium for college graduates fell during the first half of the 1970's, many researchers blamed the decline on the increase in the relative supply of college graduates. When the college wage premium increased dramatically during the 1980's, researchers offered a variety of explanations, such as skill-biased technological change and the internationalization of the U.S. economy. In this paper, we use time-series analysis to evaluate the most common explanations given for the trends in wage inequality. Using cointegration techniques, we evaluate the link between the trends in the candidate explanatory variables and wage inequality. We show that the only variable that consistently shares the same long-run trend with our wage-inequality series is the durablegoods trade deficit as a percentage of GDP. This variable not only follows the same trend as wage inequality during most of the 1980's, but also for the period from 1949 to 1979. No other single explanation shows the same long-run consistency. I. An Analysis of Trends in Wage Inequality
One of the oldest and most studied questions in development is whether the resource and environmental conditions faced by households in low-income rural areas significantly affect productivity.' The reason for this interest is clear: if productivity is significantly constrained by these factors, then the returns to investment in the form of human capital are likely to be high, and under certain conditions there may be scope for efficiency-improving policies and programs. Given this motivation it may at first seem surprising that most of the existing literature focusing on the health-productivity relationship concentrates on the effects of nutrition. While nutrition is an important contributor to good health, other components of health, especially illness, may also influence worker productivity. Moreover, in contrast to the case of nutrition, over which households have direct control, illness is affected by exposure to pathogens, something over which individual households may have little control. This public aspect of illness makes an examination of the effects of illness on productivity particularly important from a policy perspective. This distinction between the private nature of nutrition and the public nature of illness may at least in part be evident in Tables 1 and 2. These tables present the distribution of illness and calories, respectively, by wealth quartiles in three Asian countries. What is most striking about these tables is the fact that despite clear evidence that calories are importantly associated with wealth in at least two of the countries (Bangladesh and Pakistan) there is little systematic relationship between illness and wealth in any of the countries. For example, in Bangladesh, the top quartile (in terms of wealth) of the population of men and women consumes 6 percent and 8 percent more calories, respectively, than the lowest quartile. By contrast, Bangladeshi males in the upper quartile experience 19-percent more days ill over the same period than do those in the lower quartile; the figures for the women are identical. There are several possible reasons for this pattern. As suggested earlier, one possibility is that households have little control over their exposure to illness. If this is the case, then one might well conclude that the distributional effects of illness are quite limited. A second plausible explanation is that illness is measured or reported differently for better-off households. For example, a better-off individual who is generally healthy may be more readily able to identify when he or she is ill than a poor individual with low caloric intake. Moreover, to the extent that illness is measured as an alternative to work (as is the case for the Pakistani data set), a wealthier individual may be more willing to skip work on a day that he or she is ill. If this latter point is true, then the distributional consequences of illness could be quite important despite what is evident in Table 1.2 In this paper I address these and other related issues using two of the longitudinal data sets from rural Asia from which these tables were derived. In the first section of