This paper tests if real and financial linkages between countries can explain why movements in the world's largest markets often have such large effects on other financial markets, and how these cross-market linkages have changed over time. It estimates a factor model in which a country's market returns are determined by global, sectoral, and cross-country factors (returns in large financial markets) and by country-specific effects. Then it uses a new data set on bilateral linkages between the world's five largest economies and approximately 40 other markets to decompose the cross-country factor loadings into direct trade flows, competition in third markets, bank lending, and foreign direct investment. In the latter half of the 1990s, bilateral trade flows are large and significant determinants of how shocks are transmitted from large economies to other stock and bond markets. Bilateral foreign investment is usually insignificant. Therefore, despite the recent growth in global financial flows, direct trade still appears to be the most important determinant of how movements in the world's largest markets affect financial markets around the globe.

This paper analyzes the link between rising city crime rates and urban flight. Each additional reported crime is associated with a roughly one-person decline in city population. Almost all of the crime-related population decline is attributable to increased out-migration rather than a decrease in new arrivals. Households that leave the city because of crime are much more likely to remain within the Standard Metropolitan Statistical Area (SMSA) than those that leave the city for other reasons. Migration decisions of highly educated households and those with children are particularly responsive to changes in crime. Causality appears to run from rising crime rates to city depopulation.

We reformulate the “Hotelling valuation principle” to take into account the special production characteristics of hard-rock minerals. The data requirements of the revised model are still parsimonious, but the resultant valuations are some 40% below those produced by the Hotelling valuation principle. Our valuation equations are also “user-friendly,” allowing the valuer to specify price and cost expectations that need not comply with the Hotelling rule. Empirically, our model provides estimates of market value for producing mineral properties that are more accurate than those produced by the Hotelling valuation principle.

This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context of our model, that persistent volatility is caused by traders experimenting with different beliefs based upon past profit experience and their estimates of future profit experience. A major theme of our paper is to introduce adaptive agents in the spirit of Sargent (1993) but have them adapt their strategies on a time scale that is slower than the time scale on which the trading process takes place. This will lead to positive autocorrelation in volatility and volume on the time scale of the trading process which generates returns and volume data. Positive autocorrelation of volatility and volume is caused by persistence of strategy patterns that are associated with high volatility and high volume. Thee following features seen in the data: (i) The autocorrelation function of a measure of volatility such as squared returns or absolute value of returns is positive with a slowly decaying tail. (ii) The autocorrelation function of a measure of trading activity such as volume or turnover is positive with a slowly decaying tail. (iii) The cross correlation function of a measure of volatility such as squared returns is about zero for squared returns with past and future volumes and is positive for squared returns with current volumes. (iv) Abrupt changes in prices and returns occur which are hard to attach to 'news.' The last feature is obtained by a version of the model where the Law of Large Numbers fails in the large economy limit.

In the first half of this century, special attention was given to two features of the business cycle: the comovement of many individual economic series and the different behavior of the economy during expansions and contractions. Recent theoretical and empirical research has revived interest in each attribute separately, and we survey this work. Notable empirical contributions are dynamic factor models that have a single common macroeconomic factor and nonlinear regime-switching models of a macroeconomic aggregate. We conduct an empirical synthesis that incorporates both of these features. It is desirable to know the facts before attempting to explain them; hence, the attractiveness of organizing business-cycle regularities within a model-free framework. During the first half of this century, much research was devoted to obtaining just such an empirical characterization of the business cycle. The most prominent example of this work

This paper uses CPS data to analyze gender differences in black-white annual earnings trends over the 1970s and 1980s. We find that in at least two respects black women fared better than men over this period. First, due to decreasing relative annual time inputs for black males, but not black females, black women experienced increases in both annual earnings and estimated wages compared to white women, while black men gained only in terms of wages compared to white men. Second, since the gender earnings gap among whites was narrowing during this time, as black women's wages rose relative to white women's, they also made faster progress relative to white males than did black males. In other important respects, however, the experience of black men and women over the period was similar. First, for both groups, while earnings and wages relative to whites of the same sex rose during the 1970s, they stagnated or declined during the 1980s. Second, in contrast to the 1960s, younger blacks did not fare better than older blacks during the 1970s and 1980s. While in 1971, both unadjusted wage ratios and adjusted earnings ratios were highest within each sex group for labor market entrants, by 1988 these ratios were fairly similar across experience groups.

This paper analyzes the relationship between maternal labor supply and children's cognitive development, using a sample of three- and four-year-old children of female respondents from the 1986 National Longitudinal Surveys Youth Cohort (NLSY). Respondents in the NLSY were aged 21 to 29 in 1986; thus our sample consists of children of relatively young mothers. We show that for this group the impact of maternal labor supply depends upon when it occurs. Maternal employment is found to have a negative impact when it occurs during the first year of the child's life and a potentially offsetting positive effect when it occurs during the second and subsequent years. We find some evidence that boys are more sensitive to maternal labor supply than girls though the gender difference is not significant. The negative first-year effect is not mitigated to any great extent by the increased maternal income that accompanies it, though the increase in maternal income does appears to play an important role in producing the positive effect in the second and later years.

In the authors' analysis of nonwork spells for Workers Compensation Insurance, they use the family of generalized gamma distributions for the structural model of failure time and both nonparametric and parametric controls for heterogeneity. These specifications allow for nested likelihood tests of not only the correct form for parametric heterogeneity, but for the structural distributions as well. The authors find in their data that while heterogeneity is important, both parametric and nonparametric types of control do about equally well. The "best" (in terms of statistical fit) structural distribution is the generalized gamma function; the exponential distribution fits especially poorly.

Michael D. Creel, John B. Loomis, Confidence Intervals for Welfare Measures with Application to a Problem of Truncated Counts, The Review of Economics and Statistics, Vol. 73, No. 2 (May, 1991), pp. 370-373

Consumption (Economics); Income