This paper documents, for 1947–2000, seasonalities in economic activity, stock and bond returns, and relationships among them. Evidence is consistent with an annual cycle view of economic activity and risk conditions. The power of lagged stock returns to forecast economic activity is greater for quarters ending in December and March. Mean excess returns on NYSE stocks in October through March account for 78–107% of their annual means and reflect a seasonal asymmetric return reversal tendency, which in turn explains low long-horizon variance ratios. Both market losses in April through September and subsequent returns in October through March are related, but with opposing signs, to October through March economic activity. The forecasting power of five variables is greatest for October through March. Tests of an asset-pricing model indicate that expected returns vary both cross-sectionally and over time. Implications for the debate between efficient markets and behavioral finance are discussed.

Roughly one-third of world trade is intrafirm trade. This paper starts by unveiling two systematic patterns in the volume of intrafirm trade. In a panel of industries, the share of intrafirm imports in total U.S. imports is significantly higher, the higher the capital intensity of the exporting industry.

This article calculates retirement income–replacement rates for all labor market cohorts across the last 25 years and describes the changing contributions made by private pensions, social security, and assets. The factors on which replacement rates are sensitive include position in the income distribution, the use of after‐tax instead of pretax incomes, the changing family composition of households between their pre‐ and postretirement years, and differential underreporting of income by age. The debate about reforming the U.S. retirement income system starts from a base where the current system offers high income‐replacement rates for most households, especially low‐income households.

Reload options, call options granting new options on exercise, are popularly used in compensation. Although the compound option feature may seem complicated, there is a distribution-free dominant policy of exercising reload options whenever they are in the money. The optimal policy implies general formulas for numerical valuation. Simpler formulas for valuation and hedging follow from Black–Scholes assumptions with or without continuous dividends. Time vesting affects the optimal policy, but numerical results indicate that it is nearly optimal to exercise in the money whenever feasible. The results suggest that reload options produce similar incentives as employee stock options and share grants.

During Spring 2000, the Internet Stock Index declined 45%. Using a sample of internet firms, this paper investigates whether this decline was associated with new disclosures, such as earnings, analyst forecast revisions, and web-traffic measures, or to a “reassessment” by investors of pre-existing information. We find only modest evidence that the decline was associated with new disclosures. However, returns and post-decline stock prices are significantly explained by 1999 annual report data. When earnings are decomposed into gross profit and various expenses, traditional financial information contributes significantly more in explaining the cross-sectional returns and price levels than non-financial information.

Many claim that GAAP financial information has become largely irrelevant to explaining valuations. Core et al. compare financial information's value relevance for the New Economy stocks with other stocks. We supplement their analysis with new evidence on the economic determinants of the time-series variation in the coefficients mapping financial information into prices. We document significant variation in the coefficients related to proxies for changing market growth expectations and discount rates and additional variation consistent with time-varying correlated omitted variables. Such findings make it difficult to draw unambiguous inferences about the relevance and reliability of financial information from value-relevance regressions.

This paper examines how the trading behavior of various investors impacts the market reaction to a dividend signal. The dividend signaling model incorporates asymmetric information among traders, firm insiders, and the market. This interaction among market participants explains why not all dividend increases are viewed by the market as good news. The model predicts that the announcement day returns for a dividend increase are inversely related to measures of informed trading and decreasing in the level of buy demand relative to sell demand. Further, the model hypothesizes that more informed trading results in larger dividend increases. Empirical tests confirm these predictions.

For 234 large non-financial corporations using derivatives, we report the magnitude of their risk exposure hedged by financial derivatives. If interest rates, currency exchange rates, and commodity prices change simultaneously by three standard deviations, the median firm's derivatives portfolio, at most, generates 15 million in cash and 31 million in value. These amounts are modest relative to firm size, and operating and investing cash flows, and other benchmarks. Corporate derivatives use appears to be a small piece of non-financial firms’ overall risk profile. This suggests a need to rethink past empirical research documenting the importance of firms’ derivative use.

Contrary to the predictions of the standard life-cycle model, many low-lifetime-income households accumulate little wealth relative to their incomes compared to households with high lifetime income. I use data from the Panel Study of Income Dynamics and a correlated random-effects generalized-method-of-moments estimator to decompose the rich-poor gaps in wealth-to-permanent-income ratio into the portions attributable to differences in characteristics such as labor market earnings, income uncertainty, observed demographics, and the utilization of transfer programs which may have stringent income and liquid-asset tests, and those attributable to differences in the estimated coefficients on the respective characteristics. The results suggest that wealth-to-permanent-income ratios are increasing in permanent labor income and income uncertainty, but that transfer income, with or without asset tests, discourages liquid-asset accumulation. The decompositions indicate that most of the rich-poor wealth gap is attributable to differences in average characteristics and not coefficients. The leading factor driving the gap between the rich and poor in the ratio of liquid wealth to permanent income is asset-tested transfer income, whereas the leading factor driving the gap in the ratio of net worth to permanent income is labor-market earnings.