This paper provides a simple method to account for heteroskedasticity and cross-sectional dependence in samples with large cross sections and relatively few time-series observations. The method is motivated by cross-sectional regression studies in finance and accounting. Simulation evidence suggests that these estimators are dependable in small samples and may be useful when generalized least squares is infeasible, unreliable, or computationally too burdensome. We also consider efficiency issues and show that, in principle, asymptotic efficiency can be improved using a technique due to Cragg (1983).

This paper examines the market for catastrophe event risk – i.e., financial claims that are linked to losses associated with natural hazards, such as hurricanes and earthquakes. Risk management theory suggests protection by insurers and other corporations against the largest cat events is most valuable. However, most insurers purchase relatively little cat reinsurance against large events, and premiums are high relative to expected losses. To understand why the theory fails, we examine transactions that look to capital markets, rather than traditional reinsurance markets, for risk-bearing capacity. We develop eight theoretical explanations and find the most compelling to be supply restrictions associated with capital market imperfections and market power exerted by traditional reinsurers.

ABSTRACT Survey data on interest rate expectations permit separate testing of the two alternative hypotheses in traditional term structure tests: that the expectations hypothesis fails, and that expected future interest rates are ex post inefficient forecasts. We find that the source of the spread's poor predictions of future interest rates varies with maturity. At short maturities the expectations hypothesis fails. At long maturities, however, changes in the yield curve reflect changes in expected future rates one‐for‐one, an implication of the expectations hypothesis. This result confirms earlier findings that long rates underreact to short rates, but now it cannot be attributed to term premia.

[Using a new technique, and weekly data for 25 countries from 1994 to 1998, we analyze the relationship between institutional cross-border portfolio flows, and domestic and foreign equity returns. In emerging markets, institutional flows forecast statistically indistinguishable movements in country closed-end fund NAV returns and price returns. In contrast, closed-end fund flows forecast price returns, but not NAV returns. Furthermore, institutional flows display trend-following (trend-reversing) behavior in response to symmetric (asymmetric) movements in NAV and price returns. The results suggest that institutional cross-border flows are linked to fundamentals, while closed-end fund flows are a source of price pressure in the short run.]

Several puzzling aspects of the behavior of United States stock prices may be explained by the presence of a specific type of rational bubble that depends exclusively on aggregate dividends. We call bubbles of this type "intrinsic" bubbles because they derive all of their variability from exogenous economic fundamentals and none from extraneous factors. Intrinsic bubbles provide a more plausible empirical account of deviations from present-value pricing than do the traditional examples of rational bubbles. Their explanatory potential comes partly from their ability to generate persistent deviations that appear to be relatively stable over long periods.

We develop a framework for analyzing the capital allocation and capital structure decisions facing financial institutions. Our model incorporates two key features: (i) value-maximizing banks have a well-founded concern with risk management; and (ii) not all the risks they face can be frictionlessly hedged in the capital market. This approach allows us to show how bank-level risk management considerations should factor into the pricing of those risks that cannot be easily hedged. We examine several applications, including: the evaluation of proprietary trading operations, and the pricing of unhedgeable derivatives positions. We also compare our approach to the RAROC methodology that has been adopted by a number of banks.

A common finding is that the forward discount is a biased predictor of future exchange rate changes. We use survey data on exchange rate expectations to decompose the bias into portions attributable to the risk premium and expectational errors. None of the bias in our sample reflects the risk premium. We also reject the claim that the risk premium is more variable than expected depreciation. Investors would do better if they reduced fractionally the magnitude of expected depreciation. This is the same result that many authors have found with forward market data, but now it cannot be attributed to risk.

We investigate the pass-through from exchange rates to import prices when firms' future demands depend on current market shares. Foreign firms may either raise or lower their dollar export prices when the dollar appreciates temporarily (i.e., the pass-through may be perverse) and import prices may be more sensitive to expected future than to current exchange rates. We explore whether expected future exchange rates provide a clue to the puzzling recent behavior of U.S. import prices.

[Survey data provide a measure of exchange rate expectations superior to the forward rate in that no risk premium interferes. We estimate extrapolative, adaptive, and regressive models of expectations. Static or "random walk" expectations and bandwagon expectations are rejected: current appreciation generates the expectation of future depreciation because variables other than the contemporaneous spot rate receive weight. In comparing expectations to the process governing the spot rate, we find statistically significant bias.]