Exchange rate exposure and foreign exchange derivatives: do ineffective hedgers modify future derivatives use?

Recent studies examining the relationship between stock returns and exchange rate changes have provided evidence that the exchange rate exposure of non-financial companies is reduced by the use of foreign exchange derivatives. Building on such research, this study investigates whether past ineffective derivative hedging contributes to explaining future derivatives use. To the extent that companies monitor the effectiveness of their currency risk management practices, past ineffective hedgers can be expected to modify their future use of foreign exchange derivatives accordingly. In our study of 94 non-financial US multinationals, we provide evidence that the change in derivatives use from 1996–1998 to 1998–2000 can be explained in part by the ineffective hedging of currency risk in 1996–1998, controlling for variables associated with theories of optimal hedging. Additional analyses confirm that such primary results are robust to firm size, the level of foreign operations, and the use of derivatives to partially hedge currency risk. Our results imply that as exchange markets and risk management practices change, the use of derivatives to manage exchange rate risk also changes. Our contribution to this field of study is that we find evidence that past ineffective hedgers tend to increase their future use of FXDs.     

Multilateral Reforms of Trade and Environmental Policy

The paper analyzes environmental tax policy reform using a competitive model of world trade that includes production‐generated environmental damage (pollution) and trade tariffs. The authors examine the feasibility of Pareto‐improving multilateral reforms of environmental taxes, and show that any environmental tax reform that is mutually welfare‐improving when compensating lump‐sum transfers are assumed is also welfare‐improving when a suitable tariff reform (but no transfers) is combined with the tax changes. Several specific reform proposals are developed. These results expand the feasible set of mutually improving policy proposals for international policy initiatives.     

The Impacts of Unemployment on Alternative Poverty Rates

The analysis uses March Current Population Survey data to estimate state-level cross-section/time-series models of the effects of the unemployment rate on alternative poverty rates. The measures include the official headcount rate, and alternatives based higher thresholds, revised equivalence scales and income defined as inclusive and exclusive of taxes and cash and in-kind transfers. The estimated effects turn critically on the measurement approaches, both for the total sample population and for four population sub-groups. For several alternative poverty rate measures, the unemployment rate has no significant impact on poverty. By contrast, real per-capita median earnings have strong and consistently negative effects on the poverty rates of all groups studied. The findings thus provide important lessons for researchers exploring the links between economic conditions and poverty, and for policy makers developing poverty reduction strategies.     

Corporate Board Composition, Protocols, and Voting Behavior: Experimental Evidence

We examine voting by a board designed to mitigate conflicts of interest between privately informed insiders and owners. Our model demonstrates that, as argued by researchers and the business press, boards with a majority of trustworthy but uninformed “watchdogs” can implement institutionally preferred policies. Our laboratory experiments strongly support this conclusion. Our model also highlights the necessity of penalties on insiders when there is dissension among board members. However, penalties for dissent appeared to have little impact on the experimental outcomes.     

Bivariate and multivariate scaled association models. An application to homogamy of social origin and education in Hungary between 1930 and 1979

In this article we compare bivariate and multivariate models for homogamy of social origin and education to test whether bivariate models of homogamy lead to biased results. We use data on Hungarian couples married between 1930 and 1979 and loglinear models of scaled association. The results indicate some differences between bivariate and multivariate analyses. At each point of time bivariate models overestimate homogamy, both with respect to education and social origin. However, results on trends in time do not differ much between the two analyses. The exception is the period 1940–1959, in which bivariate analysis showed decreasing educational homogamy, and multivariate analysis showed an increasing trend. The latter finding can be explained by declining homogamy of social origin, as well as the weaker reproduction and cross-effects in this period.     

Using an approximate kiefer-weiss solution for testing insect population densities

Summary A sequential testing procedure called 2-SPRT for the meanμ of the negative binomial distribution with known exponentk is presented. For any fixedμ ₀(μ ₁<μ ₀<μ ₂), the 2-SPRT provides an asymptotic solution to the modified Kiefer-Weiss problem. Determination ofμ ₀ such that the test provides an approximate solution to the Kiefer-Weiss problem is described. The behavior of the 2-SPRT and the Sequential Probability Ratio Test is investigated using Monte Carlo methods. The error probabilities and the average sample numbers are compared. All the computations were carried out on the Alabama Supercomputer.     

VAR,ERROR CORRECTION AND PRETEST FORECASTS AT LONG HORIZONS

This paper focuses on the construction of forecasts over long horizons where a typical long-horizon forecast might span four years using 20 to 40 years’ data. It is argued that the presence of persistence in the form of unit or near-unit autoregressive roots poses substantial difficulties for long-horizon interval and point forecasting. These difficulties may not be overcome even by efficient pre-testing or model-selection procedures and might, in general, lead to point forecasts with large asymptotic root mean squared errors and undesirably wide prediction intervals.