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Multiple Trend Breaks and the Unit-Root Hypothesis

The Review of Economics and Statistics 1997 79(2), 212-218
Ever since Nelson and Plosser (1982) found evidence in favor of the unit-root hypothesis for 13 long-term annual macro series, observed unit - root behavior has been equated with persistence in the economy. Perron (1989) questioned this interpretation, arguing instead that the "observed" behavior may indicate failure to account for structural change. Zivot and Andrews (1992) restored confidence in the unit-root hypothesis by incorporating an endogenous break point into the specification. By allowing for the possibility of two endogenous break points, we find more evidence against the unit-root hypothesis than Zivot and Andrews, but less than Perron.

Tax Credits, Labor Supply, and Child Care

The Review of Economics and Statistics 1997 79(1), 125-135
We explore the impact of the child care tax credit in the U.S. income tax system on the labor supply decisions of married women with young children by incorporating the cost of child care into a structural labor supply model. Using data from the 1986 NLSY, we find that government subsidies to child care increase labor supply substantially. Our policy simulations show that an increase in the value of the child care tax credit (i.e., percent of expenditures subsidized) would have a much larger effect on labor supply than an increase in the annual expenditure limits of the subsidy or making the subsidy refundable.

The Term Structure of Forward Exchange Premiums and the Forecastability of Spot Exchange Rates: Correcting the Errors

The Review of Economics and Statistics 1997 79(3), 353-361
We develop a framework to extract information regarding subsequent spot rate movements from the term structure of forward exchange premiums while admitting possible deviations from rationality and the presence of risk premiums. Using weekly dollar–sterling, dollar– mark, and dollar–yen data, the restrictions implied by our framework are not rejected, and spot and forward exchange rates together are well represented by a vector error correction model (VECM). Dynamic out-of-sample forecasts up to one year ahead indicate that the VECM is strikingly superior to a range of alternative forecasts, including a random walk and standard spot-forward regressions.