Knowledge that Transforms

This paper estimates a multiple-output hospital cost function using a panel data technique that allows for correlation between unobservable individual effects and observable determinants of behavior. Analysis of 1733 facilities for the period of 1987–1991 yields estimates that differ widely from those obtained from a more standard cross-sectional procedure. While the latter method results in negative and stable measures of ray economies of scale, the panel model indicates positive economies of scale that fall slightly over time.

This paper analyzes the impact of the age structure of the population on Japan's household saving rate by applying cointegration techniques to time-series data for the 1955–1993 period. It finds that the ratio of minors to the working-age population and that of the aged to the working-age population both have a negative and significant impact on the household saving rate. This finding suggests that the life-cycle model applies even in a country such as Japan, in which this model is less likely to apply due to cultural peculiarities such as the greater prevalence of intergenerational transfers.

This paper studies the problems of estimation and inference in the linear trend model yt = α + βt + ut, where ut follows an autoregressive process with largest root ρ and β is the parameter of interest. We contrast asymptotic results for the cases | ρ | < 1 and ρ = 1 and argue that the most useful asymptotic approximations obtain from modeling ρ as local to unity. Asymptotic distributions are derived for the OLS, first-difference, infeasible GLS, and three feasible GLS estimators. These distributions depend on the local-to-unity parameter and a parameter that governs the variance of the initial error term κ. The feasible Cochrane–Orcutt estimator has poor properties, and the feasible Prais–Winsten estimator is the preferred estimator unless the researcher has sharp a priori knowledge about ρ and κ. The paper develops methods for constructing confidence intervals for β that account for uncertainty in ρ and κ. We use these results to estimate growth rates for real per-capita GDP in 128 countries.

An increase in computer usage could improve product and labor quality. Unfortunately, many quality improvements are not incorporated in price indexes. Thus, a quality bias could distort conventional estimates of the marginal productivity of computers, which are based on the assumption that prices are measured without error. Using detailed industry data, we estimate a multiple-indicators, multiple-causes model that allows us to investigate this relationship, while controlling for measurement errors. Our findings suggest that computers are an important source of quality change and that computers are positively related to productivity growth when adjustments are made for measurement errors.

Most previous studies of the dynamics of industry structure, by emphasizing changes in concentration, conceal much of the nature of underlying competitive processes. Here we employ a stochastic firm growth model, estimated on U.K. data of 1979–1986 for over 200 leading firms, to derive joint predictions about the stability of market shares and the change of concentration. We find that changes in the market shares of surviving firms are the dominant influence on concentration, which is typically fairly stable in spite of considerable market-share turbulence. Advertising plays a major role in the dynamics of market shares and, therefore, affects both concentration and turbulence.

The tail index of a density has been widely used as an indicator of the probability of getting a large deviation in a random variable. Most of the theory underlying popular estimators of it assume that the data are independently and identically distributed (i.i.d.). However, many recent applications of the estimator have been to financial data, and such data tend to exhibit long-range dependence. We show, via Monte Carlo simulations, that conventional measures of the precision of the estimator, which are based on the i.i.d. assumption, are greatly exaggerated when such dependent data are used. This conclusion also has implications for estimates of the likelihood of getting some extreme values, and we illustrate the changed conclusions one would get using equity return data.

Using an expanded version of the purchasing-power-parity condition we construct simultaneous equation models for three key exchange rates which incorporate meaningful long-run equilibrium relationships and complex short-run dynamics. We show that fully dynamic out-of-sample forecasts from these models are capable of significantly outperforming those of a random walk model over horizons as short as 3 months, and that they are also more accurate than the vast majority of professional forecasts.

This paper provides evidence that suggests that financial repression has substantial direct effects on financial development, independently of its well-known influence through the level of the real interest rate. It also demonstrates that the process of economic growth is not weakly exogenous with respect to financial development. Thus financial repression may impose real costs that are additional to those suggested by previous empirical studies.

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.

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.