Knowledge that Transforms

I analyze the relationship between firm size and the extent to which executive compensation depends on the wealth of the firm's shareholders. I use a simple agency model to motivate an econometric model of this relationship. Estimating this model on chief executive officer (CEO) compensation data using nonlinear least squares, I determine that pay-performance sensitivity (as defined by Jensen and Murphy (1990b)) appears to be approximately inversely proportional to the square root of firm size (however measured). I also analyze the properties of pay- performance sensitivity for “teams” of executives working for the same firm and show it to have similar properties as CEO pay-performance sensitivity.

The income of Puerto Rican affiliates of U.S. corporations is essentially untaxed by either Puerto Rico or the United States. This lowers the tax penalty on investment there, and also makes it attractive to shift reported taxable income from the U.S. parent corporation to the Puerto Rican affiliate. This paper investigates these two interrelated impacts of taxation by developing a structural econometric model of the joint decisions regarding investment and income shifting, and estimating the model using firm-level data on the activity U.S. corporations in Puerto Rico. The results suggest that the income shifting advantages are the predominant reason for U.S. investment in Puerto Rico.

This paper proposes an explicit test for determining the significance and the timing of slowdowns in economic growth. We examine a large sample of countries and find that a majority—though not all—exhibit a significant structural break in their postwar growth rates. We find that (a) most industrialized countries experienced postwar growth slowdowns in the early 1970s, though (b) the United States, Canada, and the United Kingdom did not, and (c) developing countries (and in particular, Latin American countries) tended to experience much more severe slowdowns which, in contrast with the more developed countries, began nearly a decade later.

The literature on energy efficiency provides numerous examples of apparently profitable technologies that are not universally adopted. Yet according to the standard neoclassical theory of investment, profit-maximizing firms should undertake all investments with a positive net present value. The standard theory also holds that the discount rate for computing the present value of a project should be the return available on other projects in the same risk class, and therefore should not depend on characteristics of the firm. This model as applied to energy-saving investments is tested by examining whether firms'characteristics influence their decision to join the Environmental Protection Agency's voluntary Green Lights program. A discrete choice regression is estimated over a large sample of participating and nonparticipating firms. Missing values in the data matrix are replaced with multiple imputations from a distribution estimated using the expectation—maximization algorithm. The results show that (1) substantial improvements in the power of hypothesis tests can be achieved through maximum-likelihood imputation of missing data, and (2) contrary to the conventional theory, the characteristics of firms do affect their decision to join Green Lights and commit to a program of investments in lighting efficiency.

Targeting is the practice of inspecting firms most likely to violate a regulation. This paper provides empirical evidence on the role of targeting in regulatory compliance. I propose that self-reporting by a firm is used to demonstrate that firms are willing to cooperate. The results indicate that there is a one-quarter penalty period following a violation. Inspections are also determined by the economic situation of the surrounding community, demonstrating that targeting opens the door to interestgroup influence. Inspections that detect violations encourage selfreporting, showing that firms demonstrate their desire to cooperate with regulators by disclosing violations.

Because women typically serve as primary care providers for their children, female labor force participation behavior is likely to be affected significantly by the costs associated with replacing maternal care with nonmaternal care. While some evidence of this phenomenon exists in the economics literature, discrepancies across studies make it difficult to provide conclusive evidence of the employment effects of these child care costs. This paper uses an improved SIPP survey design to present new evidence regarding the degree to which child care prices impede mothers' employment behavior, with additional evidence of the difference in these elasticities across marital status, empirical technique, and equation specification. This permits linking this paper to the existing evidence, drawing the conclusion that child care prices impede mothers' employment behavior significantly, with single mothers exhibiting less responsiveness in their labor force participation behavior to child care price changes than married mothers. Generally, these results support the basic finding of Ribar (1992), reject the smaller price of care elasticities found by Averett et al. (1997), Blau and Robins (1988), Connelly (1992), and Tolin (1992), but replicate the lower elasticities found in these papers by changing equation specifications. Also, significant sensitivity in the price elasticity is revealed, particularly with respect to changes in equation specification.

We amend the standard cost model to account for the role of financial capital in banking. The cost function is conditioned on the level of capital, but we model the demand for financial capital so that it can serve as a cushion against insolvency for potentially risk-averse managers and as a signal of risk for less informed outsiders. Scale economies are then computed without assuming that the bank chooses a level of capitalization that minimizes cost. We find evidence of substantial scale economies and that bank managers are risk averse and use the level of financial capital to signal the level of risk.

Recent theoretical models conjecture that the development of the financial sector is essential for economic growth. We investigate this hypothesis from a time-series perspective and find that financial sector GDP is cointegrated for many OECD countries not so much with manufacturing GDP but mostly with manufacturing total factor productivity. Moreover, this relation is in some instances characterized by long-run causality in the sense of Granger and Lin. However, even within this homogeneous group of countries, the variety of results suggests a more complex picture than is apparent from cross-sectional evidence.

The synthesis of the dynamic factor model of Stock and Watson (1989) and the regime-switching model of Hamilton (1989) proposed by Diebold and Rudebusch (1996) potentially encompasses both features of the business cycle identified by Burns and Mitchell (1946): (1) comovement among economic variables through the cycle and (2) nonlinearity in its evolution. However, maximum-likelihood estimation has required approximation. Recent advances in multimove Gibbs sampling methodology open the way to approximation-free inference in such non-Gaussian, nonlinear models. This paper estimates the model for U.S. data and attempts to address three questions: Are both features of the business cycle empirically relevant? Might the implied new index of coincident indicators be a useful one in practice? Do the resulting estimates of regime switches show evidence of duration dependence? The answers to all three would appear to be yes.

This paper examines whether monetary policy has similar effects across regions in the United States. Impulse response functions from an estimated structural vector autoregression reveal a core of regions—New England, Mideast, Plains, Southeast, and the Far West— that respond to monetary policy changes in ways that closely approximate the U.S. average response. Of the three noncore regions, one (Great Lakes) is noticeably more sensitive to monetary policy changes, and two (Southwest and Rocky Mountains) are found to be much less sensitive. A state-level version of the model is estimated and used to provide evidence on the channels for monetary policy.