Different continuous-time models for interest rates coexist in the literature. We test parametric models by comparing their implied parametric density to the same density estimated nonparametrically. We do not replace the continuous-time model by discrete approximations, even though the data are recorded at discrete intervals. The principal source of rejection of existing models is the strong nonlinearity of the drift. Around its mean, where the drift is essentially zero, the spot rate behaves like a random walk. The drift then mean-reverts strongly when far away from the mean. The volatility is higher when away from the mean. The continuous-time financial theory has developed extensive tools to price derivative securities when the underlying traded asset(s) or nontraded factor(s) follow stochastic differential equations [see Merton (1990) for examples]. However, as a practical matter, how to specify an appropriate stochastic differential equation is for the most part an unanswered question. For example, many different continuous-time The comments and suggestions of Kerry Back (the editor) and an anonymous referee were very helpful. I am also grateful to George Constantinides,

Theories based on incomplete contracting suggest that small organizations may do better than large organizations in activities that require the processing of soft information. We explore this idea in the context of bank lending to small firms, an activity that is typically thought of as relying heavily on soft information. We find that large banks are less willing than small banks to lend to informationally “difficult ” credits, such as firms that do not keep formal financial records. Moreover, controlling for the endogeneity of bank-firm matching, large banks lend at a greater distance, interact more impersonally with their borrowers, have shorter and less exclusive relationships, and do not alleviate credit constraints as effectively. All of this is consistent with small banks being better able to collect and act on soft information than large banks.

The German financial market is often characterized as a bank-based system with strong bank-customer relationships. The corresponding notion of a housebank is closely related to the theoretical idea of relationship lending. It is the objective of this paper to provide a direct comparison between housebanks and ``normal'' banks as to their credit policy. Therefore, we analyze a new data set, representing a random sample of borrowers drawn from the credit portfolios of five leading German banks over a period of five years. We use credit-file data rather than industry survey data and, thus, focus the analysis on information that is directly related to actual credit decisions. In particular, we use bank-internal borrower rating data to evaluate borrower quality, and the bank's own assessment of its housebank status to control for information-intensive relationships. The major results of our study support the view that housebanks are able to establish a distinct behavioral pattern consistent with the idea of long-term commitment. We find that housebanks do provide liquidity insurance in situations of unexpected deterioration of borrower ratings. With respect to loan pricing, we find no evidence for intra- or intertemporal price differentiation related to housebanking.

This paper argues that the documented discount on diversified firms is not per se evidence that diversification destroys value. Firms choose to diversify. We use three alternative econometric techniques to control for the endogeneity of the diversification decision, and find evidence supporting the self-selection of diversifying firms. We find a strong negative correlation between a firm's choice to diversify and firm value. The diversification discount always drops, and sometimes turns into a premium. There also exists evidence of self-selection by refocusing firms. These results point to the importance of explicitly modelling the endogeneity of the diversification status in analyzing its effect on firm value.

This paper studies the relationship between inflation, output, money and interest rates in the euro area, using data spanning 1980--2000. The P model is shown to have considerable empirical support. Thus, the "price gap" or, equivalently, the "real money gap" (the gap between current real balances and long-run equilibrium real balances), has substantial predictive power for future inflation. The real money gap contains more information about future inflation than the output gap and the Eurosystem's money-growth indicator (the gap between current M3 growth and a reference value). The results suggest that the Eurosystem's money-growth indicator is an inferior indicator of future inflation.

. The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly extend the nuisance parameter approach. How and why the nuisance parameter approach works and how it can be extended bears closely on recent developments in artificial neural networks. Statistical content is provided by viewing specification tests with nuisance parameters as tests of hypotheses about Banach-valued random elements and applying the Banach Central Limit Theorem and Law of Iterated Logarithm, leading to simple procedures that can be used as a guide to when computationally more elaborate procedures may be warranted. 1. Introduction In testing whether or not a parametric statistical model is correctly specified, there are a number of apparently distinct approaches one might take. T...

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In the presence of principal-agent problems, published macroeconomic forecasts by professional economists may not measure expectations. Forecasters may use their forecasts in order to manipulate beliefs about their ability. I test a cross-sectional implication of models of reputation and information-revelation. I find that as forecasters become older and more established, they produce more radical forecasts. Since these more radical forecasts are in general less accurate, ex post forecast accuracy grows significantly worse as forecasters become older and more established. These findings are consistent with reputational factors at work in professional macroeconomic forecasts.

This paper reviews the literature on tests for the correct specification of the functional form of parametric conditional expectation and conditional distribution models. In particular I will discuss various versions of the Integrated Conditional Moment (ICM) test and the ideas behind them. 1

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work. Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process. This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993). The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems. The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions. The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets. While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states. Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college- versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.