Knowledge that Transforms

This paper solves for equilibria of sequential bid (or English) auctions with affiliated values when jump bidding strategies may be employed to intimidate one's opponents. In these equilibria, jump bids serve as correlating devices which select asymmetric bidding functions to be played subsequently. Each possibility of jump bidding provides a Pareto improvement for the bidders from the symmetric equilibrium of a sealed bid, second-price auction. The expanded set of equilibria can approximate either first or second-price outcomes and produce exactly the set of expected prices between those two bounds. These results contrast with standard conclusions that equate English and second-price auctions. Copyright 1998 by The Review of Economic Studies Limited.

Because of the inherent uncertainty, promotion of innovation critically depends on screening mechanisms to select projects. This paper studies the relationship between bureaucracy and financial constraints as two such mechanisms. The lack of commitment to hard financial constraints interferes with its ex post screening capability; ex ante bureaucratic screening is optimally chosen as a substitute. However, bureaucracy makes mistakes by rejecting promising projects and delays innovation, and the efficiency loss due to soft financial constraints increases as prior knowledge becomes worse and as research stage investment requirements become lower. In a centralized economy, bureaucracy may reduce the number of parallel projects, particularly for projects with higher uncertainties and less research stage requirements. This theory fits much of the evidence and in particular it explains why the computer industry, but not the nuclear or aerospace industries, has fared so poorly in centralized economies.

There is frequently interest in testing that a scalar or vector time series is I(0), possibly after first-differencing or other detrending, while the I(0) assumption is also taken for granted in autocorrelation-consistent variance estimation. We propose a test for I(0) against fractional alternatives. The test is nonparametric, and indeed makes no assumptions on spectral behaviour away from zero frequency. It seems likely to have good efficiency against fractional alternatives, relative to other nonparametric tests. The test is given large sample justification, subjected to a Monte Carlo analysis of finite sample behaviour, and applied to various empirical data series.

This paper develops a method for analysing the dynamics of large cross-sections based on a factor analytic model. We use “law of large numbers” arguments to show that the number of common factors can be determined by a principal components method, the economy-wide shocks can be identified by means of simple structural VAR techniques and that the parameters of the unobserved factor model can be estimated consistently by applying OLS equation by equation. We distinguish between a technological and a non-technological shock. Identification is obtained by minimizing the negative realizations of the technology shock. Empirical results on 4-digit industrial output and productivity for the U.S. economy from 1958 to 1986 show that: (1) at least two economy-wide shocks, both having a long-run effect on sectoral output, are needed to explain the common dynamics; (2) although the technological shock accounts for at least 50% of the aggregate dynamics of output, it cannot by itself explain dynamics at business cycle frequencies; (3) sector-specific shocks explain the main bulk of total variance but generate mainly high frequency dynamics; (4) both the technological and the non-technological component of output show a peak for positive sectoral comovements of output at business cycle frequencies; (5) technological shocks are strongly correlated with the growth rates of the investment in machinery and equipment sectors and their inputs.

A conventional contract is a contract that each side of a bargain expects the other side to insist on, because it is standard and customary under the circumstances. The author considers a process of convention formation in which agents expectations evolve through repeated interactions in a large-population setting. Agents choose best replies given their knowledge of the precedents, subject to some inertia and random error in their choice behavior. Over the long run, this adaptive learning process tends to select contracts that are efficient, and egalitarian in the sense that the payoffs are centrally located on the efficiency frontier of the payoff possibility set. When the payoffs form a convex, comprehensive bargaining set, the process selects the Kalai-Smorodinsky solution. Copyright 1998 by The Review of Economic Studies Limited.

We propose a constructive, multivariate framework for assessing agreement between (generally misspecified) dynamic equilibrium models and data, which enables a complete second-order comparison of the dynamic properties of models and data. We use bootstrap algorithms to evaluate the significance of deviations between models and data, and we use goodness-of-fit criteria to produce estimators that optimize economically-relevant loss functions. We provide a detailed illustrative application to modelling the U.S. cattle cycle.

This article presents a monetary growth model where spatial separation and limited communication create a role for banks. Monetary policy interacts with the financial system's liquidity provision to affect the existence, multiplicity, and dynamical properties of equilibria. Moderate levels of risk aversion and tight monetary policy can lead to multiple steady states. Dynamical equilibria can be indeterminate, with oscillatory paths. Thus financial market frictions are a source of indeterminacies and endogenous volatility. Under plausible conditions, tight monetary policy raises the nominal interest rate and inflation rate and reduces long run output. Thus, a central bank's liquidity provision can promote growth.

An econometric methodology is proposed for reconciling inaccurate measures of latent data which are subject to accounting constraints. The method deals with the case in which the measurement errors are serially correlated, generalizing previous contributions. A class of efficient estimators are derived for the latent data. Consistent estimators for the weight matrices applied to the observed information based on a linear regression procedure are obtained together with confidence interval estimators for these weight matrices. Approximate confidence intervals are suggested for the latent data themselves together with specification tests for the assumptions underlying the procedure. An application of the proposed method is made to U.K. Gross Domestic Product in constant prices for 1958Q1–1989Q4.

Empirical estimates of the private value of patent protection are derived for four technology areas—computers, textiles, combustion engines, and pharmaceuticals—using new patent data for West Germany, 1953–1988. Patentees must pay renewal fees to keep their patents in force as well as legal expenses in order to enforce them. A dynamic stochastic discrete choice model of optimal renewal decisions is developed incorporating both learning and depreciation as well as the potential need to prosecute infringement. The evolution of the distribution of returns over the life of a group of patents is calculated for each technology using a minimum distance simulation estimator. Results indicate that the aggregate value of protection generated per year is on the order of 10% of related R&D expenditure.

We develop a methodology for analyzing the revenue and efficiency performance of auctions when buyers have private information about their willingness to pay and ability to pay. We then apply the framework to scenarios involving standard auction mechanisms. In the simplest case, where bidders face absolute spending limits, first-price auctions yield higher expected revenue and social surplus than second-price auctions. The revenue dominance of first-price auctions over second-price auctions carries over to the case where bidders have access to credit. These rankings are explained by differences in the extent to which financial constraints bind in different auction formats.