Noneconomic Engagement and International Exchange: The Case of Environmental Treaties

We examine the role of noneconomic partnerships in promoting international economic exchange. Since far-sighted countries are more willing to join costly international partnerships such as environmental treaties, environmental engagement tends to encourage international lending. Countries with such noneconomic partnerships also find it easier to engage in economic exchanges since they face the possibility that debt default might also spill over to hinder their noneconomic relationships. We present a theoretical model of these ideas and then verify their empirical importance using a bilateral cross-section of data on international cross-holdings of assets and environmental treaties. Our results support the notion that international environmental cooperation facilitates economic exchange.     

City-Regions,Neoliberal Globalization and Democracy: A Research Agenda

This paper argues that research on city-regions could benefit from more sustained and critical attention to the question of democracy. That is, it should examine more closely how decisions in city-regions are made, why they are made that way, and how they can be made more democratically. Much current research on politics in cities has framed the issue in terms of citizenship. That work has produced great insight. However, the attention to citizenship has prompted very little attention to democracy, even though the two concepts are deeply intertwined. Current interest in city-regions opens up the possibility that a vibrant line of research on democracy can be added to and engage with that on citizenship.     

Measuring Mutual Fund Performance with Characteristic-Based Benchmarks

This article develops and applies new measures of portfolio performance which use benchmarks based on the characteristics of stocks held by the portfolios that are evaluated. Specifically, the benchmarks are constructed from the returns of 125 passive portfolios that are matched with stocks held in the evaluated portfolio on the basis of the market capitalization, book-to-market, and prior-year return characteristics of those stocks. Based on these benchmarks, “Characteristic Timing” and “Characteristic Selectivity” measures are developed that detect, respectively, whether portfolio managers successfully time their portfolio weightings on these characteristics and whether managers can select stocks that outperform the average stock having the same characteristics. We apply these measures to a new database of mutual fund holdings covering over 2500 equity funds from 1975 to 1994. Our results show that mutual funds, particularly aggressive-growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability.     

Recovering Probability Distributions from Option Prices

This article derives underlying asset risk-neutral probability distributions of European options on the S&P 500 index. Nonparametric methods are used to choose probabilities that minimize an objective function subject to requiring that the probabilities are consistent with observed option and underlying asset prices. Alternative optimization specifications produce approximately the same implied distributions. A new and fast optimization technique for estimating probability distributions based on maximizing the smoothness of the resulting distribution is proposed. Since the crash, the risk-neutral probability of a three (four) standard deviation decline in the index (about ?36 percent (?46 percent) over a year) is about 10 (100) times more likely than under the assumption of lognormality.     

The Relation Between Patent Citations and Tobin's Q in the Semiconductor Industry

The market value of a firm is largely determined by the expected returns to the firm's tangible and intangible assets. However, accounting data generally excludes intangible assets. Financial variables which are constructed in part from accounting data, such as Tobin's Q, are thus biased. If measures of intangible capital are successful in explaining variation in Q, then a case can be made for incorporating such measures into future research. In high technology industries, such as the semiconductor industry, valuing a firm's intangible assets requires the valuation of its technological capital. Past studies have relied heavily on simple patent counts and research and development expenditures to quantify the technological component of a firm's intangible assets. This paper examines the ability of measures of intangible capital to explain variation in Q and considers an additional data source, patent citations. We find that stock variables created from citation data contain relevant information about the market's valuation of intangible assets.