When haste makes sense: Cracking down on street markets for illicit drugs

This paper presents an analytical approach to the tactical question: ‘What level of enforcement over time allows one to eliminate a street market for illicit drugs while expanding the least possible total effort?’ The analysis is done in the context of Caulkins' model [6] which predicts the rate of change of dealers as a function of enforcement level and several market parameters. Our analysis suggests that the simple strategy of using the maximum available enforcement intensity until the market has been eliminated minimizes the total enforcement effort required.     

A sequential model for cracking down on street markets for illicit drugs

This paper develops a sequential decision-making model for assisting law enforcement officials in allocating resources during a crackdown operation on illicit drug markets. The sequential crackdown model (SCM) considers a probabilistic framework, where the probability of incarceration of a dealer and the probability of dealing are modeled as a function of the size of a drug market, crackdown enforcement level, drug dealer's financial hardship, and other market characteristics.The model was developed and tested in consultation with enforcement officials from Philadelphia, PA and Camden, NJ. We present a detailed, step-by-step implementation scheme for updating parameters on each day of the crackdown. Parameter estimation along with examples of model usage is provided. Through these examples, we illustrate how the SCM could be helpful in understanding the response of illicit drug markets to various enforcement strategies. We further show conditions under which an alternating crackdown policy (referred to as a crackdown-backoff) or a consistent use of maximum possible enforcement would be optimal strategies for managing a drug crackdown operation. Within the context of the model and parameter estimates, we show that a much quicker and less costly collapse could be implemented if the available enforcement resources are increased. Finally, the model provides possible conditions under which a crackdown operation would be unsuccessful in eliminating a drug market.     

Critical factors in technological innovation and their policy implications

This paper explores the critical factors which affect the innovation proccess. Some ways in which some of these factors can be influenced by appropriate policy measures are discussed. In particular, the role of the federal government in promoting innovation is discussed.The role of the government in stimulating and nurturing the innovation process is a controversial one. Proponents of the free enterprise system, many of whom are spokespersons for various industries, have persistently pointed out the deleterious effects of regulation and control on the innovation process. By contrast, advocates of an activist government role are often able to cite the protection of the common welfare as a primary need for government intervention. In truth, the “government” is a patchwork of many governments, operating through many agencies and affecting firms and individuals at several levels and leverage points. The same regulation that has deleterious effects on Industry A may be a stimulus for innovation in Industry B. Even in Industry A, the regulation may act as a force in directing efforts toward certain types of R&D programs that would not otherwise be undertaken.In this paper we examine the specific instances where innovation projects, both product or process types, were affected by government regulation. We also briefly review the critical factors which affect the innovation process and how various governments in industrialized countries have taken actions to influence these factors. Finally, we examine some general guidelines for policymaking purposes.     

Pricing U.S. Dollar Index Futures Options: An Empirical Investigation

This paper develops a pricing model and empirically tests the pricing efficiency of options on the U.S. Dollar Index (USDX) futures contract. Empirical tests of the model indicate that the market consistently overprices these options relative to the derived model. This overpricing is more pronounced for out‐of‐the‐money options than for in‐the‐money options and more pronounced for put options than for call options. To validate the above results, delta neutral portfolios are created for one‐ and two‐day holding periods and consistently generate positive arbitrage profits, indicating that on average the market overprices the options on the USDX futures contracts.     

Firms’ fundamentals,macroeconomic variables and quarterly stock prices in the US

This paper modeled the effects of firms’ fundamentals such as total assets and long-term debt and of macroeconomic variables such as unemployment and interest rates on quarterly stock prices of over 3000 US firms in the period 2000–07. The merged CRSP/Compustat database was augmented by macroeconomic variables and comprehensive dynamic models were estimated by maximum likelihood taking into account heterogeneity across firms. Likelihood ratio statistics were developed for sequentially testing hypotheses regarding the adequacy of macroeconomic variables in the models. The main findings were that the estimated coefficients of lagged stock prices in simple dynamic random effects models were in the interval 0.90–0.95. Second, comprehensive dynamic models for stock prices showed that the firms’ earnings per share, total assets, long-term debt, dividends per share, and unemployment and interest rates were significant predictors; there were significant interactions between firms’ long-term debt and interest rates. Finally, implications of the results for corporate policies are discussed.     

Executive compensation, share repurchases and investment expenditures: econometric evidence from US firms

This paper modeled the dynamic inter-relationships between average salary, bonus, and stock options granted to top executives of 700 US firms using a merged ExecuComp and Compustat database. The effects of stock options granted and exercised on firms’ share repurchases and research and development and investment expenditures were investigated, taking into account simultaneity and distributional misspecification aspects. First, firms’ total assets, intangible assets, market-to-book value, and share repurchases were positively associated with the values of stock options granted. Second, stock options exercised in the previous year were significant predictors of share repurchases indicating that firms avoided dilution of earnings per share. Third, share repurchases and stock options granted were negatively associated with expenditures on research and development and long-term investments. Overall, the results suggest that high levels of stock options granted to executives and share repurchases are unlikely to have beneficial effects for raising future productivity.     

An expectations-driven interpretation of the “Great Recession”

The boom-years preceding the “great recession” were a time of rapid innovation in the financial industry. We explore the idea that both the boom and eventual bust emerged from overoptimistic expectations of efficiency-gains in the financial sector. We treat the bankruptcy costs facing intermediaries in a costly state verification problem as a stochastic process, and model the boom-bust in terms of an unfulfilled news-shock where the expected fall in costs are eventually not realized. In response to a change in expectations only, the model generates a boom-bust cycle in aggregate activity, asset prices and leverage, and a countercyclical credit spread.     

Firm and industry characteristics influencing publications of scientists in large American companies

This study examines the relationship between the volume of scientific and technical publications (papers) produced by industrial scientists, and the characteristics of the corporations in which they work. Specifically, the study examines 1. the relationship between several key financial characteristics of U. S. industrial firms and the production of scientific papers; 2. the relationship between the amount of scientific papers published by industrial scientists and the publication of patents; 3. the relationship between the quality of the scientists employed by U. S. industrial firms and the firms' output of papers and patents. Data from 225 U. S. corporations were collected for the years 1975 through 1983. The corporations chosen for the study all have a history of consistent R and D expenditure. There is a substantial correlation between patenting and the publication of scientific papers although controlling for the size of the corporation reduces the correlation. Large firms, as measured by their annual sales, produce proportionately fewer scientific papers than do small firms. The number of elite scientists in a corporation is more highly correlated with the publication of scientific papers than with patenting.     

Estimating potential for aftermarket requirements

This article will focus mainly on utility electric plant maintenance with particular emphasis on steam (nonnuclear) turbine-generator maintenance. Our objective has been to identify and examine relationships between the target market and other recorded key operating parameters that would be useful for future forecasting of trends in the target market.     

Exploiting International Stock Market Correlations with Open-end International Mutual Funds

Investors can exploit the correlations between international stock markets by trading no-load, open-end, international mutual funds. These investors in effect cheat passive investors because they buy the mutual funds at their net asset values, which do not reflect information released during the US trading day. The strategy we examine yields an annual rate of return 800 basis points above the S&P500, over a period of almost eight years.