Bivariate and multivariate scaled association models. An application to homogamy of social origin and education in Hungary between 1930 and 1979

In this article we compare bivariate and multivariate models for homogamy of social origin and education to test whether bivariate models of homogamy lead to biased results. We use data on Hungarian couples married between 1930 and 1979 and loglinear models of scaled association. The results indicate some differences between bivariate and multivariate analyses. At each point of time bivariate models overestimate homogamy, both with respect to education and social origin. However, results on trends in time do not differ much between the two analyses. The exception is the period 1940–1959, in which bivariate analysis showed decreasing educational homogamy, and multivariate analysis showed an increasing trend. The latter finding can be explained by declining homogamy of social origin, as well as the weaker reproduction and cross-effects in this period.     

Choice of utility function form: its effect on classification of risk preferences and the prediction of farmer decisions

In applications of expected utility analysis, researchers are confronted with a choice among several utility functional forms. Subjective utility values and probability distributions for price and yield were elicited from Sri Lankan producers of minor export crops. Exponential quadratic and cubic utility functions were estimated. The choice of functional form was found to affect both the classification of risk attitudes and the prediction of harvesting strategy. The exponential function was the best predictor of harvesting strategy because it was the best predictor of mature harvesting. All three functions were equally poor predictors of premature harvesting.     

Pricing Options on an Asset with Bernoulli Jump-Diffusion Returns

The price movements of certain assets can be modeled by stochastic processes that combine continuous diffusion with discrete jumps. This paper compares values of options on assets with no jumps, jumps of fixed size, and jumps drawn from a lognormal distribution. It is shown that not only the magnitude but also the direction of the mispricing of the Black-Scholes model relative to jump models can vary with the distribution family of the jump component. This paper also discusses a methodology for the numerical valuation, via a backward induction algorithm, of American options on a jump-diffusion asset whose early exercise may be profitable. These cannot, in general, be accurately priced using analytic models. The procedure has the further advantage of being easily adaptable to nonanalytic, empirical distributions of period returns and to nonstationarity in the underlying diffusion process.     

Supplier Partnerships and the Small, High-Growth Firm: Selecting for Success

Strategic partnerships are commonplace in today's global economy. Effective use of partnerships are viewed increasingly as an important issue facing small, growth-oriented firms. A key debate is how small firms should manage supplier partnerships. Contrasting the debate about the extent to which small firms are inertial versus adaptive, the impact of growth on value chain partnerships with suppliers was investigated. Data collected from 91 pharmaceutical-related firms is used to test the proposition that firm growth is related positively to maintaining or to expanding relationships with suppliers, not to terminating partnerships. The paper further posits that this relationship between firm growth and the amount purchased from a supplier is moderated by the perceived effectiveness of the value-chain partnerships such that when effectiveness is higher, the relationship between sales growth and the amount purchased from a value-chain partner is stronger. The propositions, which are tested with regression analysis, are supported partially.     

Dynamics of the federal funds target rate: a nonstationary discrete choice approach

We apply a discrete choice approach to model the empirical behaviour of the Federal Reserve in changing the federal funds target rate, the benchmark of short‐term market interest rates in the US. Our methods allow the explanatory variables to be nonstationary as well as stationary. This feature is particularly useful in the present application as many economic fundamentals that are monitored by the Fed and are believed to affect decisions to adjust interest rate targets display some nonstationarity over time. The chosen model successfully predicts the majority of the target rate changes during the time period considered (1994–2001) and helps to explain strings of similar intervention decisions by the Fed. Based on the model‐implied optimal interest rate, our findings suggest that there is a lag in the Fed's reaction to economic shocks during this period. Copyright © 2004 John Wiley & Sons, Ltd.