Lorrie L. Hoffman

New evidence on factors that influence the wealth effects of international joint ventures

Abstract Studies of the wealth effects of international joint ventures report mixed results. However, little work has been done to explain this enigma. We explain this riddle by identifying the factors which influence the wealth effects. Using a sample of 100 ventures that were announced between 1979 and 1994 we find that, on average, international joint ventures have virtually no immediate net impact on shareholder wealth. However, in-depth analysis reveals interesting findings that could explain why the results of previous studies are mixed. We find that the market reaction is more favorable when U.S. firms establish joint ventures in Asian countries, less favorable when the joint venture is established in lower risk developing countries, and less favorable when the joint venture is a manufacturing operation. In an increasingly globalized world, the results of this study hold important managerial implications.

Characterizing Linear Birth and Death Processes

Abstract This research determined the manner of convergence of certain Markov processes to their steady state limiting distributions. This article looks at linear birth and death processes with birth rate at each state determined by the immigration constant a and the natural growth multiplier b; with death rate at each state determined by fixed execution constant c and the natural declination multiplier d. All parameters are nonnegative. There is a reflective barrier at state 0. It is shown that when the natural growth multiplier is less than the declination parameter a limiting distribution exists, that is, when the multiplier difference is negative. We define a modal indicator as the ratio of the sum of the death parameters c and d diminished by immigration a to the multiplier difference. It is shown that when the modal indicator is negative then the mode occurs at state 0. When the indicator is an integer then the process is bimodal with the mode at that integral value and at the next larger integer. W...

Estimation of Parameters in the Joinpoint Two-Regime Regression Model

Of interest is the specific model called the joinpoint two-regime regression or broken line model composed of one regression line and a horizontal ray. This is a very restricted but highly useful subset of the well-researched change point problem. The usual approach, first presented by Quandt (1958), is to find estimates of the slope, intercept, and joinpoint by assuming that the error terms are generated from a normal distribution. For our specific model this method of estimation was shown by Gill (2004) to produce the maximum likelihood estimates. We develop a method that does not rely on the assumption of normal, independent, identically distributed (iid) error terms. We illustrate the method by applying it to proximity indexes of whale cow and calf pairs, and compare our new method to the Quandt estimates in a simulation study showing our new method performs adequately in the normal iid error term model and is preferable in small samples where error terms are correlated with non constant variance.