Labor income and risky investments: can part-time farmers compete?

In the developed countries, a majority of farm households receive at least as much income from nonfarm sources as from the farm. Such part-time farms have survived inspite of lower returns than full-time farms. This paper considers when lower returns to part-time farming could be compensated by risk-reduction due to diversification of income sources. The paper uses a dynamic portfolio choice model with labor income. The model and results could be applied in other contexts as well.     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions*

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper, we propose general‐to‐specific (Gets) model selection procedures to overcome these limitations. It is shown that single‐equation procedures are generally efficient for the reduction of recursive SVAR models. The small‐sample properties of the proposed reduction procedure (as implemented using PcGets) are evaluated in a realistic Monte Carlo experiment. The impulse responses generated by the selected SVAR are found to be more precise and accurate than those of the unrestricted VAR. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (Review of Economics and Statistics, Vol. 78, pp. 16–34, 1996) . The results are consistent with the Monte Carlo and question the validity of the impulse responses generated by the full system.     

Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ

Bayesian multiple imputation (MI) has become a highly useful paradigm for handling missing values in many settings. In this paper, I compare Bayesian MI with other methods – maximum likelihood, in particular—and point out some of its unique features. One key aspect of MI, the separation of the imputation phase from the analysis phase, can be advantageous in settings where the models underlying the two phases do not agree.     

A theory of global strategic alliances: The case of the global auto industry

The theory articulated in this paper suggests that the desire to reduce demand and competitive uncertainty are two separate, important motives for alliance formation. Taking this as a starting point, we predict the configuration of horizontal alliances that we might expect to observe within an industry when firms experience these uncertainties to different degrees. An empirical test of this theory using data from the global auto industry yields results consistent with the view (1) that alliances are a device for reducing both the uncertainties that arise from unpredictable demand conditions and those that arise from competitive interdependence, and (2) that variation of demand uncertainty and competitive uncertainty across firms explains differentials in both the intensity and structure of their horizontal alliance activity.     

Developing a cost-benefit analysis process for small-to-moderate expenditure decisions

During the Reagan administration, the federal government mandated the use of cost–benefit analysis (CBA) for regulatory decisions involving $100 million or more. While the use of CBAs has increased, less attention has been given to CBA processes involving smaller expenditures (regulatory and nonregulatory). As the federal budget tightens in the years ahead, the need to make hard decisions about these policies, programs, and technologies will increase. This paper describes a CBA process developed for the Office of Strategic Planning of the Social Security Administration; it was designed to handle small-to-moderate expenditure decisions (or for preliminary estimates of larger undertakings). A sample CBA using this process is provided, along with a discussion of the lessons that were learned from an initial application.     

Redesigning hospitals around patients and technology

Hospitals must drastically redesign themselves and revise their operations to be successful. Four major redesign initiatives will enable the traditional hospital to provide effective patient care while attaining its own profitability goals.     

A longitudinal study of the cause and consequences of changes in diversification in the U.S. pharmaceutical industry 1977–1986

The paper hypothesizes that diversification by firms based in the pharmaceutical industry during the 1977-86 time period was primarily undertaken to reduce the risks associated with being dependent upon a technologically dynamic environment. Consistent with this non-efficiency motive for diversification, declining economic performance is predicted. A longitudinal empirical analysis provides support for these propositions.