Inferential Causal Models: Integrating Quality & Quantity

In-depth data analysis plus statistical modeling can produce inferentialcausal models. Their creation thus combines aspects of analysis by close inspection,that is, reason analysis and cross-tabular analysis, with statistical analysis procedures,especially those that are special cases of the generalized linear model (McCullaghand Nelder, 1989; Agresti, 1996; Lindsey, 1997). This paper explores some of the roots of this combined method and suggests some new directions. An exercise clarifies some limitations of classic reason analysis by showing how the cross tabulation of variables with controls for test factors may produce better inferences. Then, given the cross tabulation of several variables, by explicating Coleman effect parameters, logistic regressions, and Poisson log-linear models, it shows how generalized linear models provide appropriate measures of effects and tests of statistical significance. Finally, to address a weakness of reason analysis, a case-control design is proposed and an example is developed.     

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.     

The baby boom, the baby bust, and the housing market A second look

I re-examine Mankiw-Weil's (MW) claim that house prices will fall 47% by 2007. MW argue that the arrival of the Baby Boom generation at adulthood drove up prices during the 1970s. When the beginnings of the Baby Bust generation matured in the 1980s, prices softened. When this generation arrives in earnest, prices will collapse. I make three points: (1) The regression upon which MW hang their prediction has an implausible -8.1% trend, which drives their prediction. (2) Demand directly influences the rental price; the asset price (MW's variable) is influenced by demand only indirectly. I re-run MW's regression, replacing the asset price with the rental price, and their prediction disappears. (3) Relying on data presented by MW, I show that housing consumption rose during the 1970s, after adjusting for income growth. Just when MW say the asset price of housing was rising, consumers behaved as if the price were falling. Consumers were right: The rental price fell by approximately 20% during the 1970s.     

Estimating the effectiveness of extension information systems using farm trials and subjective probabilities

A method of combining survey data and Dairy Herd Improvement Association (DHIA) records to achieve low cost farm trials is presented. Farm trials and surveys of current practices and production responses are useful to identify yield gaps between expectations predicted from experimental findings and actual field results. Different management schemes can be ranked using subjective probabilities and stochastic dominance to enhance successful implementation of research findings and to increase the feedback between researchers, extension workers, and producers. A survey of current masitis control practices and expected milk yield response is the example. Combining survey results with DHIA records allowed estimating the relationship between somatic cell counts (SCC) and milk yield. Eliciting beliefs about the relationship between SCC and milk yield showed that producers agreed with predictions from the statistical model. Subjective probabilities about SCC and mastitis control practices showed that our sample of experts and producers consistently ranked the different practices but extension agents had no consensus about the the most or least effective ones.     

A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis*

In this paper we compare alternative asymptotic approximations to the power of the likelihood ratio test used in covariance structure analysis for testing the fit of a model. Alternative expressions for the noncentrality parameter (ncp) lead to different approximations to the power function. It appears that for alternative covariance matrices close to the null hypothesis, the alternative ncp's lead to similar values, while for alternative covariance matrices far from H_o the different expressions for the ncp can conflict substantively. Monte Carlo evidence shows that the ncp proposed in Satorra and Saris (1985) gives the most accurate power approximations.     

Corporate Leverage and Nondebt Tax Shields: Evidence on Crowding-Out

A negative relationship between corporate leverage and tax shields has been predicted because a large nondebt tax shield reduces the expected value of interest tax savings and lessens the advantage of debt financing. Previous studies, however, have provided inconclusive and contradictory evidence on whether nondebt tax shields crowd-out debt financing. The analysis herein relies on unique constructs of discounted depreciation tax shields and presents evidence that crowding-out does not occur. Furthermore, it is shown that contradictory inferences may result from analysis of annual tax depreciation deductions instead of discounted tax shields. The findings suggest that firms with substantial cash flow from depreciation exploit their higher debt capacity by maintaining a capital structure with significantly more debt than otherwise.     

Why managers divest—Evidence from New Zealand's largest companies

Chief Executives from New Zealand's largest companies were surveyed to distinguish divesting and nondivesting companies, and to identify the relative importance of the factors and motives which led to the divestment of 208 business units in the period 1985 through 1990. The divesting companies were considerably larger and faster growing than nondivestors. The typical divestment was motivated by the need to convert unattractive assets into liquid form which could then be held to strengthen the balance sheet, or reinvested in either the core business or new areas.