The effects of mergers on price and output: Two case studies from the airline industry

The literature on industrial organization contains very little direct evidence on the effects of actual mergers. This study estimates the effects of two recent airline mergers approved by the Department of Transportation over the objection of the Department of Justice. The merger of TWA and Ozark appears to have caused a slight increase in fares and a far greater reduction in service on city pairs out of St Louis. The merger of Northwest and Republic appears to have caused a significant increase in fares and a significant reduction in overall service on city pairs out of Minneapolis-St Paul.     

Opening the Black Box: Corporate Codes of Ethics in Their Organizational Context

A review of the literature on Corporate Codes of Ethics suggests that whilst there exists an informative body of literature concerning the prevalence of such codes, their design, implementation and promulgation, it is also evident that there is a relative lack of consideration of their impact upon members' everyday organizational behaviour. By drawing upon organizational sociology and psychology this paper constructs a contextualist and interpretive model which seeks to enable an analysis and evaluation of their effects upon individual, group and organizational behaviour.     

Temporary controls on capital inflows

During the past decade a number of countries imposed capital controls that had two distinguishing features: they were asymmetric, in that they were designed principally to discourage capital inflows, and they were temporary. This paper studies formally the consequences of these policies, calibrates their potential effectiveness, and assesses their welfare implications in an environment in which the level of capital inflows can be sub-optimal. In addition, motivated by the fact that these types of controls have often been left in place after the dissipation of the shock that lead to the controls being implemented, the paper evaluates the welfare cost of procrastination in removing these types of controls.     

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.     

Risk and the miller equilibrium: Capital structure choice with risk-averse investors

Merton Miller's (1977) tax model of equilibrium capital structure choice results in capital structure irrelevance and the existence of tax clienteles, assuming the restrictive case of risk-neutrality. Relaxation of the assumption of risk-neutrality in Miller's tax framework, allowing utility-maximizing risk-averse investors, indicates that capital structure irrelevance continues to hold under reasonable assumptions about utility. Evaluation of resulting tax clienteles shows that marginal tax rates do not restrict investors from investing in equities but do affect the tax status of purchased bonds.     

Estimating nonlinear time-series models using simulated vector autoregressions

This paper develops two new methods for conducting formal statistical inference in nonlinear dynamic economic models. The two methods require very little analytical tractability, relying instead on numerical simulation of the model's dynamic behaviour. Although one of the estimators is asymptotically more efficient than the other, a Monte Carlo study shows that, for a specific application, the less efficient estimator has smaller mean squared error in samples of the size typically encountered in macroeconomics. The estimator with superior small sample performance is used to estimate the parameters of a real business cycle model using observed US time-series data.