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.     

AN EMPIRICAL INVESTIGATION INTO THE IMPACT OF PROFIT SHARING SCHEMES OF EXECUTIVIES ON THE CONTENT OF CORPORATE SUBMISSIONS ON PROPOSED ACCOUNTING STANDARDS

This paper examines the comments submitted by UK companies on 20 proposed accounting standards to test the hypotheses that executives favor standards that increase, or dampen the variance of, accounting profit numbers on which their incentive remuneration is based. Test results were generally as hypothesised but only the profit variance outcomes were statistically significant. Allowing for political environment changes affected only the profit variance results. There was no evidence that the relative monetary size of bonus payments was a significant lobbying factor. No significant differences were found between the lobbying preferences of companies with or without executive incentive schemes.     

An Analysis of Differences in Earnings Between Small and Large Commercial Banks

This paper introduces a simple, yet rich, measure of efficiency changes based on the revenue-generating-ability (RGA) principle. Using this principle, we explain the connections between efficiency changes and the variables, such as pretax profits, interest expense, non-interest expense, profit margins, loan loss provision, and asset quality. These connections are used to explain earnings differences between small and large commercial banks.     

Spreads, depths, and the impact of earnings information: an intraday analysis

For a sample of NYSE firms, we show that wide spreads are accompaniedby low depths, and that spreads widen and depths fall in responseto bigger volume. Spreads widen and depths fall in anticipationof earnings announcements; these effects are more pronouncedfor announcements with larger subsequent price changes. Spreadsare also wider following earnings announcements, but this effectdissipates quickly after controlling for volume. Collectively,our results suggest liquidity providers are sensitive to changesin information asymmetry risk and use both spreads and depthsto actively manage this risk.     

Innovative productivity and returns to scale in the pharmaceutical industry

This study shows that firms in the pharmaceutical industry experience decreasing returns to scale in R & D as the level of R & D expenditures rises. The paper presents the results of our study of the innovative output of 16 pharmaceutical firms over a 19 year period. Given the strong correlation between R & D budgets and firm size, our study suggests the wave of mergers in the industry may yield less innovative productivity than managers expect.     

The Effects of Screening and Monitoring on Credit Rationing of SMEs

In this paper, we seek to empirically assess which determinants of the capability and incentives of banks to screen and monitor firms are significant in explaining credit rationing to Italian SMEs. After testing for the presence of non‐random selection bias and the potential endogeneity of some determinants of interest, the probit model results we obtain suggest that the average banking size and the multiple banking relationship phenomenon are statistically significant factors affecting credit rationing, presumably through their impact on the aforementioned banks' capability and incentives. Other potential determinants of banks' incentives to monitor and screen, such as local banking competition and firm' capacity to collateralize, are never significant. However, when we split the sample according to the level of competition in credit markets, we find that the estimated marginal effects of all significant determinants of interest are larger in absolute value than those obtained when using the whole sample.