How to handle donor complaints

Responding to donor complaints takes great care. But know who's complaining and keep things in perspective.     

How public opinion really works

The public's thinking on issues progresses through seven predictable stages, the dean of American pollsters finds. Politicians make a big mistake just looking at raw numbers.     

EMBEDDED MATRICES FOR FINITE MARKOV CHAINS

For an arbitrary subset A of the finite state space 5 of a Markov chain the so–called embedded matrix P _A is introduced. By use of these matrices formulas expressing all kinds of probabilities can be written down almost automatically, and calculated very easily on a computer. Also derivations can be given very systematically.     

TECHNOLOGY AND SPAN OF CONTROL: WOODWARD REVISITED

This study of production operations in 95 New Jersey manufacturing firms explains the widely replicated curvilinear relationship between first line supervisory span of control and Woodward's technological complexity scale. Revisiting Woodward led to the initial proposition that the relationship was a by-product of the differing degree of task variability among the major types of production operations. A subsequent literature review of administrative requirements suggested the importance of size, complexity and automaticity on supervisory span of control. Our data indicate that variations in the span of control of production operations classified according to Woodward's scale are attributable to the underlying effects of size and task complexity. Technology, whether operationalized as Woodward's production types or automaticity of machinery explained little variation in the span of control of first line supervisors.     

Approximating the distribution of the two-stage least squares estimator when the concentration parameter is small

This paper presents a new approximation to the exact sampling distribution of the instrumental variables estimator in simultaneous equations models. It differs from many of the approximations currently available, Edgeworth expansions for example, in that it is specifically designed to work well when the concentration parameter is small. The approximation is remarkable in that simultaneously: (i) it has an extremely simple final form; (ii) in situations for which it is designed it is typically much more accurate than is the large sample normal approximation; and (iii) it is able to capture most of those stylized facts that characterize lack of identification and weak instrument scenarios. The development leading to the approximation is also novel in that it introduces techniques of some independent interest not seen in this literature hitherto.