The Dickensian Occupational Structure

Twelve of the novels of Charles Dickens provide a sample of 349 characters whose occupational achievement and mobility are investigated. The mobility patterns indicate more inheritance than in the United States. This cannot be accounted for by education, material inheritance, or morality (being a good or bad person). A model of quasi-perfect mobility, taking all diagonal frequencies as given, more closely represents the patterns. Determinants of achievement considered are social origins, number of siblings, education, marital status, morality. The characters from large families do better occupationally than those from small. Education functions primarily to redistribute success. The married are superior to the unmarried, with marriage functioning not as a selective mechanism, but exerting causal impact of its own. The evil are rewarded in this life. The basic path model of the stratification system of Dickens is similar to that of the United States.     

Bridging the Gap: A Generalized Stochastic Process for Count Data

The Bernoulli and Poisson processes are two popular discrete count processes; however, both rely on strict assumptions. We instead propose a generalized homogenous count process (which we name the Conway–Maxwell–Poisson or COM-Poisson process) that not only includes the Bernoulli and Poisson processes as special cases, but also serves as a flexible mechanism to describe count processes that approximate data with over- or under-dispersion. We introduce the process and an associated generalized waiting time distribution with several real-data applications to illustrate its flexibility for a variety of data structures. We consider model estimation under different scenarios of data availability, and assess performance through simulated and real datasets. This new generalized process will enable analysts to better model count processes where data dispersion exists in a more accommodating and flexible manner.