Job growth in early transition: Comparing two paths*

Small start‐up firms are the engine of job creation in early transition. We ask about differences in their growth across two different transition economies: Estonia, which experienced rapid destruction of pre‐existing firms, and the Czech Republic, which reduced the old sector gradually. We find that the majority of job growth corresponds to within‐industry reallocation. The within‐industry growth of small start‐up firms is similar in the two countries, in line with the convergence to Western industry firm‐size distributions. We also find similar patterns in the evolution of wage differentials between start‐ups and old firms and small differences in the extent of low‐wage employment in start‐ups across the two transition paths. JEL Classifications: J2, J3, J4, L1, O1, P2.     

'High-performance' Management Practices, Working Hours and Work–Life Balance

The effects of selected high‐performance practices and working hours on work–life balance are analysed with data from national surveys of British employees in 1992 and 2000. Alongside long hours, which are a constant source of negative job‐to‐home spillover, certain ‘high‐performance’ practices have become more strongly related to negative spillover during this period. Surprisingly, dual‐earner couples are not especially liable to spillover — if anything, less so than single‐earner couples. Additionally, the presence of young children has become less important over time. Overall, the results suggest a conflict between high‐performance practices and work‐life balance policies.     

Restricted electricity use among poor urban households

For a variety of reasons, this article argues, electricity must be seen by policy‐makers in South Africa not as the sole provider of all future household energy needs, but rather as one component of an energy mix which includes such ‘transitional’ fuels as coal, gas and paraffin. The reasons for this are that electricity is expensive for poor households; it is subject to power failures and disconnections for non‐payment; the poor find it difficult to monitor and to control their consumption; appliances are expensive and several are required to make best use of electricity; people prefer other fuels because they are familiar and have strong personal and cultural associations, and because Eskom is not trusted owing to its past ties to illegitimate local authorities and misunderstanding of electricity and how its use is monitored and charged for. Further, it is mistaken to equate ‘development’ with total electrification: most developed countries have fuel mixes which include gas and coal, particularly for cooking and heating. Accepting an affordable fuel mix for the poor in particular would focus attention on the problems currently associated with paraffin, gas and coal, namely fires, poisoning and air pollution.     

Not just understudies: The dynamics of short-term leadership

Contrary to the stereotype that the period between CEOs is a hiatus, interim and acting executives serve during an important strategic window. A model is presented to illustrate the dynamics of short-term leadership, including the precipitating circumstances for the temporary administration, the tasks of short-term leadership, and the moderating factors seen to affect the selection and success of the next chief executive. Researchers and practitioners are urged to consider more carefully the potential that a well-managed interregnum has to repair damage from a traumatic departure, buffer between administrations, and prepare the organization to accept and work with new leadership. © 1995 by John Wiley & Sons, Inc.     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

Developing a tutoring module for presentation of computerized patient management problems

The simulation problem is one of the most commonly used formats in computer-assisted instruction (CAI). In medical education, a patient simulation problem is known as a patient management problem (PMP). A number of computerized PMP systems are currently available. However, to date, there is no record of PMP systems having been developed using artificial intelligence. This is noteworthy since artificial intelligence techniques could help in the generation of more effective and intelligent instructional systems.

This paper analyzes and evaluates existing instructional simulation software in clinical medicine in terms of effective educational design attributes. Components of effective PMP systems thus identified are incorporated into a computerized instructional system which uses artificial intelligence techniques for teaching problem-solving and diagnostic skills to undergraduate medical students.