Flow and stock analysis of Polish unemployment: January 1990-June 1991*

Abstract. Unemployment is and will be for the foreseeable future one of the major issues of economies in transition. Not onIy is unemployment in post-communist economies a socially explosive problem; what happens on the unemployment front allows us to also make inferences about the state of the transition process in general. In this paper we look at Polish unemployment as it evolved from January 1990 to June 1991. A framework is developed which allows us to discuss flows into and out of unemployment. In analyzing the determinants of the various flows we discuss the macroeconomic environment brought about by the reforms and the role of prices and wages. However, we stress above all institutional and structural factors which have an impact on labour flows in the Polish post-communist economy. The stocks of several variables are also analyzed. We relate the trends of some unemployment stocks (especially the stocks of school leavers and group layoffs) to the trend of the overall stock of unemployment. We also look at the trends of vacancies and of various UIV ratios and touch upon the short run and long run trends of employment by sector. The main conclusion of the paper is that the high level of unemployment in Poland is neither due to the elimination of hidden unemployment (it actually increased in 1990!) nor a result of restructuring. The level of unemployment is high because of large inflows from outside the labour force and because hirings have been much fewer than in previous years while separations have only been slightly greater.     

Business as unusual: Coaching in Echtzeit

Business as unusual: Coaching in real time Using the concrete example of a newly founded company, the authors demonstrate how executives and employees can keep themselves, their teams and organizational unity effective and capable of action in an increasingly dynamic, complex and changing world. These managers do not ?muddle through“, they seek functioning action-coalitions where they can act as individuals in interplay with others for the good of the commonly defined whole. Increasing the effectiveness of individual managers, their units and entire businesses, decisively depends on the promotion of trust co-operation, the development of common goals and reference frameworks, and potent jointly produced diagnoses. In successful cases this leads to coherence and sense emerging for individuals, their organizational units, overlapping working teams and, in the best case, for the whole business. The authors describe their supporting function in this process and call it real time-coaching.     

Evolutionarily Stable Co-operative Commitments

If contracts cannot be fully specified Pareto optimal results may be closed off because individuals cannot rationally trust each other's promises. This paper assumes that human individuals can become internally committed not to act opportunistically and that others can detect to a certain extent whether they are dealing with an uncommitted (untrustworthy) or a committed (trustworthy) partner. Adopting an `indirect evolutionary approach' we show that co-operative commitments can survive in evolutionary competition even if conventional mechanisms like repetition, reputation, contract or promising are lacking. If detection of uncommitted individuals is neither too costly nor too unreliable there will in general be a `niche' for both committed and uncommitted actors even in one off large numbers' interactions.     

Evaluation strategies for case series: is Cox regression an alternative to the self controlled case series method for terminal events?

In this paper, we deal with the analysis of case series. The self-controlled case series method (SCCS) was developed to analyse the temporal association between time-varying exposure and an outcome event. We apply the SCCS method to the vaccination data of the German Examination Survey for Children and Adolescents (KiGGS). We illustrate that the standard SCCS method cannot be applied to terminal events such as death. In this situation, an extension of SCCS adjusted for terminal events gives unbiased point estimators. The key question of this paper is whether the general Cox regression model for time-dependent covariates may be an alternative to the adjusted SCCS method for terminal events. In contrast to the SCCS method, Cox regression is included in most software packages (SPSS, SAS, STATA, R, …) and it is easy to use. We can show that Cox regression is applicable to test the null hypothesis. In our KiGGS example without censored data, the Cox regression and the adjusted SCCS method yield point estimates almost identical to the standard SCCS method. We have conducted several simulation studies to complete the comparison of the two methods. The Cox regression shows a tendency to underestimate the true effect with prolonged risk periods and strong effects (Relative Incidence >2). If risk of the event is strongly affected by the age, the adjusted SCCS method slightly overestimates the predefined exposure effect. Cox regression has the same efficiency as the adjusted SCCS method in the simulation.     

Approximation Algorithms for Certain Network Improvement Problems

We study budget constrained network upgrading problems. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph G = (V, E), in the edge based upgrading model, it is assumed that each edge e of the given network also has an associated function ce (t) that specifies the cost of upgrading the edge by an amount t. A reduction strategy specifies for each edge e the amount by which the length (e) is to be reduced. In the node based upgrading model, a node v can be upgraded at an expense of c(v). Such an upgrade reduces the delay of each edge incident on v. For a given budget B, the goal is to find an improvement strategy such that the total cost of reduction is at most the given budget B and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint.After providing a brief overview of the models and definitions of the various problems considered, we present several new results on the complexity and approximability of network improvement problems.     

Volatility and GMM — Monte Carlo studies and empirical estimations

In this article we examine small sample properties of a generalized method of moments (GMM) estimation using Monte Carlo simulations. We assume that the generated time series describe the stochastic variance rate of a stock index. we use a mean reverting square-root process to simulate the dynamics of this instantaneous variance rate. The time series obtained are used to estimate the parameters of the assumed variance rate process by applying GMM. Our results are described and compared to estimates from empirical data which consist of volatility as well as daily volume data of the German stock market. One of our main findings is that estimates of the mean reverting parameter that are not significantly different from zero do not necessarily imply a rejection of the hypothesis of a mean reverting behavior of the underlying stochastic process.     

Family Dynamics and Self‐Injury Behaviors: A Correlation Analysis

This study tested the relationship between family dynamics and self‐injury. A total of 189 participants responded to a web‐based survey collecting information related to previous self‐injury behaviors and family dynamics. Participants were over 18 years old who had used self‐injury (intentionally harming themselves physically to relieve painful emotions without suicidal intent), but who had not used self‐injury for over a year. Results indicated that healthy family dynamics were negatively correlated and associated with higher scores of self‐injury behaviors. This study offers some evidence that family dynamics influence self‐injury behaviors. The implications for family therapy are discussed.