The problem of Iraqi nationalism

This article analyses the development of a tenuous Iraqi national identity since the creation of the Iraqi state in 1920. Informed by the ideas of Anthony D. Smith, Benedict Anderson and Eric Hobsbawm, it argues that various political actors in Iraq have sought to reshape historical memory and thus forge a national identity. Despite many setbacks and a long series of authoritarian regimes seeking to appropriate Iraqiness for their own political purposes, and recently the threat from Kurdish irredentism, this article nevertheless contends that an Iraqi cultural ‘ethnicity’ has been created over the past nine decades.     

The nearest neighbor Spearman footrule distance for bucket, interval, and partial orders

Comparing and ranking information is an important topic in social and information sciences, and in particular on the web. Its objective is to measure the difference of the preferences of voters on a set of candidates and to compute a consensus ranking. Commonly, each voter provides a total order of all candidates. Recently, this approach was generalized to bucket orders, which allow ties. In this work we further generalize and consider total, bucket, interval and partial orders. The disagreement between two orders is measured by the nearest neighbor Spearman footrule distance, which has not been studied so far. For two bucket orders and for a total and an interval order the nearest neighbor Spearman footrule distance is shown to be computable in linear time, whereas for a total and a partial order the computation is NP-hard, 4-approximable and fixed-parameter tractable. Moreover, in contrast to the well-known efficient solution of the rank aggregation problem for total orders, we prove the NP-completeness for bucket orders and establish a 4-approximation.     

Prediction in trend-renewal processes for repairable systems

Some problems of point and interval prediction in a trend-renewal process (TRP) are considered. TRP’s, whose realizations depend on a renewal distribution as well as on a trend function, comprise the non-homogeneous Poisson and renewal processes and serve as useful reliability models for repairable systems. For these processes, some possible ideas and methods for constructing the predicted next failure time and the prediction interval for the next failure time are presented. A method of constructing the predictors is also presented in the case when the renewal distribution of a TRP is unknown (and consequently, the likelihood function of this process is unknown). Using the prediction methods proposed, simulations are conducted to compare the predicted times and prediction intervals for a TRP with completely unknown renewal distribution with the corresponding results for the TRP with a Weibull renewal distribution and power law type trend function. The prediction methods are also applied to some real data.     

Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates

In this article, we analyze issues of pooling models for a given set of N individual units observed over T periods of time. When the parameters of the models are different but exhibit some similarity, pooling may lead to a reduction of the mean squared error of the estimates and forecasts. We investigate theoretically and through simulations the conditions that lead to improved performance of forecasts based on pooled estimates. We show that the superiority of pooled forecasts in small samples can deteriorate as the sample size grows. Empirical results for postwar international real gross domestic product growth rates of 18 Organization for Economic Cooperation and Development countries using a model put forward by Garcia-Ferrer, Highfield, Palm, and Zellner and Hong, among others illustrate these findings. When allowing for contemporaneous residual correlation across countries, pooling restrictions and criteria have to be rejected when formally tested, but generalized least squares (GLS)-based pooled forecasts are found to outperform GLS-based individual and ordinary least squares-based pooled and individual forecasts.     

Plan Colombia: illegal drugs,economic development and counterinsurgency – a political economy analysis of Colombia's failed war

This article examines the socioeconomic effects of the illegal drug industry on economic and social development in Colombia. It shows that illegal drugs have fostered violence and have had a negative effect on economic development. This article also shows that the Plan Colombia anti‐drug policy has been an ineffective strategy in terms of decreasing drug production, generating economic development and reducing violence. Since this study includes both a statistical analysis of the effects that violence and illegal drugs have on the economic growth of Colombia, along with an evaluation of the Plan Colombia policy programme, it fills the gap between existing empirical studies of the Colombian illegal drug industry and specific analyses of Plan Colombia.     

A macroeconometric disequilibrium analysis of current and future migration from Eastern Europe into West Germany

This paper attempts to evaluate the impact of current and future immigration flows on major macroeconomic variables of the West German economy. The analysis is based on a macroeconometric disequilibrium model for the West German economy. This model is extended until 1995 and used for several simulation experiments. Special attention is given to the notion that the effects of immigration are regime-specific, i.e., they depend on the type of disequilibrium prevailing on the goods and labor market.We are grateful for helpful comments made by Michael Burda, Gustav Heidbrink, Werner Smolny and three anonymous referees. The usual disclaimer applies.     

A critical review of graphics for subgroup analyses in clinical trials

Subgroup analyses are a routine part of clinical trials to investigate whether treatment effects are homogeneous across the study population. Graphical approaches play a key role in subgroup analyses to visualise effect sizes of subgroups, to aid the identification of groups that respond differentially, and to communicate the results to a wider audience. Many existing approaches do not capture the core information and are prone to lead to a misinterpretation of the subgroup effects. In this work, we critically appraise existing visualisation techniques, propose useful extensions to increase their utility and attempt to develop an effective visualisation approach. We focus on forest plots, UpSet plots, Galbraith plots, subpopulation treatment effect pattern plot, and contour plots, and comment on other approaches whose utility is more limited. We illustrate the methods using data from a prostate cancer study.     

A liberal paradox for judgment aggregation

In the emerging literature on judgment aggregation over logically connected propositions, expert rights or liberal rights have not been investigated yet. A group making collective judgments may assign individual members or subgroups with expert knowledge on, or particularly affected by, certain propositions the right to determine the collective judgment on those propositions. We identify a problem that generalizes Sen’s ‘liberal paradox’. Under plausible conditions, the assignment of rights to two or more individuals or subgroups is inconsistent with the unanimity principle, whereby unanimously accepted propositions are collectively accepted. The inconsistency can be avoided if individual judgments or rights satisfy special conditions. Earlier versions of this paper were presented at the LGS-4 Conference in Caen, June 2005, and at the World Congress of the Econometric Society in London, August 2005. We are grateful for the comments we received at both occasions as well as from anonymous referees. Franz Dietrich acknowledges financial support from the European Commission-DG Research Sixth Framework Programme (CIT-2-CT-2004-506084 / Polarization and Conflict Project). Christian List acknowledges the hospitality of the Social and Political Theory Program, RSSS, Australian National University.     

Niveaudurchagangszeiten zur charakterisierung sequentieller schätzverfahren

Let θ be a parameter of a homogenous additive stochastic process. In order to get an unbiased and efficient estimator for a function h(v) one has often to use sequential procedures. In this paper we consider processes of the socalled exponential class. We study level crossing times, which characterize certain sequential estimations. It is shown that the family of level crossing times for an increasing sequence of levels is also a process of the exponential class. The density function of the one-dimensional probability distributions of this new process is given Examples and applications conclude the paper.