Where Have All the Parties Gone? Fraenkel and Grofman on the Alternative Vote - Yet Again

The alternative vote (AV) is a preferential electoral system that tends to reward political moderation and compromise. Fraenkel and Grofman have repeatedly attempted to show that AV is not conducive to inter-ethnic moderation in severely divided societies. In this response to their latest attempt,the author points out that neither political party coordination of the vote nor strategic voting plays any part in their analysis. In contrast, he explains how moderate parties of one ethnic group are able to induce their supporters to cast ballots for moderate parties supported by voters of another ethnic group. Prof. Horowitz also explains why the incentives for parties to arrange interethnic vote transfers are much greater under AV than they are under systems such as single transferable vote, which is in use in Northern Ireland, and shows that Fraenkel and Grofman\u27s interpretations of AV\u27s operation in Australia, Fiji, Sri Lanka, and Papua-New Guinea are contrary to the evidence

A Federal Constituency for Belgium: Right Idea, Inadequate Method

The survival of the Belgian state is an important matter—and not just to Belgium. If, in the physical and administrative heart of Europe, groups that have lived together peacefully for nearly two centuries decide that they must part, what does that say about the prospects for more fragile, more recently constructed democracies? Partition and secession are generally bad answers to serious ethnic conflict, answers that usually have an array of negative consequences (Horowitz 2003). For this among other reasons, the proposal of the Pavia Group is to be commended. It aims to break the deadlock in Belgian politics and provide politicians with incentives to speak for the country as a whole, rather than merely for members of their own group. Furthermore, it does this by a method intended to affect politicians: attempting to change the mix of votes on which they rely for their election. This is a very good first step

Non-Asymptotic Inference in Instrumental Variables Estimation

This paper presents a simple method for carrying out inference in a wide variety of possibly nonlinear IV models under weak assumptions. The method is non-asymptotic in the sense that it provides a finite sample bound on the difference between the true and nominal probabilities of rejecting a correct null hypothesis. The method is a non-Studentized version of the Anderson-Rubin test but is motivated and analyzed differently. In contrast to the conventional Anderson-Rubin test, the method proposed here does not require restrictive distributional assumptions, linearity of the estimated model, or simultaneous equations. Nor does it require knowledge of whether the instruments are strong or weak. It does not require testing or estimating the strength of the instruments. The method can be applied to quantile IV models that may be nonlinear and can be used to test a parametric IV model against a nonparametric alternative. The results presented here hold in finite samples, regardless of the strength of the instruments.Comment: 33 pages, 5 table

Foreword: The Deprivation of Labor Relations Law

This paper discusses the development of an energy systems model for Swedenconsidering electricity, heat and direct fossil fuel consumption in the residential,industrial and transport sectors as well as the energy interaction with the other Nordiccountries and its impact on the Swedish energy system. The model is developed in theOpen source energy modelling system (OSeMOSYS) (Mark Howells 2011) andshowcases potential energy investment options for Sweden in the next four decades(2010-2050). It considers different scenarios and provides a technology neutralassessment of how Sweden can invest in energy infrastructure in the most judiciousway. The paper also describes the new user interface developed called ANSWEROSeMOSYS.The paper further discusses the results of the different scenarios. Thebusiness as usual scenario shows an inclination towards investments in nuclear power.Further scenarios consider the gradual phasing out of the use of oil in CHP plants andnuclear power as well as new energy policies and tax reforms. The paper discusses theseresults in detail and demonstrates how Sweden could improve its energy infrastructureconsidering different policy implications and constraints put up by the availability andfeasibility of different resources. Finally, the prospect of wider stakeholder engagementbased on this model is discussed. Building on the open-source nature of the model,inputs and modifications from research institutes, energy modelling experts,government bodies, as well as the wider public will be incorporated into the model. Thesource code and modelling data will be made publicly available

Constitution-Making: A Process Filled with Constraint

Constitutions are generally made by people with no previous experience in constitution making. The assistance they receive from outsiders is often less useful than it may appear. The most pertinent foreign experience may reside in distant countries, whose lessons are unknown or inaccessible. Moreover, although constitutions are intended to endure, they are often products of the particular crisis that forced their creation. Drafters are usually heavily affected by a desire to avoid repeating unpleasant historical experiences or to emulate what seem to be successful constitutional models. Theirs is a heavily constrained environment, made even more so by distrust and dissensus if the constitution follows a protracted period of internal conflict. Given all these conditions, drafting a constitution that is apt for the problems faced by the drafters is difficult, and prospects are not enhanced by advice that drafters follow a uniform constitutional process that emphasizes openness and public participation above all other values

Semiparametric models

Much empirical research is concerned with estimating conditional mean, median, or hazard functions. For example, labor economists are interested in estimating the mean wages of employed individuals conditional on characteristics such as years of work experience and education. The most frequently used estimation methods assume that the function of interest is known up to a set of constant parameters that can be estimated from data. Models in which the only unknown quantities are a finite set of constant parameters are called parametric. The use of a parametric model greatly simplifies estimation, statistical inference, and interpretation of the estimation results but is rarely justified by theoretical or other a priori considerations. Estimation and inference based on convenient but incorrect assumptions about the form of the conditional mean function can be highly misleading. --

Nonparametric Estimation of an Additive Model With a Link Function

This paper describes an estimator of the additive components of a nonparametric additive model with a known link function. When the additive components are twice continuously differentiable, the estimator is asymptotically normally distributed with a rate of convergence in probability of n^{-2/5}. This is true regardless of the (finite) dimension of the explanatory variable. Thus, in contrast to the existing asymptotically normal estimator, the new estimator has no curse of dimensionality. Moreover, the estimator has an oracle property. The asymptotic distribution of each additive component is the same as it would be if the other components were known with certainty.Comment: Published at http://dx.doi.org/10.1214/009053604000000814 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Nonparametric methods for inference in the presence of instrumental variables

We suggest two nonparametric approaches, based on kernel methods and orthogonal series to estimating regression functions in the presence of instrumental variables. For the first time in this class of problems, we derive optimal convergence rates, and show that they are attained by particular estimators. In the presence of instrumental variables the relation that identifies the regression function also defines an ill-posed inverse problem, the ``difficulty'' of which depends on eigenvalues of a certain integral operator which is determined by the joint density of endogenous and instrumental variables. We delineate the role played by problem difficulty in determining both the optimal convergence rate and the appropriate choice of smoothing parameter.Comment: Published at http://dx.doi.org/10.1214/009053605000000714 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org