Machen Parteien in der Umweltpolitik einen Unterschied?

ZusammenfassungDie Parteiendifferenztheorie nimmt an, dass sich die parteipolitische Zusammensetzung der Regierung systematisch auf die beschlossenen Policies auswirken sollte. Als eine der wichtigsten Theorien der Policyforschung ist sie auch für eine policyanalytisch geprägte Umweltpolitikforschung von zentraler Bedeutung. Allerdings wirft ihre Anwendung auf die Umweltpolitik eine Reihe von Problemen auf. Der vorliegende Beitrag stellt zunächst die Wurzeln und Grundannahmen der Parteiendifferenztheorie vor und identifiziert dann wichtige Problemfelder ihrer Anwendung auf die Umweltpolitik. Das größte Problem besteht darin, dass der Kernkonflikt der Umweltpolitik, der Konflikt zwischen Ökonomie und Ökologie, anders als Kernkonflikte in anderen Politikfeldern nicht ohne Weiteres auf der Rechts-Links-Achse abzubilden ist und sich daher im Parteiensystem nicht eindeutig niederschlägt (Cleavage-Problem). Daraus resultiert auch im Hinblick auf die empirischen Studien eine recht uneinheitliche Lage, was das Bestehen oder Nichtbestehen von systematischen Parteieneffekten in der Umweltpolitik betrifft (Empirie-Problem). Ein weiteres Problem besteht darin, dass Studien zur Parteiendifferenz in der Umweltpolitik häufig die Umweltqualität oder -performanz (und nicht politische Maßnahmen) als abhängige Variable verwenden, während deren Zusammenhang mit politischen Maßnahmen (Policies) häufig ungeklärt bleibt („Dependent Variable“-Problem). Schließlich stellt sich auch bei einer Anwendung der Parteiendifferenztheorie auf die Umweltpolitik das Problem der singulären Kausalität, das in der (oft fraglichen) Annahme besteht, dass Parteipolitik alleine Resultate erklären könne. Der Beitrag diskutiert diese Probleme und präsentiert Lösungen auf konzeptioneller, theoretischer und methodischer Ebene.

Utilization of Eight-Variable Karnaugh Maps in the Exploration of Problems of Qualitative Comparative Analysis

Qualitative Comparative Analysis (QCA) is an emergent methodology of diverse applications in many disciplines. However, its premises and techniques are continuously subject to discussion, debate, and (even) dispute. We use a regular and modular Karnaugh map to explore a prominent recently-posed eight-variable QCA problem. This problem involves a partially-defined Boolean function (PDBF), that is dominantly unspecified. Without using the algorithmic integer-programming approach, we devise a simple heuristic map procedure to discover minimal sets of supporting variables. The eight-variable problem studied herein is shown to have at least two distinct such sets, with cardinalities of 4 and 3, respectively. For these two sets, the pertinent function is still a partially-defined Boolean function (PDBF), equivalent to 210 = 1024 completely-specified Boolean functions (CSBFs) in the first case, and to four CSBFs only in the second case. We obtained formulas for the four functions of the second case, and a formula for a sample fifth function in the first case. Although only this fifth function is unate, each of the five functions studied does not have any non-essential prime implicant, and hence each of them enjoys the desirable feature of having a single IDF that is both a unique minimal sum and the complete sum. According to our scheme of first identifying a minimal set of supporting variables, we avoided the task of drawing prime-implicant loops on the initial eight-variable map, and postponed this task till the map became dramatically reduced in size. Our map techniques and results are hopefully of significant utility in future QCA applications.

No-respuesta al ítem en una encuesta de hogares en Colombia

Item nonresponse occurs when sample units do not provide information on a particular variable, problem that may affect the representativeness of the sample and the reliability of the estimates. Efforts to reduce the item nonresponse rate do not necessarily improve the quality of the information. Besides the nonresponse rate, representativeness indicators can be used to measure the quality of the collected data. This paper analyzes the wage nonresponse mechanism of a household survey in Colombia and evaluates the quality of the wage information in two different periods of time (2008:4 and 2017:4). The results show a low but increasing nonresponse rate whose behavior does not seem to be associated with the set of observables considered. This result is of value since the selection of the adequate imputation method relies on the assumptions on the missing data mechanism.

Automation of production programs by setting conditions of stabilization of the planned system

Formation of a production program is a time-consuming variable problem. To solve it, many conditions and constraints must be taken into account. Computer power allows one to quickly and accurately solve problems with many variables, unlike a person who relies on his intuition and experience. The following materials and methods were used: collection and analysis of data from construction companies of various sizes, mathematical modeling of the processes of distributing labor resources, graphic interpretation of information, computer modeling. The stages of the problem statement: description of the organizational and technological problem of distributing labor resources, mathematical formulation, modeling and algorithmization using well-known metaheuristic approaches. In the course of solving the problem, a genetic algorithm was used that allows one to quickly find solutions in equations with many variables. The following constraints were determined: deadlines, maximum and minimum number of workers at the facility, minimum number of transfer of resources, minimum involvement of a subcontractor. As a result, all the necessary mathematical models and initial data for the development of a computer program for the automated distribution of labor resources among the facilities of the production program of the construction and installation organization were obtained.

Food security policy choices: A review of the usefulness of public policy taxonomies

This paper addresses the "dependent variable"problem in food security policies, namely the difficulty in classifying food security policies that limits comparative policy studies. Policy comparisons require criteria that are general enough for broad application but sensitive to the context. A rigorous and objective basis for comparisons would allow for studying how policies, and food security policies in particular, emerge. This is important in Africa as, in the past, food security and nutrition crises have been attributed to the failure of government policies. This paper reviews the main key available public policy classifications based on their predictability, mutual-exclusivity and relevance. These include Lowi's and Wilson's typologies, the agricultural policies' classification by Norton and the FAO-FAPDA classification. The review found that available typologies do not accommodate multi-sectoral actions and are not entirely applicable to food security public policy classification. The domain shift from food policy to food security,and more recently to food systems demands that all elements in the food system to be taken into consideration in the policy process. This limits the use of policies as "dependent variables"and hence the study of how they emerge, particularly in Africa. A critique of available policy classes shows that these cannot be treated as "dependent variables". It is argued that a potential solution to the "dependent variable" problem of food security policies lies in the development of a taxonomy, simplifying their complexity with analytical shortcuts. Having reviewed Candel and Daugbjergs’ recent taxonomy, refinements are proposed to be applied in the African context. The proposed taxonomy represents an alternative to classify food security policies in Africa along four core dimensions. This classification offers prospects for researchers to study what factors drives policy-classes in one direction or the other, along the four dimensions. Although the scales and calibration of the four dimensions will need to be developed and tested, the proposed typology offers a way to treat the dimensions as “dependent variables”.

Overcoming the dependent variable problem in studying food policy

The development of a comparative food policy research agenda has been hampered by the dependent variable problem of how to delineate the policy field. Through a concise literature review, we show that the existing literature has conceptualised food policy as policy outputs, institutional orders, or discursive constructs. Focusing on the policy outputs, we define food policy as a set of policy outputs adopted to address one or more food system activities (production, processing and packaging, distribution and retailing, and consumption) with the explicit aim of affecting food system outcomes in a desired direction. The paper develops a heuristic encompassing four dimensions along which food policy outputs may differ: (i) policy scope, (ii) targeting of policy efforts, (iii) type of policy instruments applied and how these are calibrated, and (iv) integration of the various components of the policy complex. These four dimensions can be applied to characterise individual food policies and compare across countries and time. Comparing and tracking the development of food policy along these dimensions would allow for addressing follow-up questions about impacts and what explains policy change.