For political and economic theory in general, libertarianism in particular, property rights are a pillar of central importance. One might describe the schools of political and economic thought solely by their approach to property rights, for example libertarianism as expansive and communism as constrained, with a fair degree of accuracy on the system as a whole.
Despite centuries of property rights philosophy, a fundamental weakness persists that can be most easily seen from a natural science perspective. Property classifications, such as between one's physical body, personal property, and other types of so-called private property, underlie much of the property rights theory, yet these classes are more of a result of technological limitations than philosophical or real economic distinctions.
We demonstrate through a lens of molecular and developmental biology how distinctions between types of property are misguided or illusory. Using the developing human embryo as the most basic example of property acquisition, we show that all subsequent examples of greater property acquisition and its use are fundamentally the same. The point is further developed with other biological examples.
Foundational concepts are of primary importance as their mistake persists through even the most elegant deductions. In order to defend itself from the political and economic attacks, the property rights ethic must be consistent and logical. For this, any artificial or contradictory concepts must be shed.
not the case here, at least as long as descriptive accuracy is an issue. For the Austrians, driven by their desire to uncover real-world causal relationships, never even tried to express any of their theories and models in the purely formal terms. All
In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine the possibilities of applying the ANOVA kernel function and take a detailed look at data preparation tasks recommended in using the SVM method (handling of outliers). The results of the models assembled suggest that a significant improvement of classification accuracy can be achieved on the database of the first Hungarian bankruptcy model when using the SVM method as opposed to neural networks.
The article attempts to answer the question whether or not the latest bankruptcy prediction techniques are more reliable than traditional mathematical-statistical ones in Hungary. Simulation experiments carried out on the database of the first Hungarian bankruptcy prediction model clearly prove that bankruptcy models built using artificial neural networks have higher classification accuracy than models created in the 1990s based on discriminant analysis and logistic regression analysis. The article presents the main results, analyses the reasons for the differences and presents constructive proposals concerning the further development of Hungarian bankruptcy prediction.
This paper analyses the impact of the introduction of a proposed mandatory earnings-related fully-funded pension scheme, named as the second pillar, on the accumulation of pension-funds assets and possibly on the capital market development in Slovenia. First, the dynamic simulation model is developed to estimate the accumulated pension-funds assets as a percentage of GDP in each future time period under the assumption of certainty. It is followed by the assumptions and estimates of the data used for independent variables and the results obtained by implementing the model for the period of 25 years. Relaxing the assumption of certainty, the paper proceeds with estimations of accuracy of the results with three methods. It is concluded, that the estimated level of accumulated pension-funds assets in GDP 25 years after the introduction of the reform will be approximately 40% and comparable to the level in countries with developed capital markets. Also, the accuracy of the estimate is surprisingly good. It is therefore expected that besides other effects, the introduction of this pension scheme would have an important impact on the development of the Slovenian capital market.
Authors:Milena Pavlova, Jelena Arsenijevic, Wim Groot, and Godefridus Merode
Questions concerning the use of evidence in policy making increasingly attract the interest of both policymakers and researchers. It is broadly recognized that the development of integrated policy frameworks can be facilitated by the use of quantitative analytical methods, such as system modeling, computer simulation, trend analysis, and scenario analysis. Although policy projections based on these methods cannot provide direct solutions to policy problems, they can help to minimize the undesirable effects of a policy choice. This paper presents the concept design of a policy projection tool that estimates the macro-level effects of patient charges. In particular, the paper explores the usefulness of system dynamics modeling for the development of the projection tool. The overall objective of the policy projection tool is to generate evidence relevant for the analysis of patient payment policies. Based on the concept projection tool, a simplified consumption-revenue module is developed for the estimation of the annual health care consumption and the revenue from patient payments during one year. The module is applied to data from six Central and Eastern European countries to test its accuracy. The results from the module testing provide directions for further modeling steps.
Wilcox, R. R. (2001): Fundamentals of Modern Statistical Methods. Substantially Improving Power and Accuracy. New York: Springer-Verlag.
Fundamentals of Modern Statistical Methods. Substantially Improving Power