Robust improper maximum likelihood: tuning, computation, and a comparison with other methods for robust Gaussian clustering

The two main topics of this paper are the introduction of the "optimally tuned improper maximum likelihood estimator" (OTRIMLE) for robust clustering based on the multivariate Gaussian model for clusters, and a comprehensive simulation study comparing the OTRIMLE to Maximum Likelihood in Gaussian mixtures with and without noise component, mixtures of t-distributions, and the TCLUST approach for trimmed clustering. The OTRIMLE uses an improper constant density for modelling outliers and noise. This can be chosen optimally so that the non-noise part of the data looks as close to a Gaussian mixture as possible. Some deviation from Gaussianity can be traded in for lowering the estimated noise proportion. Covariance matrix constraints and computation of the OTRIMLE are also treated. In the simulation study, all methods are confronted with setups in which their model assumptions are not exactly fulfilled, and in order to evaluate the experiments in a standardized way by misclassification rates, a new model-based definition of "true clusters" is introduced that deviates from the usual identification of mixture components with clusters. In the study, every method turns out to be superior for one or more setups, but the OTRIMLE achieves the most satisfactory overall performance. The methods are also applied to two real datasets, one without and one with known "true" clusters

An adequacy approach for deciding the number of clusters for OTRIMLE robust Gaussian mixture-based clustering

We introduce a new approach to deciding the number of clusters. The approach is applied to Optimally Tuned Robust Improper Maximum Likelihood Estimation (OTRIMLE; Coretto & Hennig, Journal of the American Statistical Association111, 1648-1659) of a Gaussian mixture model allowing for observations to be classified as 'noise', but it can be applied to other clustering methods as well. The quality of a clustering is assessed by a statistic Q that measures how close the within-cluster distributions are to elliptical unimodal distributions that have the only mode in the mean. This non-parametric measure allows for non-Gaussian clusters as long as they have a good quality according to Q. The simplicity of a model is assessed by a measure S that prefers a smaller number of clusters unless additional clusters can reduce the estimated noise proportion substantially. The simplest model is then chosen that is adequate for the data in the sense that its observed value of Q is not significantly larger than what is expected for data truly generated from the fitted model, as can be assessed by parametric bootstrap. The approach is compared with model-based clustering using the Bayesian information criterion (BIC) and the integrated complete likelihood (ICL) in a simulation study and on real two data sets

Rise, fragmentation, infringement and fear: emerging urban issues in Chinese clustering in Italy

China is today facing rapid economic development and the long-term implications of China’s rise for European economy, society and culture, are constantly debated but still almost unknown. Moreover, only recently a new volume edited by Kunzmann has clearly pointed out a particular field of research like the EU spatial impact of China’s convergence in the global market. The aim of the present paper is to deal with the spatial issues related to the growing Chinese communities, especially in Italy, that are part of a more general and considerable transformation process of the traditional Chinese enclaves in EU cities: from recognizable “Chinatowns” to new hybrid urban formations where housing, retail, wholesale and even commodity production often tend to match. Key-Concepts like rise, fragmentation, infringement and fear are useful in analysing some of the more controversial socio-economic dynamics of Chinese clusters especially in a traditionally manufactured-based country like Italy, where it’s recognizable a unique paradox of a “double competition” from outside and from inside. This statement poses a serious threat to local economic systems in terms of sustainability and social cohesion, making it necessary to rethink the role and the nature of public action in facing new forms of marginality at urban and regional level

Spatial interaction modeling of interregional commodity flows

Understanding the determinants of interregional commodity flows is critical for both transportation infrastructure planning (highways, railroad tracks, river/port facilities) and regional development policies (location of activities, reducing regional disparities). Unfortunately, limited data availability has, in the past, hindered empirical research in this area. Drawing from both the spatial price equilibrium theoretical framework and the empirical literature on spatial interaction modeling and international trade, this paper expands past spatial interaction models of commodity flows by incorporating new variables into the model, using a flexible Box-Cox functional form, and applying the analysis to all manufacturing commodities. The recently released 1993 U.S. Commodity Flows Survey provides the empirical basis for estimating state-to-state flow models for 16 commodity groups over the 48 continental U.S. states. Based on input-output considerations and in order to differentiate intermediate from final commodity demands, the new variables include more detailed descriptions of the economies of the origin and destination states, such as employment and value added for the commodity sector at the origin state, wholesale employment at both ends, manufacturing employment at the destination state, and population and per-capita income at both ends. In addition, the average establishment size for the commodity at the origin is intended to measure scale or diversification effects. The competitive or agglomerative effects of the economic spatial structure are captured with competing destination and intervening opportunities variables. In addition to the average hauling distance between states, the model includes dummy variables measuring whether (1) having a common physical border, and (2) the origin or destination states being custom districts, have an effect on flows. Overall, the results show that the selected variables and functional form are very successful in explaining flow variations. The optimized Box-Cox specification proves to be superior to the log-log one in all cases. The results include the following findings: (1) the distance effect is negative and highly significant, with bulkier products hauled over shorter distances; (2) the adjacency effect is significant, with neighboring states trading more with one another, even after accounting for distance; (3) the impact of the spatial structure is of the competitive type in most cases; (4) the effects of imports and exports are significant for specific commodities; (5) wholesale activities at both origins and destinations are important facilitators of commodity flows; (6) except in one case (furniture), flows increase with product diversification; and (7) the role of intermediate and final demands for the commodities are clearly reflected by the selected employment, population and per-capita income variables. Various areas for further research are outlined.

Measuring the efficiency of regional innovation systems: an empirical assessment

We measure the efficiency of regional innovation systems (RIS) in Germany by means of a knowledge production function. This function relates private sector Research and Development (R&D) in a region to the number of inventions that have been registered by residents of that region. Two approaches are followed. First, it is assumed that differences in the productivity of private sector R&D between regions affect the slope of the KPF, which represents the marginal productivity of R&D input. The second approach assesses regional differences within the framework of a stochastic frontier knowledge production function. This approach mainly reveals differences with regard to the intercept of the knowledge production function and, therefore, with regard to the average productivity. We compare the results of both approaches and discuss a number of critical issues such as the properties of the distribution of efficiencies, the appropriate size of RIS, and how to deal with the issue of spatial autocorrelation. --Knowledge,innovation,spillovers,patents,regional analysis

External Eff ects of Education: Human Capital Spillovers in Regions and Firms

Using a matched employer-employee panel dataset for Germany, we analyze the external eff ects of education on individual wages. Following the basic framework of Moretti (2004), we allow spillover eff ects to occur both within a specifi c fi rm and a specifi c region rather than analyzing spillover eff ects only on a regional level. Controlling for individual- and fi rm-specifi c fi xed eff ects and using an instrumental variable strategy, our results confi rm the existence of positive but small external eff ects of human capital. Positive spillover eff ects within fi rms occur only for the group of high-skilled workers.External eff ects; human capital; employer-employee matched data

Low-Tech Industries and the Knowledge Economy: State of the Art and Research Challenges

This paper addresses a central problem for economic analysis and public policy in Europe. Should Europe focus on socalled high-technology or science-based industries in attempting to solve growth and employment problems? Or should it look to the growth prospects within the industries on which the European economy is actually based: low-technology and medium-technology industries (which we call LMT industries ) in manufacturing and services? These questions are the focus of a European Commission research project called PILOT Policy and Innovation in Low-Tech. This paper is a first output from the project it addresses key issues in understanding LMT industries, mainly in terms of knowledge intensity and use. There are many who argue that high-technology industries are the bearers of the new knowledge economy. They argue that Europe should focus on knowledge intensive activities in such frontier areas as ICT, biotechnology and professional services. A related claim is that mature, traditional or LMT industries are likely to move to less developed countries. We claim that these perspectives are seriously mistaken. Taken together, LMT activities account for somewhere in the region of 97 % of all economic activity in Europe. All European economies are trade-specialized in LMT products. All LMT industries are innovative they generate significant proportions of their sales from new and technological changed products. Many LMT industries and products are surviving and growing on the basis of technological upgrading, high-grade design skills and the intensive application of knowledge to innovation. They have unique forms of industrial organisation and knowledge creation, complex links to science and technology knowledge infrastructures, and important regional dimensions. Here we focuses on the creation and use of knowledge in LMT industries. We claim that in the future the European economy, especially in the context of enlargement, will continue to rest on LMT activities. This implies that growth, competitiveness, cohesion and employment in Europe will depend on the performance of LMT industries. At the present time, the knowledge-creation problems faced by such sectors are neglected in policy arenas but this will become a major challenge for EU innovation, technology and research policy

Cigarette Money and Black Market Prices around the 1948 German Miracle

This paper is an empirical study of the distribution of black prices among 120 Bavarian locations at two dates, the beginning of July, 1947 and the end of June, 1948. It shows huge differences in the liquidity of those goods either when measured with the coefficient of variation or the number of locations in which those goods were traded. The main finding is that liquidity of cigarette was very high either when measured by the coefficient of variation and or the number of counties that traded them. This made them special, even when compared with a pure fiat object such as the US dollar. Consistently with the insights of the modern theory of money, the high liquidity of cigarettes is indicative of its use as money.

Low-tech industries and the knowledge economy: state of the art and research challenges

Mitte der 1980er Jahre führte die OECD zur ökonomischen Klassifikation das Konzept der technologisch hoch-, mittel- und niedrigintensiven Branchen ein. Diese Taxonomie dient der Einschätzung von Industrien hinsichtlich ihrer Forschungs- und Entwicklungsintensität. Das Schema hat sich in der Geschäftswelt, in politischen Diskussionen und in den Wirtschaftswissenschaften etabliert. In ihrer Untersuchung gehen die Autoren der Frage nach, ob sich Europa bei der Lösung von Wachstums- und Beschäftigungsproblemen auf die so genannten hochtechnologischen bzw. wissenschaftsbasierten Industrien konzentrieren soll. Oder ist eine Betrachtung der Wachstumsaussichten in den mittleren und technologisch unbedeutenderen Industrien im verarbeitenden Gewerbe und den Dienstleistungen sinnvoller, auf denen die europäische Wirtschaft mit einem Anteil von 97 Prozent derzeit basiert? Die Autoren zeigen, dass die Zukunft der europäischen Wirtschaft, insbesondere im Kontext der EU-Erweiterung, weiterhin in den Aktivitäten der technologisch mittel- und niedrigintensiven Branchen liegt. Das impliziert, dass Wachstum, Wettbewerb, Kohäsion und Beschäftigung in Europa von den Leistungen dieser Industriesektoren abhängen wird. Somit geraten Innovation, Technologie und Forschungspolitik vor dem Hintergrund aktueller Probleme bei der Wissensgenerierung für diese Branchen zu den vorrangigsten Herausforderungen in der EU. (ICGÜbers)"In the mid-1980s, the OECD invented an economic classification that has had a spectacular career - the concept of high-technology, medium-technology and low-technology industries. This taxonomy was based primarily on the R&D intensity of industries, meaning the ratio of R&D expenditure to output. Industries with an R&D/ Turnover ratio of more than four percent were classified as high-tech. Those between one and four percent were medium-tech, and those less than one percent were low-tech. This schema has become widely used in business, in policy discussions and in economic analysis. It links with other classifications that seek to differentiate 'science-based' or 'knowledge intensive' industries from more prosaic activities. This paper addresses a central problem for economic analysis and public policy in Europe. Should Europe focus on so-called high-technology or science-based industries in attempting to solve growth and employment problems? Or should it look to the growth prospects within the industries on which the European economy is actually based: low-technology and medium-technology industries (which we call 'LMT industries') in manufacturing and services? These questions are the focus of a European Commission research project called PILOT - 'Policy and Innovation in Low-Tech' ( http://www.pilot-project.org ). This paper is a first output from the project - it addresses key issues in understanding LMT industries, mainly in terms of knowledge intensity and use. There are many who argue that high-technology industries are the bearers of the new knowledge economy. They argue that Europe should focus on knowledge intensive activities in such frontier areas as ICT, biotechnology and professional services. A related claim is that mature, traditional or LMT industries are likely to move to less developed countries. We claim that these perspectives are seriously mistaken. Taken together, LMT activities account for somewhere in the region of 97% of all economic activity in Europe. All European economies are trade-specialized in LMT products. All LMT industries are innovative - they generate significant proportions of their sales from new and technological changed products. Many LMT industries and products are surviving and growing on the basis of technological upgrading, high-grade design skills and the intensive application of knowledge to innovation. They have unique forms of industrial organisation and knowledge creation, complex links to science and technology knowledge infrastructures, and important regional dimensions. Here we focuses on the creation and use of knowledge in LMT industries. We claim that in the future the European economy, especially in the context of enlargement, will continue to rest on LMT activities. This implies that growth, competitiveness, cohesion and employment in Europe will depend on the performance of LMT industries. At the present time, the knowledge-creation problems faced by such sectors are neglected in policy arenas - but this will become a major challenge for EU innovation, technology and research policy." (author's abstract