Regional Science Inquiry

Argentino Pessoa

CEF.UP^*, Faculdade de Economia, Universidade do Porto

Rua Dr. Roberto Frias

4200-464 Porto, Portugal

Email: apessoa@fep.up.pt

Abstract

This paper reviews the most important theoretical foundations of the concept of spatial competitiveness. To that effect it deals with three levels of competitiveness: the country, the region and the tourism destination. It draws attention to the main aspects that such concepts of competitiveness must include, and it links the regional competitiveness with the related concept of cluster. Therefore, section 2 reviews the key aspects of competitiveness at the first level, highlighting the role of the main forces that act at the national level. Section 3 extends the concept to the regional level, highlighting the critical aspects that must be considered when policy tries to increase the competitiveness of a particular region. Section 4 analyses the possibilities of extending the competitiveness concept to tourism destinations. Next, the paper analyses the literature on policy advice and discusses the inconsistency between the theory and the policy designed to promote regional competitiveness. Finally, the paper presents some concluding remarks on regional policy applied to depressed regions.

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* CEF.UP – Centre for Economics and Finance at the University of Porto – is funded by the Fundação para a Ciência e Tecnologia (FCT), Portugal.

Funda YIRMIBESOGLU

Istanbul Technical University, Faculty of Architecture

funday@itu.edu.tr

Nilgun ERGUN

Istanbul Technical University, Faculty of Architecture

ergunn@itu.edu.tr

Abstract

Beyoglu, which is one of two most important historical centers in the 17 million Istanbul, and where a gentrification process is being implemented since the 1980’s. This research is based on the differences in physical, demographical and economical characteristics of Istanbul’s districts, which show a rise in ratios of crime, especially in the city center such as the Beyoglu and Eminonu districts. In the Beyoglu central district which is economically better developed and with mixed land usage, differentiation in day/night population will be analyzed in order to determine how this could affect increase in crime.

The crime survey is conducted in the Beyoglu district between 2006 and 2008. The questionnaire results provide an insight into the mapping of crime in Beyoglu streets. The purpose of the study with this questionnaire is also to analyze fear from crime in the Beyoglu streets. At the end of the research, crime prevention strategies are going to be improved and new suggestions will be presented for the streets where crime rates are high.
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Dr. Hiroshi SAKAMOTO

Research Associate Professor, The International Centre for the Study of East Asian Development (ICSEAD)

e-mail: sakamoto@icsead.or.jp

Abstract:

This study develops a simple forecasting model using Japanese prefectural data. The Markov chain, known as a stochastic model, corresponds to a first-order vector auto-regressive (VAR) model. If the transition probability matrix can be appropriately estimated, a forecasting model using the Markov chain can be constructed. This study introduces a methodology for estimating the transition probability matrix of the Markov chain using least-squares optimization. The model is used first to analyze economy-wide changes encompassing all Japanese prefectures up to 2020. Second, a shock emanating from one prefecture is inserted into the transition probability matrix to investigate its influence on the other prefectures. Finally, a Monte Carlo experiment is conducted to refine the model’s predicted outcomes. Although this study’s model is simple, we provide more sophisticated forecasting information for prefectural economies in Japan through the complicated extension.

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