Sofía Jiménez (p), Rosa Duarte, Julio Sánchez, Inmaculada Villanua

During the last two decades globalization has been one of the most important processes in the worldwide economy, standing out during the 2000s. This has made country’s trade profiles to be in the forefront of economic literature as important driver of economic growth.
The effect of export variety on economic growth has been a recurrent topic in recent literature. Some papers have found a positive and linear relationship between exports diversity and GDP per capita (Saviotti et al (2008), Lei et al (2014), Freire (2017)). Other authors such as Imbs et al (2003) or Cadot et al (2011) claim that this relation is not lineal, achieving a U-shaped pattern. That means that exports diversity would be beneficial for those countries with low income levels but specialization would be prefer when a certain stage of development is already achieved. One objective of this study is to get more insight on this topic from a multisectorial perspective.
Besides, nowadays, global value chains have been increasingly studied in economic literature, showing product fragmentation and international trade as sources of income growth. In this context, few papers have focused on the factors that make some countries be more successful than others in their position in global value chains(a good example would be the case of China and South African countries (Kaplinsky et al. (2002)), and at the best of our knowledge, no other papers have analyzed how the participation in global value chains can affected by exports diversity and to what extent can be identified regional and/or patterns in this relationship.
Our paper aims to address these questions within a multiregional input-output framework, using as a main empirical database WIOD, 2016 release (Timmer et al (2015)). We will use two measures of diversity; the well-known Herfindahl index and the measure proposed by Hausman et al (2011) based on Revealed Comparative Advantage, applied to input-output model. We will run panel data regressions to study the relation between exports diversity and, both economic growth and participation in global value chains, distinguishing from different levels of income. Our preliminary results seem to support the existence of a non-lineal relationship between VA and exports diversity as well as between it and participation in global value chains, suggesting that countries’ development is a variable to take into account when to trade policies refers.

Sophia Khalimova (p)

One of the popular instruments in assessing regional innovation development is rating of the regions. It is widely used by researchers as well as policymakers to compare regions. Our goal is to determine how objective and impartial is building ratings as a tool for assessing innovation development. There is no denying that the choice of indicators used for building influences the results of the ranking procedure. However, there is one more element in rating construction which is seldom discussed. It is specific weights of the indicators in the aggregate index. The question here is how to assign the specific weights for the results to reflect the actual innovative development. Our hypothesis is that the choice of the specific weights influences the obtained rating of regions.
Being a complex form of economic activity, innovation activity includes various elements. In our analysis innovation activity of Russian regions is considered in two aspects, i.e., the creation of innovations and the use of innovations. We construct two indices of innovative development. We analyze innovation systems of Russian regions in 1995-2015. We use official governmental statistical data, which offers a broad set of indicators describing the state of different aspects of scientific and innovation activity. For each of the aspects of innovation activity we select three indicators characterizing the state of various elements of innovation system and main input-output indicators of innovation process.
To test the hypothesis put forward above we analyze the choices of the most innovative region both in the creation of innovations and in the use of innovations when randomly assigning different specific weights. It was shown that changes of the specific weights have influence on the rating of innovative development. It was obtained that only 8 regions were on the top of rating of the creation of innovations, while in the use of innovations 15 regions could be leaders, and only two regions are in both lists. Leadership in the use of innovations is unstable compared to the creation of innovations. At the same time at a certain moment of time possible leadership of a particular region in the use of innovations is stronger than in the creation of innovations. We also examine characteristics of the regional innovative systems in the possible leading regions to find out what makes them successful.

Mitsuhiko Kataoka (p)

The local public services contributes to the social welfare improvement and reduction in the income inequalities. For nearly two decades of decentralization, Indonesia has been experiencing an extensive devolution of administrative and fiscal powers to local governments. In association with the recent decentralization process, the demands for the widespread access and cost effective public services have risen. Their competitive pressure became more intense.
This study examines the spatial distribution in public service deliveries through the household access to safe drinking water and sanitation at the district level in Indonesia. Using data envelopment analysis, we then measure the relative input-output efficiency in the public service for each district. Finally, we identify the determinant factor to inter-district gaps in input-output efficiency, by using inequality decomposition technique.
Our spatial distribution analysis revealed the more equal spatial distribution of the local public service provision than per capita income. In our efficiency analysis, Indonesia’s district government faces resource allocation inefficiency more seriously than resource utilization inefficiency. This resource allocation inefficiency is mostly caused by the excessive fiscal allocation, especially in the off-Java districts. The inter-district gaps in resource allocation inefficiency are much larger than those in resource utilization inefficiency. Thus, the governments spent the fiscal expenditure more on the off-Java districts with the lower fiscal capacity. This contributed to balance the inter-district gaps in the public service delivery.
Consequently, the capacity building in the fiscal allocation are essential for the lagged district governments in the local public services to improve the input-output efficiency and to reduce its inter-district gaps. The trainings opportunities in the budget allocation and control for the central and local government officers could be a major solution.

Tomasz Kossowski (p), Justyna Wilk

Regional Innovation Systems is one of the leading theories of economic development over the past three decades (Asheim, Smith, Oughton 2011). This is because the performance of regional economies is strongly influenced by the strength of local clusters and the vitality and plurality of innovation (Porter 2003). Therefore, innovation development exhibits a very distinctive geography, and the central role of spatial proximity and concentration in this process (Asheim, Gertler 2009).
This paper examines RIS in the spatial context. It looks for the spatial clusters of innovation, spatial specialization roadmaps, regional leaders of high technology development, as well as regional inequalities and lag in innovation.
The methodology of the research bases on a recently developed Wilk-Kossowski S index for spatial autocorrelation in symbolic data. Looking for spatial clusters of innovation, as well as for spatial proximity, we used Eurostat panel data collected for NUTS3 level in 2003-2012. These data describe different aspects of innovation processes and, mainly, are related to patent applications to the European Patent Office and its spatial distribution. For convenience, data are presented by multinomial symbolic variables (Bock and Diday 2000), and the new index of spatial autocorrelation is run on them. As a conclusion, we identify clusters of innovative regions across Europe, regarding to different patent specialization of regions.