Martin Shields (p), David Mushinski, Sammy Zahran

Eva Coll-Martinez

During the latter years of the last millennium there was a remarkable rise and subsequent fall in the number of vaginal births after cesarean (VBAC’s) in the United States. These changes coincided with changes in guidance from the American College of Obstetricians and Gynecologists (ACOG), the nation’s leading education organization for physicians specializing in obstetrics and gynecology. This guidance was informed by emerging and evolving research regarding the safety and efficacy of VBACs.

Through the 1970, it was relatively standard practice for US women to have cesareans in any delivery after a cesarean birth. Between 1980 and the mid-1990s, ACOG pronouncements regarding VBACs became increasingly less restrictive, encompassing births which previously had not been considered candidates for a VBAC (Gregory et al., 2010). However, for several reasons, ACOG updated their guidance on the appropriate recommendation for VBACs, with more stringent conditions being put in place the late-1990s. This led to a decline in the number of VBACs.

In this paper we examine the spatial components of this dynamic, focusing on the influence of “top-50 hospitals” to the common practices in a region. We hypothesize that top-50 hospitals serve as regional health innovators, with new (or changing) practices more likely to be adopted sooner in regions that have such a hospital or are located near one.

It is important to recognize that ACOG recommendations are not laws. Differences in diffusion of knowledge between close and remote places can come about for a variety of reasons, including social and professional networks, and competitive market pressures. In our empirical work we investigate whether the presence of a Top 50 hospital affected physician responses to the evolving evidence regarding VBACs for each year over the 1990-2002 period, using a Difference-in-Differences (DD) specification.

Davide Rognini (p), Patrizio Lecca, Jorge Díaz-Lanchas

martin shields

Input-output multipliers study the interdependencies between sectors, countries, and regions. The key to interpreting I-O multipliers is understanding that they represent the proportion by which a shock in a certain input or output component of the supply or demand triggers changes in the total output of a region. Traditionally, academia focused on nominal I-O multipliers. However, recent decades have witnessed a shift towards the adoption of physical or constant I-O tables for a better understanding of structural and technological change and to avoid price-biased results. Multiple applications of constant price I-O exist; however, the commonly accepted technique to obtain constant tables is the double deflation approach. While academia acknowledges the flaws of double deflation and already provides valid alternatives, all substitutes are grounded on what we consider inaccurate theoretical premises: the notion of balanced I-O tables. We believe that any method based on this assumption does not appropriately meet the requisites of constant impact analysis as it would challenge the definition of structural change, according to which a constant price system of accounts is unbalanced by nature. This disequilibrium is the source of productivity gains.
The present paper addresses the issue of constant impact analysis by proposing the single deflation method in which productivity gains (total factor productivity surplus, TFPS) play a fundamental role in determining the effect of any shock in the economy. In this sense, we apply single and double deflation to the Spanish 2016 I-O tables for 2010-2016. We then analyze variations between our proposed alternative and the standard method, observing that the differences between approaches appear quite significant depending on the sector. These results refute previous literature that tends to consider the differences between nominal and constant applications negligible. Moreover, we suggest the use of a new I-O multiplier, the TFPS multiplier, that will compute the effect of a shock in demand in the distribution of total factor productivity among sectors, countries, and regions. Finally, we provide a reinterpretation and extension of the standard TFPS identification methodology, expanding and detailing its study from 9 to 64 economic sectors.

Martin Mariš (p)

Davide Rognini

The Programme for International Student Assessment (PISA) is a set of standardised tests administered by the Organisation for Economic Co-operation and Development (OECD) to evaluate the academic performance of 15-year-old students in various countries worldwide. The test is performed every three-year cycle and primarily focuses on student excellence in reading, mathematics, and science.
Today, two such studies, PISA and TIMSS (Trends in International Mathematics and Science Study), dominate the field. These two projects, however, differ in several important ways. Unlike TIMSS, which is descriptive and analytical, PISA is exciplitly and intentionally normative. Both studies measure trends in test scores over time (Sjøberg & Jenkins, 2022). Overall, PISA has been a remarkable phenomenon. Moreover, the PISA was not merely an educational event. It involved the public rehearsal of reasons for failure or success; in some cases, public, political and academic explanations about why 'failure' was not that and why 'success' was not that either (Pereyra et al., 2011).
The paper aims to critically assess the PISA results of the involved countries (OECD member states) at the spatial-temporal level. The sample in the study incorporates the OECD group, which currently contains 38 member states, mainly developed countries (i.e., high-income economies with a high rank of HDI) analysed in the eight periods over 2000-2022. The paper's structure is organised as follows:
1. First, the theoretical part of the paper covers the fundaments of the PISA testing, its main achievements and the implications of PISA results within the framework of international literature
2. Second, the basic inference of the statistical sample is provided
3. Methodological framework and research methods are outlined.
4. Research results are presented, especially the model fit and subsequent statistics.
5. Discussion and conclusions of the study are provided.
The basic data format for statistical analysis involves longitudinal (short panel) data on two levels with occasions nested in subjects, in which subjects become clusters. The data panel is submitted to various statistical analyses, including the variance-components model, probability distribution and agglomerated hierarchical clustering. The results' variability is expected to lay the ground for spatial and temporal conditioning factors linked to the studied countries' economic growth and competitiveness.
The paper provides a comprehensive structure covering various aspects of the analysis of PISA results. The paper aims to highlight potential differences among the countries in spatial-temporal dimensions with a profound impact on gaining their competitive edge in the global economy architecture.

Peter Kovacs, Gabor Bodnar (p), Imre Lengyel

Martin Mariš

The divide between the eastern and western parts of the European Union has been widely discussed. However, significant territorial differences are undoubtedly present even within the narrower eastern region of the EU. This study focuses on the competitiveness of regions in Central and Eastern Europe (CEE). The analysis relies on the pyramid model, the theoretical background of which provides the basis for investigating the factors affecting the competitiveness of the 51 NUTS 2 regions across six CEE countries. Partial least squares structural equation modelling (PLS-SEM) is applied to examine the relationships and effect mechanisms between the model’s factors (more specifically, between the latent variables representing the factors). We have adapted our general model to the so-called overperforming and underperforming regions described by Iammarino et al. (2019), exploring the connections of their competitiveness factors in this context. Research results reveal that the effect mechanisms observed between the above-mentioned regions are completely different. Various factors can be considered as either important or less decisive in terms of competitiveness development, which could have implications for regional policy moving forward.

Eva Coll-Martinez (p), Duygu Buyukyazici

Gabor Bodnar

The present study analyses how the agglomeration of creative industries (CIs) affects the economic complexity of regions. In the field of economic geography, the capacity of cities and regions to attract and retain talents and spread creativity has been considered one of the most determining variables in regional branching and urban competitiveness strategies. Recent studies highlight the strong interindustry linkages between creative and non-creative industries that enhance the positive effects of the former over the latter.
Despite this evidence, several authors agree that more efforts should be conducted to understand and identify the complexity and the cross-fertilisation of different creative jobs working in other industries than the CIs as they may stimulate the complexity of regions, ultimately enhancing regional development and sustainable growth.
Based on this motivation, if a region has a relatively higher share of creative industries in its industry space, then that region is likely to produce goods and services that require creative and sophisticated knowledge which are the crucial sources of regional comparative advantage. Given that two components of economic complexity are ubiquity and diversity of knowledge, there could be a close relationship between the existence of creative industries and economic complexity in a spatial context.
Descriptive analyses explore the position of creative industries in the industry space by employing network tools. In addition, the regional clustering of creative industries with Revealed Comparative Advantage (RCAs) and their relation with regional economic complexity measures are analysed.
We consider several economic complexity measures such as co-location-based economic complexity, skill complexity, and knowledge complexity based on patents.
Results in this paper provide a framework to better understand the actual role of creative industries favouring the complexity and, thus, the economic diversification and growth potential of regions.