Burhan Can Karahasan (p)

Alexandre Lehoux

Impact of industrial development on local economies has been densely analyzed on the grounds that more industrial economic activity expands local growth and development. While impact of industrialization is examined from economic growth perspective impact of industrialization on labor market deprivations at different layers is relatively less analyzed. In this study, I offer a two-stage analysis to understand the instrumental role of industrial development for fostering job prospects at local and individual level. Empirical evidence is from NUTS-2 level Turkish regions and covers the 2004-2022 period. The first set of analysis questions the impact of industrial production on local unemployment patterns. After controlling for local factors that can affect unemployment and spatial externalities that can create inter-regional spillovers findings confirm that regions with more industrial production tend to have lower unemployment problem. Second set of analysis is from individual level data. We use the Household Labor Force Survey (HLFS) which is supplied at the cross-section basis for the 2004-2022 period. Since HLFS is representative at the NUTS-2 level we are able to merge the regional industrial production data with the individual level survey data. Our findings from probit type micro-econometric models reveal that after controlling for individual heterogeneity those individuals who live in NUTS-2 regions with higher industrial production have less propensity to be unemployed. This finding is robust for the whole sample period with the exception of 2008 and 2009 in which Turkish economy is heavily influenced from the side effects of the global financial crisis. Our combined findings show that influence of industrial development is not bounded at the local level as local industrial development has sizable influence on individuals’ labour market deprivations. Overall, these findings remind the necessity of policy action to foster more industrial development, not only to promote local growth but also to combat with the pervasive impact of unemployment problem.

Alexandre Lehoux (p), Alexander Lembcke , Hyejin Lee

Kenneth Castillo-Hidalgo

Among the 13 OECD countries with a GDP per capita below the OECD average in 2000, ten had narrowed the gap by 2020 (OECD, forthcoming). The pace of convergence has varied widely across regions within countries, and in some cases, regional disparities have widened. Understanding what drives these regional growth differentials is crucial to unlocking their full economic potential and fostering convergence both across and within countries.

This presentation will showcase firm-level evidence from a broader OECD project currently under development, which aims to provide insights into how policymakers can promote growth in all types of regions without compromising aggregate economic performance. The first part of the presentation will establish both the growth and productivity gap existing among regions by examining micro-level data on firms across and within a subset of OECD countries, with an emphasis on showing how major events, such as the Great Financial Crisis, have been potentially key drivers in widening the gap. More precisely, this first part will leverage both balance sheet information and firms’ characteristics to construct industry-by-region facts about their level of productivity (e.g., total factor productivity, misallocation), financial strength (e.g., leverage ratio, interest coverage ratio), and foreign direct investment (FDI).

The second part constructs similar measures but focuses on documenting start-up rates and venture capital investment using Crunchbase and Dealroom data. This section aims to provide a detailed analysis of entrepreneurial activity across regions by examining key indicators such as the rate of new business formation, start-up survival rates, and the amount and distribution of venture capital funding.

The final part builds on the findings from both exercises by correlating the constructed indicators with regional-level variables to identify the key mechanisms driving economic disparities. It explores a range of potential factors, including differences in regional infrastructure (e.g., access to universities, transport networks, and digital connectivity), institutional quality (such as governance effectiveness and regulatory frameworks), and the broader business environment. Additionally, it examines how industry composition interacts with local policies, including how sectoral specialisation, firm size distribution, and the presence of high-growth industries influence the effectiveness of regional policies. By integrating these elements, this section aims to provide a comprehensive understanding of the mechanisms that shape regional economic performance and offer insights into policies that can overcome the lagging growth faced by certain regions.

Roberta Capello, Kenneth Castillo-Hidalgo (p), Giovanni Perucca

Bart Los

Literature has provided strong evidence on the association between increasing market concentration and the emergence of ‘superstar firms’ in industries highly exposed to technological change and globalization (Autor et al., 2020; Harrison, 2024). As a consequence, firms are able to raise markups at relative advantage of the remuneration of capital over labor, with a relevant impact on functional income redistribution. Studies in this field have addressed this issue from an industrial, spatially neutral perspective, where the intensity of the effects of increasing market concentration on functional inequalities exclusively depends on the economic sectors in which firms operate.
This study aims to provide a regional approach to address this issue, accounting for the relevance of territories. The motivation for this is twofold: First, locational choices of ‘superstar firms’ are not spacially blinded, but favor localizations in which they can benefit from agglomeration economies. Second, the intensity of functional income redistributive effects in favor of capital owners is expected to be higher in regions where ‘superstar firms’ (hence, capital) are concentrated. We test this hypothesis by using data on EU companies and market concentration measures for highly disaggregated industries.
Our findings support the existence of territorial heterogeneity in the intensity of the effects of market concentration. While relative capital remuneration increases with raising market concentration, the effect is significantly higher in those regions where ‘superstar firms’ are located. Moreover, market concentration, does not only affect disparities between capital and labor owners, but also between regions with different industrial compositions. These results shed light on the relevance of the regional dimension of inequality, neglected in previous studies.

Bart Los (p), Xianjia Ye

Burhan Can Karahasan

The increased pervasiveness of global value chains has led to a change in the nature of international trade. Regions and countries do no longer just specialise in entire industries, but more so in tasks within these (Grossman and Rossi-Hansberg, 2008; Timmer et al., 2019). A region could host relatively many ‘headquarter functions’ (involving tasks related to R&D, marketing and management), while other regions could have a larger share of their workforces active in the fabrication function. Consequently, regions with comparable industry compositions might no longer be very similar in terms of the functions they perform.

This functional specialization has implications for evaluating the economic performance of regions. As is well-known from the literature on the ‘smile curve’ that characterises global value chains, fabrication activities generally capture a lower share of value added in comparison to headquarter functions (e.g., Mudambi, 2008). Hence, differences in the functional employment structure can be a determinant of the large interregional inequality in the United Kingdom (McCann, 2016; Carrascal-Incera et al., 2020), and changes therein over time. In this paper, a taxonomy of regions based on both their current functional specialisation patterns and on the changes in these over a thirty-year period will be provided. The taxonomy of regions based on changes over time is inspired by Dauth and Südekum (2016), but adds changes in the functional structure to their perspective, which exclusively focuses on industrial structure. To this end, Census data on the occupation and industry in which workers were employed are used. The analysis covers the period 1991-2021.

Questions answered are: “Which English regions specialized most in the fabrication function?”, “Which regions had industry-function patterns of employment change that were most dissimilar with such changes for England as a whole?”, and “Have employment and income growth in such regions been slower or faster than the English average?”

As stressed by Dauth and Südekum in their paper, differences in employment structure across regions have implications for policies aiming at regional development. As many regional scientists and economic geographers have argued already (see, e.g., McCann et al., 2021), place-based policies are needed, instead of one-size-fits-all plans.