“Archipelago of Enclaves” as Subnational Dynamics of Export-Driven Growth Models: A Focus on Timisoara within the FDI-Led CEE Landscape
Creators: name: Petrovici, Norbert
name: Alexe, Vlad
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 440603
subject: Economic geography
classificationCode: 380202
subject: Econometric and statistical methods
classificationCode: 440404
subject: Political economy and social change
classificationCode: 441016
subject: Urban sociology and community studies

description: "Archipelago of Enclaves” as Subnational Dynamics of Export-Driven Growth Models: A Focus on Timisoara within the FDI-Led CEE Landscape<br><b>Abstract: </b>The data supports a study that examines the integration of FDI in Timișoara, Romania, within Central and Eastern Europe's export growth models. Analyzing a network of 2,829 enterprises, we explore FDI's impact on the regional economy and domestic firms. Using logistic regression and Exponential Random Graph Models (ERGMs), we identify factors promoting FDI in tradable sectors and analyze relationship dynamics and ownership ties. Our findings highlight three primary FDI mechanisms: limited horizontal spillovers resulting in enclave formations dominated by foreign firms driving technological advancements; increasing transnational investments in high-tech startups since 2019, enhancing SME growth in an exportist context; and significant spillovers in sectors like real estate, characterized by financialization. These insights spatialize at the subnational level of FDI-led, export-driven growth models and reinterpret “transnational enclaves” from a demand-side economics perspective, re-embedding globalization’s spatial manifestations within national growth drivers.<b>Keywords:</b> multinational firms; regional economies; economic geography; technological change; networks; Eastern Europe; capitalism, varieties of; growth theory.<b>JEL Classification: </b>C21, F21, F23, O18, P16, R12<b>Categories: </b>Economic geography, Sociology, Urban Studies, Data Science<br><b>Dataset Files Description:</b>1. 'Timis_cpmpanies.xlsx': Excel dataset containing raw data of enterprises within Timișoara used in the analysis for logistic analysis.2. 'Logistic Regression.R': R script providing the analyses of company data with logistc analysis.3. 'timis_network_ergm.RData': preloaded enviroment with the network data set for the networks.4. 'ERGMs.R': R script for data analysis focusing on network dynamics within Timișoara.<b>Analytical Strategies:</b>The study employs a dual-methodological approach combining logistic regression and Exponential Random Graph Models (ERGMs). Logistic regression is used to profile FDI entities in comparison to domestic firms based on size, sectoral engagement, and technological capacity. ERGMs analyze the formation and dynamics within the network of enterprises, focusing on how FDI influences these dynamics.<b><i>Logistic Regression Analysis</i></b>The logistic regression analysis aims to identify and quantify the factors that differentiate Foreign Direct Investment (FDI) entities from domestic companies within the economic landscape of Timișoara, Romania. The dataset for this analysis includes top-performing companies in Timișoara, covering various sectors, and measures such as company size, sector engagement, and technological capacity.<b>ERGMs</b>Dataset Description: The data consists of a comprehensive network of 2,829 interconnected companies located in Timișoara. This dataset was compiled to understand the economic landscape, focusing on inter-firm relationships and ownership structures shaped by FDI. Employment figures and company turnover were extracted from the Territorial Work Inspectorate of Timiș and public balance sheets, respectively.