Robert Stehrer

This paper studies the determinants of the intentions to emigrate and conditional on migration aspirations, the destination choice in a number of Central East and Southeast European economies (CESEE). Using data from the OeNB Euro Survey, we apply a two‐stage Heckman procedure to identify the drivers of migration intentions – specifically individuals' demographic and household attributes, financial conditions, past economic experiences, and future expectations. In the second stage, conditional on the stated intention to migrate, we examine the determinants of destination choice, distinguishing between EU15, EU‐CEE, and extra‐EU countries. This micro‐level evidence indicates that economic and financial conditions (past, present, and expected) play an important role in shaping migration intentions, while non‐economic factors, including individual demographic and family attributes, as well as network ties, also exert important influence. Destination preferences, conditional on an already existing intention to migrate are not simply a mechanical extension of intention determinants. The choice of the destination region is determined mostly by marital status, educational attainment, and GDP per capita variables in the origin and destination region. This reflects the conceptualisation of migration as a two‐stage decision process, distinguishing between entry into the pool of potential migrants and destination choice within that pool. This stage‐specific perspective thus allows to differentiate determinants of intentions and destination choice of prospective mobility, that empirical results based on actual migration decisions cannot deliver.

The COVID-19 pandemic has thrown the world's economy and trade into disarray, putting international reliance in the limelight. This sparked debate on the durability and resilience of global value chains. In this paper, we construct a ‘product riskiness indicator’ for 4700 globally traded products based on components such as market concentration, clustering tendencies, network centrality of players, or international substitutability to determine which products are vulnerable to trade shocks at the global level – referred to as ‘risky’ products. In a second step, bilateral risky product imports are matched to multi-country input–output tables, allowing for an examination of the importance of globally supplied risky products by country and industry. Due to the high percentage of dangerous products in high-tech product categories, higher-tech industries are more vulnerable to supply-chain vulnerabilities. Third, we analyse the GDP impact of reshoring using a “partial global extraction method.” Assuming that risky product imports from non-EU27 nations are re-shored to EU27 countries, the EU27 GDP might rise by up to 0.5 percent. Non-EU27 countries suffer as a result of such reshoring activity. This implies that ensuring robust or at least resilient supply networks is also in the interest of the supplier countries and sectors.

We examine the drivers of labor productivity at aggregate and sectoral levels focusing on tangible and intangible ICT capital, FDI and global value chain participation. The analysis, based on a panel dataset of 18 EU countries, the US and Japan over the period 2000–2017, reveals an important role of ICT capital, especially intangible ICT capital embodied in software and databases, in driving labor productivity growth. Furthermore, backward global value chain participation is also positively associated with productivity. Contrary to expectations, we do not find evidence of a productivity-enhancing effect of foreign direct investment when controlling for phantom FDI related to special purpose entities.

Import demand elasticities are regularly used to compute trade restrictiveness indices, to transform estimated effects of trade policies into ad-valorem equivalents, or to judge on the prohibitive level of various tariff and non-tariff policy instruments. The fast rising number of negotiations of free trade agreements and the fact that non-tariff measures are at the core of these strongly motivates for an update of the import demand elasticity estimates provided by Kee, Nicita, and Olarreaga in 2008 which are based on trade data for the period 1988–2001. Following their GDP function approach, we present import demand elasticities for more than 150 countries and over 5000 products over the period 1996–2014. Countries exhibiting the highest average elasticities belong to the economically biggest countries in their respective regions, while countries with the lowest import demand elasticities are typically small island states. Import-weighted results suggest that especially countries rich in natural resources are facing an inelastic import demand, with the agri-food sector being more price-responsive than the manufacturing sector. Finally, import demand for intermediate goods seems to be more elastic than demand for products destined for final consumption.

This study sheds light on particular issues of poultry imports to the EU during the 1996–2014 period. First, we analyze the mechanisms of EU market protection through the evolution of tariffs and non-tariff measures (NTMs), both...

Instituto de Economía Pontificia Universidad Católica de Chile

Crespo-Cuaresma J., Foster N. and Stehrer R. Determinants of regional economic growth by quantile, Regional Studies. The robustness of growth determinants across European Union regions is analysed using quantile regression. Using Bayesian model averaging (BMA) on the class of quantile regression models, it is proposed that the set of relevant covariates is assessed, allowing for different effects across growth quantiles. The results indicate that the robust growth determinants differ across quantiles. The set of robust variables includes physical investment when taking country fixed-effects into account, and skill endowment and initial gross domestic product per capita when not. Even when a variable is found to be robust across quantiles, its estimated impact on growth is often found to vary across quantiles. Crespo-Cuaresma J., Foster N. et Stehrer R. Les déterminants de la croissance économique par quantile, Regional Studies. A partir d'une régression par quantile, on analyse la solidité des déterminants de la croissance à travers les régions de l'Union européenne. Employant un Bayesian Averaging Model (BMA) sur la catégorie de modèles de régression par quantile, on propose une évaluation de la covariance, compte tenu des effets différents suivant les quantiles de croissance. L'ensemble de variables solides comprend l'investissement matériel quand on tient compte des effets spécifiques à un pays, sinon la dotation en connaissance et le produit intérieur brut initial par tête. Même quand une variable s'avère solide à travers les quantiles, l'impact prévu sur la croissance varie souvent à travers les quantiles. Croissance régionale Bayesian model averaging Régression par quantiles Crespo-Cuaresma J., Foster N. und Stehrer R. Determinanten regionalen Wachstums nach Quantilen, Regional Studies. In diesem Beitrag wird die Robustheit von Wachstumsdeterminanten in EU-Regionen mittels Quantilsregressionen analysiert. Dabei wird ein Bayesian Model Averaging (BMA) für Quantilsregressionen verwendet, um die relevanten Kovariaten, die unterschiedliche Effekte in den jeweiligen Wachstumsquantilen aufweisen können, zu ermitteln. Die Resultate zeigen, dass die robusten Wachstumsdeterminanten in den jeweiligen Quantilen tatsächlich unterschiedlich sind. Unter Berücksichtigung von länderspezifischen Effekten ist insbesondere die Variable Anlageinvestitionen ein robuster Erklärungsfaktor regionalen Wachstums; ohne Berücksichtigen dieser Effekte sind Humankapitalausstattung und das Pro-Kopf-Einkommen robuste Determinanten. Auch wenn eine bestimmte Variable robust in mehreren oder allen Quantilen ist, sind die ermittelten Effekte auf das Wachstum der Regionen in den jeweiligen Quantilen oftmals unterschiedlich. Regionales Wachstum Bayesian Model Averaging Quantilsregressionen Crespo-Cuaresma J., Foster N. y Stehrer R. Determinantes del crecimiento económico regional por cuantiles, Regional Studies. Analizamos la solidez de los determinantes de crecimiento en las regiones de la Unión Europea usando una regresión cuantílica. Mediante el uso de promedios de modelo bayesiano sobre la clase de los modelos de regresión cuantílica, proponemos que se evalúe el conjunto de las covariantes correspondientes teniendo en cuenta los diferentes efectos en los cuantiles de crecimiento. Los resultados indican que los determinantes de un crecimiento sólido son diferentes entre los cuantiles. Si se tienen en cuenta los efectos fijos de cada país, la inversión física es una variable fuerte, de no ser así son variables fuertes la dotación de habilidades y el producto interno bruto per cápita inicial. Incluso cuando se halla una variable que es sólida en varios cuantiles, se observa con frecuencia que el impacto estimado en el crecimiento varía entre los cuantiles. Crecimiento regional Promedios de modelo bayesiano Regresión cuantílica