Charalampos Bakagiannis (p)

Ioanna Tziolas

Since their emergence to the geopolitical and economic spotlight in the last decades, Rare Earth Elements (REEs) lately consist a critical fragment of the ongoing trade war between China and the United States (U.S.), with the European Union (E.U.) entering the trading turbulence as a latecomer. The European Union heavily relies on Chinese raw materials that are essential for the “green transition” – more specifically the European clean energy sector showcases 98% dependence on Chinese rare earths. The leadership of the 27-member bloc has crafted ambitious plans, like the European Green Deal, encompassing large scale investments and commitments. At the same time however, the Commission has been a strong advocate of "de-risking," essentially referring to diversification of raw material sourcing: in that regard, at the end of 2023 it released the Critical Raw Materials Act (CRMA), aiming to include a partial autonomy in mining, processing as well as import diversification.
Nonetheless, these commitments appear to be embodied in gradually pushing China out of global trade – especially with strict restrictions against the Asian superpower in other strategic areas, such as semiconductor technology and tariffs regarding electric vehicles the latter becomes evident. This sort of political misconduct has led Beijing grown tired of being unilateral and opened the doors to a trade war between the two parties, consequently escalating the already enlarged geopolitical turmoil.
The present research aims to scrutinize Chinese REEs-related dominance and its implications for major global economic players, namely the European Union in the context of international trade and political economy. Taking into account the E.U.’s contradictory political decision-making, the study seeks to examine Chinese REE-supply's effects on European renewable energy. More specifically, the aim is to study the effect on European energy prices, particularly on electricity by drawing data from 2000 to 2022.
Furthermore, taking into account the theory of economic patriotism as described by Clift & Woll (2012), the research seeks to address the political economy behind China’s development plans in regard to the REE’s sector and their implications for European decarbonization. Undertaking notions like industrial policy and state intervention, China’s rare earth policies reflect a strategic blend of economic, environmental, and geopolitical considerations.
To this purpose, statistical data for several international and European databases will be employed, such as the UN COMTRADE (REE trade) and the Eurostat database, where data on electricity prices and the share of renewable energy are available.

Paul Elhorst, Petros Milionis, Ioanna Tziolas (p)

Rafael González-Val

We develop computationally efficient methods to estimate large three-dimensional spatial panel data models with multiple fixed effects using quasi-maximum likelihood (QML). We consider the spatial autoregressive (SAR) model with four common fixed effects specifications, including the most extensive with origin-time, destination-time, and pair fixed effects. In addition, we consider three extensions of the SAR model, either with multiple spatial lags in the regressand, spatial lags in the regressors, or a spatial lag in the error term.

To avoid biased parameter estimates due to incidental parameter problems, the estimation approach is based on the orthogonal transformation to demean the regressand and the regressors for the fixed effects. Furthermore, in order to use computationally efficient algorithms already developed for such models at one point in time, a lemma is developed which expresses the log-likelihood function of the model based on the orthogonal transformation into its counterpart based on the standard within transformation.

The algorithms already available cover shortcuts that reduce the number of parameters to be estimated and simplify matrix operations, such as the computation of determinants, inverses, and traces in the case of large spatial weight matrices, as well as algorithms to speed up the computation of direct and indirect effects of the regressors.

We illustrate the computational feasibility of our proposed methods by estimating several variants of the gravity model of trade with spatial lags, using a data set on regional trade flows among EU NUTS-II regions from 2000 to 2010. In all cases, we find empirical evidence in favor of local spatial dependence between trade flows affecting the estimated direct and indirect effects of common trade policy variables.

Rafael González-Val (p)

Stefano Usai

The Spanish Civil War (SCW) caused a significant population decline, disproportionately affecting young men who were married or of marrying age. This study investigates whether the male scarcity resulting from the war’s exogenous shock had transitory or permanent effects on the Spanish marriage market. Using annual data from 1900 to 2011 for two spatial units—provinces and provincial capitals—we employ a range of analytical methods to explore these effects. Time series analysis and panel data unit root tests indicate that marriage rates are stationary, suggesting that, despite a major shock like the SCW, marriage rates tend to revert to their long-term mean, although structural break tests reveal significant negative shifts in the mean marriage rates during the war period in many cases. Panel data models further show that the SCW had a significant but temporary negative effect on marriage rates at both the provincial and city levels, with the impact dissipating within 5–6 years after the war. At the provincial level, which captures the total number of marriages and population in the country, a subsequent decline in marriage rates is observed two decades after the SCW. This later decline is attributed to the ‘missing generation’ caused by the war.

Stefano Usai (p), Simona Iammarino, Diego Dessì

Charalampos Bakagiannis

Under the ongoing technological paradigm shifts, critical natural resources and materials have become essential for emerging industries and innovation frontiers. Recent disruptions in global supply chains – due to geopolitical conflicts, trade wars, political instability of the (highly) concentrated deposits worldwide, etc. – have affected the availability of critical raw materials (CRMs), raising concerns about the stability of the supply, and bringing to the fore the alternative of domestic production. Recent EU initiatives, such as the Open Strategic Autonomy (OSA) intended to make the Union more competitive and autonomous by promoting innovation along the entire value chain, particularly the Critical Raw Materials Act (CRMA) represents a bold attempt to secure a stable supply of critical and strategic raw materials. However, the EU’s strategy tends to over-rely on domestic opportunities, employing an excessively top-down approach combined with industrial and regulatory provision primarily focused on attracting new investments in the industrial sector by accelerating permitting and funding procedures. This approach risks falling short in addressing key constraints, including local-level implications, limited reserves, uncertain geological data, and inadequate technological and industrial capabilities of European regions. We combined EGDI data from the European Geological Survey (EGS) and S&P Global with BvD ORBIS information to identify vulnerable strategic areas driven by social tensions, tecnical, and resource constraints and to understand howownership-driven disparities and strategic underutilization influenced by owner- and region-specific capabilities may impact the CRMA’s ability to ensure a secure supply of CRMs while promoting balanced and fair territorial development in Europe and beyond