EU REGULAR ECONOMIC REPORT 10 PART 2 Clean Tech Value Chains Using Trade Data to Guide a Complex Policy Space Zooming in on Romania The EU RER 10 Clean tech value chains: Using trade data to guide a complex policy space shows that Romania has the potential to become a significant player in the EU’s green value chains but needs to address its weaknesses to fully capitalize on the opportunities. The EU RER 101 shows that among the 4CEEs studied, Romania performs relatively well in clean tech value chains2, standing to benefit from the opportunities that the green transition may bring. Based on conservative estimates, Roma- nia currently exports almost 0.3 percent of GDP in clean tech3 (Figure 1), generally specializes in more complex segments of the clean tech chains (Figure 2), competitively exports FIGURE 1  Exports of Net-Zero Technologies products characterized by strong external demand (Figure 3), by Value Chain and exports a high number of products with high ‘onshoring BG attractiveness’ (OAS)4, particularly in solar and wind tech- nologies (Figure 4). However, Romania demonstrates lower HR overall OAS than, for example, Poland in terms of overall in- PL vestment attractiveness, principally because of its smaller RO market size, smaller and less diversified supplier networks, and infrastructure challenges. Its logistics infrastructure 0 0.1 0.2 0.3 0.4 0.5 0.6 and processes lag Poland and the EU average, presenting a Percent of GDP potential barrier to efficient and cost-effective production Electrolysers EV Batteries Heat pumps and export of clean technologies. Moreover, compared to the Solar Wind other of the 4CEEs, Romania exports proportionately more Source: WB staff calculations. 1 World Bank Group EU Regular Economic Report 10 (EU RER) focuses on 4 Central and Eastern European (4CEEs) EU mem- ber states: Poland, Romania, Bulgaria, and Croatia. 2 For the purpose of this report, the products that either produce, store or deliver low-carbon energy will be referred to as ‘clean energy technologies’ in line with the IEA, or ‘clean tech’ for short. The EU nomenclature includes ‘clean technologies’, ‘net zero technologies’, ‘green technologies’, among others. Note that in line with the emerging nomenclature, ‘technologies’ here refer to products: capital goods, consumer goods and intermediate goods, and not ‘productive’ knowledge. The clean tech value chains mapped in this report are electric vehicle (EV) battery, heat pumps, wind, solar PV, and electrolyzers. 3 In conservative estimates – please see the main report for details. 4 Please refer to EU RER 10 Part II for more details. Onshoring attractiveness is a composite index that summarizes 18 de- mand, supply, and ease of market access variables, and is generated using Principal Component Analysis (PCA). PCA reduc- es the dimensionality of the dataset by transforming a large set of variables into a smaller set still containing most of the information. We select the maximum number of components (eigenvectors or factors) with eigenvalues greater than one. Zooming in on Romania  |  Clean tech value chains. Using trade data to guide a complex policy space  2 in subcomponents rather than final products in these technologies. Simulations conducted in the EU RER 10 Part 2 suggest that Romania’s export potential might not translate into higher export vol- umes, for example compared to Bulgaria and Croatia, possibly due to a low number of products with a high OAS in the largest market (batteries) and limited export market diversification. FIGURE 2  Exports of Clean Technologies by Complexity Share of respective technology’s exports, 2022 100 80 Percent 60 40 20 0 BG HR PL RO DE BG HR PL RO DE BG HR PL RO DE BG HR PL RO DE 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 EV batteries EV other Solar Wind Extremely Low Low Medium High Extremely High Source: Green Value Chain Explorer (WB internal) and WB calculations. Note: for panels a and b, the results are shown for three out of five clean tech manufacturing exports: EV, solar PV, and wind, in line with the current functionality of the GVCE tool. b. Extremely Low=-3