Abstract
The European Union (EU) is planning to become carbon neutral by mid-century. This bold objective might have far-reaching consequences for the region capacity to remain cost-competitive, at least in the short term. Until now the decarbonization policies (e.g. ETS and renewable support) meant higher energy prices paid by households and firms: boldest targets will probably, at least in the short and medium-term, further out pressure on energy prices. To explore the impact of climate policies on European firms’competitiveness, we extend the standard analysis that links input costs and competitiveness including a Unit Energy Cost (UEC) measure. We study the UEC dynamics in different countries and industries, assessing its main drivers (prices, energy intensity, sector composition). Modelling the relationship between firms’ foreign sales and the UEC in a gravity model setup, we find that an increase in UECs reduces bilateral exports; euro-area countries show the largest negative effects. Our results strengthen the case for pursuing a stronger integration of European energy markets in order to avoid that the ambitious long-term European decarbonization targets penalize the European manufacturers. It is also important to establish a global “carbon”level playing field such as a EU-level carbon border adjustment, or other form of EU low-carbon exports support. We finally suggest to use some energy cost indicator in monitoring country competitiveness, as it happens for ULC, for example adding UEC to the Countries’ MIP prepared by the European Commission.
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Notes
According to the 2017 World Energy Outlook, the European Union and Japan are the two regions with the highest electricity prices. Over time, EU electricity prices are predicted to become the highest in the world (see fig 6.26 of IEA, 2017).
The indicators used in the MIP scoreboard to measure price and cost competitiveness are the Real Effective Exchange Rate and the nominal Unit Labour Cost with the addition of the Export Market Share.
These sub-industries are Iron and Steel/Non-Ferrous Metals, Chemical and Petrochemical, Non-Metallic Minerals, Mining and Quarrying, Food and Tobacco, Textile and Leather, Paper Pulp and Print,Transport Equipment, Machinery, Wood and Wood Products, Construction, Non-specified (Industry).
The Combined Nomenclature (CN) is a tool for classifying goods, set up to meet the requirements both of the Common Customs Tariff and of the EU’s external trade statistics. The CN is also used in intra-EU trade statistics.
Prodcom codes are composed by 8 digits where the first 4 are related to the corresponding Nace rev. 2 classification. Using this code we are able to aggregate data at industry level. For more details see http://ec.europa.eu/eurostat/web/prodcom.
In the paper we follow the suggestions of the European Commission of using a real unit energy costs indicator, defined as energy costs as a fraction of a measure of production (European Commission 2014b). Since energy is considered an intermediate input we express energy costs as a share of the value of production instead of using the value added.
We define Energy Intensive sectors as those with a UEC greater than the 75th percentile of the country distribution during the whole sample period. Without granular information on prices at the industry level this classification might be biased because we are not considering partial or total tax exemptions and other form of price subsidies.
From 2004 EU includes Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia and Slovenia; from 2007 it also includes Bulgaria and Romania.
For an evaluation of RES deployment in Italy see Faiella et al. (2016).
Uni-directional bilateral flows represent the country export: the previous literature used an average between import and export but this might lead to biased estimators.
There is an intense debate regarding the inclusion of fixed effects in panel data analyses: according to Egger and Pfaffermayr (2003), models including bilateral effects dominate those with main effects and a selection of observable time-invariant variables; however, the inclusion of fixed bilateral effects makes it impossible to directly estimate the coefficients of time-invariant observables (like distance).
For the sake of full comparability with UECs we express labor costs as a share of the value of production.
The coefficients reported in Tables are estimated with a PQML and as such they can be interpreted as elasticities. See Gourieroux (2000).
Considering the bilateral exchange rate among the covariates does not impact significantly our results. These set of estimates are available upon request.
The contribution of the counterpart Chinese import with respect to the total import at the industry level is included as a regressor.
We use the share of value added of Agriculture, forestry and fishing; Arts, entertainment and recreation, other service activities, activities of household and extra-territorial organizations and bodies; Construction; Industry (except construction); Information and communication; Professional, scientific and technical activities; administrative and support service activities, Public administration, defense, education, human health and social work activities; Real estate activities; Wholesale and retail trade, transport, accommodation and food service activities.
Between 1999 and 2015, EA export in nominal terms grew of about 140%; excluding Germany, EA export would have increased by about 100% while in the same period German export grew of about 250%.
Shengwu et al. (2017), following Puhani (2012), argue that in case of non-linear models (in particular with a Poisson link function), the interaction parameters cannot be considered as the difference in semi-elasticity and propose a solution to fix this issue; in the bottom of Table 9 we show some estimates of the interactions that uses the same kind of adjustment.
The central line is based on the mean of the replications while the upper and lower bound are computed taking upper and lower 2.5 percent of the empirical distribution.
The practical setup of a carbon border adjustment, that does not violate the WTO legal framework, must overcome significant challenges: technical feasibility, data availability, the risk of retaliation (Rocchi et al. 2018).
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We would like to thank the participants to the 6th Italian Association of Environmental and Resource Economists (IAERE), to the World Congress of Environmental and Resource Economists (WCERE) conferences, to the eighth edition of the Italian Congress of Econometrics and Empirical Economics (ICEEE) and to the 38th edition of the International Energy Workshop (IEW). We are also indebted to Matteo Bugamelli, Federico Cingano, Paolo Sestito, Stefano Siviero, Roberto Torrini, Roberta Zizza, Francesco Zollino and three anonymous referee for their valuable comments. This paper was previously circulated under the title Energy costs and competitiveness in Europe. The views expressed do not necessarily reflect those of the Bank of Italy.
Appendices
Figures
See Fig. 11.
UEC decomposition
where
we define energy intensity as
plugging in the previous results, we obtain
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Faiella, I., Mistretta, A. The Net Zero Challenge for Firms’ Competitiveness. Environ Resource Econ 83, 85–113 (2022). https://doi.org/10.1007/s10640-022-00652-7
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DOI: https://doi.org/10.1007/s10640-022-00652-7