Electricity without borders: a plan to make the internal market work. Bruegel Blueprint Series 20, 5 September 2013

The most straightforward European single energy market design would entail a European system operator regulated by a single European regulator. This would ensure the predictable development of rules for the entire EU, significantly reducing regulatory uncertainty for electricity sector investments. But such a first-best market design is unlikely to be politically realistic in the European context for three reasons. First, the necessary changes compared to the current situation are substantial and would produce significant redistributive effects. Second, a European solution would deprive member states of the ability to manage their energy systems nationally. And third, a single European solution might fall short of being well-tailored to consumers’ preferences, which differ substantially across the EU. To nevertheless reap significant benefits from an integrated European electricity market, we propose the following blueprint: First, we suggest adding a European system-management layer to complement national operation centres and help them to better exchange information about the status of the system, expected changes and planned modifications. The ultimate aim should be to transfer the day-to-day responsibility for the safe and economic operation of the system to the European control centre. To further increase efficiency, electricity prices should be allowed to differ between all network points between and within countries. This would enable throughput of electricity through national and international lines to be safely increased without any major investments in infrastructure. Second, to ensure the consistency of national network plans and to ensure that they contribute to providing the infrastructure for a functioning single market, the role of the European ten year network development plan (TYNDP) needs to be upgraded by obliging national regulators to only approve projects planned at European level unless they can prove that deviations are beneficial. This boosted role of the TYNDP would need to be underpinned by resolving the issues of conflicting interests and information asymmetry. Therefore, the network planning process should be opened to all affected stakeholders (generators, network owners and operators, consumers, residents and others) and enable the European Agency for the Cooperation of Energy Regulators (ACER) to act as a welfare-maximising referee. An ultimate political decision by the European Parliament on the entire plan will open a negotiation process around selecting alternatives and agreeing compensation. This ensures that all stakeholders have an interest in guaranteeing a certain degree of balance of interest in the earlier stages. In fact, transparent planning, early stakeholder involvement and democratic legitimisation are well suited for minimising as much as possible local opposition to new lines. Third, sharing the cost of network investments in Europe is a critical issue. One reason is that so far even the most sophisticated models have been unable to identify the individual long-term net benefit in an uncertain environment. A workable compromise to finance new network investments would consist of three components: (i) all easily attributable cost should be levied on the responsible party; (ii) all network users that sit at nodes that are expected to receive more imports through a line extension should be obliged to pay a share of the line extension cost through their network charges; (iii) the rest of the cost is socialised to all consumers. Such a cost-distribution scheme will involve some intra-European redistribution from the well-developed countries (infrastructure-wise) to those that are catching up. However, such a scheme would perform this redistribution in a much more efficient way than the Connecting Europe Facility’s ad-hoc disbursements to politically chosen projects, because it would provide the infrastructure that is really needed.

Drivers of agricultural capital productivity in selected EU member states. Factor Markets Working Paper No. 30, September 2012

The aim of this Working Paper is to provide an empirical analysis of the marginal return on working capital and fixed capital in agriculture, based on data gathered by the Farm Accountancy Data Network from seven EU member states. Particular emphasis is placed on the detection of credit market imperfections. The key idea is to provide farm group-specific estimates of the shadow price of capital, and to use these to analyse the drivers of on-farm capital use in European agriculture. Based on Cobb Douglas estimates of farm-type specific production functions, we find that working capital is typically used in more than economically optimal quantities and often displays negative marginal returns across countries and farm types. This is less often the case with regard to fixed capital, but it is only in a small set of sectors where access to fixed capital appears severely constrained. These sectors include field crop and mixed farms in Denmark, dairy farms in East Germany, as well as mixed farms in Italy and the UK. The relationship between farm financial indicators and the estimated shadow prices of capital varies considerably across countries and sectors. Among the farms with a high shadow price for fixed capital in Denmark, high debt levels and little owned land tended to induce more intensive capital use, which may reflect the liberal Danish banking system. In East Germany, Italy and the UK, high debt levels made farmers more tightly capital constrained. Hence, in the latter group of countries, more traditional mechanisms of capital allocation based on debt capacity seemed to be at work. As a general conclusion, EU agriculture appears to be characterised by overcapitalisation rather than by credit constraints.

The Reallocation of Agricultural Labour across Sectors: An Empirical Strategy for Micro Data. Factor Markets Working Document No. 45, May 2013

This paper presents an empirical methodology for studying the reallocation of agricultural labour across sectors from micro data. Whereas different approaches have been employed in the literature to better understand the mobility of labour, looking at the determinants to exit farm employment and enter off-farm activities, the initial decision of individuals to work in agriculture, as opposed to other sectors, has often been neglected. The proposed methodology controls for the selectivity bias, which may arise in the presence of a non-random sample of the population, in this context those in agricultural employment, which would lead to biased and inconsistent estimates. A 3-step multivariate probit with two selection and one outcome equations constitutes the selected empirical approach to explore the determinants of farm labour to exit agriculture and switch occupational sector. The model can be used to take into account the different market and production structures across European member states on the allocation of agricultural labour and its adjustments.

Factor Markets in General Computable Equilibrium Models. Factor Markets Working Document No. 47, May 2013

One objective of Computable general equilibrium (CGE) models is the analysis of economy-wide effects of policy measures. The focus of the Factor Markets project is to analyse the functioning of factor markets for agriculture in the EU-27, including the Candidate Countries. While agricultural and food markets are fully integrated in a European single market, subject to an EU-wide common policy, the Common Agricultural Policy (CAP), this is not the case for the agricultural factor markets capital, labour and land. There are partly serious differences with regard to member state regulations and institutions affecting land, labour and capital markets. The presentation of this heterogeneity of factor markets amongst EU Member States have been implemented in the CGE models to improve model-based analyses of the CAP and other policy measures affecting agricultural production. This final report comprises the outcome of a systematic extension and improvement of the Modular Applied GeNeral Equilibrium Tool (MAGNET) model starting from an overview of the current state of the art to represent factor markets in CGE models to a description of work on labour, land and capital in MAGNET.

Will improved access to capital dampen the need for more agricultural land? A CGE analysis of agricultural capital markets and world-wide biofuel policies. Factor Markets Working Paper No. 48, May 2013

This paper analyses the consequences of enhanced biofuel production in regions and countries of the world that have announced plans to implement or expand on biofuel policies. The analysis considers biofuel policies implemented as binding blending targets for transportation fuels. The chosen quantitative modelling approach is two-fold: it combines the analysis of biofuel policies in a multi-sectoral economic model (MAGNET) with systematic variation of the functioning of capital and labour markets. This paper adds to existing research by considering biofuel policies in the EU, the US and various other countries with considerable agricultural production and trade, such as Brazil, India and China. Moreover, the application multi-sectoral modelling system with different assumptions on the mobility of factor markets allows for the observation of changes in economic indicators under different conditions of how factor markets work. Systematic variation of factor mobility indicates that the ‘burden’ of global biofuel policies is not equally distributed across different factors within agricultural production. Agricultural land, as the pre-dominant and sector-specific factor, is, regardless of different degrees of inter-sectoral or intra-sectoral factor mobility, the most important factor limiting the expansion of agricultural production. More capital and higher employment in agriculture will ease the pressure on additional land use – but only partly. To expand agricultural production at global scale requires both land and mobile factors adapted to increase total factor productivity in agriculture in the most efficient way.