The Impact of Pillar II Funding: Validation from a Modelling and Evaluation Perspective

We extend the Common Agricultural Policy Regionalised Impact Modelling System (CAPRI) with a regional computational general equilibrium (CGE) model to estimate the effects of the Pillar II of the Common Agricultural Policy. Our aim is to assess the modeling approach by comparing the scenario results with observations from the evaluation reports for rural development, supplemented with expert interviews and findings from the literature. For this purpose, an ex‐post scenario is developed for Germany that models the effect of the Pillar II measures in 2006. We observe a moderate impact, namely, an increase in agricultural income (5%) and agricultural land use (0.15%), particularly grassland, and a substitution of arable land with grassland. This effect leads to a total increase in agricultural production, particularly of beef, and to an increase in total greenhouse gas emissions and total nitrogen surplus for Germany. Greenhouse gas emissions and nutrient surpluses per ha, however, are reduced. We observe that farm investment programmes displace private investment. The evaluation reports confirm the moderate impact and our major results, as does the comparison with other literature. However, the conclusions about agri‐environment measures and their impact on income differ. The most important difference between our results and the evaluation reports and majority of the present literature is that we also quantify the joint effect between the whole economy and policy measures, with some contradictory effects.     

Farm Type Effects of an EU‐wide Direct Payment Harmonisation

In this study, we analyse how three scenarios involving different levels of harmonisation of common agricultural policy (CAP) decoupled payments in the EU affect the distribution of farm income across regions and farm types. We use the farm type extension of the common agricultural policy impact (CAPRI) model, which captures farm heterogeneity across the EU. The first scenario (NUTS1) assumes uniform per‐hectare payments at the NUTS1 level. The second scenario (MS‐CONV) equalises the per‐hectare rates inside each Member State (MS) and partially harmonises the single payment scheme (SPS) across MS in line with the 2011 Commission proposal. The third scenario simulates a uniform per‐hectare payment at the EU level. Depending on the implementation of the SPS, the NUTS1 flat rate induces a substantial redistribution of payments across farm types and NUTS2 regions, particularly in regions that apply the historical SPS. The MS‐CONV and EU flat‐rate schemes have more significant impacts at the EU‐wide level. In the EU‐15, almost all farms lose payments from MS‐CONV and EU‐wide flat rates, whereas in the EU‐10, almost all farm types gain from these scenarios. Our conservative estimates indicate that the flat‐rate payments could redistribute up to €8.5 billion. Lower land rental costs partially offset the losses of farm income in the EU‐15 from payment redistribution. Land rents drop for all flat‐rate scenarios across most sectors and farm sizes in the EU‐15. In the less productive new MS, the landowners’ rental income is largely unaffected by the introduction of the flat rate.     

Non-cooperative support for the asymmetric Nash bargaining solution

We study a model of non-cooperative multilateral unanimity bargaining on a full-dimensional payoff set. The probability distribution with which the proposing player is selected in each bargaining round follows an irreducible Markov process. If a proposal is rejected, negotiations break down with an exogenous probability and the next round starts with the complementary probability. As the risk of exogenous breakdown vanishes, stationary subgame perfect equilibrium payoffs converge to the weighted Nash bargaining solution with the stationary distribution of the Markov process as the weight vector.     

Green Light for Green Agricultural Policies? An Analysis at Regional and Global Scales

This paper analyses the effects of introducing biodiversity‐targeted ecological focus area (EFA) requirements on all farms with arable land in the EU by quantifying their global, regional, economic and environmental impacts in a mutually consistent way. To capture these impacts, different spatial scales need to be considered – ranging from on‐farm decisions regarding the EFA in the EU, to supply response around the world. In order to address this challenge, we combine the supply side of the CAPRI model, which offers high spatial, farm and policy resolution in the EU, with the GTAP model of global trade and land use. Both models are linked through a multi‐product, restricted‐revenue function for the EU crop sector. The results predict improved environmental status in the high‐yielding regions of the EU. However, output price increases lead to intensification in the more marginal areas of the EU where little or no additional land is taken out of production. The decrease in arable land in the EU is partially compensated by an increase of crop land, as well as increased fertiliser applications, in other regions of the globe. Thus, the improvement of environmental status in the EU comes at the price of global intensification, as well as the loss of forest and grassland areas outside the EU. Overall, we find that every hectare of land that is taken out of production in the EU increases greenhouse gas emissions in the rest of the world by 20.8 tonnes CO₂ equivalent.     

Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level

This study belongs to the barely explored research strand of “Econometric Mathematical Programming” and presents a simultaneous estimation of the cost function and of the farmers’ risk attitude parameter in a programming model setup. Resource and policy constraints of the model are allowed to be not binding. We use crop shares as decision variables to avoid scale bias and we consider price and crop yield variances separately. The model is formulated as a bi‐level programming model and the empirical application concerns three unbalanced panels of specialized arable farms observed for at least three consecutive years in Northern Italy, in the Cologne‐Aachen area in Germany and in the Grandes‐Cultures area in France over the time period 1995–2007. We achieve a quite satisfactory fit in the estimation exercise and find own and cross price elasticities from sensitivity experiments in reasonable ranges. We also propose a novel approach to derive confidence intervals around parameter estimates for Econometric Mathematical Programming.     

What Drives Marginal Abatement Costs of Greenhouse Gases on Dairy Farms? A Meta‐modelling Approach

This paper examines the relationships between the marginal abatement costs (MAC) of greenhouse gas (GHG) emissions on dairy farms and factors such as herd size, milk yield and available farm labour, on the one hand, and prices, GHG indicators and GHG reduction levels, on the other. A two‐stage Heckman procedure is used to estimate these relationships from a systematically designed set of simulations with a highly detailed mixed integer bio‐economic farm‐level model. The resulting meta‐models are then used to analyse how MAC vary across farm‐level conditions and GHG measures. We find that simpler GHG indicators lead to significantly higher MAC, and that MAC strongly increase beyond a 1–5% emission reduction, depending on farm attributes and the chosen indicator. MAC decrease rapidly with increasing farm size, but the effect levels off beyond a herd size of 40 cows. As expected, the main factors driving gross margins per dairy cow also significantly influence mitigation costs. Our results indicate high variability of MAC on real life farms. In contrast to time consuming simulations with the complex mixed integer bio‐economic programming model, the meta‐models allow the distribution of MAC in a farm population to be efficiently derived and thus could be used to upscale to regional or sector level.     

Analysing Farm‐specific Payments for Norway using the Agrispace Model

Norway maintains a complex system of activity or type specific coupled payments which account for a large share of farm income. Most of the payment rates are negatively related to farm size and are higher in remote areas compared to central regions. We present and use a newly developed recursive‐dynamic multi‐commodity model (Agrispace) with CES production functions depicting regional farm clusters derived from the full farm population. Using this model, we simulate impacts of current and alternative subsidy policies on production, prices, input use, income and farm structural change. Mapping cluster results to each farm along with behavioural rules allows estimation of individual profits and farm exits. Our results indicate that, in the short run, the current policy regime seems to support the policy objective of maintaining a variety of farms in all parts of Norway. In the long run, farm structural change is less affected by a policy reform that leaves total support levels unchanged.     

A bargaining theory of the firm

Suppose that a firm has several owners and that the future is uncertain in the sense that one out of many different states of nature will realize tomorrow. An owner’s time preference and risk attitude will determine the importance he places on payoffs in the different states. It is a well-known problem in the literature that under incomplete asset markets, a conflict about the firm’s objective function tends to arise among its owners. In this paper, we take a new approach to this problem, which is based on non-cooperative bargaining. The owners of the firm play a bargaining game in order to choose the firm’s production plan and a scheme of transfers which are payable before the uncertainty about the future state of nature is resolved. We analyze the resulting firm decision in the limit of subgame-perfect equilibria in stationary strategies. Given the distribution of bargaining power, we obtain a unique prediction for a production plan and a transfer scheme. When markets are complete, the production plan chosen corresponds to the profit-maximizing production plan as in the Arrow–Debreu model. Contrary to that model, owners typically do use transfers to redistribute profits. When markets are incomplete, the production plan chosen is almost always different from the one in a transfer-free Drèze (pseudo-)equilibrium and again owners use transfers to redistribute profits. Nevertheless, our results do support the Drèze criterion as the appropriate objective function of the firm.