Incorporating rigidity and commitment in the timing structure of macroeconomic games

This paper proposes a novel framework that generalizes the timing structure of games. Building on alternating move games and models of rational inattention, the players' actions may be rigid, i.e., infrequent. This rigidity in the timing of moves makes the game more dynamic and asynchronous, acting as a commitment mechanism. Therefore, it can enhance cooperation and often eliminate inefficient equilibrium outcomes present in the static (normal form) game. Interestingly, (i) this can happen even in a finite game (possibly as short as two periods) and (ii) without reputation building. Furthermore, (iii) the required degree of commitment may be under some circumstances arbitrarily low and under others infinitely high. Our main example comes from macroeconomics in which various rigidities have played a central role. Investigating the Kydland–Prescott–Barro–Gordon monetary policy game, we derive the necessary and sufficient degree of long-term policy commitment to low inflation under which the influential time-inconsistency problem is eliminated.     

The Neighbourhood Policy of the European Union

The European Neighbourhood Policy aims at creating a ring of stable, friendly and democratic countries surrounding the European Union. While this aim is generally accepted across the Union, major differences persist as to how it should be achieved. Where does the ENP stand today? What is its profile, potential and perspective?     

Joint Ventures versus Contractual Agreements: An Empirical Investigation

In this paper, we empirically investigate the determinants of the governance form of strategic alliances. We use a database with 1,344 worldwide alliances in several industrial sectors. In contrast with previous empirical studies, we find that alliances undertaking R&D activities are more likely to use loose forms of organization (contractual agreements) than more hierarchical ones (joint ventures), and this result is even stronger when the alliance takes place in technologically sophisticated sectors. Moreover, we show that alliances between rival firms tend also to be organized with forms closer to arm’s length transactions. When the scope of an alliance is multidimensional or the alliance is an international one, however, firms prefer more hierarchical organizations such as joint ventures. This paper was partially written while the first author was visiting the University of the Basque Country. We would like to thank Reinhilde Veugelers and the project FWO spillovers 6.0131.98 at the Katholieke Universiteit of Leuven for the use of the K.U. database. Financial support from projects Progetto Giovani Ricercatori – 1999 Universitá di Udine, SEJ 2004-02172/ECON, 9/UPV 00035.321-13560/2001, UPV 00038.321-13503/2001 is gratefully acknowledged. We are also indebted to two anonymous referees for their helpful comments.     

Integrated Management of Land Use Systems under Systemic Risks and Security Targets: A Stochastic Global Biosphere Management Model

Interdependencies among land use systems resemble a complex network connected through demand–supply relationships. Disruption of this network may catalyse systemic risks affecting food, energy, water and environmental security (FEWES) worldwide. We describe the conceptual development, expansion and practical application of a stochastic version of the Global Biosphere Management Model (GLOBIOM), used to assess competition for land use between agriculture, bioenergy and forestry at regional and global scales. In the stochastic version of the model, systemic risks of various kinds are explicitly covered and can be analysed and mitigated in all their interactions. While traditional deterministic scenario analysis produces sets of scenario‐dependent outcomes, stochastic GLOBIOM explicitly derives robust outcomes that leave the systems better‐off, independently of which scenario applies. Stochastic GLOBIOM is formulated as a stochastic optimisation model that is critical for evaluating portfolios of robust interdependent decisions: ex‐ante strategic decisions (production allocation, storage capacities) and ex‐post adaptive (demand, trading, storage control) decisions. As an example, the model is applied to the question of optimal storage facilities, as buffers for production shortfalls, to meet regional and global FEWES requirements when extreme events occur. Expected shortfalls and storage capacities have a close relationship with Value‐at‐Risk (VaR) and Conditional Value‐at‐Risk (CVaR) risk measures. A Value of Stochastic Solutions is calculated to illustrate the benefits of the stochastic over the deterministic model approach.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

Farming system modelling for agri-environmental policy design: The case of a spatially non-aggregated allocation of conservation measures

This paper addresses the issue of designing policies for habitat conservation on agricultural land. The case under study requires a non-aggregated spatial distribution of the fields to be enrolled in an agri-environmental programme. A spatially explicit mathematical programming farm-based model, which accounts for three spatial levels (field, farm and landscape), is coupled with a relevant spatial pattern index (the Ripley L-function) to analyse the design and implementation of an agri-environmental programme aimed to preserve the Tetrax tetrax in the Plaine de Niort, France. The model is run using a stylised map with heterogeneous soil types and both crop growing and mixed dairy farms. Results show that valuable insights into agri-environmental programme design are gained through a detailed representation of farming system management. The suitable, non-aggregated spatial pattern for T. tetrax conservation is more costly than less-suitable, more aggregated patterns, because it tends to require equal participation of all farms. The policy simulations reveal that the various spatial patterns can be obtained through relatively simple uniform contract structures. An effective contract structure entails a set of two degressive payments which encourages all farms to enrol at least a small share of their land in the program.     

Investment strategies in the long run with proportional transaction costs and a HARA utility function

We consider an agent who invests in a stock and a money market in order to maximize the asymptotic behaviour of expected utility of the portfolio market price in the presence of proportional transaction costs. The assumption that the portfolio market price is a geometric Brownian motion and the restriction to a utility function with hyperbolic absolute risk aversion (HARA) enable us to evaluate interval investment strategies. It is shown that the optimal interval strategy is also optimal among a wide family of strategies and that it is optimal also in a time changed model in the case of logarithmic utility.