Variability of the ocean heat content during the last millennium - an assessment with the ECHO-g Model

Studies addressing climate variability during the last millennium generally focus on variables with a direct influence on climate variability, like the fast thermal response to varying radiative forcing, or the large-scale changes in atmospheric dynamics (e. g. North Atlantic Oscillation). The ocean responds to these variations by slowly integrating in depth the upper heat flux changes, thus producing a delayed influence on ocean heat content (OHC) that can later impact low frequency SST (sea surface temperature) variability through reemergence processes. In this study, both the externally and internally driven variations of the OHC during the last millennium are investigated using a set of fully coupled simulations with the ECHO-G (coupled climate model ECHAMA4 and ocean model HOPE-G) atmosphere-ocean general circulation model (AOGCM). When compared to observations for the last 55 yr, the model tends to overestimate the global trends and underestimate the decadal OHC variability. Extending the analysis back to the last one thousand years, the main impact of the radiative forcing is an OHC increase at high latitudes, explained to some extent by a reduction in cloud cover and the subsequent increase of short-wave radiation at the surface. This OHC response is dominated by the effect of volcanism in the preindustrial era, and by the fast increase of GHGs during the last 150 yr. Likewise, salient impacts from internal climate variability are observed at regional scales. For instance, upper temperature in the equatorial Pacific is controlled by ENSO (El Nino Southern Oscillation) variability from interannual to multidecadal timescales. Also, both the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) modulate intermittently the interdecadal OHC variability in the North Pacific and Mid Atlantic, respectively. The NAO, through its influence on North Atlantic surface heat fluxes and convection, also plays an important role on the OHC at multiple timescales, leading first to a cooling in the Labrador and Irminger seas, and later on to a North Atlantic warming, associated with a delayed impact on the AMO.

Using a CGE Model to Identify the Policy Trade-Off between Unemployment and Inflation: The Efficient Phillips Curve

This paper provides a new reading of a classical economic relation: the short-run Phillips curve. Our point is that, when dealing with inflation and unemployment, policy-making can be understood as a multicriteria decisionmaking problem. Hence, we use so-called multiobjective programming in connection with a computable general equilibrium (CGE) model to determine the combinations of policy instruments that provide efficient combinations of inflation and unemployment. This approach results in an alternative version of the Phillips curve labelled as efficient Phillips curve. Our aim is to present an application of CGE models to a new area of research that can be especially useful when addressing policy exercises with real data. We apply our methodological proposal within a particular regional economy, Andalusia, in the south of Spain. This tool can give some keys for policy advice and policy implementation in the fight against unemployment and inflation.

A modified DEA model to estimate the importance of objectives with an application to agricultural economics

This paper demonstrates a connection between data envelopment analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows us to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of multiple attribute decision analysis the basic contribution of this paper is a new interpretation in terms of efficiency of the non-interactive methodology employed to estimate weights in a multicriteria approach. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures that does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.

Designing Efficient Subsidy Policies in a Regional Economy: A Multicriteria Decision-Making (MCDM)-Computable General Equilibrium (CGE) Approach

Since policy-makers usually pursue several conflicting objectives, policy-making can be understood as a multicriteria decision problem. Following the methodological proposal by André and Cardenete (2005) André, F. J. and Cardenete, M. A. 2005. Multicriteria Policy Making. Defining Efficient Policies in a General Equilibrium Model, Seville: Centro de Estudios Andaluces. Working Paper No. E2005/04, multi-objective programming is used in connection with a computable general equilibrium model to represent optimal policy-making and to obtain so-called efficient policies in an application to a regional economy (Andalusia, Spain). This approach is applied to the design of subsidy policies under two different scenarios. In the first scenario, it is assumed that the government is concerned just about two objectives: ensuring the profitability of a key strategic sector and increasing overall output. Finally, the scope of the exercise is enlarged by solving a problem with seven policy objectives, including both general and sectorial objectives. It is concluded that the observed policy could have been Pareto-improved in several directions.