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Coupling Mathematical Programming Models With Input-Output Analysis for the Economy-Energy-Environmental Assessment of the Energy Sector

Online Event |

As part of CEGIST's seminar series, we are proud to announce that Carla Henriques (ISCAC) will present the work "Coupling Mathematical Programming Models With Input-Output Analysis for the Economy-Energy-Environmental Assessment of the Energy Sector".

This seminar will take place on October 25 at 15:00, online via Zoom (link below)

Our seminars are free to attend and open to everyone. Please share with whomever may be interested.

Carla Henriques
Carla Henriques


The assessment of the trade-offs between economic growth, energy demand/supply, and their corresponding environmental and social effects are particularly relevant for energy planners and decision-makers through the use of reliable tools for supporting the process of energy policy decision-making. In this context, coupling mathematical programming models and methods with Input-Output (IO) analysis can be particularly appropriate for assisting in Economy-Energy-Environmental policy design. IO analysis is a top-down approach that can be intertwined with environmental satellite accounts provided by national statistical offices, allowing broad impact coverage of all sectors, directly and indirectly, involved with the energy sector. Furthermore, IO has influenced the outset of linear programming (LP) and it may be considered as a simple particular case of LP. The combined use of the IO methodology with LP models allows for attaining value-added information, which would not be possible to achieve with the isolated use of both techniques. Inter/intra-sector relations entrenched in IO analysis allow obtaining the production possibility frontier. LP models enable selecting the level of activities that optimize a given objective function, satisfying the production sector relations imposed by IO analysis. Additionally, IO multi-objective models allow assessing different efficient possibilities of production (i.e., output levels for each activity sector for which there is no other feasible solution that allows improving the value of a given objective function without worsening the value of, at least, other objective function) that can be reconciled with the competing axes of evaluation intrinsically at stake. Finally, the IO MOLP framework can also be extended and adjusted to accommodate the uncertainty handling of the coefficients of this kind of model, overcoming a major drawback usually mentioned related to the static nature of the IO traditional matrix.

Speaker's bio

Carla Margarida Saraiva de Oliveira Henriques is an Assistant Professor at the Coimbra Business School|ISCAC. She has been responsible for several curricular units in the areas of Economics and Business, included in the curricular plans of several Undergraduate and MSc. degrees. She is also a faculty member of the Energy for Sustainability Initiative - UC, where she supervises MSc. and PhDs. As a researcher she is an associate researcher at INESC Coimbra. She has been developing scientific work focused on the development and use of mathematical models, combining the input-output approach with multi-objective linear programming models, which allow the evaluation of the interactions between the economic, energy and environmental systems. Her research interests have also included the explicit treatment of the uncertainty inherent to the specification of the coefficients of this type of models using interval mathematical programming tools. Recently, she has also developed research work in the field of economics of education, labour market and well-being through the combination of econometric and multi-objective programming models. She has also published more than 30 papers in scientific journals with ISI impact factor and indexed to Scopus.

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