Francisco J. Andre´, M. Alejandro Cardenete (Department of Economcs, Pablo de Olavide University, Carretera de Utrera km. 1, 41008 Sevilla, Spain)
Socio-Economic Planning Sciences: 43 (2006), pp. 192-200
Objectives
This research attempted to quantify trade-offs between 2 specific policy objectives, growth and inflation, when designing fiscal policy. The model constructed a frontier of efficient policies involving real growth and inflation. The model is applied practically by offering policy recommendations that COULD have helped Spain during 1995 inefficiencies.
The methodology is claimed to be unique since it is operational and practical while remaining consistent with economic theory. The combination of Multi-objective Programming (MP) and Computable General Equilibrium (CGE) has never been attempted. It is pioneering in its application of the Paretian concept of efficiency to the field of policy design
Key Methods or Approach
The key methods were Multicriteria Decision Making (MCDM), specifically Multi-objective Programming (MP), combined with a Computable General Equilibrium (CGE) model. CGE is consistent with standard economic theory and allows measurement of effect(s) of a specific policy with real data concerning prices, production levels, tax revenues, and income distribution. This set-up allows calculation of relevant macroeconomic indicators as a function of policy instruments within a multicriteria decision problem to be solved by a policy maker.
Important Results or Conclusions
They showed that in 1995 Spain displayed some degree of inefficiency with respect to growth and inflation policy objectives. They used this model to provide two policy recommendations sets. One recommendation was general in that it considered efficiency independent of the importance of growth or inflation. The second focused on a specific objective such as increased growth or controlled inflation.
Assumptions
The litany of assumptions that accompany economic models are what is steering me away from incorporating an economic model such as general-equilibrium. Some of the assumptions for this model include:
- The CGE uses Walrasian equilbrium including the public and foreign sectors. (The meaning of this I am not exactly sure, so it is not really something that deters me from using CGE, but I did want to document it.)
- Taxes and public expenditure are taken as exogenous by consumers and firms, but are considered decision variables for the government
- The equilibrium of the economy is given by a price vector for all goods and inputs, a vector of activity levels and value for public income
- Public income must satisfy following conditions:
1) consumers maximize utility
2) firms maximize profits
3) public income equals payment of all economic agents
4) supply equals demand in all markets
This last set of mentioned assumptions are the type of required assumptions that do deter me. I do not believe that
"the consumer’s behaviour is modelled by assuming that s/he aims to
maximize welfare, which is derived from consumption goods." I also believe that firms must solely focus on maximizing profits. Lastly, is it really practical to expect supply to equal demand in all markets.
The most useful aspect of this paper were its Multi-Criteria Decision Making (MCDM) references:
(Introduction to MCDM techniques, and their applications to economic problems) Ballestero E, Romero C. Multiple criteria decision making and its applications to economic problems. Boston, MA: Kluwer Academic Publishers; 1998.
(State-of-the-art review of the field)Figueira J, Greco S, Ehrgott M, editors. Multiple criteria decision analysis state of the art surveys. International Series inOperationsResearch & Management Science, Vol. 78. Berlin: Springer-Verlag; 2005.
(Recent developments and applications of MP)Gabriel SA, Faria JA, Moglen GE. A multiobjective optimization approach to smart growth
in land development. Socio-Economic Planning Sciences 2006;40:212–48.(Recent developments and applications of MP)Gabriel SA, Faria JA, Moglen GE. A multiobjective optimization approach to smart growth
Hung ML, Yang W, Ma HW, Yang YM. A novel multiobjective programming approach dealing with qualitative and quantitative objectives for environmental management. Ecological Economics 2006;56:584–93.
Lins MPE, Angulo-Meza L, Moreira-Da-Silva AC. A multi-objective approach to determine alternative targets in data envelopment analysis. Journal of the Operational Research Society 2004;55:1090–101.
Gabriel SA, Kumar S, Ordo´n˜ez J, Nasserian A. A multiobjective optimization model for project selection with probabilistic considerations. Socio-Economic Planning Sciences 2006;40:297–313.
Ferna´ndez E, Puerto J. Multiobjective solution of the uncapacitated plant location problem. European Journal of Operational Research 2003;145:509–29.
Arroyo JEC, Armentano VA. Partial enumeration heuristic for multiobjective flowshop scheduling problems. Journal of the Operational Research Society 2004;55:1000–7.
Doerner KF, Gutjahr WJ, Hartl RF, Strauss C, Stummer C. Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection. European Journal of Operational Research 2006; 171:830–41.
According to Google Scholar this paper has been cited three times, but it was only published in 2009. That is actually good considering it has not been a whole year. The paper itself was well laid out and addressed it objectives and the format it stated in the beginning of the paper. It has no direct impact on the field of food distribution environmental or nutritional impacts. However the suggested extensions and referred MCDM methodologies could be used to create a model that addresses the multiple goals within a food value supply chain. With that in mind the Multiobjective Programming (MP) could possibly be combined with Agent-Based Modeling instead of CGE as I am not interested in being consistent with economic theory.
The conclusion of the paper included the following suggested extensions:
- Alternative multi-criteria methods that do not seek global optimum, but, rather, satisfy "reasonable" aspiration levels using goal programming
- interactive MCDM provides a way to "fine-tune" policies by incorporating preferences of policy makers once initial policy suggestions have been offered
No comments:
Post a Comment