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SIMUL

SIMUL is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand SIMUL rather than just read about it. In short: SIMUL is an econometric tool for the multidimensional (multi-sectoral and multi-regional) modelling. It allows to implement easily multidimensional econometric models according to their reduced form Y r , b = X r , b . a r , b + ε r , b {\displaystyle Y_{r,b}=X_{r,b}.a_{r,b}+\varepsilon _{r,b}} - where X and Y are two economic variables, r and b (resp.) denote the region and the branch (resp.) and where ε {\displays…

SIMUL — main illustration
SIMUL — illustration

Key takeaways

  • SIMUL belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect SIMUL to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of SIMUL from memory before moving on to harder problems.

Reference excerpt

SIMUL is an econometric tool for the multidimensional (multi-sectoral and multi-regional) modelling. It allows to implement easily multidimensional econometric models according to their reduced form Y r , b = X r , b . a r , b + ε r , b {\displaystyle Y_{r,b}=X_{r,b}.a_{r,b}+\varepsilon _{r,b}} - where X and Y are two economic variables, r and b (resp.) denote the region and the branch (resp.) and where ε {\displaystyle \varepsilon } is the residual. It has been initially developed in the middle of the 90's inside the GAMA Team of the Professor Raymond Courbis at the University of Paris 10 during the project of multi-regional and multi-sectoral national models of REGILINK (R.Courbis, 1975, 1979, 1981).

SIMUL 3.2 Since 2003, SIMUL release 3.2 has been developed independently from the REGILINK models. It can always run them but not only. The conception of SIMUL 3.2 was inspired by a software used during a long time in GAMA Team, the SIMSYS software, developed by M.C.McCracken and C.A.Sonnen. SIMUL 3.2 is a tool for preparing, estimating and running dynamic, multi-sectoral and multi-regional models. It has been developed in Turbo-Pascal and needs it during the working sessions. The user implement the econometric models into a "natural language" the SIMUL 3.2 translates, compiles and runs it according to a Code generation process. SIMUL 3.2 has been applied to French labor market analysis. SIMUL 3.2 is freely downloadable at the Econpapers website [7]

Notes

References Almon C., (1991), "The INFORUM approach to interindustry modeling", Economic Systems Research, 3(1), pp. 1–7. Brillet J.L., (1994), Modélisation économétrique - Principes et techniques, Paris, Economica, Coll.Économie et statistiques avancées, 196 p. + le logiciel Soritec Sampler. Buda R., (2010), Modélisation multi-dimensionnelle et analyse multi-régionale de l'économie française, Thèse pour le Doctorat de Sciences économiques soutenue le 23 novembre, Université de Paris-Ouest Nanterre-La Défense, 654 p. [8] Buda R., (2013), "SIMUL 3.2: An Econometric Tool for Multidimensional Modelling", Computational Economics, 41(4), pp. 517–524. [9] Buda R., (2015), "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding", Computational Economics, 46(2), pp. 325–357. [10] Courbis R., (1975), "Le modèle REGINA, modèle de développement national, régional et urbain de l'économie française", Économie Appliquée, 28(2-3). Courbis R., (1979), "Le Modèle REGINA, modèle de développement national, régional et urbain de l’économie française" in R.Courbis (Ed.), Modèles régionaux et modèles régionaux-nationaux, Paris, Cujas, Travaux du Gama, pp. 87–102. Courbis R., (1981), "La construction de modèles multinationaux : problèmes méthodologiques", in R.Courbis (Ed.), Commerce international et modèles multinationaux – Actes du IIIè colloque international d'Econométrie appliquée, Coll.Travaux du GAMA, 3, Paris, Cujas, pp. 243–247. Courbis R. & Sok H., (1983), "Le modèle ANAIS, un modèle intersectoriel détaillé de l'économie française", Prévision et Analyse économique (Cahiers du GAMA), 4(2), juin, pp. 73–101. McCracken M.C. & Sonnen C.A., (1972), A system for large econometric models: management, estimation, and simulation, in Proceedings of the Association for Computing Machinery Annual Conference, August 1972, Association for Computing Machinery. Peterson W., (1987), "Computer Software for a Large Econometric Model", in T.Barker & W.Peterson (Eds.), The Cambridge Multisectoral Dynamic Model of the British Economy, Cambridge, Cambridge University Press, pp. 105–121.

Illustrations

SIMUL illustration

Worked examples

Example 1 — a first encounter with SIMUL

Start with the simplest possible case. Write down what SIMUL claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to SIMUL before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about SIMUL ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of SIMUL

In research
SIMUL appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses SIMUL in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
SIMUL is common in secondary-school and first-year university syllabi. It links to neighbouring topics Econometrics software, Proprietary software, Windows-only software, so understanding it makes those chapters shorter.
In everyday life
Look for SIMUL outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study SIMUL in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what SIMUL means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain SIMUL out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is SIMUL in simple terms?

SIMUL is an econometric tool for the multidimensional (multi-sectoral and multi-regional) modelling. It allows to implement easily multidimensional econometric models according to their reduced form Y r , b = X r , b . a r , b + ε r , b {\displaystyle Y_{r,b}=X_{r,b}.a_{r,b}+\varepsilon _{r,b}} - w…

Why does SIMUL matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study SIMUL?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on SIMUL.

Tags

  • Econometrics software
  • Proprietary software
  • Windows-only software

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