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Large-scale macroeconometric model

Large-scale macroeconometric model is a 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 Large-scale macroeconometric model rather than just read about it. In short: Following the development of Keynesian economics, applied economics began developing forecasting models based on economic data including national income and product accounting data. In contrast with typical textbook models, these large-scale macroeconometric models used large amounts of data and based forecasts on past correlations instead of theoretical relations.

Key takeaways

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

Reference excerpt

Following the development of Keynesian economics, applied economics began developing forecasting models based on economic data including national income and product accounting data. In contrast with typical textbook models, these large-scale macroeconometric models used large amounts of data and based forecasts on past correlations instead of theoretical relations. These models estimated the relations between different macroeconomic variables using regression analysis on time series data. These models grew to include hundreds or thousands of equations describing the evolution of hundreds or thousands of prices and quantities over time, making computers essential for their solution. While the choice of which variables to include in each equation was partly guided by economic theory (for example, including past income as a determinant of consumption, as suggested by the theory of adaptive expectations), variable inclusion was mostly determined on purely empirical grounds. Large-scale macroeconometric model consists of systems of dynamic equations of the economy with the estimation of parameters using time-series data on a quarterly to yearly basis. Macroeconometric models have a supply and a demand side for estimation of these parameters. Kydland and Prescott call it the system of equations approach. Large-scale macroeconometric model can be defined as a set of stochastic equations with definitional and institutional relationships denoting the behaviour of economic agents. The supply side determines the steady state properties of the macroeconometric model. The macroeconometric model designed by the model builder is significantly influenced by his interests, information, purpose behind its construction, time and financial constraints in the research. The size and nature of the model will change based on the considerations above while building the same. According to Pesaran and Smith the macroeconometric model must have three basic characteristics viz. relevance, adequacy and consistency. Relevance means the model must be according to the requirements of the desired output. Consistency will expect the model to be inline with the existing theory and inner working of the described system. Adequacy explains the model to be better in terms of its predictive performance. The main objective of the model decides its size. In the current scenario there is an increasing interest in the use of these large-scale macroeonometric models for theory evaluation, impact analysis, policy simulation and forecasting purposes. Large-scale macroeconometric models were criticized by Robert Lucas in his critique. Lucas argued that models should be based on theory, not on empirical correlations. Because the parameters of those models were not structural, i.e. not policy-invariant, they would necessarily change whenever policy (the rules of the game) was changed, leading to potentially misleading conclusions. Only a model based on theory could account for shifting policy environments. Lucas and other new classical economists were especially critical of the use of large-scale macroeconometric models to evaluate policy impacts when they were purportedly sensitive to policy changes. Lucas summarized his critique:

Given that the structure of an econometric model consists of optimal decision rules of economic agents, and that optimal decision rules vary systematically with changes in the structure of series relevant to the decision maker, it follows that any change in policy will systematically alter the structure of econometric models.

Tinbergen developed the first comprehensive national model, which he first built for the Netherlands and later applied to the United States and the United Kingdom after World War II. The first global macroeconomic model, Wharton Econometric Forecasting Associates' LINK project, was initiated by Lawrence Klein. The model was cited in 1980 when Klein, like Tinbergen before him, won the Nobel Prize in Economics. Large-scale empirical models of this type, including the Wharton model, are still in use as of 2011, especially for forecasting purposes.

List MFMod – World Bank Project LINK at Wharton MIT-Penn-Social Science Research Council

See also Macroeconomic model Time series Lucas critique Dynamic stochastic general equilibrium Consensus forecast

References

Further reading Brown, T. Merritt (1970). Specification and Uses of Econometric Models. London: Macmillan. ISBN 0-333-07411-4. Desai, Meghnad (1976). Applied Econometrics. New York: McGraw-Hill. pp. 233–268. ISBN 0-07-016541-6. Epstein, Roy J. (1987). "The Emergence of Structural Estimation". A History of Econometrics. Amsterdam: Elsevier. pp. 47–78. ISBN 0-444-70267-9. Malgrange, Pierre; Muet, Pierre-Alain, eds. (1984). Contemporary Macroeconomic Modelling. Oxford: Blackwell. ISBN 0-631-13471-9. Naylor, Thomas H.; Boughton, James M. (1971). Computer Simulation Experiments with Models of Economic Systems. New York: Wiley. pp. 126–152. ISBN 0-471-63070-5. Wynn, R. F.; Holden, K. (1974). An Introduction to Applied Econometric Analysis. London: Macmillan. pp. 105–175. ISBN 0-333-16711-2.

Worked examples

Example 1 — a first encounter with Large-scale macroeconometric model

Start with the simplest possible case. Write down what Large-scale macroeconometric model claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In 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 Large-scale macroeconometric model 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 Large-scale macroeconometric model 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 Large-scale macroeconometric model

In research
Large-scale macroeconometric model appears in 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 Large-scale macroeconometric model 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
Large-scale macroeconometric model is common in secondary-school and first-year university syllabi. It links to neighbouring topics Econometric models, Macroeconomic forecasting, so understanding it makes those chapters shorter.
In everyday life
Look for Large-scale macroeconometric model 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 Large-scale macroeconometric model in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Large-scale macroeconometric model 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 Large-scale macroeconometric model out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Large-scale macroeconometric model in simple terms?

Following the development of Keynesian economics, applied economics began developing forecasting models based on economic data including national income and product accounting data. In contrast with typical textbook models, these large-scale macroeconometric models used large amounts of data and ba…

Why does Large-scale macroeconometric model matter?

Because it connects several 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 Large-scale macroeconometric model?

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 Large-scale macroeconometric model.

Tags

  • Econometric models
  • Macroeconomic forecasting

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