Major Approaches to Economic Forecasting

Major Approaches to Economic Forecasting

Economic forecasting typically falls under one of three distinct approaches:

  1. Econometric modeling.
  2. Economic indicators.
  3. Checklists.

Econometric Modeling

Econometric modeling is the use of statistical methods to map out relationships among economic variables. Models may range from simple to extensive and complex systems with hundreds of formulas. Modelers use economic variables such as interest rates, commodity prices, exchange rates, etc. The models will then produce the forecasts they were designed to calculate, including GDP or asset prices.

Strengths of Econometric Modeling

  • Models can be quite robust.
  • Many factors can be included.
  • Data may be collected and consistently used within models to quickly generate output.
  • Models deliver quantitative estimates of the impact of changes in exogenous variables.
  • The modeling process imposes discipline and consistency in analysis.

Weaknesses of Econometric Modeling

  • Models can be complex and time-consuming to formulate.
  • Inputs are not easy to forecast.
  • The relationship among variables may not be static.
  • Models may be misspecified.
  • A false sense of precision may arise.
  • Econometric modeling rarely forecasts turning points well.

Economic Indicators

These are economic statistics released by official agencies and/or private organizations. These indicators contain information on an economy’s recent activity or its current or future position in the business cycle. Analysts look at leading economic indicators since they have economy-related predictive powers. It’s noteworthy that a leading economic indicator is designed to move ahead of the business cycle. A diffusion index, which measures multiple indicators at a time, may be used to gain a broader perspective on the timing of the business cycle. Examples of some common leading economic indicators include:

  1. The yield curve.
  2. The consumer confidence index.
  3. Weekly jobless claims.

Strengths of Econometric Indicators

  • Generally intuitive and easy to construct.
  • Focus primarily on identifying turning points.
  • May be available from third parties, which makes them easy to track.

Weaknesses of Econometric Indicators

  • Subject to frequent revision.
  • Current data is unreliable since historical analysis input can provide false signals.
  • May provide little more than binary directional guidance.


To assess the overall economy, forecasters may consider a wide range of economic data. Checklists can include whatever important variables the forecasters deem worthy. They do not always take a standard form.

Strengths of Checklists

  • Limited complexity.
  • Flexible.
  • Structural changes can easily be incorporated.
  • Items can easily be added or dropped.
  • They can draw on any information from any source as desired.
  • Scope: Can include virtually any topics, perspectives, theories, or assumptions.

Weaknesses of Checklists

  • Subjective.
  • Arbitrary.
  • Judgmental.
  • Time-consuming.
  • The manual process limits the depth of analysis.
  • There is no precise mechanism for combining disparate information.
  • Impose no consistency of analysis across items or different points in time.
  • It may allow biased and inconsistent views, theories, or assumptions.


Which of the three approaches listed previously is most likely subject to misspecification (bias)?

  1. Checlikists.
  2. Economic indicators.
  3. Econometric modeling.


The correct answer is C.

As econometric modeling relies on building a model, it is most likely subject to misspecification. Since econometric modeling allows for the most precision out of all approaches, if its process (calculation methodology) is biased, it will continue producing biased results as output.


A and B are incorrect. In contrast, economic indicators and the checklist approach tend to lead to binary output or more simplistic results such as ‘growing vs. shrinking’ or ‘improving vs. deteriorating’ without always specifying precise numbers, as might be the case with econometric modeling.

Reading 1: Capital Market Expectations – Part 1 (Framework and Macro Considerations)

Los 1 (e) Compare major approaches to economic forecasting


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