# Demand Estimation and Forecasting

Pages: 14 (2594 words) Published: September 12, 2013

Demand Estimation

Demand Curve Estimation

■ Simple Linear Demand Curves

■ The best estimation method balances marginal costs and marginal benefits.

■ Simple linear relations are useful for demand estimation.

■ Using Simple Linear Demand Curves

■ Straight-line relations give useful approximations.

Identification Problem

■ Changing Nature of Demand Relations

■ Demand relations are dynamic.

■ Interplay of Supply and Demand

■ Economic conditions affect demand and supply.

■ Shifts in Demand and Supply

■ Curve shifts can be estimated.

Simultaneous Relations

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Interview and Experimental Methods

■ Consumer Interviews

■ Interviews can solicit useful information when market data is scarce.

■ Interview opinions often differ from actual market transaction data.

■ Market Experiments

■ Controlled experiments can generate useful insight.

Experiments can become expensive

Regression Analysis

■ What Is a Statistical Relation?

■ A statistical relation exists when averages are related.

■ A deterministic relation is true by definition.

■ Specifying the Regression Model

■ Dependent variable Y is caused by X.

■ X variables are independently determined from Y.

■ Least Squares Method

■ Minimize sum of squared residuals.

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Measuring Regression Model Significance

■ Standard Error of the Estimate SEE) increases with scatter about the regression line.

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Goodness of Fit, r and R2

■ r = 1 means perfect correlation; r = 0 means no correlation.

■ R2 = 1 means perfect fit; R2 = 0 means no relation.

■ Corrected Coefficient of Determination, R2

Adjusts R2 downward for small samples

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F statistic

Tells if R2 is statistically significant

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Measures of Individual Variable Significance

t statistics

■ t statistics compare a sample characteristic to the standard deviation of that characteristic.

■ A calculated t statistic more than two suggests a strong effect of X on Y (95 % confidence).

■ A calculated t statistic more than three suggests a very strong effect of X on Y (99 % confidence).

■ Two-tail t Tests

■ Tests of effect.

■ One-Tail t Tests

■ Tests of magnitude or direction.

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Forecasting

Forecasting Application

■ Macroeconomic Applications

■ Predictions of economic activity at the national or international level.

■ Microeconomic Applications

■ Predictions of company and industry performance.

■ Forecast Techniques

■ Qualitative analysis.

■ Trend analysis and projection.

■ Exponential smoothing.

■ Econometric methods.

Qualitative Analysis

■ Expert Opinion

■ Informed personal insight is always useful.

■ Panel consensus reconciles different views.

■ Delphi method seeks informed consensus.

■ Survey Techniques

■ Random samples give population profile.

■ Stratified samples give detailed profiles of population segments.

Trend Analysis and Projection

■ Trends in Economic Data

■ Secular trends reflect growth and decline.

■ Cyclical fluctuations show rhythmic variation.

■ Seasonal variation (weather, custom).

Random influences are unpredictable

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Linear Trend Analysis

■ Growth Trend Analysis

■ Linear and Growth Trend Comparison

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■ What Is the Business Cycle?

■ Rhythmic pattern of economic expansion and contraction.

■ Economic Indicators

■ Useful leading, coincident and lagging...