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.
■ 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.
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
■ 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.
Measuring Regression Model Significance
■ Standard Error of the Estimate SEE) increases with scatter about the regression line.
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
Tells if R2 is statistically significant
Measures of Individual Variable Significance
■ 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.
■ 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.
■ 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
Linear Trend Analysis
■ Growth Trend Analysis
■ Linear and Growth Trend Comparison
■ What Is the Business Cycle?
■ Rhythmic pattern of economic expansion and contraction.
■ Economic Indicators
■ Useful leading, coincident and lagging...
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