1. 9. Valuing Impacts from Observed Behavior: Direct
Reading:
BGVW, Chapters 13

2. 1. Introduction
Need to measure social surplus. These are found as areas under demand and supply curves. Triangles, trapezoids and so forth.
Curves are usually unknown, so analyst need to find ways to estimate them the curves and, in turn, calculate the triangles.
Well look at some direct estimation techniques and then some indirect ways to measure shadow values -- infer values indirectly from other markets and behaviors.

3. 2. Direct Estimation One point plus slope or elasticity.
Usually know one point (current price & quantity).
If slope is also known (literature on demand for the good you are interested in studying), then it is a simple matter to extrapolate the demand curve.
in the basic demand equation below, for example, may be estimated from various studies
price
quantity
slope

4. If so, it is a simple matter to sketch out the shape of the curve around this point.
price p0
quantity q0

5. If so, it is a simple matter to sketch out the shape of the curve around this point.
price p0
quantity q0

6. Or, may just use the demand equation
Or, may just use the demand equation. Plug in current p and q to get intercept Then you have an estimate of the equation.

7. Refuse fee example from book
Refuse fee example from book. Current price is zero, town plans to raise fee to $.05 per pound.
Graph:
Social cost is $.06
initial zero price point
Robin Jenkins. The Economics of Solid Waste Reduction: The Impact of User Fees lb/p/d
Note: Validity.

8. Elasticities and linear demand
Elasticities and linear demand. If you know demand is linear and you have an elasticity measure instead of a slope, you can calculate the slope as
You need to know price at which elasticity was calculated in the original study.
Same basic strategy can be followed for constant elasticity demand curves
Discuss example in book (p. 324)

11. Extrapolating from a few points.
You know a few points of p,q from historic data and you try to “fit ” a line through these points. Usually 2 or 3 points.
Example from book
Known data points

12. Notes sensitivity to functional form controlling for other factors
validity of measures from only 2 points
Extrapolating beyond ‘relevant range’

13. Many Points/Econometrics
Suppose you have many observations of price and quantity from a time series or cross sectional data set.
price
quantity

14. Regress q on p, or fit a line to this scatter of points
Regress q on p, or fit a line to this scatter of points. You’d have something like the red linear regression or blue non-linear regression
price
quantity

15. Use the estimated line in your analysis Types of data
individual vs. aggregate
time series (annual/monthly) vs. cross sectional
examples: electricity, farm crops, water, consumer goods galore, automobiles, oil, minerals markets, traffic, computers, wine ……
Major econometric issues
(1) Omitted variable bias
(2) Autocorrelation in time series data

16. (3) Identification Problem: Are you estmating a deamnd curve or a supply curve when you estimate the relationship between p and q?
The ideal case. (Rain example. Cross sectional stories.) Shifting supply is sketching out a demand curve.
Stable demand curve
Shifting supply curves
price
quantity

17. (3) Identification Problem: Are you estmating a deamnd curve or a supply curve when you estimate the relationship between p and q?
The ideal case. (Rain example. Cross sectional stories.) Shifting supply is sketching out a demand curve.
Stable demand curve
Shifting supply curve
price
quantity
Observations

18. But it could have been supply that was sketched out
price
quantity

19. Simultaneous equations/instrumental variables
Trouble and likely outcome is that you observe price and quantity relationships that get both shifts.
Simultaneous equations/instrumental variables
price
quanity