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4. Estimating Demand from Market Data

Reading:➝Boardman, Chapter 4

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 we need to find ways to estimate them and, in then, calculate the triangles.

➝Here we look at some common ways of estimating demand.

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2. One Point Plus Slope or Elasticity

➝Usually know one point (current price & quantity).

➝ If you can get the slope from existing studies or using a plausible estimate and you are willing to assume linearity (impose structure), it is a simple to estimate demand

➝ Same is true if you get the elasticity. In this case you can estimate a linear or constant elasticity demand curve

➝ See next slide

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2. 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.

Known data points

➝Comments• Sensitivity to functional form• Controlling for other factors• Validity of measures from only 2 points• Extrapolating beyond ‘relevant range’

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3. Many Points Econometrics

➝Cross-Sectional or Time-Series data on p,q

price

quantity

( ; )Estimted demandq f p β=

➝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

( ; )Estimted demandq f p β=

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➝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

➥Omitted variable bias

➥Autocorrelation in time series data

( , , , )own substq f p p y d=

➥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

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» But it could have been supply that was sketched out

price

quantity

➥Trouble and likely outcome is that you observe price and quantity relationships that get both shifts.

➥Simultaneous equations/instrumental variables

price

quanity