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Modeling Price Elasticity. Kiran Ravulapati, Katia Frank, Wassim Chaar Delta Technology, Atlanta, GA 30354. What is Price Elasticity ?. Price Elasticity (PE) A PE of -1.5 means there is a 1.5% drop in demand for a 1% increase in price. Price Elasticity - Literature.

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modeling price elasticity

Modeling Price Elasticity

Kiran Ravulapati, Katia Frank, Wassim Chaar

Delta Technology, Atlanta, GA 30354

what is price elasticity
What is Price Elasticity ?
  • Price Elasticity (PE)
  • A PE of -1.5 means there is a 1.5% drop in demand for a 1% increase in price.
price elasticity literature
Price Elasticity - Literature
  • Past research modeled price elasticity at a macro level using aggregated, high level data.

- Oum, Tae H., Zhang, Anmin and Zhang, Yimin (1993) “Inter-Firm Rivalry and Firm-Specific Price elasticities in Deregulated Airline Markets,” Journal of Transport Economics and Policy,27, 171-192

  • Price elasticity at product level received little attention. Perhaps, this is because of the revenue management effects involved.
price elasticity assumptions
Price Elasticity - Assumptions
  • We modeled simple price elasticity only. Interaction between products is not considered.
  • We studied the ‘vacuum’ scenario i.e., all airlines in the market have same prices.
  • Revenue management effects are consistent.
price elasticity vacuum

Bookings for market XXX-YYY

Discounted Coach

demand

0-10

30-40

60-70

90-100

120-130

150-160

180-190

210-220

240-250

270-280

300-310

330-340

360-370

390-400

420-430

fareband

Price Elasticity - “Vacuum”

Step 1: Divide historical demand/price data into fare bands.

price elasticity vacuum1
Price Elasticity - “Vacuum”

Step 2: Remove RM effect by cumulating demand.

Bookings for market XXX-YYY

Discounted Coach

Cumulative Demand

0-10

30-40

60-70

90-100

120-130

150-160

180-190

210-220

240-250

270-280

300-310

330-340

360-370

390-400

420-430

fareband

price elasticity vacuum2
Price Elasticity - “Vacuum”

Step 3: Adjust the curve for sell up.

Bookings for market XXX-YYY

Discounted Coach

Cumulative Demand

Adjusted Cumulative Demand

0-10

30-40

60-70

90-100

120-130

150-160

180-190

210-220

240-250

270-280

300-310

330-340

360-370

390-400

420-430

fareband

price elasticity sell up
Price Elasticity - Sell Up

Total Demand = 16 + 50 + 30 = 96

Demand

20

50

30

$50-$70

$70-$90

$90-$110

0.8*20 = 16

30

price elasticity vacuum3
Price Elasticity - “Vacuum”

Step 4: Fit a function to the adjusted demand curve using regression analysis and calculate price elasticity.

Price Vs Demand Curve for market XXX-YYY

Discounted Coach

Demand

0-10

30-40

60-70

90-100

120-130

150-160

180-190

210-220

240-250

270-280

300-310

330-340

360-370

390-400

420-430

fareband

price elasticity summary
Price Elasticity - Summary
  • This model is a first step towards developing a methodology for price elasticity.
  • Select a representative sample of historical data.
  • Group only similar markets/products for this analysis.
  • To capture seasonal changes in prices, this analysis should be repeated for each season using new data.
price elasticity summary1
Price Elasticity - Summary
  • Revenue management effects, spill and capacity limits, should be used to determine the impact of fare increase/decrease.
  • Methodology can be used at various aggregate levels - market/region/airline/products.
  • Possible extensions

- Impact of fare rules

- Interaction between substitutable products