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Market for Lemons. A market full of “lemons” or unreliable products may result from differences in information on product quality between buyer and seller. Buyers may base demand for a good such as a used vehicle on the average quality of the good in the market.
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Market for Lemons • A market full of “lemons” or unreliable products may result from differences in information on product quality between buyer and seller. • Buyers may base demand for a good such as a used vehicle on the average quality of the good in the market. • May drive out of the market the supply of good vehicles – further decreasing the quality of vehicles on the market.
A Direct Test of the “Lemons” Model • This paper directly tests the idea that used vehicles (trucks) differ in quality from the market for new vehicles. • Quality measured by the (lack of) maintenance on a vehicle. • Data for the study taken from a 1977 survey of truck owners that records: • the model year of truck • whether the truck belongs to original purchaser or was acquired used • truck’s mileage • whether the truck required major maintenance in the preceding 12 months
A Direct Test of the “Lemons” Model • Data indicates whether any maintenance was undertaken in any of five categories (engine, transmission, brakes, rear axle, and other). • Data doesn’t provide information on actual cost of maintenance. • The implication of the “lemons” model is that used trucks would on average be lower quality. • Need more maintenance than trucks purchased new.
A Direct Test of the “Lemons” Model • Paper initially presents evidence only for engine maintenance. • In three of the years, a higher proportion of used trucks required engine maintenance than new.
A Direct Test of the “Lemons” Model • Simple comparison of sample proportions is a crude test of “lemons” hypothesis. • Used trucks for every model had on average much more mileage than trucks owned by original purchasers. • Vehicles with more mileage would normally require more maintenance.
A Direct Test of the “Lemons” Model • Paper groups trucks by model year and mileage range. • Compares the proportion of each group requiring maintenance in each of the five maintenance categories. • Tests for statistical significance of difference in proportions.
A Direct Test of the “Lemons” Model • An example of a grouping: • 1974 model year trucks • With between 40,000 and 50,000 miles • Compares proportion of the new and used trucks that required a specific maintenance (engine, transmission, brakes, rear axle, and other). • Paper makes up to four comparisons for each grouping.
A Direct Test of the “Lemons” Model • Tests for statistical significance. • The difference in sample proportions must be large in order to conclude that a relationship holds generally for all trucks. • Hypothesis is that used trucks with fewer miles will more likely be relative “lemons” than those with more miles.
A Direct Test of the “Lemons” Model • Paper finds that in most cases, used trucks are not inferior to new. • Concludes little evidence of “lemons” in the market for trucks.
Test of the Lemons Model: Comment • This paper argues previous paper used incorrect methodology to test lemons model. • Using same data, paper finds evidence of lemons by making two changes in methodology: • Directly estimates maintenance costs • Groups trucks by distinguishing between relatively new owners and those who are not.
Test of the Lemons Model: Comment • Paper converts maintenance data into dollar costs by using information on average costs by category (in 1977):
Test of the Lemons Model: Comment • Separates trucks into: • Those that had been purchased (used) within one year of the 1977 survey. • Those that been acquired either used or new in previous period and kept by owner. No transaction had taken place within a year of the 1977 survey for those trucks. • Hypothesizes that recently transacted trucks in the used market are more likely to be lemons. • Owners who have held on to their vehicles are discouraged from selling because of the lemons problem.
Test of the Lemons Model: Comment • Finds that trucks that have been transacted in a given time period have significantly higher average maintenance costs. • The difference in means is statistically significant and is evidence of a “lemons” problem in the market.
