Presentation on theme: "Market for Lemons A market full of “lemons” or unreliable products may result from differences in information on product quality between buyer and seller."— Presentation transcript:
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: a.the model year of truck b.whether the truck belongs to original purchaser or was acquired used c.truck’s mileage d.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: a.1974 model year trucks b.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: a.Directly estimates maintenance costs b.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: a.Those that had been purchased (used) within one year of the 1977 survey. b.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.