Your friend gives you the data from a day of taco sales at each of the 40 food trucks, and asks you to estimate a demand curve. They let each taco truck driver set their own price, so there's lots of variance in prices. Qi =B0 +B1 Pi +ui j=1to40. You look at the data and discover that the correlation of Q and P is positive in this sample. Your friend laughs at you, --they learned in high school that demand curves slope downwards Explain how a positive correlation of Q and P might happen, by describing at least one real life omitted variable that might result in a positive correlation, and using the terms linear causal effect and the omitted variable bias formula

Microeconomic Theory
12th Edition
ISBN:9781337517942
Author:NICHOLSON
Publisher:NICHOLSON
Chapter3: Preferences And Utility
Section: Chapter Questions
Problem 3.12P
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Your friend gives you the data from a day of taco sales at each of the 40 food trucks, and asks you to
estimate a demand curve. They let each taco truck driver set their own price, so there's lots of variance
in prices.
Qi =B0 +B1 Pi +ui i=1to40.
You look at the data and discover that the correlation of Q and P is positive in this sample. Your friend
laughs at you, --they learned in high school that demand curves slope downwards
Explain how a positive correlation of Q and P might happen, by describing at least one real life omitted
variable that might result in a positive correlation, and using the terms linear causal effect and the
omitted variable bias formula.
Transcribed Image Text:Your friend gives you the data from a day of taco sales at each of the 40 food trucks, and asks you to estimate a demand curve. They let each taco truck driver set their own price, so there's lots of variance in prices. Qi =B0 +B1 Pi +ui i=1to40. You look at the data and discover that the correlation of Q and P is positive in this sample. Your friend laughs at you, --they learned in high school that demand curves slope downwards Explain how a positive correlation of Q and P might happen, by describing at least one real life omitted variable that might result in a positive correlation, and using the terms linear causal effect and the omitted variable bias formula.
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