G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/w20604
来源IDWorking Paper 20604
Why You Can't Find a Taxi in the Rain and Other Labor Supply Lessons from Cab Drivers
Henry S. Farber
发表日期2014-10-20
出版年2014
语种英语
摘要In a seminal paper, Camerer, Babcock, Loewenstein, and Thaler (1997) find that the wage elasticity of daily hours of work New York City (NYC) taxi drivers is negative and conclude that their labor supply behavior is consistent with target earning (having reference dependent preferences). I replicate and extend the CBLT analysis using data from all trips taken in all taxi cabs in NYC for the five years from 2009-2013. The overall pattern in my data is clear: drivers tend to respond positively to unanticipated as well as anticipated increases in earnings opportunities. This is consistent with the neoclassical optimizing model of labor supply and does not support the reference dependent preferences model.
主题Microeconomics ; Behavioral Economics ; Labor Economics ; Labor Supply and Demand
URLhttps://www.nber.org/papers/w20604
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/578278
推荐引用方式
GB/T 7714
Henry S. Farber. Why You Can't Find a Taxi in the Rain and Other Labor Supply Lessons from Cab Drivers. 2014.
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