| fish | R Documentation |
Wooldridge Source: K Graddy (1995), “Testing for Imperfect Competition at the Fulton Fish Market,” RAND Journal of Economics 26, 75-92. Professor Graddy's collaborator on a later paper, Professor Joshua Angrist at MIT, kindly provided me with these data. Data loads lazily.
data('fish')
A data.frame with 97 observations on 20 variables:
prca: price for Asian buyers
prcw: price for white buyers
qtya: quantity sold to Asians
qtyw: quantity sold to whites
mon: =1 if Monday
tues: =1 if Tuesday
wed: =1 if Wednesday
thurs: =1 if Thursday
speed2: min past 2 days wind speeds
wave2: avg max last 2 days wave height
speed3: 3 day lagged max windspeed
wave3: avg max wave hghts of 3 & 4 day lagged hghts
avgprc: ((prca*qtya) + (prcw*qtyw))/(qtya + qtyw)
totqty: qtya + qtyw
lavgprc: log(avgprc)
ltotqty: log(totqty)
t: time trend
lavgp_1: lavgprc[_n-1]
gavgprc: lavgprc - lavgp_1
gavgp_1: gavgprc[_n-1]
This is a nice example of how to go about finding exogenous variables to use as instrumental variables. Often, weather conditions can be assumed to affect supply while having a negligible effect on demand. If so, the weather variables are valid instrumental variables for price in the demand equation. It is a simple matter to test whether prices vary with weather conditions by estimating the reduced form for price.
Used in Text: pages 443, 580
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
str(fish)