Description Usage Format Details Source Examples
Data from Fulton fish market collected by Graddy (1995, 2006). See also Hendry and Nielsen (2007) and Johansen and Nielsen (2014)
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Matrix with 111 rows of daily data and 13 variables.
Documentation on the Fulton Fish market and original data can be found in Graddy (1995, 2006). Documentation for aggregated data used here can be found in Angrist, Graddy and Imbens (2000). Data used as example in Hendry and Nielsen (2007). Downloaded from Econometric Modeling.
The data set comprises aggregated daily prices and quantities of whiting sold in the period 2 December 1991 to 8 May 1992. In particular it has the variables
1 if Monday, 0 otherwise.
1 if Tuesday, 0 otherwise.
1 if Wednesday, 0 otherwise.
1 if Thursday, 0 otherwise
1 if Wave hight greater than 4.5 feet Wind speed greater than 18 knots Based on moving averages of the last three days' wind speed and wave height before the trading day, as measured off the coast of Long Island and reported in the New York Times boating forecast.
1 if Wave hight greater than 3.8 feet Wind speed greater than 13 knots excluding stormy days. Based on moving averages of the last three days' wind speed and wave height before the trading day, as measured off the coast of Long Island and reported in the New York Times boating forecast.
Prices are average prices in US dollars per pound.
Quantities are pounds of whiting per day.
1 if rainy wheather on shore.
1 if cold wheather on shore.
Square of windspeed.
Angrist, J.D., Graddy, K. and Imbens, G.W. (2000) The interpretation of instrumental variables estimators in simultaneous equations models with an application to the demand for fish. Review of Economic Studies 67, 499-527.
Graddy, K. (1995) Testing for imperfect competition at the Fulton Fish Market. RAND Journal of Economics 26, 75-92.
Graddy, K. (2006) The Fulton Fish Market. Journal of Economic Perspectives 20, 207-220.
Hendry, D.F. and Nielsen, B. (2007) Econometric Modeling. Princeton University Press.
Johansen, S. and Nielsen, B. (2014) Outlier detection algorithms for least squares time series. Download: Nuffield DP.
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