86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
"""Grunfeld (1950) Investment Data"""
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import pandas as pd
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from statsmodels.datasets import utils as du
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__docformat__ = 'restructuredtext'
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COPYRIGHT = """This is public domain."""
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TITLE = __doc__
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SOURCE = """This is the Grunfeld (1950) Investment Data.
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The source for the data was the original 11-firm data set from Grunfeld's Ph.D.
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thesis recreated by Kleiber and Zeileis (2008) "The Grunfeld Data at 50".
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The data can be found here.
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http://statmath.wu-wien.ac.at/~zeileis/grunfeld/
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For a note on the many versions of the Grunfeld data circulating see:
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http://www.stanford.edu/~clint/bench/grunfeld.htm
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"""
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DESCRSHORT = """Grunfeld (1950) Investment Data for 11 U.S. Firms."""
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DESCRLONG = DESCRSHORT
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NOTE = """::
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Number of observations - 220 (20 years for 11 firms)
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Number of variables - 5
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Variables name definitions::
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invest - Gross investment in 1947 dollars
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value - Market value as of Dec. 31 in 1947 dollars
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capital - Stock of plant and equipment in 1947 dollars
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firm - General Motors, US Steel, General Electric, Chrysler,
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Atlantic Refining, IBM, Union Oil, Westinghouse, Goodyear,
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Diamond Match, American Steel
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year - 1935 - 1954
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Note that raw_data has firm expanded to dummy variables, since it is a
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string categorical variable.
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"""
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def load():
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"""
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Loads the Grunfeld data and returns a Dataset class.
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Returns
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-------
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Dataset
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See DATASET_PROPOSAL.txt for more information.
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Notes
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-----
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raw_data has the firm variable expanded to dummy variables for each
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firm (ie., there is no reference dummy)
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"""
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return load_pandas()
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def load_pandas():
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"""
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Loads the Grunfeld data and returns a Dataset class.
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Returns
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-------
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Dataset
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See DATASET_PROPOSAL.txt for more information.
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Notes
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-----
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raw_data has the firm variable expanded to dummy variables for each
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firm (ie., there is no reference dummy)
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"""
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data = _get_data()
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data.year = data.year.astype(float)
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raw_data = pd.get_dummies(data)
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ds = du.process_pandas(data, endog_idx=0)
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ds.raw_data = raw_data
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return ds
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def _get_data():
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data = du.load_csv(__file__, 'grunfeld.csv')
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return data
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