General Electric and Westinghouse capital data.

data(gew)

Format

A data frame with 20 observations on the following 7 variables. All variables are numeric vectors. Variables ending in .g correspond to General Electric and those ending in .w are Westinghouse.

year

The observations are the years from 1934 to 1953

invest.g, invest.w

investment figures. These are \(I=\) Gross investment = additions to plant and equipment plus maintenance and repairs in millions of dollars deflated by \(P_1\).

capital.g, capital.w

capital stocks. These are \(C=\) The stock of plant and equipment = accumulated sum of net additions to plant and equipment deflated by \(P_1\) minus depreciation allowance deflated by \(P_3\).

value.g, value.w

market values. These are \(F=\) Value of the firm = price of common and preferred shares at December 31 (or average price of December 31 and January 31 of the following year) times number of common and preferred shares outstanding plus total book value of debt at December 31 in millions of dollars deflated by \(P_2\).

Details

These data are a subset of a table in Boot and de Wit (1960), also known as the Grunfeld data. It is used a lot in econometrics, e.g., for seemingly unrelated regressions (see SURff).

Here, \(P_1 =\) Implicit price deflator of producers durable equipment (base 1947), \(P_2 =\) Implicit price deflator of G.N.P. (base 1947), \(P_3 =\) Depreciation expense deflator = ten years moving average of wholesale price index of metals and metal products (base 1947).

Source

Table 10 of: Boot, J. C. G. and de Wit, G. M. (1960) Investment Demand: An Empirical Contribution to the Aggregation Problem. International Economic Review, 1, 3–30.

Grunfeld, Y. (1958) The Determinants of Corporate Investment. Unpublished PhD Thesis (Chicago).

See also

SURff, http://statmath.wu.ac.at/~zeileis/grunfeld (the link might now be stale).

References

Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, 57, 348–368.

Examples

str(gew)
#> 'data.frame':	20 obs. of  7 variables:
#>  $ year     : int  1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 ...
#>  $ invest.g : num  33.1 45 77.2 44.6 48.1 74.4 113 91.9 61.3 56.8 ...
#>  $ value.g  : num  1171 2016 2803 2040 2256 ...
#>  $ capital.g: num  97.8 104.4 118 156.2 172.6 ...
#>  $ invest.w : num  12.9 25.9 35 22.9 18.8 ...
#>  $ value.w  : num  192 516 729 560 520 ...
#>  $ capital.w: num  1.8 0.8 7.4 18.1 23.5 26.5 36.2 60.8 84.4 91.2 ...