value_decom {dfvad}

Decomposing Value Added Growth into Explanatory Factors

Description

This method for decomposing nominal value added growth is proposed by Diewert and Fox (2018), which identifies the contributions from efficiency change, growth of primary inputs, changes in output and input prices, technical progress and returns to scale.

Usage

value_decom(x, w, y, p, t, data)

Arguments

x

A string (or a vector of strings) indicating the quantity columns.

w

A string (or a vector of strings) indicating the input price columns.

y

A string (or a vector of strings) indicating the the output quantity columns.

p

A string (or a vector of strings) indicating the the output price columns.

t

A string indicating the time period column.

data

A data frame containing input prices, input quantities, output prices, output quantities, and the time period.

Value

A list containing a growth-value table and a level-value table of explanatory factors for value added growth decomposition. It is sorted by the time period.

References

Diewert, W. E. and Fox, K. J. (2018). Decomposing value added growth into explanatory factors. In The Oxford Handbook of Productivity Analysis, chapter 19, page 625–662. Oxford University Press: New York.

Examples

# Use the built-in dataset "mining"
table1 <- value_decom(c("h2","x2"), c("w2","u2"), "y2", "p2", "year", mining)[[1]]
table2 <- value_decom(c("h2","x2"), c("w2","u2"), "y2", "p2", "year", mining)[[2]]