faremalm2 {nonparaeff}
Description
Calculate productivity growth index under the DEA framework.
Usage
faremalm2(dat = NULL, noutput = 1, id = "id", year = "year")
Arguments
- dat
- A data frame to be evaluated. The format of this data frame is data.frame(id, year, outputs, inputs). This data frame should have a balanced panel data form.
- noutput
- The number of outputs.
- id
- A column name for the producer index.
- year
- A column name for the time index.
Details
The Malmquist productivity growth index is calculated. For model specification, take a look at Fare et al. (1994).
Values
A data frame with ( id: the id index of the original data. time: the time index of the original data. y's: original outputs x's: original inputs Dt2t2: D^{t+1} (x^{t+1}, y^{t+1}) Dtt2: D^{t} (x^{t+1}, y^{t+1}) Dt2t: D^{t+1} (x^t, y^t) ec: efficiency change tc: technical change pc: productivity change
References
Cooper, W., Seiford, L. and Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer Verlag, New York.
Fare, R., Grosskopf, S., Norris, M. and Zhang, Z. (1994). Productivity growth, technical progress and efficiency change in industrialized countries. American Economic Review, 84(1):66-83.
Lee, J. and Oh, D. (forthcoming). Efficiency Analysis: Data Envelopment Analysis. Press (in Korean).
See Also
dea
Examples
malm.dat <- data.frame(id = rep(LETTERS[1:3], 3), time = rep(1:3, each = 3), y = c(1, 2, 2, 3, 2, 8, 3, 2, 5), x = c(2, 3, 7, 3, 5, 6, 8, 9, 6)) malm.re1 <- faremalm2(malm.dat, noutput = 1, id = "id", year = "time") ## Malmquist productivity growth index of OECD countries library(pwt) ## Use Penn World Table my.dat <- pwt5.6 head(my.dat) my.oecd.ctry <- c("AUS", "AUT", "BEL", "CAN", "CHE", "DNK", "ESP", "FIN", "FRA", "GBR", "GER", "GRC", "IRL", "ISL", "ITA", "JPN", "KOR", "LUX", "MEX", "NLD", "NOR", "NZL", "PRT", "SWE", "TUR", "USA", "DEU") my.dat <- my.dat[my.dat$wbcode %in% my.oecd.ctry,] my.dat <- my.dat[my.dat$year %in% 1980:1990,] my.dat$rgdpl <- as.numeric(my.dat$rgdpl) ## GDP per capita my.dat$pop <- as.numeric(my.dat$pop) ## total population (1000) my.dat$rgdpwok <- as.numeric(my.dat$rgdpwok) ## GDP per labor my.dat$kapw <- as.numeric(my.dat$kapw) ## Capital stock per labor my.dat$gdp <- my.dat$rgdpl * my.dat$pop ## Total GDP of a country my.dat$labor <- with(my.dat, gdp/rgdpwok) ## Total labor force my.dat$capital <- with(my.dat, kapw * labor) ## Toal capital stock oecd <- my.dat[, c("wbcode", "year", "gdp", "labor", "capital")] re.oecd <- faremalm2(dat = oecd, noutput = 1, id = "wbcode", year = "year") ## productivity growth for each country pc.c <- tapply(re.oecd$pc, re.oecd$wbcode, geometric.mean) ## a trend of productivity growth of OECD countries pc.y <- tapply(re.oecd$pc, re.oecd$year, geometric.mean) ## efficiency change for each country ec.c <- tapply(re.oecd$ec, re.oecd$wbcode, geometric.mean) ## a trend of efficiency change of OECD countries ec.y <- tapply(re.oecd$ec, re.oecd$year, geometric.mean)
Documentation reproduced from package nonparaeff, version 0.5-8. License: GPL (>= 2)