swissrailways: Data on Swiss railways
In sfaR: Stochastic Frontier Analysis using R
swissrailways R Documentation
Data on Swiss railways
Description
This dataset is an unbalanced panel of 50 Swiss railway companies over the period 1985-1997.
Usage
swissrailways
Format
A data frame with 605 observations on the following 42 variables.
- ID
Firm identification.
- YEAR
Year identification.
- NI
Number of years observed.
- STOPS
Number of stops in network.
- NETWORK
Network length (in meters).
- NARROW_T
Dummy variable for railroads with narrow track.
- RACK
Dummy variable for ‘rack rail’ in network.
- TUNNEL
Dummy variable for network with tunnels over 300 meters on average.
- T
Time indicator, first year = 0.
- Q2
Passenger output – passenger km.
- Q3
Freight output – ton km.
- CT
Total cost (1,000 Swiss franc).
- PL
Labor price.
- PE
Electricity price.
- PK
Capital price.
- VIRAGE
1 for railroads with curvy tracks.
- LNCT
Log of CT/PE.
- LNQ2
Log of Q2.
- LNQ3
Log of Q3.
- LNNET
Log of NETWORK/1000.
- LNPL
Log of PL/PE.
- LNPE
Log of PE.
- LNPK
Log of PK/PE.
- LNSTOP
Log of STOPS.
- MLNQ2
Mean of LNQ2.
- MLNQ3
Mean of LNQ3.
- MLNNET
Mean of LNNET.
- MLNPL
Mean of LNPL.
- MLNPK
Mean of LNPK.
- MLNSTOP
Mean of LNSTOP.
Details
The dataset is extracted from the annual reports of the Swiss Federal Office of Statistics
on public transport companies and has been used in Farsi et al. (2005).
Source
http://pages.stern.nyu.edu/~wgreene/Text/Edition7/tablelist8new.htm
http://people.stern.nyu.edu/wgreene/Microeconometrics.htm
References
Farsi, M., M. Filippini, and W. Greene. 2005. Efficiency measurement in network industries: Application to the Swiss railway companies. Journal of Regulatory Economics, 28:69–90.
Examples
str(swissrailways)
sfaR documentation built on May 3, 2022, 3 p.m.
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| swissrailways | R Documentation |
Data on Swiss railways
Description
This dataset is an unbalanced panel of 50 Swiss railway companies over the period 1985-1997.
Usage
swissrailways
Format
A data frame with 605 observations on the following 42 variables.
- ID
Firm identification.
- YEAR
Year identification.
- NI
Number of years observed.
- STOPS
Number of stops in network.
- NETWORK
Network length (in meters).
- NARROW_T
Dummy variable for railroads with narrow track.
- RACK
Dummy variable for ‘rack rail’ in network.
- TUNNEL
Dummy variable for network with tunnels over 300 meters on average.
- T
Time indicator, first year = 0.
- Q2
Passenger output – passenger km.
- Q3
Freight output – ton km.
- CT
Total cost (1,000 Swiss franc).
- PL
Labor price.
- PE
Electricity price.
- PK
Capital price.
- VIRAGE
1 for railroads with curvy tracks.
- LNCT
Log of
CT/PE.- LNQ2
Log of
Q2.- LNQ3
Log of
Q3.- LNNET
Log of
NETWORK/1000.- LNPL
Log of
PL/PE.- LNPE
Log of
PE.- LNPK
Log of
PK/PE.- LNSTOP
Log of
STOPS.- MLNQ2
Mean of
LNQ2.- MLNQ3
Mean of
LNQ3.- MLNNET
Mean of
LNNET.- MLNPL
Mean of
LNPL.- MLNPK
Mean of
LNPK.- MLNSTOP
Mean of
LNSTOP.
Details
The dataset is extracted from the annual reports of the Swiss Federal Office of Statistics on public transport companies and has been used in Farsi et al. (2005).
Source
http://pages.stern.nyu.edu/~wgreene/Text/Edition7/tablelist8new.htm
http://people.stern.nyu.edu/wgreene/Microeconometrics.htm
References
Farsi, M., M. Filippini, and W. Greene. 2005. Efficiency measurement in network industries: Application to the Swiss railway companies. Journal of Regulatory Economics, 28:69–90.
Examples
str(swissrailways)
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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