swissrailways: Data on Swiss railway companies
In sfaR: Stochastic Frontier Analysis Routines
swissrailways R Documentation
Data on Swiss railway companies
Description
This dataset is an unbalanced panel of 50 Swiss railway companies over the
period 1985-1997.
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 July 9, 2023, 6:58 p.m.
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| swissrailways | R Documentation |
Data on Swiss railway companies
Description
This dataset is an unbalanced panel of 50 Swiss railway companies over the period 1985-1997.
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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