Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies

By M. Farsi, Massimo Filippini, William H. Greene. 2004

177 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/e64870f15bb1ee5b8a5e8e7b16787687d1a7d35c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Massimo Filippini
2. J. Zorić
3. L. Hunt
4. Mark Armstrong
5. Dennis Hilgers
6. Hannes W. Lampe
7. D. E. Sappington
8. S. Daidone

In Management Science and Operations Research

1. Mark Armstrong
2. D. E. Sappington
3. Dennis Hilgers
4. Hannes W. Lampe
5. L. Hunt
6. Massimo Filippini
7. S. Daidone
8. Federico Belotti

In Strategy and Management

1. L. Hunt
2. Dennis Hilgers
3. Hannes W. Lampe
4. Mark Armstrong
5. Massimo Filippini
6. D. E. Sappington
7. J. Zorić
8. N. Hrovatin

Citations in the corpus

• Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods (2008, background): “and Pollitt (2003), Farsi et al. (2005a) , Farsi and Filippini (2006).”
• Persistent and transient productive inefficiency: a maximum simulated likelihood approach (2015, unknown): “Some studies utilize several SFAs for panel data and compare the ranking and the values of the estimated indicators of efficiency (e.g., Farsi et al. 2005b; Abdulai and Tietje 2007; Baranzini and Faust 2014).”
• Application of Panel Data Models in Benchmarking Analysis of the Electricity Distribution Sector (2006, unknown): “16 See also Greene (2002b) and Battese and Coelli (1992).”
• US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach (2012, methodology): “As discussed in Farsi et al. (2005b) all these approaches (PM, REM and TREM) can suffer from the ‘unobserved variables bias’, because the unobserved characteristics may not be distributed independently of the explanatory variables.19 In order to address this econometric problem, this study follows…”
• Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach (2011, methodology): “For a successful application of these models in network industries, see Farsi, et al. (2005) and Farsi, et al. (2006).”
• Regulation, Competition and Liberalization (2005, background): “It is important to emphasize at the outset that the discussion in both this section and the next 79 See Shleifer (1985), Sobel (1999), Carrington et al. (2002), and Farsi et al. (2005), for example.”
• Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA (2015, methodology): “…/ 40.25 / 15.32) Examining several approaches on data from: The World Health Organization (Greene, 2004) U.S. banking industry (Greene, 2005b; Greene, 2005c) Swiss railway companies (Farsi et al., 2005) Regional bus companies (Farsi et al., 2006) 64 (24.62) 66 (25.38) 93 (35.77) 17 (6.54) 20 (7.69)”
• Stochastic Frontier Analysis using Stata (2013, methodology): “A detailed description of the Swiss railway transport system and complete information on the variables used are available in Farsi, Filippini, and Greene (2005).”