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Productivity Growth in Passenger-Bus Transportation: A Heteroskedastic Error Component Model with Unbalanced Panel Data

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  • Kumbhakar, Subal C
  • Bhattacharyya, Arunava

Abstract

This paper considers an econometric approach to measure total factor productivity (TFP) growth and technical change (TC) for 31 publicly owned passenger-bus companies in India during 1983-1987. A translog variable cost function is used to represent the production technology. Firm heterogeneity is incorporated in the cost function using an error component model with firm-specific variances. TFP growth is decomposed into TC and economies of scale components. The TC component is further decomposed into pure, non-neutral, scale, and quasi-fixed factors/network components. An ownership group-wise comparison reveals that the public undertakings exhibit the highest rate of productivity growth, followed by the units operated by the state and local governments. The main source of TFP growth for the public undertakings and government operated units is economies of scale, while the main source of falling TFP growth for corporations is technological regress.

Suggested Citation

  • Kumbhakar, Subal C & Bhattacharyya, Arunava, 1996. "Productivity Growth in Passenger-Bus Transportation: A Heteroskedastic Error Component Model with Unbalanced Panel Data," Empirical Economics, Springer, vol. 21(4), pages 557-573.
  • Handle: RePEc:spr:empeco:v:21:y:1996:i:4:p:557-73
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    Cited by:

    1. Yves Croissant & William Roy & Joan Canton, 2013. "Reducing urban public transport costs by tendering lots: a panel data estimation," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3711-3722, September.
    2. Cubukcu, K. Mert, 2008. "Examining the cost structure of urban bus transit industry: does urban geography help?," Journal of Transport Geography, Elsevier, vol. 16(4), pages 278-291.
    3. Tsionas, Efthymios G. & Baltas, Nicholas C. & Chionis, Dionysios P., 2011. "Rail infrastructure charging in Hellenic railways," Journal of Policy Modeling, Elsevier, vol. 33(3), pages 370-380, May.
    4. Obeng, K. & Sakano, R. & Naanwaab, C., 2016. "Understanding overall output efficiency in public transit systems: The roles of input regulations, perceived budget and input subsidies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 133-150.
    5. Loizides, John & Tsionas, Efthymios G., 2002. "Productivity growth in European railways: a new approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(7), pages 633-644, August.
    6. Wonchul Kim & Sung Hyo Hong, 2021. "The Effect of COVID-19 on the Efficiency of Intercity Bus Operation: The Case of Chungnam," Sustainability, MDPI, vol. 13(11), pages 1-11, May.
    7. Anand Venkatesh & Shivam Kushwaha, 2017. "Measuring technical efficiency of passenger bus companies in India: a non-radial data envelopment analysis approach," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 706-723, December.
    8. Estache, Antonio & Kouassi, Eugene, 2002. "Sector organization, governance, and the inefficiency of African water utilities," Policy Research Working Paper Series 2890, The World Bank.
    9. Ganji, S.S. & Dehghani, Alireza & Ajirlu, Shahrouz Fathi, 2024. "Evaluation of intercity road passenger transportation using a novel double-frontier game-regret-cross-efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).

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