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Multi-dimensional interactions in the oilfield market: A jackknife model averaging approach of spatial productivity analysis

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  • Gong, Binlei

Abstract

This paper develops a methodology to assess the productivity in oilfield service companies, taking multi-dimensional interactions (e.g., regions, segments, products) into account. Firstly, various spatial models are utilized on 54 oilfield service firms to estimate the production function that separately accounts for cross-sectional dependence in business segment and geography, where the general spatial model (GSM) is found to be the most efficient. Secondly, two GSM models, one accounting for interactions in business segments and the other in geography, are combined in a Jackknife model averaging method to derive the aggregate production function of the oilfield market. Evidence of cross-sectional dependence and constant returns to scale are found, as well as positive spillover effects across firms. Moreover, the oilfield market had achieved high-speed growth in productivity since 2003, but experienced a significant crash in 2009 after the financial crisis and productivity has stagnated in recent years.

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  • Gong, Binlei, 2020. "Multi-dimensional interactions in the oilfield market: A jackknife model averaging approach of spatial productivity analysis," Energy Economics, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:eneeco:v:86:y:2020:i:c:s0140988317302992
    DOI: 10.1016/j.eneco.2017.08.032
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    as
    1. Peter R. Hartley & Kenneth B. Medlock III, 2013. "Changes in the Operational Efficiency of National Oil Companies," The Energy Journal, , vol. 34(2), pages 27-58, April.
    2. Peter Kedron & Sharmistha Bagchi-Sen, 2012. "Foreign direct investment in Europe by multinational pharmaceutical companies from India," Journal of Economic Geography, Oxford University Press, vol. 12(4), pages 809-839, July.
    3. Fallahi, Alireza & Ebrahimi, Reza & Ghaderi, S.F., 2011. "Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study," Energy, Elsevier, vol. 36(11), pages 6398-6405.
    4. Riccardo Crescenzi & Carlo Pietrobelli & Roberta Rabellotti, 2014. "Innovation drivers, value chains and the geography of multinational corporations in Europe," Journal of Economic Geography, Oxford University Press, vol. 14(6), pages 1053-1086.
    5. Christian von Hirschhausen & Astrid Cullmann & Andreas Kappeler, 2006. "Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2553-2566.
    6. Jan De Loecker & Pinelopi K. Goldberg & Amit K. Khandelwal & Nina Pavcnik, 2016. "Prices, Markups, and Trade Reform," Econometrica, Econometric Society, vol. 84, pages 445-510, March.
    7. Stacy Eller & Peter Hartley & Kenneth Medlock, 2011. "Empirical evidence on the operational efficiency of National Oil Companies," Empirical Economics, Springer, vol. 40(3), pages 623-643, May.
    8. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    9. Piccolo, Salvatore & Tarantino, Emanuele & Ursino, Giovanni, 2015. "The value of transparency in multidivisional firms," International Journal of Industrial Organization, Elsevier, vol. 41(C), pages 9-18.
    10. Berk, Istemi & Rauch, Jannes, 2016. "Regulatory interventions in the US oil and gas sector: How do the stock markets perceive the CFTC's announcements during the 2008 financial crisis?," Energy Economics, Elsevier, vol. 54(C), pages 337-348.
    11. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    12. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    13. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    14. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    15. Ramos, Sofia B. & Veiga, Helena, 2011. "Risk factors in oil and gas industry returns: International evidence," Energy Economics, Elsevier, vol. 33(3), pages 525-542, May.
    16. Lucia Foster & John Haltiwanger & Chad Syverson, 2008. "Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?," American Economic Review, American Economic Association, vol. 98(1), pages 394-425, March.
    17. Abbott, Malcolm, 2006. "The productivity and efficiency of the Australian electricity supply industry," Energy Economics, Elsevier, vol. 28(4), pages 444-454, July.
    18. Michael J. Artis & Ernest Miguelez & Rosina Moreno, 2012. "Agglomeration economies and regional intangible assets: an empirical investigation," Journal of Economic Geography, Oxford University Press, vol. 12(6), pages 1167-1189, November.
    19. Berlemann Michael & Wesselhöft Jan-Erik, 2014. "Estimating Aggregate Capital Stocks Using the Perpetual Inventory Method: A Survey of Previous Implementations and New Empirical Evidence for 103 Countries," Review of Economics, De Gruyter, vol. 65(1), pages 1-34, April.
    20. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    21. Markus Eberhardt & Francis Teal, 2013. "No Mangoes in the Tundra: Spatial Heterogeneity in Agricultural Productivity Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 914-939, December.
    22. Hartley, Peter & Medlock III, Kenneth B., 2008. "A model of the operation and development of a National Oil Company," Energy Economics, Elsevier, vol. 30(5), pages 2459-2485, September.
    23. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    24. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).
    25. Claudio Detotto & Manuela Pulina & Juan Brida, 2014. "Assessing the productivity of the Italian hospitality sector: a post-WDEA pooled-truncated and spatial analysis," Journal of Productivity Analysis, Springer, vol. 42(2), pages 103-121, October.
    26. Jaepil Han & Deockhyun Ryu & Robin Sickles, 2016. "How to Measure Spillover Effects of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 259-294, Emerald Group Publishing Limited.
    27. Anthony J. Glass & Karligash Kenjegalieva & Robin C. Sickles, 2016. "Returns to scale and curvature in the presence of spillovers: evidence from European countries," Oxford Economic Papers, Oxford University Press, vol. 68(1), pages 40-63.
    28. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    29. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, June.
    30. Hansen, Bruce E. & Racine, Jeffrey S., 2012. "Jackknife model averaging," Journal of Econometrics, Elsevier, vol. 167(1), pages 38-46.
    31. Wolf, Christian, 2009. "Does ownership matter? The performance and efficiency of State Oil vs. Private Oil (1987-2006)," Energy Policy, Elsevier, vol. 37(7), pages 2642-2652, July.
    32. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    33. Pérez-Reyes, Raúl & Tovar, Beatriz, 2009. "Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms," Energy Policy, Elsevier, vol. 37(6), pages 2249-2261, June.
    34. Haggerty, Julia & Gude, Patricia H. & Delorey, Mark & Rasker, Ray, 2014. "Long-term effects of income specialization in oil and gas extraction: The U.S. West, 1980–2011," Energy Economics, Elsevier, vol. 45(C), pages 186-195.
    35. Sabet, Amir H. & Heaney, Richard, 2016. "An event study analysis of oil and gas firm acreage and reserve acquisitions," Energy Economics, Elsevier, vol. 57(C), pages 215-227.
    36. Dupont, Diane P. & Grafton, R. Quentin & Kirkley, James & Squires, Dale, 2002. "Capacity utilization measures and excess capacity in multi-product privatized fisheries," Resource and Energy Economics, Elsevier, vol. 24(3), pages 193-210, June.
    37. Phan, Dinh & Nguyen, Hoa & Faff, Robert, 2014. "Uncovering the asymmetric linkage between financial derivatives and firm value — The case of oil and gas exploration and production companies," Energy Economics, Elsevier, vol. 45(C), pages 340-352.
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    2. Pablo Ponce & José Álvarez-García & Mary Cumbicus & María de la Cruz del Río-Rama, 2021. "Spatial Externalities of Income Inequality on Security in Latin America," Mathematics, MDPI, vol. 9(3), pages 1-19, January.
    3. Binlei Gong, 2020. "New Growth Accounting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 641-661, March.
    4. Binlei Gong & Robin C. Sickles, 2021. "Resource allocation in multi-divisional multi-product firms," Journal of Productivity Analysis, Springer, vol. 55(2), pages 47-70, April.
    5. Gong, Binlei, 2020. "Measuring and Achieving World Agricultural Convergence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304347, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Multi-dimensional interactions; Spatial econometric model; Model averaging method; Global oilfield market;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels

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