IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v10y2022i12p303-d987781.html
   My bibliography  Save this article

Technical Efficiency and Productivity Growth of Crude Palm Oil: Variation across Years, Locations, and Firm Sizes in Indonesia

Author

Listed:
  • Haura Azzahra Tarbiyah Islamiya

    (Economics Department, Faculty of Economics and Business, Airlangga University, 4-6 Airlangga Street, Surabaya 50115, Indonesia)

  • Dyah Wulan Sari

    (Economics Department, Faculty of Economics and Business, Airlangga University, 4-6 Airlangga Street, Surabaya 50115, Indonesia)

  • Mohammad Zeqi Yasin

    (Economics Department, Faculty of Economics and Business, University of Jember, 37 Kalimantan Street, Jember 68121, Indonesia)

  • Wenny Restikasari

    (Economics Department, Faculty of Economics and Business, Surabaya State University, 2 Ketintang Street, Surabaya 60231, Indonesia)

  • Mohd Shahidan Shaari

    (Economics Department, Faculty of Economics and Business, Airlangga University, 4-6 Airlangga Street, Surabaya 50115, Indonesia
    Faculty of Business and Communication, Universiti Malaysia Perlis, Exit Lebuhraya Changlun Street, Arau 02600, Malaysia)

  • Mochamad Devis Susandika

    (Economics Department, Faculty of Economics and Business, Airlangga University, 4-6 Airlangga Street, Surabaya 50115, Indonesia
    Regional Secretariat Economic Bureu, East Java Provincial Government, 110 Pahlawan Street, Surabaya 60174, Indonesia)

Abstract

Crude palm oil (CPO) is a valuable commodity for Indonesia’s economy as the country has become the world’s biggest producer and exporter. Therefore, maintaining productivity in the CPO industry is crucial to ensure that the global demand is met. This study aims to examine Indonesian CPO productivity and its components using total factor productivity growth (TFPg) with stochastic frontier analysis. This study analyzes the variation in the TFPg across years, locations, and firm sizes. The first two analyses imply that, on average, the CPO industry’s productivity declines annually, with firms in 20 provinces experiencing negative TFPg. Regarding size, the analysis demonstrates that the technical efficiency change (TEC) and technical change (TC) have regressed the TFPg in all scale firms. However, medium firms saw a smaller decline in comparison to large firms. Conversely, large firms possess slightly better scale efficiency change (SEC) than medium firms, although both types attain a negative SEC. The findings also show that the main factor contributing to the gain or decline in productivity is TC, which suggests the urgency of innovative technology in the CPO industry.

Suggested Citation

  • Haura Azzahra Tarbiyah Islamiya & Dyah Wulan Sari & Mohammad Zeqi Yasin & Wenny Restikasari & Mohd Shahidan Shaari & Mochamad Devis Susandika, 2022. "Technical Efficiency and Productivity Growth of Crude Palm Oil: Variation across Years, Locations, and Firm Sizes in Indonesia," Economies, MDPI, vol. 10(12), pages 1-13, November.
    • Handle: RePEc:gam:jecomi:v:10:y:2022:i:12:p:303-:d:987781
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/10/12/303/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7099/10/12/303/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    2. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    3. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    4. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    5. Margono, Heru & Sharma, Subhash C., 2006. "Efficiency and productivity analyses of Indonesian manufacturing industries," Journal of Asian Economics, Elsevier, vol. 17(6), pages 979-995, December.
    6. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    7. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    2. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    3. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    4. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    5. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    6. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    7. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    8. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
    9. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    10. Matthias Walter, 2011. "Some Determinants of Cost Efficiency in German Public Transport," Journal of Transport Economics and Policy, University of Bath, vol. 45(1), pages 1-20, January.
    11. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    12. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    13. Emilie Caldeira & Alou Adessé Dama & Ali Compaoré & Mario Mansour & Grégoire Rota-Graziosi, 2020. "Tax effort in Sub-Saharan African countries : evidence from a new dataset," Working Papers hal-02543162, HAL.
    14. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    15. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    16. Evangelia Desli & Subhash Ray & Subal Kumbhakar, 2003. "A dynamic stochastic frontier production model with time-varying efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 10(10), pages 623-626.
    17. Lingran Yuan & Shurui Zhang & Shuo Wang & Zesen Qian & Binlei Gong, 2021. "World agricultural convergence," Journal of Productivity Analysis, Springer, vol. 55(2), pages 135-153, April.
    18. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    19. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    20. Julio Peña & Julio Aguirre & René Cerca D'amico, 2004. "Pesca demersal en Chile: eficiencia técnica y escalas de operación," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 119-160, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecomi:v:10:y:2022:i:12:p:303-:d:987781. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.