IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v77y2022ics030142072200109x.html
   My bibliography  Save this article

Considering the recent increase in license fees in Turkey, how can the negative effect of the fees on the mining operating costs be reduced?

Author

Listed:
  • Yıldız, Taşkın Deniz

Abstract

In Turkey, for mining enterprises to realize their activities and conduct mining production, they are obliged to pay operating license fees annually. This obligation starts from the date of operating license application, about 1–1.5 years before the enterprises obtain a production permit. In recent years, an increase in the operating license fees has occurred as a result of the amendments made in the mining legislation. These increases made in the fees might become revenue loss in the forthcoming years despite creating an increase in the revenues of the state. In Turkey, according to Law No.7164 came into force in 2019, mineral groups, operating license areas and periods are considered in the calculation of operating license fee. In this direction, these factors in the fee calculation were used in the calculations by means of the answers given by enterprises through SurveyMonkey program. These fees paid to start from the mining operating license application to obtaining an operation permit are included in the investment cost. These costs were proportioned to the investment costs of the enterprises. Fees paid after obtaining an operation permit are operating costs. And, these fees were proportioned to the operating costs of the enterprises. Also, operating license fees per hectare were calculated. All these data were compared for the legislation periods 2005–2015, 2016–2019, 2020 and after in Turkey. An increase of 98% on average on US$ basis has arisen in these fees in 2020 compared to the legislation period 2016–2019 due to the new formula foreseen particularly in the calculation of operating license fees. Also, mining enterprises paid these fees 3.5% more on US$ basis in 2021 compared to 2020 due to the license period being considered in the new calculation formula. Although the rate of increase decreases every year, increases close to this rate will emerge. Mining enterprises should be responsible for the calculation method and conditions of operating license fee that is valid on the date when operating licenses are obtained. And, they should annually pay operating license fees according to this method. Considering that enterprises pay high fees for other land uses too, the increasing license fees should be demanded from enterprises in the direction that they will not create mining cost risk and that the state will charge the optimum fee. If there will not be discounts in the other fees required from enterprises, in line with the expectation of the mining sector, the operating license fee calculation methods in the previous legislation periods can be applied. This fee may not be taken before the operation permit. Or, even if the current operating license fee formula is applied, changes can be made in the critera used in the formula. Within the scope, if permit area is used instead of license area in the calculation, operating license fees will be calculated ∼50–55% deducted.

Suggested Citation

  • Yıldız, Taşkın Deniz, 2022. "Considering the recent increase in license fees in Turkey, how can the negative effect of the fees on the mining operating costs be reduced?," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s030142072200109x
    DOI: 10.1016/j.resourpol.2022.102660
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030142072200109X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.102660?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Celine de Quatrebarbes & Bertrand Laporte, 2015. "What do we know about the mineral resource rent sharing in Africa?," CERDI Working papers halshs-01146279, HAL.
    2. Rademeyer, Maryke C. & Minnitt, Richard C.A. & Falcon, Rosemary M.S., 2019. "A mathematical optimisation approach to modelling the economics of a coal mine," Resources Policy, Elsevier, vol. 62(C), pages 561-570.
    3. Smith, James L., 2013. "Issues in extractive resource taxation: A review of research methods and models," Resources Policy, Elsevier, vol. 38(3), pages 320-331.
    4. Guj, Pietro & Chandra, Atul, 2019. "Comparing different real option valuation approaches as applied to a copper mine," Resources Policy, Elsevier, vol. 61(C), pages 180-189.
    5. Marina Nevskaya & Sergey Seleznev & Vladimir Masloboev & Elena Klyuchnikova & Diminriy Makarov, 2021. "Involving small and medium-sized mining industry businesses in mining waste processing in the Russian Federation," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(1), pages 81-86, April.
    6. Söderholm, Kristina & Söderholm, Patrik & Helenius, Heidi & Pettersson, Maria & Viklund, Roine & Masloboev, Vladimir & Mingaleva, Tatiana & Petrov, Viktor, 2015. "Environmental regulation and competitiveness in the mining industry: Permitting processes with special focus on Finland, Sweden and Russia," Resources Policy, Elsevier, vol. 43(C), pages 130-142.
    7. Fraser, Rob & Kingwell, Ross, 1997. "Can expected tax revenue be increased by an investment-preserving switch from ad valorem royalties to a resource rent tax?," Resources Policy, Elsevier, vol. 23(3), pages 103-108, September.
    8. Gligoric, Zoran & Gligoric, Milos & Dimitrijevic, Bojan & Grozdanovic, Ines & Milutinovic, Aleksandar & Ganic, Aleksandar & Gojkovic, Zoran, 2020. "Model of room and pillar production planning in small scale underground mines with metal price and operating cost uncertainty," Resources Policy, Elsevier, vol. 65(C).
    9. Hazra, Tanmoy & Samanta, Biswajit & Dey, Kaushik, 2019. "Real option valuation of an Indian iron ore deposit through system dynamics model," Resources Policy, Elsevier, vol. 60(C), pages 288-299.
    10. Humphreys, D., 2001. "Sustainable development: can the mining industry afford it?," Resources Policy, Elsevier, vol. 27(1), pages 1-7, March.
    11. Bomsel, O. & Borkey, P. & Glachant, M. & Leveque, F., 1996. "Is there room for environmental self-regulation in the mining sector?," Resources Policy, Elsevier, vol. 22(1-2), pages 79-86.
    12. Magnus Ericsson & Olof Löf, 2019. "Mining’s contribution to national economies between 1996 and 2016," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 32(2), pages 223-250, July.
    13. Abdelwahed, Loujaina, 2020. "More oil, more or less taxes? New evidence on the impact of resource revenue on domestic tax revenue," Resources Policy, Elsevier, vol. 68(C).
    14. Mai, Ngoc Luan & Topal, Erkan & Erten, Oktay & Sommerville, Bruce, 2019. "A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming," Resources Policy, Elsevier, vol. 62(C), pages 571-579.
    15. Sanoh,Aly & Coulibaly,Massaoly, 2015. "Socioeconomic and fiscal impact of large-scale gold mining in Mali," Policy Research Working Paper Series 7467, The World Bank.
    16. Andrzej Gałaś & Alicja Kot-Niewiadomska & Hubert Czerw & Vladimir Simić & Michael Tost & Linda Wårell & Slávka Gałaś, 2021. "Impact of Covid-19 on the Mining Sector and Raw Materials Security in Selected European Countries," Resources, MDPI, vol. 10(5), pages 1-23, April.
    17. Groeneveld, Benjamin & Topal, Erkan & Leenders, Bob, 2019. "Examining system configuration in an open pit mine design," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    18. Ardian, Aldin & Kumral, Mustafa, 2020. "Incorporating stochastic correlations into mining project evaluation using the Jacobi process," Resources Policy, Elsevier, vol. 65(C).
    19. Ajak, Ajak Duany & Lilford, Eric & Topal, Erkan, 2018. "Application of predictive data mining to create mine plan flexibility in the face of geological uncertainty," Resources Policy, Elsevier, vol. 55(C), pages 62-79.
    20. Michael Priester & Magnus Ericsson & Peter Dolega & Olof Löf, 2019. "Mineral grades: an important indicator for environmental impact of mineral exploitation," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 32(1), pages 49-73, April.
    21. Nourali, Hamidreza & Osanloo, Morteza, 2019. "Mining capital cost estimation using Support Vector Regression (SVR)," Resources Policy, Elsevier, vol. 62(C), pages 527-540.
    22. Yıldız, Taşkın Deniz & Kural, Orhan, 2020. "The effects of the mining operation activities permit process on the mining sector in Turkey," Resources Policy, Elsevier, vol. 69(C).
    23. Dehghani, Hesam & Ataee-pour, Majid & Esfahanipour, Akbar, 2014. "Evaluation of the mining projects under economic uncertainties using multidimensional binomial tree," Resources Policy, Elsevier, vol. 39(C), pages 124-133.
    24. Yıldırım, Seda & Gedikli, Ayfer & Erdoğan, Seyfettin & Yıldırım, Durmuş Çağrı, 2020. "Natural resources rents-financial development nexus: Evidence from sixteen developing countries," Resources Policy, Elsevier, vol. 68(C).
    25. Kulczycka, Joanna & Wirth, Herbert & Hausner, Jerzy, 2017. "Polish tax policy - its impact on the mineral sector," Resources Policy, Elsevier, vol. 52(C), pages 72-80.
    26. Dehghani, Hesam & Ataee-pour, Majid, 2012. "Determination of the effect of operating cost uncertainty on mining project evaluation," Resources Policy, Elsevier, vol. 37(1), pages 109-117.
    27. Njowa, G. & Musingwini, C., 2018. "A framework for interfacing mineral asset valuation and financial reporting," Resources Policy, Elsevier, vol. 56(C), pages 3-15.
    28. Schantz, Radford Jr, 1994. "Purpose and effects of a royalty on public land minerals," Resources Policy, Elsevier, vol. 20(1), pages 35-48, March.
    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. Yıldız, Taşkın Deniz, 2022. "Supervisor fund expectation for the guarantee of salaries in the presence of the effect of permanent supervisor salaries on mining operating costs in Turkey," Resources Policy, Elsevier, vol. 77(C).
    2. Yıldız, Taşkın Deniz, 2022. "How can the state rights be calculated by considering a high share of state right in mining operating costs in Turkey?," Resources Policy, Elsevier, vol. 75(C).
    3. Yıldız, Taşkın Deniz, 2023. "How can shares be increased for indigenous peoples in state rights paid by mining companies? An education incentive through direct contribution to the people," Resources Policy, Elsevier, vol. 85(PA).
    4. Yıldız, Taşkın Deniz, 2023. "Changes in the salaries of mining engineers as they obtain managerial and OHS specialist positions in Turkey: By what criteria can salaries be increased?," Resources Policy, Elsevier, vol. 84(C).
    5. Yıldız, Taşkın Deniz, 2022. "Are the compensations given to mining enterprises due to the overlapping with other investments in Turkey enough? Expectations of compensation for profit deprivation," Resources Policy, Elsevier, vol. 75(C).
    6. Yıldız, Taşkın Deniz, 2020. "The impacts of EIA procedure on the mining sector in the permit process of mining operating activities & Turkey analysis," Resources Policy, Elsevier, vol. 67(C).
    7. Yıldız, Taşkın Deniz, 2020. "Waste management costs (WMC) of mining companies in Turkey: Can waste recovery help meeting these costs?," Resources Policy, Elsevier, vol. 68(C).
    8. Yıldız, Taşkın Deniz & Güner, Mehmet Oğuz & Kural, Orhan, 2024. "Effects of EU-Compliant mining waste regulation on Turkish mining sector: A review of characterization, classification, storage, management, recovery of mineral wastes," Resources Policy, Elsevier, vol. 90(C).
    9. Bertrand Laporte & Céline de Quatrebarbes & Yannick Bouterige, 2019. "Rent sharing and progressivity of tax regimes in the mining sector: An analysis of 21 African gold-producing countries [Partage de la rente et progressivité des régimes fiscaux dans le secteur mini," CERDI Working papers halshs-02103047, HAL.
    10. Bertrand Laporte & Celine de Quatrebarbes & Yannick Bouterige, 2022. "Tax design and rent sharing in mining sector: Evidence from African gold‐producing countries," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(6), pages 1176-1196, August.
    11. Söderholm, Patrik, 2023. "How environmental permitting uncertainty in large-scale mining could influence subcontractors: The underlying chicken-and-egg problem," Resources Policy, Elsevier, vol. 82(C).
    12. Chuan-Chuan Ko & Chien-Yu Liu & Zan-Yu Chen & Jing Zhou, 2019. "Sustainable Development Economic Strategy Model for Reducing Carbon Emission by Using Real Options Approach," Sustainability, MDPI, vol. 11(19), pages 1-14, October.
    13. Kamel, Ahmed & Elwageeh, Mohamed & Bonduà, Stefano & Elkarmoty, Mohamed, 2023. "Evaluation of mining projects subjected to economic uncertainties using the Monte Carlo simulation and the binomial tree method: Case study in a phosphate mine in Egypt," Resources Policy, Elsevier, vol. 80(C).
    14. Bertrand Laporte & Céline de Quatrebarbes & Yannick Bouterige, 2018. "A model for sharing mineral resource rent in African countries [Un modèle de partage de la rente minière dans les pays africains]," Post-Print hal-01975695, HAL.
    15. Bourgain, Arnaud & Zanaj, Skerdilajda, 2020. "A tax competition approach to resource taxation in developing countries," Resources Policy, Elsevier, vol. 65(C).
    16. Asatryan, Zareh & Baskaran, Thushyanthan & Birkholz, Carlo & Hufschmidt, Patrick, 2021. "Regional redistribution of mineral resource wealth in Africa," ZEW Discussion Papers 21-032, ZEW - Leibniz Centre for European Economic Research.
    17. Bertinelli, Luisito & Bourgain, Arnaud & Zanaj, Skerdilajda, 2022. "Taxes and declared profits: Evidence from gold mines in Africa," Resources Policy, Elsevier, vol. 78(C).
    18. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    19. Bertrand Laporte & Céline de Quatrebarbes & Yannick Bouterige, 2017. "Mining taxation in Africa: The gold mining industry in 14 countries from 1980 to 2015," CERDI Working papers halshs-01545361, HAL.
    20. Johnson, Eva Liedholm & Ericsson, Magnus & Löf, Anton, 2023. "The mining permitting process in selected developed economies," Land Use Policy, Elsevier, vol. 131(C).

    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:eee:jrpoli:v:77:y:2022:i:c:s030142072200109x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.