Determination of Optimal Green Tax Rate on Greenhouse Gas Emissions in Dairy Farms of Hamadan Province

مجله اقتصاد و توسعه کشاورزی

Article 3, Volume 32, Issue 3 - Serial Number 41, October 2018, Pages 227-236   

Document Type: Research Article

DOI: 10.22067/jead2.v32i3.71669

Authors

H. Balali^{* 1}; Gh Khaledian¹; A. Samdeliri²

¹Bu-Ali Sina University

²Sayyed- Jamalledin- AsadAbadi

Abstract

Introduction: One of the challenges faced by governments in the last century is environmental crisis such as greenhouse gasses. Due to population growth in the world, human activities including agriculture and dairy cattle industry for providing food security for peoples have increased and caused the more pollution and greenhouse gasses emission. to the extent that the amount of greenhouse gasses released by agriculture and dairy cattle's activities in the world is more than greenhouse gasses produced by transportation activities. The main agricultural greenhouse gases (GHG) are methane and nitrous oxide. Methane is produced in the rumen of the cows by methanogen microbes and are naturally present in all ruminant animals. Most methane is emitted when cattle burp. Nitrous Oxide is emitted from soil when urine, faeces and fertilizers broken down by microbes in the soil. Governments and policy makers, by applying policies and programs are struggling to overcome the problems encountered in the environmental field and reduce the negative and harmful effects of human functions on the environment. One of the ways to control and reduce environmental damages such as greenhouse gasses is using economic tools and policies such as taxes on environmental degradation activities.
‌Materials and Methods: This study aimed to evaluate the appropriate green tax rate on methane emissions in dairy cattle industry in Hamedan province. Therefore, of 44 dairy farms in Hamedan province were chosen by simple sampling method and data were collected about the cost of producing this section through questionnaires during 1395-96. By calculating the share of costs using shephard lemma and the Iterative Seemingly Unrelated Regressions method (ISUR), the cost function and cost sharing equations were estimated as a system. The advantage of the current model is that the ISUR estimators utilize the information present in the error correlation of the cross regressions (or equations) and consequently are more efficient than single equation estimation methods such as ordinary least squares. In the selected model the price of animal feed (Pfood(, price of medicine and vaccination )Pmedicin (, price of energy(Pene( and labor wage (Pwag(, are the independent variables.
Results and Discussion: The results indicated that about 52% of the pattern coefficients were significant. Thus using Translog cost function is appropriate for estimating the cost function in dairy cattle units. The calculated R2 criterion for Translog cost function is estimated about 0.99 in this research, which implies that about 99 percent of the variations of milk’s total cost are defined by the variables including animal feed price, labor wage, energy price and the price of medicine and vaccination. Parameters for the input share equations including animal feed price, labor wage, energy price and the price of medicine and vaccination, are calculated respectively as 0.53, 0.36, 0.64, 0.57 and 0.34 for the income share equation. The adjusted coefficient of determination, () for the Translog cost function, is about 0.98, and parameters for the input share equations including animal feed price, labor wage, energy price and the price of medicine and vaccination is respectively 0.47, 0.28, 0.47, 0.36 and 0.22 for the income share equation. Based on the results, the D.W of the equation is 1.98, that indicates the fitted regression is true and there is no autoregressions between residuals and independent variables.
Conclusion: Based on this study results, the appropriate green tax rate for methane emissions in the dairy cattle industry is 1.1% per kilogram of milk production. The results revealed a negative relationship among green tax rate and pollution emissions coefficient and marginal cost of production. Also, a positive relationship between green tax rate and the output price has been detected. This signifies that by increasing green tax rate, the emission of pollutions by dairy cattles is reduced. So putting emphasize on the application of green taxes in order to reduce emissions of methane greenhouse gas. It is also recommended that relevant organizations such as the country's environmental organization, by examining the prevalent infrastructure in the country and providing conditions, use green taxes as an economic tool for controlling and reducing environmental pollution. Moreover, in the feasibility studies and the pre-construction of the generating unit, the green tax should be considered in the evaluations.

Keywords

Dairy cattle; Translog cost function; ISUR; Green Tax

References

1- Abbaspour M., Ahmadian M., Abedi Z., and Shojaee M. 2010. Developing the economic model of green tax for polluting industries. World Applied Sciences Journal, 10: 1279-1282.

2- Agricultural Statistics. 2011. Office of statistics and information technology ministry of agriculture Jihad.

3- Amir Beigi H., and Ahmadi Asour A. 2007. Air hygiene and pollution control methods (Environmental and Industrial. Andisheh Rafi, First Printing, Tehran. (In Persian)

4- Asadi M. 2009. The cost of losses resulted from air pollution in Iran and the necessity of introduction of green taxes. Tax Research, 16(3). (In Persian)

5- Azizi Gh. 2004. Climate Change. Ghomes, Tehran.

6- Bakhshodeh M., and Akbari A. 2010. The production economy of its application in agriculture. First Edition (Third Edition), University of Bahonar Kerman Publications, p. 363. (In Persian)

7- Cornejo C., and Wilkie A.C. 2010. Greenhouse gas emissions and biogas potential from livestock in Ecuador. 8-Ene. for Sus. Deve. 14(4): 256-266.

8- Deelchand T., and Padgett C. 2009. Size and Scale Economies in Japanese Cooperative Banking. ICMA Center Discussion Papers in Finance, pp. 1-29.

9- Environmental Council of the Sixth Development Plan- Proposed Provisions of the Environment, July 2015.

10- Energy balance sheet of 2010. 2011. Deputy of Electricity and Energy Affairs Office of Planning for Electricity and Energy.

11- Ghorbani M., and Firooz Zare A. 2008. An introduction to environment valuation. First edition, Published by Ferdowsi University of Mashhad. First Edition. (In Persian)

12- Hassanloo S., Khalilian S., and Amirnejad H. 2015. The estimation of optimum green tax on emission of CO2 by cement industry in Iran. Journal of Environmental Research, 6(12): 39-50. (In Persian with English abstract)

13- Hosseini S. and Ghobani M. 2005. Soil erosion economics. Published by Ferdowsi University of Mashhad. First Edition.

14- IPCC. 1996. Guidelines for National Greenhouse Gas Inventories.

15- Kim Y. D., Han H.O. and Moon Y.S. 2011. The empirical effects of a gasoline tax on CO2 emissions reductions from transportation sector in Korea. Energy Policy, No. 39, pp.

16- Lee M., and Zhang N. 2012. Technical efficiency, shadow price of carbon dioxide emissions, and substitutability for energy in the Chinese manufacturing industries. Energy.

17- Paul S., and Bhattacharya R. 2004. CO2 emission from energy use in India: a decomposition analysis. Energy Policy, Retrieved, from: http://linkinghub.elsevier.com/retrieve/pii/S0301421502003117.

18- Marcin T.C. 1991. Cost function approach for estimating derived demand for composite wood products. Proceedings of the 1991 Symposium on Systems Analysis in Forest Resources, March 3-6, pp. 225-240.

19- Mc Court A., Yan T., Mayne C.S., and Porter M.G. 2006. Prediction of methane output in beef cattle from indirect respiration calorimetry data. InInternational Congress Series, 1293: 46-49. Elsevier.

20- Moghimi M., Shahnooshi N., Akbar Moghaddam B., and Daneshvar M. 2011. Study of the Welfare and environmental effects of green tax and reduction of fuel subsidy in Iran using the calculable general equilibrium model. Agricultural Economics and Development, 75: 108-79. (In Persian)

21- Molaei M., and Sani F. 2015. Estimation of technical efficiency and environmental performance of dairy cattle farms in Sarab (Data Envelopment Analysis Approach). Journal of Animal Science Researches, 25(4). (In Persian)

22- NRC. 2001. Nutrient Requirements of Beef Cattle. Seventh Revised Edition: Nat Academic Science. Washington DC. USA.

23- Pazhouyan J., and Amin Rashti N. 2007. The green taxes, with emphasizes on gasoline consumption. Journal of Economic Research Review, 7(1): 15-44. (In Persian with English abstract)

24- Pourkhabaz A.S., and Pourkhabaz H. 2002. The major environmental disturbances of the present century (Acid rain, Ozone layer, Global warming). BH nashr, Mashhad. (In Persian)

25- Saghayean Nezhad S. H., and Borhani A. 1996. Estimation of translog cost function for cement industry and its applications. Knowledge and Development, 4: 138-89. (In Persian)

26- Sharzeii G., Getmiri M., and Rastifar O. 2002. Investigating the structure of production and cost of rice production: a case study in Guilan province (1997). Agriculture Sciences and Technology, Natural Resources, 1: 56-45. (In Persian)

27- Shojaei M. 2010. Presenting a tax model for sustainable environmental management in Iran (Case study paper industry). Environment doctorate dissertation, Unpublished, Faculty of Environment and Energy, Islamic Azad University, Science and Research Branch of Tehran. (In Persian)

28- Stier J.C. 1985. Implication of factor substitution, economies of scale and technological change in the United State pulps and paper Industry”. Forest Science, 31(4): 320-327.

29- Torkamaani J., and Kalai A. 2001. Application of translog multiproduct cost function for estimating cost and inputs" functions in agriculture: case study of Fars province. Journal Eqtesad-e Keshavarziva Towse'e. 9(34): 101-124. (In Persian with English abstract)

30- Tu S.et al. 2009. A decomposition analysis of CO2 emissions from energy use: Turkish Case, 37: 4689-4699.

31- WMO, World Meteorological Organization. 2006. The state of greenhouse gases in the atmosphere using global observations through 2004. No. 1:14, http://www.wmo.com

32- “World bank”. (2016). www.worldbank.org.

33- Ozkan B., Kurklu A., and Akcaoz H. 2004. An input–output energy analysis in greenhouse vegetable production: a case study for Antalya region of Turkey. Biom. Bioen. 26(1): 89-95.

34- Shortall O.K., and Barnes A.P. 2013. Greenhouse gas emissions and the technical efficiency of farmers. Journal Ecol Indic, 29: 478-488.

35- Xue B., Wang L.Z., and Yan T. 2014. Methane emission inventories for enteric fermentation and manure management of yak, buffalo and dairy and beef cattle in china from 1988 to 2009. Agriculture, Ecosystems and Environment, 195(1): 202-210.