Environmental pollution and economic growth elasticities of maritime and air transportations in Iran

Taghvaee, Vahid Mohamad; Agheli, Lotfali; Assari Arani, Abbas; Nodehi, Mehrab; Shirazi, Jalil Khodaparast Article Environmental pollution and economic growth elasticities of maritime and air transportations in Iran Marine Economics and Management (MAEM) Provided in Cooperation with: Ocean University of China, Qingdao Suggested Citation: Taghvaee, Vahid Mohamad; Agheli, Lotfali; Assari Arani, Abbas; Nodehi, Mehrab; Shirazi, Jalil Khodaparast (2019) : Environmental pollution and economic growth elasticities of maritime and air transportations in Iran, Marine Economics and Management (MAEM), ISSN 2516-158X, Emerald, Leeds, Vol. 2, Iss. 2, pp. 114-123, https://doi.org/10.1108/MAEM-09-2019-0008 This Version is available at: https://hdl.handle.net/10419/320047 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Environmental pollution and economic growth elasticities of maritime and air transportations in Iran Vahid Mohamad Taghvaee, Lotfali Agheli and Abbas Assari Arani Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran Mehrab Nodehi Department of Civil Engineering, Engineering Faculty, Islamic Azad University, Gorgan Branch, Gorgan, Iran, and Jalil Khodaparast Shirazi Department of Economics, Islamic Azad University, Shiraz Branch, Shiraz, Iran Abstract Purpose –The purpose of this paper is to examine the effects of maritime and air transportation on the environment and economy of Iran. The authors specify two dynamic models of the environmental pollution and the economic growth. Then, the authors estimate the environmental and economic elasticities of maritime and air transportation in short run and long run in Iran during 1978–2012. Design/methodology/approach –The authors estimate the environmental and economic elasticities of maritime elasticities in short and long run, using simultaneous equations system. Findings –The findings indicate that the short- and long-run environmental pollution elasticities of maritime transportation are higher than those of the air ones. In addition, the economic growth elasticities are greater in the air transportation compared to maritime one. As a result, the maritime transportation is more pollutant and less productive in Iran in comparison with the air transportation. Originality/value –The policymakers are advised to improve the infrastructure of maritime transportation from both the environmental and economic point of views. Consequently, the air transportation is considered as a cleaner and more beneficial transportation mode in Iran, where geographical position limits the maritime transport as a widespread transportation mode. Keywords Iran, Economic growth Paper type Research paper 1. Introduction Transportation plays an important role in the environmental pollution and economic growth. According to IEA (2009), about 25 percent of the world’s energy is attributed to transport and about 5 percent of this energy is responsible for the whole environmental changes, while projecting that this amount will be likely to increase 50 percent by 2030 and 80 percent by 2050. As shown in Figure 1, transportation boosts the international trade and Marine Economics and Management Vol. 2 No. 2, 2019 pp. 114-123 Emerald Publishing Limited 2516-158X DOI 10.1108/MAEM-09-2019-0008 Received 6 September 2019 Accepted 9 October 2019 The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/2516-158X.htm © Vahid Mohamad Taghvaee, Lotfali Agheli, Abbas Assari Arani, Mehrab Nodehi and Jalil Khodaparast Shirazi. Published in Marine Economics and Management. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode The authors express deep gratitude to the Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, which supports the research technically. 114 MAEM 2,2 technical efficiency, and stimulates the economic growth. Economic growth, in turn, causes the environmental pollution. In addition, transportation has conflicting effects on the environmental pollution. It consumes a high volume of fuels and pollutes the environment; whereas it can reduce the environmental pollution with higher efficiency in carrying the cargos, like maritime transportation (Farhani et al., 2014; Taghvaee et al., 2017). There are four modes of transportations including road, rail, air and maritime transportation. Among them, maritime transportation has the highest potential for carrying goods in high volume; and air transportation is the fastest mode of transportation, boosting the economic growth. Nonetheless, both pollute the environment due to consumption of high volumes of fossil fuels (IEA, 2009; Taghvaee and Hajiani, 2015; IMO, 2016; Larkin et al., 2016; IATA, 2014). Globally, transport energy use increased steadily at between 2 and 2.5 percent per year during 1971–2006. Figure 2 shows transport energy use by mode in the world in 2008. Maritime and air transportations show the highest shares, after road transportation which ranks the first (IEA, 2009). Maritime transportation is of the largest capacity for shipping commodities; and the air one is the most rapid mode. Both maritime and air transportation modes increase the flows of the international trade, and encourage the economic growth (Taghvaee and Hajiani, 2015; IMO, 2016; Larkin et al., 2016; IATA, 2014). As mentioned earlier, these modes of transportation increase the environmental pollution. Figure 2 shows the extrapolation of CO 2 emissions among the modes of transport Transportation Trade Economic Growth Source: Researchers’ elaboration based on Farhani et al. (2014) and Taghvaee et al. (2017) findings Environmental Pollution Efficiency Energy Consumption Figure 1. Transportation, environmental pollution and economic growth 2.5 Energy use (thousand Mtoe) Non-specified (transport) Pipeline transport Domestic navigation World marine bunkers Rail Domestic aviation International aviation Road freight Road passenger 2 1.5 1 0.5 0 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 Source: IEA (2009) Figure 2. World energy consumption, by transportation mode in 2008 115 Environmental pollution and economic growth (Grames per ton-KM) (IMO, 2009). Based on Figure 3, the air mode burns high volume of fuel to operate at high speed, emitting intensive carbon dioxide (CO 2 ) (IATA, 2014). Maritime transportation plays a dual role in the CO 2 emissions, especially in the countries, which have access to the open seas like Iran. As Figure 4 shows, Iran is among the most pollutant countries in terms of CO 2 emissions from maritime transportation. On the one hand, it can increase carbon dioxide emissions due to the high volume of cargos, since cargo shipping requires burning an extremely high volume of fuels, which emits considerable CO 2 (Taghvaee and Hajiani, 2015). On the other hand, it can mitigate environmental pollution because of economies of scale in carrying bulk cargos (IMO, 2016). Thus, transportation by ships and aircrafts has various effects on the economic growth and environmental pollution, specifically in the geo-strategic countries such as Iran, which connects the East to the West. In this regard, the environmental and economic effects of air and sea transportation are comparable with each other (Larkin et al., 2016; IATA, 2014). 3.0, Very large container vessel (18,000 teu)* 4.9, Oil tanker (80,000–119,999 dwt) 7.9, Bulk carrier (10,000–34,999 dwt) 80.0, Truck (> 40 tons) Source: IMO (2009) GHG Study (*AP Moller-Maersk, 2014) Air freight (747, capacity 113 tons), 0 100 200 300 400 500 435.0 Figure 3. CO 2 emissions from various modes of transportation in the world 150°0′0″W90°0′0″W30°0′0″W60°0′0″E120°0′0″E180°0′0″ 70°0′0″N 50°0′0″N 30°0′0″N 10°0′0″N 10°0′0″S 30°0′0″S 50°0′0″S 70°0′0″S Global CO2 emissions (ton) Data Source: exactEarth, IHS and ArcGIS © International Council on Clean Transportation, 2017 0–100 100–5,000 5,000–25,000 25,000–100,000 >100,000 120°0′0″E 60°0′0″E 30°0′0″W 90°0′0″W 150°0′0″W 70°0′0″S 50°0′0″S 30°0′0″S 10°0′0″S 10°0′0″N 30°0′0″N 50°0′0″N 70°0′0″N 0°0′0″180°0′0″ 0°0′0″ Source: IMO (2009) GHG Study (*AP Moller-Maersk, 2014) Figure 4. Global CO 2 emissions 116 MAEM 2,2 The purpose of this study is to compare the maritime transportation effects with air transportation ones on the environment and economy of Iran in order to seek the most efficient and the cleanest transportation mode. 2. Methodology and model We compare the environmental and economic effects of maritime and air transportation in the short and long run in Iran during 1978–2012 using two dynamic log-linear models. Following Farhani et al. (2014), Taghvaee et al. (2017) and Taghvaee and Hajiani, we specify the models as follows (IMO, 2016; Larkin et al., 2016; IATA, 2014): LCO2t¼a0þa1LMtþa2LAtþa3LYtþa4LCO2t1þa5Dtþet;(1) LYt¼b0þb1LMtþb2LAtþb3TRtþb4LYt1þb5Dtþmt;(2) where CO 2 is carbon dioxide emissions. Mand Adenote maritime and air transportation modes, respectively. Yis GDP, and TR is trade volume. α s and β s show the parameters of models. Dis the dummy variable which is set 0 for the war years (1980–1989) and 1 for the remaining years. Lis the natural logarithm; tis year; eand mare the error terms. α 1 ,α 2 and α 3 are the short-run elasticities of environmental pollution and β 1 ,β 2 and β 3 give the short-run elasticities of the economic growth. The long-run elasticities are α 1 /1−α 4 ,α 2 /1−α 4 ,andα 3 /1 −α 4 for the environmental pollution; and β 1 /1−β 4 ,β 2 /1−β 4 and β 3 /1−β 4 for the economic growth (Sene, 2012). Before running the models, we check the variables for the unit root, preventing the spurious regression. The regressions with non-stationary variables are not reliable statistically. This study applies the Augmented Dickey–Fuller (ADF) unit root test as the most common test for stationarity (Taghavee and Hajiani, 2014; Taghvaee et al., 2017). 3. Data The annual data are derived from World Development Indicator (2014), except for the maritime and air transportation variables, which come from the Central Bank of Iran (Economic Research and Policy Department of Iran, 2016). The per capita sea and air transportation of goods are measured in metric ton per person. The per capita CO 2 emission, measured in metric ton per person, is the proxy for the environmental pollution. The per capita GDP, measured in constant 2005 US$ per person, is the proxy for the economic growth. Trade, measured as the percentage of GDP, is the proxy for trade openness. All data are in natural logarithm, which are represented in the appendix of the paper after the references. Figures 5 and 6, respectively, display the logarithms of per capita maritime and air transportation volume. With regard to Figure 5, maritime transportation has grown substantially over the period 1978–2012, raising a question: whether its growth is consistent with environmental and economic infrastructure (Parsa et al.,2019).Figure6,however, displays that the air transportation has not experienced higher growth rates. This might be caused by misallocation of budget for this transportation mode. Figure 6 is another evidence for the low investment in air transportation in comparison with the maritime transportation. Figure 7 represents the number of ships and planes in proportion to the number of ports and airports in Iran in 2015. It shows a high intensity of maritime transportation in comparison with the air mode, supporting the lower investment in the latter mode. Figures 8 and 9 exhibit the per capita CO 2 emissions and GDP in natural logarithms. Based on Figure 8, per capita CO 2 emission has increased moderately in the period under study, which is an evidence against the sustainable development in Iran. In other words, the development process of Iran is inconsistent with the environmental considerations, urging regulations that are more stringent, specifically in the transportation infrastructure. Figure 9, however, does not show a considerable increase in economic growth in Iran in the 117 Environmental pollution and economic growth 1978 0 –2 –4 –6 –8 LA 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Source: Central Bank of Iran, 2018 (Economic Research and Policy Department of Iran, 2016) Figure 6. Logarithm of per capita air transportation volume in Iran 1 0.5 0 –0.5 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 –1 –1.5 LM Source: Central Bank of Iran, 2018 (Economic Research and Policy Department of Iran, 2016) Figure 5. Logarithm of per capita maritime transportation volume 3.74 1,982.13 0 500 1,000 1,500 2,000 2,500 Active Airplane fleet/Active Airports Ship fleet/Active Ports Source: Comprehensive Transport Statistics (2015) Figure 7. The ratio of ship/ airplane fleet to air/ ports in Iran (2015) 118 MAEM 2,2 same period. It suggests that the development process does not match economic growth. Transportation infrastructure, for example, should be reformed to support economic growth efficiently in Iran. In general, the development process in Iran lacks considerable growth and environmental sustainability. For a more accurate analysis, we run Models (1) and (2) to estimate the environmental pollution and economic growth elasticities of maritime and air transportation. 4. Results As earlier said, testing against unit root is the first stage of estimation of a time series model. Table I reports the results of ADF unit root test. In this test, the null hypothesis implies unit root and non-stationarity of a series. Based on the results, all variables are stationary in level. Accordingly, it confirms that the regressions are not spurious and thus, we run the models without concerning about the spurious regression results. Table II represents the estimation results of the environmental pollution model. All coefficients are statistically significant at the 5 percent level of significance. These coefficients show that the environmental pollution is inelastic with respect to maritime and 0 1 2 3 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 LCO2 Source: World Bank, World Development Indicator, 2018 (World Development Indicator, 2014) Figure 8. Logarithm of per capita CO 2 emissions in Iran 7 7.5 8 8.5 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 LY Source: World Bank, World Development Indicator, 2018 (World Development Indicator, 2014) Figure 9. Logarithm of per capita GDP in Iran LTR LM LA LCO 2 LY t-stat. −5.16 −4.02 −3.77 −4.34 −3.77 Prob. 0.00 0.01 0.03 0.00 0.03 Stationarity I(0) I(0) I(0) I(0) I(0) Source: Authors’findings Table I. Results of the Augmented Dickey– Fuller unit root tests (intercept and trend in level, max lags ¼6) 119 Environmental pollution and economic growth air transportation modes and per capita GDP, both in the short and long run. The short-run elasticities of environmental pollution with respect to maritime and air transportation are 18 and 6 percent, respectively; and the long-run ones are 27 and 9 percent, respectively. In addition, the environmental pollution elasticities of maritime transportation are three times of the air transportation ones. Table III shows the estimation results of the economic growth model. In this model, all coefficients are again statistically significant. The coefficients indicate that the per capita GDP is inelastic with respect to maritime and air transportation modes and trade volume both in the short and long run. The short-run elasticities of per capita GDP with respect to maritime and air transportation are 5 and 10 percent, respectively; and the long-run ones are 12 and 25 percent, respectively. As a result, the elasticities of economic growth, denoted by per capita GDP, with respect to air transportation are twice as those of the maritime transportation. 5. Discussion Based on Table IV, the maritime transportation is more pollutant than the air one. The resulted elasticities in Table IV suggest that the maritime transportation is more pollutant than it would be economically beneficial. Air transportation, however, generates Variable Coefficient t-statistic Prob. LM 0.18 4.75 0.00 LA 0.06 1.69 0.10 LY 0.24 2.30 0.02 LCO 2t−1 0.35 3.09 0.00 α 1 /1−α 4 0.27 α 2 /1−α 4 0.09 α 3 /1−α 4 0.36 Source: Authors’findings Table II. Results of the CO 2 model estimation Variable Coefficient t-statistic Prob. LM 0.05 2.56 0.01 LA 0.10 2.78 0.00 LTR 0.15 3.42 0.00 LY t−1 0.60 9.21 0.00 β 1 /1−β 4 0.12 β 2 /1−β 4 0.25 β 3 /1−β 4 0.37 Source: Authors’findings Table III. Results of the GDP model estimation Elasticities Environmental pollution Economic growth Period Short run Long run Short run Long run LM 0.18 0.27 0.05 0.12 LA 0.06 0.09 0.10 0.25 LY 0.24 0.36 na na LTR na na 0.15 0.37 Source: Authors’findings Table IV. Estimated elasticities of environmental pollution and economic growth in the short and long run 120 MAEM 2,2 more economic benefits with lower environmental contaminants. These results originate from the higher investment in the maritime infrastructure in comparison with the air one, leaving low scope for the investment in the aviation mode. Not only the long-run elasticities confirm the above-mentioned claims, but also the short run ones provide us with the evidence for the selection of air rather than maritime transportation, since the former mode is a cleaner and economic choice for developing transportation network in Iran. The geographical position of Iran is another evidence for this suggestion, since the majority of the country has no direct access to the sea transportation, which can offer the capacityformoregrowthincomparisonwiththe air transportation. Certainly, the above-mentioned discussion does not mean ignoring investment in maritime transportation; but rather, it gives a comparative analysis between maritime and air transportation modes. In another word, the air transportation has higher priority for investment and development, compared with the maritime one. However, the policy makers are recommended to reform the infrastructure of maritime transportation to make it more consistent with the environment and economic aspects. 6. Conclusion This study compared the environmental and economic effects of maritime and air transportation in Iran. Using econometric methodology, it employed two log-linear models to estimate the environmental pollution and economic growth elasticities of maritime and air transportation in the short and long run in Iran during 1978–2012. The data were derived from the Central Bank of Iran and the World Bank. The results show the higher maritime transportation elasticities of environmental pollution and lower elasticities of the economic growth, compared with the air transportation. Given the results, it is implied that the maritime transportation is more pollutant and less productive in Iran, in comparison with the air transportation. The policymakers are advised to improve the infrastructure of maritime transportation from both the environmental and economic point of views. The air transportation is a cleaner and more beneficial alternative for development as a public transportation in Iran, where geography offers less capacity for selecting the maritime transport as a widespread transportation mode. Furthermore, policy makers can provide the air transportation industry with more investment to achieve its goals. For future research, it is recommended to analyze comparatively the four modes of transportation, adding the road and rail transportation. It clears the way for revealing the best alternative mode of transportation for inclusive development in Iran. References Comprehensive Transport Statistics (2015), “Ministry of Roads and Urban Development of the Islamic Republic of Iran”. Economic Research and Policy Department of Iran (2016), “Central Bank of the Islamic Republic of Iran, Economic Time Series, Database”, available at: http://tsd.cbi.ir/ Farhani, S., Chaibi, A. and Rault, C. (2014), “CO2 emissions, output, energy consumption, and trade in Tunisia”,Economic Modelling, Vol. 38, February, pp. 426-434, doi: 10.1016/j.econmod.2014.01.025. IATA (2014), “Aviation economic benefits”, International Air Transportation Association. IEA (2009), Transport, Energy, and CO2: Moving Toward Sustainability, International Energy Agency, Paris, available at: www.iea.org/publications/freepublications/publication/transport2009.pdf (accessed December 25, 2018). 121 Environmental pollution and economic growth