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Nexus of FDI, population, energy production, and water resources in South Asia: a fresh insight from dynamic common correlated effects (DCCE)

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Abstract

The purpose of this study is to explore the empirical relationship between foreign direct investment (FDI), population, energy production, and water resources in South Asia. The newly developed approach dynamic common correlated effects (DCCE) by Chudik and Pesaran (Journal of Econometrics 188:393–420, 2015a) for measuring co-integration has been applied in the present study. This procedure provides significant robust outcomes in the presence of cross-sectional dependence among the cross-sectional units. The findings confirmed that earlier models, such as mean group (MG), pooled mean group (PMG), and augmented mean group (AMG), which have been used in the literature for long data, provide misleading results in the presence of cross-sectional dependence among the cross-sectional units. A statistically significant and negative result has been observed between FDI, population, energy production, and water resources in South Asia. The governments of South Asian economies must encourage green FDI initiatives for water management, ensuring water security, securing natural resources for enhancing the sustainable development of regional economies.

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Fig. 1

Notes

  1. 1.

    https://www.undp.org/content/undp/en/home/sustainable-development-goals.html

  2. 2.

    We employed xtwest command for Westerlund co-integration.

  3. 3.

    UN World Water Development Report 1; UNESCO/Berghahn Books: New York, 2003.

References

  1. Abughlelesha SM, Lateh HB (2013) A review and analysis of the impact of population growth on water resources in Libya. World Appl Sci J 23(7):965–971

  2. Alcamo J, Döll P, Henrichs T, Kaspar F, Lehner B, Rösch T et al (2003) Global estimates of water withdrawals and availability under current and future “business-as-usual” conditions. Hydrol Sci J Sci Hydrol 48(3):339–348

  3. Alcamo J, Acosta-Michalik L, Carius A, Eierdanz F, Klein R, Krömker D, Tänzler D (2008) A new approach to quantifying and comparing vulnerability to drought. Reg Environ Chang 8(4):137–149

  4. Aldaya MM, Chapagain AK, Hoekstra AY, Mekonnen MM (2012) The water footprint assessment manual: setting the global standard. Routledge, Abingdon

  5. Anselin L (2001) Spatial econometrics. A companion to theoretical econometrics.310330

  6. Arnell NW (2004) Climate change and global water resources: SRES emissions and socio-economic scenarios. Glob Environ Chang 14(1):31–52

  7. Asian Development Bank (2015) Scaling Up to Meet New Development Challenges. Annual Report. [online] 6 ADB Avenue, Mandaluyong City. https://www.adb.org/sites/default/files/institutional-document/182852/adb-annual-report-2015.pdf. Accessed 12 Jul 2019

  8. Asian Development Bank (ADB) (2017) Sustainable Infrastructure for future needs. Annual Report. [online] 6 ADB Avenue, Mandaluyong City: ADB. https://www.adb.org/sites/default/files/institutional-document/411996/adb-annual-report-2017.pdf. Accessed 12 Jul 2019

  9. Avery S (2010) Hydrological impacts of Ethiopia’s Omo Basin on Kenya’s Lake Turkana water levels and fishery. Report. African Development Bank, Addis Ababa

  10. Awan SA, Meo MS, Ghimire A, Wu RY, Zhuang PF (2018) Is trade openness good or bad for environment in Pakistan; an ARDL bounds testing approach. In 4th Annual International Conference on Management, Economics and Social Development (ICMESD 2018). Atlantis Press

  11. Bai J, Ng S (2004) A PANIC attack on unit roots and cointegration. Econometrica 72(4):1127–1178

  12. Banerjee A, Cockerell L, Russell B (2001) An I (2) analysis of inflation and the markup. J Appl Econ 16(3):221–240

  13. Blackburne EF, Frank MW (2016) Estimation of nonstationary heterogeneous panels. Stata J 7(2):197

  14. Bloom DE, Rosenberg L (2011) The future of South Asia: population dynamics, economic prospects, and regional coherence. WDAForum, University of St. Gallen

  15. Bossio D, Erkossa T, Dile Y, McCartney M, Killiches F, Hoff H (2012) Water implications of foreign direct investment in Ethiopia’s agricultural sector. Water Altern 5(2)

  16. Bruinsma J (2009) The resource outlook to 2050: by how much do land, water, and crop yields need to increase by 2050, expert meeting on how to feed the world by 2050, 24–26 June 2009. FAO, Rome

  17. Carter NT (2013) (Energy-water nexus: the energy sector’s water use. Congressional Research Service.

  18. Chang Y (2004) Bootstrap unit root tests in panels with cross-sectional dependency. J Econ 120:263–293

  19. Chellaney, B. (2016). Yes, Asia is the most water-strapped continent. [online] PolitiFact. Available at: https://www.politifact.com/globalnews/statements/2017/jan/06/brahma-chellaney/yes-asia-most-water-strapped-continent/. [Accessed 10 Jul. 2019].

  20. Chen J, Shi H, Sivakumar B, Peart RM (2016) Population, water, food, energy and dams. Renew Sust Energ Rev 56:18–28

  21. Choi I (2006) Nonstationary Panels. In: Patterson K, Mills TC (eds) Palgrave handbooks of econometrics 1. Palgrave Macmillan, New York, pp 511–539

  22. Chudik A, Pesaran MH (2015a) Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. J Econ 188(2):393–420

  23. Chudik A, Pesaran MH (2015b) Large panel data models with cross-sectional dependence: a survey. In: Baltagi B (ed) The Oxford handbook of panel data. Oxford University Press, New York, pp 82–99

  24. De Hoyos RE, Sarafidis V (2006) Testing for cross-sectional dependence in panel-data models. Stata J 6(4):482–496

  25. Ditzen J (2016) XTDCCE: Estimating dynamic common correlated effects in Stata. SEEC Discussion Papers, 1601

  26. Duarte R, Pinilla V, Serrano A (2013) Looking backward to look forward: water use and economic growth from a long-term perspective. Appl Econ 46:212–224

  27. Eberhardt M (2012) Estimating panel time-series models with heterogeneous slopes. Stata J 12(1):61–71

  28. Elias E, Abdi F (2010) Putting pastoralists on the policy agenda: land alienation in Southern Ethiopia. IIED, London

  29. Ercin EA, Hoekstra YA (2014) Water footprint scenarios for 2050: a global analysis. Environ Int 64:71–82

  30. Exploring the Energy-Water-Food Nexus to Address Water Scarcity in South Asian Economies (ESMAP), 2018. https://www.esmap.org/node/56603

  31. Falkenmark M (1997) Meeting water requirements of an expanding world population. Philos Trans R Soc Lond Ser B Biol Sci 352(1356):929–936

  32. Falkenmark M, Widstrand C (1992) 1992. Population and water resources: a delicate balance. Popul Bull 47(3):1–36

  33. Falkenmark M, Lundqvist J, Widstrand C (1989) Macro-scale water scarcity requires micro-scale approaches: aspects of vulnerability in semi-arid development. In Natural resources forum (Vol. 13, No. 4, pp. 258–267). Oxford, UK: Blackwell Publishing Ltd

  34. Falkenmark M, Rockström J, Karlberg L (2009) Present and future water requirements for feeding humanity. Food Sec 1(1):59–69

  35. Fung F, Lopez A, New M (2011) Water availability in +2 °C and +4 °C worlds. Philos Trans R Soc Lond A 369(1934):99–116

  36. Güler Ö (2009) Wind energy status in electrical energy production of Turkey. Renew Sust Energ Rev 13(2):473–478

  37. Hightower M, Pierce SA (2008) The energy challenge. Nature 452(7185):285–286

  38. Hitam MB, Borhan HB (2012) FDI, growth and the environment: impact on quality of life in Malaysia. Procedia Soc Behav Sci 50:333–342

  39. Hossain MS (2011) Panel estimation for CO2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. Energy Policy 39(11):6991–6999

  40. Hsiao C, Tahmiscioglu AK (2008) Estimation of dynamic panel data models with both individual and time-specific effects. J Statist Plann Inference 138(9):2698–2721

  41. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115(1):53–74

  42. Jorgenson AK (2007) Does foreign investment harm the air we breathe and the water we drink? A cross-national study of carbon dioxide emissions and organic water pollution in less-developed countries, 1975 to 2000. Organ Environ 20(2):137–156

  43. Kahia M, Aïssa MSB, Charfeddine L (2016) Impact of renewable and non-renewable energy consumption on economic growth: new evidence from the MENA Net Oil Exporting Countries (NOECs). Energy 116:102–115

  44. Kapetanios G, Pesaran MH, Yamagata T (2011) Panels with nonstationary multifactor error structures. J Econ 160:326–348

  45. Kenny SD, Wilkinson R (Eds) (2011) The water-energy nexus in the American West. Edward Elgar Publishing

  46. Keulertz M, Woertz E (2015) Financial challenges of the nexus: pathways for investment in water, energy and agriculture in the Arab world. Int J Water Resour Dev 31:3

  47. Khanji ES, Hudson J (2016) Water utilization and water quality in endogenous economic growth. Environ Dev Econ 1:1–23

  48. Korzun VI, Sokolov AA, Budyko MI, Voskresensky KP, Kalinin GP, Konoplyantsev AA et al (1978) editors. World water balance and water resources of the earth, studies and reports in hydrology 25. UNESCO, Paris

  49. L’vovich MI (1979) World water resources and their future. Chelsea, LithoCrafters

  50. Lee TC, Hashim H, Ho SC, Fan VY, Klemes JJ (2017) Sustaining the low-carbon emission development in Asia and beyond: sustainable energy, water, transportation and low-carbon emission technology. J Clean Prod 146:1–13

  51. Levin A, Lin CF (2002) and Chu., C.S.J, Unit root test in panel data: asymptotic and finite sample properties. J Econ 108:1–24

  52. Levin A, Lin CF, Chu CS, J (2002) Unit root tests in panel data: asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1–24.

  53. Liu Y, Chen Y (2006) Impact of population growth and land-use change on water resources and ecosystems of the arid Tarim River Basin in Western China. Int J Sust Dev World Ecol 13(4):295–305

  54. Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and a new simple test, Oxford Bulletin of Economics and Statistics, 61(S1), 631–652

  55. Mancosu N, Snyder LR, Kyriakakis G, Spano D (2015) Water scarcity and future challenges for food production. Water 7:975–992

  56. Masood J, Farooq F, Saeed M (2015) CO2 and environment change evidence from Pakistan. Rev Econ Dev Stud 1(2):57–72

  57. Massachusetts Institute of Technology (2016). Water problems in Asia’s future?. MIT News. [online] Cambridge, MA 02139-4307. http://news.mit.edu/2016/water-problems-asia-0330 . Accessed 12 Jul 2019

  58. McKinsey (2009) Charting our water future. [online] McKinsey & Company. https://www.mckinsey.com/businessfunctions/sustainability/our-insights/charting-our-water-future. Accessed 11 Jul. 2019

  59. Moon HR, Perron B (2004) Testing for a unit root in panels with dynamic factors. J Econ 122:81–126

  60. Neal T (2015) Estimating heterogeneous coefficients in panel data models with endogenous regressors and common factors. Workblacking Paper.

  61. Nechifor V, Winning M (2018) Global economic and food security impacts of demand-driven water scarcity—alternative water management options for a thirsty world. Water, 10(10), 1442.

  62. Ohlsson L, Appelgren B (1998) Water and social resource scarcity. Food and Agricultural Organization, Rome

  63. Okello C, Tomasello B, Greggio N, Wambiji N, Antonellini M (2015a) Impact of population growth and climate change on the freshwater resources of Lamu Island, Kenya. Water 7(3):1264–1290

  64. Okello C, Tomasello B, Greggio N, Wambiji N, Antonellini M (2015b) Impact of population growth and climate change on the freshwater resources of Lamu Island, Kenya. Water 7(3):1264–1290

  65. Oki T, Kanae S (2006) Global hydrological cycles and world water resources. Science 313(5790):1068–1072

  66. Pedroni P (1999) Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxf Bull Econ Stat 61:653–670

  67. Pedroni P (2000) Fully modified OLS for heterogeneous cointegrated panels. Adv Econ 15:93–130

  68. Pedroni P (2001) Purchasing power parity tests in cointegrated panels. Rev Econ Stat 83(4):727–731

  69. Pedroni P (2004) Panel cointegration. Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Economet Theor 20(3):597–625

  70. Perron P (1991) Test consistency with varying sampling frequency. Economet Theor 7(3):341–368

  71. Persyn D, Westerlund J (2008) Error-correction-based cointegration tests for panel data. Stata J 8(2):232–241

  72. Pesaran MH (2004) General diagnostic tests for cross section dependence in panels

  73. Pesaran MH (2006) Estimation and inference in large heterogenous panels with multifactor error structure. Econometrica 74(4), 967–1012

  74. Pesaran MH (2007) A simple panel unit root test in the presence of cross section dependence. J Appl Econ 22:265–312

  75. Pesaran MH, Smith R (1995a) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68(1):79–113

  76. Pesaran MH, Smith R (1995b) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68(1):79–113

  77. Pesaran MH, Shin Y, Smith RP (1999) Pooled mean group estimation of dynamic heterogeneous panels. J Am Stat Assoc 94(446):621–634

  78. Pieters H, Swinnen J (2016) Trading-off volatility and distortions? Food policy during price spikes. Food Policy, 61, 27–39

  79. Price G, Alam R, Hasan S, Humayun F, Kabir MH, Karki CS, ... & Shakya PR (2014) Attitudes to water in South Asia. Royal Institute of International Affairs

  80. Raskin I, Smith RD, Salt DE (1997) Phytoremediation of metals: using plants to remove pollutants from the environment. Curr Opin Biotechnol 8(2):221–226

  81. Robertson D, Symons J (2000) Factor residuals in SUR regressions: estimating panels allowing for cross sectional correlation (No. 473). Centre for Economic Performance, London School of Economics and Political Science

  82. Rosegrant MW, Ringler C, Zhu T (2009) Water for agriculture: maintaining food security under growing scarcity. Annu Rev Environ Resour 34(1):205–222

  83. Rudra N, Alkon M, Joshi S (2018) FDI, poverty, and the politics of potable water access. Econ Polit 30:366–393

  84. Schleich J, Hillenbrand T (2009) Determinants of residential water demand in Germany. Ecol Econ 68(6):1756–1769

  85. Schnoor JL (2011) Water–energy nexus. Environ Sci Technol. ACS Publications. 45:12, 50–65

  86. Seckler D, Amarasinghe U, Molden DJ, de Silva R, Barker R (1998) World water demand and supply, 1990 to 2025: Scenarios and Issues. IWMI Research Report 19. IWMI, Colombo

  87. Shiklomanov IA (2000) Appraisal and assessment of world water resources. Water Int 25(1):11–32

  88. Shiller, Perron (1985) Testing the random walk hypothesis: power versus frequency of observation. Econ Lett 18:381–386

  89. Smith LV, Leybourne S, Kim TH, Newbold P (2004) More powerful panel data unit root tests with an application to mean reversion in real exchange rates. Journal of Applied Econometrics, 19(2), 147–170.

  90. Stucki V, Sojamo S (2012) Nouns and numbers of the water–energy–security nexus in central Asia. Int J Water Resour Dev 28(3):2012

  91. Sun Y, Tong ST, Fang M, Yang YJ (2013) Exploring the effects of population growth on future land use change in the Las Vegas Wash watershed: an integrated approach of geospatial modeling and analytics. Environ Dev Sustain 15(6):1495–1515

  92. Surie M (2016) South Asia’s Water Crisis: A Problem of Scarcity Amid Abundance. [online] The Asia Foundation. Available at: https://asiafoundation.org/2015/03/25/south-asias-water-crisis-a-problem-of-scarcity-amid-abundance/. [Accessed 10 Jul. 2019].

  93. Thomas JS, Durham B (2003) Integrated water resource management: looking at the whole picture. Desalination 156(1–3):21–28

  94. Tsoutsos T, Frantzeskaki N, Gekas V (2005) Environmental impacts from the solar energy technologies. Energy Policy 33(3):289–296

  95. Turkay M (2017) Heterogeneity across emerging market central bank reaction functions. Cent Bank Rev 17(3):111–116

  96. Urbain JRYJ, Westerlund J (2006) Spurious regression in nonstationary panels with cross-unit cointegration

  97. Vanham D, Hoekstra AY, Bidoglio G (2013) Potential water saving through changes in European diets. Environ Int 61:45–56

  98. Vörösmarty CJ, Green P, Salisbury J, Lammers RB (2000) Global water resources: vulnerability from climate change and population growth. Science 289(5477):284–288

  99. Westerlund J (2006a) Testing for panel cointegration with a level break. Econ Lett 91:27–33

  100. Westerlund J (2006b) Testing for panel cointegration with multiple structural breaks. Oxf Bull Econ Stat 68:101–132

  101. Westerlund J, Edgerton DL (2007) A panel bootstrap cointegration test. Econ Lett 97(3):185–190

  102. Westerlund J, Edgerton DL (2008) A simple test for cointegration in dependent panels with structural breaks. Oxf Bull Econ Stat 70(5):665–704

  103. Water Shortages Slow Energy Production Worldwide. [online] The World Bank Group. https://www.worldbank.org/en/news/press-release/2014/01/20/water-shortages-energy-production-worldwide. Accessed 12 Jul 2019

  104. World Water Assessment Programme (UNESCO WWAP) (2015) World Water Development Report, Water for a Sustainable World

  105. Zhang C, Anadon LD (2013a) Life cycle water use of energy production and its environmental impacts in China. Environ Sci Technol 47(24):14459–14467

  106. Zhang C, Anadon LD (2013b) Life cycle water use of energy production and its environmental impacts in China. Environ Sci Technol 47(24):14459–14467

  107. Zheng H, Chiew FH, Charles S, Podger G (2018) Future climate and runoff projections across South Asia from CMIP5 global climate models and hydrological modelling. J Hydrol Reg Stud 18:92–109

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Correspondence to Hira Arain.

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Arain, H., Han, L. & Meo, M.S. Nexus of FDI, population, energy production, and water resources in South Asia: a fresh insight from dynamic common correlated effects (DCCE). Environ Sci Pollut Res 26, 27128–27137 (2019). https://doi.org/10.1007/s11356-019-05903-7

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Keywords

  • Water crisis
  • Cross-sectional dependence
  • Westerlund co-integration
  • FDI

JEL Classification

  • C01
  • F36
  • P23