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A Nonlinear Panel ARDL Analysis of Pollution Haven/Halo Hypothesis

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Advances in Econometrics, Operational Research, Data Science and Actuarial Studies

Part of the book series: Contributions to Economics ((CE))

Abstract

There is a growing popularity for the nonlinear econometric approaches, since linkages among variables are not always linear. Nonlinear approaches provide a broader range of knowledge compared to the linear model. This research aims to assess the impact of foreign direct investment on pollution. To capture the potential asymmetries resulting from rise and fall in the foreign direct investments, the nonlinear panel autoregressive distributed lag approach is employed. In the empirical analysis, annual data of selected 22 transition economies from 1995 to 2016 is utilized. The findings highlighted the existence of asymmetric linkages among variables. In other words, evidence reveals that positive shock in foreign direct investment improves environmental quality, while the negative shock is detrimental to the environment.

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References

  • Altug S, Ashley R, Patterson DM (1999) Are technology shocks nonlinear? Macroecon Dyn 3(4):506–533

    Google Scholar 

  • Atil A, Lahiani A, Nguyen DK (2014) Asymmetric and nonlinear pass-through of crude oil prices to gasoline and natural gas prices. Energy Policy Elsevier 65(C):567–573

    Google Scholar 

  • Baek J (2016) A new look at the FDI–income–energy–environment nexus: dynamic panel data analysis of ASEAN. Energy Policy 91:22–27

    Google Scholar 

  • Bakirtaş I, Çetin MA (2017) Revisiting the environmental Kuznets curve and pollution haven hypotheses: MIKTA sample. Environ Sci Pollut Res 24(22):18273–18283. https://doi.org/10.1007/s11356-017-9462-y. Epub PMID: 28639013

  • Balke N, Fomby T (1997) Threshold cointegration. Int Econ Rev 38(3):627–645. https://doi.org/10.2307/2527284

    Google Scholar 

  • Balsalobre-Lorente D, Gokmenoglu KK, Taspinar N, Cantos-Cantos JM (2019) An approach to the pollution haven and pollution halo hypotheses in MINT countries. Environ Sci Pollut Res 26:23010–23026. https://doi.org/10.1007/s11356-019-05446-x

    Google Scholar 

  • Baltagi BH, Pesaran MH (2007) Heterogeneity and cross section dependence in panel data models: theory and application. J Appl Economet 22(2):229–232

    Google Scholar 

  • Baltagi BH, Griffin JM, Xiong W (2000) To pool or not to pool: homogeneous versus heterogeneous estimators applied to cigarette demand. Rev Econ Stat 82(1):117–126

    Google Scholar 

  • Blackburne EF, Frank MW (2007) Estimation of nonstationary heterogeneous panels. Stand Genomic Sci 7(2):197–208. https://doi.org/10.1177/1536867X0700700204

    Google Scholar 

  • Canepa A, Chini EZ, Alqaralleh H (2019) Global cities and local housing market cycles. J R Estate Financ Econ 1–27. https://doi.org/10.1007/s11146-019-09734-8

  • Favara G (2003) An empirical reassessment of the relationship between finance and growth. IMF, Washington, DC

    Google Scholar 

  • Gaibulloev K, Sandler T, Sul D (2014) Dynamic panel analysis under cross-sectional dependence. Polit Anal 22:258–273. https://doi.org/10.1093/pan/mpt029

    Google Scholar 

  • Grandmont JM (1985) On endogenous competitive business cycles. Econometrica 53:995–1045

    Google Scholar 

  • Granger CWJ, Yoon G (2002) Cointegration. University of California, Economics Working Paper No. 2002-02. https://ssrn.com/abstract=313831. https://doi.org/10.2139/ssrn.313831

  • Guzel AE, Okumus I (2020) Revisiting the pollution haven hypothesis in ASEAN-5 countries: new insights from panel data analysis. Environ Sci Pollut Res 27:18157–18167. https://doi.org/10.1007/s11356-020-08317-y

    Google Scholar 

  • Hall R (1990) Invariance properties of Solow's productivity residual. In: Diamond P (ed) Growth/productivity/employment. MIT Press, Cambridge

    Google Scholar 

  • Hao Y, Liu YM (2015) Has the development of FDI and foreign trade contributed to China’s CO2 emissions? An empirical study with provincial panel data. Nat Hazards 76:1079–1091. https://doi.org/10.1007/s11069-014-1534-4

    Google Scholar 

  • Hausman JA (1978) Specification tests in econometrics. Econometrica 46(6):1251–1271

    Google Scholar 

  • Hinich MJ, Mendes EM, Stone L (2005) Detecting nonlinearity in time series: surrogate and bootstrap approaches. Stud Nonlinear Dyn Econo 9(4):1–13

    Google Scholar 

  • Işik C, Kasımatı E, Ongan S (2017) Analyzing the causalities between economic growth, financial development, international trade, tourism expenditure and the CO2 emissions in Greece. Energy Sources Part B Econ Plan Policy 12:665–673. https://doi.org/10.1080/15567249.2016.1263251

    Google Scholar 

  • Jensen VM (1996) Trade and environment: the pollution haven hypothesis and the industrial flight hypothesis; some perspectives on theory and empirics. University of Oslo, Centre for Development and the Environment, Norway

    Google Scholar 

  • Keynes JM (1936) The general theory of employment, interest and money. Macmillan, London

    Google Scholar 

  • Kim TH, Lee YS, Newbold P (2004) Spurious nonlinear regressions in econometrics. School of Economics, University of Nottingham, Nottingham NG7 2RD, UK

    Google Scholar 

  • Koop G, Potter SM (2001) Are apparent findings of nonlinearity due to structural instability in economic timeseries? Economet J 4(1):37–55

    Google Scholar 

  • Kotchoni R (2018) Detecting and Measuring Nonlinearity. Econometrics 6(37):1–27

    Google Scholar 

  • Lau LS, Choong CK, Eng YK (2014) Investigation of the environmental Kuznets curve for carbon emissions in Malaysia: do foreign direct investment and trade matter? Energy Policy 68:490–497

    Google Scholar 

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

    Google Scholar 

  • Liew VKS, Chong TTL, Lim KP (2003) The inadequacy of linear autoregressive model for real exchange rates: empirical evidence from Asian economies. Appl Econ 35:1387–1392

    Google Scholar 

  • Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and a new simple test. Oxford Bull Econ Stat 61:631–665

    Google Scholar 

  • Mensi W, Shahzad SJH, Hammoudeh S, Hamed A-YK (2017) Asymmetric impacts of public and private investments on the non-oil GDP of Saudi Arabia. Int Econ 156:1–16. https://doi.org/10.1016/j.inteco.2017.10.003

    Google Scholar 

  • Merican Y, Yusop Z, Noor ZM, Hook LS (2007) Foreign direct investment and the pollution in five ASEAN nations. Int J Econ Manag 1(2):245–261

    Google Scholar 

  • Mert M, Bölük G (2016) Do foreign direct investment and renewable energy consumption affect the CO2 emissions? New evidence from a panel ARDL approach to Kyoto Annex countries. Environ Sci Pollut Res 23:21669–21681. https://doi.org/10.1007/s11356-016-7413-7

    Google Scholar 

  • Mert M, Caglar AE (2020) Testing pollution haven and pollution halo hypotheses for Turkey: a new perspective. Environ Sci Pollut Res 27:32933–32943. https://doi.org/10.1007/s11356-020-09469-7

    Google Scholar 

  • Mihajlović V, Marjanović G (2020) Asymmetries in effects of domestic inflation drivers in the Baltic states: a Phillips curve-based nonlinear ARDL approach. Balt J Econ 20(1):94–116. https://doi.org/10.1080/1406099X.2020.1770946

    Google Scholar 

  • Munir Q, Kok SC (2015) Purchasing power parity of ASEAN-5 countries revisited: heterogeneity, structural breaks and cross-sectional dependence. Glob Econ Rev 44(1):116–149. https://doi.org/10.1080/1226508X.2015.1012091

    Google Scholar 

  • Nguyen CP, Schinckus C, Su TD (2020) Economic integration and CO2 emissions: evidence from emerging economies. Clim Dev 12(4):369–384. https://doi.org/10.1080/17565529.2019.1630350

    Google Scholar 

  • O’Connell PGJ (1998) The overvaluation of purchasing power parity. J Int Econ 44:1–20

    Google Scholar 

  • Öztürk Z, Öz D (2016) The Relationship between energy consumption, income, foreign direct investment, and CO2 emissions: the case of Turkey. Çankırı Karatekin Üniversitesi İİBF Dergisi 6(2):269–288

    Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  • Pesaran MH, Shin Y, Smith RP (1999) Pooled mean group estimation of dynamic heterogeneous panels. J Am Stat Assoc 94:621–634. https://doi.org/10.1080/01621459.1999.10474156

    Google Scholar 

  • Pesaran MH, Shin Y, Smith RJ (2001) Bounds testing approaches to the analysis of level relationships. J Appl Econ 16:289–326

    Google Scholar 

  • Pesaran MH, Shin Y, Smith RP (2004) Pooled mean group estimation of dynamic heterogeneous panels. ESE Discussion Papers No: 16

    Google Scholar 

  • Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. Working Paper No: 0435, University of Cambridge

    Google Scholar 

  • Rafindadi AA, Muye IM, Kaita RA (2018) The effects of FDI and energy consumption on environmental pollution in predominantly resource-based economies of the GCC. Sustain Energy Technol Assess 25:126–137

    Google Scholar 

  • Rahman UR, Chongbo W, Ahmad M (2019) An (a)symmetric analysis of the pollution haven hypothesis in the context of Pakistan: a non-linear approach. Carbon Manag 10(3):227–239. https://doi.org/10.1080/17583004.2019.1577179

    Google Scholar 

  • Sapkota P, Bastola U (2017) Foreign direct investment, income, and environmental pollution in developing countries: Panel data analysis of Latin America. Energy Econ 64:206–212

    Google Scholar 

  • Schorderet Y (2003) Asymmetric cointegration. Working paper No: 2003.01, University of Geneva

    Google Scholar 

  • Shahbaz M, Nasir MA, Roubaud D (2018) Environmental degradation in France: the effects of FDI, financial development, and energy innovations. Energy Econ 74:843–857

    Google Scholar 

  • Shin Y, Yu B, Greenwood-Nimmo M (2014) Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. Festschrift in honor of Peter Schmidt. Springer, New York, pp 281–314

    Google Scholar 

  • Sichel DE (1993) Business cycle asymmetry: a deeper look. Econ Inq 31(2):224–236

    Google Scholar 

  • Solarin SA, Al-Mulali U, Musah I, Ozturk I (2017) Investigating the pollution haven hypothesis in Ghana: an empirical investigation. Energy (Elsevier) 124(C):706–719

    Google Scholar 

  • Sun C, Zhang F, Xu M (2017) Investigation of pollution haven hypothesis for China: an ARDL approach with breakpoint unit root tests. J Clean Prod 161:153–164

    Google Scholar 

  • Tang CF, Tan BW (2015) The impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in Vietnam. Energy 79:447–454

    Google Scholar 

  • U.S. Energy information database. https://www.eia.gov/. Accessed 15 Sept 2020

  • Union of Concerned Scientists Data (2020) https://www.ucsusa.org/resources/each-countrys-share-co2-emissions. Accessed 1 Oct 2020

  • World Bank database. www.worldbank.org. Accessed 21 Sept 2020

  • Yavuz NÇ, Yilanci V (2012) Testing for nonlinearity in G7 macroeconomic time series. Rom J Econ Forecast 3:69–79

    Google Scholar 

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Authors and Affiliations

  1. Department of Econometrics, Marmara University, Istanbul, Turkey

    Ebru Çağlayan-Akay

  2. Department of Economics, Kyrgyz-Turkish Manas University, Bishkek, Kyrgyzstan

    Zamira Oskonbaeva

Authors
  1. Ebru Çağlayan-Akay
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  2. Zamira Oskonbaeva
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Corresponding author

Correspondence to Zamira Oskonbaeva .

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Editors and Affiliations

  1. Faculty of Economics and Admin. Sciences, Trakya University, Edirne, Turkey

    M. Kenan Terzioğlu

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Çağlayan-Akay, E., Oskonbaeva, Z. (2022). A Nonlinear Panel ARDL Analysis of Pollution Haven/Halo Hypothesis. In: Terzioğlu, M.K. (eds) Advances in Econometrics, Operational Research, Data Science and Actuarial Studies. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-85254-2_11

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