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Climate change and economic growth: a heterogeneous panel data approach

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Abstract

Climate change is a global phenomenon. Its impact on economic growth must therefore be analyzed in accordance with its (time-varying) common effects. We present an econometric analysis that evaluates this effect taking into account its global nature. Contrary to previous evidence that ignores the global effects, we obtain that the rising temperature has not decreased growth in real GDP per capita in the second half of the twentieth century for the world countries. However, we obtain a negative effect of rising temperatures and a positive effect of rising precipitation in poor countries. This positive effect of rising precipitation is also confirmed for hot and temperate countries.

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Notes

  1. We have also performed tests without trends and results are confirmed. We should be clear that the non-stationary empirical strategy that we are following is appropriate to deal with empirical applications in which just some of the variables are non-stationary (see, e.g., Eberhardt and Teal 2011).

  2. There are however a number of countries with positive significant signs. Those are Belize, Dominican Republic, El Salvador, Haiti, Mauritania, Mozambique, Nigeria, Sierra Leone, Uganda in the regression of column 1 and Argentina, Dominican Republic, Germany, Jordan, Mozambique, and Saudi Arabia.

References

  • Banks AS, Wilson K (2015) Cross-national time-series data archive. Databanks International, Jerusalem. Available at http://www.databanksinternational.com

    Google Scholar 

  • Banerjee A, Carrion-i-Silvestre J (2011) Testing for panel cointegration using common correlated effects estimators. Paper presented at the 14th Applied Economics Meeting, Huelva

  • Barreca A, Clay K, Deschenes O, Greenstone M, Shapiro J (2013) Adapting to climate change: the remarkable decline in the U.S. temperature-mortality relationship over the 20th Century. NBER Working Paper, 18692

  • Bailey N, Kapetanios G, Pesaran MH (2016) Exponent of Cross? Sectional Dependence: Estimation and Inference. J Appl Econ 31:929–960. https://doi.org/10.1002/jae.2476

    Article  Google Scholar 

  • Burgess R, Donaldson D (2010) Can openness mitigate the effects of weather shocks? Evidence from India’s famine era. Am Econ Rev 100(2):449–53

    Article  Google Scholar 

  • Burke (2015) Global non-linear effect of temperature on economic production. Nature 527:235–239

    Article  CAS  Google Scholar 

  • Chudik A, Pesaran M (2013) Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Working Paper No. 146

  • Dell M, Jones B, Olken B (2012) Temperature shocks and economic growth: evidence from the last half century. American Journal of Economics: Macroeconomics 4(3):66–95

    Google Scholar 

  • Dell M, Jones B, Olken B (2014) What do we learn from the weather? The new climate—economy literature. J Econ Lit 52(3):740–798

    Article  Google Scholar 

  • Eberhardt M, Prebistero A (2015) Public debt and growth: heterogeneity and non-linearity. J Int Econ 97:45–58

    Article  Google Scholar 

  • Eberhardt M, Teal F (2011) Econometrics for grumblers: a new look at the literature on cross-country growth empirics. J Econ Surv 25(1):109–155

    Article  Google Scholar 

  • Feenstra R, Inklaar R, Timmer M (2015) The next generation of the Penn World Table. Am Econ Rev 105(10):3150–3182

    Article  Google Scholar 

  • Pesaran M (2004) General diagnostic tests for cross section dependence in panels. University of Cambridge, mimeo

  • Pesaran M (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74(4):967–1012

    Article  Google Scholar 

  • Pesaran M (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econ 22 (2):265–312

    Article  Google Scholar 

  • Pesaran M (2015) Testing weak cross-sectional dependence in large panels. Econ Rev 34(6-10):1089–1117

    Article  Google Scholar 

  • Waldinger M (2015) The economic effects of long-term climate change: evidence from the little ice age. Centre for Climate Change Economics and Policy Working Paper

Download references

Funding

Tiago Neves Sequeira (CEFAGE-UBI has financial support from FCT, Portugal, and FEDER/COMPETE 2020, through grant UID/ECO/04007/2013 (POCI-01-0145-FEDER-007659)).

Marcelo Serra Santos (CEFAGE-UBI has financial support from FCT, Portugal, and FEDER/COMPETE 2020, through grant UID/ECO/04007/2013 (POCI-01-0145-FEDER-007659)).

Manuela Magalhães received financial support from FCT (via POCI, project number 24068/2005), from the University of Warwick, from the University of Alicante, and from the Spanish Ministry of Economics and Competition (ECO2012-36719).

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Correspondence to Tiago Neves Sequeira.

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Responsible Editor: Philippe Garrigues

Appendix: A

Appendix: A

A.1 Panel unit-root tests

Table 7 Panel unit-root tests

A.2 Descriptive statistics

Table 8 Descriptive statistics for rich countries
Table 9 Descriptive statistics for poor countries
Table 10 Descriptive statistics for cold countries
Table 11 Descriptive statistics for temperate countries
Table 12 Descriptive statistics for hot countries

A.3 Samples

A.3.1 GDP variable sample

United Arab Emirates; Algeria; Albania; Angola; Argentina; Australia; Austria; Botswana; Belgium; Bahamas; Bangladesh; Belize; Bolivia; Myanmar; Benin; Brazil; Bhutan; Bulgaria; Burundi; Canada; Chad; Sri Lanka; Congo, Republic of; Congo, Dem. Rep.; China; Chile; Cameroon; Comoros; Colombia; Costa Rica; Central African Republic; Cape Verde; Cyprus; Denmark; Dominican Republic; Ecuador; Egypt; Ireland; El Salvador; Finland; Fiji; France; Gambia, The; Gabon; Ghana; Germany; Greece; Guatemala; Haiti; Honduras; Hungary; Iceland; Indonesia; India; Iran; Israel; Italy; Cote dÌvoire; Japan; Jamaica; Jordan; Kenya; Korea, Republic of; Kuwait; Liberia; Lesotho; Luxembourg; Madagascar; Mongolia; Malawi; Mali; Morocco; Mauritius; Mauritania; Oman; Mexico; Malaysia; Mozambique; Niger; Nigeria; Netherlands; Norway; Nepal; Suriname; South Africa; Nicaragua; New Zealand; Paraguay; Peru; Pakistan; Panama; Portugal; Guinea-Bissau; Romania; Philippines; Rwanda; Saudi Arabia; Senegal; Sierra Leone; Spain; Sudan; Sweden; Syria; Switzerland; Trinidad and Tobago; Thailand; Togo; Tunisia; Turkey; Uganda; UK; USA; Burkina Faso; Uruguay; St.Vincent and Grenadines; Venezuela; Swaziland; Zambia; Zimbabwe.

A.3.2 Industrial output sample

Argentina; Australia; Austria; Belgium; Bolivia; Brazil; Canada; Chile; Colombia; Costa Rica; Denmark; Dominican Republic; Ecuador; Ireland; El Salvador; Finland; France; Greece; Guatemala; Honduras; India; Israel; Italy; Japan; Jordan; Luxembourg; Morocco; Mexico; Netherlands; Norway; South Africa; Nicaragua; Paraguay; Peru; Panama; Portugal; Philippines; Spain; Sweden; Switzerland; Thailand; Turkey; UK; USA; Uruguay; Venezuela.

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Sequeira, T.N., Santos, M.S. & Magalhães, M. Climate change and economic growth: a heterogeneous panel data approach. Environ Sci Pollut Res 25, 22725–22735 (2018). https://doi.org/10.1007/s11356-018-2305-7

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