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Revalidation of temperature changes on economic impacts: a meta-analysis


To identify appropriate strategies for temperature change adaptation, the economic impacts of temperature changes are critical to be understood. Despite a wide investigation about this issue, the obtained evidence is still mixed, including positive linear, negative linear, U-shaped, inverted U-shaped, or even irrelevant relationships. To address this question, we investigated the findings of collected studies through a meta-analysis based on 87 studies with 2977 estimates. We first examined the genuine effects between temperature changes and economic impacts based on statistical models (i.e., funnel plots, MST and FAT-PET-PEESE tests). Then, we adopted the meta-regression method to identify the sensitive modeling characteristics influencing the research outcomes. The results illustrate four major conclusions. First, there is a negative relationship between temperature changes and economic outputs in linear regression analysis, and an inverted U-shaped relationship in quadratic regression specifications. Second, research areas and temperature variables involved in individual studies have significant effects on current economic consequence analysis. Particularly, rich countries located in colder climates can even benefit from temperature changes, whereas poor countries located in hotter climates suffered adverse impacts. Third, the resilience factors should be involved in future prediction models to investigate the mitigation effects. Fourth, the sensitive modeling specifications were different according to different research sub-objects. The results obtained can provide implications for the sustainable development of the economy and human society caused by climatic change, and can also make contributions to advance the theory and practice of future temperature change consequence analysis.

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Fig. 1

Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.


  1. 1.

    Primary sectors, secondary sectors, and tertiary sectors in this paper referred to agriculture, manufacturing, and services, respectively.

  2. 2.

    If there were no clear t-values in the original studies, but both the regression coefficient and the standard error were presented, then t-value = regression coefficient/standard error. For ease of discussion, this paper reports t-values always in a way that “negative” impact means that the costs of temperature changes were larger. However, if the studies investigated the relationship between temperature changes and diseases or deaths, then the positive t-values indicated that temperature changes were positively correlated with the effects of diseases and deaths. Therefore, we changed the signs of the coefficients to evaluate them between different studies.

  3. 3.

    Due to the word limit, Appendix Table 1–4 and Appendix Figure 1–5 were included in the supplementary materials.

  4. 4.

    Two stepwise regression models were performed (forward-stepwise and backward-stepwise) to extract variables at 5% level of significance.

  5. 5.

    Due to the small number of estimates from quadratic regression analysis, the funnel plots of quadratic regression analysis were performed between temperature changes and aggregate output, human capital, and the output of primary sectors. Also, the meta-regression analysis on different research objects was performed based on estimates derived from linear regression analysis.


  1. Acevedo S, Mrkaic M, Novta N, Pugacheva E, Topalova P (2020) The effects of weather shocks on economic activity: what are the channels of impact? J Macroecon 65:103207

    Article  Google Scholar 

  2. Beine M, Jeusette L (2019) A meta-analysis of the literature on climate change and migration. No 12639, IZA discussion papers, Institute of Labor Economics (IZA)

  3. Cai X, Lu Y, Wang J (2018) The impact of temperature on manufacturing worker productivity: evidence from personnel data. J Comp Econ 46:889–905

    Article  Google Scholar 

  4. Challinor AJ, Watson J, Lobell DB, Howden S, Smith D, Chhetri N (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Chang 4:287–291

    Article  Google Scholar 

  5. Chandio AA, Jiang Y, Rehman A, Rauf A (2020) Short and long-run impacts of climate change on agriculture: an empirical evidence from China. Int J Clim Chang Strateg Manag 12(2):201–221

    Article  Google Scholar 

  6. Chen X, Yang L (2019) Temperature and industrial output: firm-level evidence from China. J Environ Econ Manag 95:257–274

    Article  Google Scholar 

  7. Colacito R, Hoffmann B, Phan T (2019) Temperature and growth: a panel analysis of the United States. J Money Credit Bank 51:313–368

    Article  Google Scholar 

  8. Copiello S, Grillenzoni C (2020) Economic development and climate change. Which is the cause and which the effect? Energy Rep 6:49–59

    Article  Google Scholar 

  9. Cui X (2020) Climate change and adaptation in agriculture: evidence from US cropping patterns. J Environ Econ Manag 101:102306

    Article  Google Scholar 

  10. Dell M, Jones BF, Olken BA (2008) Climate change and economic growth: Evidence from the last half century. NBER Working Paper No. 14132, National Bureau of Economic Research. Available at

  11. Falco C, Galeotti M, Olper A (2019) Climate change and migration: is agriculture the main channel? Glob Environ Chang 59:101995

    Article  Google Scholar 

  12. Fisher AC, Hanemann WM, Roberts MJ, Schlenker W (2012) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather: comment. Am Econ Rev 102:3749–3760

    Article  Google Scholar 

  13. Glass GV (1976) Primary, secondary, and meta-analysis of research. Educ Res 5:3–8

    Article  Google Scholar 

  14. Grotjahn R, Black R, Leung R, Wehner MF, Barlow M, Bosilovich M, Gershunov A, Gutowski WJ, Gyakum JR, Katz RW (2016) North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends. Clim Dyn 46:1151–1184

    Article  Google Scholar 

  15. Gunby P, Jin Y, Reed WR (2017) Did FDI really cause Chinese economic growth? A meta-analysis. World Dev 90:242–255

    Article  Google Scholar 

  16. Gurevitch J, Koricheva J, Nakagawa S, Stewart G (2018) Meta-analysis and the science of research synthesis. Nature 555:175–182

    Article  Google Scholar 

  17. Havranek T, Irsova Z (2017) Do borders really slash trade? A meta-analysis. IMF Econ Rev 65:365–396

    Article  Google Scholar 

  18. He J, Su Y, Fang X (2020) To what extent did changes in temperature affect China’s socioeconomic development from the Western Han Dynasty to the Five Dynasties period? J Quat Sci 35:433–443

    Article  Google Scholar 

  19. Henseler M, Schumacher I (2019) The impact of weather on economic growth and its production factors. Clim Chang 154:417–433

    Article  Google Scholar 

  20. Hsiang SM (2010) Temperatures and cyclones strongly associated with economic production in the Caribbean and Central America. Proc Natl Acad Sci U S A 107:15367–15372

    Article  Google Scholar 

  21. Hsiang S, Kopp R, Jina A, Rising J, Delgado M, Mohan S, Rasmussen D, Muir-Wood R, Wilson P, Oppenheimer M (2017) Estimating economic damage from climate change in the United States. Science 356:1362–1369

    Article  Google Scholar 

  22. Jain A, O'Sullivan R, Taraz V (2020) Temperature and economic activity: evidence from India. J Environ Sci Policy 9:430–446

    Google Scholar 

  23. Knox J, Hess T, Daccache A, Wheeler T (2012) Climate change impacts on crop productivity in Africa and South Asia. Environ Res Lett 7:034032

    Article  Google Scholar 

  24. Korhonen M, Kangasraasio S, Svento R (2019) Do people adapt to climate change? Evidence from the industrialized countries. Int J Clim Chang Strateg Manag 11(1):54–71

    Article  Google Scholar 

  25. Lanzafame M (2014) Temperature, rainfall and economic growth in Africa. Empir Econ 46:1–18

    Article  Google Scholar 

  26. Lazzaroni S, van Bergeijk PA (2014) Natural disasters’ impact, factors of resilience and development: a meta-analysis of the macroeconomic literature. Ecol Econ 107:333–346

    Article  Google Scholar 

  27. Melo PC, Graham DJ, Noland RB (2009) A meta-analysis of estimates of urban agglomeration economies. Reg Sci Urban Econ 39(3):332–342

    Article  Google Scholar 

  28. Mendelsohn R, Nordhaus WD, Shaw D (1994) The impact of global warming on agriculture: a Ricardian analysis. Am Econ Rev 84:753–771

    Google Scholar 

  29. Miles J (2005) Tolerance and variance inflation factor. In: Everitt BS, Howell D (eds) Encyclopedia of statistics in behavioral science. Wiley, Hoboken, NJ

    Google Scholar 

  30. Moore FC, Diaz DB (2015) Temperature impacts on economic growth warrant stringent mitigation policy. Nat Clim Chang 5:127–131

    Article  Google Scholar 

  31. Ng P, Zhao X (2011) No matter how it is measured, income declines with global warming. Ecol Econ 70:963–970

    Article  Google Scholar 

  32. Nomura S, Blangiardo M, Tsubokura M, Nishikawa Y, Gilmour S, Kami M, Hodgson S (2016) Post-nuclear disaster evacuation and survival amongst elderly people in Fukushima: a comparative analysis between evacuees and non-evacuees. Prev Med 82:77–82

    Article  Google Scholar 

  33. Peterson TC, Heim RR Jr, Hirsch R, Kaiser DP, Brooks H, Diffenbaugh NS, Dole RM, Giovannettone JP, Guirguis K, Karl TR (2013) Monitoring and understanding changes in heat waves, cold waves, floods, and droughts in the United States: state of knowledge. Bull Am Meteorol Soc 94:821–834

    Article  Google Scholar 

  34. Pretis F, Schwarz M, Tang K, Haustein K, Allen MR (2018) Uncertain impacts on economic growth when stabilizing global temperatures at 1.5 C or 2 C warming. Proc Math Phys Eng Sci A 376:20160460

    Google Scholar 

  35. Šedová B, Čizmaziová L, Cook A (2021) A meta-analysis of climate migration literature. CEPA Discussion Papers No. 29, Center for Economic Policy Analysis. Available at

  36. Seetanah B, Fauzel S (2019) Investigating the impact of climate change on the tourism sector: evidence from a sample of island economies. Tour Rev 74(2):194–203

    Article  Google Scholar 

  37. Stanley TD (2008) Meta-regression methods for detecting and estimating empirical effects in the presence of publication selection. Oxf Bull Econ Stat 70:103–127

    Google Scholar 

  38. Stanley TD, Doucouliagos H (2014) Meta-regression approximations to reduce publication selection bias. Res Synth Methods 5:60–78

    Article  Google Scholar 

  39. Stanley TD, Doucouliagos C, Jarrell SB (2008) Meta-regression analysis as the socio-economics of economics research. J Socio-Econ 37:276–292

    Article  Google Scholar 

  40. World Meteorological Organization (2020). The state of the global climate 2020. Available online at:

  41. Zhang P, Deschenes O, Meng K, Zhang J (2018) Temperature effects on productivity and factor reallocation: evidence from a half million Chinese manufacturing plants. J Environ Econ Manag 88:1–17

    Article  Google Scholar 

  42. Zhou L, Chen Z (2020) Are CGE models reliable for disaster impact analyses? Econ Syst Res 33:20–46

    Article  Google Scholar 

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The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first author would like to acknowledge the financial support from the China Scholarship Council (CSC) scholarship, No. 201908320518, the National Social and Scientific Fund Program of China (16ZDA047, 18ZDA052).

Author information




All of the authors contributed to the study conception and design. Ling Tan: conceptualization, software, methodology, and writing—original draft; Kun Zhou: data collecting and methodology; Hui Zheng: methodology and language modification; Lianshui Li: guidance, review, and editing.

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Correspondence to Ling Tan.

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Tan, L., Zhou, K., Zheng, H. et al. Revalidation of temperature changes on economic impacts: a meta-analysis. Climatic Change 168, 7 (2021).

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  • Temperature change
  • Economic impact
  • Meta-analysis
  • Empirical research