Run away? Air pollution and emigration interests in China


This paper investigates the impact of air pollution on people’s interest in emigration. Using an online search index on “emigration” which is positively correlated with its search volume, we develop a city-by-day measurement of people’s emigration sentiment. We find that searches on “emigration” will grow by approximately 2.3–4.8% the next day if today’s air quality index (AQI) is increased by 100 points. In addition, such an effect is more pronounced when the AQI level is above 200, a sign of “heavily polluted” and “severely polluted” days. We also find that such effect differs by destination countries and by metropolitan areas.

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    Regarding whether the net “brain drain effect” is detrimental or beneficial to the source country remains controversial. For example, Vidal (1998) suggests that emigration to a higher return to skills country may encourage people in the source country to invest in human capital; Chen (2006) argues that the relaxation of restrictions on the emigration of high-skilled workers will damage the economic growth of a source country in the long run, although a “brain gain” may happen in the short run. Beine et al. (2008) find that most countries combining low levels of human capital and low migration rates of skilled workers tend to be positively affected by the brain drain, whereas the brain drain appears to have negative growth effects in countries where the migration rate of the highly educated is above 20% and/or where the proportion of people with higher education is above 5%. Agrawal et al. (2011) indicate that the emigration of highly skilled individuals weakens local knowledge networks (brain drain) but may help remaining innovators access valuable knowledge accumulated abroad (brain bank).

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    Another example is that Chinese buyers spent more than 221 billion U.S. Dollars on property in the U.S. alone, between April 2013 and March 2014. See

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    A growing body of literature studies the health impacts of air pollution. For example, Chay and Greenstone (2003) and Currie and Walker (2011) estimate the significant effects of air pollution on the infant mortality rate, premature births, and low birth weight using the U.S. data. Schlenker and Walker (2015) focus on a shorter time span of the impacts and show the contemporaneous health impacts of air pollution for various population cohorts. Using China’s data, Chen et al. (2013) find that the higher concentration levels of total suspended particulate (TSP) due to the winter heating policy in north China is responsible for approximately 5.5 years of lower life expectancy. Zhang et al. (2015) show that air pollution significantly reduces short-term hedonic happiness.

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    We assume that emigration searches by people who have planned to move are less likely to be affected by temporary shocks, such as air pollution.

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    Although we do not use GT for our empirical analysis in this paper, it is worth noting that GT and Baidu Index have a very high correlation (0.84 and 0.78, respectively) when searching universities and companies in China as suggested by Vaughan and Chen (2015). In this paper, we assume that the search index algorithm is similar between Baidu Index and GT since Baidu does not publicize its methodology on constructing the Index.

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    The numbers refer to

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    We also collect data for six pollutants, namely PM2.5, SO2, NO2, PM10, CO, and O3. However, we still use the AQI as the major measurement of air quality in our analysis, because it scientifically considers the concentration levels of different pollutants. More importantly, in our data, we find that PM2.5 only accounts for about 45% of polluting days as a major pollutant. The other pollutants, such as PM10, O3, and NO2, accounts for about 27, 19, and 3.5% of polluting days as major pollutants, respectively. Therefore, pollutant-specific concentrations may not be representative enough as a measurement for overall air quality. Please refer to for the new Ambient air quality standard (GB3095-2012).

  13. 13.

    Please refer to Table 2 of the Technical Regulation on Ambient Air Quality Index available at

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    In our analysis, we find that the results from OLS regressions and Poisson regressions all point to similar conclusions.

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    To avoid the perfect multicollinearity problem in the regression, we omit the first category A Q I 1 in Eq. 2.

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    Please refer to Table 2 of the Technical Regulation on Ambient Air Quality Index available at

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    The impact of AQI on people’s emigration decision could be either physiological or behavioral or both. We try to disentangle these two mechanisms by conducting regression discontinuity style regressions at the cutoffs of various AQI levels to examine whether search intensity changes significantly right above and below the cutoff points. We find that the estimated coefficient is sensitive to the econometric setting of the regression discontinuity design, therefore we do not find robust evidence for the potential behavioral effects at the cutoffs. The results are available upon request.

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    We cannot cluster the standard errors at the city level as in previous regressions because there are only five cities with PM2.5 measurement from the U.S. Embassy and the Consulates. Therefore, we adopt robust standard errors for these regressions.

  19. 19.

    Please refer to Table 1 of the Technical Regulation on Ambient Air Quality Index available at

  20. 20.

    We check the robustness of our results using the concentration of each pollutant, including PM2.5, PM10, SO2, NO2, CO, and O3. The results are reported in Appendix Table 13. We find that the results are largely consistent with our main results in terms of both significance and magnitude. It should be noted that the coefficient on CO is much larger than the rest of the pollutants, because the mean value of the CO concentration is much lower than the other pollutants as shown in Table 1.

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    The accumulated number of emigrants is approximately 9.34 million by the end of 2013, of a total population of approximately 1.4 billion.


  1. Agrawal A, Kapur D, McHale J, Oettl A (2011) Brain drain or brain bank? the impact of skilled emigration on poor-country innovation. J Urban Econ 69 (1):43–55

    Article  Google Scholar 

  2. Askitas N, Zimmermann KF (2015) Health and well-being in the great recession. Int J Manpow 36(1): 26–47

    Article  Google Scholar 

  3. Beine M, Docquier F, Rapoport H (2008) Brain drain and human capital formation in developing countries: Winners and losers*. Econ J 118(528):631–652

    Article  Google Scholar 

  4. Brandt L, Rawski TG (2008) China’s great economic transformation. Cambridge university press

  5. Chay KY, Greenstone M (2003) The impact of air pollution on infant mortality: Evidence from geographic variation in pollution shocks induced by a recession. Q J Econ 118(3):1121–1167

    Article  Google Scholar 

  6. Chen H-J (2006) International migration and economic growth: a source country perspective. J Popul Econ 19(4):725–748

    Article  Google Scholar 

  7. Chen Y, Jin GZ, Kumar N, Shi G (2012) Gaming in air pollution data? lessons from China. BE J Econ Anal Policy 12(3)

  8. Chen Y, Ebenstein A, Greenstone M, Li H (2013) Evidence on the impact of sustained exposure to air pollution on life expectancy from China’s huai river policy. Proc Natl Acad Sci 110(32):12936–12941

    Article  Google Scholar 

  9. Choi H, Varian H (2012) Predicting the present with google trends. Econ Record 88(s1):2–9

    Article  Google Scholar 

  10. Currie J, Walker R (2011) Traffic congestion and infant health: Evidence from e-zpass. Am Econ J Appl Econ 3(1):65–90

    Article  Google Scholar 

  11. Currie J, Hanushek EA, Kahn EM, Neidell M, Rivkin SG (2009) Does pollution increase school absences? Rev Econ Stat 91(4):682–694

    Article  Google Scholar 

  12. Docquier F, Rapoport H (2012) Globalization, brain drain, and development. J Econ Lit, 681–730

  13. Goel S, Hofman JM, Lahaie S, Pennock DM, Watts DJ (2010) Predicting consumer behavior with web search. Proc Natl Acad Sci 107(41):17486–17490

    Article  Google Scholar 

  14. Graff Zivin J, Neidell M (2012) The impact of pollution on worker productivity. Am Econ Rev 102(7):3652–73

    Article  Google Scholar 

  15. Hatton TJ, Williamson JG (2002) What fundamentals drive world migration? Technical report, National Bureau of Economic Research

  16. He J, Liu H, Salvo A (2016) Severe air pollution and labor productivity: Evidence from industrial towns in china. IZA Discussion Paper No. 8916

  17. Hirshleifer D, Shumway T, et al (2003) Good day sunshine: Stock returns and the weather. J Financ, 58(3)

  18. Hunt J (2006) Staunching emigration from east Germany: Age and the determinants of migration. J Eur Econ Assoc 4(5):1014–1037

    Article  Google Scholar 

  19. Karemera D, Oguledo VI, Davis B (2000) A gravity model analysis of international migration to north america. Appl Econ 32(13):1745–1755

    Article  Google Scholar 

  20. Kearney MS, Levine PB (2015) Media influences on social outcomes: the impact of mtv’s 16 and pregnant on teen childbearing. Am Econ Rev 105(12):3597–3632

    Article  Google Scholar 

  21. Mayda AM (2010) International migration: a panel data analysis of the determinants of bilateral flows. J Popul Econ 23(4):1249–1274

    Article  Google Scholar 

  22. Mu Q, Zhang J (2014) Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks. Available at SSRN 2518032

  23. Ortega F, Peri G (2009) The causes and effects of international migrations: Evidence from oecd countries 1980-2005. Technical report, National Bureau of Economic Research

  24. Saunders EM (1993) Stock prices and wall street weather. Am Econ Rev, 1337–1345

  25. Schneider F (2015) Does corruption promote emigration? IZA World of Labor

  26. Schlenker W, Walker WR (2015) Airports, air pollution, and contemporaneous health. Rev Econ Stud 83(2):768–809

    Article  Google Scholar 

  27. Stafford TM (2015) Indoor air quality and academic performance. J Environ Econ Manag 70:34–50

    Article  Google Scholar 

  28. Sun C, Kahn ME, Zheng S (2017) Self-protection investment exacerbates air pollution exposure inequality in urban China. Ecol Econ 131:468–474

    Article  Google Scholar 

  29. Tefft N (2011) Insights on unemployment, unemployment insurance, and mental health. J Health Econ 30(2):258–264

    Article  Google Scholar 

  30. Vaughan L, Chen Y (2015) Data mining from web search queries: a comparison of google trends and baidu index. J Assoc Inf Sci Technol 66(1):13–22

    Article  Google Scholar 

  31. Viard VB, Fu S (2015) The effect of beijing’s driving restrictions on pollution and economic activity. J Public Econ 125:98–115

    Article  Google Scholar 

  32. Vidal J-P (1998) The effect of emigration on human capital formation. J Popul Econ 11(4):589–600

    Article  Google Scholar 

  33. Zhang X, Zhang X, Chen X (2015) Happiness in the air: How does a dirty sky affect subjective well-being? IZA Discussion Paper No. 9312.

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We are grateful to Sumit Agarwal, Yongheng Deng, Shuaizhang Feng, Shihe Fu, Xiaobo Zhang, Klaus F. Zimmermann (the Editor), two anonymous reviewers, and seminar participants at the National University of Singapore for their valuable comments and suggestions. Thanks to Qingyue Open Environmental Data Center ( for support on Environmental data processing. Qin acknowledges financial support from the Academic Research Fund - Tier 1 (WBS: R-297-000-129-133). Zhu acknowledges financial support from the National Natural Science Foundation of China (Project 71603103). All remaining errors are ours.

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Correspondence to Yu Qin.

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This study was funded by Ministry of Education, Singapore (grant number R-297-000-129-133) and the National Natural Science Foundation of China (grant number 71603103).

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Responsible editor: Klaus F. Zimmermann


Appendix Figure

Fig. 7

Linear relationship between search volume and Baidu Index. Data source:

Appendix Table

Table 13 Impacts of Different Pollutants on Baidu Index of “Emigration”

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Qin, Y., Zhu, H. Run away? Air pollution and emigration interests in China. J Popul Econ 31, 235–266 (2018).

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  • Emigration
  • Air pollution
  • China
  • Online searches

JEL Classification

  • Q53
  • Q56
  • R23