No Access

Amsterdam School of Economics, University of Amsterdam, P. O. Box 15867, 1001 NJ Amsterdam, The Netherlands

Department of Economics, University of Stellenbosch, South Africa

https://doi.org/10.1142/S0217590820500460Cited by:0 (Source: Crossref)

Abstract

Intermittently, Singapore suffers from severe air pollution in periods of intense forest and peatland fires on neighboring South-Asian islands. A recent American Economic Review article modeled the causal relationships between fire intensity in Indonesia and air pollution (PSI) in Singapore, and between PSI and health clinic visits in Singapore. We find serious flaws in the quantitative assessment of these relationships. Attempts are made to repair these using the same classic methodology and data, but also by alternative methods requiring less speculative assumptions. Although actually more detailed data are required, there are some results produced which seem more credible.

Keywords:

JEL: C12, C13, C26, I1, Q53

References

Andrews, I, J Stock and L Sun [2019] Weak instruments in IV regression: Theory and practice. Annual Review of Economics, 11, 727–753. Crossref, Web of Science, Google Scholar
Baum, CF, ME Schaffer and S Stillman [2007] Enhanced routines for instrumental variables/generalized method of moments estimation and testing. The Stata Journal, 7, 465–506. Crossref, Web of Science, Google Scholar
Bind, M-A [2019] Causal modeling in environmental health. Annual Review of Public Health, 40, 23–43. Crossref, Web of Science, Google Scholar
Cameron, AC and PK Trivedi [2005] Microeconometrics; Methods and Applications. Cambridge University Press. Crossref, Google Scholar
Dominici, F, M Greenstone and CR Sunstein [2014] Particulate matter matters. Science, 344, 257–259. Crossref, Web of Science, Google Scholar
Imbens, GW [2014] Instrumental Variables: An econometrician’s perspective. Statistical Science, 29, 323–358. Crossref, Web of Science, Google Scholar
Kiviet, JF [2017] Discriminating between (in)valid external instruments and (in)valid exclusion restrictions. Journal of Econometric Methods, 6, 1–9. Crossref, Google Scholar
Kiviet, JF (2020a). Testing the impossible: Identifying exclusion restrictions. To appear in The Journal of Econometrics, https://doi.org/10.1016/j.jeconom.2020.04.018. Google Scholar
Kiviet, JF (2020b). Instrument-free inference under confined regressor endogeneity; derivations and applications. Stellenbosch Working paper series no. WP09/2020. Google Scholar
Kiviet, JF and S Kripfganz (2020). Reassessment of classic case studies in labor economics with new instrument-free methods. Mimeo. https://sites.google.com/site/homepagejfk/ Google Scholar
Kripfganz, S and JF Kiviet [2020] Kinkyreg: Instrument-free inference for linear regression models with endogenous regressors. Community-Contributed Stata Program, Mimeo. http://www.kripfganz.de/research/Kripfganz_Kiviet_kinkyreg.html Google Scholar
Murray, MP [2006] Avoiding invalid instruments and coping with weak instruments. Journal of Economic Perspectives, 20, 111–132. Crossref, Web of Science, Google Scholar
Sheldon, TL and C Sankaran [2017] The impact of Indonesian forest fires on Singaporean pollution and health. American Economic Review, 107, 526–529. Crossref, Web of Science, Google Scholar
Quah, E [2002] Transboundary pollution in Southeast Asia: The Indonesian fires. World Development, 30, 429–441. Crossref, Web of Science, Google Scholar
Quah, E and WM Chia (2019). What the 2015 haze cost S’pore: $1.83 billion. The Straits Times, September 17. Google Scholar