Analisis Perang Dagang terhadap Lingkungan, Lestari atau Tercederai?

Dengan demikian kita dapat menarik kesimpulan bahwa jika perang dagang antara Amerika Serikat dan negara-negara lain terus berlanjut, kualitas lingkungan (EPI) akan terus menurun.

Referensi

1. Achim Z., & Torsten H. (2002). Diagnostic Checking in Regression Relationships. R News 2(3), 7-10. URL https://CRAN.R-project.org/doc/Rnews/
2. Adrian T., & Kurt H. (2018). tseries: Time Series Analysis and Computational Finance. R package version 0.10-46.
3. Antweiler W., Copeland B. R., & Taylor M. S. (2001). Is Free Trade Good for the Environment? American Economic Review,91(4), 877-908. doi:10.1257/aer.91.4.877
4. Bernard J. & Mandal S. K. (2016). The impact of trade openness on environmental quality: An empirical analysis of emerging and developing economies. Environmental Impact III. doi:10.2495/eid160181
5. Copeland B., & Taylor M. S. (2003). Trade, Growth and the Environment. doi:10.3386/w9823
6. Croissant Y., & Millo G. (2008). "Panel Data Econometrics in R: The plm Package." Journal of Statistical Software *27*(2), pp. 1-43. doi: 10.18637/jss.v027.i02 (URL: http://doi.org/10.18637/jss.v027.i02).
7. Grossman G., & Krueger A. (1991). Environmental Impacts of a North American Free Trade Agreement. doi:10.3386/w3914
8. Hadley W., & Jennifer B. (2018). readxl: Read  Excel Files. R package version 1.3.0.  https://CRAN.R-project.org/package=readxl
9. Hlavac, Marek. (2018). stargazer: Well-Formatted  Regression and Summary Statistics Tables. R package version 5.2.1. https://CRAN.R-project.org/package=stargazer
10. International Monetary Fund. (2018). World Economic Outlook; Challenges to Steady Growth October 2018. Washington D.C. : International Monetary Fund
11. Millo G,. (2017). "Robust Standard Error Estimators for Panel Models: A Unifying Approach." Journal of Statistical Software, *82*(3), 1-27. doi: 10.18637/jss.v082.i03 (URL: http:/doi.org/10.18637/jss.v082.i03)
12. R Core Team (2018). R: A language and environment for statistical  computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.