Class location: Zoom (link on Canvas)
Class time: Tues/Thurs 3:00-4:15
Office hours: Tues/Thurs 4:20-4:50 (link on Canvas)
Teaching assistant: Diego Cardoso
TA office hours: Mon 3:00-4:00 (link on Canvas)
Textbook: A Course in Environmental Economics by Phaneuf and Requate is required. Causal Inference: The Mixtape by Cunningham is also required and free.
Prerequisites: MATH 1110 or equivalent.
Course description: An introduction to environmental economics. The first half of the class focuses on the core theory, theory of regulation, and theory of welfare analysis. The second half of the course covers empirical topics. We will be learning how to use R for empirical research in environmental economics.
Course requirements: Students are expected to attend the Zoom class sessions if they are in a reasonable timezone. If you are not (e.g. 12 hour difference) you may take the course asynchronously. Students are expected to prepare for class, prelims, and complete problem sets outside of class.
- Prelims: 30% and 25%
- Problem sets: 20%
- Final project paper: 20%
- Final project presentation: 5%
The grading scale is:
- A: 92-100; A-: 90-91
- B+: 88-89; B: 82-87; B-: 80-81
- C+: 78-79; C: 72-77; C-: 70-71
- D+: 68-69; D: 62-67; D-: 60-61
- F: < 60
There will be 2 prelims. You will have 24 hours for the theory prelim. You will have 48 hours for the empirical prelim. The class time is reserved for Zoom office hours for any questions. You are expected to complete the prelims on your own, not in groups. Your higher-scoring prelim will be 30% of your grade, your lower-scoring prelim will be 25% of your grade. If you miss a prelim without an acceptable excuse you will receive a zero. If you have an acceptable excuse (these must be brought in beforehand except for sickness, injuries, accidents, etc) an alternative prelim will be scheduled. If you miss a prelim and do not notify me beforehand you must have a valid document (doctor's note, etc) explaining why you missed class and were not able to let me know before the missed prelim. Prelims submitted late will have a 30% deduction.
You will have 4 problem sets. You may work in groups of up to 3 on problem sets. Problem sets may be turned in late with a penalty of 20% of that homework's grade for each day it is late. Problem sets are due at the start of class on Canvas.
For your final project you can choose between a literature review or a data dive. Descriptions of both are below and more details will come a few weeks into the semester.
You can do a literature review on up to 5 papers on an environmental, resource, or energy economics topic of your choice. Your goal will be to summarise the findings, find common threads, and work yet to be done in the area. In the last two weeks of class you will give a short presentation of your review of the literature. Papers are due after the semi-final period. My approval of your choice of papers is required before you start the literature review.
You can find a new dataset that we do not cover in class but appears useful for environmental economics research. Your goal is to describe the data, how you get them, how you use them, and what makes them relevant. You will also need to do some preliminary analysis on the data. In the last two weeks of class you will give a short presentation of the data and your preliminary analysis. Papers are due after the semi-final period. My approval of your choice of dataset is required before you start the literature review.
Some sections of the course have readings (available on Canvas if not in the book or through the library). The lectures, homeworks and exams will draw from these readings. Lecture notes will be posted online at the end of each section.
- Theory prelim: October 13
- Empirical prelim: December 3
- Final project paper due: December 16
- Final project presentations: December 8, 10, 15
Attendance: Class attendance is not explicitly required but highly recommended.
Grade appeals: If you wish to appeal your grade on a prelim or problem you must bring it to my attention, in writing, within 24 hours of when the prelim or problem set is returned. Grades brought to my attention after this will not be eligible for a grade appeal. I reserve the right to regrade the entire assignment and the new grade will be final.
Group work: For problem sets, you may consult with me or Diego during office hours, or with other students. Problem sets can done in groups of up to 3. If you work in a group, turn in only one assignment for the group. You must complete prelims without help.
Integrity of credit: I expect every student in this course to abide by the Cornell University Code of Academic Integrity. I strongly encourage collaboration in this course, but each student is responsible for making sure that she or he follows the rules laid out in this syllabus, and with those stated in the Code of Academic Integrity. Any student found to have violated the stated policies on problem sets will receive a zero for that assignment, and any student found to have cheated on a prelim will receive a zero on that prelim. Multiple violations in a semester may result in failure of the course. The Code of Academic Integrity is available for review here: https://cuinfo.cornell.edu/aic.cfm.
Sep 3: Micro and math recap [slides posted]
Reading: None
Sep 8: Theory of externalities [slides posted]
Reading: PR Chapter 1
Sep 10: Introduction to the theory of environmental policy [slides posted]
Reading: PR Chapter 3
Sep 15: Imperfect information [slides posted]
Reading: PR Chapter 4.1.1-4.1.2
Sep 17: Competitive output markets [slides posted]
Reading: PR Chapter 5
Sep 22: Non-competitive output markets [slides posted]
Reading: PR Chapter 6
Sep 24: Pre-existing distortions [slides posted]
Reading: PR Chapter 7
Sep 29: Theory of applied welfare economics [slides posted]
Reading: PR Chapter 14
Oct 1: Theory of applied welfare economics [slides posted]
Reading: PR Chapter 14
Oct 6: Revealed preference models [skipped]
Reading: PR Chapter 15
Oct 8: Hedonics [slides posted]
Reading: PR Chapter 18
Oct 15: R and the tidyverse, causal inference [slides posted]
Reading:
- Mixtape: properties of regression, directed acyclical graphs, potential outcomes causal model
- Greenstone, M. and Gayer, T., 2009. Quasi-experimental and experimental approaches to environmental economics. Journal of Environmental Economics and Management, 57(1), pp.21-44.
We will be using RStudio Cloud for computing.
Reading:
- Mixtape: properties of regression, directed acyclical graphs, potential outcomes causal model
- Guiteras, Raymond, James Levinsohn, and Ahmed Mushfiq Mobarak. "Encouraging sanitation investment in the developing world: a cluster-randomized trial." Science 348, no. 6237 (2015): 903-906.
Reading:
- Mixtape: regression discontinuity
- Geocomputation with R
- Burgess, R., Costa, F. and Olken, B.A., 2019. The Brazilian Amazon’s Double Reversal of Fortune.
Oct 27: Hedonics [skipping for now]
Reading: Muehlenbachs, Lucija, Elisheba Spiller, and Christopher Timmins. "The housing market impacts of shale gas development." American Economic Review 105, no. 12 (2015): 3633-59.
Reading:
- Mixtape: difference-in-differences
- Hollingsworth A. and Rudik, I., 2021. The effect of leaded gasoline on elderly mortality: Evidence from regulatory exemptions. American Economic Journal: Economic Policy.
- Graff Zivin, J. and Neidell, M., 2013. Environment, health, and human capital. Journal of Economic Literature, 51(3), pp.689-730.
Reading:
- Mixtape: difference-in-differences
- Hollingsworth A. and Rudik, I., 2021. The effect of leaded gasoline on elderly mortality: Evidence from regulatory exemptions. American Economic Journal: Economic Policy.
- Graff Zivin, J. and Neidell, M., 2013. Environment, health, and human capital. Journal of Economic Literature, 51(3), pp.689-730.
Nov 5: Climate change science [slides posted]
Reading:
- Hsiang, S. and Robert Kopp. 2018. An economist's guide to climate change science, Journal of Economic Perspectives, Vol. 32, No. 4, pp. 3-32.
- Hsiang, S., 2016. Climate econometrics. Annual Review of Resource Economics, 8, pp.43-75.
- Good resource on doing climate-econ research: ClimateEstimate.net
Nov 10: Climate change and the Ricardian model [slides posted]
Reading:
- Mendelsohn, R., Nordhaus, W.D. and Shaw, D., 1994. The impact of global warming on agriculture: a Ricardian analysis. The American economic review, pp.753-771.
- Ortiz‐Bobea, A., 2020. The role of nonfarm influences in Ricardian estimates of climate change impacts on US agriculture. American Journal of Agricultural Economics, 102(3), pp.934-959.
Reading: Deschênes, O. and Greenstone, M., 2007. The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. American Economic Review, 97(1), pp.354-385.
Reading:
- Geocomputation with R
- Zou, E., 2021. Unwatched pollution: The effect of intermittent monitoring on air quality. American Economic Review.
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