Week 1: Value of Life; Causality; Poverty Trap
It has been a week since the start of the DEDP program, and I’ve been enjoying it a lot! In this post, I will talk about some of the interesting topics we covered this week. Then, I will share the number of hours I spent on each course.
Overall, I was amazed by economists’ creativity in coming up with ways to measure unobservable variables in the world. In Microeconomics, we used the concept of revealed preferences to calculate how much people value their time and lives. The value of life can be estimated based on how people choose to pay for safety features to lower their risk of death or the payment they get for risky jobs. In the US, the Office of Transportation Policy estimated the value of a statistical life equal to $9.6 million.
I couldn’t find similar numbers from the Ministry of Transport in Saudi Arabia. Yet, I came across this paper from 2015 that values the statistical life in Saudi Arabia to be equal to SAR3.4 million ($0.9 million). I wonder if someone ever tried to measure that value based on the amount of Diyah (in Arabic: دية). If I wasn’t mistaken, a Diyah is a financial compensation paid to the deceased’s family in the case of manslaughter. A document from 2013 stated its value to be around SAR300 thousand ($80 thousand) — much less than the estimate in the 2015 paper!
In Data Analysis for Social Scientists, we learned how data can be powerful. We discussed the Enron scandal and how auditors modified their balance sheets to indicate a clean bill of health. We then talked about how data can be deceitful.
One example was the correlation between autism and GMOs by Dr. Stephanie Seneff, a senior research scientist at MIT CSAIL. The findings were criticized by many, and some were even able to correlate autism and healthy organic food! The bottom line is we can’t simply conclude that a relationship is causal. It has to be argued.
The Challenges of Global Poverty introduced me to a topic I always wanted to learn more about: the S-shaped poverty curve and what it means to be stuck in a poverty trap. The S-shaped curve relates income in terms of nutrition to work capacity. The concepts will be extended in the next weeks on food, health, and education. I’m mostly excited about the latter. I think after completing this course, I will be able to read and understand Professor Ray’s paper on aspiration and inequality. He talked a bit about his work on aspiration in the interview below and I was really captivated by it.
Foundations of Development Policy course is covering the same topics as the Challenges of Global Poverty, but the models are much more advanced. It was very depressing to know how the model we’ve studying can explain the prevalence of deaths among girls over boys in periods of drought. Families don’t have enough to feed both of their kids, and they allocate all resources toward the most favorable one.
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The course assumes you’ve completed Microeconomics and Data Analysis for Social Scientists. I had to go over Professor Ray’s textbook (pages 489–504) to better understand the mappings and make sense of the models in the slides. You can find my summary below or download it from here.
Week 1 Effort
I’m using the word “effort” to indicate the number of hours I spent on video lectures, reading assignments, finger/lecture exercises (FE), problem sets (PS), and participation in the course forums.
- Microeconomics: 16 hours! Mostly because there are no slides, and I had to write down everything myself.
- Designing and Running Randomized Evaluations: 10 hours. The MCQs can be very tricky! I should’ve studied the lectures more before attempting any of the exercises.
- Data Analysis for Social Scientists: 6 hours.
- The Challenges of Global Poverty: 8 hours.
- Foundations of Development Policy: 9 hours. I started the course very late, and skipped the introduction to R module. I assumed it is going to be the same as all the other courses. Unfortunately, I was wrong. They covered new commands that could’ve saved me time and points! I did not include the time that I took to write the summary that I shared with you above (~5 hours, I don’t why it took me so much time either 😅).
I hope you found this post helpful! If you have any questions or comments, feel free to write them below or shoot me an email at blog@hayaalsh.com.
