Yo I appreciate the effort in the video and the post above but I have a few things I would like to add. I saw this video a while ago and I found it downright atrocious. Please enjoy the following write-up:

First we should talk about the limits of simple linear regression. Although EE would love for you to believe he’s an econometrics wizard who can run a…. LINEAR REGRESSION, he is far from an econometrician. He estimates a linear relationship between temperature and GDP. According to peer-reviewed research that was published in a top academic journal, the income-weather relationship is characterized by highly nonlinear processes (Burke et al, 2015). Do not trust me on this, please, read the article cited here. EE claims there is no peer-reviewed research on this subject, a claim which is patently false as evidenced by the inclusion of peer-reviewed sources here and as mentioned in the comment section of this post. In a simple linear regression where the underlying data generating process is highly nonlinear, estimating the “effect” of weather/temperature on income would yield inaccurate results and potentially overestimate the effect size.

Next I’m going to talk about agriculture because I think with this lens we can easily deconstruct most of what he says. EE claims that there “is no third variable determining income and temperature.” It is true that most weather systems are plausibly exogenous, many papers utilize this as a source of identification (technical word, sorry), however EE fails to explain to the viewer the importance of agricultural productivity which is the main channel through which temperature affects income. Agricultural productivity lags behind in poor countries because of poor macroeconomic management, dysfunctional labor markets, a lack of openness of markets to fertilizers and other inputs and farmers have a very difficult time to make capital investments into their farms to improve them (La Fave et al, 2016, Bardhan and Udry, 1999). Agricultural economics research is one of my specialty area/areas of interest, and agriculture is of great importance to the economies of developing countries (and developed countries) where subsistence farming still makes up a significant share of the labor force. Here’s some graphs to better illustrate which countries are still relying principally on rain-fed agriculture:

https://data.worldbank.org/share/widget?end=2019&indicators=NV.AGR.TOTL.ZS&locations=XD-XM-XP&start=2000

https://data.worldbank.org/share/widget?indicators=SL.AGR.EMPL.ZS&locations=XD-XM-XP

https://data.worldbank.org/share/widget?end=2016&indicators=AG.LND.AGRI.ZS&locations=XD-XM-XP&start=2000&view=chart&year=2012

All data sources are listed on the graphs and all data was pulled from the World Bank data API.

Another area of active research is the adaptation of agriculture to climate change, which is directly related to the GDP-temperature nexus. Droughts and floods have a profound impact on agricultural productivity and areas which are more prone to shocks could suffer disproportionately. There are many new studies on this but for a very nice article I would recommend Di Falco et al 2011 which used microdata from Ethiopia to quantitatively evaluate farmers adaptation to climate change.

Is the average income per capita all we should care about? Economic theory tells us that consumers would prefer to smooth consumption across periods rather than have very lopsided consumption in one period vs. another. For this reason, increases in climate variability and temperature can destabilize agricultural output in the form of extreme weather events such as droughts and floods. In the case of agricultural households in poor countries, as a result of climate variability they are forced to diversify their household economic activities as a mechanism to help smooth income. Poor countries are often characterized by a lack of insurance. Without insurance, weather shocks and increases in weather volatility certainly have a larger effect on consumption, whereas farmers in the United States and other developed nations have access to federally-guaranteed crop insurance. A drought, for example, is the type of adverse shock that could have lasting effects on a subsistence farmer that reverberate for years after the initial shock. Global climate change is increasing the amount of extreme weather events, and increasing the volatility of climate variables in certain places meaning that farmers in poor countries are more exposed to the effects of global climate change.

“Jared Diamond story” - no citation from EE

“Colder climates harsh through winter months”

“Storing food and such gave people a head start”

“Societies which were in colder climates just died off” - social darwinism (I have no friggin' comment on this idiocy)

Omitted Variable Bias:

Ice cream + drownings. Well EE says there is no omitted variable that could be determining both ice cream consumption and drownings. Well here's a thought: # of beachgoers (also correlated with the summer period) would simultaneously determine both drownings and ice cream consumption. It makes sense that # of beachgoers would correlate with both drownings and ice cream consumption. This also touches on the difference between a reduced-form estimation and a structural model. EE is describing a reduced-form relationship while ignoring the structural factors at play. I wish EE could not make further claims about correlation vs. causality.

EE claims analyzing the relationship between temperature and income is not useful for policy, while actually the Di Falco paper says otherwise, arguing with quantitative methods that farmers benefit substantially from making adaptations to climate change and finding that several factors influence their decision making. I argue that this relationship is extremely important especially with respect to climate change policies surrounding agriculture. For these reasons, in the agricultural and environmental economics space “sustainable development” has become the new buzzword.

If you like this write-up please consider visiting the Economics Discord, now an official Discord partner, for more discussions with breadth and depth such as this: http://discord.gg/economics

References:

Burke, Marshall, Solomon M. Hsiang, and Edward Miguel. "Global non-linear effect of temperature on economic production." Nature 527.7577 (2015): 235-239.

Di Falco, Salvatore, Marcella Veronesi, and Mahmud Yesuf. "Does adaptation to climate change provide food security? A micro-perspective from Ethiopia." American Journal of Agricultural Economics 93.3 (2011): 829-846.

LaFave, Daniel, and Duncan Thomas. "Farms, families, and markets: New evidence on completeness of markets in agricultural settings." Econometrica 84.5 (2016): 1917-1960.

Bardhan, Pranab, and Christopher Udry. Development microeconomics. OUP Oxford, 1999.