1°C = $762

When people think about advanced economies they will think of places like, Germany, Switzerland, Norway, Sweden all countries with a very high GDP Per Capita. On the opposite end of the spectrum there are underdeveloped nations, like those in sub-Saharan Africa, Central America, the middle east, and areas of southeast Asia. There are all manner of factors that make poor countries poor and rich countries rich. Many of these factors have been explored in depth by many experts, when we look at economies like the democratic republic of the Congo all the way up to places like Switzerland and Norway. Political Stability, industry, natural resource wealth are all incredibly important variables but there is something extra here that just doesn’t seem to make sense. Cold countries are richer than hot countries. This is a bizarre correlation but it’s clear as day to see. This is a map of the world with color-coding for countries’ GDP per Capita.

The poorest countries are centralized?in the hottest parts of the world,?what’s more, is that apart from?a few outliers almost all of the?developed countries in the world?exist outside of the tropics. So what is going on here? Is there actually a statistical?correlation between cold and prosperity? Could this just be a co-incidence and if this relationship is real,?what could possibly be causing it?

The phenomenon of rich area’s congregating?to the cold even looks like it takes place?within individual countries. Take Australia for example,??it’s two largest cities are Melbourne,?and Sydney, located below the tropical belt. Logically speaking the most prosperous city in?Australia should be Darwin. It is much closer to?significant natural resource wealth and it is?significantly closer to trading partners like?China, Malaysia and Indonesia. But it’s not! In fact Darwin is actually the poorest capital?city in Australia while also being the hottest.?So since theory anecdotally holds?true at all levels it is time to. Look at the data No conclusive studies have?ever been done on this subject, and in fact the?only peer-reviewed paper we were able to find?on the subject did not look at raw data. This is always a really important step to?take because sometimes things sound true when?presented, but the results do not match up. For example, it sounds like the average amount?of arms for an American Male to have is 2. This?theory would likely by supported by the anecdotal?evidence that every American Male someone would?think of off the top of their head has… 2 arms! But in reality, the average amount of arms?an American male has is 1.998 because 2.2?people in every thousand have lost an arm. Put another way, most American Men?have an above-average amount of arms. So statistics is fun and the?results are sometimes surprising. Fortunately for the sake of this theory?though the data is very simple. We want to see the correlation between?the average temprature of a country and??the GDP per capita of that country. If we do a simple linear regression on??this we find a few really interesting results. As predicted, there is a negative relationship??between temperature and GDP per capita.?For every extra degree Celsius in average?national temperature, the expected value?of GDP per capita falls by $762 per year.?This means that if country A is 10 degrees?colder than country B, it is expected to have?a GDP per Capita $7,620 a year larger. When we do statistical analysis we also?look at a value called R Squared. Statisticians have a knack for making?everything sound more complicated than it actually?is so what the R Squared value means in plain?English is how much of the result is determined?by the variables in the model compared to other?factors that haven’t been considered. For example, if we were looking at the?correlation between height and weight we would?expect a positive relationship. The taller?someone is the heavier they tend to be. Using this example we may find an R squared?value of 0.5, meaning that 50% of someones?weight is determined by their height. This would mean that another 50%?is explained by another factor,?(or factors) not in our model. In this example,?it would probably be how uhh, round they are. The relationship between temperature and?GDP per capita gave us an R squared value??of 0.09. This means that 9% of a countries?prosperity is determined by its temperature. This sound pretty insignificant,?but it is actually huge?That other 91% would then be made up of things?like credit rating, natural resource wealth,?infrastructure, government stability and?whole range of other factors that people?would expect to be far more important?to an economy than the weather. So the relationship is here! And it’s pretty?significant. But before this devolves into a??statistics lesson it is still important?to address potential problems. Namely The outliers, and the?cause-effect relationship. There are some significant?outliers in this set of data.?Bahrain, Qatar, the UAE and Singapore are all?very hot and very rich. For the first three,?natural resource wealth has overcome?any inherent burden of hot weather.?Singapore is just a genuine outlier?that flies in the face of this theory. We would also be reminisce if?we didn’t mention North Korea,?it is very cold and very poor. Which is an example?of political instability being a heavier burden?than the apparent benefit of a colder climate. The other thing that is really important to look?at when exploring economic relationships?is cause and effect. Or rather that??correlation does not always mean Causation.

Why do economies not like it hot??

There are actually a range of theories on?this issue. But the reality is there is not??yet a conclusive answer. The most prominent theory?is that of economic selection. Cold climates are very harsh during winter months.?In a country like norway, people would not survive?through these winters unless they planned ahead to?stockpile food, build good shelters, and reserved?fuels like oil, coal, or wood to keep warm. From the outset, this gave these economies?a head start. It wasn’t so much that people?were more industrious because of the cold,?it was more so that societies that weren’t??industrious just froze and died off. A basic mud hut is a sufficient shelter?in tropical regions and food is available?to hunt and gather year-round so there was??not the same impetus to build larger?more engineered dwellings and become?a society that valued storing resources. This kind of forced industriousness would??compound on itself over many generations to?produce a society that values capital goods?more so than a society that has had?it easy throughout its existence.?A critique of this theory is that a majority?particularly prosperous ancient civilizations?were centered in warm regions. Ancient egypt, Mesopotamia, the mayans,?the persians, all called very hot regions home. This should discredit this theory but instead,?it actually offers even more insight. If we were to look at the correlation of?temperature and wealth 2,000 years ago you?would actually get the opposite result. Hotter nations were richer. So why did this change??It changed because global industries changed.?2,000 years ago the wealth of a country was??effectively determined by how much food it could?produce. More food meant it could feed more people?to toil more field to produce more food. Modern farming techniques did not exist?and even the most powerful empires would?constantly struggle through famines. Warmer climates could grow more?food, and hence harbor more wealth. In the modern world, wealth?is no longer determined by how?much a country can farm. Instead, it is?determined by Industry and innovation. The societies which had been forced to adapt and?innovate their way around a hostile environment?for centuries could now come into their own?and lead the world into the age of industry.

The good news amongst all of this is that cold?countries got a bit of a head start in the age of?innovation but places like Singapore show that?this is not a head start that will last forever.?

Every country has potential?regardless of the weather outside.