Turning and turning in a widening gyre A conventional narrative among political commentators of our day has been one of increasing polarisation and a collapsing ‘middle’. In economics, leading international think-tanks like the OECD are writing reports with catchy titles like “Under Pressure: The Squeezed Middle Class“. In the media, pundits are falling over each
Divided we tweet It seems that the public debate is divisive as never before. Left versus right. Social Justice Warriors (whatever they are) versus the alt-right (whatever that is). Admittedly, this impression may simply be a result of our unhealthy addiction to social media, which through its Algorithms of Hate and its cloak of anonymity
United we chat; divided we shout at each other I promised myself I would not write a post about the Charlottesville riots, the near universal condemnation of Donald Trump’s nuanced position and the taking down of Confederate-era statues. Yet a recent conversation has forced my figurative hand onto the keyboard. I’ll keep my promise nonetheless,
A gap by Any Other Name… The official website for statistics of the European Union is called Eurostat. If you visit their website, and I highly suggest you do, you will find among the many interesting databases one for the Gender Pay Gap, which measures the difference in average gross hourly earnings between men and
If you know me or have visited this blog before, you’ll know that my book, The Hydra, is about overpopulation. In it, a scientist decides the world is so full of humans, that he must save the planet by engineering and releasing an infertility virus. I won’t give away too much of the plot, but
Dirty old classism As I prepare to leave Dublin, I find myself reflecting on the things that make life in this city special. Many are splendid: the quick Dublin wit, the pleasant gift of the gab, the unique blend of international culture and local identity. But some are less worthy of celebration, and in this
Despite my better judgement, I have recently found myself getting into social media exchanges with supporters of Hillary Clinton’s presidential bid. These exchanges are often acrimonious and always pointless, because no one ever manages to convince anyone else of their point of view on social media. However, the arguments
As with birth rates, we use data for 4 categories of countries from 1990 to 2015 (100 observations total). We have two explanatory variables, AGE and Y, where AGE is defined as the percentage of the population aged over 65 and Y is per capita GDP.
After eyeballing the scattergrams, we test the following functional form:
d = (minY^a)/Y^a * (1/AGE^g)
Where minY is the constant equal to the smallest value of Y in the series.
Logarithmic transformation gives:
ln(d) = ln(minY^a) – a*ln(Y) – g*ln(AGE)
which we test on the data using OLS. Here are the results:
Adjusted R square: 75.191
Intercept coefficient: 7.37384
t-Stat: 20.4011
Y coefficient: -1.01444
t-Stat: -13.1059
AGE coefficient: 2.0097
t-Stat: 11.5208
The estimated intercept is a good, but not perfect, approximation of ln(minY^a)
Here are the fitted against actual values of the scattergram for death rate against per capita GDP:
While the results are not as good as with the birth rates calculations, it is nevertheless a good enough fit and the explanatory variables have a strong enough confidence factor to be usable in our estimations.
We begin by examining the scatter of data for 100 observations of per capita GDP and per capita emissions for 4 categories of countries, over 25 years (1990 – 2015).
The scatter suggests a cubic functional form, so we test:
GHG = a + b*Y + c*Y^2 + d*Y^3
where GHG are per capita emissions of GHG, and Y is per capita GDP.
The results from OLS regression are:
Adjusted R square: 0.980438073
coefficient a: 1090
t-stat a: 3.06
coefficient b: 0.709310153
t-Stat b: 8.241453
coefficient c: -0.0000047025
t-Stat c: -1.01233
coefficient d: -0.000000000105314
t-Stat d: -1.47005
While the t-scores on the squared and cubed terms are low, the number of observations are also limited.
Here is the plot of the fitted against actual values:
