My Review of Hideo Yokoyama’s “Six Four”

By Graham

In the age of click-bait and instant gratification, consumers of casual entertainment have limited tolerance for excessive detail and slow pacing. We have come to expect an easy payoff, and when an author dares to challenge us to enter a world where nothing comes easy, we can be quick to bail.

I’ll confess I was tempted to do just that while reading Six Four, my first – and perhaps last – excursion into the weird world of Japanese “police fiction”. I hesitate to say “thriller”, since the book was more a careful exposition of the inner workings of a regional police heirarchy, than a gripping page turner. The ‘thrills’ were well contained.

And yet if you can forgive the author his contempt for the reader, this book is in many ways worth the effort. The writing is terse yet powerful, though as ever it isn’t clear whether this is to the author’s credit, or the translator’s.

The central character Mikami, but also his wife and colleagues, come alive, drawing us in to their hunt for his runaway teenage daughter, and the frustration of their internal battles with the detectives and the local press corps. Incredibly, I found myself worrying alongside the local police that the visit of the Police High Commissioner to Prefecture D would not receive sufficient press coverage, bringing disgrace to Mikami and his team at Media Relations.

Perhaps the patience and dedication it takes to get the most out of reading Six Four teaches us something about the Japanese psyche? Perhaps it teaches us something about the nature of detective work? For sure we learn a lot about the bureaucracy of the Japanese police force.

Whether that is worth the investment in time and attention, is for the reader to decide.

 Category: Book Reviews

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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: