TPC: Valid Economic Measure or just more silliness?
William P. Baird
recently. Actually, really, honestly, it was a case of, at best,
pointing out that Russia is screwed by having Siberia and the
population there. In effect, the economists involved with
writing the book argued that Siberia is, and will be for the
foreseeable future, a net economic drain on Russia.
The problem is, as has been pointed out to me in the past by
canuckistanis, that working and living in the cold is damned
hard. What I mean by that is that the work that can be done
during the extremely low temperature time periods is far more
expensive to do, takes a lot more time, and the results cost a
lot more to maintain. It seems pretty obvious, but it also
seems that the a few more degrees of cold can and do make
huge difference by making everything a lot harder to do.
One of the measures of what a country 'should' be is that
according to the authors is what they call 'Temperature Per
Capita' (TPC). It's a function as follows:
Person Degrees = Region's Population X Mean January Temperature
TPC = SUM(Regional Person Degrees)/ Nation's Population
For Example, Yanqistan Region has a population of 10 and mean
January temperature of 1. It's bordered by Canuckistan Region
with a population of 4 and a mean january temperature of -10.
YDR is also bordered by Latinostan with a population of 6 and a
mean january temperature of 15.
Latinostan's Person Degrees is 90, Yanqistan's 10, and Canuckistan's
is -40. That gives us a TPC for NorAm of 2.
Some real life numbers that the authos use are historical and come out
to be...
United States: 1.1 (1930)
Sweden: -3.9 (1930)
Canada: -9.9 (1931)
Russia: -11.6 (1927)
The authors argue that TPC is directly linked to the nation's economic
potential. The US having a mild TPC indicates that it will be
economically successful. Russia having a very low TPC indicates
that it will not be even with full market reforms[2].
so, I guess what I am aseeking is whether or not TPC is considered
a valid measurement of, well, anything? Or is it simply a artificial
and meaningless construct?
Will
1. Siberian Curse: How Communist Planners Left Russia Out
in the Cold. ISBN: 0815736452
2. Unless it moves the population out of Siberia on a massive
scale or global warming pushes up the average temperature.
--
William P Baird Do you know why the road less traveled by
Home: anzhalyu@gmail. has so few sightseers? Normally, there
Work: wba...@nersc.go is something big, mean, with very sharp
Blog: thedragonstales teeth - and quite the appetite! - waiting
+ com/v/.blogspot.com somewhere along its dark and twisty bends.
Coyu
> I read a book[1] about the th economic woes of Siberia here
> recently. Actually, really, honestly, it was a case of, at best,
> pointing out that Russia is screwed by having Siberia and the
> population there. In effect, the economists involved with
> writing the book argued that Siberia is, and will be for the
> foreseeable future, a net economic drain on Russia.
> 1. Siberian Curse: How Communist Planners Left Russia Out
> in the Cold. ISBN: 0815736452
I'm not spotting a review on eh.net, but looking at the Brookings
Institution's highlight review page, Sachs, Ferguson, Pipes,
Brzezinski and Lieven all have good things to say about it, and
Sachs and Ferguson (when not being paid off by the Torygraph)
would certainly spot any econ bibble-babble.
I'll put it on the next Amazon order. Might be a bit.
C.
Coyu
> I read a book[1] about the th economic woes of Siberia here
> recently. Actually, really, honestly, it was a case of, at best,
> pointing out that Russia is screwed by having Siberia and the
> population there. In effect, the economists involved with
> writing the book argued that Siberia is, and will be for the
> foreseeable future, a net economic drain on Russia.
Thought experiment: someone in 1920 writes a similar book about
the deleterious effects of the tropics and humidity on an economy,
and predicts that Atlanta and Miami would be doomed to remain
backwaters and economic drains on the Northeastern urban core of the
US, and that there were natural climatic limits to the growth of Los
Angeles, while the British should cut and run from Hong Kong and
Singapore, since aside from their strategic location, they would
never amount to much.
Anyway. B Garid once brought up this idea before. It sounded
strange and a little bogus then -- Minneapolis does just fine,
thank you -- and it sounds a little bogus now. But here's Hill and
Gaddy on the topic:
"One of the most ambitious tasks performed in the Cost of the Cold
project was to simulate what Russia's population distribution might
have looked like if it had evolved according to market economy
principles in the twentieth century. This so-called counterfactual
exercise concluded that Siberia and the Far East today are
overpopulated to the tune of as many as 16 million people. Translated
into terms of TPC, this means that Russia at the end of the Soviet
period was as much as 1.5 degrees colder than it "might have been."
Because there is a cost of cold, the locational structure bequeathed
to Russia by the communist planners represents a tax on today's
economy. How big a tax? A cautious estimate is that for each degree
that Russia's TPC is lowered, its gross domestic product (GDP) is
reduced by 1.5-2 percent. By that calculation, the "cold tax" that
Russia pays is in the neighborhood of 2.25-3 percent a year. This is
a huge amount. To illustrate: a Russian economy that otherwise would
be capable of growing at 5 percent a year for 15 years would
sacrifice from one-half to two-thirds of its potential growth because
of the mislocation of so much of its economy and people in the east."
Here's Grigory Ioffe's analysis, from the Journal of Regional Science
in 2005:
"The crux of the matter is the calculation of a parameter called
temperature per capita (TPC), which is a weighted average of the mean
January temperature of all Russian cities over 10,000 in population.
The statistical weight is each city's population. The 1930 estimates
of TPC are presented for Russia, Sweden, Canada, and the United
States, as are the estimates of change in TPC between 1930 and 1990.
It appears that at the start of the period, Russia had the lowest TPC
(minus 11.6 degrees Celsius compared with minus 9.9 degrees for
Canada), and that throughout the 1930-1990 period, Russia's TPC
declined progressively due to expansion into colder areas, while
Canada's TPC increased due to a different strategy of resource
exploitation recognizing a limited pool of labor in the coldest
regions. A similar calculation was published by Treivish (2002). He
used the same indicator, which he applied to a more generalized set
of spatial units (regions instead of individual cities), and he came
to the same conclusion that Russia has probably expanded too much
into harsh environments. However, Treivish's interpretation of this
result is far less radical than Hill and Gaddy's.
"Apparently, Treivish's interpretation is in line with the numerous
discussions conducted in Russia since the late 1960s. They have
invariably focused on a myriad of smaller industrial settlements
scattered in the vast universe of the Russian north, not on such
giants as Novosibirsk, Omsk, Krasnoyarsk, Sverdlovsk, Perm, etc.
According to Hill and Gaddy, however, it is precisely these
population centers that appear to be the ''major offenders''
(p. 39).
Simply put, a contribution of the cities to TPC is directly
proportional to their sizes, and the above-mentioned cities are
''millionaires.'' Therefore, nothing short of a depopulation
strategy for these cities (not just for Norilsk, Magadan, Khanty-
Mansiisk, or Yakutsk, which are much smaller) would bring Russia's
economic geography in line with that of other northern countries,
notably Canada.
"In regional geography, the most relevant and inclusive notion is
that of the principal settlement belt (_glavnaya polosa rasseleniya_)
of the former Soviet Union, which is the extension of the European
area of spatially continual settlement. This belt has a shape of a
latitudinal wedge: its broader western edge more or less fits the
imaginary line linking Saint Petersburg, Lviv, and Odessa, and the
wedge gradually narrows as one proceeds east until it becomes a strip
along the Trans-Siberian Railway Line. Within this spatial pattern,
the locations of Novosibirsk, Omsk, Yekaterinburg, Irkutsk,
Krasnoyarsk, and Perm are not accidental: most of them are at a
junction of a major river and the railway line. Coupled with the role
of central places with respect to the surrounding areas, nodes like
these have a powerful development potential.
"From that perspective, the comparison of Duluth, Minnesota, and Perm
contained in Chapter 3 of Hill and Gaddy's book is flawed. The
authors observe that both cities are located at the same latitude,
both have cold winters, and both began as ''iron cities'' (my
phrase),
but while Duluth has shrunk after reaching 200,000 residents, Perm was
driven to more than one million in size. The point is, however, that
in the American ecumene and in a mental map of the average American,
Duluth is a marginal location, whereas Perm is anything but marginal
in Russia. It is a prominent node within the principal settlement belt.
Winnipeg is to the north of Duluth and has winters even colder than
Duluth, yet it is a sizable (650,000 residents) city in Canada. Simply
comparing cities along the same parallel of latitude is pointless; the
frame of national geographic reference is immensely meaningful, and
the authors do not seem to take this into account. Interestingly, from
Chapter 7, one learns that the city of Novosibirsk, which is the number
one offender in terms of TPC, ranks seventh among all Russian cities in
foreign direct investment. This is no accident, as this offender has a
fairly advanced urban environment. It contains prominent schools,
quality theaters (including a famed ballet company), and a
concentration of research institutions of the Russian Academy of
Sciences, and it is the only successful case of development of such a
concentration outside Moscow and Saint Petersburg."
Ioffe also refers to Tatania Mikhailova's 2002 Penn State Ph.D.
dissertation, ''Where Russians Should Live: A Counterfactual
Alternative to Soviet Location Policy,'' which I should track down
via the Michigan server.
Cristina Chuen, writing for the Bulletin of the Atomic Scientists,
starts off:
"In early January, as I was waiting to take off from Yekaterinburg, in
the Russian heartland, I could not help but appreciate just how cold
Russia is. With ice crusting the airplane's wings, snow blowing
fiercely, and the thermometer at 30 below zero, I had to wonder how --
and why -- 1.2 million people live in remote, frozen Yekaterinburg,
Russia's fifth-largest city."
Immediately, my "wuss" alarm bells started ringing. Guess what?
She agrees with the thesis..
Granted, I have yet to read the book. But there is something going on
here which does not seem to be about the economic effects of climate.
Coyu
> Ioffe also refers to Tatania Mikhailova's 2002 Penn State Ph.D.
> dissertation, ''Where Russians Should Live: A Counterfactual
> Alternative to Soviet Location Policy,'' which I should track down
> via the Michigan server.
Ioffe's article had the author's name and thesis title wrong. It's:
"Essays on Russian economic geography: measuring spatial
inefficiency"
Tatiana N. Mikhailova
Abstract
Compared with other transition countries Russia faces the
burden of extreme cold. This is not, however, strictly a
function of geography. Soviet location policy directly
affected the average (population weighted) temperature of
the Russian economy. Soviet policy moved industry and
population from the western part of the country to the
east, effectively making Russia even colder than it was in
the pre-Soviet era. Movements to the east have the
significant impact on aggregate temperature because the
isotherms on the Eurasian continent resemble lines of
longitude, not latitude. Thus, the Russian economy entering
transition faces not only the usual burden of an
inhospitable Russian climate, but also suffers from the
extra disadvantage due to the legacy of Soviet location
policy.
In this thesis I estimate the cost to Russian economy of
the inefficient spatial allocation of its productive
resources. Spatial inefficiency can result not only in
added production and distribution costs -- when regional
comparative advantages are not exploited and unnecessary
transportation and communication expenditures are incurred
-- but also the wrong allocation of labor brings
inefficiency in consumption: there are extra costs
associated with people living in unsuitable places. In the
Russian context, "unsuitable" usually means "too far" and
"too cold." I focus on the "cost of cold," or precisely,
the cost of production being wrongly located in places with
a climate too cold.
The first essay is a counterfactual exercise. To obtain a
benchmark of spatial efficiency, I construct an allocation
of industry and population that would result in Russia in
the absence of Soviet location policy. To design such an
allocation, I impose Canadian behavior on Russian initial
conditions. I estimate a spatial dynamic model on Canadian
regional panel data in a multinomial logit framework. I
then project the estimated relationship onto Russia. The
result is a hypothetical allocation of population and
industry, specific to Russia's endowment and initial
conditions, but free of any disadvantages stemming from
Russian historical circumstances.
This procedure, however, ignores the effect of WWII -- a
major exogenous shock to Russian economy with no precedent
in Canada. We should expect that war would have an impact
on industry allocation irrespective of economic or
political system. To account for the possible effects of
WWII I conduct a separate simulation exercise, taking into
account the fact that the war was fought primarily in the
west. The results of this exercise show that the eastern
part of Russia is still significantly overdeveloped -- in
other words, WWII explains only a small part of the
misallocation.
I construct an index of Temperature Per Capita (TPC) to
capture the effect of location on aggregate temperature.
Unlike other temperature indicators widely used in
empirical growth literature, TPC is obtained by
aggregating the temperature readings not over the
territory, but over the population distribution. Thus, it
provides more informative measure of temperature-related
comparative advantages or disadvantages of the economy,
especially in short-run. I use the estimated allocation
of population to construct the counterfactual TPC. The
comparison with the actual TPC reveals that due to Soviet
location policy Russia has become about 1.5 C "colder."
In the second essay I estimate the cost of cold directly.
The most profound consequences of cold are extra energy
use, added construction costs, health effects and
productivity loss. Using Russian regional data on energy
use, health and production I estimate the elasticity of
each of these factors with respect to temperature. I then
use these elasticities together with the TPC indices of
the actual and the projected allocation to estimate the
extra burden of cold that resulted from the Soviet location
policy.
The results show strong and significant effect of cold on
all the factors examined. An increase in TPC of 1.5 C would
have improved aggregate health indicators: average infant
mortality rate would have been 1.5% lower, country-wide
aggregate mortality rate -- at least 0.8% lower. The
estimations for construction industry reveal a 3.5%
productivity loss in the actual allocation compared to the
counterfactual.
The most significant impact of cold is on energy consumption.
Cross-sectional analysis reveals that consumption of various
kinds of energy by manufacturing produces increases 2.5 to 4%
when January temperature drops 1 C. Thus, 1.5 C TPC difference
between the actual and counterfactual allocations translates
into 3.5-6% industrial energy consumption increase country-wide.
The similar results were obtained for the residential energy
consumption: various estimates point on 6 to 9% total energy
loss due to the misallocation of population. The cost of extra
energy consumption and the loss of construction productivity
amount to 1.2% to 2.1% of Russian GDP yearly.
Carlos again. This actually has some meat on it, and looks
like it will repay the effort.
Randy McDonald
>
> [deletia]
>
> I'm not spotting a review on eh.net, but looking at the Brookings
> Institution's highlight review page, Sachs, Ferguson, Pipes,
> Brzezinski and Lieven all have good things to say about it, and
> Sachs and Ferguson (when not being paid off by the Torygraph)
> would certainly spot any econ bibble-babble.
>
> I'll put it on the next Amazon order. Might be a bit.
I read it in 2004. I liked it, FWIW.
> C.
--
R.F. McDonald
r_f_mc...@yahoo.ca
http://www.livejournal.com/users/rfmcdpei/
"What! call a Turk, a Jew, and a Siamese, my brother? Yes, of course;
for are we all not children of the same father, and the creatures of
the same God?"
- Voltaire, from _Treatise on Tolerance,_ 1763
James Nicoll
warming? And clathrates are a good source of greenhouse gases
_and_ a potential fuel? Hrm.
--
http://www.cic.gc.ca/english/immigrate/
http://www.livejournal.com/users/james_nicoll
William P. Baird
> Thought experiment: someone in 1920 writes a similar book about
> the deleterious effects of the tropics and humidity on an economy,
> and predicts that Atlanta and Miami would be doomed to remain
> backwaters and economic drains on the Northeastern urban core of the
> US, and that there were natural climatic limits to the growth of Los
> Angeles, while the British should cut and run from Hong Kong and
> Singapore, since aside from their strategic location, they would
> never amount to much.
Actually, if TPC worked out as a valid economic measure, I was
going to ask if there was an upper limit as well as lower limit for
the ideal TPC for a country. IE is there a significant heat tax as
well as cold tax?
> Anyway. B Garid once brought up this idea before. It sounded
> strange and a little bogus then -- Minneapolis does just fine,
> thank you -- and it sounds a little bogus now. But here's Hill and
> Gaddy on the topic:
>
> "One of the most ambitious tasks performed in the Cost of the Cold
> project was to simulate what Russia's population distribution might
> have looked like if it had evolved according to market economy
> principles in the twentieth century. This so-called counterfactual
> exercise concluded that Siberia and the Far East today are
> overpopulated to the tune of as many as 16 million people. Translated
> into terms of TPC, this means that Russia at the end of the Soviet
> period was as much as 1.5 degrees colder than it "might have been."
They have a counter example of Duluth, Minnesota and its development
in the 20th century to support their hypothesis. We're doing a big
maintenance today. If I get a lull I'll post chunks. Prolly over
lunch.
> Ioffe also refers to Tatania Mikhailova's 2002 Penn State Ph.D.
> dissertation, ''Where Russians Should Live: A Counterfactual
> Alternative to Soviet Location Policy,'' which I should track down
> via the Michigan server.
They reference it in the book. More than reference it. They discuss
it. She posits a noncommunist Russia or at least one that follows
a more Canadian trajectory starting from the 1900s.
> Immediately, my "wuss" alarm bells started ringing. Guess what?
> She agrees with the thesis..
wuss alarms went off for me too, but then I grew up in wild temperature
differences with very dry air. *shrugs*
> Granted, I have yet to read the book. But there is something going on
> here which does not seem to be about the economic effects of climate.
There's a bunch going on here...I'd love to see your opinion, but I'm
equally curious if you're done vomitting from reading _Collapse_ yet.
heh.
Will
William P. Baird
> So what Canada needs is more people and more global
> warming? And clathrates are a good source of greenhouse gases
> _and_ a potential fuel? Hrm.
They have to go up simultaneously, but yeah, according to the
TPC hypothesis, that's what Canada needs.
That's just one more point in favor of the Russo-Canuckistani
conspiracy being behind Global Warming.
Will
James Nicoll
William P. Baird <anzh...@gmail.com> wrote:
>James Nicoll wrote:
>> So what Canada needs is more people and more global
>> warming? And clathrates are a good source of greenhouse gases
>> _and_ a potential fuel? Hrm.
>
>They have to go up simultaneously, but yeah, according to the
>TPC hypothesis, that's what Canada needs.
>
>That's just one more point in favor of the Russo-Canuckistani
>conspiracy being behind Global Warming.
It seems a bit hard on the Gulf Coasters, though, esp if
the Gulf Stream shuts down. I mean, that heat is going to go
somewhere and why not to fuel really kick-ass hurricanes?
It's even more hard on Bangladesh, thanks to pre-existing
weather patterns and the low elevation.
By the way, are you aware a lot of Canada's immigrants are
(as one might expect) from the subcontinent? I wonder how they hear
terms like "Canuckistani"? Actually, I kind of expect the term to be
adopted by the latest version of the Western Concept Party, not that
that will be your fault.
William P. Baird
> It seems a bit hard on the Gulf Coasters, though, esp if
> the Gulf Stream shuts down. I mean, that heat is going to go
> somewhere and why not to fuel really kick-ass hurricanes?
Well, you guys are always bad mouthing red staters. Obviously
this is just a way to actually fix the problem. Make them move
to blue states that will drown out the bit of red there.
> It's even more hard on Bangladesh, thanks to pre-existing
> weather patterns and the low elevation.
ouch. oh yeah.
> By the way, are you aware a lot of Canada's immigrants are
> (as one might expect) from the subcontinent?
yep.
> I wonder how they hear terms like "Canuckistani"?
hm. Interesting. I started using it after someone, I think Carlos
actually, called the US Yankeestan or some such after 9-11.
Yanqistan and Canuckistan were my personal mental cousins of
that. Partially because -stan does mean 'land of' or very close to
that. If they're offensive, I'll very quickly withdraw them. However
I do sometimes refer to myself as a Yanqistani irl. *shrugs*
> Actually, I kind of expect the term to be
> adopted by the latest version of the Western Concept Party, not that
> that will be your fault.
Interesting. I googled for 'Western Concept Party' and didn't find
much.
Interestingly, what I did find was some sort of seperatist party from
circa 1980. I take it they were a bunch of racist sobs then too?
*sighs*
Coyu
> > Granted, I have yet to read the book. But there is something going on
> > here which does not seem to be about the economic effects of climate.
>
> There's a bunch going on here...I'd love to see your opinion, but I'm
> equally curious if you're done vomitting from reading _Collapse_ yet.
> heh.
No. I am still marvelling at the "How to Lie With Maps" example, which
compares political trouble spots with areas facing biodiversity threats
(Guess what? The maps are the same.) I never knew that Mongolia
and the Philippines were so troubled, and that the Sudan was not.
James Nicoll
>> weather patterns and the low elevation.
>
>ouch. oh yeah.
If I were India, I would be researching how to house a hundred
million incomers, with the assumption that it might be necessary to do
this quickly.
>that. If they're offensive, I'll very quickly withdraw them. However
I don't think it is, yet. For some reason we don't see too
many of the Canadian White Knight types around here.
>
>> Actually, I kind of expect the term to be
>> adopted by the latest version of the Western Concept Party, not that
>> that will be your fault.
>
>Interesting. I googled for 'Western Concept Party' and didn't find
>much.
>Interestingly, what I did find was some sort of seperatist party from
>circa 1980. I take it they were a bunch of racist sobs then too?
>*sighs*
>
These are the guys who the Reform Party was careful to kick
out, not that it did that much good.
The most well known leader was Doug Christie, a lawyer whose
client list includes such well known people as Keegstra, Zundel and
Droege.
As far as I can tell, there is no inherent reason why western
seperatism need be racist, but then there's no reason why unions need
to be racist either and we got WORKERS OF THE WORLD UNITE FOR A WHITE
SOUTH AFRICA. In this case, the platform the WCC had included points like
* An end to immigration to preserve our environment, culture and stability.
* Preservation of our Christian culture and European heritage.
* One official language of Western Canada.
There was also lip service to egalitarianism along the lines
of "equal rights for all, with no special status for any race, or
ethnic origin" but since immigration would be ended, I imagine the
main effect would be to negate treaties with the natives.
Hmmm. I am getting an amusing idea for a dystopic west, run by the
worst tendecies of the old SoCreds and the new WCCers.
Gareth Wilson
James Nicoll wrote:
>
> * One official language of Western Canada.
Interesting that they didn't specify which language. I'd go for
Nuxálk, myself.
Sydney Webb
[snip]
> hm. Interesting. I started using it after someone, I think Carlos
> actually, called the US Yankeestan or some such after 9-11.
I'd be more likely to give credit to kindly Uncle Alan Lothian for the
coinage.
> Yanqistan and Canuckistan were my personal mental cousins of
> that. Partially because -stan does mean 'land of' or very close to
> that. If they're offensive, I'll very quickly withdraw them. However
> I do sometimes refer to myself as a Yanqistani irl. *shrugs*
Absolutely. In Farsi 'Inglistan' is England.
ObFuture: How far would Canada go to subvert efforts against global
warning, if she felt it were in her interests to do so. Which countries
might apply sanctions against her, and what might these sanctions be, to
convince Canada her interests lay elsewhere. I'm looking mainly at the
next 10 years and am willing to accept that in that timeframe there
might be no sanctions at all.
- Syd
--
"Gotta go now, the crocs are biting ..."
- John Quiggin
William P. Baird
> "Essays on Russian economic geography: measuring spatial
> inefficiency"
>
> Tatiana N. Mikhailova
> The first essay is a counterfactual exercise.
What if the Russians Had Behaved Like Canadians
So far we have established the following: Russia is cold, even
in the rigorous economic sense of having a low TPC; Russia
became colder in the twenieth century; and the decline in TPC
was costly. What now remains is to see whether Russia's costs
were avoidable, that is, whether Russia's allocation of its
economy in its thermal space was indeed a /mis/allocation. To
answer that question, Tatiana Mikhailova performed an
innovative simulation to see how different Russia would have
been with a market economy rather than a Soviet planned
economy.
Mikhailova writes: "While we can almost certainly infer that the
Soviet system deviated from the optimal path of spatial
development, the extent of the distortion is unknown until a
counterfactual path - a spatial development pattern that
market forces would have produced - has been derived."[1]
In her paper, Mikhailova uses econometric techniques to
simulate how Russia might have developed if the market
forces had operated. She writes: "The idea for the
simulation exercise is simple: I use Canadian behavior as
a benchmark of the spatial dynamics in a market economy
but apply it to Russian initial conditions and endowment."
In other words, Mikhailova studies the way Canadians
distributed their population over the territory during the
twenieth century in relation to where they began and what
resources there were and where they were located. This
establishes a pattern of spatial dynamics and its
dependance on initial conditions. Substituting Russia's
own initial conditions, she can then infer where Russians
would have ended up if they had "behaved like Canadians."
Why the choice of Canada?
[Because] there is no other country in the world to Russia
in climate and size. Both economies possess and export
abundant natural resources. Less obvious, but equally
important is the fact that both Russia and Canada at the
beginning of the [20th] century (and still have) vast
undeveloped amounts of land. Russia was still effectively
expanding east, and Canada colonized its west. Neither
country seemed to be in a long-run spatial equilibrium, but
they were "moving in similar directions."
Mikhailova presents a range of estimates to account for
two further important adjustments in the comparison between
Russia and Canada. The first is the effect of World War II,
which had devastating effects on the population and
infrastructure in the western part of Russia and led to
evacuation to the east of a large part of industry. The
second effect is the difference in birth rates in populations
in various regions of the Soviet Union. Even after these
adjustements, her conclusion is unambiguous:
The present allocation of population and industry in Russia
inherited from the Soviet system is far different from what
which would have occurred in the absence of Soviet location
policy. It is colder and further to the east. Namely, the
eastern part of the country is noticeably overpopulated
compared to the counterfactual market allocation, while
the western part experiences a relative population deficit.
The excess population in the Siberian and Far Eastern
regions ranges from 10 [million] to 15.7 million people
according to various esstimates.
As we now know from the TPC exercise, that the excess
population in the esast means that Russia also ahs "excess
cold" and "excess cost." The TPC of Mikhailova's
counterfactual, the Canada-like Russia of 1990 would have
been as much as 1.5 degrees warmer[2] than the real
Russia's actually was by the end of the Soviet period.
Because of the cost of the cold, the locational structure
bequeathed to Russia by the communist planners
represents a tax on today's economy. How big of a tax?
With Mikhailova's estimate of Russia's "excess cold"
- up to 1.5 degrees of TPC - we might seem to be
tantalizingly close to answering our original question for
this entire section: What does the cold cost Russia?
As noted earlier, however, we lack a solid estimate of
the cost per degree of excess cold for Russia. The U.S.
estimate cited in table 3-5 was around 1-1.5 percent of
GDP per degree. Dare we simply say that Russia pays at
least that much, and probably much more, and then
calculate accordingly that its total cost is at least 1.5 X 1-1.5
= 1.5 - 2.25 percent of GDP per year? As tempting as it is
to do that, we think there are too many unreseolved issues.
The fact remains that a full accounting of Russia's "cost of
the cold" is a major task that remains to be done. In
appendix D, we outline a research agenda.
The Siberian Curse
Pgs 51 - 53:
1. fsck! This is innovative?! Carlos! Dude! You've got a
*BRILLIANT* academic career just waiting to happen
with rigorous counterfactuals!
2. In terms of TPC, not real temperature.
> Carlos again. This actually has some meat on it, and looks
> like it will repay the effort.
Duluth will have to wait. Time is out for transcription.
Will
Old Toby
> By the way, are you aware a lot of Canada's immigrants are
> (as one might expect) from the subcontinent? I wonder how they hear
> terms like "Canuckistani"?
Actually, from what I've seen, Pakistanis tend to take more offense
when you leave out the "-stani" then when you attach it inapropriately...
And I've seen various immigrant groups use constructions not too far
from "Canuckistani" to refer to their own hybrid state, frex "Nuyorican"
for "New York Puerto Rican"
Old Toby
Least Known Dog on the Net
Coyu
a) I want to -- very carefully -- go through her regressions. I
think she misses an important variable or two regarding transport
and population. (Noel, this is where I might actually want to try
a gravity model. Hypothesis: Canada's population clusters near
the US border because the massive market weight of the US is
there. If the US had been replaced with the Khanate of Khiva,
would Canadian development followed the pattern it did?)
b) Is the problem one of lack of transparency in costs? The US
economy suffers large net losses because of traffic jams; but
they're not directly visible to the individual driver.
A utopianist might then conclude that we should all be using
ratnermollersegways. Look, the model suggests significant
productivity gains! Uh-huh.
b1) Expecting transparency in cold weather subsidies in
Russia is probably like expecting transparency in water
subsidies in the Sunbelt.
James Nicoll
Coyu <co...@aol.com> wrote:
>Hypothesis: Canada's population clusters near
>the US border because the massive market weight of the US is
>there. If the US had been replaced with the Khanate of Khiva,
>would Canadian development followed the pattern it did?)
Upper and Lower Canada offer some attractive features:
not _too_ cold (by our standards) and the Great Lakes plus
the St Lawrence are handy for shipping Central Canadian
goods to Europe.
lucky
"James Nicoll" <jdni...@panix.com> wrote in message
news:dslfhs$j7u$1...@reader2.panix.com...
> In article <1139674179.6...@g43g2000cwa.googlegroups.com>,
> Coyu <co...@aol.com> wrote:
>
>>Hypothesis: Canada's population clusters near
>>the US border because the massive market weight of the US is
>>there. If the US had been replaced with the Khanate of Khiva,
>>would Canadian development followed the pattern it did?)
>
> Upper and Lower Canada offer some attractive features:
> not _too_ cold (by our standards) and the Great Lakes plus
> the St Lawrence are handy for shipping Central Canadian
> goods to Europe.
Given climate I'm guessing no matter who was south of the line a great deal
of Canada's population would be along the border and that north/south trade
would be easier and more natural than east/west. The Maritimes' historic
grudge is that Confederation infringed on Atlantic seaboard trade with New
England to their detriment and to the favour of Central Canada. Unless a
truly economically repellent US existed that north/south draw would always
be there. Bulk transport is much easier/cheaper by sea.
Coyu
> >Hypothesis: Canada's population clusters near
> >the US border because the massive market weight of the US is
> >there. If the US had been replaced with the Khanate of Khiva,
> >would Canadian development followed the pattern it did?)
>
> Upper and Lower Canada offer some attractive features:
> not _too_ cold (by our standards) and the Great Lakes plus
> the St Lawrence are handy for shipping Central Canadian
> goods to Europe.
Okay, some further information on the Canadian developmental model
Mikhailova came up with. It's a typical economic linear regression
model. She divides Canada into 38/9 (counting Newfoundland after
its merger) regional units, and analyzes them thusly:
[warning: econ geek stuff ahead]
POPUL_t
Population in year t. Source: Census of Canada.
IND_t
Manufacturing employment in year t. Source: Census of Canada.
AREA
Area of the division, sq. km. For divisions containing more than
one census district, the areas of these districts were added up.
Source: Census of Canada, 1991.
TEMP
Average January temperature, degrees C. For large regions where
average temperature varies across the region, the temperature in
a largest city was taken.
DISTCAP
Direct (straight line) distance from a largest city in a region to
Toronto, or Moscow for the Russian version.
RR_t
Number of railroad branches leading from the largest city in a
year t. For any given region this characteristic can increase
over time as new railroads are built.
COAL_t
Dummy=1 if significant amount of coal was mined in a region in a
year t, and a region is a net exporter of coal. Mining sufficient
for the local needs only is ignored. This characteristic can
change over time, as new coalmines are explored or old mines are
closed.
METALS_t
Dummy=1 if significant amount of any metal ores were mined in a
region in a year t. The same definition of "significant operation"
as with coal is applied. Can vary with time.
OIL_t
Dummy=1 if significant amount of oil was extracted in a region in
a year t. The same definition of "significant operation" as with
coal is applied. Can vary with time.
TIMBER_t
Dummy=1 if at least 1/3 of the territory is covered with forrest
and the significant amount of logging is taking place. The same
definition of "significant operation" as with coal is applied. Can
vary with time.
PORT
Dummy=1, if a largest city in a region is a port. Included are
Canadian ports on the Atlantic and Pacific oceans, on Great lakes
and on St. Laurence river, and Russian ports on all seas and
Caspian lake.
R_ABROAD
Dummy=1 if there is a direct (not through some other region)
transportation route abroad from the largest city in a region.
Transportation routes are railroads, conventional roads, or
waterways.
FARMING
Dummy=1 if at least 1/3 of the land is classified as "having no
major obstacles for agriculture." For Canada, corresponds to land
type A and B in agricultural lands classification.
URBAN
Urbanization rate of the region in 1911. Source: Census of Canada.
Canadians, do these factors sound like plausible causes for 20th
century Canadian regional population growth or loss to you?
Mikhailova sets up a series of regressions, computing the
population and industrial employment for 1921 from 1911's data,
1931 from 1921 data, etc. Through a process of 'dynamic modeling',
she discards some year's variables as being unimportant for the
model. (It smacks a little of data mining to me, frankly. But
most of the variables she discards are the 'dummy' variables
regarding natural resource factor endowments, which I personally
think are pretty weak as explanatory variables for Canadian
regional population growth anyway.)
To come up with Russian counterfactual numbers, she puts Russian
1911 oblast/regional data through each decade's Canadian
regression, coming up with projected data for an alternate *1991.
So it's very important that the Canadian model produces plausible
results. Here's Mikhailova:
"First and foremost, the Canadian projection errors should be
examined (subjectively, at least) for any visible spatial bias. If
the differences between projected and actual population values do
not appear spatially random, the model is likely biased and should
not be used for the Russian projections."
"Second, the in-sample (Canadian) forecast error must be evaluated
numerically. Several criteria can be proposed to compare different
models. I use the sum of relative (weighted by the actual
population) squared differences between the actual and projected
populations in 1991."
"Of all possible models (i.e. subsets of explanatory variables) I
choose the one that minimizes [the above -- CY] equation. My
motivation was to choose the criterion that is focused on the
terminal period distribution and does not overlook the 'small'
low-populated regions -- the Canadian North, as this work is
focused mostly on the implications for its Russian counterpart --
Siberia and the Far East. Thus, weighting the errors by region's
population is necessary to guarantee equal treatment of all
regions. Only final year errors are taken into account."
So she's aware of the problem. What's the result, though?
"The model does worse predicting the population in large
metropolitan areas. Several regions with major cities (Vancouver,
Toronto, Montreal, Edmonton) have been growing fast during the
century and have strongly positive unexplained error -- actual
population is seriously higher than projected. The other large
cities (Winnipeg, Halifax, Ottawa, etc) have either negative or
near zero error. On average, however, the population of the
biggest metropolitan areas is underestimated."
It turns out that her Canadian model underpredicts the
population of the Vancouver area in 1991 by 660 thousand people,
the Toronto area by 1.3 million people, the Montreal area by 1.2
million people, and the Quebec city area by 250 thousand people.
(Her prediction for the Yukon and PEI is smack on, though.) In
comparison, Canada's population was 28 million in 1991.
So it appears that Mikhailova's model would claim for Canada
itself that its major urban areas are much too large! It's no
wonder she finds the same thing for Siberia's cities.
This seems to me a really weak reed to base any Russian domestic
policy decisions on.
Davi...@missouristate.edu
Well perhaps Canda's cities are larger than what a purely market based
economy would predict. Isn't there a tendency for central cities within
Canadian provinces? Is this tendency related to centralized
bureaucracies?
> This seems to me a really weak reed to base any Russian domestic
> policy decisions on.
Is the model a panel study? I think that would make more sense than a
normal time-series linear regression model.
What is the r-bar^2 of Mikhailova's model?
Perhaps it would make more sense to have a model that included
government employment (perhaps difficult to quantify for early years)
or government subsidies. Canadian development was influenced to some
degree by the government. How else could you explain Whitehorse?
If I was constructing a model like this I'd try to look into average
days of high temperatures below freezing. I think days of below
freezing high temperatures will vary by region (due to various
geographic factors) and be significant.
David Kohlhoff
Coyu
> Well perhaps Canda's cities are larger than what a purely market based
> economy would predict.
You misunderstand. This isn't an equilibrium model per se.
> > This seems to me a really weak reed to base any Russian domestic
> > policy decisions on.
>
> Is the model a panel study? I think that would make more sense than a
> normal time-series linear regression model.
Um, it's a panel dataset, used in a regression model. Mikhailova is
not sampling representative areas of Canada; she's using the whole
Mackenzie, divided into 30-odd parts.
> What is the r-bar^2 of Mikhailova's model?
It's supposedly 0.99 for the population, 0.98 for industrial
employment.
However, I have some doubts whether she used the right method to
calculate the correlation -- she gives a bulk r^2 with the total number
of observations for the whole set of regressions, while I would have
given r^2 for each decade's regression, and the number of samples
for each.
Also, the coefficients are much iffier for the industrial employment
regressions.
> Perhaps it would make more sense to have a model that included
> government employment (perhaps difficult to quantify for early years)
> or government subsidies.
It might, but then how do you apply it to Russia?
> If I was constructing a model like this I'd try to look into average
> days of high temperatures below freezing. I think days of below
> freezing high temperatures will vary by region (due to various
> geographic factors) and be significant.
Here's what I would use:
POPUL_t
Population in year t.
IND_t
Manufacturing employment in year t.
URBAN
Urbanization rate of the region in 1911.
AREA
Area of the regions, sq. km. For density effects.
TEMPJAN
Average January temperature, degrees C.
GROW
Average length of frost-free growing season.
DISTCAP
Direct (straight line) distance from a largest city in a region to
Toronto, or Moscow for the Russian version.
DISTUS
Direct (straight line distance) to the continental US. This factor
will be zeroed out in the Russian version, and also in a
counterfactual "Canada with no US" version. Note that DISTCAP and
DISTUS define a (degenerate) coordinate system for Canada.
TRANSCON
Dummy = 1 if the region includes the (non-core) primary
transcontinental railroad line.
PORT
Fraction of year important ports in region are not icebound; 0
if no ports.
PRIMPROD
Dummy = 1 if the region is a net exporter of coal, oil, metals,
or timber.
Davi...@missouristate.edu
> David Kohlhoff wrote:
>
> > Well perhaps Canda's cities are larger than what a purely market based
> > economy would predict.
>
> You misunderstand. This isn't an equilibrium model per se.
Oh.
> > > This seems to me a really weak reed to base any Russian domestic
> > > policy decisions on.
> >
> > Is the model a panel study? I think that would make more sense than a
> > normal time-series linear regression model.
>
> Um, it's a panel dataset, used in a regression model. Mikhailova is
> not sampling representative areas of Canada; she's using the whole
> Mackenzie, divided into 30-odd parts.
>
> > What is the r-bar^2 of Mikhailova's model?
>
> It's supposedly 0.99 for the population, 0.98 for industrial
> employment.
That seems much too high.
> However, I have some doubts whether she used the right method to
> calculate the correlation -- she gives a bulk r^2 with the total number
> of observations for the whole set of regressions, while I would have
> given r^2 for each decade's regression, and the number of samples
> for each.
>
> Also, the coefficients are much iffier for the industrial employment
> regressions.
>
> > Perhaps it would make more sense to have a model that included
> > government employment (perhaps difficult to quantify for early years)
> > or government subsidies.
>
> It might, but then how do you apply it to Russia?
Well I would include government employment in Canada (to capture the
effect it has on the other variables). Then I'd set a regression of
Russian regions'/cities' government employment using the other
variables (to mirror government employment following the Canadian
model).
In this manner government employment would not unduly bias the model
towards understating population in some metropolises.
> > If I was constructing a model like this I'd try to look into average
> > days of high temperatures below freezing. I think days of below
> > freezing high temperatures will vary by region (due to various
> > geographic factors) and be significant.
>
> Here's what I would use:
>
> POPUL_t
>
> Population in year t.
>
> IND_t
>
> Manufacturing employment in year t.
>
> URBAN
>
> Urbanization rate of the region in 1911.
>
> AREA
>
> Area of the regions, sq. km. For density effects.
>
> TEMPJAN
>
> Average January temperature, degrees C.
>
> GROW
>
> Average length of frost-free growing season.
Absolutely.
> DISTCAP
>
> Direct (straight line) distance from a largest city in a region to
> Toronto, or Moscow for the Russian version.
>
> DISTUS
>
> Direct (straight line distance) to the continental US. This factor
> will be zeroed out in the Russian version, and also in a
> counterfactual "Canada with no US" version. Note that DISTCAP and
> DISTUS define a (degenerate) coordinate system for Canada.
>
> TRANSCON
>
> Dummy = 1 if the region includes the (non-core) primary
> transcontinental railroad line.
>
> PORT
>
> Fraction of year important ports in region are not icebound; 0
> if no ports.
>
> PRIMPROD
>
> Dummy = 1 if the region is a net exporter of coal, oil, metals,
> or timber.
Why?
Would relative prices be that different?
David Kohlhoff
Coyu
> > > What is the r-bar^2 of Mikhailova's model?
> >
> > It's supposedly 0.99 for the population, 0.98 for industrial
> > employment.
>
> That seems much too high.
Yes. Like I said, I have some doubts here.
> > > Perhaps it would make more sense to have a model that included
> > > government employment (perhaps difficult to quantify for early years)
> > > or government subsidies.
> >
> > It might, but then how do you apply it to Russia?
>
> Well I would include government employment in Canada (to capture the
> effect it has on the other variables). Then I'd set a regression of
> Russian regions'/cities' government employment using the other
> variables (to mirror government employment following the Canadian
> model).
>
> In this manner government employment would not unduly bias the model
> towards understating population in some metropolises.
Um. In the Soviet Union -- the comparison to which is the whole
point of this exercise -- there was very little private enterprise.
In effect, everyone was a government employee.
My question isn't how-because-I-don't-know-how-to-do-it but how-
because-how-would-that-tell-you-anything-you-didn't-already-know?
> > PRIMPROD
> >
> > Dummy = 1 if the region is a net exporter of coal, oil, metals,
> > or timber.
> Why?
> Would relative prices be that different?
Again, this is not an equilibrium model. There is nothing about
prices here. I would include this variable to see whether
extraction industries were a significant factor in Canadian
regional growth. Because they certainly were in Russia.
Davi...@missouristate.edu
> David Kohlhoff wrote:
>
> > > > What is the r-bar^2 of Mikhailova's model?
> > >
> > > It's supposedly 0.99 for the population, 0.98 for industrial
> > > employment.
> >
> > That seems much too high.
>
> Yes. Like I said, I have some doubts here.
>
> > > > Perhaps it would make more sense to have a model that included
> > > > government employment (perhaps difficult to quantify for early years)
> > > > or government subsidies.
> > >
> > > It might, but then how do you apply it to Russia?
> >
> > Well I would include government employment in Canada (to capture the
> > effect it has on the other variables). Then I'd set a regression of
> > Russian regions'/cities' government employment using the other
> > variables (to mirror government employment following the Canadian
> > model).
> >
> > In this manner government employment would not unduly bias the model
> > towards understating population in some metropolises.
>
> Um. In the Soviet Union -- the comparison to which is the whole
> point of this exercise -- there was very little private enterprise.
> In effect, everyone was a government employee.
>
> My question isn't how-because-I-don't-know-how-to-do-it but how-
> because-how-would-that-tell-you-anything-you-didn't-already-know?
The model was made to explain Canadian regional growth. Accounting and
correcting for government employment shows what regional growth would
be without that employment. I'd expect this to get rid of some
underestimation of some Canadian metropolises. Once you use the model
for Russian regional growth you could drop the government employees
coefficient and variable for all I care (your other coefficients would
have some of their downward bias corrected though). I was just pointing
out that an accurate model would correct for this downward bias in
Canada's population before applying the model to Russia.
>
> > > PRIMPROD
> > >
> > > Dummy = 1 if the region is a net exporter of coal, oil, metals,
> > > or timber.
> > Why?
> > Would relative prices be that different?
>
> Again, this is not an equilibrium model. There is nothing about
> prices here. I would include this variable to see whether
> extraction industries were a significant factor in Canadian
> regional growth. Because they certainly were in Russia.
Ok well how likely is that data to be available far back for regions?
David Kohlhoff
Coyu
> > > Well I would include government employment in Canada (to capture the
> > > effect it has on the other variables). Then I'd set a regression of
> > > Russian regions'/cities' government employment using the other
> > > variables (to mirror government employment following the Canadian
> > > model).
> > >
> > > In this manner government employment would not unduly bias the model
> > > towards understating population in some metropolises.
> >
> > Um. In the Soviet Union -- the comparison to which is the whole
> > point of this exercise -- there was very little private enterprise.
> > In effect, everyone was a government employee.
> >
> > My question isn't how-because-I-don't-know-how-to-do-it but how-
> > because-how-would-that-tell-you-anything-you-didn't-already-know?
>
> The model was made to explain Canadian regional growth.
No. The model was made to use as a counterfactual in Russian
economic growth, to see how Russia would have developed along
Canadian lines.
Part of successful model building is knowing what to abstract. For
example, I might construct a model of Canadian regional growth
that splits its population groups between Anglophones and
Francophones. It might give me more accurate results. But if my
purpose in constructing the model was to compare cold country
regional growth, it would be kind of silly to include it, since
there's no close parallel to the A/F divide in Russia.
> > > > PRIMPROD
> > > >
> > > > Dummy = 1 if the region is a net exporter of coal, oil, metals,
> > > > or timber.
> > > Why?
> > > Would relative prices be that different?
> >
> > Again, this is not an equilibrium model. There is nothing about
> > prices here. I would include this variable to see whether
> > extraction industries were a significant factor in Canadian
> > regional growth. Because they certainly were in Russia.
>
> Ok well how likely is that data to be available far back for regions?
... the data were available for the original model. This dummy
variable simply combines the coal, oil, metal, and timber dummy
variables in Mikhailova's original.
Davi...@missouristate.edu
> David Kohlhoff wrote:
>
> > > > Well I would include government employment in Canada (to capture the
> > > > effect it has on the other variables). Then I'd set a regression of
> > > > Russian regions'/cities' government employment using the other
> > > > variables (to mirror government employment following the Canadian
> > > > model).
> > > >
> > > > In this manner government employment would not unduly bias the model
> > > > towards understating population in some metropolises.
> > >
> > > Um. In the Soviet Union -- the comparison to which is the whole
> > > point of this exercise -- there was very little private enterprise.
> > > In effect, everyone was a government employee.
> > >
> > > My question isn't how-because-I-don't-know-how-to-do-it but how-
> > > because-how-would-that-tell-you-anything-you-didn't-already-know?
> >
> > The model was made to explain Canadian regional growth.
>
> No. The model was made to use as a counterfactual in Russian
> economic growth, to see how Russia would have developed along
> Canadian lines.
But the model underestimates the population of many Canadian cities.
This would make the model difficult to validly interpret for Russian
cities. How would you correct for that?
<snip>
>
> > > > > PRIMPROD
> > > > >
> > > > > Dummy = 1 if the region is a net exporter of coal, oil, metals,
> > > > > or timber.
> > > > Why?
> > > > Would relative prices be that different?
> > >
<snip>
> ... the data were available for the original model. This dummy
> variable simply combines the coal, oil, metal, and timber dummy
> variables in Mikhailova's original.
I'd expect a very large variation among the 1's of this variable. A
region that exports metal and coal is unlikely to be similar to a
region that exports oil.
David Kohlhoff
Coyu
> > > > > Well I would include government employment in Canada (to capture the
> > > > > effect it has on the other variables). Then I'd set a regression of
> > > > > Russian regions'/cities' government employment using the other
> > > > > variables (to mirror government employment following the Canadian
> > > > > model).
> > > > >
> > > > > In this manner government employment would not unduly bias the model
> > > > > towards understating population in some metropolises.
> > > >
> > > > Um. In the Soviet Union -- the comparison to which is the whole
> > > > point of this exercise -- there was very little private enterprise.
> > > > In effect, everyone was a government employee.
> > > >
> > > > My question isn't how-because-I-don't-know-how-to-do-it but how-
> > > > because-how-would-that-tell-you-anything-you-didn't-already-know?
> > >
> > > The model was made to explain Canadian regional growth.
> >
> > No. The model was made to use as a counterfactual in Russian
> > economic growth, to see how Russia would have developed along
> > Canadian lines.
>
> But the model underestimates the population of many Canadian cities.
> This would make the model difficult to validly interpret for Russian
> cities. How would you correct for that?
Argh. DK, have you _read_ what I've been writing? I would not use
Mikhailova's model. I don't like Mikhailova's model. I don't _trust_
Mikhailova's model. I've described how I would make a start at
correcting it in previous posts.
Please, some reading comprehension, DK. I know you can. I've
respected you by answering comments of yours that I've found
incredibly silly. Please do the same for me.
> > ... the data were available for the original model. This dummy
> > variable simply combines the coal, oil, metal, and timber dummy
> > variables in Mikhailova's original.
>
> I'd expect a very large variation among the 1's of this variable. A
> region that exports metal and coal is unlikely to be similar to a
> region that exports oil.
I myself would not. Modern resource extraction industries have
much more in common developmentally than you seem to realize.
Davi...@missouristate.edu
> David Kohlhoff wrote:
> > > ... the data were available for the original model. This dummy
> > > variable simply combines the coal, oil, metal, and timber dummy
> > > variables in Mikhailova's original.
> >
> > I'd expect a very large variation among the 1's of this variable. A
> > region that exports metal and coal is unlikely to be similar to a
> > region that exports oil.
>
> I myself would not. Modern resource extraction industries have
> much more in common developmentally than you seem to realize.
So would the dummy be '1' if the region was net exporter at the start
or at the end or over aggregated over the entire period?
While modern resource extraction industries have much in common was
this true for all periods the data covers?
David Kohlhoff
Coyu
> > > > ... the data were available for the original model. This dummy
> > > > variable simply combines the coal, oil, metal, and timber dummy
> > > > variables in Mikhailova's original.
> > >
> > > I'd expect a very large variation among the 1's of this variable. A
> > > region that exports metal and coal is unlikely to be similar to a
> > > region that exports oil.
> >
> > I myself would not. Modern resource extraction industries have
> > much more in common developmentally than you seem to realize.
>
> So would the dummy be '1' if the region was net exporter at the start
> or at the end or over aggregated over the entire period?
David, what part of "Dummy=1 if significant amount of [x were
extracted] in a region in a year t" did you not understand?
If you're not going to read the thread before you comment, why
are you bothering to comment?
Davi...@missouristate.edu
I'm going to go away for a while.
Dave
Coyu
> > > So would the dummy be '1' if the region was net exporter at the start
> > > or at the end or over aggregated over the entire period?
> >
> > David, what part of "Dummy=1 if significant amount of [x were
> > extracted] in a region in a year t" did you not understand?
> >
> > If you're not going to read the thread before you comment, why
> > are you bothering to comment?
>
> I'm going to go away for a while.
I'm not trying to be harsh, but jeez. These are not hard things.
The Horny Goat
>Again, this is not an equilibrium model. There is nothing about
>prices here. I would include this variable to see whether
>extraction industries were a significant factor in Canadian
>regional growth. Because they certainly were in Russia.
Given that the start date of the study was 1911 there would certainly
have been SOME regions of Canada where mining was important.
I don't have any empirical data to offer but the regions of Canada
where mining is important now are not the same areas as nearly a
century ago. For instance I don't believe nickel had been discovered
in Sudbury in 1911. Nor was pretty much anything in British Columbia
known about mining except that there had been a gold rush in the 1850s
and that there was coal in the Nanaimo area (long ago worked out). The
silver / lead / zinc mines of the Kootenays had yet to be discovered.
Nor do I think people were even fantasizing about Leduc much less
finding anything worthwhile there.
Coyu
> I don't have any empirical data to offer but the regions of Canada
> where mining is important now are not the same areas as nearly a
> century ago. For instance I don't believe nickel had been discovered
> in Sudbury in 1911.
Actually, it had been known, as a significant and bothersome
impurity in Sudbury copper, since the 1880s. The mining consortium
considered buying off the Mond carbonyl process (so beloved by
asteroid mining geeks) in order to process it, but negotiations fell
through. Then Mond bought property in Sudbury of his own.
[googling] Apparently even Thomas Edison got in on the act, since
he needed nickel for a new form of storage battery.
Anyway, this was all well before 1911.
The Horny Goat
OK fair enough - I realized after I made the original posting that I
could easily have Googled the city of Sudbury website and found the
answers you're giving fairly readily. Around here we call that a
"Homer Simpson moment"
I'm not sure why I didn't do that since I routinely Google municipal
websites to check facts on SHWI - I did that most recently with the
fellow who posted a mini-scenario involving the cities of Victoria and
Ottawa in the 1840s - I was pretty sure I had my facts straight but
did the checking to confirm I was right (in this case I was).
Having said that I share your view that the Russian scenario produces
entirely dodgy results when applied to Canada and strongly suspect the
results would look even stranger if applied to the USA.
The Horny Goat
>It turns out that her Canadian model underpredicts the
>population of the Vancouver area in 1991 by 660 thousand people,
>the Toronto area by 1.3 million people, the Montreal area by 1.2
>million people, and the Quebec city area by 250 thousand people.
>(Her prediction for the Yukon and PEI is smack on, though.) In
>comparison, Canada's population was 28 million in 1991.
>
>So it appears that Mikhailova's model would claim for Canada
>itself that its major urban areas are much too large! It's no
>wonder she finds the same thing for Siberia's cities.
>
>This seems to me a really weak reed to base any Russian domestic
>policy decisions on.
As a point of information, when she says 'large' does she mean
population or land area? Vancouver proper is considerably more densely
packed than Toronto and Montreal while Calgary and Edmonton are less
densely packed. I'll simply note in passing that the 'shortfalls' in
Vancouver, Montreal and Toronto are all short by roughly the same
percentage.
I don't think it takes PhD level knowledge to predict from 1911 data
the current populations of regions that are at most 100k or 150k
(Yukon and PEI)
At the same time one thing obviously not included in her study is that
both Canada and the United States were FAR more attractive to migrants
in 1911 (or pretty much ANY time during 1911 to 1991) than Russia and
that there might perhaps be a reason for that.