Very, very interesting.

Thank you very much for your post.

Peace and best wishes.

Xi

On Mar 26, 5:41 pm, antidefm <[email protected]> wrote:
> http://www.russiatoday.com/About_Us/Blogs/With_words_we_govern_men___...
>
> Most scholars have omitted economics in studies of war. However,
> economics and war are inseparable. Most previous studies have looked
> at the effects of war on economies of states. Today, when most
> developed or developing states have settled down, domestic economies
> and internal stability (by oppression or allowed freedoms) become top
> priorities. So, why do states fight each other? There are those that
> believe the cause to be simply the thirst for power, but some believe
> that it is more complex. Nevertheless, neither have done analyses of
> economies of states, and very few have gone as far as trying to
> explain why some states initiate attacks on other states.
>
> Narrowing down the beginning of this path to determine the correlation
> between economics and war, we first should look at economic stability.
> States that feel they cannot sustain a war effort are unlikely to go
> to war. But how would stability of an economy be measured? When
> investors look at futures, options, bonds, and stock markets, they
> often consider volatility of prices in order to see which commodity,
> firm, or bond has the least volatility. That means that investors look
> at entries that can provide them the most stability. This formula can
> also be looked at to compare two states’ economies on the same level,
> regardless of the size of the real GDP or its real growth. The
> volatility formula is such:
>
> LOGSi = LOG(Pi / P(i-1))
> • LOG is the logarithmic function.
> • Pi is the current price
> • Pi-1 is the previous price
>
> ALOGS = Tlogs / n
> • ALOGS is the average of the logarithms.
> • Tlogs is the total of the logarithm for the time span.
> • n is the number of periods for the specified time span.
>
> • SSD is the sum of the squared differences.
> • indicates to add the squares of all n differences.
> • LOGSi is the logarithm of the price change for period i.
> • ALOGS is the average of the logarithms.
>
> • HV stands for Historic Volatility
> • TP = Total Periods
>
> What I have done is to gather a list of interstate conflicts from
> 1980-2003 (real GDP data is not completely available for the most
> current period). I gathered real GDP data from 1970-2003 for all
> states involved in the conflicts, broke them down according to
> attacking and defending states (attacking states having initiated the
> attack on the internationally recognized territory of the defending
> state), and then ran the formula for each of the states taking into
> account 5 years of real GDP data prior to the conflict. That is, if
> the conflict initiated in 1980, I would need to look at the years
> 1974-1979 for volatility.
>
> Here is the table that I came up with after running the stats.
>
> (click the original link to see the 
> table)http://www.russiatoday.com/About_Us/Blogs/With_words_we_govern_men___...
>
> This table shows us that when two states face off against one another,
> the state with the higher real GDP volatility (that is, more unstable)
> will most likely get attacked by its rival. This table does not
> explain the reasons for the two nations going to war, but it is one of
> the first explanations needed to support the theory presented in a
> previous article that I wrote for RT titled Why Do We Go To War?
>
> It is necessary to look at the economies of both states involved in a
> dispute because that will present a more clear picture of which state
> is more likely to attack first, thus instigating an open conflict.
>
> To reiterate the theory being researched:
>
> A nation will be attacked if it has a weak economy compared to its
> rival, a strong central ideology, and if it presents a threat to the
> free flow of resources.
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