Proof of Peace Economics
The proof of Peace Economics rests not just in correlations with productivity and capital investment over -.99. It further goes on to create accurate long term models in America and Germany and the World Economy with similarly high correlations. Then it was further tested roughly by decade over the twentieth century to see if it applies generally to the major countries, and in subsequent time periods after the initial 1986 models were built, and in all cases the concept continues to apply well. It also applies to explain regional economic growth 1981-1985 and in regional unemployment changes 1985-1991 with correlations of 0.97. Then there is the World War II correlation of -.97 from 1941-1948 between military burden and the economy. There are just too many high correlations in highly varied tests to be just chance or autocorrelation or some other excuse for doubt.
When Ruth Leger Sivard published a nineteen year study of the seven leading capitalist economies plus Sweden and Denmark, she was satisfied to present it as a bar chart in her new reference work World Military and Social Expenditures when she went private after leaving the public sector under the Reagan administration in 1981. The editor of the Journal of Peace Research in Oslo connected to the Nobel Peace Prize published an article that took that data and came up with a correlation of -.81 between military spending presented as a percentage of each nation’s economy and the rate of growth of manufacturing productivity in that same nation. I started by decoding the bar chart into numbers and ran the first correlation at -.81. But I also graphed the bar chart results with military spending on the x axis and manufacturing productivity on the y axis. It was obvious from the graph that Canada was an outlier. Dropping Canada, the correlation improves to -.98. I noticed that Britain and France were somewhat off the straight trade-off line where the two statistics add up to 9 for each nation approximately. So I tried using weighted averages to compute an English America and Western Europe data point. Amazingly, this three point continental correlation (with Japan for East Asia) was now a stunning -.997, a perfect one when rounded to two decimal places. This stable Western World economy operating under the Bretton Woods trade regime showed that all these nations were so similar that the only long term difference was the military. The first conclusion was that resources used in the military were just like other manufacturing resources but without a product useful in the civilian economy. Hence military spending lowered the economic growth curve by diverted resources from the heart of the economy to a political purpose outside of any benefit contributed to the economy. Although military spending pumps lots of money into the economy and supports many communities, no one is fed, clothed, housed, or transported by military operations. The tail is there but not the head. The inputs are there but not the outputs. Those who work in the military “factory” benefit, but they produce nothing tangible for the benefit of the rest of society, just all the abstract platitudes about defending the society which does not boost the economy. That’s what the math says, that’s not just my own platitude.
In Ruth Sivard’s second issue she published a bar chart showing the inverse relationship between military spending and capital investment over a twenty year period with the same countries. My work with these numbers shows that capital investment plus military spending equals a common total of about 20.5% of GDP for these five countries: United States, Germany, France, Britain, and Sweden. These are the four largest NATO countries and the largest Scandinavian country. Japan over-performs on this test (25% of GDP) and the secondary economies of their respective continents, Canada and Italy underperform (17% of GDP). Others have found this military capital trade-off in countries as diverse as Australia and Finland. The five country correlation is -.993. This would also explain the first productivity finding, that military spending is essentially lost capital investment.
LONG TERM MODEL
The common period cross cultural comparisons of Sivard are a good first step, but will the concept perform for a slightly more complex model of the United States from 1920 to 1983, a longitudinal model in one country? The answer was a loud yes, first beginning with my work in progress in December 1985 of the first three decades after WWII. Military spending alone was where I started all investigations, then adjusted as necessary to add other factors. The first factor added was the deficit. The huge amounts of military spending were almost completely offset by deficits for America during the war. Although this alone seemed to make the deficit a positive able to offset the military negative, there were other confirming cases such as after WWI and again after the 1936, 1978 and 1990 tax increases and the massive tax cuts under Reagan. The second factor was the 54 year cycle. Various multiyear averagings were used on the economic growth data to locate the economic tops and bottoms. Fortunately, majorities of these moving averages would usually agree on one year as the top or bottom. By this method, 1898 and 1952 are tops and 1928 and 1982 are bottoms. Then the literature suggested competing evidence for military spending leading to economic growth or slowing economic growth. The modeling of adding back the missing military to the actual economic growth showed clear camel’s hump bulges after WWII for both America and Germany, high in the fifties, lower in the sixties and seventies. This was the Kondratiev Wave, and it verified that military spending reduced economic growth. A friend gave me a book in 1981 before I knew about Sivard (and when I still believed in military Keynesianism) that specified the Kondratiev Wave. It was a 24 year up cycle and a 30 year down cycle. Testing the economic growth data, I came up with an amplitude of plus 3% to minus 3% of the underlying economic growth rate. Because I’m an engineer, I knew that a sine wave was the answer to a differential equation, so I used a sine wave with the just mentioned parameters to begin the modeling. I did not have to alter any of the parameters after that. I compared the actual manufacturing productivity each year with the model predicted manufacturing productivity. There were significant differences each year. But then I wondered if these differences would smooth out over time, so I accumulated the differences continuously over time. Lo and behold, most astonishingly, the differences would completely cancel out over time every eight, nine, or ten years. These cycles are called Juglar cycles. The common sense model was complete. Measuring the Juglar cycles, the correlation was once again .999. It could be slightly lower if you allowed for degrees of freedom, but that does not make sense since the parameters were each independently derived.
SHORT TERM EFFECTS
All the long term data indicate a physics-like level of proof for longer periods of time and larger economic areas. So when the regional results came in at correlation .97 for the Reagan buildup or the end of Cold War builddown of the military, that slightly lower result was consistent, as the units were only part of a nation, actually 16 or 17 mini-regions, because cities are the economic hubs, not states. For example, WI IL IN is greater Chicago, and CT NY NJ is greater New York. Then the year by year results actually showed a year by year direct effect of military budget changes. Two or three year trends were more accurate than single year effects. The only area where military spending appears to stimulate an economy and lower military spending lowers the economy is the war situation. But this is an illusion, because the adrenaline flows in the beginning of wars and ebbs after. The war boom postwar bust is the exception that proves the rule. Actually military spending not covered for by deficits will bring an economy down quickly; see my detailed analysis of WWII. The war bonding kept pace with the military in 1942 and 1943 as the economic growth matched New Deal levels, then failed to keep up with the military spending cutting the growth rate in half in 1944, doubled the gap between military and deficit in 1945 leading to negative growth that year. The longer the war runs, the deeper the postwar recession for just these types of reasons. The Kennedy tax cuts actually were responsible for only one third of the economic change from the slow growth fifties to the high growth sixties. The military cuts were the other two thirds of the economic boost. Then the nineties end of the Cold War initially created a post war slump that later doubled the economic growth rate under Clinton due to lower military spending. Nobel Laureate and Clinton economist Stiglitz says as much in a British newspaper editorial.
The accuracy of my economic models make it extremely implausible that anything more accurate could show up and compete with those models. And I did not detail here all the many year by year verifications of the basics in the model. There are no major events of the economy of 20th century America that do not conform to the models I’ve developed to explain it all. The economic model makes other explanations look exceedingly pale by comparison, as twenty year 99% accuracy after twenty year 99% accuracy creates an elegant 99% accurate 64 year simple model of manufacturing productivity, the essence of economic growth. This model will be the new physics-like backbone to the social sciences, as precision empire modeling and cycle theory replace the sloppiness in existing macroeconomics and climate change theories.
As published in the original Peace Economics book, still ahead of its time in 2014:
Here are all the numbers used in the US model from 1920 to 1983 and the detailed write-up:
Dr. Peace, Dr. Bob Reuschlein,
best contact firstname.lastname@example.org
to leave message 608-230-6640
for more info http://www.realeconomy.com (Peace Economics 1986 available for $10 ebook)