Christopher A. Lawrence, War by Numbers Understanding Conventional Combat (Lincoln, NE: Potomac Books, 2017) 390 pages, $39.95
War by Numbers assesses the nature of conventional warfare through the analysis of historical combat. Christopher A. Lawrence (President and Executive Director of The Dupuy Institute) establishes what we know about conventional combat and why we know it. By demonstrating the impact a variety of factors have on combat he moves such analysis beyond the work of Carl von Clausewitz and into modern data and interpretation.
Using vast data sets, Lawrence examines force ratios, the human factor in case studies from World War II and beyond, the combat value of superior situational awareness, and the effects of dispersion, among other elements. Lawrence challenges existing interpretations of conventional warfare and shows how such combat should be conducted in the future, simultaneously broadening our understanding of what it means to fight wars by the numbers.
The book is available in paperback directly from Potomac Books and in paperback and Kindle from Amazon.
I just received my 15 author copies of War by Numbers. So it is now available for $39.95 from Potomac Books (University of Nebraska Press): War by Numbers
This means it should be available from Amazon.com next week: War by Numbers
I don’t how quickly the foreign book sellers will receive them, but expect them to have copies available in the next couple of weeks.
I did not order 200 copies for The Dupuy Institute to sell, unlike I did with America’s Modern Wars, so it will not be directly available from us: http://www.dupuyinstitute.org/booksfs.htm
This figure is on page 175 of the book, Chapter 14: Advance Rates:
Continuing with the next posting on the nineteenth lecture from Professor Michael Spagat’s Economics of Warfare course that he gives at Royal Holloway University. It is posted on his blog Wars, Numbers and Human Losses at: https://mikespagat.wordpress.com/
This lecture continues the discussion of terrorism, this time he is looking at a paper by Gassebner and Luechinger on terrorism (starts on page 13 of the lecture). This is similar to what was done for causes of war in a paper by Hegre and Sambanis that was presented in lecture 11:
So, the two authors ended up running a large number of regressions trying out many different combinations of variables and looking for those that are consistently significant. They used three different terrorism databases, resulting in them testing 18 different variables to each of the three different databases and looking at locations, victims and perpetrators (see slides 14 and 15). This gets a little involved and you are probably not going to sort it all out unless you read their paper (which costs $40 to order a copy…I did not).
What is particularly interesting to me is that the same variable has different values depending on what database is used. The values are of Coef. (median coefficient estimate), CDF (cumulative distribution function) and % sig. (the percent the estimate was statistically signicant). For example “Ethnic tensions” has values of -0.0007, 0.544 and 18.4 in the Iterate database, has values of 0.040, 0.911 and 63.1 in the GTD databases, and has values of 0.011, 0.627 and 15.2 in the MIPT database. Not sure what this really means (see slide 14). I have never done any analysis using someone else’s data base. I have always collected by own data and analyzed it.
Anyhow, the results are (see slides 18 & 19).
Strong police states with religious tensions seem to be favored targets of terrorists.
Bigger, economically repressive and richer countries seem to attract terrorist attacks.
“Law and order” seems to discourage terrorism (this does conflict with point 1 above).
A more foreign portfolio investment seen positively associated with terrorism.
Higher natural resource exports as associated with fewer attacks on a county’s citizens.
Citizens from countries with a “youth bulge” are attacked relatively less and do not attack more often.
Fewer telephones are associated with more attacks.
Countries with centrist governments seem to export terrorists
Tom Lea, “The 2,000 Yard Stare” 1944 [Oil on canvas, 36 x 28 Life Collection of Art WWII, U.S. Army Center of Military History, Fort Belvoir, Virginia]
That idea that fatigue is a human factor in combat seems relatively uncontroversial. Military history is replete with examples of how the limits of human physical and mental endurance have affected the character of fighting and the outcome of battles. Perhaps the most salient aspect of military training is preparing soldiers to deal with the rigors of warfare.
Trevor Dupuy was aware that fatigue has a degrading effect on the effectiveness of troops in combat, but he never was able to study the topic specifically himself. He was aware of other examinations of historical experience that were relevant to the issue.
An approximate value for the daily effect of fatigue upon the effectiveness of weapons employment emerged from a HERO study several years ago. There is no question that fatigue has a comparable degrading effect upon the ability of a force to advance. I know of no research to ascertain that effect. Until such research is performed, I have arbitrarily assumed that the degrading effect of fatigue upon advance rates is the same as its degrading effect upon weapons effectiveness. To those who might be shocked at such an assumption, my response is: We know there is an effect; it is better to use a crude approximation of that effect than to ignore it…
During World War II when Colonel S.L.A. Marshall was the Chief Historian of the US European Theater of Operations, he undertook a number of interviews of units just after they had been in combat. After the war, in his book Men Against Fire, Marshall asserted that his interviews revealed that only 15% of US infantry soldiers fired their small arms weapons in combat. This revelation created something of a sensation at the time.
It has since been demonstrated that Marshall did not really have solid, scientific data for his assertion. But those who criticize Marshall for unscholarly, unscientific work should realize that in private life he was an exceptionally good newspaper reporter. His conclusions, based upon his observations, may have been largely intuitive, but I am convinced that they were generally, if not specifically, sound…
One of the few examples of the use of military history in the West in recent years was an important study done at the British Defence Operational Analysis Establishment (DOAE) by David Rowland. An unclassified condensation of that study was published in the June 1986 issue of the Journal of the Royal United Services Institution (RUSI). The article, “Assessments of Combat Degradation,” demonstrates conclusively that, in historical combat, small arms weapons have had only one-seventh to one-tenth of their theoretical effectiveness. Rowland does not attempt to say why this is so, but it is interesting that his value of one-seventh is very close to the S. L. A. Marshall 15% figure. Both values translate into casualty effects very similar to those that have emerged from my own research.
The intent of this post is not to rehash the debate on Marshall. As Dupuy noted above, even if Marshall’s conclusions were not based on empirical evidence, his observations on combat were nevertheless on to something important. (Details on the Marshall debate can be easily found with a Google search. A brief discussion took place on the old TDI Forum in 2007.)
The exhaustion factor (ex) of a fresh unit is 1.0; this is the maximum ex value.
At the conclusion of an engagement, a new ex factor will be calculated for each side.
A unit in normal offensive or defensive combat has its ex factor reduced by .05 for each consecutive day of combat; the ex factor cannot be less than 0.5.
An attacking unit opposed by delaying tactics has its ex factor reduced by 0.05 per day.
A defending unit in delay posture neither loses nor gains in its ex factor.
A withdrawing unit, not seriously engaged, has its ex factor augmented at the rate of 0.05 per day.
An advancing unit in pursuit, and not seriously delayed, neither loses nor gains in its ex factor.
For a unit in reserve, or in non-active posture, an exhaustion factor of less than 1.0 is augmented at the rate of .1 per day.
When a unit in combat, or recently in combat, is reinforced by a unit at least half of its size (in numbers of men), it adopts the ex factor of the reinforcing unit or—if the ex factor of the reinforcing unit is the same or lower than that of the reinforced—both adopt an ex factor 0.1 higher than that of the reinforced unit at the time of reinforcement, save that an ex factor cannot be greater than 1.0.
When a unit in combat, or recently in combat, is reinforced by a unit less than half its size, but not less than one quarter its size, augmentations or modifications of ex factors will be 0.5 times those provided for in paragraph 9, above. When the reinforcing unit is less than one-quarter the size of the reinforced unit, but not less than one-tenth its size, augmentations or modifications of ex factors will be 0.25 times those provided for in paragraph 9, above.
* Approximate reflection of preliminary QJM assessment of effects of casualty and fatigue, WWII engagements. These rates are for division or smaller size; for corps and larger units exhaustion rates are calculated for component divisions and smaller separate units.
EXAMPLES OF APPLICATION
A division in continuous offensive combat for five days stays in the line in inactive posture for two days, then resumes the offensive:
Combat exhaustion effect: 1 – (5 x .05) = 0.75;
Recuperation effect: 75 + (2 x .l) = 0.95.
A division in defensive posture for fifteen days is ordered to undertake a counterattack:
Combat exhaustion effect: 1 – (15 x .05) =0.25; this is below the minimum ex factor, which therefore applies: 0.5;
Recuperation effect: None; ex factor is 0.5.
A division in offensive posture for three days is reinforced by two fresh brigades:
Combat exhaustion effect: 1 – (3 x .05) = 0.85;
Reinforcement effect: Augmentation from 0.85 to 1.0.
A division in offensive posture for three days is reinforced by one fresh brigade:
Combat exhaustion effect: 1 – (3 x .05) = 0.85;
Reinforcement effect: 0.5 x augmentation from 0.85 to 1 = 0.93.
Continuing with a second posting on the nineteenth and second to last lecture from Professor Michael Spagat’s Economics of Warfare course that he gives at Royal Holloway University. It is posted on his blog Wars, Numbers and Human Losses at: https://mikespagat.wordpress.com/
This lecture continues the discussion of terrorism, this time he is looking at a paper by Gassebner and Luechinger on terrorism. This is similar to what was done for causes of war in a paper by Hegre and Sambanis that was presented in lecture 11:
This discussion of Hegre and Sambanis covered only the last two pages of the lecture (slides 23 and 24 of lecture 11) and I did not mention it when I first blogged about it.. I guess I probably need to now, turning this posting into the follow-up post on lecture 11. Hegre and Sambanis looked at 88 variables related to causes of war and by running regressions tried to determine which ones are consistently correlated with the onset of war.
GDP per capita is negatively associate with civil war onset (meaning: rich countries are less likely to have civil wars).
Having had a previous war is positively associated with civil war onset…the more recent the war the stronger the association (meaning: war beget wars?).
Country size (population and territory) is positively associated with civil war onset (meaning: big countries tend to have more wars.).
This last point is interesting as country size and population also showed up in our insurgency studies related to the success of the insurgents. Big populated counties tended to have more successful insurgencies than small countries. In Chapter 3, page 47 of America’s Modern Wars I provided the following chart:
Insurgencies with Foreign Intervention
Circumstances Number of cases Percent Blue Victory
Indigenous Population > 9 million 10 20
Intervening Force Commitment > 100,000 8 0
Peak Insurgent Force Size > 30,000 13 23
“Blue Victory” = counterinsurgent victory
Anyhow, I have not gotten past the first sentence of slide 13 for this post, and we are already around 300 words in this post, so probably best to pick up the rest of lecture 19 in a subsequent post.
One of my earliest blog posts, done in December 2015 was on “Defeating an Insurgency by Air.” It was in part inspired by the Republican debate at the time and people talking about “carpet bombing” ISIL.
I gather the part of the article that gives people heartburn is: “So, we are left to state that we cannot think of a single insurgency that was defeated by airpower, primarily defeated by airpower, or even seriously undermined by airpower. Perhaps there is a case we are missing. It is probably safe to say that if it has never successfully been done in over a hundred insurgencies over the last hundred years, then it is something not likely to occur now.”
Now, we do go on a hunt for other cases. This led to the follow-up blog posts:
This last post was actually not tagged as an “air power” subject, but I felt it was particularly relevant….and yes, we do have two blog posts with the same title. But this second one has this cool graph: