Category Insurgency & Counterinsurgency

Economics of Warfare 12

Examining the twelfth 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 paper continues with discussion of the studies done by Fearon and Laitin (lecture 11, slide 5) and Collier and Hoeffler (lecture 11, slide 15) on civil wars. The lecture basically goes through and tests or challenges their papers in two areas: 1) ability to predict, and 2) causality.

Warning: This lecture may cause you to lose confidence in multi-variant regression models.

I already had. If you go to my book America’s Modern Wars, in Chapter 6 (pages 63-69) I propose a two-variable model of insurgency success or failure. I then tested the model back to the cases I used to make up the model and the model predicted the correct result in 53 out of 68 cases used (77.9%). The model predicted incorrectly in 15 cases, or over 20% of the time. Now, if I was at a blackjack table in Vegas, I would be pretty damn happy to predict the outcome of game almost 80% of the time. The problem I had is that I could not find a clear third variable. I could easily explain away why 7 of the 15 cases were incorrectly predicted, although they were for a variety of reasons; but I could not easily explain why the other 8 cases were incorrectly predicted. In three of the cases the model predicted a red win (insurgents won) when the blue side won (the counterinsurgents); and in four of the cases the model predicted a blue win when the red side won (page 67). There was clearly a third, fourth or fifth variable in play here, but I could never figure out exactly what it was, and it was probably multiple variables. This was the next step and would have been pursued further if we could have obtained further funding.

Of course, we could have just added three or more additional variables to the model and this would have certainly improved the fit….but what are we really doing? This is the point where I begin to loose confidence in adding more variables, so I choose not to.

Getting back to Dr. Spagat’s lecture, one person analyzed the two papers by Fearon and Laitin (called FL) and Collier and Hoeffler (called CH) as to their predictive value. They were not very good at prediction, and sometimes gave false predictions (slide 6). Note that the “false positives” outnumbered the correct predictions for the Collier and Hoeffler model.

On slide 10, Dr. Spagat shows the variables used in each model and how much each variable impacts the results. You will note that one to three variables in each model provide far more explanatory value than the rest of the variables. GDP sort of stands out in both models, although one uses GDP while the other uses GDP growth, which are very different values. There are also some odd variables in there (for example using “squared commodity dependence” in addition to using “commodity dependence” in one model).

Dr. Spagat then goes into the issue of causality, ending up with a discussion on rainfall. Unfortunately, the real world is more complex than the models. A regression model assumes that the inputs are “independent” variables and the output is a “dependent” variable. Yet, in the real world, there can be another variable out there that is influencing both the “independent” and the “dependent” variable. Also, the alleged “dependent” variable can sometimes influence the independent variables. This he discusses in slide 12 (“This is, while it is true that low or negative growth might cause conflict is also true that conflict might cause low or negative growth.”).

Note that Dr. Spagat does address using different measurements of variables in slide 22 (rainfall levels vice growth rates in rainfall). This is an issue. Does one use an independent variable with an clear value (like a GDP figure) or does one use the change in the value of the variable over time as the measure (like percent change in GDP)?

The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%2012.pdf

 

The Yemen Raid

Hard to ignore this one. According to White House reports 14 members of Al-Qaeda in the Arabian Peninsula (AQAP) were killed. We lost one person, three  four injured and a $70 million Osprey. There were 10, 15, or 16 civilians killed. According to one report there were a total of 30 people killed (14 + 16 = 30?).

A few news reports:

https://www.yahoo.com/news/civilians-likely-killed-us-raid-yemen-pentagon-014654537.html

This article provides the figures of 16 civilians killed (8 women and 8 children)

http://www.huffingtonpost.com/entry/us-military-probing-more-possible-civilian-deaths-in-yemen-raid_us_5892bf5de4b0af07cb6b8930?

This article provides the estimate of 30 people killed at the site, including 10 civilians. It also say at least 15 civilians killed, according to U.S. military officials. “The military officials who spoke to Reuters on condition of anonymity said “a brutal firefight” killed Owens and at least 15 Yemeni women and children.” It also notes that “Some of the women were firing at the U.S. force, Pentagon spokesman Captain Jeff Davis told reporters.”

Also:

U.S. military officials….said, the attacking SEAL team found itself dropping onto a reinforced Al Qaeda base defended by landmines, snipers, and a larger than expected contingent of heavily armed Islamist extremists.

One of the three U.S. officials said on-the-ground surveillance of the compound was “minimal, at best.”

“The decision was made—to leave it to the incoming administration, partly in the hope that more and better intelligence could be collected,” that official said.

There were two Osprey’s used in the raid. One suffered engine failure (remember Operation Eagle Claw: Operation_Eagle_Claw).

The UK Guardian is more direct: http://theweek.com/speedreads/677442/trumps-disastrous-first-military-strike-previously-been-rejected-by-Obama

[Colonel John] Thomas said he did not know why the prior administration did not authorize the operation, but said the Obama administration had effectively exercised a “pocket veto” over it.

A former official said the operation had been reviewed several times, but the underlying intelligence was not judged strong enough to justify the risks, and the case was left to the incoming Trump administration to make it own judgment.”

Colonel Thomas is the Central Command spokesman:

https://www.washingtonpost.com/world/national-security/us-acknowledges-civilian-deaths-in-trump-authorized-yemen-raid/2017/02/01/e1f56c3c-e8e0-11e6-80c2-30e57e57e05d_story.html?utm_campaign=pubexchange&utm_medium=referral&utm_source=huffingtonpost.com&utm_term=.76e64d7a6149

Anyhow, I think people will be talking about this one for a while.

 

Country Size

This is a continuation of my previous post: Economics of Warfare 11. It is based upon a review of Michael Spagat’s lecture: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%2011.pdf

The Fearon and Laitin study on the “Determinants of Civil War Onset” (link to paper on slide 5) had eight factors that influenced that chance of a new civil war (they are listed on slides 8 and 10). One of them is “population (positive effect)”. This is summarized by Michael Spagat as “more people, more chances for war.” The Collier and Hoeffler paper came to similar conclusions on this (link to paper on slide 15). As Michael Spagat summarizes it “Population size is still positive and significant” (slide 16). And then there is a third paper by Hegre and Sambanis (like to paper on slide 23) that states that “country size (population and territory) is positively associated with civil war onset” (slide 24).

Now when we did our insurgency studies we also saw the same thing as it related to winning or losing an insurgency. It show up in our Iraq Casualty Estimate (see America’s Modern Wars, Chapter 1) and in subsequent analysis. Quite simply, insurgencies in large countries were often successful. For example, when we looked at all 10 insurgencies with foreign intervention where the indigenous population was greater than 9 million, the insurgents won 80% of the time (see page 47). In our original Iraq estimate for the cases we had, we found the insurgencies won 71% of the time in large countries (290,079-2,381,740 square kilometers…14 cases); 100% of the time in populous countries (population of 9,529,000 or higher…7 cases); and 78% of time in countries with a large border (which is probably related to country size). This is on pages 17-18.

Apparently size matters when it comes to violence. I am not sure of the cause-and-effect here. Obviously, there are many other factors at play. The Symbonese Liberation Army (SLA)…the people who kidnapped Patty Hearst…were a small urban insurgency operating in a large populous country (the United States). It fizzled quickly. So, it certainly does not mean any insurgency in any large place is an issue. But, there does seem to be some correlation here that continues to haunt analysis of insurgencies and the onset of civil war (which are two different subjects, but somewhat related).

Economics of Warfare 11

Examining the eleventh 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 discusses analysis of cross-country datasets, correlations, and then discussed some problems with statistical testing in general. This is worth reading carefully in its entirety.

The datasets they are discussing in the first slides I assume are from the “correlates of war” (COW) dataset, a publically available data set that many in academia have used. We have never used it. When we created the MISS (Modern Insurgency Spread Sheets…now called DISS), we built them entirely from our own research.

He then looks at two different studies on the probability of conflict, one done by Fearon and Laitin (slide 5) and the other done by Collier and Hoeffler (slide 15). Even though they are based upon the same data, they produced somewhat different results (all, of course, to 90% or 95% confidence intervals). He summarizes the conclusions of the Fearon and Laitin study on slides 8 and 10 and the conclusions to the Collier and Hoeffler study on slides 16 and 18. It is worth comparing the differences.

Throughout this paper, he starts giving warnings about the problems with this analysis. First he discusses “story lines” on slides 12 – 14. This is important. One you have a correlation….then most people are clever enough to be able to explain why such a correlation exists, be it right or wrong.

But the part of the lecture that hit home with me starts with the statement that “These reported results may just have come out out that way by luck or chance.” (slide 20). The cartoon on slide 22 makes the point. Basically, if you test 20 different things, even if they are completely irrelevant, even to a 95% confidence interval; then with average luck you will get at least one correlation! Test enough things, and you will get a correlation. By the same token, add enough variables to your regression model and you will get a fit.

This is done all the time and I did discuss it in America’s Modern Wars, page 73-75 on a study done by CAA (Center for Army Analysis) in 2009 using our MISS. As I note in the book they identified 34 variables and then built a regression model based upon 11 of them and then boiled the final model down to four: 1) Number of Red Factions, 2) Counterinsurgent per Insurgent Ratio (Peak), 3) Counterinsurgent Developed Nation and 4) Political Concept. As their model was based on force ratio and political concept, it was similar to my regression model, except they added two more variables to the model. The problem is that one of those variables, “Number of Red Factions,” should not have been added. As I note in my book “In our original research we did not systematically and rigorously establish a count of factions for insurgency…. It should not have been used as a variable without further research.”

To continue from my book: “My fear it that this variable (“number of factions”) worked in their regression model because it was helping to shape the curve even though there is not a clear cause-and-effect relationship here. Also, because of the methodology they choose, which was establishing variables based upon statistical significance, as opposed to there being a solid theoretical basis for it, then I believe that statistically there should be around two ‘false’ correlations among those 11 variables.”

I end up concluding: “My natural tendency as a modeler was to make sure I had clearly identified cause-and-effect relationships before I moved forward. That is why my approach starts simply (two variables) and moves forward from there. It is also why I independently examined each possible variable in some depth. In addition, I reviewed and examined a range of theorists before proceeding (see Chapter Seventeen). I have had the experience of dumping lots of variables into a regression model, and lo-and-behold, something fits. It is important to make sure you have clearly established cause-and-effect.”

Anyhow, what Dr. Spagat warns of on slide 22 is what some people are actually doing. It is not a mistake made by grad students, but a mistake that a professional DOD analytical organization has done.

Enough preaching; the link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%2011.pdf

 

Economics of Warfare 10

Examining the tenth 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 starts with a discussion of coups and assassinations, specifically focusing on a study of “CIA-supported coups.” There are five of them: Iran (1953), Chile (1973), Guatemala (1954), Congo (DRC) (1960) and Cuba (1961). All of these are over 40 years ago.  The chart on page 4, listing some of our nefarious operations is worth a glance. I find it curious that “Project Camelot” is listed, which was simply a research project done being done by the Special Operations Research Office (SORO) that got bad press. A timeline for the five coups are provided on slide 6. Of course, being economists, they tie all these events to stock prices. Still, it is worth looking at slide 8, discussing some points related to the Guatemala coup, as is the following slide, listing expropriated companies. They then look at the effects of secret coup authorizations on stock returns (hey, I thought they were secret !!!). The kicker is slide 16 “The results suggest that US foreign policy was operating as a tool of a handful of private companies and the individuals involved were profiteering off their influence on the US government.” Having never really analyzed this issue myself, I am hesitant to comment on it.

On slide 17 they switch to a study on assassinations. On slide 19 it is stated they came up with 298 assassination attempts since 1875 (to 2002) of which 59 were successful and 47 were not “serious attempts.” So, 23.5% of serious attempts succeed? How many times did they try to assassinate French president Charles De Gualle? Oh, and 55% of them were done by gun, 31% by explosive device (slide 20). Guns succeeded 31% of time, while explosive devices only succeeded 7% of the time. The “other category,” which apparently includes “stoning” succeeded 44% of the time! Slide 23 provides assassination attempts (and successes) over time, with World War II (1939-1945) being a particularly peaceful period of time (as far as assassinations go). The presentation then goes into a long discussion on the impact of assassinations on war, with their conclusions presented on slide 33. Basically it is 1) “There is some evidence that having a successful assassination attempt rather than a failed one increase the probability that an intense war will end.” and 2) “There is evidence that having a successful assassination attempt rather than a failed one increases the probability that a moderate war will turn into an intense war.” So….might work for you, might work against you?

In my book America’s Modern Wars, we do briefly discuss decapitating insurgencies (page 151-153). We also did not come up with a clear answer. We only had about dozen cases to look at, and of the four we examined in depth, in all cases the insurgency still won. Our conclusions were (page 153): “Now this is not to say we should not go after insurgent leadership when we have the chance. We obviously should. But, it is to stress that you should be careful about giving ‘decapitation’ too much importance as a strategic answer to your counterinsurgent problem.” and “Still, if you have the means to try decapitation, it is important to do so in such a way that you do not kill civilians or give them propaganda tools that they can use. In the end, if you are losing the propaganda war while you are trying to decapitate, then you are working against yourself.”  

The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%2010.pdf

Military Effectiveness and Cheese-Eating Surrender Monkeys

The International Security Studies Forum (ISSF) has posted a roundtable review on H-Diplo of Jasen J. Castillo’s Endurance and War: The National Sources of Military Cohesion (Stanford, CA: Stanford University Press, 2014). As the introduction by Alexander B. Downes of The George Washington University lays out, there is a considerable political science literature that addresses the question of military effectiveness, or why some militaries are more effective combatants than others. Castillo focused on why some armies fight hard, even when faced with heavy casualties and the prospect of defeat, and why some become ineffective or simply collapse. The example most often cited in this context – as Downes and Castillo do – is the French Army. Why were the French routed so quickly in 1940 when they had fought so much harder and incurred far higher casualties in 1914? (Is this characterization of the French entirely fair? I’ll take a look at that question below.)

According to Downes, for his analysis, Castillo defined military cohesion as staying power and battlefield performance. He identified two factors that were primary in determining military cohesion: the persuasiveness of a regime’s ideology and coercive powers and the military’s ability to train its troops free from political interference. From this, Castillo drew two conclusions, one counterintuitive, the other in line with prevailing professional military thought.

  • “First, regimes that exert high levels of control over society—through a combination of an ideology that demands ‘unconditional loyalty’ (such as nationalism, communism, or fascism) and the power to compel recalcitrant individuals to conform—will field militaries with greater staying power than states with low levels of societal control.”
  • “Second, states that provide their military establishments with the autonomy necessary to engage in rigorous and realistic training will generate armies that fight in a determined yet flexible fashion.”

Based on his analysis, Castillo defines four military archetypes:

  • “Messianic militaries are the most fearsome of the lot. Produced by countries with high levels of regime control that give their militaries the autonomy to train, such as Nazi Germany, messianic militaries possess great staying power and superior battlefield performance.”
  • “Authoritarian militaries are also generated by nations with strong regime control over society, but are a notch below their messianic cousins because the regime systematically interferes in the military’s affairs. These militaries have strong staying power but are less nimble on the battlefield. The Red Army under Joseph Stalin is a good example.”
  • “Countries with low regime control but high military autonomy produce professional militaries. These militaries—such as the U.S. military in Vietnam—perform well in battle but gradually lose the will to fight as victory recedes into the distance.”
  • “Apathetic militaries, finally, are characteristic of states with both low regime control and low military autonomy, like France in 1940. These militaries fall apart quickly when faced with adversity.”

The discussion panel – Brendan Rittenhouse Green, (University of Cincinnati); Phil Haun (Yale University); Austin Long (Columbia University); and Caitlin Talmadge (The George Washington University) – reviewed Castillo’s work favorably. Their discussion and Castillo’s response are well worth the time to read.

Now, to the matter of France’s alleged “apathetic military.” The performance of the French Army in 1940 has earned the country the infamous reputation of being “cheese eating surrender monkeys.” Is this really fair? Well, if measured in terms of France’s perseverance in post-World War II counterinsurgency conflicts, the answer is most definitely no.

As detailed in Chris Lawrence’s book America’s Modern Wars, TDI looked at the relationship between national cost of foreign interventions and the outcome of insurgencies. One method used to measure national burden was the willingness of intervening states to sustain casualties. TDI found a strong correlation between high levels of casualties to intervening states and the failure of counterinsurgency efforts.

Among the cases in TDI’s database of post-World War II insurgencies, interventions, and peace-keeping operations, the French were the most willing, by far, to sustain the burden of casualties waging counterinsurgencies. In all but one of 17 years of continuous post-World War II conflict in Indochina and Algeria, democratic France’s apathetic military lost from 1 to 8 soldiers killed per 100,000 of its population.

In comparison, the U.S. suffered a similar casualty burden in Vietnam for only five years, incurring losses of 1.99 to 7.07 killed per 100,000 population between 1966 and 1970, which led to “Vietnamization” and withdrawal by 1973. The United Kingdom was even more sensitive to casualties. It waged multiple post-World War II insurgencies. Two that it won, in Malaya and Northern Ireland, produced casualty burdens of 0.09 British killed per 100,000 during its 13 years; Northern Ireland (1968–1998) never got above 0.19 British soldiers killed per 100,000 during its 31 years and for 20 of those years was below 0.025 per 100,000. The British also lost several counterinsurgencies with far lower casualty burdens than those of the French. Of those, the bloodiest was Palestine, where British losses peaked at 0.28 killed per 100,000 in 1948, which is also the year they withdrew.

Of the allegedly fearsome “authoritarian militaries,” only Portugal rivaled the staying power of the French. Portugal’s dictatorial Estado Novo government waged three losing counterinsurgencies in Africa over 14 years, suffering from 1 to 3.5 soldiers killed per 100,000 for 14 years, and between 2.5 and 3.5 killed per 100,000 in nine of those years. The failure of these wars also contributed to the overthrow of Portugal’s dictatorship.

The Soviet Union’s authoritarian military had a casualty burden between 0.22 and 0.75 soldiers killed per 100,000 in Afghanistan from 1980 through 1988. It withdrew after losing 14,571 dead (the U.S. suffered 58,000 killed in Vietnam) and the conflict is often cited as a factor in the collapse of the Soviet government in 1989.

Castillo’s analysis and analytical framework, which I have not yet read, appears intriguing and has received critical praise. Like much analysis of military history, however, it seems to explain the exceptions — the brilliant victories and unexpected defeats — rather than the far more prevalent cases of indecisive or muddled outcomes.

Economics of Warfare 7

Examining the seventh 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, which starts by discussing the “Dirty War Index”, remains focused on civilian casualties. He presents on slide 4 the “Dirty War Index” (DWI), which is actually something we could have used for our insurgency work.

The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%207.pdf

We did something very similar in pages 88-92 in the section on “Use of Firepower” in America’s Modern Wars. On page 89 we have a chart with three columns tracking civilians casualties. They are 1) (civilians killed)/(CI/INS killed); 2) civilians killed/insurgents killed; and 3) total civilians killed/100,000 population. We only have data for nine cases (nine insurgencies). The first two formulations are ratios but the same data could be used to calculate an ersatz DWI. We then discussed the problem with Irish Loyalists Militias on pages 89-90 (using the exact same data as Dr. Spagat used on slide 6) and then we looked at 35 insurgencies compared to 1) rules of engagements, 2) civilians killed/insurgents kills, and 3) total civilians killed/100,00 population (pages 90-91). Our conclusions were (page 92):

In general, there does seem to be a pattern where insurgencies win more often if the number of civilians killed compared to the number of insurgents killed is greater than 10, but there is no statistical support for such an assumption.

This was a case where we needed to do a lot more work, but never got back to it (read: defense budget cuts and sequestration).

Slides 5 and 6 of Dr. Spagat’s lecture are worth looking at. You will note that in Colombia that while the guerrillas and government forces were responsible for their share of civilian casualties, it was the paramilitaries who were doing a lot of the bloodletting. Government ties to some of these paramilitaries have been an issue. As Dr. Spagat puts it (slide 7) “Their relationship with government forces is murky and controversial.” Slide 6 is from Northern Ireland. Again the “Loyalist Paramilities” are the worst offenders. Probably good policy to keep the Shiite militias out of Mosul.

On slide 10, Dr. Spagat switches from the rather depressing discussion of civilian casualties (which is a subject that needs to be discussed and analyzed more than it has) to a discussing of the “Benefits of Peace.” Because of the nature of our customers, we haven’t done a lot of work on peace…not that we don’t want to. He ends up looking at housing prices in Northern Ireland. Slide 13 has the total killings in Northern Ireland by quarter, although only from 1983 and on. The war was far more bloody in the early 1970s and the violence declined notably after that. The figures on slide 14 catches my attention because at one point in our insurgency studies we also looked at distribution of casualties by region in Northern Ireland, compared to Vietnam and compared to two other wars. We noted at the time that unequal distribution of casualties by geography was at a similar ratio between Northern Ireland and Vietnam. We did not go any further with this effort, because we needed a whole lot more cases and we could not see a pattern with what we had examined (and it took a lot of time). This effort was discussed in our report on terrain (Report I-12: http://www.dupuyinstitute.org/tdipub3.htm) but I am pretty sure I left it out of my book.

Anyhow, Figure 15 shows housing prices in Northern Ireland. Not particularly surprising, peace is good for housing prices. You probably could have guessed that without a statistical analysis. The rest of the slides just go into more depth on the statistics behind this (slides 17-19). Then there is a discussion on “sampling rare events” (slides 20-29). Note the mention of bootstrapping on slide 29: Bootstrapping_(statistics)

Economics of Warfare 6

Examining the sixth 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/

In this lecture, Dr. Spagat works from three existing database from the Uppsala Conflict Data Program (run by a group in Sweden). We were aware of these when we were doing our work on insurgencies, but never tapped them. We probably would have at some point, if the work had continued.

Anyhow, Dr. Spagat continues with his analysis of civilian casualties in conflict. We certainly could have done something useful with his Civilian Targeting Index (CTI — defined on slide 3) and looking at whether it effected the outcome of an insurgency. Slide 4 is worth noting, as is slide 8.

The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%206.pdf

On slide 6 is his four “key take-home” points. They are:

  1. “First, the majority (61%) of all formally organized actors in armed conflict during 2002-2007 refrained from killing civilians in deliberate, direct targeting…”
  2. “Second, actors were more likely to have carried out some degree of civilian targeting (CTI > 0), as opposed to none (CTI = 0), if they participated in armed conflict for three or more years rather than for one year….”
  3. “Third, among actors that targeted civilians (there were 88 of them), those that engaged in great scales of armed conflict concentrated less of their lethal behavior into civilian targeting and more into involvement with battle fatalities…”
  4. “Fourth, an actor’s likelihood and degree of targeting civilians was unaffected by whether it was a state or a non-state group.”

Now, granted this is a snap-shot of only five years, but it is one with more than 88 cases in it, but it is still interesting to note. None of the work we did support nor contradicts any of these results.

Slides 9 to 13 is a discussion of logistic regression and linear regression, which is something that I think everyone should understand, but won’t be surprised if our readers choose to skip it. There are some interesting (as always) Slides are pages 14, 16, 17 and 21. In fact, slide 21 is a pretty good to use in an argument with someone who thinks things are only getting worse. It is worth your while to look at it.

Starting on slide 22 to the end (slide 34), Dr. Spagat takes on counter-arguments developed as a result of examining World Health Surveys (WHS), which is a point worth noting. Lots of people like to throw around figures. These figures are not always very accurate.

Anyhow, these lectures are great to flip through, and if you actually carefully (and painfully) read through them, it is probably a better use of your time than most things you will do this week.

Economics of Warfare 5

Examining the fifth 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 is about regressions and logistics regressions. Now, I think everyone should take a econometrics course….but just a warning, this is all pretty dry stuff. So, if you choose to skip it, don’t blame you.

The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%205.pdf

On the other hand, what he is discussing is using regression models to analyze the nature of the civilian casualties, including in the Rwandan genocide. This gets a little hard to discuss. On slide 11, you can learn that in the Kibuye Prefecture in 1994 there were 31,117 people killed by machete, 9,779 killed by clubs and 442 burned alive. Not exactly relaxing reading.

Slide 20 tracks Israeli and Palestinian deaths from 2000-2005, which is a lot less.

Anyhow, Dr. Spagat’s work often focuses on civilian casualties. These are often a significant part of warfare, even if we don’t particularly like to address it. For example,. the United States lost over 4,000 troops in Iraq 2003-2011. Iraq lost over 150,000 people during that time. The same pattern for Vietnam, where the United States lost over 58,000 people in what was the third bloodiest war in our history. Vietnam lost one to two million people !

I did attempt to address civilian casualties in our insurgency work. It is also addressed in my book America’s Modern Wars in Chapter 9 “Rules of Engagement and Measurements of Brutality” and Chapter 15 “The Burden of War.” I am not sure that this attention to civilian casualties was fully appreciated by our DOD customers, but it was there because sadly, it is always a significant part of warfare. Tragically, sometimes so is genocide, as recently demonstrated by ISIL. Dr. Spagat, in a course on the “Economics of Warfare,” is quite correct to focus on civilian casualties.

P.S. I have been informed by Dr. Spagat that he still has another ten lectures to post up on his blog.

 

Economics of Warfare 4

Examining the fourth 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 one is on “opportunity costs,” linear regression, comparing unemployment rates to violence, and the effectiveness of some civil action problems in Iraq to violence. This discussion does get into the weeds, so to say. It is not casual reading.  The link to the lecture is here: http://personal.rhul.ac.uk/uhte/014/Economics%20of%20Warfare/Lecture%204.pdf

To summarize:

  1. On slide 9 there are links to two papers by Dr. Eli Berman and others: 1) Do Working Men Rebel? Insurgency and Unemployment in Afghanistan, Iraq and the Philippines? (2011) and 2) Modest, Secure and Informed: Successful Development in Conflict Zones (2013).
  2. Conclusion on Berman’s first paper: It is a little more complicated than a simple trade-off between violence in an insurgency and unemployment (slides 11-13). In fact the relationship is “negative.” As Dr. Spagat notes (slide 26): “In summary, I would say that the relationship between unemployment and violence in Iraq is not tiny, but it is not big either.”
  3. Conclusions on Berman’s second paper: This one look at levels of funding versus insurgent attacks. There are of course problems with trying to determine cause and effect here (see slides 29-30). As Dr. Spagat notes (slide 41): “Again, we wind up with a statistically significant effect that does not have enormous practical significance.”

Now, I did discuss civil works briefly in Chapter 14 of America’s Modern Wars. It is a grab bag chapter called “Other Issues” that looked at 1) Duration of Insurgencies by Type of Insurgency, 2) Outcome of Insurgency by Type of Insurgency, 3) Winning Hearts and Minds, 4) Decapitating Insurgencies, 5) Early Suppression of Insurgencies, 6) Wounded to Killed Ratios, 7) Exchange Rates, 8) Bleeding an Insurgency to Death, and 9) Focus on Population.

In the section on “Winning Hearts and Minds” we ended up noting (on page 151) that:

As much as people talk about winning hearts and minds (a Vietnam-era phrase, which of course, was not entirely successful), there is no program, theory, agenda or list that tells the counterinsurgent what he must do to achieve this….

In the long run, there needs to be a focused analytical effort that looks at what efforts in other insurgencies have actually worked in the long run to gain support from the population, and what efforts in other insurgencies have not made that much of an impact. Considering the large amount of money being spent on these efforts, it is surprising that nothing systematic has been developed on this.

I do start the Chapter (page 147) with a great quote written by Bernard Fall in 1967:

Civic action is not the construction of privies or the distribution of anti-malaria sprays. One can’t fight an ideology; one can’t fight a militant doctrine with better privies. Yet this is done constantly. One side says, “Land Reform,” and the other side say, “Better culverts.” One side says “We are going to kill all of those nasty village chiefs and landlords.” The other side says, “Yes, but look, we want to give you prize pigs to improve your strain.” These arguments just do not match. Simple but adequate appeals will have to be found sooner or later.

Anyhow, it does not look like this has all been resolved yet. The line to remember is: “One can’t fight an ideology, one can’t fight a militant doctrine with better privies.”