Posts from April, 2011
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April 29th, 2011

Marshall B. Burke et al. Warming increases the risk of civil war in Africa

Halvard Buhaug, Climate not to blame for African civil wars


Burke et al. (2009)’s study concentrated on the correlation between the intensity of warfare in Africa and the temperature. Burke et al. (2009) proposed an empirical model to find such correlation. Based on their model, Burke et al. (2009) were able to extrapolate data into 2030 and their finding suggested that in longer term, climate increase will outweigh other offsetting effects such as continued democratization and intensify armed conflicts across Africa, therefore urged a reform of governments and foreign aid policies to deal with rising temperature.

Burke et al. (2009) used a linear empirical model to reflect the relevance between climate change and the number of armed conflicts per country. The model defines armed conflicts as conflicts that directly results > 1000 casualties. A compensate factor ci were used to adjust bias towards some characteristics of certain country. Yearly correlated factor are adjusted with diyeari. The overall model can be represented simply as

〖war〗_it=f(x_it )+c_i+d_i 〖year〗_i+ε_it

The temperature variable xit is a computed average over whole year and a whole country.

Burke et al. (2009) spent large part of their article on reflecting the implications of their finding. Particularly, they used public data about prediction of future climate change to reason about future number of armed conflicts. Their calculation suggested of a 54% rise in average likelihood of conflict across Africa.

In later discussion, Burke et al. (2009) argued that comparing to previous studies, temperature served as a better indicator than precipitation. They went further and argued that since temperature and precipitation are negatively correlated, previous finding of increased conflict during drier years might be partly capturing the effect of hotter year. On speculation of why temperature caused increased conflict, Burke et al. (2009) provided the context of how temperature interacted with agriculture. Temperature affects agricultural yields both through increases in crop evapotraspiration and through accelerated crop development which accounts for 10% - 30% crop yields per ˚C of Africa. Because the poorest households in rural area Africa derive 60% - 100% of their income from agricultural activities, temperature will have strong economic consequence to them. From previous studies we knew that economic welfare is the single most significant factor for conflict incidence, Burke et al. (2009) were able to establish the link between temperature and conflict incidence.

Burke et al. (2009) believed so strongly in this link that in their conclusion, they proposed two solutions which directly addressed the agricultural part. First, aid donors and governments should improve Africa agriculture to deal with extreme heat. Second, implementing an insurance scheme to protect poor societies from climate shocks therefore reduce the risk of civil war in Afirca.


Buhaug (2010) examined the computation model and several arguments about how climate change would intensify the conflicts in Africa. His investigation argued that the climate change is a poor predictor of armed conflict. Instead, widespread ethno-political exclusion, poor national economy, and the collapse of the Cold War system are sufficient to explain Africa civil wars.

Buhaug (2010) started by examining assumptions Burke et al. (2009) made in their computation model. As we noted in the previous section, Burke et al. (2009) only marked war as conflict with > 1000 casualties. Moreover, conflicts are discretized across year. For example, the Sierra Leone civil war is widely accepted as lasting from March 1991 to late 2000, but in Burke et al. (2009)’s model, the war is only accounted for year 1997-1998. Buhaug (2010) argued that it would make little sense to account the causality of a war lasting 8 years to the climate change in the middle of 2 years. In Burke et al. (2009)’s finding, Buhaug (2010) also questioned the ignorant on the data of conflict after 2002 because the civil war incidence and severity have decreased while the global warming effect continues.

In later chapter, Buhaug (2010) presented a more comprehensive and arguably more thoughtful analysis of the relevance between civil war risk in Sub-Saharan Africa and short-term climate variations. The analysis takes into account of conflicts that far lower than 1000 annual casualties (minimum of 25 annual battle deaths) and distinguished the outbreak of war with the incidence of war. A particular attention was paid to address the climate change before the initiation of conflict.

Surprisingly, Buhaug (2010) found that the preliminary inspection supported the climate-driving conflict claim. However, with sensitivity analysis, which is common to examine the robustness of a model, Buhaug (2010) pointed out how fragile such model is. With more dependent variables have been introduced to the model, Buhaug (2010) argued that the collapse of the Cold War system was the major contributor to civil war in Africa with significant margin on statistic certainty (p < 5%). Such effect can also be explained from political viewpoint due to the increasing concern on national security. In the following discussion, Buhaug (2010) attacked the frangibility of such model for which, by slight modification, the coefficients jumped back and forth from positive to negative all with uncertainty below 5%. Even more, the data directly shows that an unusually wet period followed by more conflicts (> 1000 causalities) which is contradict to the notion of scarcity-induced conflicts. In addition, Buhaug (2010) addressed some pitfalls in his own modeling. First, he argued that in all empirical studies on this subject, they applied country-level averaged climate data which may mask out local anomalies. If it turns out such local variance is large enough, a different conclusion may be drawn. Second, his own study is only focusing on short-term climate change but long-term environment change may have more security implications, and that may change the political environment accordingly. Third, the intensity of global warming impact may be undervalued since the famous hockey stick graph suggested a dramatically change in temperature thus may trigger some major tipping point events. If that happens, this presented analysis would be invalid.

In the closing section, Buhaug (2010) suggested that even though global warming is a real challenge, letting the debate based on some unverified and nonrobust scientific findings would be too daunting to make real progress.


In social studies, empirical data is usually hard to obtain, and the correlations between them is hard to serve as an argument for causality analysis. There are usually three reasons for a pair of correlation which have significant certainty to appear. First, one side of the equation is the cause, and the other side is the consequence. Second, both sides are the consequences of a “hidden” cause. Third, an unlikely random event that incurred the significant certainty happened due to many tries and errors. Social scientists paid a lot of attentions to distinguish the cause from consequence. For example, it usually indicates a cause if one side of the equation is hard to change. If both sides are easy to change, tracing and reasoning the link between them becomes crucial. However, much less attentions are paid to distinguish from the third reason.

Burke et al. (2009)’s analysis is arguably unconventional. They took climate change and tried to recover the association with the number of conflicts in Africa. It is obvious that since temperature is hard to change by artificial events, if such correlation does exist, we can safely attribute temperature as the cause of conflicts in Africa.

Though the conclusion is eye-catchy and Burke et al. (2009) went further to extrapolate their data into future in order to gain some insights into political choices, they failed to address some fundamental issues of their model.

The discretization method for counting war is arbitrary. Burke et al. (2009) didn’t provide any justification for the choice of 1000 as threshold. The civil war is counted as a single one instead of treating them as individual battles. Although the outbreak of a civil war took unusual momentum to pull off, the intensity of such war is only relevant to individual battles. For a linear regression model which essentially would only fit by painting intensity of warfare, such ignorant is worrisome.

To further assess their argument, Burke et al. (2009) tried to draw the actual causality chain out and their temperature-agriculture-economic-warfare chain seems convincing. However, it brings up another question: if agriculture is so important, why don’t analyze the relationship between agricultural activities and warfare at first place? The causality chain also pointed out some weaknesses in their model. For example, the variables in the model such as temperature and GDP are actually dependent on each other. Such existence of dependency would diminish their finding because now, for prediction, the cascading effect (one variable change would cause other variables to be adjusted accordingly) would not be properly captured in the existing model when plug in one variable (the linear regression model assumes independency of its variables).

The trouble of interdependence between variables gets reflected on their future projection of civil war risk in Africa. If temperature has a direct impact on economic growth as they suggested, the offsetting effect of economic growth they mentioned later will collide with the former one, it is unclear which side will win since the dependency is not properly analyzed. By having such dependency of variables, they entered the loop of reasoning and cannot get any sound conclusion out.


Buhaug (2010) attacked Burke et al. (2009) in a more constructed way than mine. The most significant contribution in his paper is to rebuild and reexamine Burke et al. (2009)’s model. The sensitivity analysis confirmed my worrying on several seeming arbitrary choices in original model.

To go beyond reexamining original model, Buhaug (2010) also presented a modified version which in principle should reveal more insights into the causality of civil war in Sub-Saharan Africa. The irrelevancy of temperature in his new model is expected based on his analysis of original model even he included more aspects of short-term climate change (first derivative of temperature etc.) in the new model. It seems like a second confirmation of how fragile Burke et al. (2009)’s model is.

It is very interesting to see a model that consists of a lot variables, however, it should be noted that, to make such a complex model robust, a large number of training data is required. This is known as overfitting problem to statisticians. However, to solve the overfitting problem, Buhaug (2010) used linear regression model rather than logistic regression model. The choice is a source of trouble. For me, it is inconsistent since he specifically addressed the problem of using linear regression model in Burke et al. (2009)’s paper (mainly because in previous step, we discretized/binarized warfare as target function).

Buhaug (2010) took a lengthy paragraph to reason why the discretization method of warfare used in Burke et al. (2009) was broken. His argument deserves some merits, but I don’t find that is as important as he argued. Though the outbreak of civil war is significant, the intensity of a certain war is never be a function of how severe the outbreak is. The World War I started as revenge to political murder but the argument for the war quickly shifted away. A civil war should be viewed as a collection of battles, thus, the severity of certain battle can be determined by other factors in that time frame. If Burke et al. (2009)’s analysis is robust enough, such discretization method should be OK for their model.


Since more and more data has been gathered thanks to the advancement of information technology, social scientists and alike started to use statistic model to reason about certain events. However, extreme caution should be taken in the process and certain mathematic competency should be required in order to avoid faulty analysis.

War is a serious business. Doing causality analysis for warfare does not only require macro-scoped statistics, also requires detailed field work. Social science doesn’t share the luxury with physics of doing controlled-variable experiment. Thus, any study consists of empirical analysis should be carefully carried out.

In short, there is no magic dose for the Africa problem.

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April 26th, 2011

Like most people in technology, I don’t like the title of “Business Development Manager”, and I am not proud of my taste. This is a necessary position, and I don’t like it only because of my engineer-oriented prejudice. That led me to think about the root of my prejudice last night.

We humans are collectors. In many archeology site, many instruments have no better explanation other than ornaments. We love rice and pigs, because they can be stored. Thus, these stored surplus drove human society to survive through hard times.

In modern societies, we still value things that can last. Fine art, real estates, antiques and minerals captured large amount of fortune in our economy. As an engineer, we are proud that “we actually build things”. The difference between actress and waitress is that during a certain period of time, actresses can build up stored value through media storage technique whereas waitresses have nothing left.

That’s the same problem of business development personnel. They build up their professional network, but that is something cannot be materialized. You cannot point someone to something and argued that you have a sophisticated connections in such industry.

Well, that may not be true now thanks to Facebook and LinkedIn. biz-devs can now build up their social network in measurable way. If you are a radical thinker, that is not much different from coding or mining bitcoin (they are all in digital form, no physical goods are created in the process). The stored value in digital form already works, it is just matter of the time to apply more gaming attributes to it (badges, level-ups etc.).

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April 24th, 2011


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April 21st, 2011

The best line I heard yesterday is: the sad, beautiful fact is that we are all going to miss almost everything.

When I was a teenager, some older ones urged me to experience life, “do whatever you can to enjoy it”. After all, life is too short, having fun. The sad part is that, no matter what you have done, you will miss most things in life.

If this is the last day of my life, would I be satisfied? When I was dead, would someone claim that “without him, the human kind would take several more decades to get where we are now”. The believers of historical inevitability would call me a liar, but one man’s determination can make the difference. Half a century ago, one nation’s determination stretched the ability of mankind to its extreme, and we sent a man to the moon 40 years long before every piece of the technology is ready (when the first commercial rocket reached the orbit).

If I, myself alone, can put a man to the Mars by 2030, that’s all the difference.

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April 9th, 2011

When I was 5, there was a beautiful transformer in the toy shop. I absolutely loved it, but I couldn’t have it because my father said no. That’s the first time I felt the hunger. At that time, I had no idea what money was.

It is my personal belief that polite, patient founders would fail. There seems to be a few echoes. Hunger, among other things, to me, is the most important characteristic of entrepreneur. Let me summarize it with the timeless quote from our beloved Gordon Gekko: Greed, for lack of a better word, is good. Greed is right. Greed works. Greed clarifies, cuts through, and captures, the essence of the evolutionary spirit. Greed, in all of its forms; greed for life, for money, for love, knowledge, has marked the upward surge of mankind and greed, you mark my words, will not only save Teldar Paper, but that other malfunctioning corporation called the U.S.A.

I used to be one.

I didn’t know what money was until 9. This time, material satisfaction finally got me through a magical media people nowadays praised as “remote-control airplane”. Money can buy that thing. It doesn’t matter what fiat currency is, the important lesson of life is that money can buy security. At that moment, I achieved the enlightenment. (It is almost like the miraculous time when the water pumped through little Helen Keller’s palm or the first time of ejaculation that symbolizes the manhood of any 10-year-old little boy.)

There is no income for a 10-year-old little boy other than robbing other kids in lower grade. I had neither the bad taste nor the muscle. So, I did a little market research. You see, there were two places for potential customers: on the road/play yard or in the school. The market on the road/play yard was pretty much free. Anyone could have business with little kids in these places, the competition is ruthless. In school, it was monopoly. There were certain inefficiencies that could be exploited. The first business I opened was “homework trading”. If you could take a moment and think about it, the market is untouched. Admittedly, there were some exchange of homeworks after school, but no money involved. The execution was extremely bare-boned. My allies would finish most homework before afternoon, and we sell it for 1 or 2 bulks per copy. Those were happy days and I was innocently stupid of not charging commission fee.

It is very naive to many people of building something and then sell it. It is no-brainer, not scalable and not “passive”. Once more, I did it again later. My business went pretty well until one day a teacher broke in and figured everything out. It was not a big deal for other kids but a big drawback for me. I have no other income source. My family didn’t give me money in daily basis, and I hated to ask. The only stable income in my hand other than the “homework business” was yearly gift money from grandma (around 200 bulks).

I made an offer to my father. Here is the deal, I contribute 200 bulks to the purchase of PC, and I owned 1/4 share of that computer, thus, it automatically translated to 1/4 usage time. My initial programming experience was purely drove by profit, and purposeful. It was not a coincidence that the first shareware I developed was a simple photo-editing one (Fantasia Photo). I did the research, and at that time, the digital camera market just took off. There are several tens of thousands installs, but only a few payments. Barely, I recovered my cost.

There were certain risks associated with “making stuff and sell it” which I haven’t envisioned before. Nowadays, I quote porn site a heck lot of time, no joking, they did fantastic job at monetization. No, they have crappy product, but every pixel is purposely placed in order to trick you into paywall. Their marketing is shameless, directly injected into every dark, dirty corner of the Internet. Unfortunately, at 14, my experience with porn site only told me that the Internet was the best thing ever. The only education was: the Internet is awesome, do something with it and get rich quick. Have you ever heard of ISEF? Yes, that was my funding source. The best part of that money is: it is non-binding, so I can explore whatever I want. But the worst part of that money is: it is non-binding, so I have no pressure on growth. That was when I showed my early obsession symptom. Taking a leap when technology is not ready, bad; polishing every pixel before releasing, double bad. Heck, I didn’t make truck-load money, but I have covered my living expense.

It follows that I dropped out from University and started a two year business adventure and failed miserably. That was when I started to reflect. There are certain traits of entrepreneurs that I am enthusiastic about. They are hungry, stressful, nervous, hard-to-deal-with and due all the respect, haters of work-life balance. I was lack of, well, I can be easily distracted, obsessed on new and shiny stuff.

It is so sad that my gut still only want to build amazing stuff despite all these years of failure.