I was just screwing around with some data we collected a bit ago. In a nutshell, I’m working to try to improve the way we measure household wealth in developing countries. For the past 15 years, researchers have relied on a composite index based up easily observable household assets (a la Filmer/Pritchett, 2001).
Enumerators enter a households and quickly note the type of house construction, toilet facilities and the presence of things like radios, TVs, cars, bicycles, etc. Principal Components Analysis (PCA) is then used to create a single continuous measure of household wealth, which is then often broken into quantiles to somewhat appeal to our sense of class and privilege or lack thereof.
It’s a quick and dirty measure that’s almost universally used in large surveys in developing countries. It is the standard for quantifying wealth for Measure DHS, a USAID funded group which does large surveys in developing countries everywhere.
First, I take major issue with the use of PCA to create the composite. PCA assumes that inputs are continuous and normally distributed but the elements of the asset index are often dichotomous (yes/no) or categorical. Further, PCA is extremely sensitive to variations in the level of normality of the elements used, so that results will vary wildly depending on whether you induce normality in your variables or not.
It’s silly to use PCA on this kind of data, but people do it anyway and feel good about it. I’m sure that some of the reason for this is the inclusion of PCA in SPSS (why would anyone ever use SPSS (or PASW or whatever it is now)? a question for another day…)
So… we collected some data. I created a 220 question survey which asked questions typical of the DHS surveys, in addition to non-sensitive questions on household expenditures, income sources, non-observable assets like land and access to banking services and financial activity.
The DHS focuses exclusive on material assets mainly out of convenience, but also of the assumption that assets held today represent purchases in the past, which can act as pretty rough indicators of household income. So I started there and collected what they collect in addition to all my other stuff.
This time, however, I abandoned PCA and opted for Multiple Correspondence Analysis, a technique similar to PCA but intended for categorical data. The end result is similar. You get a set of weights for each item, which (in this case) are then tallied up to create a single continuous measure of wealth (or something like it) for each household in the data set.
Like PCA, the results are somewhat weak. The method only captured about 12% of the variation in the data set, which sort of begs the question as to what is happening with the other 88%. However, we got a cool graph which you can see up on the left. If you look closely, you can see that the variables used tend to follow an intuitive gradient of wealth, running from people who don’t have anything at all and shit in the shrubs to people who have cars and flush toilets.
We surveyed three areas, representing differing levels of development. Looking at how wealth varies by area. we can see that there is one very poor area, which very little variation to the others which have somewhat more spread, and a mean level of wealth that is considerably higher. All of this agreed with intuition.
“Area A” is known to be very rural, isolated and quite poor. Areas B and C are somewhat better though they are somewhat different contextually.
My biggest question, though, was whether a purely asset based index can truly represent a household’s financial status. I wondered if whether large expenditures on things like school fees and health care might actually depress the amount of money available to buy material items.
Thus, we also collected data on common expenditures such schools fees and health care, but also on weekly purchases of cell phone airtime. Interetinngly we found that over all the two were positively correlated with one another, suggesting that higher expenses do not depress the ability for households to make purchases, but found that this relationship does not hold among very poor households.
There is nothing to suggest that high expenses are having a negative effect on material assets among extremely poor households located in Area A at all. It might be the case that there is no relationship at all. This could indicate something else. Though overall there might not be a depressive effect of health care and school costs on material purchases, they might be preventing households from improving their situation. It might only be after a certain point that the two diverge from one another and households are then able to handle paying for both effectively.
Also of interest were the similar patterns found in the three areas.
I was just reading this on the Guardian’s Poverty Matters blog:
First, identify the most important issues. One of the main problems of the MDGs, as noted in countless analyses, was their failure to bring the major structural issues to the table. I know of no one who thinks that aid is the most important contribution that wealthier countries can make to development, but the vague terms of MDG eight allowed politicians to get away with aid promises (which in some cases they didn’t keep) rather than setting a bold agenda for transformational change in global financial governance, dealing with illicit financial flows, for example, taking bold steps towards international tax reform, and introducing fairer mechanisms for working out debt repayments.
Well, yeah, very true, but again this type of reporting skirts the issue of where those illicit flows are coming from and who took out the loans. The problem with the MDGs was that it failed to put any pressure on leaders of developing countries to stop being parasites. Worse yet, they didn’t allow for the provision and protection of basic individual rights to free expression, judicial rights and economic freedom, instead opting for a few vague and unverifiable targets which failed to address structural problems WITHIN developing countries.
In Kenya, at least, the government is bleeding the populace dry. Evidence from countries such as Botswana and Korea has shown that countries who want to develop can. The biggest obstacle (among all the other obstacles) to development is a lack of political will to do it.
To its credit, the article goes on to point out that domestic ag subsidies in wealthy countries are distorting the world market and preventing developing countries from being competitive on the world market. Eliminating these subsidies will be a real challenge, at least in the US. First, subsidies control price and market volatilities. The US electorate would go bonkers if the price of food went up and down like the price of corn does in developing countries. Second, Americans simply like subsidies and enjoy protecting agricultural interests at all levels. The right likes to pander to farmers for the rural vote while the left is somewhat bummed out because their favorite organic farms don’t have access to them. Though the left loves to pay lip service to ending ag subsidies, I can’t imagine they’d be all that sad if they were offered to their local hippie farmers. That’s speculation for another day, however, and I’m no expert on ag matters.
I hate to be pessimistic about development, but the barriers to progress are hobbled by forces both within and without developing countries and no one seems to be tackling the right issues to improve matters.
I was just reading a comment in the new Journal of the American Society of Tropical Medicine and Hygiene “After Malaria is controlled, what next?”
Fortunately for all of our jobs, there is little to worry about. Malaria, as a complex environmental/political/economic public health problem, won’t be controlled anytime soon. As there’s no indication that many sub-Saharan countries will effectively ameliorate their political problems and also no sign that, despite the “Rising Africa” narrative, African countries will develop in such a way that economic rewards will trickle down to the poorest of the poor, malaria transmission will continue unabated. This is a horribly unfortunate outcome for the people, particularly small children, who have to live with malaria in their daily lives.
In all of the places it occurs, malaria is merely a symptom of a greater political and economic failure.
Indeed, we really know less about the causes of suffering and death in the tropics than many believe. Even vital statistics of birth and death are unrecorded in many areas of the world, much less the accurate causes of disease and death. Some diagnoses, such as malaria, dengue fever, and typhoid fever, are often ascribed to patients’ illnesses without laboratory confirmation. Under the shadow of the umbrella of these diagnoses, other diseases are lurking. I have found significant incidences of spotted fever and typhus group rickettsioses and ehrlichiosis among series of diagnostic samples of patients suspected to have malaria, typhoid, and dengue in tropical geographic locations, where these rickettsial and ehrlichial diseases were previously not even considered by physicians to exist.4–8 Control of malaria or dengue would reveal the presence and magnitude of other currently hidden diseases and stimulate studies to identify the etiologic agents.
This is the problem with our public health fascination with malaria. We are missing all of the other pathogens and conditions which case untold suffering in the poorest and most isolated communities. It can’t be the case that malaria acts in a box. In fact, it could be the case, that multiple pathogens coordinate their efforts to extract as many human biological and behavioral resources as possible to obtain maximum opportunities for reproduction and sustenance. A public health system only designed to look for and treat a limited window of diseases misses the opportunity to disrupt what is probably a vast ecological complex.
First, we have a problem of poor diagnostics. Facilities traditionally treat most fevers presumptively as malaria, dispensing drugs appropriate to that condition. However, conditions like dengue fever exhibit similar symptoms. While is it extremely likely that dengue is all over the African continent, particularly in urban areas, there is little ability to identify true dengue cases in the public health sector, and thus, in addition to mistreating patients, the extent of the disease burden is unknown. We cannot tackle large public health issues without proper data.
Second, we have the problem of all of the “known unknowns,” that is, we know for a fact that there’s more out there than we have data for but we also know (or at least I do) that there is a greater disease ecology out there. We know that many pathogens interact with one another for their mutual advantage or to haplessly effect significantly worse outcomes. The awful synergy of HIV and TB is just one example.
OK, I’m going to go and deal with my own pathogenic tenant which I think I’ve identified as an enteric pathogen of the genus Pseudomonas, which might have taken hold opportunistically through an influenza infection. This is complete speculation, however. Data quality issues prevent a reliable diagnosis!
As much as we’d like to believe it, babies aren’t a blank slate. Babies not only bear the social and economic legacies of the families which produce the, but also the scars of a lifetime of immunological insults.
This week, a paper, “Does in utero Exposure to Illness Matter? The 1918 Influenza Epidemic in Taiwan as a Natural Experiment,” appeared in the journal of the National Bureau of Economic Research which tracks the long term effects of the 1918-1920 worldwide influenza pandemic.
Turns out that babies which were born to mothers in that period were, on average, shorter than people born in other years, had more developmental problems, and, possibly, suffered from long term problems of chronic disease.
This paper tests whether in utero conditions affect long-run developmental outcomes using the 1918 influenza pandemic in Taiwan as a natural experiment. Combining several historical and current datasets, we find that cohorts in utero during the pandemic are shorter as children/adolescents and less educated compared to other birth cohorts. We also find that they are more likely to have serious health problems including kidney disease, circulatory and respiratory problems, and diabetes in old age. Despite possible positive selection on health outcomes due to high infant mortality rates during this period (18 percent), our paper finds a strong negative impact of in utero exposure to influenza.
It’s interesting to me, in that it’s a study of health on one of Japan’s former colonies, but also because Taiwan’s indicators in 1918 were atrocious. More than a fifth of babies didn’t live to see their fifth birthday, deaths in childbirth were common and life was short. In other words, it’s a lot like a lot of African contexts today.
The long term outcomes of common developing world diseases have mostly been ignored. There is every reason to believe that one of the reasons African countries suffer economically is that people’s developmental trajectory is set before even exiting the womb. SO we’re fighting against not only a bleak economic past, but also against a constant legacy of infectious insults.
And to moms in the developed world…. get your flu shots.
This question has been bothering me for a while. While it’s obvious that Godzilla would only visit Japan and the US given that the US and Japan are the only countries which make Godzilla movies, I’ve long been puzzled as to why Godzilla would visit those two exclusively. Specifically, why doesn’t Godzilla visit poor countries? (Note: I realize that Godzilla is a good guy, but ask readers to remember that he didn’t start out that way)
Certainly, the environmental devastation in poor countries is as extensive as in wealthy countries (and perhaps moreso, given the lack of financial and political resources to measure it, let alone do anything about it), making Tanzania, for example, just as much a candidate for kaiju destruction as any other.
But what would happen? First, were Godzilla appear on the shores of the coast of Kenya, he’d (is it male?) have to plow through the port of Mombasa. Godzilla may be destructive, but he’s known to follow standard immigration procedures. He’d meet little resistance, given Kenya’s lax border protection. At the worst, he’d be asked to pay $50 to stay for three months.
Mombasa isn’t a big town, so he’d be over the island and into the country in a matter a seconds, though he might consider a pleasant break on the beach. After finally eradicating Kenya’s terror problem and quashing any ideas of Mombasan separatism, he’d stroll to the Mombasa highway and lumber up to Nairobi, where the real action could start.
In contrast to Japan and the US, Godzilla would find the response by the local military to be tepid at best. A few planes might buzz around aimlessly and a couple of tanks might lob some rounds at his legs, but the military, lacking any incentive to loot cell phones or liquor would probably simply slink away in short order. Response from the African Union or the UN would be slow coming, as they’d have to wait to see if the media reacted with sufficient outrage to warrant action. The US would most certainly refuse to be involved in anything other than a support role.
Godzilla would plod through Nairobi and lay waste to the City Centre in a matter of seconds. It would be like a child stepping through a grandmothers flower garden. He’d probably quickly become bored, lacking much to topple over outside of a few unfinished apartment buildings and maybe a mall here and there. If he were after human destruction, he might take a few steps through Kibera, where he’d certainly kill a half a million people in the space of a single Godzilla breath.
After an anti-climactic fight in Nairobi, he’d have to take a break in Karen to consider what to do next. Maybe he’d move on to Kampala? Or regret his decision and move back to India? It’s hard to say.
The human costs would be incredible. A couple of million people would likely die immediately, the majority of which would be poor given the incredible density in slums like Kibera and their inability to properly evacuate from the city. The sleep inducing traffic jams are unavoidable even under normal circumstances. A manic run for the countryside by all of Nairobi would only make things worse but squatter settlements and slums would reappear within days.
In the long term, however, Godzilla’s destruction of Kenya might pay off. Massive amounts of funding would appear from a number of international sources to rebuild Nairobi’s devastated infrastructure. The Chinese would appear and immediately start rebuilding the highway system from scratch using cheap imported labor. The Americans would set about reconstructing Kenya’s likely devastated military and ports. The British would dump money into overhauling Nairobi’s failing sanitation system, long due for replacement. Kenya would get an infrastructural reboot.
On the other hand, real estate speculators would flow in like flies on roadkill, hoping for a payoff once Kenya’s economy got back on track. Where real estate prices would have crashed immediately following the destruction of Nairobi, leading to a cheap scramble for land, the current real estate boom soon again be underway. Domestic investors would now have even less incentive to develop Kenya’s manufacturing sector and the economy would hobble along as it did before.
Given the political chaos following Godzilla’s destruction of the central government, Chinese investors would grab as much agricultural land as possible, citing “gifts” of highways and football stadiums further entrenching China’s increasingly overbearing presence in the country.
In essence, Kenya, as independent state, would cease to exist.
It might be the case, however, that the destruction of Kenya’s cities might finally sway the Kenyan citizenry away from tribal politics and toward a truly democratic state. People can, and do, often surprise us, but this would be a hard, hard road given that most of the reconstruction would not be democratically determined, but rather orchestrated by World Bank and UN technocrats and Chinese land grabs. It’s clear that Kenya’s self interested leaders would do nothing to stop it.
So, conclusion? Kenya would win big in improved infrastructure, but lose big given the resultant political weakness. In the long term, Kenya might regain some of it’s political footing given improvements in the domestic economy, but it would take decades and a lot of political will to make this happen.
These words are mostly regional and the uses and nuances of calling people stupid also vary by place.
Over dinner, I was reminded of an episode of Tante Night Scoop, an investigative television program which ran throughout the 90’s. They did an exhaustive survey and mapped the locations of the common ways of calling people stupid throughout Japan.
Of interest is the centrality of the word “aho,” commonly used throughout the Kansai region of Japan (and denoted in red) and the radial spread of “baka” (denoted in blue), a word mostly associated with Tokyo and commonly found in Kanto-centric anime programs.
The map was intended as entertainment, but it has serious historical significance.
When people move, they take words with them. It would appear that people in Kansai, historically the political and economic center of Japan, had little reason to leave the region, which would explain “aho”‘s limited spread. Baka, however, can be found on both sides of Kanto, indicating that there were strong connections between the two sides, despite the distance between them.
Oddly, the other words for “stupid” occupy the same radii from Kansai indicating that certain groups of people had peculiar spatial advantages in trade, where as others did not. Though I really have no idea, I’m thinking that particular perishable products traded with Kansai might have different spoiling times necessitating particular proximities. It’s important also to note that the extreme peripheries might have been trading non-perishable resources like coal, which, though heavy, doesn’t rot.
Economics, trade and language have deep links. English wouldn’t exist without it, and the many forms of English spoken throughout the world have been influenced by the multitude of groups of people who chose to speak it to facilitate trade.
OK, enough for now and back to Kenya.
I just got back from Bookstop in the Yaya Centre shopping mall in Nairobi, one of my favorite bookstores in the world. It’s an Africanist’s paradise. My bank account is always a bit lighter and my suitcase a bit heavier after I visit.
Today, a customer was coming in to pick up Thomas Piketty’s Capital in the Twenty-First Century, a 700 page economics tome which has been topping the best seller lists everywhere and probably one the best economics books to appear in the past 50 years. The gentleman looked a bit intimidated by its size.
A bit later, a younger Kenyan woman came in with a bag full of books that she was hoping to trade for her copy. The book costs the equivalent of about $70 in Kenya.
The owner apparently ordered 100 copies, but was only able to get 25. He says he has orders for all 100 copies, many from Kenyan college students which he sees as an encouraging sign. I have to agree.