Developing country growth models should look outwards

Just finished reading another paper on growth theory. The conclusion of the paper was that growth is unpredictable in developing countries and the classical descriptors of growth - capital accumulation, labour accumulation, education accumulation - are very poor at predicting rapid economic expansion.

The conclusion is familiar from other papers. The interpretation on results is often that growth is due to idiosyncratic or unknowable causes. This deduction is related to the idea that the missing features of growth lie primarily within economies, since if the causes were international then idiosyncracy would be improbable. The "within economy" hypothesis uses the same theoretical approach, if not the identical variables, to the classical model which the papers themselves find to be empirically inadequate.

The within economy hypothesis is in itself inadequate to explain one of the salient facts of economic growth's history, that developed countries grew far slower than today's fastest growing developing countries when they were in comparable "within country" states. The observation in one of my earlier posts about the instability of the lagged term coefficients across countries is empirical demonstration of the fact.

Both of these observations could be explained if the presence of today's developed countries is responsible for much of the faster growth rates for developing countries. The explanation is the obvious one, is compatible with core economic theory, and has early empirical support in the significance of variables such as openness and technology transfer in models which bother to include them.

Growth models should no longer look inwards, but outwards.

Removing the lag term as a modelling objective

I've presented some arguments and data recently on why the lagged income term in growth models is an indicator that the basic modelling might not be up to much. I would still use a lagged term in my models for the reasons that 1) it captures, badly, the effect of omitted and probably unobservable variables and 2) everyone else uses it. However, removing the lagged term whilst maintaining or improving the basic fit of the model is a good goal for modelling and variable choice.

Sub-Saharan book production

On the UN data website, there is information on how many books are published in different countries. The data on Sub-Saharan countries is patchy, with only a dozen or so countries present. It can be found at http://data.un.org/Data.aspx?d=UNESCO&f=srID%3a25420

I am not sure whether to believe the data, as some of the figures are so small. Ghana for example in 1998 is recorded as having published just seven books, while Togo apparently published just five. Perhaps their authors choose to publish outside the country for subsequent import back in. Something looks strange when you compare with Malawi's figure of 120 books in 1996. There are also healthy publication industries in DR Congo and Ethiopia, and some of their books crop up in UK bookshops.

Butare, Texas

One of the features on my website (admittedly, it is courtesy of Google Maps) is the ability to see photos for places in Africa. You can go to http://www.investinginafrica.org/, then click on the interactive map option, then select the "more" menu, then tick photos. Photos appear all over the continent.

If you zoom into Rwanda (between DR Congo and Tanzania) there is a photo for Butare, in the south of the country. The photo can be found directly at http://www.panoramio.com/photo/1290656.

I think that Butare could be twinned with so many small towns around the world in so many eras - it has the look of British seaside towns today, of US mid Western towns in the 19th century, of French North African colonies in the 1950s, of southern Spanish towns in the early part of the 20th century. What do you think?

Investing in Africa is back

My website Investing in Africa is back online. It was offline for a few weeks while some hosting administration was performed. No further interruptions are planned.

Monte Carlo simulations as standard

Many of the estimation methods used in econometrics produce a biased result when applied to real datasets. In other words, if you want to know what value b is, the estimate tends to be b + some other constant value.

The theoretical understanding of the methods is imperfect, so we do not always know how much the bias is, and we therefore can't correct for it. Monte Carlo estimation gives a way of finding out without having perfect theoretical knowledge. It works by simulating lots of data from a model where you know the parameter values, then you apply the estimation method to the data and get estimated parameter values, then you subtract the real values from the estimated ones and you get your estimated bias. There is an assumption here (ergodicity, meaning convergence of sampled values to real ones) but it is not too restrictive.

It is unusual for papers to report corrections for their estimates based on Monte Carlo simulation, and much more usual to report estimates from different estimation methods. That's OK, but biases can be persistent across different methods, so it is not as comforting to get similar estimates as authors say.

So: here's to Monte Carlo reporting.

Rwanda embassy attempted arson

There was a reported attempted arson attack at the Rwandan embassy last week (http://news.bbc.co.uk/1/hi/world/africa/7401398.stm). The report describes the context of how four Rwandans are due to be deported from the UK for suspected involvement in the 1994 genocide.

I find the arson particularly worrying because of the implication for events in Rwanda. Activities by expatriates in the UK can indicate imminent unrest in their native lands. Prior to the outbreak of conflict in Cote d'Ivoire, posters in French were stuck up in London calling for action against an Ivoirian political leader. Rwanda is in a more tense situation than Cote d'Ivoire was, with the Rwandan militias responsible for the killings in 1994 still at large just over the border in Western Congo and with a refugee civilian population accompanying them. They have been there for fourteen years without anyone being able to reach an adequate resolution for the region, and the possibility of their re-entry in Rwanda is not insignificant.