Are Power Pools the Answer to Chronic Power Shortages?

Auriol and Biancini have a nice theoretical take on the subject of regional power pools in the World Bank Economic Review:

Power market integration is analyzed in a two-country model with nationally regulated firms and costly public funds. If the generation costs between the two countries are too similar, negative business stealing outweighs efficiency gains so that, subsequent to integration, welfare decreases in both regions. Integration is welfare enhancing when the cost difference between two regions is large enough. The benefits from export profits increase the total welfare in the exporting country, whereas the importing country benefits from a lower price. In this case, market integration also improves incentives to invest compared to autarky. The investment levels remain inefficient, however, especially for transportation facilities. Free riding reduces incentives to invest in these public-good components of the network, whereas business stealing tends to decrease the capacity to finance new investment.


Existing and Planned Power Pools in Africa

There is a lot of excitement in the power sector in Africa these days. Eastern Africa will probably be the most power-rich in the next few years: Ethiopia’s 1870MW Gibe III will likely come online later this year (oh, and there is the ongoing Grand Renaissance Dam project that will produce 6000MW [or 2800MW?]); Kenya has had a massive push for geothermal, solar and wind generation; and Kenya, Uganda, and Tanzania have commercially viable deposits of oil and gas that will also come online within the next six years. The region is also very well integrated, although there is need to upgrade power transmission infrastructure. The Bank has an ongoing project in this regard [that is way behind schedule].

For more on this subject see my commentary on energy sector integration in Africa over at the African Development Bank blog.

On the upcoming Nigerian elections

On February 14 Nigerians will go to the polls in what is arguably the most important election in the world this year. Here is a (small) collection of things you need to read before then:

1. Alex Thurston has a great backgrounder for CSIS on the upcoming Nigerian elections. Want to know about the coalitions angling for power in Abuja and state capitals all over Nigeria and how ongoing political maneuvers will impact the outcome of the presidential election? Then click here.

2. Earlier this month Nigerian journalist Tolu Ogunlesi wrote an excellent piece for FT that emphasized the fact that this will be Nigeria’s closest and most unpredictable election yet (a point echoed by Zainab Usman, a Nigerian DPhil Candidate at Oxford, over at African Arguments). The level of competition will no doubt put pressure on INEC, and the losing candidate, to ensure that the legitimacy of the process is not tarnished, regardless of the outcome.

3. Brookings has a nice summary of some of the key political and policy issues at stake in this year’s election.

4. In the only detailed forecast that I have seen ahead of the election, DaMina Advisors project that APC’s Rt. Gen. Muhammadu Buhari will win with 51% of the vote (and get 25% in at least 27 states). There have not been any reliable polling data coming out of Nigeria in this election cycle, so take DaMina’s projections with a Naija size grain of salt.

5. And lastly, here is an op-ed from the former Governor of the Central Bank of Nigeria, Charles Soludo, on the economic dimension of this year’s election, as well as incumbent Goodluck Jonathan’s many failures.

If you have suggestions on interesting analyses ahead of the election please do share in the comments section.

Working in Development

Sentences to ponder:

Field experience is one of the most important things you can have as an aspiring development professional. It demonstrates your understanding of what development is like on the ground, and shows your genuine commitment to working in the sector. Even a few months in the field scores you more CV points than a much longer period in an office in London or New York.

What’s more, you may be able to land a position with more responsibility than you would back home. For example, our intern Marcus has just returned after two years as a manager of an educational project in Ghana, a job he secured with little previous experience.

For more on what you really need to know before deciding to pursue a career in international development click here.

The ICC’s case against Uhuru Kenyatta

Following the collapse of the case against President Uhuru Kenyatta of Kenya, ICC prosecutor Fatou Bensouda made public her case against Mr. Kenyatta for his alleged role in the 2007-08 post-election violence in Kenya. More than 1300 people died and 300,000 were displaced.

You can find the public [redacted] version of the prosecution pre-trial brief here.

UPDATE: And here is the defence’s response.

On the Zambian Presidential By-Election

Zambians go to the polls today to elect a president to serve the remainder of the late Michael Sata’s term. President Sata died on the 28th of October, 2014. The winner of the by-election will be office until late 2016 when when elections are due for both the presidency and the National Assembly.

Today’s contest is between the two front-runners: Edgar Lungu, the candidate of the ruling Patriotic Front (PF); and Hakainde Hichilema (HH), the candidate of the United Party for National Development (UPND). Lungu has the advantage of incumbency, and a favorable electoral map (interim president Guy Scott is constitutionally barred from running). As the table below shows, support for Sata in the last election (2011) was concentrated in provinces that were both vote-rich (column 7) and recorded high turnout (column 5). HH’s support has historically been strongest in his native Southern Province and the vote-poor Western and Northwestern Provinces. He is also competitive in Central Province.

Presidential Election Results (2011)
Province Sata (PF) Banda (MMD) Hichilema (UPND) Turnout Turnout (2008) Vote Share (Ascending)
Northwestern 10.85 50.21 35.24 54.88 42.7 6.249513033
Western 23.12 33.2 28.21 47.77 38.4 6.800182089
Luapula 73.54 22.9 0.85 50.49 37.8 7.447270534
Central 28.28 48.21 20.82 46.87 40.6 8.149764957
Eastern 18.46 72.6 3.33 49.89 40.5 11.60268286
Southern 6.59 19.15 71.41 58.04 49.8 13.47451036
Northern 64.18 32.16 0.78 57.28 44.6 13.62680466
Lusaka 55.94 30.76 11.29 52.05 50.7 14.50255098
Copperbelt 67.88 26.22 3.57 59.5 52.8 18.14672051

HH’s chances will depend on whether the fallout within PF (Lungu’s nomination did not occur without incident) and the implosion of MMD produce a swing in his favor. Disaffected MMD supporters will therefore be a critical swing bloc. Furthermore, ahead of the elections Hichilema managed to get the endorsement of Geoffrey B. Mwamba (GBM), a former minister in the Sata government. But it is unclear whether GBM will be able to sway voters in his native north of the country, which voted solidly for Sata in 2011 (see map below). Sata, like GBM, was from Northern Province (since divided into Northern and Muchinga Provinces).

Sata constituency level vote share (% of votes cast)

Sata constituency level vote share (% of votes cast)

A low turnout today will favor PF. In the last presidential by-election (in 2008) turnout was 45.43%, 8 percentage points lower than the 53.65% recorded in the 2011 General Election. PF, with its wide support in the more urbanized Copperbelt and Lusaka (see map and table, column 6), therefore enters the race with a distinct advantage. If Hichilema is to have a chance he must not lose the turnout contest, and at the same time win by wide margins in the northwest, west and south of the country.

Of course the biggest unknown is whether Lungu can attract the same level of support as did Sata in 2011 (I lean towards him getting a sizable sympathy vote). Lungu is new to the presidential race, while HH has run multiple times. HH therefore has an assured strong base in the south (and possibly west) and better name recognition across the country. So despite PF’s incumbency status (which is no small matter), in many ways this is an open race.

From a research perspective, I’ll be keen to observe how the map above changes once all the votes are in. Which regions of the country will swing out of the PF column? Will the MMD survive this election? Can HH break out of his “Southern” tag?

Whatever the results, this by-election is a warm-up to what promises to be a very exciting General Election in 2016 (Also, I hope to have opinion poll data to play with ahead of the 2016 contest).

Taxation in Africa

Why do developing countries tax so little?

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Fig. 1: click on image to enlarge

Besley and Persson begin to provide answers in this 2014 paper:

Low-income countries typically collect taxes of between 10 to 20 percent of GDP while the average for high-income countries is more like 40 percent. In order to understand taxation, economic development, and the relationships between them, we need to think about the forces that drive the development process. Poor countries are poor for certain reasons, and these reasons can also help to explain their weakness in raising tax revenue.

……….low taxation may reflect a range of factors that also help to explain why low-taxing countries are poor. From this perspective, the most important challenge is taking steps that encourage development, rather than special measures focused exclusively on improving the tax system.

Click on image to enlarge

Fig. 2: click on image to enlarge

In the specific case of Africa, here is a chart from 2010 (2007) showing the tax mix in African states. We know from theory that the share of direct taxes in the tax mix tends to be a good proxy for state capacity.

But the structure of the economy appears to matter, and endogenously determines both the proportion of taxes as a share of output collected (see Figure 1 above) and whether states bother to invest in the capacity to exact direct taxes (see the extreme case of oil rich Equatorial Guinea).

Lastly, the tax story in Africa points to a positive increase in state capacity over the last 25 years. Since the early 1990s, the region’s mean tax revenue as a share of GDP has grown from 22% to more than 27%. Per capita tax collection has also been on the rise. That said, there is quite a bit of variance in these measures, with lower income countries doing considerably worse than their richer counterparts.

More here. See also here.

Update: Morten Jerven (author of Poor Numbers) just alerted me of the existence of this cool dataset on taxation and development.

On the IMF and Ebola

Did IMF policies lead to the inability of the health systems in Liberia, Guinea, and Sierra Leone to contain the ongoing Ebola outbreak?

There has been a lot of back and forth on this question in the blogosphere, the most prominent being posts over at the Monkey Cage Blog by Benton and Dionne on the one hand, and Blattman on the other.

It’s really hard to pin the total collapse of the health sectors in the Mano River Region on specific IMF policies. We don’t have counterfactual Mano River Regions that: (a) did not experience civil wars in the early 1990s, (b) did not have to implement structural adjustment policies (because of severe self-inflicted fiscal distress), and/or (c) reformed their institutions and systems of government to make them more responsive and efficient in providing social services before the outbreak in late 2013.

So the best we can do, really, is to speculate (see this informative post by Morten Jerven).

As Blattman argues, countries that required IMF help from the late 1980s did so because their central banks and treasuries had failed at managing their fiscal and monetary policies (the IMF was essentially a central bank of last resort). Which raises the possibility that perhaps we should blame these countries’ troubles on the Latin American countries that made everyone realize that the developing world’s debt in the early 1980s was unsustainable; or the world commodity crises of the 1970s.

In light of the events of the early 1980s, a plausible simple defense of the IMF is that things could have been much worse (total financial collapse) if it had not intervened. In other words, that it is not clear whether, left to their own devices, highly indebted developing countries would have had an autonomous recovery in a manner that would have laid the foundation for their healthcare systems to be strong enough to identify and contain an Ebola outbreak in their respective remote rural regions in late 2013.

That said, IMF interventions – whatever the justifications – had consequences. The discussion in the blogosphere so far has almost exclusively focused on the fiscal effects of IMF policies (specifically with regard to social spending). But as Herbst has argued in “The Structural Adjustment of Politics in Africa,” there were political consequences as well:

……… there has been almost no attention devoted to what structural adjustment, if implemented, means for the way that politics is actually carried out in African nations. The failure to examine the long-term consequences of economic reform for politics is particularly surprising given that the major instruments of structural adjustment — public sector reform, devaluation, elimination of marketing boards—threaten to change not only the constituencies that African leaders look to for support but the way in which leaders relate to their supporters in the countries south of the Sahara.

……… The paper finds that structural adjustment makes the political climate much riskier for leaders while weakening the central apparatus of the state on which rulers have long relied to stay in power.

Time horizon concerns have significant effects on whether politicians choose to invest in public goods.  The obvious question then is: Without top-down procrustean IMF intervention back then, would highly indebted governments have avoided total economic meltdown via policies that were (relatively more) incentive compatible with their unique political economies? The studies highlighted by Dionne and Benton delve into some of the political economy consequences of SAPs, and the specific ways in which they impacted social service provision.

So going back to the question of whether the IMF reduced the Mano River Region’s capacity to handle Ebola, the simple answer is that we can’t tell for sure. The case for a direct causal relationship is weak at best. But there are also lots of possible causal mechanisms that indirectly implicate the IMF. There is a reason why so many smart academics criticized the implementation of SAPs.

The lesson here is twofold:

(i) Neither the Bank nor the IMF are omnipotent puppet masters able to direct public policy in developing countries. But the same developing countries also lack the ability to perfectly sidestep the policy prescriptions from the IFIs. They have agency, but in very tight corners.

and (ii) International intervention should always, to the extent that is reasonably possible, be embedded in domestic political economies. We (the royal we in development research & practice) like talking about self-enforcing this and that, but then prefer to play “neutral” and “apolitical” interveners all the time. Because we do not live in a world of benevolent social planners, there is seldom anything like a disinterested, value-neutral, and victimless intervention.

The Long-Run Economic Impact of the Tse Tse Fly in Sub-Saharan Africa

The Tse Tse is estimated to have had substantial effects on precolonial Africa: a one standard deviation increase in the TSI [Tse Tse suitability index] is associated with a 23 percentage point decrease in the likelihood an African ethnic group had large domesticated animals, a nine percentage point decrease in intensive cultivation and a six percentage point reduction in plow use. A one standard deviation increase in the TSI is correlated with a 53 percent reduction in historical population density….

The TSI has a negative correlation with current economic outcomes as measured by satellite light density or the observed cattle distribution in Africa. The modern analysis is performed at the district level and is robust to including country fixed effects. The evidence suggests that the relationship between the TSI and satellite lights is driven by the Tse Tse’s effect on shaping historical institutions, particularly political centralization.

You can find the entire paper here.

HT Tyler Cowen.

On Bad Roads (in pictures)

Even presidents get stuck on bad roads when it rains. Here is President Joseph Kabila of the Democratic Republic of Congo. The DRC has a landmass of 2,267,048 sq km, and 2,794 km of paved roads.





What can be done to increase road access in the DRC? Big projects like this will definitely help. But a big accelerator of the process will probably be urbanization. Kinshasa is the second largest city in Sub-Saharan Africa, after Lagos. Many of you probably have never heard of Mbuji Mayi, a city of about 1.7 million people (Other big cities in the DRC include Lubumbashi, Kisangani, Bukavu, and Kananga, and Tshikapa).

The projected rapid urbanization rate in Africa, and much of the developing world, is often depicted as a disaster waiting to happen (largely due to poor infrastructure and lack of jobs). But urbanization can also be seen as an opportunity to take advantage of economies of scale to provide public goods at a lower cost. It might even have a positive impact on agricultural productivity – by creating reliable concentrated markets in urban areas and possibility through greater levels of land consolidation to take advantage of scale. That said, governments will still have to build major highways linking cities, and farms with markets.

Political Engineering and Defense Contracts in the United States

Here’s a paragraph from James Fallows’ great piece on the American Military in The Atlantic:

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Source locations for parts of the F-35 (more than 90 Congressional districts)

A $10 million parts contract in one congressional district builds one representative’s support. Two $5 million contracts in two districts are twice as good, and better all around would be three contracts at $3 million apiece. Every participant in the military-contracting process understands this logic: the prime contractors who parcel out supply deals around the country, the military’s procurement officers who divide work among contractors, the politicians who vote up or down on the results. In the late 1980s, a coalition of so-called cheap hawks in Congress tried to cut funding for the B-2 bomber. They got nowhere after it became clear that work for the project was being carried out in 46 states and no fewer than 383 congressional districts (of 435 total). The difference between then and now is that in 1989, Northrop, the main contractor for the plane, had to release previously classified data to demonstrate how broadly the dollars were being spread.

More here.