The Ghanaian communications regulator fined five Ghanaian telecom companies a total of 1.2 million GHC today for providing poor quality services, a move sure to be popular with pretty much everyone, since people in Ghana love their phones and hate all the phone companies. 

To give you an example of what poor services means, I haven't been able to call or text anyone on MTN, or receive calls, since I arrived in Sunyani yesterday-- and it was like that all over Brong Ahafo when I left last week.  This isn't some village in the mountains-- Sunyani is a district capital.

The fines were based on failure to provide coverage, geographically and temporally. The highest fine went to Airtel, which has actually provided pretty reliable services for my internet modem, including the hookup to write this article.

In my opinion, the highest fine should have gone to Vodafone, for their atrocious service. Vodafone is the only provider of cable internet in Tamale, and has the only nice, reliable internet cafe. When home and business internet lines go down, they never come fix them, despite repeated calls requesting they do so. Why should they? They can keep charging the monthly rate, plus get additional income when people are forced to go to the internet cafe. This is why natural monopolies must be regulated.

A taxi driver in Tamale recently gave me an interesting lesson in taxi ride pricing.  It turns out that there are two different types of taxis on the road. The most common are drivers that rent the car from someone else. They pay for the fuel they use during the day, and pay a flat rate fee to the taxi owner, usually around 20 GHC per day.  The other type of drivers are those that own the car they drive.

The two types of drivers bear different marginal costs for each taxi ride they give.  The latter, who own the cars they drive, bear the cost of the fuel for the car, their own time (valued at nearly zero in Ghana) and the depreciation of the vehicle due to the ride.  The former, who rent the car at a fixed rate, don’t bear the last cost—the vehicle depreciation.  Therefore they are willing to accept lower prices for each taxi ride.

The driver who told me this of course owned his own car, and was trying to convince me that even though the cost of a taxi across Tamale is always 3 or 4 GHC, it wasn’t fair to pay him less than 5 cedis.

Unfortunately for him, as much as I like a good economic theory, I can also identify a good economic strategy: in this case, using the length of a taxi ride to badger an expat into paying more. (The driver also happened to take the longest possible route through town.) I paid him 4 GHC, consistent with providing incentives to honor the agreed-upon price.

After years of remaining a theoretical plaything for money nerds like me, nominal GDP targeting has suddenly become a thing.   NGDP targeting has been getting love from economists across the political spectrum, which naturally means laypeople across the spectrum are responding with skepticism. Drudged up from what I remember from Prof. Burdekin's Money and Banking, I present the basics of NGDP targeting:

What is NGDP targeting?

NGDP targeting means that the central bank sets monetary policy to target nominal gross domestic product, that is, GDP that is not adjusted for price level.  The beauty of NGDP targeting is that since both prices and output are part of NGDP, both of these things influence monetary policy even though only one metric is considered.  Either NGDP level, or growth, can be targeted.

Why liberal economists like it: liberal economists tend to be more supportive of considering economic growth, not just inflation, when setting monetary policy.  NGDP targeting naturally includes growth as an input.

Why conservative economists like it: conservative economists tend to prefer simple, transparent rules for monetary policy, as opposed to opaque systems that give broad discretion to policy makers. NGDP targeting is easy to understand and easy to see if policy makers have met their goal.

So how is it different?

The Federal Reserve has what’s called a dual mandate—they are charged with considering both prices and economic output when setting policy.  (Some central banks, like the European Central Bank, are charged with only considering prices.)  The Federal Reserve does not commit to following any particular formula for setting monetary policy, but it is largely believed to behave as if it follows the Taylor Rule, meaning it considers deviations from target inflation rates and target employment rates.   Targeting NGDP would provide the Federal Reserve with a mandate to specifically target deviations from output targets.

There are other things a central bank can consider besides prices, employment, and output when setting policy, such as money growth and asset prices.  A central bank with broad discretion can consider all of these things, but this comes at the cost of making monetary policy decisions less transparent.

But what about QE2??

So where do things like quantitative easing fit into all this? It is important to distinguish between the tools used to set monetary policy and the tools used to implement monetary policy.  Tools used to set monetary policy, such as Taylor Rules, money growth target, or NGDP targeting, tell the central bank whether they need to tighten or loosen policy.  The tools used to implement monetary policy generally remain the same regardless of what policy prescription tool you use.  If interest rates are at zero, and inflation is low and unemployment high, you need quantitative easing to get to your targets.  If interest rates are at zero and NGDP is below target—guess what, you still need quantitative easing to get to your target.

Targeting Growth vs. Level

If you are going to target NGDP, you have to decide whether to target NGDP growth rate or NGDP level. Most of the cool kids in economics prefer level targeting.  Level targeting has the benefit of allowing for catch up periods: after the economy has had a downturn, it natural that it have a period of both higher growth and inflation to catch up to where it would have been pre-downturn.

So let’s do it?

To me, whether NGDP targeting should be implemented actually involves three different questions:

1.       Should GDP be considered when setting monetary policy?  The downside to considering GDP or other factors is that the central bank places less weight on price stability, which is bad if you are an inflation hawk.  The benefit is that drops in GDP often lead drops in inflation or unemployment, so considering GDP can help the central bank adjust to new economic trends more quickly.

2.       Should the central bank target levels rather than growth rates? When it comes to prices, levels are arbitrary—it’s change in prices that matter. That’s the primary logic behind targeting inflation rather than price level.  However, as discussed above, it is natural for an economy that has been sluggish for a while to have a period of higher growth and higher inflation to “catch up” after a downturn, so monetary policy that accommodates this can make sense. This accommodation can actually help end a downturn more quickly—if during a downturn, people know they can expect extra high inflation in the future, they have an incentive to spend more now, stimulating the economy.  The flip side to all this, which I haven’t seen discussed much, is that monetary policy lags the trends a bit.  This sounds great when you are coming out of a recession, but what about when you are coming out of an expansion? Would the people keen to see accommodating monetary policy continue as growth picks up be equally keen to see tight monetary policy stay in place when growth comes to an end?

3.       Should the central bank have a clearly defined rule? The benefit of a rule is that it provides transparency and sets expectations, and expectations are essential for effective monetary policy.  The downside of a rule is less flexibility, and loss of credibility if the central bank fails to meet its targets.

If you answered yes to all of the above, then NGDP level targeting is for you.  Personally, I agree that a central bank with a dual mandate should consider GDP.  However, I think that the central bank should have some flexibility in targeting levels versus growth, and that growth is sometimes the more appropriate metric.   Moreover, I think that a central bank like the Federal Reserve, that has a high level of trust and credibility, has more to lose from committing to a rule like NGDP level targeting than it has to gain, since failure to achieve the target would hurt its credibility.  As it is, the Federal Reserve can consider the policy prescriptions of an NGDP target, while also considering Taylor Rules, asset prices, and other economic data when setting monetary policy.

Recently, in a small village print shop with an old copy machine discarded from Canada or Belgium or some such place, I received a printing bill for twice the amount I expected-- because I printed my document from a pen drive.

Newcomers to Ghana are often warned of the dangers of "promiscuous" pen drives. which can spread viruses. (The term seems increasingly appropriate the more I consider the mechanics of using a pen drive.)

It is interesting to see that shops recognize the risk and tax it by charging higher rates on printing from pen drives. I was a bit put out, however, because the additional rate is charged per page, even though the virus risk is no different for printing a one-page document than a 100-page document. I'm looking forward to finding the shop that charges a flat rate fee for using a pen drive. I'll admit the deterrent is effective though: next time, I will email my document to myself.

How do you find an office in a town in Ghana? Mostly, you walk into town, chat up everyone you meet, tell them you are looking for an office, and give them your contact number. People are usually happy to help. Be outgoing, and soon you can have a beautiful, blue office like ours.

Chris Blattman recently blogged about the moral absurdity of running regressions where the dependent variable is “war deaths”.  While looking at death, illness, hunger, and poverty through the lens of statistics may seem rather reptilian, I think many researchers have emotional reactions to the data they work with.  For me, these connections hit hard and unexpectedly, often when I am tired and working late, and they come despite efforts to be dispassionate about the data I am looking at.

Survey editing is prime territory for emotional connections to data. When editing surveys, you see the story of an individual respondent in a way that you don’t when you are looking at columns of aggregated data .  Once, I was reading a survey where a respondent reported that a household member had experienced a headache.  I turned the page to the question on outcomes of health events.  The headache had resulted in death for that household member—despite the family spending an amount equal to roughly one-fourth of Ghana’s annual GDP per capita on health care for that individual.  The shock of the outcome hit me almost physically. Another respondent reported testing positive for HIV. Sitting alone in the Tamale office at night, I struggled to pull myself together, shoo the bugs out of my computer keyboard, and make my way home.

The “death” outcome became a dependent variable in regressions I later ran looking at determinants of health outcomes.  Luckily, there were very few events of death in my sample.  We also looked at a number of food insecurity events: individuals going to bed hungry, or not eating for an entire day, for example.  These were, unfortunately, common among our respondents.  I don’t deal well with feeling hungry myself, and for me, food insecurity statistics evoke desperately sad, human images: a man’s disappointment at foregoing his favorite fish; a young student trying to sleep before an exam while feeling the distracting ache of hunger; an elderly woman going without food for a day so her grandchildren can eat; a mother having to tell her thin children there is no food today.  

These emotional connections often seem like a distraction, something that prevents us from approaching our analysis logically and dispassionately.  In all honesty, part of my attraction to quantitative research tools might be to protect myself from these types of emotional connections to problems.  But it our ability to have these connections, even through layers of statistics, is tied to a very deep belief in the importance of what we are doing, and that counts for something.  Hey, at least I’m not working in finance.

A major study was recently found to contain an error that led the study to overestimate the cost-effectiveness of deworming by a factor of 100. (Note that this was NOT the IPA RCT study of deworming in Kenya, which found deworming to be highly cost-effective in part due to large positive spillover effects.)

This is the type of thing that keeps project associates up at night-- when we aren't staying up trying to track the surveys that came in that day, writing .do files to analyze our data, or drafting reports containing our results. The fact that we work long hours, on tight schedules, sometimes while delirious with malaria doesn't help. My most recent report was 120 pages long, and based on what must be tens of thousands of lines of stata code.  It's hard to believe there are zero errors in that code.

So how I am going to sleep tonight? I know two sets of eyes have looked over the code used in the analysis. I've looked critically at the findings to see if they make sense, and if they are consistent with the rest of the data. We might not be able to catch everything (were there some observations I should have recoded for that question?) But hopefully we can catch the "factor of 100" errors.

Also, I am really tired.

Mile -26.2.  It’s pitch dark, and I’ve just arrived at the finish line on my moto.  The time is a few minutes after 4am.  It’s not that unusual for me to be awake at 4am on a Sunday morning.  Jokers, which manages to be both shady and upscale, was still packed with SUVs when I passed it on the way to the race course.  What’s unusual is for 4am on a Sunday to be “early”.

Mile -15. The shuttle provided from the finish line to the start line is hopelessly lost somewhere in Teshie.  Good thing, or else how would we know we were running a marathon in Ghana?  If we wanted a reliable transportation to a marathon, we’d be in Boston. 

Mile -18. The marathon is scheduled to start in 5 minutes.  We are still lost in Teshie.

Mile 0. We arrive at the start line in Prampram almost an hour late. They’ve delayed the start for us. We hop of the shuttle, and we line up almost immediately.  There is no time to use the facilities (sparse bushes, in this case.)  Luckily, unlike my male counterparts who can easily wee anywhere in Ghana, I know how to hold it—and I will, for 22 miles.

Mile 1. Everything is beautiful. It’s not hot yet, we run past a group of drummers playing for us, I’ve got my running mix on my mp3 player, and I am feeling strong.

Mile 4. “California Love” feels less appropriate running through the morning sunlight in the bush around Prampram than it does running through Jamestown after dark.

Mile 5.  Because the Accra International Marathon is small, each runner gets a lot of personal attention.  Trucks pass up and down the race course, handing us water out the window and making sure we are okay. I notice that one of the escort trucks is provided by an insurance company. I chuckle.

Mile 6.  Why are they giving us so much water?

Mile 7.  What, water again? Oh, no—the truck driving beside me actually doesn’t want to give me water this time.  They’ve noticed I am carrying medical tape, and a runner behind me has developed some bad blisters. I turn around, find the runner, and help him tape up his feet, and we both continue the race.

Mile 9. One-third done! Woot! But I’m not feeling so strong anymore.

Mile 10. Traffic police are stopping traffic to let each runner go through the roundabouts in Tema.  The police wave and yell encouragement. I wonder if the economic gain from the race outweighs the cost of the traffic disruption.

Mile 13.1. Halfway there! Wait, somehow that doesn’t seem so encouraging…

Mile 13.2. It’s my turn to strip off my socks and tape up some aspiring blisters.  I still need to pee.

Mile 15.  Where the f*** are all the banana ladies? I’m hungry, as I have eschewed the abomination that is energy gels.

Mile 16. I have 10 miles to go, and I feel completely out of juice, but there is no way I’m not finishing. I pull back. My strategy at this point is to concentrate on making it through to mile 20, and then hope for an adrenaline rush to get me through the last 6 miles.

Mile 17. I’m running right along a gorgeous beach, with a view down the coastline. Wait, I have to run that far. I consider jumping in the ocean and swimming to the finish line.  I bet it would be less painful. Even though the current is going the other way.

Mile 18. The route veers away from the coast. The breeze is less, and it’s hot as hell. Why aren’t they giving us more water? Can I buy insurance if the sponsor car comes by? Talk about adverse selection…

Mile 18.5. A man pulls up beside me in a car and tells me he wants to meet me.  I don’t reply. It seems more polite than the only other imaginable response at this point.

Mile 19. I seem to have alien foot syndrome. Spasms in my lower leg muscles are causing my feet to twitch involuntarily, making it hard to keep proper foot alignment as I run.

Mile 19.5. Finally, a banana lady! She seems confused about my desire to pay 1 GHC for 1 banana, and take off with it without a bag or my change, but things work out.

Mile 20. Time to give a wake-up call to my nutrition and transportation sponsors, Kris and Par.  The prospect of calling my friends while running has been a source of motivation for the last several miles. I call Kris, and he and Par are already at the finish line, along with my boss Jessica, who is also out to support me. I hope they brought plenty of beers, because it will be another hour before I get there.

Mile 21. What was I thinking? Too late to stop now though.

Mile 22. If you are going to run 22 miles to pee, you might as well do it in style. I stop at the Ramada to use the washroom.  I take two sachets of water from the station here, drinking one and packing the other in the bottle at my waist. 

Mile 22-26. There are no more water stations for the rest of the race, and the heat is stifling at this point, even with a breeze.  I’m glad I packed my water bottle; it lasts me till about mile 24. We are now on my home turf—I run through Teshie often.  The familiar terrain tricks my body into a more familiar pace, and I pick up speed a little.

Mile 26.2. I manage to finish, if not strong, at least without looking like I had to drag myself over the finish line.  Jessica, Par, and Kris are there cheering for me.  They help me find water, turn in my place tag, and generally not fall over.  I finished 9th among women, which probably isn’t saying much in such a small race, but I’ll take it.  They had out bags of jollof rice, which somehow seems right.  I celebrate finishing in the proper fashion, with a bottle of Johnnie Walker, much to the delight of the Rasta musicians providing the post-race entertainment.

After.  Par, my transportation sponsor, road my moto home for me.  Kris, my nutrition sponsor—he provided every calorie used during the race with the exception of the afore-mentioned banana—loaded me into his car and drove me home.  Jessica, Par and Kris all took photos for me.  A day after the race, I am pretty stiff.  I am not driving my moto because my calf muscle is too sore to shift reliably.  My tape did well with friction issues, but I have a few blisters, including one wrapping around my smallest toe, making that toe about double in size.  I’m hungry all the time. All in all, I actually think I got off pretty lightly, given that I was certainly underprepared, and the conditions were tough.  I estimate that I drank 5-6 liters of water during the race (That’s twice the recommended amount for avoiding hyponatremia. I don’t think the people who made that recommendation have ever run a marathon in Africa.)  The satisfaction of finishing a marathon was definitely worth it, and I think I’d like to give it another go.  Big 5 marathon, here I come?

PS. If you’ve read this far, you deserve to know that the bottle of Johnnie Walker was filled with apple juice.  A message to other JW fans in West Africa: break your bottles when you are done with them.  You never know what they can be refilled (and sold) with!

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The pangolin, one of my favorite animals, recently made the news.  This unusual looking anteater is being hunted to extinction due to demand for its meat and scales, which are believed to, among other things, enhance sexual prowess in traditional Asian medicine.

Enforcement efforts have not been able to put a stop to the trade.   Although trade in these products must continue to be illegal, and these laws must be enforced, they will not be sufficient to stem this problem.  Here’s why:

·         Lesson from the drug war: fighting supply doesn’t work with products that have inelastic demand.  When demand is not very price sensitive, limiting supply just causes the price of the product to rise, giving more incentive for people to keep supplying.  Endangered species products for use in medicine likely fall into this category, as likely perceive these medical cures as a need.  According to the article, an entire dead pangolin used to be valued at $5; today the scales alone go for $250. Powdered rhino horn can be more valuable by weight than gold or cocaine.  That’s a pretty big incentive to break the law.

·         Economic conditions will continue to enable higher prices and more demand.  Rising incomes in China and South East Asia, the source of much of the demand for endangered species products, will further accommodate higher prices for these products.

·         Creating efficient disincentives in the source countries is difficult.  When deciding whether to break a law, economic actors compare the benefit of the crime with the penalty, weighted by the likelihood they will get caught.  In poor countries, the resources available for enforcement are limited, so likelihood of getting caught can be low.  Higher prices, driven by the previous two factors, can entice more sophisticated suppliers to enter the market, who are better at evading enforcement efforts.   In cases where suppliers are poor, penalties such as fines may be ineffective, because the supplier has little to lose.

·         Endangered species parts might be non-normal goods—meaning that higher prices actually raise demand.  In the case of medicines, a higher priced medicine might create a larger placebo effect, for the same reason people who know the price of an expensive wine tend to rate its taste more highly.  In the case of luxury goods, the scarcity of the product, and fact that it is illicit, might actually increase the prestige associated with owning it.

These factors imply that to put a real stop to endangered species products trade, we must address the demand side.  There are a couple potential approaches:

1.       Try to shift the demand curve left.  This involves decreasing the number of people demanding the product, or decreasing the amount of product that each person demands.  In order to do this, you have to convince people that they don’t need these products, or that they are inferior to other options.  Intense education, shame campaigns, and social pressure to embrace modern medicines might be approaches to achieving this.

2.       Make demand more elastic by increasing substitutes.  If you cannot convince people they don’t need these products, you might still be able to make demand more price sensitive if you can convince them that other substitutes can suffice.  Endangered species parts might be replaced with parts from more common animals in traditional medicine recipes.  This might be achieved by working with practitioners of traditional medicine to promote recipes that don’t include endangered species parts.  This strategy, however, runs the risk of transferring the over-demand to other species.

Any strategy aimed at demand is incredibly daunting, as it involves changing long-held cultural beliefs and behaviors, practiced even among the highly educated.  And some traditional medicines work:  ma huang, traditionally used to treat colds, contains pseudoephedrine,  the active ingredient in many over-the-counter cold medicines, and Artemisia, another traditional medicine, is now a standard component in most malaria treatments.  It is not easy to convince people that while their age-old belief that Artemisia cures malaria is true, their age-old belief that anything remotely phallic increases sexual prowess isn’t.  Though if you think a pangolin looks phallic, you are probably long overdue for an STD screening.

The Ghanaian press recently published a story claiming that 90% of police officers in Ghana are alcoholics. Despite the hyperbolic headline, the actual statistic in the text is a bit more ambiguous-- it says that 90% of police have medical conditions such as hypertension and cardiovascular or heart disease that can be linked to alcoholism.

The best part of the story? The police service try to reassure the public that police officers are tested before being sent to other countries for peacekeeping. I take this to mean that if they send 10% of police abroad, then we must have 100% boozed cops here in Ghana.