In my last post, I talked about numbers, about progress and about impact we could measure at Al Mokha. Economists tend to get wrapped up in numbers. This group of people is richer, you might say, and an economist wants to know, okay, but how do measure “rich”? Is it how much money or how many assets they have; is it how much they earn? How do you get a representative sample to answer your questions? How do you know that someone’s observable (or unobservable) characteristics aren’t influencing the way they perceive the question?
Economists have largely settled these questions. With a little effort, you could get to a point where you could measure “rich” satisfactorily, where you could answer the question of who is richest.
But some questions are simply unanswerable within the paradigm of statistical causality. Some of those questions are ones that Al Mokha wants to answer.
For instance, is coffee the best answer to Yemen’s woes?
The government of Yemen certainly thinks it’s an important part of the equation:
Coffee production and export is a vital contributor to Yemen's economy, with tens of thousands of families relying on it for income. Yet, the recent waves of conflict have challenged the sustainability of many of these farms, as the frequent shortage of water, lack of access to transportation, and the absence of an infrastructural support system have drastically affected production and output. Hence, post-conflict agricultural rehabilitation will need to address the revival of coffee production as an integral economic sector. (Abdulrahman Al-Eryani, Economic Development Officer, Embassy of Yemen in the US, podcast).
So, clearly a big deal, but does agricultural investment and revitalization represent the best way to jumpstart Yemen’s GDP growth? To employ those who might otherwise engage in terrorism? To increase the welfare of Yemen’s farmers and citizens? Will increasing demand for coffee lead to more coffee production, or are there other associated outcomes that are actually more favorable?
Best is a really tough word for economists. In order to really answer these questions, I’d ideally want two identical Yemens, one in which Al Mokha goes in and injects a bunch of demand into the coffee sector perhaps along with some other programming, perhaps not, and one in which Al Mokha never existed. This Al Mokha-less world would be our counterfactual. Without a counterfactual, I can’t say from a statistical or causal standpoint that Al Mokha coffee is doing great things for Yemen or for the United States’ foreign policy goals. The old correlation is not causation cliché is very important here.
But that’s just one counterfactual. To get the “best” answer, I’d probably also need a couple of other Yemens. One where someone goes in and injects cash into tourism, another into foreign aid, another into call centers, and really any number or combination of other development strategies. After we played out all the scenarios, I’d measure things like terrorism and farmer incomes, and all sorts of other outcomes and see which Yemen came out on top. And we'd have to do all this before any intervention, too, because we need a baseline. This is clearly not going to happen, not least of all because it would take some supremely awesome bending of space and time, but also because it wouldn’t be ethical to take Yemenis through the ringer like that.
If we’re unable to answer the question of whether this is the best model, can we at least determine whether is it a good model?
I think the answer is yes.
First, we can look at what other people have said. Lots of smart economists, organizations, and thinkers have written about how to improve farmers’ lots in the developing the world. A growing literature shows how fair trade might not be all that great for farmers. Higher prices don’t necessarily offset lower yields and while some Fair Trade households in Mexico saw greater schooling for girls, there wasn’t much effect for boys (e.g., Gitter, Nunn). Maybe farmers just need better access to storage for their products to smooth out prices over time.
We can also look at how individuals respond to incentives. For instance, farmers may change their crops when faced with the possibility to reduce price volatility. These farmers like stable prices and so will choose crops that give them that (or at least more of that). If we think about how this applies to Al Mokha’s model, we can ask questions like: Are coffee prices stable right now? Can Al Mokha help stabilize them through increased demand? How much demand is needed?
We can use these insights to shape our model.
Second, we need to decide what are Al Mokha’s goals? These are often not so easy to measure. There are lots of metrics we might want to think about: Are Yemenis happy? Are farmers (subjectively or objectively) better off? Is violence less extreme or affecting commerce less? Is the United States government happy with Yemen’s policy progress?
From there, we can go back to the original intent of Anda (Founder of Al Mokha): to promote a development model based on exports of Yemeni coffee where Yemenis are decision-makers about how that market develops. To hear him describe it, he knows deep in his gut that this is the way to go, but he also wants to know that he's on the right track. That's the hard-to-measure part.
If we can’t measure everything we would like to either due to inability to collect data or a fundamental “unmeasurability” of some metric, then perhaps we should go back to those experts, those papers. Does Al Mokha make a compelling case for fomenting development through a relatively hands-off model of building up the coffee sector?
For that, we must ask, Who are the relevant stakeholders and experts to whom we can pose this fundamental question? Do we care about the opinions of policymakers? Diplomats? Consumers? People in the military? Economists? Yemeni farmers? Other Yemenis? And what about ideology? Does a strategy based in free-market, neoclassical economics appeal to people at different ends of the political spectrum? Does it matter?
Right now, we are moving forward on the basis of this two-pronged approach:
we tap the wisdom of experts and stakeholders and we scrutinize and apply the latest economic research. To that we add entrepreneurial optimism and strive towards coffee's $1 billion opportunity for Yemen.
"I'm positive I'm right" (Anda)
But that's a lot of generalities. You want specifics. How will Al Mokha show it is improving lives? How will Al Mokha show it is making Yemen stable?
In the next post you'll hear from Anda as he declares with bravado, "I'm positive I'm right" and you'll hear from me as I say, "Prove it".
"Prove it" (Erin, photo courtesy of Breyt Photography)
For now, I’ll leave you with this: From deep in our guts and to our most logical, quantitative rebuttal, we're thinking hard about how to make sure that Al Mokha has an impact that is large, positive, and scalable.
Those interested in trying Al Mokha's coffee can shop at www.almokha.com
Erin is Al Mokha's Board Advisor in developmental economics. She has no financial interests in Al Mokha and has received no compensation for this post.
If you’ve been hanging out with us at Al Mokha for some time, you know that "Mocha" or "Mokha" means coffee from Yemen. And you’ve heard the story before: coffee cultivation started in Yemen circa 1450 and shipped from the port city of Al Mokha; and that’s how place name became synonymous with product.
Similarly, if you scratch your head a moment, you may think, hmm…maybe "java" literally means coffee from the Indonesian island of Java. And you’d be right.
Not only that, but you would be putting your finger on the “world’s second coffee™”. In about 1699, the Dutch East India Company began cultivating and exporting coffee from Java. This new origin ended Yemen's 250-year monopoly.
So there you go, and it’s pretty obvious how you would end up with a blend. Take Mocha + Java—i.e. world’s first and second coffee—and voila, Mocha-Java, the World’s First Blend™. This is hardly a complex mathematical equation.
As a development economist with interests that are a little outside the norm, I spend a lot of my day thinking about how to measure unmeasurable things. How prevalent is a certain belief? And how does it affect people’s behavior? Can one violent event, or experience, be objectively seen as worse or more violent than another? And if so, what determines that violence—scope, tenor, frequency? How do we fix it?
So, when Anda told me he wanted to start thinking more about impact and measurement at Al Mokha, I jumped up and down with glee. From the moment he and I first talked development and coffee in Cambridge almost a year ago, I’d been questioning, "cool, but how do you measure that?"
In Part I, Anda wrote about the perils of trying to be a salesperson / academic, and how that duality plays out in the business: investors want to see sales growth whereas economists (me!) want to see real, measureable change in things like poverty levels, in coffee production, in anything we can quantify with data.
So we're working towards that. In this post, Part 2, I introduce myself and in parts III- V we tackle some tough questions.
Well, who am I? If you're here frequently you know Anda and you've heard mention of some of his advisors (as he spins tales of sinking all his time into a startup). I'm the nerdy PhD obsessed with data and development. I have a doctoral degree in economics. I spend most of my time reading and writing papers on violence against women and children and female labor force participation. In the headline photo that's me doing research for the IRC in Nyarugusu, Tanzania. Basically, I spend a lot of time thinking about very economist-y things like incentives.
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