In a nice new(ish) working paper, Anandi Mani and Emma Riley review the recent and expanding literature on social networks, role models, peer effects, and aspirations in low and middle-income countries. In this post, I will summarize Mani and Riley’s review of the literature and offer my own commentary along the way. I will also comment on some of the methodological challenges implicit in this literature and will end with a discussion of what this all means for development policy.
Aspirations, or future-oriented goals, influence how we make choices in the present. In recent years, development economists have developed a particular interest in the way aspirations influence human behavior. The figure below plots my calculation of the number of published articles that mention “aspirations” cataloged in the EconLit database from 1956 through 2016.
I am a bit behind on this, but earlier this year a nice new paper on aspirations was published in the Journal of Economic Behavior & Organization. The paper, entitled “Aspirations Failure and Formation in rural Nepal” is co-authored by a team of researchers who are currently performing really interesting field-work in Nepal. Here is a link to a Feed the Future Policy Brief and here is the abstract to the paper:
What is a “Gustibus Multiplier”?
That is what I thought when I read the title of Michael Carter’s recent paper in Agricultural Economics entitled, “What farmers want: the ‘gustibus multiplier’ and other behavioral insights on agricultural development“.
In David McKenzie’s most recent Weekly Links, he posted a link to an interview with Erik Hurst, who is an economist at the University of Chicago’s Booth School of Business. The interview spanned a wide range of topics including Erik’s work on income inequality, the decline of the US manufacturing industry, college attendance, and (what Erik calls) endogenous gentrification. The whole interview is fascinating to read, but I’d like to highlight one part of the interview that I find particularly interesting.
Question: Many people have an image of the typical entrepreneur in their head and it often includes a significant taste for risk and large long-term aspirations. What does your work on entrepreneurship suggest about that profile?
Erik Hurst: Most small businesses are plumbers and dry cleaners and local shopkeepers and house painters. These are great and important occupations, but empirically essentially none of them grow. They start small and stay small well into their life cycle. A plumber often starts out by himself and then hires just one or two people. And when you ask them if they want to be big over time, they say no. That’s not their ambition. This is important because a lot of our models assume businesses want to grow. Thinking most small businesses are like Google is not even close to being accurate. They are a tiny fraction.
My work with Ben Pugsley has been emphasizing the importance of nonpecuniary benefits to small-business formation. Because when you ask small-business people what their favorite part of their job is, it’s not making a lot of money. They do earn an income and they’re very happy with it, but they get even more satisfaction from being their own boss and having flexibility and all of those other nonpecuniary benefits that come with being the median entrepreneur in the United States.
In our culture we seem to want to subsidize small businesses because it’s the American dream. I think that could be fine, if you believe that there’s a friction out there preventing some small businesses from starting or growing. But you might want to target that friction directly as opposed to targeting all small businesses generically. Ben and I have a recent paper in which we show in a simple model that if you subsidize all small businesses, in a world with nonpecuniary benefits being the big driver of small-business entry, the policy is highly regressive. Why? High-wealth people are already small-business owners because they can afford the nonpecuniary benefits that come with owning a small business. So in that world, we’re basically just transferring money to high-wealth people when we subsidize small businesses overall, and that’s something we need to consider.
Excellent points, I think. I’ve been having discussions with some colleagues of mine about similar issues in developing countries. A lot of very popular international development policies aim to support entrepreneurship in developing countries (i.e. microcredit, business skills training, etc.). Unfortunately many of these programs often fail to pave a smooth and wide road out of poverty for the average household. One reason to explain this failure is that it seems many assume that everyone who owns a business is an entrepreneur who is risk-loving and aspires to grow and expand their business beyond it’s current level. This assumption breaks down in many developing countries (in similar ways to how Erik describes the breakdown in the US).
This has lead my colleagues and I to conclude that we many need a different word for, and a method for identifying, an “entrepreneur who doesn’t aspire to grow their business”. This sort of semantic and empirical innovation would have several interrelated benefits.
First, it would help policymakers better target certain policies and programs to individuals who would actually benefit from the program. Instead of rolling out a micro-loan product or a business skills training program to the population in general (which may lead to either diluted average effects or regressive benefits – as discussed above) programs could target specific individuals who actually aspire to grow and expand their business. Including everyone else will be wasteful because even if all the necessary external constraints are lifted (i.e. credit, skills, insurance, access to markets, etc.), these individuals may still not grow their business because they do not desire to do so.
Second, this innovation would also help empirical development economists who run experiments to estimate the impacts and cost-effectiveness of policies and programs. If it were possible to correctly diagnose development interventions that aim to support entrepreneurship and administer them only to those who are risk-loving and aspire to grow their business then, statistical tests would be much more accurate. As Bruce Wydick explains in a recent blog post on Diagnosis and Development Impact:
Suppose that a is the average treatment effect of an intervention on the properly diagnosed, e is the externality of the intervention to all others in the treatment group (with no externality to the control), and d is the percent of the treatment group that is diagnosed correctly. In this case, the ITT is just the weighted average of these effects between the properly diagnosed and others (the misdiagnosed) and is ad + e(1 – d). To estimate the ITT with 95% confidence and 80% power, the condition must hold that ad + e(1 – d) = 2.8SE , or that the percent correctly diagnosed must be equal to d = 2.8SE – e / a – e (where 2.8 is the sum of corresponding z-scores of 1.96 and 0.84 and SE is the standard error.) Assuming a > e, first differentiation shows this yields a negative relationship between d and e; analysis of the second derivative shows the relationship to be concave, as shown in the figure [in this link]. This yields a continuous set of statistical power contours that illustrate the trade-off in ITT estimations between correct diagnosis and the strength of externalities within the pool of subjects exposed to the intervention. Statistically speaking, the result is quite similar to the loss in statistical power one experiences with a treatment that is targeted at treatment group, but where very few people actually take up the treatment.
So, I’d say we need to think of a term for “entrepreneurs who don’t aspire to grow their business”. That is the first hurdle to jump. The second is to find ways to effectively diagnose risk aptitude and aspirations (or better yet hope for business growth). Some ideas come to mind – methods for estimating risk preferences are well established and I have a working paper currently out for review that makes some initial steps in validating a method for quantifying measures of hope and aspirations – but these methods need to be further investigated and tested.
HT: David McKenzie
The International Monetary Fund (IMF) recently released it’s projections for GDP growth in the year 2016. The country on top of the list? Myanmar. At 8.6%. That’s a lot and is (on the surface) quite encouraging for a country who’s economy pales in comparison to even the economy of it’s neighbor, Thailand. With vast political and economic reforms have come increased consumer confidence, large inflows of foreign direct investment, and a strengthened partnership with “the international community”.
But, as any economist will tell you GDP is a measurement of economic performance not a measurement of well-being. In fact, rapid economic growth, like what Myanmar is experiencing at the moment, can result in a range of effects on well-being. At the extremes of this range are effects that seem to be opposites of each other. Here is Ghatak, Ghosh, and Kotwal (2014) commenting on the past decade in India:
[2004-2013 was] a period during which growth accelerated, Indians started saving and investing more, the economy opened up, foreign investment came rushing in, poverty declined sharply and building of infrastructure gathered pace . . . [But a] period of fast growth in a poor country can put significant stress on the system which it must cope with. Growth can also unleash powerful aspirations as well as frustrations, and political parties who can tap into these emotions reap the benefits.
If the next decade for Myanmar looks at all like the past decade for India, many would consider this to be a success. As the economy opens up bringing with it accelerated growth, increased foreign investment, large investments in infrastructure, and a sharp decline in poverty on average; questions remain. Will these advancements unleash powerful aspirations or vast frustration? Will the dividends of peace, security, and democracy include the farmers, fishermen, entrepreneurs, and families in the rural areas or will the impacts be contained to the rapidly developing urban areas?
This past week I was able to attend the Agricultural & Applied Economics Association Annual Meeting in San Fransisco. It was a fun event with lots of good discussion. In this post I’ll highlight a few of the most interesting sessions I attended. Unfortunately due to the nature of these sort of events, I was only able to attend a small fraction of the available sessions. I know I missed an excellent session on Incorporating Ethics in Economic Analysis with Paul Thompson, Jayson Lusk, David Just, and Harvey James Jr.
Agriculture in Africa: Telling Myths from Facts
The first session I went to summarized a large research project aiming to close the data (and knowledge) gap about agriculture in Africa by implementing nationally representative household surveys in six African countries. Here is a short intro video:
The research aims to confirm or deny the validity of several commonly perceived wisdoms about agriculture in Africa such as:
- The use of modern inputs, like chemical fertilizer, remains dismally low.
- Land, labor, and capital markets remain largely incomplete and imperfect.
- Agricultural labor productivity is low.
- Land is abundant and land markets are poorly developed.
- Access to credit remains low.
- African youth are leaving agriculture en mass.
- Trees on farms are negligible.
- African agriculture is intensifying.
- Women perform the bulk of Africa’s agricultural tasks.
- Seasonality continues to permeate rural livelihoods.
- Smallholder market participation remains limited.
- Post-harvest losses are large.
- Droughts dominate Africa’s risk environment.
- African farmers are increasingly diversifying their incomes.
- Agricultural commercialization and diversification improves nutritional outcomes.
I think this is a great list of “perceived wisdoms” because looking it over, I have a vague feeling or opinion about each one of these items, yet I have no data or evidence to back up this belief.
Aspirations, Social Networks, and Economic Behavior
As readers of this blog will know I’m thinking a lot about aspirations (or hope) as it relates to economic behavior. Some great new research as presented by a PhD candidate from the University of Georgia on this broad topic from work in Nepal.
Here’s the working paper: Social Drivers of Aspirations Formations and Failure in Rural Nepal.
I think this is an important research area and this paper makes a great contribution. The authors measure the association between individual’s aspirations for income and assets and the income and assets of people in their social network. This is important as it provides evidence of the theoretical work of Debraj Ray and Arjun Appadurai – saying that people’s hopes and aspirations for the future( which probably determine future-oriented decisions) is influenced by the relative levels of income and assets of others who have similar characteristics to them.
Agricultural Commercialization in the Developing World
There are two papers that deserve a mention under this topic. The first is a study on the welfare impacts of rising quinoa prices. Basically, should consumers in the developed world continue to consume quinoa at the rate we currently do? In short (and at risk of oversimplification) YES! It actually helps people in Peru. Read more from Marc Bellemare’s blog on Quinoa Nonsense, or Why the World Still Needs Agricultural Economists.
The second is a presentation on a replication study of Dean Karlan’s study on the impacts of export crop adoption in Kenya. In light of all the drama about the de-worming paper this past week, it was super interesting to see first-hand how a real replication study actually works. I’m still not sure what the term ‘replication study’ actually means, but I enjoyed this presentation and its implications for the rigor of the scientific process.
Applying Behavioral and Experimental Economics
I was also able to attend and participate in a post-conference workshop on behavioral and experimental economics. Part of this workshop was a great “mini-mentoring” lunch were I was able to discuss some research ideas with some very insightful folks. Most of the workshop was presentations by established researchers who are applying behavioral and experimental methods to their research on food policy, nutrition, and environmental policy. It was fascinating!
The highlight presentation discussed a recently published paper by David Just and Andrew Hanks on the Hidden Cost of Regulation: Emotional Responses to Command and Control.
There were certainly other excellent presentations, I just didn’t have a chance to see them. If you attended the conference, feel free to complete the list in the comments below.
Two years ago I was a senior in college and sitting in a professor’s office discussing several topics I could focus on for a senior thesis. At the time the economics of happiness was gaining a lot of momentum as a research topic. I asked my professor if I could think about the concept of hope from an economic perspective. We did some searching for relevant literature and didn’t really find much. I moved on to a different topic.
Fast forward to now. The economics of hope has a growing and promising literature. I have plans to travel to Myanmar to try and collect data to better understand this topic. As I begin to dig into the literature, I thought it would be nice to record a roadmap of sorts.
Two summary resources provide a great starting point, and much of the insights in this blog post:
- Travis Lybbert and Bruce Wydick‘s (2015) working paper on Poverty, Aspirations, and the Economics of Hope
- Ester Duflo’s (2013) talk on Hope, Aspirations, and the Design of the Fight Against Poverty
What does hope have to do with economics?
At first it may seem like there is not much connecting a light and fluffy topic like hope with cold and calculating economics. Generally economists have a lot to say about a lot of things. But hope is a topic that has historically belonged to theologians, philosophers, poets, and signer-song-writers. At second thought, however, hope is fundamental to any economic activity. Consider the words of Martin Luther:
Everything that is done in the world is done by hope. No husbandman would sow one grain of corn, if he hoped not it would grow up and become seed; no bachelor would marry a wife, if he hoped not to have children; no merchant or tradesman would set himself to work, if he did not hope to reap benefit thereby. How much more, then, does hope urge us on to everlasting life and salvation?
And John Stuart Mill:
A hopeful disposition gives a spur to the faculties and keeps all the working energies in good working order.
What we talk about when we talk about hope
There are a couple ways the word hope is used in english language and the difference between the two is subtle. Consider the difference between two sentences: “I hope it is sunny tomorrow.” and “I hope to go for a run tomorrow.” Both use the term hope but in different ways. Both terms indicate some sort of uncertainty but the second usage implies human agency. I may hope it is sunny tomorrow, but there is nothing I can do to make it sunny. I also may hope to go for a run tomorrow and I certainly can do things to make that happen. Lybbert and Wydick create a helpful figure to represent the differences between “Hope 1”, “Hope 2”, “Hopeless 1”, and “Hopeless 2”.
Hopelessness 1 is experienced by someone with both low agency over the future and low optimism about the future. This is a person who is feeling both hopeless and helpless. For example a victim of a famine who has no food availability in the future and no way to get it either. Hopelessness 2 is experienced by someone with high agency over the future but low optimism about the future. This is a person who is feeling hopeless but not helpless. For example someone who works very hard to survive but doesn’t see a future of any other way of life. Hope 1 is experienced by someone with low agency over the future but high optimism about the future. This is someone who hopes it will be sunny tomorrow. Hope 2 is experience by someone with both high agency over the future and high optimism about the future. This is someone who hopes to go for a run tomorrow.
As Lybbert and Wydick explain:
Distinguishing between these types of hope is useful, but individuals often experience hope as a combination of Hope 1 and Hope 2. Both types of hope, for example, are manifest in the case of a famine victim, or someone who is trapped, lost, or stranded, where a person may have to take painful but proactive steps to survive (internal agency) while awaiting relief or rescue (external to agency). Consider similarly the plight of someone suffering from a potentially terminal disease, in which there is some probability that a breakthrough in treating the disease may occur in the future. Survival thus depends on two events: (i) that the breakthrough occurs by time t; and (ii) that the patient is able to survive until time t. Hope for the patient thus consists of Hope 1 (hope that the breakthrough will occur) and Hope 2 (hoping to remain as healthy as is possible until the breakthrough arrives), which implies some degree of agency that may involve costs. (We might call this type of hope “Hope 1.5.”) In contrast, a person beset by hopelessness has concluded that the joint probability of these events is sufficiently dwarfed by the agency costs of survival, ensuring the unfortunate outcome.
Hope seems to matter (some evidence)
Abhijit Banerjee, Esther Duflo, Raghabendra Chattopadhyay, and Jeremy Shapiro have a (2011) working paper entitled Targeting the Hard-Core Poor: An Impact Assessment. In it they evaluate a program designed to provide development services to people who don’t (for whatever reason) take up microfinance when it is offered to them. The program transferred assets (cow, goat, chickens) worth about $100 to the ultra-poor in Murshidabad, India. The results of the program were huge! 21% increase in earned income. 15% increase in consumption. An hour more work per day. Large psychological health effects. These effects are surprising given the amount of the asset transfer. What could be happening? Why are the benefits of giving an extremely poor person in India $100 WAY more than $100? What is making this return so large? Several things could be happening:
Perhaps the asset freed up a “nutrition based poverty trap”. In such a trap wages are so low that by working all day an you would only make, say, 800 calories, far lower than the necessary 1200, or so, calories needed per day. In this type of situation you will not be able to work or work very little and you will be very unproductive and stay very poor. So perhaps an asset transfer allows you to earn a small return on the asset (i.e. the cow gives milk, the chickens lay eggs etc.) and this pushes you above the necessary 1200 calories per day. Now the return on a $100 asset transfer is magnified by the workings of the labor market that you are now able to take advantage of because you are now able to put in a full day of work. Even if the labor market wages are still very low the return from the ultra-poor asset transfer will be quite large.
This nutrition based poverty trap isn’t what seems to be happening in Murshidabad. If the people were so poor that they didn’t have enough food to eat to work for enough hours every day then by giving an asset (such as a cow), all of the extra consumption should be in the form of food. Because feeding yourself adequately is the most productive thing to do. But in this impact assessment the authors find similar increases in overall consumption (15%) and food consumption (17%). People seem to be increasing expenditures in everything, not just food. Moreover, within food consumption the ultra-poor seem to be substituting for higher priced food that is not necessarily the most calories. For example less grains, more meat. Basically if these people were starving they would have maximized the calories available with their resources.
Another possibility is a so-called “credit trap”. In other words the ultra-poor do not have the ability to gain credit (due to a lack of durable assets to use as collateral, or lack of access to a provider, etc.). This again doesn’t seem to be the case because the program in Murshidabad, India was implemented by a microcredit organization explicitly targeting these people because they couldn’t get them to borrow money. So there was a organization in the area providing credit without a restriction of having collateral.
Still another possibility is mental health or psychological health. The beneficiaries of the program recognized fewer symptoms of depression, fewer symptoms of stress, and feeling much happier. This perhaps (as hypothesized by Duflo) could be the mechanism that leads to the large returns on the $100 asset transfer to the ultra poor. The question is whether there is such thing as a “hopelessness trap” (or as Dalton, Ghosal, and Mani (2013) call an “aspirations failure”). Said differently the expectation of future poverty exacerbates current poverty.
Take for example a seamstress. There is a huge difference between the productivity between sewing by hand and having a sewing machine. Additionally there is a big difference between having a mechanical sewing machine and a manual sewing machine. Additionally, there is a difference between having one mechanical sewing machine and two mechanical sewing machines. And so on and so on. In economist speak, the production function for a seamstress has discrete steps. An investment has a threshold before it becomes profitable. The problem is you can’t buy one tenth of a machine. You have to buy the whole thing. If someone is so poor and “hopeless” that they think they will never be able to cross the critical threshold for profitability, there is little incentive to be as productive and rational as possible. Perhaps you should spend more time buying toys for your child rather than save for a sewing machine if you never think you’ll be able to save enough for a sewing machine.
Hope then is a capability (a la Amartya Sen). Hope is a fuel that makes us capable of achieving things. And it also provides motivation to invest in business, education, health, etc.
So, how do we make people hopeful?
There could be many ways, several that have been recorded in the literature so far include:
- Lori Beaman, Esther Duflo, Rohini Pande, and Petia Topalova have a paper (2012) (published in Science) showing that girls in india have higher aspirations and therefore higher education outcomes when there is a female in a leadership role in their region or area.
- Tanguy Bernard, Stefan Dercon, Kate Orkin, and Alemayehu Seyoum Taffesse have a working paper (2013) revealing that people who were shown a video of similar people succeeding in agriculture or small business were measured as having higher aspirations. Additionally there were secondary effects in improved savings, credit behavior, education investment, and time spent working.
- Paul Glewwe, Phillip Ross, and Bruce Wydick have a working paper (2015) which shows that involvement in Compassion International’s child sponsorship program lead to higher aspirations and self-esteem.
For a long time those working in development have been focusing on external constraints to economic outcomes. We always think of the obvious things like credit, or agricultural inputs, or business skills training, or health, or nutrition, etc. Perhaps it is time to think about the internal constraints to economic outcomes. Things like aspirations, beliefs, or attitudes. All things that make up what we call hope.
(There is also a theological perspective of all this. Undoubtably, there will be more on that later.)