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'It has never been more possible'

2020-10-09

Over a period of two years, the Ceres2030 team spent researching answers to the questions of how much it will how much it will cost to realize SDG 2 and where that money should be spent most effectively. IISD Senior Advisor and Ceres2030 Co-director Carin Smaller about small farmers, machine learning and women empowerment.

What is the starting point of “Ceres2030”?

Five years ago the world came together and agreed to these global goals. And one of them was the most important one: to end hunger. But people have tried to solve this problem for decades now. The interesting about “goal 2” is that it wants to end hunger with a strong focus on small farmers and small producers in the poorest countries – and trying to end hunger in ways that are consistent with our climate commitments and with our environmental goals.

And what is the significance of the study?

When this goal was launched as part of the Agenda 2030, there was a realisation that there is not enough evidence about how we could actually improve the incomes and the productivity of the farmers in these poor countries, mostly in Africa, nor how to do it in a way that would promote sustainable agriculture and resilient food systems. The question was: Do we have answers, what is the best way to improve farmers’ incomes doing it in an environmentally sustainably way – and what it is going to cost?

Who asked?

The BMZ and the Bill and Melinda Gates foundation came to us and said: We want you to use the highest standards in research and economic modelling to provide answers to these questions.

It is really important for policy makers to be able to make decisions with the evidence they have. They need to know where to direct their public spending.

Why are the costs being asked specifically?

It is really important for policy makers to be able to make decisions with the evidence they have. They need to know where to direct their public spending. And that is as much important for donors as for the countries themselves. It is no good just knowing what needs to be done if you don’t know the scale of the budget you need to achieve the goal. So, the cost is there to help say: This is what needs to be done and this is what we can confidently say to scale the resources in order to achieve it.

You said, the study focuses on increasing the income and productivity of small farmers - why?

Because, paradoxically, these are the people who are most likely to experience hunger. They are the people who are most often left out of economic growth and least likely to benefit from technological change. And they are the people who are most often left out of political decision making. This represents one of the largest and most vulnerable groups and those who are struggling at most. Importantly, they are also the group that is most vulnerable to climate change.

More and more people are suffering from hunger. Is the goal of "Zero Hunger 2030" becoming increasingly distant?

Absolutely not. This is so achievable and so within reach – it has never been more possible. If you look what is happening in the world today, you see governments spending unprecedented amounts of money in response to Covid-19 – the cost of achieving the end of hunger is going to be a fraction of what it is costing now in response to the pandemic. We were surprised how achievable this goal really is. It is not going to require a huge and impossible effort. It is really doable.

Conflicts contribute to hunger, too. Climate change is taking place heavily. How do you cope with that?

There have been always conflicts, and they will always be a source of increasing hunger. This is the reality and we know from the last few years that a big chunk of the rise in hunger has been in conflict areas. But you still have dozens of countries who are conflict free and who have unacceptable levels of hunger. This is where we really have to make progress. That does not mean that we are not interested in the people who live in conflict areas, but there is a particular pattern of investment you need when you see that hunger levels rise because of a conflict. It is often an access issue, like other people in these areas preventing people from getting food or using hunger as a tool. You need totally different forms of spending to access.

In the study, you write down everything that still needs to be done. Can you express in percent how much has already been done?

There has been a huge amount of attention and investment in solving this problem – but it has not been enough. The additional efforts that are needed, are totally within the scope of our political leaders and it is not wild and crazy what we are putting forward.

You use modeling as a method - what are the advantages?

People want to know how much it is going to cost them so solve problems – like ending hunger. Especially when you are speaking to governments, whether to donors or in the countries with high levels of hunger. What the model helps us to do is to assess: Okay, here are your targets, you want, by example, to double income of your farmers – how much does it cost and what is the most effective way doing it? The model at the most basic level will generate the sense of the resources you need. And because it uses existing data sources, we know what has been spent on this issue in the past, let us say how much it takes to spend money on research and development of a new crop variety. So we know what it costs, put these parameters in the model and we can tell you how many crop varieties you need to spend money on. Our model tries to spend money in the most cost effective way and in the most optimal way. We are not just going to ask 20 countries, all of them in the same region, to increase production of wheat and more food for people. We are going to make sure that the investments are smart, that it fits for everyone and that it increases income and that it does not create these unattended consequences where actually no one is better off.

What does the model have in mind?

Our model has interactions that occur between all levels of an economy, across different sectors of the economy and between countries. So we can be sure that you are not going to be asking Uganda, Tanzania and Zambia and Malawi to all increase production in the same crop. There will be a complementary strategy that the producers in the countries all can make money, can all improve their productivity but do it in a way where there is actually a market demand. This particular type of model that we use is a general equilibrium model that allows us to see the interactions. Everything interacts with each other – and the costs are much more cost effective and optimal.

And what does the model not do?

It is not giving you the roadmap to ending hunger. That work still has to be done at the country level with the countries’ stakeholders, civil society, farmers, private sector; all we can give you is a scale of the resources that is going to be required and the types of things that the money should be spent on. But the detail, i.e. what, how much and where has to happen on the country level.

Are there any scales that are not covered by machine learning?

The machine learning that we use in Ceres does not calculate costs. The machine scans all the literature that has been written on the subject. That is the beauty of the machine! It says: Okay, we look at 60 databases, we look at all articles that have been written about small scale producers and environmental issues around agriculture, and we will figure out which one is the most relevant and then we give our research teams the most relevant ones. We will all be quite overwhelmed by how much has been written in the past 20 years.

How much?

There has been hundreds and thousands of articles written that our machine was able to find in these 60 databases.

How much time would it take without a machine to absorb this literature?

Six, seven years. At least three times of the time that took us.

Despite 20 years of discourse around the need to promote gender equality, there is actually very little attention which is being paid to solve this problem.

How important is it to empower women?

This is probably one of the biggest lessons that is going to come from this study. Despite 20 years of discourse around the need to promote gender equality and women’s empowerment, there is actually very little attention which is being paid to solve this problem in the literature. We all know it is crucial. We are not the ones who put it on the map because it is already known, but it is worrying that despite all the talk about the importance of it how little attention it has been given in the research community.

What is the role of fertilizers and synthetic pesticides – and what about the meaning of ecological agriculture?

We don’t put forward the one and only model of agriculture that you need to promote. Our study was to look at the evidence saying about what works and how much it is going to cost. We don’t have a preference. But you will see, when the findings will come out, that a lot of people looked at ecological methods of farming and the model even includes an intervention around agroforestry to help improve livestock productivity.

Do you expect resistance to the findings of the study?

Resistance is maybe not the word I would use, but I want to encourage a very critical look at our findings and a debate on it.

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(c) Christof Krackhardt/Brot für die Welt

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Not waiting for a savior

By Lidet Tadesse

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Support for sustainable start-ups

Companies in Africa that need financing between $20,000 and $200,000 find relatively few investors, as this sector is too large for microcredit and too small for institutional investors. This creates a "gap in the middle" where companies have limited options. A project of the World Resource Institute provides a remedy with the Landaccelerator 2020.

A World Resources Institute project

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'It has never been more possible'

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By Michael Brüntrup und Daniel Tsegai

By Brot für die Welt

By Claudia Voß

Interview with Jacob Schewe

By Maria Smentek

By Marwa Shumo

By Stig Tanzmann

By Paul van Zwieten

Event report by Jan Rübel (Zeitenspiegel)

A study by Markus Hanisch, Agustina Malvido, Johanna Hansmann, Alexander Mewes, Moritz Reigl, Nicole Paganini (SLE)

A report by INEF and Kindernothilfe

By Anna Sophia Rainer

By Jan Rübel