Can policy simulations help developing economies after COVID-19?
4 June 2020
More than 80 developing and middle-income countries have requested financial help from the International Monetary Fund (IMF) in recent months to cope with the economic pressure from the COVID-19 epidemic and imminent global recession. Radical actions such as an urgent moratorium on sovereign debt payments, and elimination of current bilateral-tariffs and non-tariff barriers are being discussed by the Group of 20 major economies.
This is not the first time world leaders gather to discuss debt. In the 1990s, the African continent was plagued by debt that weighed on public budgets. But as previous experience shows, it’s one thing to propose debt relief and another to make it work.
In a recent article commenting on debt relief and forgiveness proposals, Romuald Wadagni, Benin’s Minister of Finance, recalled the experience of the Heavily Indebted Poor Countries (HIPC) Initiative and the Multilateral Debt Relief Initiative (MDRI) in the late 1990s.
Since the domestic policies and institutional capacity of the HIPC were not changed fundamentally, he argued, in the long run, mismanagement of the MDRI initiative left beneficiary countries unattractive to the global finance market and dependent on limited funding options, where debt repayment comes ahead of any public welfare spending. To make debt relief and forgiveness programmes successful, beneficiary countries need to improve their policymaking and day-to-day policy implementation capacities.
Policymaking in uncertain times
In the wake of COVID-19, countries are responding to rapid and radical policy challenges in unprecedented ways.
Policymakers know that making good, fast decisions is challenging under the best of circumstances. These challenges are greatest where conditions are unfamiliar, uncertain and uncontrollable. So, when policymakers were hit by the unfamiliar COVID-19 virus which quickly turned into a pandemic, even in the most sophisticated parts of the world governments were faced with paralysing uncertainty and irrefutable evidence that the existing socio-economic and political systems were at risk of breaking down.
Looking at the rapidly growing unemployment rate in the US, the rapid decline in GDP growth rates in Europe and dwindling forecasts for businesses, governments need to make unprecedented decisions, such as a month-long lockdown of the economy to save lives and protect public health systems.
Simply taking a decision in these uncertain times requires courage from policy leaders, who have to make do with inadequate data and circumstances that are, to some degree, outside their control. That’s bound to cause hardships.
India announced a national lockdown with only four hours of notice, and South African police and soldiers were authorised to use rubber bullets to enforce lockdown in Johannesburg. Developing countries are rushing to launch contact tracing applications.
While on the one hand, experts are raising questions about the sophistication of the public sector to not abuse their power and governments’ ability to manage these radical approaches without creating unintended economic or political damage, on the other hand, it is clear that there is a real need for the public sector to step up and lead us through this crisis.
The wave of the COVID-19 pandemic just started to peak in developing countries.
In the post-COVID-19 world, the quality of the public sector will be challenged and tested. The 80 countries requesting financial help especially will be under growing pressure to deliver better results with less: meeting societal and business needs; adapting service provisions to changing demographic, technological and societal conditions; and promoting equitable resilience to all aspects of sustainable development. Governments need to boost their own confidence and ownership to design good policies independently, as Wadagni highlighted in his argument to the multilateral agencies.
Policy simulation for the post-COVID-19 world
During normal times, policymakers could wait for more information before making a decision. Such policies, often termed “evidence based policies” could be challenging to formulate in the post-COVID-19 economy due to unclear, uncertain, and unfamiliar data. In order to overcome data scarcity, developing countries typically tend to apply two approaches: policy learning and policy diffusion.
Policy learning involves policymakers who, over a long period of time, are able to produce a new policy by learning from past experience and by compiling evidence and including new information. Policy diffusion is often led by external experts (e.g., consultants) who scan the horizon for comparative case studies, identify best practices, and help translate and adapt the practice to another country.
In the post-COVID world, policy learning and policy diffusion will both be more difficult. A crisis of this scale will wipe out many successes and gains made by many countries, rendering historical data less useful. Many governments and businesses are changing their operational practices significantly. Theories on capitalism and globalisation are being flipped on their heads.
Due to COVID-19 as well as the oil price drop, developing countries are facing a disproportionate impact. Through permanent job loss, loss of remittances, rising prices, and disruptions in public welfare services such as education and health care, it is estimated by the World Bank that an additional 40-60 million people will fall into extreme poverty (under $1.90/day) in 2020, compared to 2019.
New research further estimates that the ongoing crisis and emerging global recession is erasing almost all the progress made in the last five years and that the 2030 global sustainable development goals (SDGs) will now be very difficult to meet.
Instead, policymakers need to intensify their capacities to engage in resilience thinking. Resilience thinking is a trainable skill where people within an organisation transform, optimise the use of available resources, and enhance existing capacity to survive in the face of unpredictable adversity or crisis. To improve resilience thinking, we need to start talking about how to build the capacity of the policymakers in the public sector who are responsible for developing effective policies and administering them on a day-to-day basis.
Effective policies are action-oriented; they provide clear guidelines and enough detail to direct behaviour toward specific goals or objectives but are not so detailed that they discourage personnel from following the policy or creatively adapting the policy to fit nuanced conditions. As we know, policies that may be timely and correct but aren’t properly enforced or enforceable by management often lead to poor policy outcomes and loss of trust in the governance system.
One approach to improving resilience thinking capabilities in a very short period of time is to invest in developing “Policy Simulation Labs” (PSL) to enable policymakers to simulate policy outcomes before drafting actual policies to implement. Especially in the post-pandemic world, simulations can offer decision-makers access to events that can otherwise not be directly observed, and in a safe and controlled environment. Clinical simulation labs are very familiar tools in healthcare systems, where simulation labs are used for the study of how to improve the quality and safety of healthcare.
Using policy simulations to solve wicked problems
At the Resilience and Sustainable Development Programme (RSDP), inspired by the success of clinical approaches to simulating experience and reaction for medical professionals, we are developing policy simulation-based research.
In 2019 we developed the first national Policy Simulation Lab in Bangladesh to help developing countries' public, private and civil society leaders improve their resilience thinking capacity. Foreign Minister Dr AK Abdul Momen, reflecting on the outcome of the four day PSL, stated that “if we could connect our mainframe administrative and productive platforms to a certain measure of design innovation — Bangladesh will pass through the eye of the needle successfully.”
So, what is a policy simulation lab? A PSL is a medium through which a simulation scenario is delivered to participants. A PSL is different from a policy innovation lab (PIL), although in both cases, the objective is to develop better public policies. While a PIL focuses on the design of the policy to make it more human-centred, a PSL aims to improve the implementation steps of a policy to ensure the policy impacts are positive and outcomes are sustainable. A recent study on PIL found that that policy innovation itself is a dynamic space; new labs are emerging and disappearing all the time, partly because of lack of funding, institutional demand and misunderstanding of the value of design thinking.
A PSL is the newest addition, which combines complex systems design methods with social science theories to offer “lifelike experience” to policymakers to simulate how their policies would address a particular challenge. Similar to the clinical simulation labs, in PSLs, the participants are drawn from the stakeholder network, which includes beneficiaries (like patients in clinical case). Participants’ reactions and behaviours, which are part of their critical thinking capacity and leadership capability, are as close as possible to what they would experience and do in a real situation, so their perceptions of events, timing, environment and cues are all in sync with their personal and organisational models of operation.
In order to get a sense of what simulation labs are like and are able to do, Netflix's docuseries "Pandemic: How to Prevent an Outbreak" documentary is illustrative. It sets out how clinical simulation labs are preparing the New York City public health systems while training medical professionals in response to COVID-19. The labs are part of the government's plan for accelerating the preparedness for the uncertainty and uncontrollability of the pandemic.
Similarly, PSLs offer “just-in-time-training” opportunities by helping to diagnose problems, test new approaches before they are deployed for real by registering stakeholders' reactions and establishing a knowledge-sharing platform by co-creating solutions. In the future, a PSL would not only leverage human processors (catalyse engagement with stakeholders) but also apply frontier technology such as artificial intelligence and big data capacity to map systems and find analogies. Building analogy and mapping systems can lead to unexpected, counter-intuitive results and identify so-called wicked problems.
Urgent investment needed
If developing countries' governments can put their will and resources into implementing digital tracking systems to confront the COVID-19 crisis in a matter of weeks, there should be no doubt that developing countries can attain resilience and continue on the sustainable development track. These countries need to prioritise their public sector officers' capacity building to ensure policy implementations are aligned with the policy objectives. Now of course, funding is an issue. And such funds need to be sustainable in the long term.
Concurrently, given the prominence of the government in the post-COVID-19 world, the global investment community can deploy instruments such as social impact bonds (SIB) to focus on capacity building amongst public sector officers in developing countries. SIBs would finance the delivery of skills training and policy support to public sector officers from central to local level who will need to work at scale, innovate policies at speed and implement solutions at cost. In addition to debt relief or debt restructuring, multilateral agencies can help create policy simulators in the governments to improve overall the resilience thinking capacity of the decision-makers, representing public, private and civil society organisations responsible for cooperating to build a better future.
There is too little time to spend it collecting evidence, or to wait for best practices from elsewhere. Every developing country's government should have a policy simulation lab, where there will be a new post for “policy simulators” who are able to run simulations on various policy challenges, just as they have posts for accountants and macroeconomic forecasters.