Global Working Paper Series
At the Duke University Center for International and Global Studies (DUCIGS), we are actively engaged in publishing new research. The Duke Global Working Paper Series provides a space for scholars from across the disciplines to explore international topics. DUCIGS welcomes submissions from Duke experts and affiliated scholars.
Papers in this series are published to the Social Science Research Network as part of the Duke Global Working Paper Series. This series is edited by Giovanni Zanalda.
For the style guide and submission form visit: https://duke.qualtrics.com/jfe/form/SV_6zFTllGEGelzUZT
For more information, email Rohini Thakkar (rt54@duke.edu).
India is a lower-middle-income country (LMIC) with 21% of its population living below the international poverty line. Yet, its government health expenditure in 2016 was only 1.17% of its ross domestic product (GDP), a share that is even lower than the average for low-income countries. India also faces a shift in disease burden, with non-communicable diseases (NCDs) emerging as top causes of mortality while infectious diseases and maternal, neonatal, and nutritional health remain areas of concern. To address these challenges and improve healthcare access and affordability for poor and vulnerable populations, India launched Pradhan Mantri Jan Arogya Yojana (PM-JAY) in 2018 as a successor to the Rashtriya Swasthya Bima Yojana (RSBY) scheme. To further inform policy development, we synthesized the early experiences of PM-JAY by conducting a narrative review, focusing on the three dimensions of universal health coverage (UHC): population coverage, service coverage, and financial risk protection.
As more countries move from low- to middle-income status, they are perceived as increasingly capable of financing their own health systems. Some donors have begun to transition their support out of such middle-income countries (MICs) to redirect their funds to countries with greater needs. However, this transition may leave a funding gap for MICs that could be difficult to fill when external resources decline. If not carefully managed, such financial shifts could lead to the loss of health gains that occurred while receiving substantial external financial support. Understanding levels of donor dependency (i.e., whether or not a country is likely to have capacity to fill a funding gap caused by donor transition) and donor concentration (i.e., when only a few donors make up the majority of aid) can illuminate areas of potential vulnerability for transition. In this study, we analyzed Kenya’s health system for donor dependency and donor concentration.
Although the proportion of the world’s population living in poverty has declined substantially over the last two decades, the absolute number of people that live in poverty or vulnerable conditions has remained high. Nearly 70% of the poor now live in countries classified as middle-income.3 We conducted a document review and comparative analysis of six of the largest global health donors to better understand the extent to which they incorporate subnational poverty into their allocation decisions and programming. The donors we studied were Gavi, the Vaccine Alliance (Gavi); the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund); the President’s Emergency Plan for AIDS Relief (PEPFAR); the United States Agency for International Development (USAID)—specifically, its Global Health Bureau; the World Bank’s International Development Association (IDA); and the Government of Japan. We found that most donor high-level strategy documentation allude to the relationship between poverty and health by, for example, noting the financial burden of specific diseases targeted or the disproportionate disease burdens that may fall on the poorest people. However, only two of these donors, Gavi and IDA, incorporate any subnational poverty indicators or broader subnational poverty focus that could be tracked and monitored over time. Gavi and IDA also integrate household level wealth or health expenditure data in their routine monitoring processes, though there is limited information about how much this integration influences how these two donors target aid toward the poorest communities. For the other four donors—Global Fund, PEPFAR, USAID, and Japan—subnational poverty is either not addressed or else is invoked in the context of other social or demographic factors that make certain groups of people vulnerable to disease (e.g., sex workers’ vulnerability to HIV).
Many countries are now transitioning away from donor aid for health as they move from low- to middle-income status and see improved health outcomes. To promote better planning and preparedness for transition, many transition readiness assessment tools (TRAs) have been developed in recent years. The goal of this study was to identify and review existing TRAs to better understand the current landscape of how such tools are being used and the potential gaps among the currently available tools. There are several key limitations among existing tools. There are also many areas of overlap between tools, as well as clear gaps among the current tools available. For example, limited consideration has been given to emerging challenges for transitioning countries, such as demographic and disease transitions (e.g., aging populations and a shift in the burden of disease from infections to non-communicable diseases). Many critical health interventions, including vaccines and maternal and child health services, are ignored by current TRAs. Donors are the financial and technical “drivers” of all the TRAs, and so these tools are not being shaped by transitioning countries themselves. Therefore, it is difficult to determine whether or not the TRAs as designed will address the most critical needs of transitioning countries. Additionally, the role that in-country stakeholders are expected to play in the assessment process is not clearly defined and the methodologies of TRAs are not publicly available, thereby potentially limiting their usefulness to users.
This paper provides a summary survey of the policy approaches to artificial intelligence-based technologies in China, the European Union, and the United States. China has the most aggressive approach, launching major initiatives since 2015 such as ‘Made in China 2025’, the Internet Plus Plan, the New Generation Artificial Intelligence Development Plan, and the Artificial Intelligence Standardization White Paper. In 2018, the EU finalized both the European AI Strategy and ‘Made in Europe’ or the Coordinated Plan on the Development and Use of Artificial Intelligence. Despite a traditional reticence to adopt national strategies and perhaps pushed by growing concerns about China, the US Government announced the American AI Initiative and a National AI R&D Strategic Plan in 2019. The AI approaches in these three economies reflect their relative strengths—state control in China, citizen voice in Europe, and business practices in America. Unencumbered by privacy concerns, China’s strategy is geared to exploit the abundance of domestic data and to develop AI talent through central schemes and massive injections of money. The European Union’s regulations and spending priorities are guided by the objective of building citizen trust in AI-based technologies by safeguarding privacy and ameliorating disruptions in national labor markets. The mainstay of the US approach is to strengthen the linkages between business and AI-related research, and find ways to fund basic R&D. Despite efforts to indigenize AI innovations, all three economies face challenges. China’s AI strategy continues to rely disproportionately on just three tech giants: Baidu, Tencent and Alibaba, which have investments in more than a 100 AI-involved companies. Europe’s AI resources are unbalanced geographically—a quarter of Europe’s AI talent is in the UK and another quarter in Germany and France—and Brexit poses a serious risk. More than half of the AI talent in the US is foreign born, so immigration policies will inevitably be a central component of a national AI strategy.
First, this paper discusses how AI-based technologies that are powering the “Fourth Industrial Revolution” are similar in their speed, effects and prerequisites to general purpose technologies (GPTs) that came before and how they are different. AI-based technologies are similar to the steam engine, electric power, and information technology in that (a) they change the nature of work but do not reduce it in aggregate; (b) they increase productivity when accompanied by innovations in business process and investment in human capital; and (c) they leave little room for leapfrogging because profitable adoption of new techniques requires having adapted to previous rounds. AI is different from earlier GPTs mainly in that the speed of its spread is likely to be faster. Second, it provides an economic classification of these technologies based on the channels through which they reduce costs, distinguishing between transactional, informational, and operational technologies. This distinction is relevant because they differ in their structural, social and spatial effects. Third, the paper provides a framework that brings together the economic consequences of AI-based technologies and common policy goals: competitiveness, cohesion and convergence. Finally, it illustrates how this framework can be applied to the European Union. EU member states do least well in transactional platforms where scale matters a lot, they do somewhat better in informational technologies where both market size and regulations matter, and some of them are global leaders in the development and use of AI-based operational technologies such as robots. As with earlier waves of technical change, creation and adoption of AI-based technologies will require good education and well-designed R&D incentives, regulatory capacity, and robust tax-and-transfer systems.
African utilities face the complex and interrelated challenges of being capital constrained, having a relatively low demand base of customers with lower abilities to pay, high levels of system inefficiency, and very large unserved and underserved populations in their service territory. Traditional business-as-usual methods for electrification have fallen short, and utilities in sub-Saharan Africa are critically under-equipped for the universal access challenge. Advances in digitized and decentralized technology offer new delivery models for reliable and affordable access that African utilities could leverage to solve these dual challenges of financial sustainability and universal access. Indeed, though the 'future grid' conversation predominantly focuses on advanced energy markets, the value proposition of such advances is arguably stronger in African markets. From the literature, we find that the inertia of the entrenched regulatory frameworks governing competition, tariffs, and investment priorities are a major hurdle keeping African utility incentives at odds with technology trends and propose reforms. Using case studies, we identify key regulatory reforms needed to transform the sector, and best practice models for novel public-private sector engagement to unlock opportunity.
There have been significant improvements in recent years in the early stage development of products for poverty-related and neglected diseases (PRNDs). However, there are still major challenges in the funding of late-stage clinical trials of candidate products for these diseases. For vaccine development specifically, Rappuoli and colleagues recently concluded that “these improvements in the early development process have revealed a new, and possibly more perilous, Valley of Death in the late vaccine development phase.” There are three major challenges in conducting phase III trials for PRND product development. First, such trials are expensive and companies often shy away from investing in them because there is no commercial market for most PRNDs. Second, there is poor coordination on late-stage trials across R&D initiatives. At present, there is no overarching global mechanism that is “steering the ship”—there is no universally agreed upon process for prioritizing R&D investments for PRNDs, for selecting the most promising candidates, or for coordinating the multiple, overlapping research programs worldwide. The result is duplication, waste, and ultimately delays in the development of products. Third, current R&D efforts for PRNDs are “top-down”—they are controlled by high-income countries (HICs) and have generally done poorly at including decision-makers from high-burden countries. It is policymakers in low- and middle-income countries (LMICs) who are in the trenches when it comes to controlling PRNDs—yet they are often not at the table when it comes to deciding on what gets funded, where research is conducted, who gets access to intellectual property, and where and how the technologies end up being manufactured. All these steps need to be “globalized” if we are to develop and deploy new control tools.
This paper based on Ambassador W. Robert Pearson’s inaugural lecture of the DUCIGS/Rethinking Diplomacy Program at Duke University focuses on how the combination of the disciplines of diplomacy and science plays an important role in facilitating the solution of complex issues. The author introduces a “collaboration model” for modern problem solving of complex problems, including those where good science is a key factor, with many stakeholders. In this model, diplomacy can act as the “facilitator” or the “mediator” to manage that process. In order to succeed with a “collaboration model,” five elements are required: (1) involvement of all the essential stakeholders (those that could make or break an agreement), (2) consensus definition of the problem, (3) sufficient common interests to generate a productive dialogue, (4) a shared commitment by the stakeholders to finding a solution, and (5) successful post-agreement implementation that stands the test of time. Examples of successful stories include the international Ozone Agreement and the agreement on the UN Sustainable Development Goals. The author concludes that in today’s world all science is also politics. Knowing what is needed to solve a problem is not enough. Knowing how to persuade the broader public, businesses and governments to do what is needed requires knowing the best way to make that happen. The best way to help make that happen is to use the best tools of diplomacy. Science and diplomacy thus become indispensable partners for human progress.
Many donors are reconsidering their approach to providing health aid to countries that are viewed as becoming increasingly capable of self-financing their own development. To better understand this phenomenon, we analyzed the transition approaches adopted by six key global health donors, three multilateral and three bilateral, who provided nearly 75% of all disbursed official development assistance for health in 2016. We conducted a desk-based review and triangulated our findings with semi-structured key informant interviews.
We found: 1) there is no consensus on the terminology used to describe the transition process;
2) donors vary in terms of the formality of their policies, the indicators used to allocate resources and/or trigger transition, and the timeline/duration of transition; 3) some donors view the unit of transition at the sector or program level rather than the country level; and 4) donors provide varying degrees of support before, during, and after transition.
Our findings suggest that more explicit transition approaches and greater definitional clarity are needed. Donors should avoid a “one size fits all” approach—a lack of flexibility puts countries at risk. Evidence should be generated and shared on which transition modalities work best and under which circumstances. Donors should communicate with each other and avoid transitioning at the same time. As more low-income countries transition to middle-income status, transitions away from donor support for health will become an increasingly important phenomenon to understand.