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News Article | November 17, 2016
Site: www.eurekalert.org

Health and financial literacy played important part in determining who bought coverage on ACA exchanges Uninsured individuals who had greater knowledge about health insurance and financial issues were more likely to gain coverage after health insurance exchanges opened under the federal Affordable Care Act, according to a new RAND Corporation study. For a typical person who was uninsured in 2013, the chance of being insured in 2015 was 9.2 percentage points higher if they had high health insurance literacy as compared to someone with low health insurance literacy, after adjusting for other factors. The effects of high health insurance and financial literacy were significantly linked to obtaining coverage even after researchers considered other factors, such as a person's income level, employment and political affiliation. Researchers say the findings have implications for improving insurance uptake in insurance markets, suggesting it is important to improve the public's health insurance literacy, as well as to design health plans and supporting materials that can be easily understood. "Limited health insurance and financial literacy may make it difficult for consumers to assess whether insurance premiums are 'worth it'," said Katherine Carman, senior author of the study and an economist at RAND, a nonprofit research organization. "Efforts to decrease the number of uninsured adults should consider that these individuals may have a hard time deciphering health insurance information." The findings are published online by the journal Medical Care. The study is based on surveys conducted with 2,742 adults aged 18 to 64 who participate in the RAND American Life Panel, a nationally representative internet-based survey panel. Participants' health insurance and financial literacy was assessed by brief questionnaires commonly used to test financial literacy. Researchers also assessed participants' health insurance status in the fall of 2013 (before health insurance exchanges created under the ACA opened) and again in the spring of 2015. Overall, about 60 percent of study participants who were initially uninsured gained health insurance by spring of 2015. Among people with high health insurance literacy who were uninsured in 2013, 64 percent had obtained coverage by 2015, compared with 48 percent among those with low health insurance literacy, before adjusting for other factors. Among people with high financial literacy who were uninsured in 2013, 70 percent had obtained coverage by 2015, compared to 56 percent among those with low financial literacy. "It is remarkable that the association between financial literacy and people's insurance decisions is similar in size to things we normally associate as being a key to someone having health insurance, such as education levels and whether someone is employed," Carman said. Researchers say that findings demonstrate that policies and programs intended to further reduce the numbers of uninsured -- especially through Medicaid and the ACA marketplaces -- should take into account the financial literacy and health insurance knowledge of the groups they are trying to reach. "Because the ACA relies on consumer choice, those who are uninsured and have low health insurance literacy represent a particularly vulnerable population because obtaining coverage may be especially difficult for them," Carman said. Support for the study was provided by the National Institute on Aging and the Bing Center for Health Economics at RAND. Other authors of the study are Maximiliane Hoerl, Amelia Wuppermann and Joachim K. Winter of the University of Munich, Silvia H. Barcellos of the University of Southern California, and Sebastian Bauhoff of the Center for Global Development. RAND Health is the nation's largest independent health policy research program, with a broad research portfolio that focuses on health care costs, quality and public health preparedness, among other topics.


News Article | October 5, 2016
Site: www.nature.com

Ask Matthew Hansen to show off his data and he hunches over his computer like a possessed video gamer. With a few mouse clicks, he flies over the globe and zooms in on a forest in Indonesia. The area is designated as a preserve — supposedly protected from deforestation — but Hansen's data reveal a different reality. Bird's-eye images of the trees taken every eight days flash by on the screen. At first, a few red spots perforate the green canopy around the preserve's edge. Then they spread, like bloodstains. “That's got to be illegal fires,” he says. “The forest is getting chewed up.” Hansen is among the world's foremost forest sentries. In 2013, he and his colleagues used satellite data to produce the first global, high-resolution maps of where trees are growing and disappearing1. Those images revealed some large-scale patterns for the first time, such as that Indonesia had nearly equalled Brazil as the country with the world's highest rate of tropical deforestation. Since then, his team has refined its methods and can now reveal the loss of trees within days. Just as important is what Hansen does with the underlying data. Unlike some scientists, he makes them freely available online, giving activists, companies and others the ability to monitor activities such as illegal logging and mining, which have destroyed millions of hectares of forest per year over the past few decades. The data have enabled non-governmental organizations (NGOs) and officials in Peru, Congo and other nations to see deforestation as it happens. And they let countries monitor each other's trees — potentially a crucial step in enforcing the international climate agreement signed in Paris last December. But some have argued that the maps do not always work as advertised. For instance, they lump together destruction of natural forests and the harvesting of managed ones, which critics say leads to inflated estimates of deforestation. And others question whether satellites can monitor forest loss and growth accurately enough to determine how well countries are complying with their commitments on climate change and deforestation, including the Paris deal. One thing no one disputes is that Hansen is showing the world how mapping from the sky can have an impact on the ground. “If you want to know what's up, you look at what Matt's doing,” says Martin Herold, a remote-sensing expert at Wageningen University in the Netherlands. “Nobody's even close.” Hansen instantly disarms people with his down-to-earth nature. On an unseasonably warm day earlier this year, he was wearing shorts and a short-sleeved shirt when his assistant reminded him that he was due at a meeting. “I'm not dressed for that at all,” he laughed as he set off across the campus of the University of Maryland in College Park. His informality helps when working with both African farmers and Hollywood actors, with whom he mingles as easily as with other scientists and policy wonks. But beneath the casual exterior is an intensity that has made Hansen one of the world's most sought-after experts on forests. Growing up in Indiana surrounded by farm fields, Hansen did not spend a lot of time among trees. But he was struck by trips to the state's few remaining patches of original hardwood forest, which reminded him of Lothlórien, the sylvan kingdom of the elves in The Lord of the Rings. He studied electrical engineering at university and then was accepted into law school, but neither stoked his passion. What did excite him was adventure, and he got plenty of it when he headed to what was then Zaire (now the Democratic Republic of the Congo) to volunteer with the Peace Corps. But when he returned, he still had no clear career direction. “I came back and I thought, what do I like? I like maps,” he says. So he went to the University of North Carolina in Charlotte for master's degrees in geography and civil engineering. He took a job at the University of Maryland in 1994 and has been mapping land-cover change using satellite data ever since, picking up a PhD in 2002. Hansen has pursued a single goal: to map global land cover with the highest possible resolution using cheap or free data, to better visualize the human footprint on the planet. He has specialized in writing programs to identify diverse types of vegetation — from boreal conifers to palm plantations — using the handful of light frequencies that satellite sensors collect. “He's an exceptionally good geographer,” says long-time colleague Thomas Loveland of the US Geological Survey in Sioux Falls, South Dakota. “He really has an understanding of what this planet's made of.” Hansen and his colleagues also meticulously 'ground-truth' their maps by picking random samples of GPS points and getting to them by any means necessary. “It's his favourite type of vacation, to throw random points on ground and go visit them,” says his postdoc Alexandra Tyukavina. In the mid-1990s, when Hansen was starting, the best information about tree cover came from country-level ground-based assessments, in which crews measured individual trees in representative plots and then extrapolated across large regions. Such measurements were — and still are — used alongside remote-sensing data by the Food and Agriculture Organization of the United Nations (FAO) in its periodic global forest assessments. But many countries lack the resources to conduct regular surveys, and others publish statistics that seem unreliable. So Hansen set his sights on producing what he calls a “globally consistent, locally relevant product” from data available to everyone in the world. But first he had to wait for technology — sensors in space and computer processing power on the ground — to catch up. The first global land-cover map from the University of Maryland came out2 in 1994, using data from the Advanced Very High Resolution Radiometer (one of a series of orbiting imagers operated by the US National Oceanic and Atmospheric Administration). It had enormous pixels of one degree latitude by one degree longitude, much too coarse to make out details of forests. A big step forward came when NASA launched its two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, which gather data at a resolution of up to 250 metres. In 2008, Hansen and his colleagues produced a map3 that started to reveal large-scale trends in the tropics, such as that nearly half of widespread humid tropical-forest loss between 2000 and 2005 occurred in Brazil. Around that time, scientists working for both the Brazilian government and local NGOs used MODIS and other data sources to develop their own maps and issue alerts when large clearings appeared. This helped officials to use financial pressure, law enforcement and other means to dramatically reduce deforestation in the Amazon, the world's largest and most carbon-rich tropical-forest region. That success inspired Hansen. But in many other tropical countries, rising consumer demand for commodities such as cattle, soya beans and palm oil has created powerful incentives to clear tropical forests. And in poorer countries, where heavy tree-felling equipment is rare and clearings tend to be small, MODIS's blocky images have proved less useful. Hansen knew that he needed to make his maps sharp enough to show roads snaking their way into previously untouched forests — an almost universal harbinger of larger clear-cutting. “We had to push the spatial resolution because we're interested in humans,” he says. In fact, the data that he needed already existed. Since 1972, Landsat satellites had been collecting images of Earth's surface, starting at a resolution of 80 by 80 metres per pixel and improving to 30 metres in 1982 — roughly the size of two basketball courts side-by-side. But those images had to be bought individually, at costs from hundreds to thousands of dollars each — much too expensive for a global study. That changed in 2008, when the US government made all Landsat images free, including 3.6 million archived ones. Hansen immediately began making 30-metre-resolution maps showing how tree cover was changing in regions of interest, such as Indonesia and parts of Russia. But making a global map still required processing power out of reach of any university computer cluster. A solution appeared when Hansen met Google engineer Rebecca Moore at a conference in Brazil. Moore was looking for scientists to try out her Earth Engine, a platform to analyse remote-sensing data using Google's cloud-computing capabilities. Hansen and Moore's teams processed the Landsat archive back to 2000 and translated it into annually updated maps that anybody with a computer and an Internet connection could view. “Matt was the first scientist who really leapt onto the platform with a global-scale analysis,” Moore says. In 2013, Hansen, Moore, Loveland and others published1 their results in Science, showing where trees had appeared or disappeared every year from 2000 to 2012. The maps lit up the research community, which for the first time could see the world's forests shift in one consistent picture (see 'Better eyesight in space'). The fact that Hansen put his raw data on the web for others to scrutinize and use has also drawn admiration. But it didn't take long for the critics to chime in. Many have objected to Hansen's use of 'forest', which he defines to include oil-palm plantations and agroforestry, categories not included in FAO data sets. That made his deforestation estimates higher than many previous ones, such as the FAO's. The widespread publicity has further stoked concerns that non-experts are ill-equipped to interpret the data. “I personally think the data set was in some sense oversold,” says Herold. Hansen's visibility added to the scientific scrutiny. On the day that his Science paper was published, for example, he was in California showing his maps to actor Harrison Ford in a scene filmed for the 2014 US television series 'Years of Living Dangerously'. Ford later confronted Indonesia's forestry minister with some of the findings. Other concerns have emerged. Some drier forests, such as those in parts of Africa and South America, have relatively sparse tree cover and might never reach the threshold that Hansen uses to define forest, which is that 30% of a pixel is occupied by vegetation at least 5 metres tall. So when those areas are cleared, the change might not register as forest loss, says Peter Holmgren, director of the Center for International Forestry Research in Bogor, Indonesia. Satellites struggle even more to capture forest gain, he adds, because the signal from growing trees is subtler than that of trees falling. For these and other reasons, he has warned against using Hansen's data to assess progress towards international climate and deforestation commitments, arguing that nations should instead invest in on-the-ground monitoring systems. Hansen acknowledges that his maps do not supply everything. “You can't fit everybody's needs,” he says. But his team is working to add data and make improvements that will show what activities are causing forests to change, and will differentiate plantations from natural forests. “That's what we have to do next, to make it more valuable.” Some of the objections have been more political. Hansen's map was particularly embarrassing for Indonesia because it came out during the 2013 UN climate talks, and revealed that deforestation rates in the country had spiked after a 2011 moratorium on new logging permits was announced. Indonesia's forestry ministry countered that Hansen and his colleagues were including large areas that the government had designated as plantation, unfairly overstating the deforestation. Hansen's group responded the following year with a more sophisticated analysis4, which confirmed that, in 2012, more primary tropical forest had fallen in Indonesia than in any other country. For Hansen, the country's refusal to come clean about its forests is frustrating. But increasing transparency will take time, says Belinda Margono, a scientist with the Indonesian Ministry of Forestry who earned her PhD with Hansen and led the follow-up study by his group. She says that the maps have already helped to set that shift in motion, by promoting a culture of data sharing and openness, and by creating pressure to respond. “Sometimes the government has more courage to release the data after they see what's reported by the global system.” Larger forces are also at work. Nations and corporations are under increasing pressure to show that they are conserving forest to meet commitments under the Paris agreement or in sustainability-certification programmes for products such as palm oil. Since his 2013 paper, Hansen has become a globe-trotting door-to-door salesman of sorts, hawking his maps to forest ministers, corporate accountability officers, NGOs and others who need to keep an eye on forests. As almost 200 nations were hammering out the climate deal in Paris last December, Hansen was nearby, receiving a glowing introduction before he spoke at an environmental conference. “Matt and his team ushered in really a new era of measuring deforestation,” said Frances Seymour, a forest-policy researcher at the Center for Global Development in Washington DC. “He's now immortalized because everybody talks about the Matt Hansen data on tree-cover change.” Hansen is now working to push his technique even further. Inspired by Brazil's alerts, he has begun processing and displaying data on tree loss as it happens in Peru, Congo, parts of Indonesia and Brazil. In the few months since the alerts went public, Peruvian environmental ministry personnel have used them to expose and shut down an illegal gold-mining operation. The alerts' very existence can have an impact, says remote-sensing scientist Fred Stolle of the World Resources Institute in Washington DC, which is releasing them weekly on its Global Forest Watch online platform. “People know now that they can be seen from space.” Hansen hopes to expand his alerts to the whole tropics by the end of the year, and later to cover the globe. The European Space Agency's Sentinel-2 satellites, which will collect data starting next year with a resolution of up to 10 metres, will enable him to update even more frequently. Between the travel and the research, Hansen keeps a hectic schedule. But on a rare quiet afternoon, he can explore the world's forests from his desk on the edge of the Maryland campus. As he pans over Peru, a sea of green gives way to a rectangular island of pink that has grown during the past two years. “Someone went out there and clear-cut that,” he says. The view that Hansen has opened up, of trees falling all over the world, does not always reflect the best in people. “It's fucking alarming,” he says. “The human footprint is amazing. We are a rapacious species.” But making that view available to everyone, he says, could help to rein our species in. “I hope it will bring some order to the chaos.”


News Article | November 2, 2016
Site: www.newscientist.com

HUMANS migrate. It is a characteristic of our species. Yet now a migration crisis is headline news. More than a million desperate people fled to Europe in 2015, and nearly 4000 died trying. The influx is increasing and about to swell more as the weather improves. The United Nations says Europe faces “an imminent humanitarian crisis, largely of its own making”. And it is not alone. The UN has also censured Australia for sending boatloads of refugees to squalid camps in other countries. And US politicians talk of building a wall while tens of thousands of lone children flee violence in Latin America across the US-Mexican border. In January, the World Economic Forum ranked large-scale refugee flows as its global risk of highest concern. When the US Council on Foreign Relations drew up its top 10 priorities for conflict prevention in 2016, it included political instability in the EU caused by the influx of migrants. Concerns about refugees and economic migrants are grist to the mill for those who want Britain to vote to leave the EU in June. And there’s no doubt that migration will increase as the world’s economy becomes more globalised, and as demographic and environmental pressures bite. Should we be alarmed? What is the truth about migration? It is an emotive issue. But the scientific study of what happens when humans move is starting to supply some non-emotive answers. It’s showing that many widespread beliefs don’t hold up to scrutiny. “Concern about immigrants falls sharply when people are given even the most basic facts,” says Peter Sutherland, the UN Special Representative for migration. One analyst even says that removing all barriers to migration would be like finding trillion dollar bills on the sidewalk. The millions fleeing Syria have shone a spotlight on refugees, but that tragedy is just a small part of a bigger picture. More than 240 million people worldwide are international migrants. Refugees account for fewer than 10 per cent of the total and, in theory, they are the least contentious group, because many countries have signed international commitments to admit them. The rest are moving to work, or to join family members who have jobs. When such people travel with refugees, they are often derided as “just” economic migrants. This is unfair, says Alex Betts, head of the Refugee Studies Centre at the University of Oxford. Whether or not they meet the official definition of a refugee, many are escaping dire conditions that pose a threat to their survival. Although globalisation of the world’s economy has lifted millions out of poverty, it has not been able to create enough jobs where there are people in need of work. Aid funds are starting to address this problem – but for the most part people must go where there are jobs. That’s why some see migration as a crisis. The 2008 financial crash spawned insecurity about jobs and concerns about economic migrants. Several populist parties took the opportunity to warn of a flood of freeloaders at the gates, increasing the issue’s political visibility and hardening the policies of some mainstream parties, including in the UK. The US government decided not to bail out firms that hired too many immigrants. Spain paid migrants to leave – even after they had stopped coming as jobs disappeared. And feelings of insecurity remain. “The logic driving this is the idea that migrant workers present additional competition for scarce jobs,” says Ian Goldin at the University of Oxford. Indeed, it is probably part of our evolved nature to think that more for you means less for me (see “The truth about migration: How evolution made us xenophobes“). But that’s not how modern economies work. If economies really were zero-sum games in this way, wages would go down as labour supply increased and natives might well lose jobs to immigrants. But no modern economic system is that simple, says Jacques Poot at the University of Waikato, New Zealand. The knock-on of economic migration is that increased labour also brings an increase in profit, which business owners can invest in more production. They can also diversify, creating opportunities for a broader range of workers. In addition, migration means workers can be more efficiently matched to demand, and make the economy more resilient by doing jobs natives won’t or can’t do. “More people expand the economy,” says Goldin, because people are moving from where they cannot work productively to where they can. In a survey of 15 European countries, the UN’s International Labour Organisation (ILO) found that for every 1 per cent increase in a country’s population caused by immigration, its GDP grew between 1.25 and 1.5 per cent. The World Bank estimates that if immigrants increased the workforces of wealthy countries by 3 per cent, that would boost world GDP by $356 billion by 2025. And removing all barriers to migration could have a massive effect. A meta-analysis of several independent mathematical models suggests it would increase world GDP by between 50 and 150 per cent. “There appear to be trillion-dollar bills on the sidewalk” if we lift restrictions on emigration, says Michael Clemens at the Center for Global Development, a think tank in Washington DC, who did the research. But who gets those billions? Most of the extra wealth goes to migrants and to their home countries. In 2015, migrants sent home $440 billion, two and a half times the amount those countries received in foreign aid – promoting development and jobs at home. But what do natives of countries that attract migrants get out of it? In the EU it has been difficult to tease out the effect of free movement of workers from other economic results of membership. However, a study of non-EU member Switzerland is illuminating. Different parts of Switzerland allowed free access to EU workers at different times, enabling Giovanni Peri of the University of California, Davis, to isolate the effects. He found that while the workforce grew by 4 per cent, there was no change in wages and employment for natives overall. Wages increased a little for more educated Swiss people, who got jobs supervising newcomers, while some less educated Swiss people were displaced into different jobs. Peri has also looked at the situation in the US. “Data show that immigrants expand the US economy’s productive capacity, stimulate investment and promote specialisation, which in the long run boosts productivity,” he says. “There is no evidence that immigrants crowd out US-born workers in either the short or the long run.” Natives instead capitalise on language and other skills by moving from manual jobs to better-paid positions. Peri calculates that immigration to the US between 1990 and 2007 boosted the average wage by $5100 – a quarter of the total wage rise during that period. Further evidence comes from a meta-analysis Poot did in 2010, which collated all the research done up until that point. It reveals that rises in a country’s workforce attributable to foreign-born workers have only a small effect on wages, which could be positive or negative. At worst, a 1 per cent rise caused wages to fall by 0.2 per cent, mostly for earlier generations of immigrants. The impact on the availability of jobs for natives is “basically zero”, he says. Any tendency for wages to fall with an increase in immigration can be counteracted by enforcing a minimum wage. The UK Migration Advisory Committee came to a similar conclusion in 2012. “EU and non-EU migrants who have been in the UK for over five years are not associated with the displacement of British-born workers,” it reported. Very recent migrants do have a small impact, but mainly on previous migrants. What’s more, the ILO notes that low-skilled migrants do “dirty, dangerous and difficult” jobs, which locals do not want – crop picking, care work, cleaning and the like. Meanwhile, highly skilled migrants plug chronic labour shortages in sectors such as healthcare, education and IT. Nearly a third of UK doctors and 13 per cent of nurses are foreign-born. Another presumption made about migrants is that they put a strain on benefit systems. This is also not borne out by the evidence. “It is widely assumed that economic migrants are mainly poor people out to live off the tax money of the relatively rich,” says human rights expert Ian Buruma. “Most of them are not spongers. They want to work.” A lot go not to countries offering generous benefits, but to where there are jobs. Some 82 million people, 36 per cent of the world’s current migrants, have moved from one developing country to another, especially from Haiti to the Dominican Republic, Egypt to Jordan, Indonesia to Malaysia and Burkina Faso to Ivory Coast. Those who do end up in wealthier countries are not the burden people sometimes assume. The Organisation for Economic Co-operation and Development, which represents 34 of the world’s wealthiest nations, calculates that its immigrants on average pay as much in taxes as they take in benefits. Recent research shows that EU workers in the UK take less from the benefits system than native Brits do, mostly because they are younger on average. Moreover, they bring in education paid for by their native countries, and many return to their homeland before they need social security. Based on recent numbers, Britain should conservatively expect 140,000 net immigrants a year for the next 50 years. The Office for Budget Responsibility, the UK’s fiscal watchdog, calculates that if that number doubled, it would cut UK government debt by almost a third – while stopping immigration would up the debt by almost 50 per cent. Illegal migrants make a surprising extra contribution, says Goldin. While many work “informally” without declaring income for taxes, those in formal work often have taxes automatically deducted from their pay cheques, but rarely claim benefits for fear of discovery. Social security paid by employers on behalf of such migrants, but never claimed by them, netted the US $20 billion between 1990 and 1998, says Goldin. That, plus social security contributions by young legal migrants who will not need benefits for decades, is now keeping US social security afloat, he says. “One of the dominant, but empirically unjustified images is of masses of people flowing in… taking away jobs, pushing up housing prices and overloading social services,” writes Stephen Castles at the University of Sydney, Australia, and two colleagues in their book, The Age of Migration. They argue that an increase in migration is often the result rather than the cause of economic changes that harm natives – such as neoliberal economic policies. “The overwhelming majority of research finds small to no effects of migration on employment and wages,” says Douglas Nelson of Tulane University in New Orleans. “On purely economic grounds, immigration is good for everyone.” That may come as a welcome surprise to many. But economics is not the whole story. If perceptions about jobs and wages were the only problem, you would expect anti-immigrant views to run high where jobs are scarce. Yet a 2013 study of 24 European countries found that people living in areas of high unemployment tended not to have negative views of migrants. So, what else are we worried about? One major issue is a perceived threat to social cohesion. In particular, immigrants are often associated with crime. But here again the evidence doesn’t stack up. In 2013, Brian Bell at the London School of Economics and his colleagues found no change in violent crime in Britain linked either to a wave of asylum seekers in the 1990s, or eastern EU migrants after 2004. The asylum seekers were associated with a small increases in property crime such as theft – boosting existing local crime rates some 2 per cent – perhaps because they were not allowed to work, suggest the authors. But areas where eastern Europeans settled had significantly less of any crime. Another study found that immigrants had no impact on crime in Italy. And immigrants in the US are much less likely to commit crimes and are imprisoned less often than native-born Americans. Tim Wadsworth of the University of Colorado has even suggested that a rise in immigration in the 1990s may have driven an overall drop in US crime rates since then. Nevertheless, immigrants can put pressure on local communities. High rates of arrival can temporarily strain schools, housing and other services. “That is what people tend to see,” says Goldin. He says investment is required to mitigate these problems. “Governments need to manage the costs, which tend to be short-term and local,” he says. That’s a challenge, but it can be done. Bryan Caplan of George Mason University in Fairfax, Virginia, points out that since the 1990s, 155 million Chinese have moved from the countryside to cities for work. “This shows it’s entirely possible to build new homes for hundreds of millions of migrants given a couple of decades.” China may be managing the biggest mass migration in history, but there’s one problem it mostly doesn’t face. Perceived threats to national identity often top natives’ list of concerns about immigrants. It can even be an issue when such identities are relatively recent constructs. But countries with a clear ethnic identity and no recent history of significant immigration face the biggest problem, says Nelson. “It’s tricky for Sweden, which went from essentially no immigrants to 16 per cent in half a generation,” he says. And Denmark is another nation where anxiety over the loss of cultural homogeneity has been blamed for a backlash against immigrants. Elsewhere, there has been a hardening of attitudes. Ellie Vasta of Macquarie University in Sydney, Australia, is trying to understand why Europe, which embraced multiculturalism in the 1970s, today calls for cohesion and nationalism, demanding that immigrants conform and testing them for “Britishness” or “Dutchness”. She blames an increasing loss of cohesion in society due to “individualising” forces from mass media to the structure of work. As people rely more on their own resources, they have a longing for community. The presence of foreigners appears to disrupt this, creating a “desire to control differences”, she says. Research by Robert Putnam at Harvard University suggests this move away from multiculturalism could be problematic. He finds that increased diversity lowers “social capital” such as trust, cooperation and altruism. However, this can be overcome in societies that accommodate, rather than erase, diversity by creating “a new, broader sense of ‘we'”. In other words, success lies not in assimilation, but in adaptation on both sides. Canada has tried to achieve this by basing its national identity on immigration. Canadian prime minister Justin Trudeau told the World Economic Forum in Davos, Switzerland, this year that “diversity is the engine of investment. It generates creativity that enriches the world.” This view is shared by complex systems analyst Scott Page at the University of Michigan, Ann Arbor. He argues that culturally diverse groups, from cities to research teams, consistently outperform less diverse groups due to “cognitive diversity” – exposure to disagreement and alternative ways of thinking. “Immigration provides a steady inflow of new ways of seeing and thinking – hence the great success of immigrants in business start-ups, science and the arts,” he says. But more diversity means more complexity, and that requires more energy to maintain – investment in language skills, for example. The fact that immigrants have settled more successfully in some places than others suggests that specific efforts are required to get this right. Achieving broad agreement on core goals and principles is one, says Page. We had better learn how to manage diversity soon because it’s about to skyrocket in wealthy countries. As birth rates fall, there’s a growing realisation that workers from abroad will be required to take up the slack (see “The truth about migration: Rich countries need immigrants“). In addition, the fertility of incomers can stay higher than that of natives for several generations. In 2011, for the first time since mass European migration in the 19th century, more non-white than white babies were born in the US, mainly to recent Asian and Hispanic immigrants and their children. By 2050, white Americans will be a minority, says Bill Frey of the Brookings Institution in Washington DC. That’s good news for the US, he adds, because it gives the country a younger workforce and outlook than its competitors in Europe and Japan. Even if we finesse multiculturalism, there is a potential game changer looming on the horizon. Massive automation and use of robotics could make production less dependent on human labour. This “fourth industrial revolution” may see governments paying their citizens a guaranteed minimum wage independent of work. There has been little discussion of how this might affect a mobile global workforce. However, some warn that cheap, automated production in wealthy countries could destroy export markets for poor countries. This would worsen unemployment and political instability – and also massively boost migration pressure. One way to prepare for this would be to take a more coordinated and strategic approach to the global workforce. As it is, it’s hard to track migration amidst a mess of non-standardised data and incompatible rules. Countries do not agree on who is a migrant. Even the EU has no common policy or information for matching people to jobs. Migrants are usually managed by foreign ministries, not labour ministries that understand the job market. “What could be of real value would be for governments, companies and trade unions to get together and look at where the labour shortages are, and how they could be filled, with natives or migrants,” says Michelle Leighton, head of migration at the ILO. Amazingly, says Goldin, there is no global body to oversee the movement of people. Governments belong to the International Organisation for Migration but it is not an official UN agency so cannot set common policy. Instead, each country jealously guards its borders while competing for workers. Goldin and others think there should be a UN agency managing migration in the global interest, rather than leaving it to nations with differing interests – and power. This, combined with real empirical understanding of the impacts of migration, might finally allow humanity to capitalise on the huge positive potential of its ancient penchant for moving. Read more on the truth about migration here This article appeared in print under the headline “On the road again” Leader: “Migration: Do we want to go forwards or backwards?”


Meyer-Rath G.,Boston University | Meyer-Rath G.,University of Witwatersrand | Over M.,Center for Global Development
PLoS Medicine | Year: 2012

Policy discussions about the feasibility of massively scaling up antiretroviral therapy (ART) to reduce HIV transmission and incidence hinge on accurately projecting the cost of such scale-up in comparison to the benefits from reduced HIV incidence and mortality. We review the available literature on modelled estimates of the cost of providing ART to different populations around the world, and suggest alternative methods of characterising cost when modelling several decades into the future. In past economic analyses of ART provision, costs were often assumed to vary by disease stage and treatment regimen, but for treatment as prevention, in particular, most analyses assume a uniform cost per patient. This approach disregards variables that can affect unit cost, such as differences in factor prices (i.e., the prices of supplies and services) and the scale and scope of operations (i.e., the sizes and types of facilities providing ART). We discuss several of these variables, and then present a worked example of a flexible cost function used to determine the effect of scale on the cost of a proposed scale-up of treatment as prevention in South Africa. Adjusting previously estimated costs of universal testing and treatment in South Africa for diseconomies of small scale, i.e., more patients being treated in smaller facilities, adds 42% to the expected future cost of the intervention. © 2012 Meyer-Rath and Over.


In a joint study, researchers at Dartmouth College and the Center for Global Development have found that the policy of excluding nearly half a million Mexican braceros (manual laborers) from U.S. farms in the early 1960's did not in fact raise wages and employment for domestic farm workers. The findings were released this week as a National Bureau of Economic Research working paper. The bracero exclusion removed almost half of the Mexican-born workers in the U.S. labor market at the time. Using newly digitized archival data on state-level farm wages and employment from the U.S. government, the authors found that farm wages in states with high exposure to bracero workers did not rise significantly faster than in states with low or no exposure to bracero workers after they were excluded from the country at the end of 1964. This refutes the claim made at the time by the Kennedy and Johnson Administrations--a claim that drove the decision to exclude the braceros--that it would benefit domestic farm workers. In high exposure states, farms lost, on average, one-third of their seasonal workforce. Furthermore, the average number of domestic seasonal farm workers did not rise significantly faster in high- and compared to low-exposure states after exclusion, "the opposite of what would be expected if bracero exclusion had crowded more domestic labor into farm work." Helping to account for the policy's lack of labor market effects, the researchers found that the bracero exclusion accelerated mechanization in the production of crops where mechanization technologies had been developed. Production of other crops tended to fall. Available for comment are study co-authors Ethan G. Lewis, associate professor of economics at Dartmouth, at ethan.g.lewis@dartmouth.edu, and Michael A. Clemens, senior fellow at the Center for Global Development, at mclemens@cgdev.org. Hannah M. Postel, research associate at the Center for Global Development, also served as a co-author.


News Article | December 24, 2015
Site: www.rdmag.com

The decorative lights seen around U.S. neighborhoods during the holiday season consume about 6.6 billion kWh of energy every year, according to the U.S. Dept. of Energy. A recent post from the Center for Global Development said that usage exceeds the national electricity consumption of developing countries, such as El Salvador, Ethiopia, Tanzania, Nepal, and Cambodia. While the U.S. number only amounts to 0.2% of U.S. energy consumption, it’s enough to power 14 million refrigerators. El Salvador, which uses the highest amount of energy of the listed countries, topped its yearly use at 5.35 kWh. Cambodia, the lowest, was at 3.06 billion kWh. “I think Christmas lights are a good thing. A beautiful thing! I’m not trying to be anti-Christmas at all,” said Todd Moss, one of the post’s writers, to NPR. According to Moss, the post was meant to highlight the differences in energy use between rich and poor countries. As developing countries increase their usage of electricity, their needs go beyond what current renewable technologies are capable of achieving. “I get an annual notice from Pepco, the power company in Washington, D.C., and Maryland, where I live. The fuel mix for D.C. and Maryland is 95.9 percent from coal, gas and nuclear; 4 percent renewable — including 2 percent wind, 0.1 percent solar,” Moss said to NPR. “It's pretty rich for me to sit in Washington, D.C., and tell Ghana they can't build one natural gas power plant.” Though the Dept. of Energy statistic cited comes from 2008, Moss said he would be surprised if energy consumed during the holidays changed significantly in 2015. “Lights are something we take for granted, but a lot of countries around the world don't have enough electricity to run a refrigerator or create jobs,” said Moss to NPR. “And we should be humble in the kind of advice we give countries about how they should develop energy sources.”


News Article | December 6, 2016
Site: www.npr.org

To Help The Poorest Of The Poor, First You Have To Find Them In the quest to help the poor, it's difficult to know whose needs are the greatest. Without clear data, it's tough to know who to help first. The traditional way to look for the poorest of the poor is with household surveys. They are the primary source of data for policy decisions, but they have drawbacks. "Household surveys are expensive, and the coverage is not great," says Stefano Ermon, an assistant professor of computer science at Stanford University. So Ermon is heading up a new project to create a method of gathering poverty data using satellite images — which eventually could help policymakers make more informed decisions. The use of satellite images isn't new. It's the emphasis on daytime pictures that's innovative. Nighttime pictures can reveal some information about consumption, the "use of goods and services by households." The theory is, if people could afford a high level of consumption, then people could afford to use a lot of electricity. So the nighttime satellite image of the region would be bright. On the other hand, if the region is dark, then people in the region presumably cannot afford to use much electricity. This would mean a low level of consumption in the region. The problem with nighttime images is that "they don't show much gradation in the poorest parts," Ermon says. In other words, these images don't distinguish poor regions from very poor regions — which is where some policymakers may be aiming their limited resources. So Ermon and his team developed a computer program to analyze daytime satellite images — just as available as nighttime images but with more visual details. Ermon says his new model goes beyond looking at just differences in electricity use, also analyzing roads, houses and features of the terrain. Nobody, not even Ermon, completely understands how the new model extracts economic data from geographic information. "The model is extremely complicated [and] we don't know exactly what the model is looking for in the images," Ermon says. All we know for now is that the model works pretty well. Indeed, a paper Ermon and his team published in Science this summer states that their program can "identify image features that can explain up to 75 percent of the variation in local level economic outcomes." The paper states that Ermon's new method outperforms nighttime imagery analysis with a "81.2 percent increase." "What the Stanford team has shown is that daylight beats night lights," wrote Justin Sandefur, a senior fellow at the Center for Global Development, in a post on the center's blog. "This is a cool technique that I'm sure will (and should) get a lot of use among researchers, and will hopefully catalyze further refinements to the approach." The computer program analyzes satellite images alongside the survey data from five countries where household surveys have been conducted recently — Malawai, Nigeria, Rwanda, Tanzania and Uganda. The program picks out connections between visual features of images and numerical data from the survey. Sandefur, who helped design the Tanzania survey the Ermon group used, supports the group's work. But he cautions that it's not ready to act as the sole basis for policy decisions. His quantitative analysis of the group's work finds that the group "gets the poverty status right 60 percent of the time," which is not much better than random guessing. "The accuracy is just not nearly refined enough to target a social program," Sandefur says. "I could guarantee you urban legends would spread about what would make you look poor from space." So the day of replacing door-to-door surveys with observations from the outer space has yet to come. Nonetheless, the World Bank is receptive to the idea of incorporating the data. "We see satellite images as a complement [to household surveys], not a substitute," says David Newhouse, a senior economist at the World Bank. "Putting the two together would make a lot of sense." Then again, the point of the Ermon group's research is to shed light on regions with little to no survey data. "If it's that information-poor, then we might as well use this," says Jonathan Drake, an imagery analyst at the American Association of the Advancement of Science. "I think it shows considerable promise." "We've received a large number of request for data from both academic, government and non-governmental organizations," Ermon says. While not everyone thinks Ermon's project provides accurate enough data for policymaking purposes, Ermon says his method does "better than existing methods." His group plans to work on the project, investigating the "practical benefits of using [their] new poverty data."


News Article | December 6, 2016
Site: www.npr.org

To Help The Poorest Of The Poor, First You Have To Find Them In the quest to help the poor, it's difficult to know whose needs are the greatest. Without clear data, it's tough to know who to help first. The traditional way to look for the poorest of the poor is with household surveys. They are the primary source of data for policy decisions, but they have drawbacks. "Household surveys are expensive, and the coverage is not great," says Stefano Ermon, an assistant professor of computer science at Stanford University. So Ermon is heading up a new project to create a method of gathering poverty data using satellite images — which eventually could help policymakers make more informed decisions. The use of satellite images isn't new. It's the emphasis on daytime pictures that's innovative. Nighttime pictures can reveal some information about consumption, the "use of goods and services by households." The theory is, if people could afford a high level of consumption, then people could afford to use a lot of electricity. So the nighttime satellite image of the region would be bright. On the other hand, if the region is dark, then people in the region presumably cannot afford to use much electricity. This would mean a low level of consumption in the region. The problem with nighttime images is that "they don't show much gradation in the poorest parts," Ermon says. In other words, these images don't distinguish poor regions from very poor regions — which is where some policymakers may be aiming their limited resources. So Ermon and his team developed a computer program to analyze daytime satellite images — just as available as nighttime images but with more visual details. Ermon says his new model goes beyond looking at just differences in electricity use, also analyzing roads, houses and features of the terrain. Nobody, not even Ermon, completely understands how the new model extracts economic data from geographic information. "The model is extremely complicated [and] we don't know exactly what the model is looking for in the images," Ermon says. All we know for now is that the model works pretty well. Indeed, a paper Ermon and his team published in Science this summer states that their program can "identify image features that can explain up to 75 percent of the variation in local level economic outcomes." The paper states that Ermon's new method outperforms nighttime imagery analysis with a "81.2 percent increase." "What the Stanford team has shown is that daylight beats night lights," wrote Justin Sandefur, a senior fellow at the Center for Global Development, in a post on the center's blog. "This is a cool technique that I'm sure will (and should) get a lot of use among researchers, and will hopefully catalyze further refinements to the approach." The computer program analyzes satellite images alongside the survey data from five countries where household surveys have been conducted recently — Malawai, Nigeria, Rwanda, Tanzania and Uganda. The program picks out connections between visual features of images and numerical data from the survey. Sandefur, who helped design the Tanzania survey the Ermon group used, supports the group's work. But he cautions that it's not ready to act as the sole basis for policy decisions. His quantitative analysis of the group's work finds that the group "gets the poverty status right 60 percent of the time," which is not much better than random guessing. "The accuracy is just not nearly refined enough to target a social program," Sandefur says. "I could guarantee you urban legends would spread about what would make you look poor from space." So the day of replacing door-to-door surveys with observations from the outer space has yet to come. Nonetheless, the World Bank is receptive to the idea of incorporating the data. "We see satellite images as a complement [to household surveys], not a substitute," says David Newhouse, a senior economist at the World Bank. "Putting the two together would make a lot of sense." Then again, the point of the Ermon group's research is to shed light on regions with little to no survey data. "If it's that information-poor, then we might as well use this," says Jonathan Drake, an imagery analyst at the American Association of the Advancement of Science. "I think it shows considerable promise." "We've received a large number of request for data from both academic, government and non-governmental organizations," Ermon says. While not everyone thinks Ermon's project provides accurate enough data for policymaking purposes, Ermon says his method does "better than existing methods." His group plans to work on the project, investigating the "practical benefits of using [their] new poverty data."


Savedoff W.D.,Center for Global Development | De Ferranti D.,Results for Development Institute | Smith A.L.,Social Insight | Fan V.,Center for Global Development
The Lancet | Year: 2012

Countries have reached universal health coverage by diff erent paths and with varying health systems. Nonetheless, the trajectory toward universal health coverage regularly has three common features. The fi rst is a political process driven by a variety of social forces to create public programmes or regulations that expand access to care, improve equity, and pool fi nancial risks. The second is a growth in incomes and a concomitant rise in health spending, which buys more health services for more people. The third is an increase in the share of health spending that is pooled rather than paid out-of-pocket by households. This pooled share is sometimes mobilised as taxes and channelled through governments that provide or subsidise care-in other cases it is mobilised in the form of contributions to mandatory insurance schemes. The predominance of pooled spending is a necessary condition (but not suffi cient) for achieving universal health coverage. This paper describes common patterns in countries that have successfully provided universal access to health care and considers how economic growth, demographics, technology, politics, and health spending have intersected to bring about this major development in public health.


Fan V.Y.,Center for Global Development | Duran D.,Center for Global Development | Silverman R.,Center for Global Development | Glassman A.,Center for Global Development
The Lancet Global Health | Year: 2013

Background: Performance-based financing can be used by global health funding agencies to improve programme performance and thus value for money. The Global Fund to Fight AIDS, Tuberculosis and Malaria was one of the first global-health funders to deploy a performance-based financing system. However, its complex, multistep system for calculating and paying on grant ratings has several components that are subjective and discretionary. We aimed to test the association between grant ratings and disbursements, an indication of the extent to which incentives for performance are transmitted to grant recipients. Methods: We obtained publicly available data for 508 Global Fund grants from 2003 to 2012 with performance ratings and corresponding disbursements, merged with other datasets that contained data for relevant country characteristics. We used regression analysis to identify predictors of grant disbursements in phase 2 (typically the latter 3 of 5 years of a grant), using two dependent variables: whether a grant had any phase-2 disbursements, and the phase-2 disbursement amount. In a separate analysis, we also investigated the predictors of grant performance ratings. Findings: Grant performance rating in phase 1 was positively associated with having any disbursements in phase 2, but no association was seen between phase-1 ratings and phase-2 disbursement amounts. Furthermore, performance ratings are not replicable by external observers, both because subjective and discretionary decisions are made in the generation of performance measures and because the underlying data are not available. Interpretation: The Global Fund's present performance-based funding system does not adequately convey incentives for performance to recipients, and the organisation should redesign this system to explicitly link a portion of the funds to a simple performance measure in health coverage or outcomes, measured independently and robustly. Funding: Bill & Melinda Gates Foundation. © 2013 Fan et al. Open Access article distributed under the terms of CC BY-NC-SA.

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