Group items tagged

Long read from the New Yorker on employment statistics. Good economic statistics benefit the left and the right, government and business. Without reliable data, businesses can't take risks on investments. Boeing, for example, decides how many 787 Dreamliners to build and therefore how many people to employ based on its Current Market Outlook forecast, which is rooted in government data and projects aircraft demand for the next twenty years.

Interesting to see such a fact check from a government agency. In recent times, simplistic and occasionally completely inaccurate information about Sweden and Swedish migration policy has been disseminated. Here, the Swedish Ministry for Foreign Affairs looks at some of the most common claims.

Australia should revamp how it selects major transport projects, so that governments can better know which new roads and railways are worth building and avoid squandering billions of dollars of public money on the wrong projects. The 'discount rate' Australian governments have applied to assess the value of proposed projects has been stuck at 7 per cent since at least 1989, even though the price of money has fallen from about 8 per cent to 1 per cent since then.

Interesting discussion of a contentious issue (although a little light on evidence!!) Tallinn, known for its digital government and successful tech startups, is often referred to as Europe's innovation capital. Now celebrating five years of free public transport for all citizens, the government is planning to make Estonia the first free public transport nation. Allan Alaküla, Head of Tallinn European Union Office, shares some valuable insights for other cities.

There's a form of casual violence that kills 1.25 million people a year (3 times more than malaria) and injures up to 50ODI roads cover million more. 90% of the deaths are of poor people (usually men) in poor countries. No guns are involved and there's lots of things governments can do to fix it. But you'll hardly ever read about it in the development literature, although road safety did make it into the Sustainable Development Goals (as did everything else, it has to be said) - targets 3.6 and 11.2 for SDG geeks. So hats off to ODI (again) for not only painstakingly building the case for taking action on a major cause of death and misery in poor countries (see below), but also exploring the politics and institutions that so far have prevented governments from taking action.

Good example of a contentious issue. In an Australian study published today, we show that if the government were to combine taxes and subsidies on a range of foods and beverages, it could substantially improve the health of Australians and potentially free up billions in health care spending.

Until the first Abbott-Hockey budget in 2014, a statement of budget measures that disproportionately affect women was published at budget time. At times given different names, the first was delivered with the Hawke government's 1984 budget. In its foreword, then Prime Minister Hawke promised that "within the overall economic objectives of the government" important budget decisions would from then on be made "with full knowledge of their impact on women". These women's budget statements shed light on the impact of decisions that might have been thought to have little to do with gender, such as the Hawke government's reduction of tariffs on imports of clothing, textiles and footwear. The statement pointed out that two-thirds of the workers in these industries were women and that without special support for retraining (which was given) they would be disproportionately disadvantaged. Increasingly, and especially during the Rudd and Gillard governments, the statements made visible the economic impact of women's greater responsibility for unpaid care work.

One way of working out if the data you're gathering is particularly sensitive is to do a thought experiment: what would happen if this data got into the hands of a malicious actor? Who would be keen to get their hands on it? What are the worst things that they could do with this data? Sometimes, though, it can be hard to put yourself in the shoes of your enemies, or to envision potential future actions. As a result, practising data minimisation is a keystone of a rights-based, responsible data approach. And sadly, it's the opposite of the approach we're seeing governments around the world take.

How do we measure illegal activity? How do we estimate the size of the 'black economy'? Some nice visualisations in this report. The Australian government has announced a taskforce to "crack down on the black economy", with a panel reportedly to consider measures such as removing the $100 note from circulation and limiting cash transactions above a certain limit. One estimate of the underground economy from 1999, which only considered cash transactions and excluded illegal activities, put the size of the underground economy at around 15% of gross domestic product. However, a more recent estimate by the Australian Bureau of Statistics (ABS) in 2013, which encompassed proceeds from illegal activities as well as other areas, estimated the size to be far smaller, at only 2.1% of GDP.

'Significance' is a magazine published by the UK Royal Statistical Society and American Statistical Association. E.g. this article discusses the data we might use to analyse food security, thinking about what sources of data are available and the questions they might help us answer. "data on food insecurity is biased towards the environment in which it was created and the priorities of those who collect or commission it. Data from schools is concerned with reimbursement; government data might be focused on budgetary constraints or accountability; grocery stores could (if willing) tell us what food is bought, but not how it is used; meanwhile, non-profits are most interested in demonstrating impact to funders. There is a wide variety of data sets available, but very few are created with the intent to understand the real drivers of hunger and poverty. The data may be repurposed, but modellers must be especially careful to moderate the assumptions of each data set. ...... It is also especially important that those experiencing hunger and poverty are consulted when designing any data analysis project. The input of domain experts is crucial to the success of data science endeavours, and those experiencing poverty know the right questions to ask."

During the 2016 EU referendum campaign, both sides used statistics pretty freely to back their arguments. Understandably, UK broadcasters felt compelled to balance competing perspectives, giving audiences the opportunity to hear the relative merits of leaving or remaining in the EU. In doing so, however, the truth of these statistical claims was not always properly tested. This might help explain some of the public's misconceptions about EU membership. So, for example, although independent sources repeatedly challenged the Leave campaign's claim that the UK government spent £350m per week on EU membership, an IPSOS MORI survey found that almost half of respondents believed this was true just days before the election. Of the 6,916 news items examined in our research, more than 20% featured a statistic. Most of these statistical references were fairly vague, with little or limited context or explanation. Overall, only a third provided some context or made use of comparative data. Statistics featured mostly in stories about business, the economy, politics and health. So, for example, three-quarters of all economics items featured at least one statistic, compared to almost half of news about business. But there were some areas - where statistics might play a useful role in communicating trends or levels of risk - that statistics were rarely used.

How we track our economy influences everything from government spending and taxes to home lending and business investment. The Conversation series The Way We Measure takes a close look at economic indicators to better understand what's going on. Ever since 1944, Gross Domestic Product (GDP) has been a primary measure of economic growth. It's in the news regularly and, even though few can define what it means, there is general acceptance that when GDP is growing, things are good. There are problems with this simplistic formulation.

Read the comments alongside the article here - interesting speculation and use of evidence. initiatives will not turn the affordability problem around while tax settings continue to support existing homeowners and investors at the expense of first time buyers and renters. Moreover, apart from a brief interruption 2008-2012, the Commonwealth has been steadily winding back its explicit housing role for more than 20 years. The post of housing minister was deleted in 2013, and just last month Government senators dismissed calls for renewed Commonwealth housing policy leadership recommended by the Senate's extensive (2013-2015) Affordable Housing Inquiry. This complacency cannot go unchallenged.

Excellent discussion of absolute and relative risk in the context of alcohol safety. "But claiming there is no 'safe' level does not seem an argument for abstention. There is no safe level of driving, but government do not recommend that people avoid driving."

In August 2016, the Australian government released an "anonymised" data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people. Names and other identifying features were removed from the records in an effort to protect individuals' privacy, but a research team from the University of Melbourne soon discovered that it was simple to re-identify people, and learn about their entire medical history without their consent, by comparing the dataset to other publicly available information, such as reports of celebrities having babies or athletes having surgeries.

Australian farms generate huge volumes of agricultural data. Examples include the types of crops being grown, crop yields, livestock numbers and locations, types of fertilisers and pesticides being used, soil types, rainfall and more. This data is typically collected through the use of digital farming machinery and buildings featuring robotics and digital technologies, artificial intelligence, and devices connected to the internet ("internet of things", or IoT). But a recent review from the Australian Bureau of Statistics and the Australian Bureau of Agricultural and Resource Economics highlights the patchy and fragmented nature of existing government and industry approaches to agricultural data. What that means is Australian farmers are currently not adequately protected from their farm data being collected and used without their knowledge or consent.

"Between 2000 and 2015, nearly every African country improved childhood nutrition, especially in reducing stunted growth caused by malnutrition" .... " national averages do not tell the full story. In Kenya, for example, rates of wasting in children under 5 were below 6% on average nationwide in 2015, yet in certain regions plagued by several years of poor rains, crop failure and disease outbreaks, estimated levels of wasting reach as high as 28%."... "Such fine-grained insight brings tremendous responsibility to act. It shows governments, international agencies and donors exactly where to direct resources and support."..."This shows how crucial it is to invest in data. Data gaps undermine our ability to target resources, develop policies and track accountability. Without good data, we're flying blind. If you can't see it, you can't solve it."

Interesting links to different sources discussing data on teacher pay, and what it shows in relation to different things that stakeholders might care about. educator pay varies significantly across states, from an average of $44,921 in Oklahoma to $77,957 in New York. Why should school administrators and government leaders care about teacher pay - beyond wanting their employees to be able to afford their living expenses? Below, we present research that examines this issue. What scholars have found is that teacher salaries are linked to employee retention and that better pay seems to draw smarter people to the field and into the classroom. It's not clear, however, whether higher salaries result in higher student achievement.

EVERYONE HAS A THEORY about who's to blame for the housing shortage that's driving up prices and chasing Bay Area families out of the region. A new poll offers surprising insights into where most of us point the finger: not at the government officials who control what homes are built where, but at the tech companies that have flooded this region with jobs and the real estate developers trying to maximize profits.

journalists often write about public opinion polls, which are designed to measure the public's attitudes about an issue or idea. Some of the most high-profile polls center on elections and politics. Newsrooms tend to follow these polls closely to see which candidates are ahead, who's most likely to win and what issues voters feel most strongly about. Other polls also offer insights into how people think. For example, a government agency might commission a poll to get a sense of whether local voters would support a sales tax increase to help fund school construction. Researchers frequently conduct national polls to better understand how Americans feel about public policy topics such as gun control, immigration reform and decriminalizing drug use. When covering polls, it's important for journalists to try to gauge the quality of a poll and make sure claims made about the results actually match the data collected. Sometimes, pollsters overgeneralize or exaggerate their findings. Sometimes, flaws in the way they choose participants or collect data make it tough to tell what the results really mean. Below are 11 questions we suggest journalists ask before reporting on poll results. While most of this information probably won't make it into a story or broadcast, the answers will help journalists decide how to frame a poll's findings - or whether to cover them at all.