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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.

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.

This is a great list of evidence based stories by FiveThirtyEight (FiveThirtyEight uses statistical analysis - hard numbers - to tell compelling stories about elections, politics, sports, science, economics) They also produced a list of some great stories from other venues: http://fivethirtyeight.com/features/damn-we-wish-wed-written-these-11-stories/

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.

Exhorted by President Trump, federal administrators and many Republican state officials are drafting rules requiring people to work in exchange for Medicaid, housing aid and food assistance. But what happens when the poor live where work is hard to find? In Michigan, the state's Senate has passed a proposal that would exempt Medicaid recipients from a work requirement partly on the basis of geography - if they live in a county where unemployment exceeds 8.5 percent. Michigan's approach, critics point out, would mean that poor, mostly white rural counties are exempted, but not the predominantly black, economically troubled cities of Detroit and Flint.

Argument: Because deductions (the amount of income you can claim is not-taxable) will be reduced, even though the tax rate will go down, the richest will not in fact see an absolute reduction in tax paid. Counterargument - looking at the data, this is in fact not the case...

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.

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.

An introduction to a set of deep dive articles an important issue....When we tell people that we work at the intersection of statistics and human rights, the reaction is often surprise. Everyone knows that lawyers and journalists think about human rights problems … but statisticians? Yet, documenting and proving human rights abuses frequently involves the need for quantification. In the case of war crimes and genocide, guilt or innocence can hinge on questions of whether violence was systematic and widespread or one group was targeted at a differential rate compared to others. Similar issues can arise in assessing violations of civil, social, and economic rights. Sometimes the questions can be answered through simple tabulations, but often, more-complex methods of data collection and analysis are required.

Most of the poor people in the world are women. In no country on earth are women economically equal to men, and Australia is no exception. Research from Acoss and the University of New South Wales last year showed that a higher share of people living in poverty in Australia are women. The experience of living below the breadline in our very wealthy nation is a gendered one, for reasons that are complex and intertwined. As women progress through life, they encounter a series of barriers and setbacks that simply do not encumber men in the same way. The cause of gendered poverty is structural. It is entrenched in our workplace settings, and embedded in our personal relationships. It is at play at every stage of a woman's life, from childhood to the grave, making its mark on our education, our employment, our homes, our familial responsibilities and our retirement options. At its heart is the simple fact that women do the lion's share of caring for others. Caring is women's work, and our society does not value women's work.

Machines are besting humans in more and more tasks; thanks to technology, fewer Americans make more stuff in less time. But today economists debate not whether machines are changing the workplace and making us more efficient - they certainly are - but whether the result is a net loss of jobs. The figures above may look dire. But compare the number of manufacturing jobs and total jobs in the chart below. Since 1990, the total non-farm workforce has grown 33 percent, more than accounting for the manufacturing jobs lost.

Protests against racial injustice and the COVID-19 pandemic have exposed racial inequalities rife within social and economic systems around the world. Fed up with police brutality and systemic racism against African Americans and other racialised groups, people staged protests against racial injustice in all 50 states across the United States.Apart from these examples, however, there is surprisingly little data or discourse about the impact of the disease on racial and ethnic minorities in the rest of Europe. This silence speaks volumes about Europe's approach to racism.The vast majority of EU member states do not use the concept of race or ethnic origin in data collection, in spite of policies like the European Racial Equality Directive and the Employment Equality Directive which prohibit racial or ethnic discrimination. France outright prohibits it.Without disaggregated data, it is virtually impossible to quantify the extent of discrimination experienced by racial and ethnic groups or the impacts of COVID-19 on their lives.

Christopher Pyne has overstated how well Australia is performing on jobs and growth compared to other major economies. IMF estimates for 2016 on GDP growth had put Australia ahead of the G7 countries. But the latest available data - which are actual figures as of the third quarter of 2016, not estimates - show that Australia's cumulative growth in 2016 so far is at the level of the G7 and not higher. So Australia is performing in line with the G7 and slightly worse than the OECD average.

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.

How does the "smashed avo" hook shape this discussion? Look at how statistics are used in this report to inform the debate and critique a narrow perspective. There's no doubt there are differences between the experiences and opportunities of young people compared to their parents. But when you enter the smashed avocado debate of baby boomers versus millennials, you overlook the inequality between members of the same generation. This also misses other ways inequality is perpetuated, such as through the intergenerational transfer of wealth. It's uncomfortable for many to admit but Australia is a hugely unequal society, both in terms of incomes and wealth. Australian households in the top 20% account for half of the income stream, that's about 12 times more than the bottom 20%. At the far ends of the distribution, the average weekly after tax income of the top 5% is 13 times that of the bottom 5%. But this isn't just an artefact of wealth in different generations. There are multiple ways we can glean this, most notably in relation to poverty.

Why probability and understanding statistical fallacies matters Some of our most important decisions are shaped by something as random as the order in which we make them. The gambler's fallacy, as it's known, affects loan officers, federal judges -- and probably you too. How to avoid it? The first step is to admit just how fallible we all are.

'Killer facts' are those punchy, memorable, headline-grabbing statistics that make reports special. They cut through the technicalities to fire people up about changing the world. They are picked up and repeated endlessly by the media and politicians. They are known as 'killer' facts because if they are really effective, they 'kill off' the opposition's arguments. The right killer fact can have more impact than the whole of a well-researched report.

Bald-faced lies are, thankfully, fairly rare in Australian politics. Being caught in an outright fib or blooper is still seen as shameful. The problem in Australia is that facts and statistics are frequently twisted to paint a misleading picture. Weasel-words, cherry-picking and overstatements are common. Our politicians and lobby groups are masterful at disguising opinion and ideology as fact, and making statements that, ultimately, aren't checkable. These tactics are harder to spot, but equally dangerous. FactCheck: Is 30% of Northern Territory farmland and 22% of Tasmanian farmland foreign-owned? Election FactCheck: are many refugees illiterate and innumerate? Election FactCheck Q&A: has the NBN been delayed? Election FactCheck Q&A: is it true Australia's unemployment payment level hasn't increased in over 20 years? And more...

As the author of this FactCheck, I was asked to review the facts on Australia's foreign aid spending from the Menzies era to 2016-17. Sir Robert Menzies was prime minister from 1949 to 1966, which is the Menzies era for present purposes. (Menzies also served as prime minister from 1939 to 1941.) I examined the evidence for and against this statement: Aid was at its highest under Menzies, at 0.5% … when per capita income was much lower. - World Vision Australia Chief Advocate Tim Costello, quoted in The Sydney Morning Herald, December 28, 2016. I found the statement to be incorrect, strictly interpreted, though Costello's broader point is valid. The ratio of Australia's aid to its gross national income has never exceeded 0.48%, and that level was achieved slightly after the conclusion of the Menzies era, in the financial year 1967-68. Below, I explain how I arrived at this conclusion, providing more detail than could be accommodated in the FactCheck itself.

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.