Group items tagged

Interesting discussion of a contentious issue related to the idea of a 'basic income' (but here, in a development context). Martin Ravallion (former Chief Economist of the World Bank, now at CGD) published a useful paper this week asking exactly this question. As he says, there's no simple answer - which is why the question is so interesting. Both 'the right to work' and 'the right to income' aim to secure a more fundamental right: freedom from poverty. Workfare has a long history, notably in India, where the National Rural Employment Guarantee Act (NREGA) guarantees (in theory) up to 100 days work per year, paid at a minimum wage, to anyone who requests it. Cash transfers (often with conditions) have expanded enormously in recent years, while the hot topic of Universal Basic Income (UBI) has advocates across the political spectrum. Which of these approaches is most cost-effective? Ravallion sets out the arguments clearly.

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.

'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."