Links. The standard of living and how to measure it.
How to measure the standard of living? Is it about market production? Or about happiness? Or about market production plus home production (the washing machine!) plus government production? Or about utility? Or even about ‘the biological standard of living’? Or where we live? Or all of these? Below, three excerpts from recent articles about this, from John Komlos, Diane Coyle and Eurostat.
My take:(1) we should be wary of national averages while (2) national accounts are highly useful and even indispensable to calculate (using input-output models) the change in CO2 production caused by a change in final demand, technology or gasoline taxes. These accounts are not just about GDP, though GDP is, in an accounting sense, the emergent statistical keystone of a national money based economy. And (3), as Komlos shows social differences permeate our entire life.
1) John Komlos has a new article which argues that the biological standard of living is important. And it begins at the beginning. In the womb. An excerpt:
For instance, babies born prior to the 37 weeks of gestation or weighing less than 5.5 pounds will be disadvantaged for the rest of their lives in just about everything including their lifetime earnings. Fetuses exposed to toxins or infections will be irreparably damaged. The elephant in the room that we’ve been ignoring for the most part is that inequality — the big social issue of our time — begins amazingly during those 37 weeks. … The kind of inhumane deprivation that exists in the dysfunctional low-income crime-ridden environment that is colloquially called a slum and which the federal government refers euphemistically as “targeted census tracts,” leads to stress, anxiety, abuse, poor nutrition, infrequent doctor visits or no visits at all until the time of delivery, because of lack of money and lack of health insurance. Inadequate micronutrients, insufficient vitamin B or infections lead to all sorts of complications and suboptimal outcomes including birth defects, stillbirths, pre-term delivery and low birthweight followed by high infant mortality. The emotional stress that invariably accompanies such poverty all too often makes things much worse and all too often means that the fetus has to contend with toxins such as lead , alcohol, nicotine and heroin. In other words, in the targeted census tracts, just getting into the world as a healthy baby is a major challenge in and of itself. … The data are stark and unmistakable:<!–more–> in every single metric that matters to long run health or earning capacity, African American babies are disadvantaged by the time they take their very first breath in the world. For instance, blacks have a much higher rate of preterm births than whites 20 percent vs. 12 percent. Low birth weight (LBW) is also a major setback: it is 8 percent among whites but 16 percent among blacks, a whopping four times as high as in Sweden or Finland. LBW, defined as a weight of less than 5.5 pounds, has harmful effects forever and is also a main cause of infant mortality. No wonder that the mortality rate among African American infants is 2.2 times that of whites.
2) Diane Coyle discusses in a new discussion paper if GDP is an apt metric of social welfare
There have long been objections to the GDP-centricity of economic policy, and quite a number of suggested alternatives – dating at least as far back as the Club of Rome. These alternatives are gaining significant traction in the media and in policy debates, and – if my experience is typical – also among students and members of the public. There is huge interest in ‘happiness’ or well-being as a policy aim and metric. And of course the Sen-Stiglitz-Fitoussi work and its follow-up, along with the European Commission’s ‘GDP and Beyond’ and the OECD’s Better Life Index are clear evidence of official interest in a different approach to measuring the economy, one very explicitly based on social welfare… This is surely the right aim. Statistics shape the boundaries of what is politically possible. They originated in the development of the modern, administrative nation state, and have a strongly performative character. In modern democracies we surely do want statistics that enable citizens to hold policymakers to account for social welfare rather than simply aggregate economic activity. The ideal indicators should have the following characteristics: they should be linked to the kinds of levers available to policymakers or to outcomes policy can plausibly affect; they should be available as consistent time series and in a timely enough manner that there is some meaningful attribution of outcomes to policy decisions; they should be not-too-complicated and reasonably intuitive.
3) From Eurostat (these data show that the variable ‘capital city ‘ should be introduced in our geographical/economic models; also the UK has uncommonly large regional differences in income):
In 2013, regional2 GDP per capita, expressed in terms of purchasing power standards, ranged from 27% of the EU28 average in the French overseas department of Mayotte, to 325% of the average in Inner London in the United Kingdom. This information is taken from data released by Eurostat, the statistical office of the European Union..The leading regions in the ranking of regional GDP per capita in 2013, after Inner London in the United Kingdom (325% of the average), were the Grand Duchy of Luxembourg (258%), Bruxelles/Brussel in Belgium (207%), Hamburg in Germany (195%), …. After Mayotte in France (27%), the lowest regions in the ranking were all in Bulgaria and Romania: Severozapaden (30%), Severen tsentralen (31%) and Yuzhen tsentralen (32%) in Bulgaria and Nord-Est in Romania (34%). It should be noted, however, that in some regions the GDP per capita figures can be significantly influenced by ommuter flows. Net commuter inflows in these regions push up production to a level that could not be achieved by he resident active population on its own. There is a corresponding effect in regions with commuter outflows.