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Feeding the craving for precision on global poverty

Francisco Ferreira's picture

Online pundits, hurried journalists and policymakers love precision. They crave numbers. Preferably exact numbers; ranges suggest uncertainty and make them anxious. As a result, they will love the World Poverty Clock (WPC), a new website that claims to track progress towards ending global poverty in real time (see also this blog and Financial Times article). The website tells you that 632,470,507 people are currently living in extreme poverty - or were, on December 6 at 10:00am… Even more amazingly, the site claims to forecast poverty at any point in the future until 2030, the deadline for the UN’s Sustainable Development Goals. By scrolling along the elegant timeline on the bottom of the WPC screen you will learn, for example, that in 2028, 459,309,506 people will be living in extreme poverty!

Scenarios are not merely uncertain forecasts

Hans Timmer's picture

My previous blog ended with a question about the usefulness of anticipating the long-term future if that future is highly uncertain. Ever since the 1982 article on “Trends and random walks in macroeconomic time series” by Nelson and Plosser, there has been a debate about the long-term statistical properties of GDP and other macroeconomic variables. Nelson and Plosser could not reject the hypothesis of a random walk (with drift), which means that random shocks have a permanent impact on the level of GDP and that the uncertainty interval around forecasts becomes wider and wider with every year you try to peek farther into the future. The message seems to be: If next year’s world is already very uncertain, don’t even bother forecasting the world in 2030.

Others found that “macroeconomic time series are best construed as stationary fluctuations around a deterministic trend function”, if you allow for a few structural breaks in the trend. The consequences for long-term forecasting are huge because, in this case, random shocks are transitory, there is mean reversion, and it is in fact easier to analyze long-term trends than short-term fluctuations.

In the long run, we all want to be alive, and thrive

Hans Timmer's picture

Ninety years ago, in his A Tract on Monetary Reform Keynes famously wrote “In the long run we are all dead”. That observation recently stirred a lot of debate for all the wrong reasons, after Niall Ferguson obnoxiously claimed that Keynes did not care about the future because he was childless. Whether Keynes cared about the long-term future or not (and whether he had children or not) is completely irrelevant in this context, as many (e.g. Brad DeLong and Paul Krugman) have pointed out.

The actual context in which Keynes wrote this observation was a discussion about the quantity theory of money, which states that doubling the supply of money will only double the prices, but will have no consequences for other parts of the economy. This is the classical dichotomy between real and nominal variables. Keynes argued: “Now in the long run this is probably true”. But “In the long run we are all dead. Economists set themselves too easy, too useless a task if in tempestuous seasons they can only tell us that when the storm is long past the ocean is flat again.”  So, Keynes’ point was obviously not that the future doesn’t matter. His point was that simple theories that might describe long-term relationships are just not good enough to deal with current issues. In the short run, changes in money supply can have all kinds of important consequences beyond the price levels. Economists will have to make their hands dirty and delve into the complicated dynamics of the here and now.