5 votes

Understanding measurement issues is key to understanding ‘economic growth’

Posted by skybrian
Tags: economics, nigeria, industrial revolution, history, growth.economic, substack.notes on the crises, author.nathan tankus
https://nathantankus.substack.com/p/in-april-2014-gdp-in-nigeria-jumped

Link information

This data is scraped automatically and may be incorrect.

Title
In April 2014, GDP in Nigeria Jumped 89%. How the Hell Did That Happen?
Authors
Notes on the Crises
Word count
1799 words

4 comments

  1. szferi
    Link
    I use macro data all day long. Even in countries like the US, not all data is equally reliable and we use various techniques to post-process them. Bayesian techniques are typically applied...

    I use macro data all day long. Even in countries like the US, not all data is equally reliable and we use various techniques to post-process them. Bayesian techniques are typically applied assuming measurement errors around every datapoints. But for countries like China and Nigeria or any other one outside of OECD, it is common practice to not use the GDP data directly, but re-estimate them from higher frequency more reliable data, sometimes not even measured by the given country stat office. There are also interesting crowdsourcing experiences to collect data directly from the field like Wordbank food price data and Premise.

    3 votes
  2. [2]
    skybrian
    Link
    From the article: [...] [...] [...]

    From the article:

    Few dispute that the textile industry and other steam engine dependent sectors experienced a revolution. But the impact on economic growth of all this depends on the relative importance of these sectors in the period in question. If the manufacturing sector grew at 10 percent per annum, but only accounted for 1 percent of the activity in year 1, then its impact on aggregate will not be 10 percent — but 0.1 percent. On the other hand, if the sector was accounting for 10 percent of the economy then its growth impact would have been to raise the size of the total economy by one whole percent. This is what’s known as an “index number problem”.

    [...]

    In order for these two amounts to be comparable, they are expressed in constant prices. In many countries, this is done by always comparing one years GDP, with the GDP at the previous year’s prices. But there is no data availability to make such calculations every year.

    The easiest way of doing this, particularly if data are sparse — which they are at most African statistical offices — is to generate "base year" estimates for future level estimates. When picking a base year the statistical office chooses a year when it has more information on the economy than normally available. This includes data from a household, agricultural or industrial survey. The information from these survey instruments is added to the normally available administrative data, to form a new GDP estimate. This new total is then weighted by sectors, thereafter other indicators and proxies are used to calculate new annual estimates.

    [...]

    Thus, when the base year is out of date, the GDP series becomes an increasingly unreliable guide to interpreting underlying economic change. For instance when the Nigerian GDP was recalculated, a quarter of a century had passed since the previous base year of 1990.

    What do we now know of economic performance in Nigeria or Sub-Saharan Africa? It is a bit complicated. We know now that Nigerian GDP was, according to the revised figures, underestimated by 89 percent. When did this new economic activity appear? That would require some serious forensic accounting to establish. Sadly, the data sources are not good enough to figure it out. Unrecorded remains unrecorded.

    [...]

    The advantage of coming at the problem of economic statistics as an Economic Historian is that one is keenly aware that the statistics are not given, they are made. That means that statistics are social and political products. In mainstream economic debates the biggest part of the discussion is focused on what drives inflation, and why employment is up or down. Meanwhile less attention is given to the very basic problem that while we know what employment and inflation are in theory, it is technically impossible to measure it cleanly.

    The notion that we scientists can let the data or the evidence speak for itself is misleading. Skilled journalists, historians and lawyers interrogate witnesses and sources to figure who made the observation, and the biases behind what they observed. And in our own way, economists and finance writers have to interrogate these soft numbers that we too often treat as hard facts.

    2 votes
    1. skybrian
      Link Parent
      Also see poor numbers and what to do about them:

      Also see poor numbers and what to do about them:

      In the library there was a dearth of publications and I could find no record of any activity that may or may not have taken place in the late 1970s, the 1980s, and the early 1990s. From what I could find it seemed that the data and methods used to estimate Zambian national income had last been revised in 1994. A short report on methodology had been prepared, but it was unpublished and was circulated internally as a manual for the national accountants. It revealed the real state of affairs of national income statistics in Zambia. I was surprised by the lack of basic data and the rudimentary methods in use. From what I could see regular and reliable data were available only on government finances and the copper sector. The entire agricultural sector was accounted for by observing trends in crop forecasts for eight agricultural commodities. For the rest of the economy there seemed to be no usable data. The construction sector was assumed to grow at the same rate as cement production and imports. Retail, wholesale, and transport sectors were all assumed to grow at the same rate as agricultural and copper production, while business services were also assumed to grow at the same rate.

  3. [2]
    Comment deleted by author
    Link
    1. skybrian
      Link Parent
      Nigeria is an extreme case, but I think the point is that economic numbers are only as good as the data-gathering and assumptions being made. Of course there is much more and better data in other...

      Nigeria is an extreme case, but I think the point is that economic numbers are only as good as the data-gathering and assumptions being made. Of course there is much more and better data in other countries.

      As non-economists reading the news, I don't see what we can do about it though, other than be a little less trusting. For people in the field, it would be an argument to dig deeper.

      1 vote