Mismeasuring Long Run Growth: The Bias from Spliced National Accounts
by Leandro Prados de la Escosura (Carlos III)
Abstract: Comparisons of economic performance over space and time largely depend on how statistical evidence from national accounts and historical estimates are spliced. To allow for changes in relative prices, GDP benchmark years in national accounts are periodically replaced with new and more recent ones. Thus, a homogeneous long-run GDP series requires linking different temporal segments of national accounts. The choice of the splicing procedure may result in substantial differences in GDP levels and growth, particularly as an economy undergoes deep structural transformation. An inadequate splicing may result in a serious bias in the measurement of GDP levels and growth rates.
Alternative splicing solutions are discussed in this paper for the particular case of Spain, a fast growing country in the second half of the twentieth century. It is concluded that the usual linking procedure, retropolation, has serious flows as it tends to bias GDP levels upwards and, consequently, to underestimate growth rates, especially for developing countries experiencing structural change. An alternative interpolation procedure is proposed.
Source: http://econpapers.repec.org/paper/cgewacage/202.htm
Distributed in NEP-HIS on 2015 – 01 – 09
Reviewed by Cristián Ducoing
Dealing with National Accounts (hereafter NA) is a hard; dealing with NA in the long run is even harder…..
Broadly speaking, a quick and ready comparison of economic performance for a period of sixty years or more, would typically source its data from the Maddison project. However and as with any other human endevour, this data is not free from error. Potential and actual errors in measuring economic growth is highly relevant economic history research, particularly if we want to improve its public policy impact. See for instance the (brief) discussion in Xavier Marquez’s blog around how the choice of measure can significantly under or overstate importance of Lee Kuan Yew as ruler of Singapore.
The paper by Leandro Prados de la Escosura, therefore, contributes to a growing debate around establishing which is the “best” GDP measure to ascertain economic performance in the long run (i.e. 60 or more years). For some time now Prados de la Escosura has been searching for new ways to measure economic development in the long run. This body of work is now made out of over 60 articles in peer reviewed journals, book chapters and academic books. In this paper, the latest addition to assessing welfare levels in the long run, Prados de la Escosura discusses the problems in using alternative benchmarks and issues of spliced NA in a country with a notorious structural change, Spain. The main hypothesis developed in this article is to ascertain differences that could appear in the long run NA according to the method used to splice NA benchmarks. So, the BIG question is retropolation or interpolation?
Leandro Prados de la Escosura. Source: http://www.aehe.net
Retropolation: As Prados de la Escosura says, involves a method that is …, widely used by national accountants (and implicitly accepted in international comparisons). [T]he backward projection, or retropolation, approach, accepts the reference level provided by the most recent benchmark estimate…. In other words, the researcher accepts the current benchmark and splits it with the past series (using the variation rates of the past estimations). What is the issue here? Selecting the most recent benchmark results in a higher GDP estimate because, by its nature, this benchmark encompasses a greater number of economic activities. For instance, the ranking of relative income for the UK and France changes significantly when including estimates of prostitution and narcotrafic. This “weird” example shows how with a higher current level and using past variation rates, long-run estimates of GDP will be artificially improved in value. This approach thus can lead us to find historical anomalies such as a richer Spain overtaking France in the XIXth century (See Prados de la Escosura figure 3 below).
An alternative to the backward projection linkage is the interpolation procedure. This method accepts the levels computed directly for each benchmark year as the best possible estimates, on the grounds that they have been obtained with ”complete” information on quantities and prices in the earlier period. This procedure keeps the initial level unaltered, probably being lower than the level estimated by the retropolation approach.
There are two more recent methods to splice NA series derived from the methods described above: the “mixed splicing” proposed by Angel de la Fuente (2014), which uses a parameter to capture the severity of the initial error in the original benchmark. The problem with this solution is the arbitrary value assigned (parameter). Let’s see it graphically and using data for the Maddison project. As it is well known, these figures were recently updated by Jutta Bolt and Jan Luiten van Zanden while the database built thanks to the contributions of several scholars around the world and using a same currency (i.e. the international Geary-Kheamy dollar) to measure NA. Now, in figure 1 shows a plot of GDP per capita of France, UK, USA and Spain using data from the Madison project.
GDP per capita $G-K 1990. France, UK, USA and Spain. 1850 – 2012
The graph suggests that Spain was always poorer than France. But this could change if the chosen method to split NA is the retropolation approach. Probably we need a graph just with France to appreciate the differences. Please see figure 2:
GDP pc Ratio between Spain and France. Bolt&vanZanden (2014) with data from Prados de la Escosura (2003)
Figure 2 now suggests an apparent convergence of Spain with France in the period 1957 to 2006. The average growth rate for Spain in this period was almost 3,5% p.a. and in the case of France average growth shrinks to 2,2% p.a. Anecdotal observation as well as documented evidence around Spainish levels of inequality and poverty make this result hard to believe. Prados de la Escosura goes on to help us ascertain this differences in measurement graphically by brining together estimates of retropolation and interpolation approaches in a single graph (see figure 3 below):
Figure 3. Spain’s Comparative Real Per Capita GDP with Alternative Linear Splicing (2011 EKS $) (logs).
In summary, this paper by Prados de la Escosura is a great contribution to the debate on long run economic performance. It poises interesting challenges scholars researching long-term growth and dealing with NA and international comparisons. The benchmarks and split between different sources is always a source of problems to international comparative studies but also to long-term study of the same country. Moving beyond the technical implications discussed by Prados de la Escosura in this paper, economic history research could benefit from a debate to look for alternative measures or proxies for long-run growth, because GDP as the main source of international comparisons is becoming “dated” and ineffective to deal with new research in inequality, genuine savings Genuine Savings, energy consumption, complexity and gaps between development and developed countries to name but a few.
References
Bolt, J. and J. L. van Zanden (2014). The Maddison Project: collaborative research on historical national accounts. The Economic History Review, 67 (3): 627–651.
Prados de la Escosura, Leandro (2003) El progreso económico de España (1850-2000). Madrid, Fundación BBVA, , 762 pp.
PS:
1) This paper by Prados de la Escosura has already been published in Cliometrica and with the same title
2) Prados de la Escosura’s A new historical database on economic freedom in OECD countries | VOX, CEPR’s Policy Portal.
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