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Voorbeeld van de inhoud
29 October International Development asConcept and Narrative, and How we
measure development
29/10 Jerven, Moren (2013) ‘What do we know about Income
and Growth in Africa?’
What do we know about income and growth in sub-Saharan Africa?
o answer is: much less than we like to think
o data are unreliable and potentially seriously misleading
most pressing problem w the quality of data is ignorance among those who use the data
o the pragmatic approach is to accept the data at face value
on the domestic political scene, there is little to no transparent debate about the issue
At the same time, both the dependence on and demand for economic statistics is
increasing
o aims of development are increasingly stated as quantifiable targets, as they are framed,
for instance, by MDG
o buzzword in development community is “evidence-based policy”
Leading scholars know that the data are weak, but most data users are incapable of
judging exactly how weak and how this weakness affects policy analysis
What Is National Accounting?
National income measurement is governed by global standard: United Nations System of
National Accounts (SNA)
The standards of national accounts have since been revised three times, so that there are
four versions
o in addition to the SNA 1953, there are also SNA 1968, SNA 1993, and SNA 2008
Many people are not familiar with this system and may scarcely have heard of it, but it is
the framework that generates most of our basic info about national economies
o Its main product is most important development indicators of them all
national income and economic growth
o In theory, this global norm is now followed by all members of UN member states
o Data is regularly collected by UN Statistical Office and disseminated by its agencies to
rate and rank all wealth and progress of nations of the world
The resulting metric, and object of study in this book, is GDP, or GNI, referred to as
national income
, o This statistic is used to measure size of economy, and this is data by which countries are
ranked as developed or less developed
o Economic growth is measure of change in real GDP per capita
o In theory, this measure is obtained by combining value of all of value-added activities in
an economy throughout one year and dividing that total by size of country’s population
in that year
In practice, this measure does not reach that assumed level of accuracy, even in
countries with developed economies
National Accounts in Africa: The Main Problems
central issue in national income accounting
o deciding which economic activities/actors should/can be included in official accounts
o often referred to as the “production boundary”
In all economies a distinction between recorded and unrecorded economic activity exists
o In “developed” economies, unrecorded activity consists of illegitimate economic
activity and economic activity within family household
o In most African economies unrecorded economy is so large and therefore so
economically important that to leave it unrecorded is unsatisfactory
In theory, there are three distinct ways of aggregating GDP
o 1. income method
o 2. expenditure method
o 3 production method
1.
o first approach adds up profits, rents, interest, dividends, salaries, and wages
o In practice, this approach has not been suitable for estimating GDP African economies
2.
o expenditure approach is more feasible, at least at first glance
o components are private consumption, I, G consumption, and balance of X and M
o problem: personal consumption and part of capital formation related to rural and
small-scale economic activities
3.
o production method totals estimates of value added (output - intermediate
consumption) per sector (agriculture, mining, manufacturing, construction, and
different services) to equal total value added, or GDP
o has been preferred in official national income accounting in postcolonial Africa
While System of National Accounts suggests all 3 methods should be estimated
independently, thus providing check on accuracy of each estimate, this is not done
, o postcolonial national accounts have typically been estimated using production method,
while expenditure on private consumption has typically not been estimated
independently but has been derived as what is called a “residual”
o In practice, this means that instead of reaching an independent estimate of this
important component, an estimate is reached by subtracting all other components of
expenditures from GDP estimate that was reached using production approach
A Survey of the National Income Evidence
There are 3 major sources of national income data
o 1. the World Development Indicators
o 2. the Penn World Tables
o 3. the datasets of Angus Maddison
o Each is based on national account files as prepared by nat statistical agencies, but differ
in modifications they use, purchasing adjustments they use, and acc to their currencies
1.
o The World Development Indicators database is maintained by World Bank Group
o It is data source most commonly used in public domains such as politics and the media
2.
o database maintained by economists at University of Pennsylvania
o ones most commonly used by growth economists in cross-country growth regressions
3.
o datasets produced by Angus Maddison
o commonly used by economic historians and economists
o regularly updated by Groningen Growth and Development Center at Uni of Groningen
The 3 sources agree on ranking of some countries but disagree on most and in some
cases with a large discrepancy
There are also large fluctuations in the rankings
pressing Q: is inconsistency in reporting in diff datasets common to all income data?
o True: there is always some variation btwn estimates, depending on which source of
data was used and what method was chosen to express data in intern currency
o BUT: range of variation (therefore uncertainty of info) deriving from African economies
is much larger
o sources agreed about relative income ranking for majority of Latin American countries
Thus, the same data sources are more reliable on Latin American countries
Why is there so much disagreement in the African data?
o systematic variation in cash values means that income per capita measures are quoted
in intern dollars from diff years
Maddison uses 1990
, World Development Indicators database uses 1995
the Penn World Tables uses 1996
Furthermore, income estimates reported in datasets provided by Penn World Tables and
WDI differ bc diff formulas were used to calculate intern price estimates
! main problem lies with the primary source
o intern GDP per capita datasets all take national account files, provided by statistical
agencies, as a starting point
o datasets inherit all problems of data quality from country where data are collected
But there are other, more important sources of disagreement
o data series provided by nat statistical agencies are subject to revisions, and various
official series exist with diff base years that cover the same time period
o This problem goes back to the nature of these datasets
not truly glob datasets; are nat data from various states that intern databases
disseminate
Alwyn Young
o discovered problem of absent data and unclear provenance when attempting to build
up and revise a database for African measures of living standards
o argued that underlying data supporting estimates for living standards are minimal or
nonexistent
Possibly to reassure data users, it reports that “these gap-filling procedures are run
automatically, with no human intervention.”
o procedure results in discrepancies btwn GDP data provided from the nat statistical
offices and those generated at World Bank
country-level information was gathered through respective nat statistical office websites
confusion regarding sub-Saharan African economic growth and income
The base year is of crucial importance
o significance of outdated base years might be reemphasized with an empirical example
Kenia
general rule thumb: base year should be changed every decade to avoid maj distortions
In conclusion
o rankings of African economies acc to GDP levels should not be taken at face value
o In large part, info recorded in databases is the result of automatic data permutations,
preliminary estimates, or negotiated numbers
o Thus, differences in GDP levels that can be observed in databases are as likely to be
product of statistical methods as they are to provide info about economic realities
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