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Measuring GDP in Europe

World Economics - September 2015

Speed Read
  • Only two European countries have out of date base years and World Economics estimates that bringing these up to date could add only US$4.3 billion to aggregate GDP for the group as a whole.
  • The use of different national income standards across Europe has an impact on cross-country comparability and in some cases leads to an underestimation of GDP. It is estimated that the application of the latest standard would add US$827 billion or 3.6% to European GDP overall.
  • Most European countries use a national income accounting standard that fails to adequately record the informal economy which estimates if accurate suggest could account for between 8% and 47% of GDP in countries across the region.
  • In total the under-measurement of GDP on all grounds noted above could add between 12% and 51% to European GDP.


 

Europe Economic Data: The problems

In this paper the quality and the reliability of official national income accounting data is investigated for 41 countries across Europe.[1]



1. Resources Available to Measure National Income

Although for some countries the quality of national income statistics is constrained by the capacity and resources devoted to national statistics offices to follow international best practice, this is a less serious issue in Europe than in the Americas, Asia and in Africa. There is a global standard set by the United Nations for measuring national income,[2] but poorer countries generally report lower quality statistics because of the reduced resources available to national statistical offices to implement best practice and together with the paucity of comprehensive household and business surveys available. This is a general problem across the world. Given the disparity in per capita income across Europe, some differences in the quality of economic statistics are inevitable. In 2013, GDP per capita across the continent in PPP terms (2011 relative prices) ranged from US$91,048 in Luxembourg to US$4,692 in Moldova with a median income of US$28,897. [3]

 

These problems can all be rectified by increasing the resources available for national income accounting exercises, but there are other significant data problems which distort the measurement of the relative size of national economies and the validity of inter-country comparisons of living standards and growth rates across Europe. The most significant specific data issues which impact of GDP estimation in Europe are:

  1. The failure to update base years regularly.
  2. The use of outdated standards of national accounting.
  3. The degree to which the shadow economy (including informal activities, illicit activities and the income derived from crime) are measured.



1. Base Year Problem

Real growth in the activity of an economy is estimated by comparing GDP at current and at constant prices. Constant price estimates use the price relatives of a particular year, known as a base year or benchmark year, to weight the volume components of production. But since the structure of production and relative prices over time are dynamic, the pattern of relative prices and the industries surveyed in the base year become less relevant over time. The time elapsed between current estimates of GDP and the base year is of crucial importance to the accuracy of national income data. According to Jerven (2013) failures to regularly update a base year in which the structure and relative prices of an economy are monitored can lead to serious bias in the estimation of GDP. He refers to the case of Ghana when estimated GDP was uplifted by 60% overnight as a result of an update in the base year from 1993 to 2006. In 2014, the Nigerian National Bureau of Statistics released new estimates of GDP showing a rise of 59.5% after the economy’s base year was updated from 1990 to 2010. One of the reasons for these large uplifts is that better estimates of some economic activities such as telecommunications, tourism and financial services were made by statisticians while some previously unrecorded activities from the informal sector were included.

The best current international practice is to update a country’s base year every five years. However, most European countries (with the exception of Macedonia and Montenegro) now adopt the practice of chaining where price relatives are updated every year (See Table 1)[4]. Although chaining allows continual updates to be made to the structure of production and consumption, it requires considerable expenditure on resources by statistical offices.

 

 

Reassessing GDP in Europe

In this section, we report on an exercise to estimate the impact on estimated GDP if Macedonia and Montenegro updated their base years to 2013. In order to produce data that is not affected by exchange rate fluctuations we use World Bank GDP data which is estimated at (Purchasing Power Parity) PPP data in constant international US dollars order to make inter country comparisons of  European countries.

 

The methodology used to estimate what would happen if the two countries updated their base years is crude and involves applying an estimated constant cumulative annual rate of growth to the years between the last reported base year and 2013 on top of the underlying rate of real growth. The longer the period between 2013 and the last base year and the higher the assumed cumulative growth rate, the higher the uplift that would be expected from rebasing. Analysing the existing economic data after carrying out this procedure shows that aggregate GDP in Montenegro and Macedonia may be underestimated by around 12%.

Two assumptions were necessary to carry this exercise out:

  1. The choice of the latest base year data series to apply on a country by country basis. These have been selected by inspecting the WDI, and IMF metadata as reported in Table 1 with account taken of inconsistencies between sources.
  2. An estimate of the cumulative annual rate which would act as a proxy by replicating over time the effect of the uplift created in one year by rebasing GDP. 

 

Inconsistent Base Year Data: The reported base years or the practice of chaining from the World Bank, and the IMF are shown by country in Table 1. Given the number of differences between these 3sources in reported base years or the practice of chaining, the source(s) generally used to calculate how many years the latest base year was out-of-date or if chaining was relevant was highlighted in bold. Furthermore, the number of years the two countries base year are calculated as the difference between the last reported base year and 2013.

 

 

Table 1: Reported Base Years by Source 

Country

 Reported Base Year

Base Year

Years out of date

WDI

IMF

Albania

Chained

Chained

Chained

0

Austria

Chained

Chained

Chained

0

Belarus

Chained

Chained

Chained

0

Belgium

2005

Chained

Chained

0

Bosnia and Herzegovina

Chained

Chained

Chained

0

Bulgaria

Chained

Chained

Chained

0

Croatia

Chained

2005

Chained

0

Cyprus

Chained

Chained

Chained

0

Czech Republic

Chained

Chained

Chained

0

Denmark

2005

Chained

Chained

0

Estonia

2005

Chained

Chained

0

Finland

Chained

Chained

Chained

0

France

Chained

Chained

Chained

0

Georgia

Chained

Chained

Chained

0

Germany

Chained

Chained

Chained

0

Greece

Chained

Chained

Chained

0

Hungary

Chained

Chained

Chained

0

Iceland

Chained

Chained

Chained

0

Ireland

Chained

Chained

Chained

0

Italy

Chained

Chained

Chained

0

Kosovo

2008

2013

2013

0

Latvia

2010

Chained

Chained

0

Lithuania

2010

Chained

Chained

0

Luxembourg

Chained

Chained

Chained

0

Macedonia, FYR

2005

2005

2005

8

Malta

Chained

Chained

Chained

0

Moldova

Chained

1995

Chained

0

Montenegro

2000

2006

2006

7

Netherlands

Chained

Chained

Chained

0

Norway

Chained

Chained

Chained

0

Poland

Chained

Chained

Chained

0

Portugal

2005

Chained

Chained

0

Romania

2000

Chained

Chained

0

Russian Federation

2000

Chained

Chained

0

Serbia

Chained

Chained

Chained

0

Slovak Republic

Chained

Chained

Chained

0

Slovenia

Chained

Chained

Chained

0

Spain

Chained

Chained

Chained

0

Sweden

Chained

Chained

Chained

0

Switzerland

Chained

Chained

Chained

0

Ukraine

Chained

1998

Chained

0

United Kingdom

Chained

Chained

Chained

0

Sources: World Bank, IMF       

 

   

Cumulative annual rate: The assumed annual rate that would act as a proxy by replicating over time the effect of the uplift created in one year by rebasing GDP was 1.6% per annum in Europe. This was based on an econometric model from a sample of 39 GDP national rebasing exercises carried out across the world excluding Africa which uses a higher rate of 2.52%.

 

Results: In 2013, the two countries analysed had a combined GDP of US$34.6 billion. The uplift applied to Montenegro was (7 x 1.6%) 11.2% and that applied to Macedonia was (8 x 1.6%) 12.8% raising the estimated GDP for both countries if rebasing occurs to US$38.9 billion.



3. Outdated National Accounting Standards

The harmonized System of National Accounts (SNA) was created by the international community to facilitate the comparability of economic statistics and standards. Since 1953 there have been three revisions to recommended SNA standards, in 1968, 1993, and in 2008, all approved by the United Nations Statistical Commission. SNA 2008 has already been implemented in Australia in 2009, Canada in 2012, in the USA in 2013 and New Zealand in 2014, causing problems in making international comparisons between this group of countries and those using SNA 1993, or earlier versions. 

In Europe, three countries use SNA 1993, which only aids global comparisons between them and other countries that still use this outdated standard. However, among the 28 European Union member countries, a separate system of national accounting is used, the European Standard of Accounts (ESA). This is broadly based on the SNA system and so far there have been two European standards ESA95, (based on SNA 1993) and ESA 2010 (based on SNA 2008). Two countries Russia and Ukraine have implemented SNA 2008. See Table 2.


 Table 2: Accounting Standards by Country

Country

GDP US$PPP 2013
(million)

European National Accounting Standard

Germany

3,539,320

 ESA 2010

France

2,478,251

ESA 2010

United Kingdom

2,452,415

ESA 2010

Italy

2,112,704

ESA 2010

Spain

1,542,768

 ESA 2010

Poland

912,748

ESA 2010

Netherlands

775,728

ESA 2010

Belgium

464,899

ESA 2010

Switzerland

460,605

 ESA 2010

Sweden

428,622

 ESA 2010

Austria

382,263

ESA 2010

Romania

379,134

ESA 2010

Norway

333,427

ESA 2010

Czech Republic

305,101

ESA 2010

Portugal

287,672

ESA 2010

Greece

283,041

 ESA 2010

Denmark

245,834

ESA 2010

Hungary

230,867

ESA 2010

Finland

216,848

ESA 2010

Ireland

210,037

ESA 2010

Slovak Republic

143,437

ESA 2010

Bulgaria

114,293

ESA 2010

Serbia

93,276

ESA 2010

Croatia

90,861

ESA 2010

Slovenia

59,447

ESA 2010

Luxembourg

49,472

ESA 2010

Estonia

34,035

ESA 2010

Cyprus

26,891

ESA 2010

Macedonia, FYR

25,841

ESA 2010

Iceland

13,610

ESA 2010

Malta

12,332

ESA 2010

 

Country

GDP US$PPP 2013
(million)

European National Accounting Standard

Belarus

167,081

ESA 1995

Lithuania

76,056

ESA 1995

Latvia

45,352

ESA 1995

Bosnia and Herzegovina

36,515

ESA 1995

Montenegro

8,781

ESA 1995

 

Country

GDP US$PPP 2013
(million)

UN National Accounting Standard

Russian Federation

3,592,401

SNA 2008

Ukraine

391,851

SNA 2008

Albania

28,759

SNA 1993

Moldova

16,697

 SNA 1993

Kosovo

16,178

SNA 1993


Source: World Bank, IMF, Eurostat 


In October 2014, the first set of revised GDP estimates based on ESA 2010 were published for the 28 European Union countries which lead to large estimated shifts in national income levels in most member states. The main methodological differences between SNA 1993 and SNA 2008, which have been replicated between ESA 95 and ESA 2010, include the treatment of government accounts, capital expenditure and intellectual property. ESA 2010 has also incorporated a number of improvements in statistical analysis including better means of monitoring and measuring the informal sector and some illegal activities. The implementation of this change means that whereas the national accounts of the 28 European Union countries are broadly comparable between themselves and with the USA, Canada, Australia and New Zealand, comparisons are less reliable for the other European countries listed above. The longer it takes for these other European countries to adopt the new SNA 2008 standard the less reliable will be economic comparisons between themselves and other countries in Europe and the rest of the developed world. 

 

The differences between GDP measured in accordance with SNA 1993 and SNA 2008 are significant. The adoption by the US of most of the accounting guidelines of SNA 2008 led to a comprehensive revision of its national income and product accounts. In the US revised estimates of GDP and other major macroeconomic aggregates made by the Bureau of Economic Analysis (BEA) produced a 3.6% upward revision of GDP in 2012. In Europe, the implementation of the methodological changes in ESA 2010 produced a rise in GDP in 2010 of 2.3%. 


The main methodological changes brought about by the adoption of the new European standard are shown in Table 3 although it is noteworthy that most of the size of the GDP revision, just over eighty percent of it, was due to the decision to capitalise research and development expenditures.

 Table 3: Effects of major ESA 2010 changes on EU GDP 2014

Source of Revision to GDP

Percent of EU 28 GDP 2010

Total Revision

2.27%

Capitalisation of research and development

1.86%

Capitalisation of military weapon systems

0.17%

Inexpensive tools for common operators

0.07%

Government public/private sector delineation

0.06%

Employers pension schemes

0.06%

Other Methodological Changes

0.05%

Source: Eurostat (2015)

 

 

The capitalisation of expenditures on weapons systems revised EU‑28 GDP by 0.17% respectively, while the revised treatment of small tools, such as saws, spades, knives, axes, hammers and other hand tools, where ESA 2010 eliminated the monetary threshold for the purchase of these items to be recognised as capital expenditure, accounted for a revision of 0.07%. The change to the sector classification of government and the recording of employers’ pension schemes revised GDP up by 0.06% each. At the national level the largest impacts from methodological changes from the implementation of ESA 2010 GDP levels were registered for Sweden (4.4%) and Finland (4.0%) while the smallest impact was registered in Bulgaria (0.4%). The results of the application of the methodological changes arising from the implementation of ESA 2010 for each country is shown in Table 4.



4. The Shadow Economy Problem 
All economies have many unrecorded economic transactions which bias downwards official estimates of GDP, employment and income per head. The SNA 1993 national income accounting standard recognised the importance of the informal economy particularly in developing economies defining it as belonging to the household sector, but there was no explicit methodological recommendation as to how to measure its size. The SNA 2008 standard goes a lot further in defining the informal sector and in placing the onus of measurement on national statistical offices adopting the standard to include estimates within the framework of national income accounting.

The SNA 2008 standard recommends a number of methods and improved statistical sampling to estimate the informal economy which have been replicated in Europe by the implementation of ESA 2010 which also produced a number statistical improvements which led to a further upward estimate of EU-28 by an additional 1.4% in 2010. These included making estimates of illegal activities and in total raised total GDP in the 28 countries by 1.4%. The total EU28 uplift as a result of both the methodological and statistical improvements arising from the application of ESA 2010 was 3.7%. The data from Eurostat also provides a country-by-country breakdown of the impact of the implementation of ESA 2010 broken down by methodical changes and statistical improvements. At the national level the largest impacts from statistical improvements on 2010 GDP levels were registered for the Netherlands (5.9%) while a negative impact was registered in Luxembourg (-1.4%).

 

The assumed revision estimate that would act as a proxy if the non-EU countries implemented ESA 2010 was 3.7%. Applying the rebasing, the adjustments for the implementation of ESA 2010 and the implied adjustment for ESA 1995 to ESA 2010 and SNA 1993 to SNA 2008 produces a rise in estimated European GDP in 2013 of US$827 billion or 3.6% measured in PPP dollars.

The full results of all adjustments are shown in Table 4.

 

Table 4: European Revision of GDP by % Size of Uplift

Country

GDP PPP 2013 Actual (US$ million)

Rebasing Uplift

ESA 2010 % Uplift

Total Uplift %

GDP PPP 2013 Revised (US$ million)

Methodological Uplift

Statistical Uplift

Macedonia FYR

25,841

12.8

2.3

1.4

16.5

30,105

Montenegro

8,781

11.2

2.3

1.4

14.9

10,028

Netherlands

775,728

0

1.7

5.9

7.6

834,683

Sweden

460,605

0

4.4

1.1

5.5

452,196

United Kingdom

2,452,415

0

2.3

2.6

4.9

2,572,583

Finland

216,848

0

4.2

0.5

4.7

227,040

Czech Republic

305,101

0

3.1

1.2

4.3

317,915

Ireland

210,037

0

3.6

0.6

4.2

218,859

Russian Federation

3,592,401

0

2.4

1.3

3.7

3,725,320

Switzerland

460,605

0

2.3

1.4

3.7

477,647

Ukraine

391,851

0

2.3

1.4

3.7

406,349

Norway

333,427

0

2.3

1.4

3.7

345,764

Belarus

167,081

0

2.3

1.4

3.7

169,370

Serbia

93,276

0

2.3

1.4

3.7

96,727

Bosnia & Herzegovina

36,515

0

2.3

1.4

3.7

37,866

Albania

28,759

0

2.3

1.4

3.7

29,823

Moldova

16,697

0

2.3

1.4

3.7

16,926

Kosovo

16,178

0

2.3

1.4

3.7

16,777

Iceland

13,610

0

2.3

1.4

3.7

13,796

Italy

2,112,704

0

1.6

1.9

3.4

2,184,536

Portugal

287,672

0

2.1

1.3

3.4

297,453

Germany

3,539,320

0

2.7

0.6

3.3

3,656,118

Spain

1,542,768

0

1.6

1.7

3.3

1,593,679

France

2,478.25

0

2.4

0.8

3.2

2,557,555

Austria

382,263

0

3.7

-0.5

3.2

394,495

Belgium

464,899

0

2.4

0.4

2.8

477,916

Denmark

245,834

0

2.7

-0.2

2.5

251,980

Malta

12,332

0

0.5

1.7

2.2

12,603

Slovenia

59,447

0

2.0

0.1

2.1

60,695

Bulgaria

114,293

0

0.4

1.6

2.0

116,579

Romania

379,134

0

0.6

1.3

1.9

386,338

Slovak Republic

143,437

0

1.8

0.1

1.9

146,162

Greece

283,042

0

1.3

0.5

1.8

288,136

Poland

912,748

0

1.2

0.5

1.7

928,265

Hungary

230,867

0

1.6

0

1.6

234,561

Croatia

90,861

0

0.5

0.8

1.3

92,042

Croatia

90,861

0

0.5

0.8

1.3

92,042

Cyprus

26,891

0

1.1

0.2

1.3

27,241

Estonia

34,035

0

1.4

-0.2

1.2

34,443

Lithuania

76,056

0

0.8

0.3

1.1

76,893

Luxembourg

49,472

0

1.6

-1.4

0.2

50,461

Latvia

43,352

0

1.1

-1.2

-0.1

453,073

Total Europe

23,085,450

N/A

N/A

N/A

3.60%

23,913,233

 

However, the estimates of the shadow economy and illegal activities undertaken as a result of the application of ESA 2010 across the European Union are dwarfed when a comparison is made with the data presented by Freidrich Schneider, a leading expert on the size and importance of grey economic activity across the world. Based on his estimates for 2007 which covers 38 of the European countries investigated in this analysis, Table 5 shows that according to Schneider (2013) the relative size of the shadow economies across Europe ranged from 8.1% of GDP in Switzerland to 46.8% in the Ukraine. The size of shadow economy across the 28 European Union economies ranged from 9.4% in Luxembourg to 32.7% in Bulgaria. [5] In contrast, the statistical improvements enacted by ESA 2010 ranged from -1.2% in Latvia to 5.9% in the Netherlands. Generally, although the estimates were smaller in scale there was little correspondence with Schneider’s estimates. The implementation of ESA 2010 which implemented a number of statistical improvements including making estimates of illegal activities raised total GDP in the 28 countries by only 1.4%.


Table 5: The Shadow Economy % of National Income 

Country

% of National Income

41% - 50%

Ukraine

46.8

Moldova*

44.3

Belarus

43.3

Russian Federation

40.6

31% - 40%

Macedonia, FYR

34.9

Albania

32.9

Bosnia and Herzegovina

32.8

Bulgaria

32.7

Croatia

30.4

Romania

30.2

30 % and Below

Lithuania

29.7

Estonia

29.5

Latvia

27.2

Italy

26.8

Cyprus

26.5

Greece

26.5

Malta

26.5

Poland

26.0

Slovenia

24.7

Hungary

23.7

Portugal

23.0

Spain

22.2

Belgium

21.3

Norway

18.0

Sweden

17.9

Czech Republic

17.0

Finland

17.0

Denmark

16.9

Slovak Republic

16.8

Ireland

15.4

Germany

15.3

Iceland

15.0

France

14.7

Netherlands

13.0

United Kingdom

12.2

Austria

9.5

Luxembourg

9.4

Switzerland

8.1

 Source: Schneider and Williams (2013).
*Shadow Economy data for Moldova only available for year 2006.

 

  

5. Conclusion 

Europe is split between countries using the same, albeit outdated, national accounting methodology SNA1993 or ESA 1995, and those who use the newer ESA 2010, which is based on SNA 2008. This makes it relatively sound to compare the European Union countries with OECD countries such as the US, Canada, Australia and New Zealand, but it will make comparisons between non-EU countries and the OECD problematic as SNA 2008 is progressively adopted. The information already available on estimates of the size of the shadow economy economies (See Table 5) suggests that significant additional upward revisions may be needed despite the adoption of ESA 2010 and SNA 2008 since the new standard only goes so far in devoting resources to measuring informal and illicit activities. In Europe, however, Tables 1 and 4 show that unlike many other parts of the world the extensive use of chaining means that out of date base years is less of a problem. This means that there would be only one effective change in the rankings of countries in Europe by GDP size as a result of rebasing with Macedonia moving up by a few places.

 


References

Eurostat (2015), “Annual national accounts - how ESA 2010 has changed the main GDP aggregates”

http://ec.europa.eu/eurostat/statistics-explained/index.php/Annual_national_accounts_-_how_ESA_2010_has_changed_the_main_GDP_aggregates

 

Jerven, M. (2013) Poor Numbers: How we are misled by African Development Statistics and what to do about it, Cornell.

 

Schneider, F and Williams, C. C., (2013) The Shadow Economy, Institute of Economic Affairs, Hobart Paper 172.



[1] A number of countries were excluded from this study as no GDP PPP data was available for the year 2013: Andorra, Channel Islands, Faeroe Islands, Greenland, Isle of Man, Liechtenstein, Monaco, and San Marino.

[2] The United Nations System of National Accounts (SNA): http://unstats.un.org/unsd/nationalaccount/

[3] GDP per capita figures at PPP are from the World Bank, World Development Indicators http://data.worldbank.org/products/wdi

[4] This means that there would be no effective change in the rankings of countries in Europe by GDP size as a result of rebasing.

[5] No Shadow Economy data was available for the following countries: Kosovo, Montenegro, and Serbia.




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