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World Competitiveness Ranking

A comprehensive annual report and worldwide reference point on the competitiveness of countries

World Competitiveness Ranking

A comprehensive annual report and worldwide reference point on the competitiveness of countries

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World Competitiveness Ranking

The IMD World Competitiveness Yearbook (WCY), first published in 1989, is a comprehensive annual report and worldwide reference point on the competitiveness of countries. It provides benchmarking and trends, as well as statistics and survey data based on extensive research. It analyzes and ranks countries according to how they manage their competencies to achieve long-term value creation. An economy’s competitiveness cannot be reduced only to GDP and productivity because enterprises also have to cope with political, social and cultural dimensions. Governments therefore need to provide an environment characterized by efficient infrastructures, institutions, and policies that encourage sustainable value creation by enterprises.

The IMD World Competitiveness Ranking emphasizes a long-term trend highlighted in past editions – that the countries on the top of the list each have a unique approach to becoming competitive.

The Yearbook provides extensive coverage of 64 economies, chosen based on the availability of comparable international statistics and our collaboration with local Partner Institutes, which contribute to the collection of survey data and ensure that all data are reliable, accurate and as up-to-date as possible. This year, we have the privilege of collaborating with a unique global network of Partner Institutes in 57 countries.

The World Competitiveness Ranking is based on 336 competitiveness criteria selected as a result of comprehensive research using economic literature, international, national, and regional sources, and feedback from the business community, government agencies, and academics. The criteria are revised and updated regularly as new theories, research, and data become available and as the global economy evolves.

 - IMD Business School
World Competitiveness Ranking 2023 Results

Agile governance and good access to markets boost citizens’ quality of life, says new IMD research

IMD’s World Competitiveness Center’s latest report on global economic competitiveness gives leaders guidance for navigating a “fragmented” world

Denmark, Ireland and Switzerland have been named the top three among 64 economies measured for their global competitiveness in the 2023 IMD World Competitiveness Ranking, published today by the World Competitiveness Center for the 35th consecutive year.

Denmark maintained its grip on first place from last year, when it enjoyed a momentous inaugural rise to the top, Ireland made a remarkable leap from 11th to take second place, and Switzerland held its nerve in third, after dropping from second place in 2022 and first place in 2021.

All three are small economies that make good use of their access to markets and trading partners – as does Singapore, which came fourth.

Rankings full list of results

2023

Country

2022

Ranking Change

01

Denmark

01

02

Ireland

11

+9

03

Switzerland

02

-1


04

Singapore

03

-1

05

Netherlands

06

+1

06

Taiwan, China

07

+1

07

Hong Kong SAR

05

-2

08

Sweden

04

-4

09

USA

10

+1

10

UAE

12

+2

11

Finland

08

-3

12

Qatar

18

+6

13

Belgium

21

+8

14

Norway

09

-5

15

Canada

14

-1

16

Iceland

16

17

Saudi Arabia

24

+7

18

Czech Republic

26

+8

19

Australia

19

20

Luxembourg

13

-7

21

China

17

-4

22

Germany

15

-7

23

Israel

25

+2

24

Austria

20

-4

25

Bahrain

30

+5

26

Estonia

22

-4

27

Malaysia

32

+5

28

Korea Rep.

27

-1

29

United Kingdom

23

-6

30

Thailand

33

+3

31

New Zealand

31

32

Lithuania

29

-3

33

France

28

-5

34

Indonesia

44

+10

35

Japan

34

-1

36

Spain

36

37

Kazakhstan

43

+6

38

Kuwait


39

Portugal

42

+3

40

India

37

-3

41

Italy

41

42

Slovenia

38

-4

43

Poland

50

+7

44

Chile

45

+1

45

Cyprus

40

-5

46

Hungary

39

-7

47

Turkey

52

+5

48

Romania

51

+3

49

Greece

47

-2

50

Croatia

46

-4

51

Latvia

35

-16

52

Philippines

48

-4

53

Slovak Republic

49

-4

54

Jordan

56

+2

55

Peru

54

-1

56

Mexico

55

-1

57

Bulgaria

53

-4

58

Colombia

57

-1

59

Botswana

58

-1

60

Brazil

59

-1

61

South Africa

60

-1

62

Mongolia

61

-1

63

Argentina

62

-1

64

Venezuela

63

-1

Overall and Factor Rankings – Five years
Overall

Country

2019

2020

2021

2022

2023

Argentina

61

62

63

62

63

Australia

18

18

22

19

19

Austria

19

16

19

20

24

Bahrain

30

25

Belgium

27

25

24

21

13

Botswana

61

58

59

Brazil

59

56

57

59

60

Bulgaria

48

48

53

53

57

Canada

13

8

14

14

15

Chile

42

38

44

45

44

China

14

20

16

17

21

Colombia

52

54

56

57

58

Croatia

60

60

59

46

50

Cyprus

41

30

33

40

45

Czech Republic

33

33

34

26

18

Denmark

08

02

03

01

01

Estonia

35

28

26

22

26

Finland

15

13

11

08

11

France

31

32

29

28

33

Germany

17

17

15

15

22

Greece

58

49

46

47

49

Hong Kong SAR

02

05

07

05

07

Hungary

47

47

42

39

46

Iceland

20

21

21

16

16

India

43

43

43

37

40

Indonesia

32

40

37

44

34

Ireland

07

12

13

11

02

Israel

24

26

27

25

23

Italy

44

44

41

41

41

Japan

30

34

31

34

35

Jordan

57

58

49

56

54

Kazakhstan

34

42

35

43

37

Korea Rep.

28

23

23

27

28

Kuwait

38

Latvia

40

41

38

35

51

Lithuania

29

31

30

29

32

Luxembourg

12

15

12

13

20

Malaysia

22

27

25

32

27

Mexico

50

53

55

55

56

Mongolia

62

61

60

61

62

Netherlands

06

04

04

06

05

New Zealand

21

22

20

31

31

Norway

11

07

06

09

14

Peru

55

52

58

54

55

Philippines

46

45

52

48

52

Poland

38

39

47

50

43

Portugal

39

37

36

42

39

Qatar

10

14

17

18

12

Romania

49

51

48

51

48

Saudi Arabia

26

24

32

24

17

Singapore

01

01

05

03

04

Slovak Republic

53

57

50

49

53

Slovenia

37

35

40

38

42

South Africa

56

59

62

60

61

Spain

36

36

39

36

36

Sweden

09

06

02

04

08

Switzerland

04

03

01

02

03

Taiwan, China

16

11

08

07

06

Thailand

25

29

28

33

30

Turkey

51

46

51

52

47

UAE

05

09

09

12

10

United Kingdom

23

19

18

23

29

USA

03

10

10

10

09

Venezuela

63

63

64

63

64

Economic Performance

Country

2019

2020

2021

2022

2023

Argentina

61

60

59

57

59

Australia

14

23

19

16

10

Austria

20

15

20

24

22

Bahrain

39

23

Belgium

37

25

24

14

13

Botswana

62

60

62

Brazil

57

56

51

48

41

Bulgaria

47

34

41

49

48

Canada

12

10

14

10

09

Chile

48

50

53

50

52

China

02

07

04

04

08

Colombia

50

52

56

45

37

Croatia

55

45

50

32

46

Cyprus

19

13

13

38

47

Czech Republic

17

16

23

18

27

Denmark

26

21

17

13

15

Estonia

44

35

29

33

54

Finland

35

43

34

44

39

France

34

32

28

17

24

Germany

09

05

03

05

12

Greece

60

55

52

51

58

Hong Kong SAR

10

28

30

15

36

Hungary

46

19

08

08

21

Iceland

54

58

55

56

45

India

24

37

37

28

33

Indonesia

25

26

35

42

29

Ireland

06

12

22

07

01

Israel

40

39

36

36

31

Italy

53

42

39

41

44

Japan

16

11

12

20

26

Jordan

62

62

63

62

63

Kazakhstan

45

48

45

58

57

Korea Rep.

27

27

18

22

14

Kuwait

19

Latvia

52

53

44

54

55

Lithuania

39

33

33

43

49

Luxembourg

04

08

10

01

38

Malaysia

11

09

15

12

07

Mexico

28

38

49

27

30

Mongolia

58

59

58

61

60

Netherlands

13

01

02

19

11

New Zealand

36

40

32

47

50

Norway

32

30

25

25

17

Peru

41

51

60

40

53

Philippines

38

44

57

53

40

Poland

18

29

27

29

25

Portugal

43

41

43

46

42

Qatar

03

06

11

09

05

Romania

49

46

40

55

51

Saudi Arabia

30

20

48

31

06

Singapore

05

03

01

02

03

Slovak Republic

42

49

47

52

56

Slovenia

33

36

31

26

34

South Africa

59

61

61

59

61

Spain

29

31

42

35

32

Sweden

21

22

16

21

28

Switzerland

23

18

07

30

18

Taiwan, China

15

17

06

11

20

Thailand

08

14

21

34

16

Turkey

51

57

46

37

43

UAE

07

04

09

06

04

United Kingdom

22

24

26

23

35

USA

01

02

05

03

02

Venezuela

63

63

64

63

64

Government Efficiency

Country

2019

2020

2021

2022

2023

Argentina

61

63

64

63

64

Australia

13

15

16

16

18

Austria

28

25

29

34

36

Bahrain

20

20

Belgium

36

35

37

33

22

Botswana

42

41

37

Brazil

62

61

62

61

62

Bulgaria

42

39

47

49

55

Canada

14

10

15

18

16

Chile

26

20

22

30

32

China

35

37

27

29

35

Colombia

56

56

58

59

61

Croatia

58

59

57

46

49

Cyprus

32

21

25

24

30

Czech Republic

34

36

36

22

17

Denmark

06

04

07

06

05

Estonia

27

19

18

15

15

Finland

17

16

14

10

13

France

48

46

39

40

47

Germany

22

24

23

21

27

Greece

60

52

52

55

53

Hong Kong SAR

01

01

01

02

02

Hungary

45

47

40

37

40

Iceland

15

17

17

14

19

India

46

50

46

45

44

Indonesia

25

31

26

35

31

Ireland

11

13

13

11

03

Israel

30

27

33

32

34

Italy

53

57

55

54

56

Japan

38

41

41

39

42

Jordan

43

45

35

44

41

Kazakhstan

21

29

21

25

23

Korea Rep.

31

28

34

36

38

Kuwait

26

Latvia

33

32

32

28

39

Lithuania

29

33

31

23

33

Luxembourg

10

12

10

13

10

Malaysia

24

30

30

38

29

Mexico

52

55

59

60

60

Mongolia

59

53

54

57

58

Netherlands

09

11

12

12

12

New Zealand

08

08

11

17

21

Norway

07

06

04

05

09

Peru

49

40

48

52

50

Philippines

41

42

45

48

52

Poland

44

43

56

56

54

Portugal

37

34

38

43

43

Qatar

05

07

06

07

04

Romania

51

49

44

47

46

Saudi Arabia

18

22

24

19

11

Singapore

03

05

05

04

07

Slovak Republic

57

60

51

51

48

Slovenia

39

38

43

42

45

South Africa

50

54

61

53

59

Spain

40

44

49

50

51

Sweden

16

14

09

09

14

Switzerland

04

02

02

01

01

Taiwan, China

12

09

08

08

06

Thailand

20

23

20

31

24

Turkey

55

51

60

58

57

UAE

02

03

03

03

08

United Kingdom

19

18

19

26

28

USA

23

26

28

27

25

Venezuela

63

62

63

62

63

Business Efficiency

Country

2019

2020

2021

2022

2023

Argentina

59

62

63

63

63

Australia

24

21

34

26

30

Austria

17

16

18

18

26

Bahrain

24

22

Belgium

28

22

20

19

05

Botswana

61

57

50

Brazil

57

47

49

52

61

Bulgaria

54

53

59

59

62

Canada

16

10

16

13

17

Chile

41

37

40

41

45

China

15

18

17

15

21

Colombia

47

52

51

60

59

Croatia

63

63

64

49

56

Cyprus

52

35

43

44

55

Czech Republic

37

38

41

29

15

Denmark

07

01

01

01

01

Estonia

33

27

31

22

25

Finland

13

13

12

05

09

France

38

43

36

35

39

Germany

26

25

23

21

29

Greece

58

51

44

46

48

Hong Kong SAR

02

02

03

07

11

Hungary

56

59

56

48

58

Iceland

19

15

14

08

10

India

30

32

32

23

28

Indonesia

20

31

25

31

20

Ireland

03

05

11

11

03

Israel

21

26

29

27

24

Italy

42

45

35

34

38

Japan

46

55

48

51

47

Jordan

35

46

33

45

36

Kazakhstan

29

34

28

32

31

Korea Rep.

34

28

27

33

33

Kuwait

42

Latvia

43

44

42

37

57

Lithuania

23

24

30

25

27

Luxembourg

12

17

13

20

19

Malaysia

18

29

24

38

32

Mexico

49

48

47

47

51

Mongolia

61

57

60

61

64

Netherlands

04

04

04

03

02

New Zealand

22

30

22

36

35

Norway

08

08

06

10

18

Peru

55

50

53

53

53

Philippines

32

33

37

39

40

Poland

36

40

57

58

43

Portugal

45

41

38

42

41

Qatar

10

11

15

14

12

Romania

51

54

52

50

49

Saudi Arabia

25

19

26

16

13

Singapore

05

06

09

09

08

Slovak Republic

60

61

55

54

52

Slovenia

40

39

45

43

46

South Africa

44

56

58

56

54

Spain

39

42

39

40

37

Sweden

06

03

02

02

06

Switzerland

09

09

05

04

07

Taiwan, China

14

12

07

06

04

Thailand

27

23

21

30

23

Turkey

48

36

46

55

44

UAE

01

07

08

17

16

United Kingdom

31

20

19

28

34

USA

11

14

10

12

14

Venezuela

62

60

62

62

60

Infrastructure

Country

2019

2020

2021

2022

2023

Argentina

51

52

56

54

56

Australia

17

18

23

19

20

Austria

11

10

12

10

15

Bahrain

39

37

Belgium

21

19

19

20

10

Botswana

63

61

61

Brazil

54

53

52

53

55

Bulgaria

50

50

54

51

54

Canada

12

08

08

11

11

Chile

47

45

45

47

46

China

16

22

18

21

21

Colombia

56

56

53

56

57

Croatia

49

48

50

45

45

Cyprus

42

38

41

40

42

Czech Republic

31

32

31

28

24

Denmark

03

02

03

02

02

Estonia

34

33

30

27

29

Finland

05

04

05

04

03

France

09

13

15

15

17

Germany

10

11

10

09

14

Greece

41

39

39

41

40

Hong Kong SAR

22

14

16

14

13

Hungary

39

41

37

36

38

Iceland

13

17

09

08

07

India

55

49

49

49

52

Indonesia

53

55

57

52

51

Ireland

23

23

20

23

19

Israel

18

20

21

17

18

Italy

32

30

29

31

30

Japan

15

21

22

22

23

Jordan

58

58

55

55

53

Kazakhstan

43

51

47

46

47

Korea Rep.

20

17

16

16

16

Kuwait

49

Latvia

35

37

35

35

41

Lithuania

30

34

34

32

31

Luxembourg

25

24

24

24

25

Malaysia

28

31

32

37

35

Mexico

57

57

58

58

59

Mongolia

62

62

62

62

63

Netherlands

08

09

07

05

05

New Zealand

24

25

25

29

28

Norway

07

06

04

06

08

Peru

61

60

60

59

60

Philippines

59

59

59

57

58

Poland

36

35

42

43

39

Portugal

29

27

27

30

32

Qatar

40

40

40

38

33

Romania

48

47

48

48

50

Saudi Arabia

38

36

36

34

34

Singapore

06

07

11

12

09

Slovak Republic

44

46

44

42

44

Slovenia

27

29

33

33

36

South Africa

60

61

61

60

62

Spain

26

26

26

25

27

Sweden

04

01

02

03

04

Switzerland

02

03

01

01

01

Taiwan, China

19

15

14

13

12

Thailand

45

44

43

44

43

Turkey

46

43

46

50

48

UAE

33

28

28

26

26

United Kingdom

14

12

13

18

22

USA

01

05

06

07

06

Venezuela

63

63

64

63

64

World Competitiveness Booklet 2023

Browse this summary of the full report

Competitiveness Country Profiles

Summary country profiles are available in the free version of IMD World Competitiveness Online for all 64 countries covered in 2023 (+ Russia and Ukraine for 2021), including the Competitiveness, Digital, and Talent rankings. Discover the profiles in our online database:

Methodology and principles of analysis

Below is an explanation of the methodology used by the IMD World Competitiveness Center to develop the IMD World Competitiveness Ranking, the IMD World Digital Competitiveness Ranking, and the IMD World Talent Report. Although the methodology is intended to be general, ranking-specific examples are mentioned throughout. This does not mean, however, that the principle under discussion is not applicable to the other rankings. The specificities of each ranking are introduced in the tables, as indicated.

 

How does the IMD World Competitiveness Yearbook measure competitiveness?

Over the past two decades, the methodology used to assess the competitiveness of countries has been fine-tuned to take into account the evolution of the global environment and new research. In this way, the WCY keeps pace with structural changes in national environments and the rapidly changing technological revolution. We make these changes gradually so that we can preserve the comparability of results from year to year and highlight the evolution of an economy’s performance relative to the competitiveness of others.

Based on analysis made by leading scholars and on our own research, all criteria is grouped into sub-factors. Each sub-factor does not necessarily include the same number of criteria (for example, it takes more criteria to assess Education than to evaluate Prices). Sub-factors, irrespective of the number of criteria they contain, have the same weight in the overall consolidation of results.

In the case of the World Competitiveness Ranking, for example, the weight of each sub-factor is 5% (20 x 5 = 100). This allows us to “lock” the weight of the sub-factors regardless of the number of criteria they include. We believe that this approach improves the reliability of the results and helps ensure a high degree of compatibility with past results. Statistics are sometimes prone to errors or omission, locking the weights of sub-factors has the same function as building “fire barriers”; it prevents problems from spreading in a disproportionate way.

The WCY uses different types of data to measure quantifiable and qualitative issues separately. Statistical indicators are acquired from international, national and regional organizations, private institutions and our Partner Institutes. These statistics are referred to in the WCY as hard data. The hard data represent a weight of two-thirds in the overall rankings.

Additional criteria are drawn from our annual Executive Opinion Survey and are referred to in the WCY as survey data. The survey questions are included in the Yearbook as individual criteria and are also used to calculate the overall rankings, representing a weight of one-third.

Executive Opinion Survey

Our Executive Opinion Survey complements the statistics we use from international, national, and regional sources. While the hard data show how competitiveness is measured over a specific period of time, the survey data measures competitiveness as it is perceived by market participants.

The survey is designed to quantify issues that are not easily measured, for example: management practices, corruption, adaptive attitudes, and the agility of companies. The survey responses reflect present and future perceptions of competitiveness by business executives who are dealing with international business situations. Their responses are more recent and closer to reality since there is no time lag with the year under consideration, which is often a problem with hard data, which show a “picture of the past.”

The Executive Opinion Survey is sent to mid- and upper-level managers in all the economies studied. The sample of respondents is representative of the entire economy, covering a cross-section of the business community in all economic sectors. In order to be statistically representative, we select a sample size that is proportional to the GDP breakdown of economic sectors of the economy.

The survey respondents are nationals or expatriates, in domestic or international enterprises who have resided at least a year in the economy under consideration. They are asked to evaluate the present and future competitiveness conditions of the economy in which they work, drawing from their domestic and international experience.

The online survey takes place from end of February to beginning of May. All responses are treated as confidential. In 2023, we received 6,400 responses from the 64 economies worldwide. The respondents assess the competitiveness issues by answering the questions on a scale of 1 to 6. The average value for each economy is then calculated and converted into a 0 to 10.

How are the rankings calculated?

The essential building block for the rankings is the standardized value for all the criteria (i.e., STD value). The first step is to compute the STD value for each criterion using the data available for all the economies (see the next section Data Processing Methodology for more detail). We then rank the economies based on the criteria that are used in the aggregation: a combination of hard and survey data.

Additional criteria are presented for background information only; they are not included in the aggregation of data to determine the overall rankings. Details on the type and number of criteria used in the calculation of each of the rankings are presented in the table below. In most cases, a higher value is better, for example, for Gross Domestic Product; the economy withthe highest standardized value is ranked first while the one with the lowest is last. However, for some criteria the inverse may be true, where the lowest value is the most competitive, for example, Software Piracy. In these cases, a reverse ranking is used: the economy with the highest standardized value is ranked last and the one with the lowest is first.

Ranking/Report

Hard Data

Survey

Background information

Total ranked criteria

World Competitiveness 2023

164

92

80

336

World Digital Competitiveness 2022

34 

20

3

57

World Talent 2022

 14

17

34

Data Processing Methodology

Standard Deviation Method

As distinct criteria exhibit different scales and units, a comparable standard measure – the Standard Deviation Method (SDM) – is used to compute the overall, factor and sub-factor results. It measures the relative difference between the economies’ performances, resulting in a more accurate assessment of each country’s relative position in the final rankings.

First, for each criterion, we compute the average value for the entire population of economies. Then, the standard deviation is calculated using the following formula:

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x = original value
x ̅= average value of all the economies
N = number of economies
S = standard deviation

Subsequently, we compute each of the economies’ STD values for the all the ranked criteria. The STD is calculated by subtracting the average value of the 64 economies from the economy’s original value and then dividing the result by the standard deviation.

The STD value for criteria i is calculated as follows:

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x = original value
x ̅= average value of all the economies
N = number of economies
S = standard deviation

Subsequently, we compute each of the economies’ STD values for the all the ranked criteria. The STD is calculated by subtracting the average value of the 64 economies from the economy’s original value and then dividing the result by the standard deviation.

The STD value for criteria i is calculated as follows:

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Aggregation of Data and Rankings
In the WCY some criteria are provided as background information only and are not included in the determination of the rankings. Some background data, however, are presented in ranking order while others are shown alphabetically.

STD values are calculated for each individual criterion, based on the STD method described above. All hard data indicators are reviewed to determine the shape of the distribution. Non-normally distributed data is normalized by taking the log. The STD is then calculated using the logged values.

The sub-factor rankings are determined by calculating the average of the STD values of all criteria comprising the sub-factor. All the hard data have a weight of 1. The survey data are weighted so that the survey accounts for one- third in the determination of the overall ranking. When data are unavailable for a particular economy, the missing values are replaced by STD values that are imputed from the average of existing data within the sub-factor. Taking the average for each sub-factor enables us to “lock”

the weight of all the sub-factors irrespective of the number of criteria they contain so that each sub-factor has an equal impact on the overall rankings.

Next, we aggregate the sub-factor STD values to determine the factor rankings. Only ranked criteria are aggregated to obtain these rankings. The STD values of the factors are then aggregated to determine the overall rankings. All the ranked criteria comprised in the factors are thus included in the consolidation of data.

Since all the statistics are standardized, they can be aggregated to compute indices. We use these index values, which we call “scores,” to compute the Factors and the Overall Rankings. It should be noted that across the factors, only one economy has a value equal to 100 and one economy a value equal to 0. To calculate the overall rankings, we take the average of the factors’ scores of the respective ranking (Competitiveness, Digital or Talent) and then convert them into an index with the leading economy given a value of 100.

Survey Criteria
Each year we conduct a survey to quantify issues related to competitiveness for which there are no hard statistics. The survey is an in- depth 92-point questionnaire sent to middle and upper level managers in the economies included in the rankings. The distribution reflects a breakdown of industry by sectors: primary, industry/manufacturing and services/finance.

In 2023 we received 6,400 responses for an average of approximately 100 replies per economy. The target list is determined by IMD and has been developed over many years with the collaboration of our Partner Institutes worldwide. Confidentiality is ensured and the list is updated every year. Respondents answer only for the economy in which they have worked and resided in the past year. Results, therefore, reflect widespread knowledge about each economy and draw on the wealth of their international experience.

The respondents assess the competitiveness issues by answering the questions on a scale of 1-6, with 1 indicating a negative perception and 6 indicating the most positive perception. The WCY calculates the average value for each economy, then the data is converted from a1-6 scale to a 0-10 scale, using the formula below.

Finally, the survey responses are transformed into their standard deviation values, from which the rankings are calculated.

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where X = average value.

Trends
A trend or growth rate offers a more dynamic assessment than absolute values. The formulas used to calculate trends and growth rates are explained below:

1. Annual real growth rate (i = inflation rate):

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2. Average annual percentage growth rate (n = number of periods):

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Growth formulas, however, may have shortcomings. The average annual growth rate fails to reveal the real extent of changes, as it flattens or inflates year-to-year growth rates. For example, an average growth rate over two years might be calculated at 15%, while in reality there was 5% growth between the first and second years, and 25% between the second and third years. The average annual growth is used only when data vary widely in the middle years of a period, and less widely between the first and last years of the period. It is also used in cases where it is impossible to combine negative and positive initial and final values. This approach gives a more accurate picture than the compound rate under these circumstances.

 

Deflated Values
The following formula is used when calculating real growth rates from nominal values, because it takes into account cumulative inflation (e.g., real growth in Household Consumption Expenditure). The final deflated value is then used to obtain the annual real growth rate.

Taking a five-year time span as an example: Deflated final value (i = inflation rate):

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