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3 Vietnam’s agricultural trade competitiveness by the NRCA

3 Vietnam’s agricultural trade competitiveness by the NRCA

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competitive sectors (0.07 ≥ NRCA values > 0). These results, in general, are different to

those of the RCA and the RTA indices.

Table 4-13: Vietnam’s top agricultural trade competitiveness by the NRCA

No.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27



Code

071

042

036

034

037

057

231

075

246

054

074

265

035

046

411

058

245

062

264

244

261

047

122

223

061

045

212



Commodity

Coffee,coffee substitute

Rice

Crustaceans,molluscs etc

Fish,fresh,chilled,frozn

Fish etc.prepd,prsvd.nes

Fruit,nuts excl.oil nuts

Natural rubber, etc.

Spices

Wood in chips, particles

Vegetables

Tea and mate

Vegetable textile fibres

Fish,dried,salted,smoked

Meal,flour of wheat,msln

Animal oils and fats

Fruit,preserved,prepared

Fuel wood, wood charcoal

Sugar confectionery

Jute,oth.textl.bast fibr

Cork, natural, raw; waste

Silk

Other cereal meal,flours

Tobacco, manufactured

Oilseed(oth.fix.veg.oil)

Sugars,molasses,honey

Other cereals, unmilled

Furskins, raw

Max

Average

Competitive sectors



NRCA

(1997)

0.88

1.61

0.98

0.11

0.18

0.14

0.34

0.15

0.02

0.02

0.08

0.00

0.03

-0.01

-0.01

0.09

0.01

-0.01

0.00

0.00

0.01

0.00

-0.06

0.00

-0.03

0.00

0.00

1.61

0.07

22.00



NRCA

(2014)



NRCA

(1997-2014)



1.76

1.48

1.45

1.18

0.96

0.94

0.83

0.68

0.57

0.26

0.09

0.02

0.01

0.01

0.01

0.00

0.00

0.00

0.00

0.00

0.00

-0.01

-0.01

-0.01

-0.02

-0.02

-0.02

1.76

0.11

19.00



1.08

1.49

1.50

0.72

0.32

0.48

0.73

0.27

0.17

0.06

0.09

0.01

0.05

0.00

0.00

0.02

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.01

-0.02

-0.01

-0.01

1.50

0.09

22.00



Source: Own calculation based on the data of UN Comtrade (2017)

Vietnam, in overall, obtains strong comparative advantages in fishery sectors such as

fish and crustaceans; and crop sectors such as rice, coffee, tea, spices, fruit & nuts, and

vegetables whilst it has comparative disadvantage in livestock sectors such as live



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animal, meat, and eggs & birds; and processed food sectors such as butter, cheese,

chocolate, and other processed foods.

4.3.2 Analyzing the dynamics of of the NRCA indicators

The changes of the NRCA indicators between 1997 and 2014

There are significant changes of the NRCA values between 1997 and 2014. Vietnam

achieves the growing competitiveness in 17 sectors while it incurs the losing

competitiveness in 44 sectors. The top competitiveness increasing sectors are

fish,fresh,chilled,frozn; coffee,coffee substitute; fruit,nuts excl.oil nuts, while the top

competitiveness decreasing sectors oilseed; other meat,meat offal; edible prod.preprtns.

There are three agricultural sectors reversely moving up and five agricultural sectors

reversely moving down. (Table 4-14).

Table 4-14: The changes of the NRCA indicator ranks between 1997 and 2014

Top Increase

Fish,fresh,chilled,frozn

Coffee,coffee substitute

Fruit,nuts excl.oil nuts

Fish etc.prepd,prsvd.nes

Wood in chips, particles



Top Decrease

Oilseed(sft.fix veg.oil)

Other meat, meat offal

Edible prod.preprtns,nes

Alcoholic beverages

Fixed veg.fat,oils,other



Up Reversion

Meal,flour of wheat,msln

Animal oils and fats

Sugar confectionery



Down Reversion

Oilseed(sft.fix veg.oil)

Edible prod.preprtns,nes

Fixed veg.fat,oils,other

Crude animal materls.nes

Eggs,birds,yolks,albumin



Source: Own calculation based on the data of UN Comtrade (2017)

The general pattern of the NRCA indicators by the OLS method

The regression results for the NRCA dynamics in three periods 1997-2005, 20062014, and 1997-2014 bring in the values of  > 1 and /R > 1. These results satisfy both

necessary and sufficient conditions to confirm that Vietnam has the increase in the

overall specialization trade pattern. In other words, the result explains that Vietnam

gains the increasing competitiveness in the initial strong competitive sectors whilst it

loses the competitiveness in the initial weak competitive sectors. The agricultural

competitiveness pattern of the country, thus, has a divergent pattern over all periods

(Table 4-15). This result of the NRCA is different to those of the RCA and the RTA.

The mobility and stability of the NRCA indicators by Markov matrix



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The stability and mobility analysis of the NRCA indicators by Markov transition

probability matrix requires the classifications of the competitiveness values. This study

employs quartile method to group the NRCA values of 1,037 observations in 18 years

into four classes (Table 4-16). The neutral point value of zero is remained in class 1; the

class 2 includes the values from zero to quartile 2; the class 3 is from quartile 2 to

quartile 3; and the class 4 is higher than quartile 3. Let 𝑝𝑖𝑗 (i, j = 1, 2, 3, 4) denotes a

one-step transition probability. It is, specifically, the transition or mobility probability

for a commodity to move from the class i of year t to the class j of year (t +1).

Table 4-15: The OLS estimation results for the NRCA indicators over time

β

1.05



1997 - 2005

R

0.91



β/R

1.15



β

1.36



2006-2014

R

0.92



β/R

1.48



1997 - 2014

R

0.81



β

1.34



β/R

1.67



Source: Own calculation based on the data of UN Comtrade (2017)

Table 4-16: The classification of the of NRCA values and the interpretations

Categories

Class 1

Class 2

Class 3

Class 4



Interpretation

Non-competitiveness

Weak competitiveness

Medium competitiveness

Strong competitiveness



NRCA values

≤0

≤ 0.067

≤ 0.478

> 0.478



Source: Own calculation based on the data of UN Comtrade (2017)

Table 4-17: The Markov transition probability matrix for the NRCA indicators

M-Shorrocks

0.17

Stability

87.04

Mobility

4.32



Obs: 1,037

Class 1

Class 2

Class 3

Class 4

Total

Long run



Class 1

94.89

20.79

1.1

0

66.35

64.10



Class 2

4.96

73.03

12.09

0

16.88

3.73



Class 3

0.15

6.18

80.22

0

8.2

3.87



Class 4

0

0

6.59

100

8.58

28.39



Source: Own calculation based on the data of UN Comtrade (2017)

The diagonal elements of the matrix indicate the stability of sectors persistently

remaining in their initial classes. The result shows high stabilities in the NRCA

indicators over time. The sectors in class 1 and class 4 obtain the highest probabilities of

stabilities (97.56 and 100 percent). In other words, this result confirms that the initial

weakest competitive agricultural sectors steadily continue to stay in their ranks over the



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period and the strongest competitive agricultural sectors perfectly remain in their initial

positions. The off-diagonal terms of the matrix, namely the probability of moving from

one class to another from the year “t” to the year “t+1”, provides further information on

the mobility of the NRCA values. The strong competitiveness sectors (class 4) perfectly

persist in their initial class. No agricultural sector moves from class 4 backwards class 1,

2 and 3 as well as from class 1, 2 forward class 4. Another finding is that the movements

from stronger classes back to weaker classes have greater probability than from the

weaker classes to the stronger classes (Table 4-17). The average probability of stability

or diagonal elements is 87.04 whilst the average value of mobility or off-diagonal

elements is only 4.32 percent. M-Shorrocks index of 0.17 confirms a low degree of

mobility of the NRCA indicators. The total probability result shows that there is the

highest probability of the NRCA values moving to class 1 with 66.35 percent and the

lowest probability of the NRCA values moving to class 3 with 8.2 percent (Table 4-17).

Table 4-18: The top gaining and losing trends of the NRCA indicators

Code

034

231

071

037

057

246

075

098

041

112

422

022

012

222



Commodity

Fish,fresh,chilled,frozn

Natural rubber,etc.

Coffee,coffee substitute

Fish etc.prepd,prsvd.nes

Fruit,nuts excl.oil nuts

Wood in chips,particles

Spices

Edible prod.preprtns,nes

Wheat,meslin,unmilled

Alcoholic beverages

Fixed veg.fat,oils,other

Milk and cream

Other meat,meat offal

Oilseed(sft.fix veg.oil)

Gaining trend groups

Losing trend groups





0.082

0.069

0.058

0.047

0.040

0.033

0.023

-0.008

-0.009

-0.009

-0.010

-0.012

-0.014

-0.022

14.00

37.00



p-value

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.002

0.000

0.000



R2

0.91

0.78

0.57

0.85

0.89

0.80

0.63

0.78

0.78

0.91

0.87

0.47

0.84

0.90



NRCA 1997

-0.03

-0.04

-0.03

-0.01

-0.01

-0.04

-0.01

-0.01

0.04

-0.01

-0.01

-0.04

0.02

-0.01



NRCA 2014

-0.10

-0.21

-0.31

-0.02

-0.09

-0.17

-0.04

-0.03

-0.03

-0.13

0.01

-0.09

-0.15

-0.05



Source: Own calculation based on the data of UN Comtrade (2017)

The trends of the NRCA indicators

The trend analysis result of the NRCA values over the period 1997-2014 illustrates

that Vietnam obtains the gaining trends in 14 agricultural sectors with β > 0 and the



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country has the losing trends in 37 agricultural sectors with β < 0. The country has the

most increasing comparative advantages in fish,fresh,chilled,frozn; natural rubber;

coffee, coffee substitute; fish etc.prepd,prsvd.nes; and fruit,nuts excl.oil nuts. The result

also helps to predict that Vietnam might continue to obtain the stronger comparative

advantage in these sectors during this period and in the future. Conversely, Vietnam has

the most decreasing comparative advantages in oil-seeds; other meat,meat offal; milk

and cream; fixed veg.fat,oils,other; and alcoholic beverages and these sectors could

continue to lose their comparative advantages in the future (Table 4-18).

4.4 The consistencies of the trade performance indices: sector-ranking

The sector-ranking consistency tests for the RCA, RTA, and NRCA indices as

cardinal, ordinal and dichotomous measures indicate the general differences and

similarities of these indicators in assessing the competitiveness. The result, generally,

shows in Table 4-19 that these indices are strongly consistent as cardinal and

dichotomous measures while they are averagely consistent as ordinal measures. This

means that the counting both export and import data in the RTA may not significantly

impact on identifying the degrees of the agricultural competitiveness and determining

whether a country obtains the competitiveness in an agricultural sector while the

counting may relatively change the competitiveness rankings of the agricultural sectors.

Specifically, as cardinal measures, the correlation coefficients of the RCA & the

RTA, the RCA & the NRCA, the RTA & the NRCA are relatively high with the average

coefficient values of 0.96, 0.86, and 0.83, respectively. This means that the RCA & the

RTA are extremely consistent as cardinal measures and the RCA & the NRCA, the RTA

& the NRCA are strongly consistent as cardinal measures to identify and explain the

degrees and structures of the agricultural competitiveness. The strongest consistencies

are between the RCA & the RTA in 1997, 2000, and 2002 with the coefficient values of

more than 0.98. As ordinal measures, the correlation coefficients of the RCA & the

RTA, the RTA & the NRCA are low while the correlation coefficient of the RCA & the



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NRCA is relatively high with the mean coefficient values of 0.65, 0.66, and 0.75,

respectively. This means that the RCA & the NRCA are strongly consistent while the

RTA & the RCA, the RTA & the NRCA are weakly consistent as ordinal measures to

rank and explain the positions and structures of the agricultural competitiveness. The

weakest consistencies are between the RCA & the RTA in 2003 and 2006 with the

coefficient values of 0.60 and 0.57. As dichotomous measures, the RCA & the NRCA

are perfectly consistent with the matching shares of 1 due to the derivation of the NRCA

from the neutral-point of the RCA. The consistencies between the RTA & the RCA, the

RTA & the NRCA are relatively strong and similar with the same matching shares in all

years. This means that the RCA & the NRCA are perfectly consistent and the RTA &

the RCA, the RTA & the NRCA are strongly consistent as dichotomous measures to

determine whether a country has competitiveness in an agricultural sector and explain

that competitiveness structures.

Table 4-19: The consistencies the RCA, the RTA, and the NRCA by sector-ranking



Year

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Average



RCA

RTA

0.98

0.96

0.97

0.98

0.96

0.98

0.97

0.94

0.94

0.96

0.97

0.96

0.96

0.93

0.95

0.94

0.92

0.94

0.96



Cardinal

RCA

RTA

NRCA

NRCA

0.91

0.90

0.94

0.91

0.91

0.90

0.78

0.79

0.85

0.84

0.84

0.84

0.87

0.87

0.88

0.84

0.89

0.84

0.88

0.84

0.89

0.86

0.91

0.88

0.87

0.84

0.88

0.82

0.81

0.77

0.81

0.76

0.79

0.72

0.79

0.73

0.86

0.83



RCA

RTA

0.79

0.64

0.64

0.64

0.70

0.63

0.60

0.62

0.61

0.57

0.63

0.67

0.65

0.65

0.62

0.63

0.63

0.68

0.65



Ordinal

RCA

NRCA

0.75

0.65

0.71

0.79

0.81

0.82

0.80

0.74

0.79

0.79

0.78

0.75

0.73

0.75

0.78

0.72

0.72

0.68

0.75



RTA

NRCA

0.72

0.63

0.61

0.70

0.63

0.63

0.60

0.63

0.61

0.62

0.66

0.68

0.70

0.71

0.69

0.68

0.70

0.71

0.66



RCA

RTA

0.75

0.84

0.77

0.77

0.75

0.74

0.74

0.80

0.77

0.75

0.82

0.89

0.84

0.87

0.82

0.82

0.87

0.84

0.80



Source: Own calculation based on the data of UN Comtrade (2017)



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Dichotomous

RCA

RTA

NRCA

NRCA

1.00

0.75

1.00

0.75

1.00

0.77

1.00

0.77

1.00

0.75

1.00

0.74

1.00

0.74

1.00

0.80

1.00

0.77

1.00

0.75

1.00

0.82

1.00

0.89

1.00

0.84

1.00

0.87

1.00

0.82

1.00

0.82

1.00

0.87

1.00

0.84

1.00

0.80



103



CHAPTER 5:



THE ASEAN COUNTRIES’ AGRICULTURAL



TRADE PATTERNS: THE CROSS-COUNTRIES ANALYSIS

In order to understand the agricultural trade competitiveness pattern of Vietnam in

comparison with regional countries under the context of the global economic

integration, this chapter assesses the static agricultural competitiveness patterns of the

ASEAN countries by employing the RCA, the RTA, and the NRCA indices over the

period 1997-2015. The consistency between these indices is also tested by crosscountries in the case of the ASEAN countries. OLS method and Markov matrix are used

to analyze the dynamics of the competitiveness indicators over time. In order to

understand whether these countries are complementary or competing in the global

agricultural market, this section then investigate the agricultural trade complementarity

the ASEAN countries on the global agricultural market over the period 1997-2015 by

employing the TCI, the ESI, and Spearman’s rank correlation coefficients for

competitiveness indicators.

The results, generally, show that: (i) the ASEAN countries achieve the strongest

competitiveness in crop sectors, wood sectors, and fishery sectors such as rice, natural

rubber, spices, fixed vegetable fats and oils, wood in chips, fuel wood, fish, and

crustaceans. Vietnam, Thailand, and Indonesia are the strongest agricultural competitive

countries whilst Brunei, Singapore, and Cambodia are the weakest agricultural

competitive countries; (ii) the countries have the convergent patterns in agricultural

competitiveness except for Indonesia, Cambodia, and Brunei; and (iii) they successfully

maintain the rankings of the strong agricultural competitive sectors with the high

probabilities of these sectors to stay persistently in their initial class. The

competitiveness indices are strongly consistent as cardinal and dichotomous measures

whilst they are weakly consistent as ordinal measures; (iv) the ASEAN countries’

agricultural export patterns are weakly complementary in matching the regional import

demands; while (v) they are relatively complementary in exporting agricultural products



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to the world market; (vi) the countries’ agricultural competitiveness patterns are more

affected by and benefited from the global integration than the regional integration; and

(vii) the countries, moreover, tend to become more substitutable over time. The results

suggest that the ASEAN countries should cooperate and utilize the internal markets to

enhance the competitiveness and predominantly focus on the external markets.

In conclusion, though Vietnam has relatively strong competitiveness in agriculture it

is facing hard competitions from the regional countries such as Thailand and Indonesia

in both domestic and global markets. These competitions or substitutability in

agriculture seem to be increase over time. Therefore, the country should utilize its

strong competitive agricultural commodities such as wood in chips, spices, rice, natural

rubber, coffee, crustaceans, and fish to develop its market shares in the local and

regional markets. Moreover, Vietnam needs to enhance and take advantage of the

international economic relationships such as APEC, WTO, TPP-CPTPP, the ASEAN’s

relationships with India, Australia, China and bilateral trade agreements with United

States, Japan, Chile, Korea, Eurasian Economic Union, and European Communities to

expand its market shares on the world markets.

5.1 The agricultural international trade performance of ASEAN countries

5.1.1 Agricultural competitiveness by the RCA

In general, the ASEAN member countries have become more competitive in

agricultural sectors exporting to world markets over the regional economic integration

process with a growing number of competitive agricultural sectors (RCA > 1), namely,

86 competitive sectors in 1997 in comparison with 99 competitive sectors in 2015.

Cambodia, Indonesia, Malaysia, Philippines, and Thailand obtain more number of

agricultural competitive sectors while Singapore and Vietnam decrease the number of

competitive sectors. Brunei, especially, does not have comparative advantage in any

agricultural sectors. On the average of the period, Vietnam is the most competitive in

agriculture with 23 competitive sectors (accounting for 38 percent), followed by



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Indonesia and Thailand with 20 (accounting for 33 percent) and 18 competitive sectors

(accounting for 30 percent). In 2015, Indonesia becomes is the most competitive in

agriculture with 24 competitive sectors (accounting for 39 percent), followed by

Thailand and Vietnam with 20 (accounting for 33 percent) and 18 competitive sectors

(accounting for 30 percent). Vietnam obtains the highest mean values of RCA in 1997

and on the average, followed by Indonesia and Thailand while Indonesia has the highest

mean value in 2015, followed by Thailand and Vietnam. In 2015, natural rubber is the

strongest competitive sector on Cambodia and Thailand, and the rank is not changed

over the period; fixed veg.fat,oils,other is the strongest competitive sector of Indonesia

and Malaysia; while Philippines, Vietnam, Singapore, and Brunei achieve the strongest

competitiveness in fuel wood, wood charcoal; edible prod.preprtns,nes; wood in chips,

particles; and non-alcohol.beverage,nes, respectively. Vietnam, Thailand, and Indonesia

exhibit strong competitiveness in agricultural sectors whilst Brunei, Singapore, and

Cambodia incur the weak competitiveness in agricultural sectors. The ASEAN

countries, in overall, obtain the strong competitiveness in crop and crop processing

sectors, wood sectors, and fishery sectors such as rice, natural rubber, spices, fixed

vegetable fats and oils, wood in chips, fuel wood, fish, and crustaceans (Table 5-1).

Table 5-1: The agricultural competitiveness of the ASEAN countries by the RCA

RCA > 1

Brunei

Cambodia

Indonesia

Malaysia

Philippines

Singapore

Thailand

Vietnam



Strongest Sector



Max RCA



Mean RCA



1997



2015



Average



1997



2015



Average



1997



2015



Average



1997



2015



Average



0

3

13

11

12

7

18

22



0

5

24

13

15

4

20

18



0

4

20

12

14

3

18

23



111

231

231

422

422

075

231

042



111

231

422

422

245

098

231

246



111

231

422

422

422

075

231

042



0.1

9.0

27.0

29.6

17.1

5.8

30.6

66.3



0.2

23.7

52.3

23.0

13.6

2.0

29.6

18.2



0.1

14.7

37.6

28.8

10.2

2.7

31.6

36.5



0.01

0.30

1.92

1.61

1.12

0.46

2.29

3.72



0.02

0.90

3.08

1.50

1.03

0.24

2.05

1.81



0.01

0.51

2.39

1.56

0.88

0.29

2.22

3.06



Source: Own calculation based on the data of UN Comtrade (2017)

* The agricultural commodity code is presented in the Appendix 4.

The classification of weak, medium, and strong competitiveness is identified by

quartile method and the boundaries of un-competitiveness class and competitiveness



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class are remained for all ASEAN countries under study in every year. The

classification of the index is presented as follows: (i) the un-competitive class: RCA ≤ 1;

(ii) the weak competitive class: 1 < RCA ≤ 2.72; (iii) the medium competitive class:

2.72 < RCA ≤ 7.22; and (iv) the strong competitive class: RCA > 7.22. The result shows

that Indonesia, Vietnam, and Thailand achieve the most number of strong competitive

sectors; Malaysia, Philippines, and Cambodia gain some strong competitive sectors

while Singapore and Brunei have no strong competitive sector (Table 5-2).

Table 5-2: The number of strong agricultural competitive sectors by the RCA

1997

2015

Average



Brunei

0

0

0



Cambodia

1

2

2



Indonesia

5

7

7



Malaysia

4

2

3



Philippines

3

2

1



Singapore

0

0

0



Thailand

5

5

4



Vietnam

6

5

6



Source: Own calculation based on the data of UN Comtrade (2017)

5.1.2 Agricultural competitiveness by the RTA

The agricultural competitiveness of the ASEAN countries by the RTA index is

relatively different from by the RCA index. These countries, in general, decrease the

number of competitive agricultural sectors between 1997 and 2015. The ASEAN

countries obtain the competitiveness in 168 agricultural sectors in 1997 while they have

the competitiveness in only 148 agricultural sectors in 2015. In general, Thailand,

Vietnam, and Indonesia are still the strongest competitive countries in agricultural

sectors by the RTA index with the numbers of competitive sectors of 33, 37, and 25,

respectively in 2015. However, the high mean RTA value of 3.5 shows that Indonesia is

more specialized and the stronger competitive in agriculture than Thailand. Brunei,

Singapore, and Cambodia obtain the competitiveness in 2, 10, and 13 agricultural

sectors in 2015 and also become the weakest competitive countries in agriculture by the

RTA. The strongest agricultural sectors of the ASEAN countries are relatively similar

between the RCA and the RTA indices, excepting Brunei (Table 5-3).

The differences between the results of the RCA and the RTA significantly clarify the

role of import in the calculation and competitiveness explanation. The positions of the



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107



top strong competitiveness agricultural sectors of the ASEAN countries seem not to be

different between the RCA and RTA indices. This proves that the ASEAN countries

will specialize in producing and exporting the top strong competitiveness agricultural

commodities with the minimum or less imports of the similar agricultural products.

Table 5-3: The agricultural competitiveness of the ASEAN countries by the RTA

RTA > 1

Brunei

Cambodia

Indonesia

Malaysia

hilippines

Singapore

Thailand

Vietnam



Strongest Sector



Max RTA



Mean RTA



1997



2015



Average



1997



2015



Average



1997



2015



Average



1997



2015



Average



1

11

27

22

20

22

32

33



2

13

27

21

17

10

33

25



1

14

24

21

17

13

32

27



211

231

231

422

422

075

231

042



248

231

422

422

245

098

231

246



211

231

422

422

422

098

231

042



0.0

9.0

37.8

54.7

18.8

3.2

47.4

82.3



0.0

24.2

115.5

30.5

14.0

1.4

49.3

22.5



0.0

14.9

66.2

48.0

10.4

0.4

51.5

43.3



-1.8

-1.0

1.4

1.6

0.5

0.0

2.4

3.2



-1.8

-0.7

3.5

0.7

-0.2

-0.2

1.9

0.7



-2.1

-0.4

1.8

1.2

-0.1

-0.1

2.2

2.2



Source: Own calculation based on the data of UN Comtrade (2017)

* The agricultural commodity code is presented in the Appendix 5.

5.1.3 Agricultural competitiveness by NRCA index

The NRCA and the RCA present the same results of the numbers of competitive

sectors in the ASEAN countries. The only difference is the number of competitive

sectors in Vietnam on the average value due to the mean calculation of over period

1997-2015. This similarity can be explained by the nature on the NRCA formula

derived from the comparative-advantage-neutral point of the RCA index. The strongest

competitive sectors by the NRCA are, however, relatively different from those by the

RCA and the RTA. Indonesia, Malaysia, and Philippines achieve the strongest

competitiveness in fixed veg.fat,oils,other in 1997, 2015, and on the average while rice

and natural rubber, etc. are the strongest competitive sectors of Cambodia, Thailand, and

Vietnam. Brunei does not have the competitiveness in any agricultural sectors by the

NRCA index (Table 5-4).

In general, there are the relative similarities of the agricultural competitiveness

patterns among Indonesia, Malaysia, and Philippines with the strongest competitiveness

in 422, 425, and 245; among Vietnam, Thailand, and Cambodia with the strongest



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