As coming to Vietnamese culture, it refers to the culture of agriculture. Every country has agriculture, but the culture of agriculture is only in some Asian countries, including Vietnam. In the soul of the Vietnamese is always a pure soul and pure. In recent decades it seems that people are trying to change this with the "industrialization and modernization" movement, trying to force the Vietnamese people instead of using the advantages of cultivation, breeding become workers. When Vietnamese people's strengths are not used and promoted, they have to try or be forced to use their weakness. Thus, the failure is almost inevitable. This study examines the change in the interactions between agriculture, forestry and fisheries with other sectors of the economy based on the structure of the 2012 and 2016 Input Output (I/O) tables of Vietnam.

In recent years, the high GDP growth, along with falling in the share value-added of the agriculture, forestry and fishery sectors in GDP seems to be the trend in Vietnam. Vietnam’s government (in both central and local levels) encourages change economic structure following this trend. Therefore, the share of agriculture, forestry and fishery sectors in GDP decreases from 18.4% in 2010 to 15.3% in 2017, the figure for manufacturing, and construction sectors increase slightly while the figure for service sectors raises significantly (Table 1). Due to such orientation, the amount of investment in agriculture, forestry and fishery fell down, accounted for about 8% of the total investment in 2005, and only about 6% up to 2017, whereas the figure for industry& construction, and for services accounted for the similar amount, about 47% of total investment [1]. An industry considered to be of relative importance to the economy is the one with the good index of the power of dispersion and sensitivity of dispersion, and high spillover effect to value-added but low spillover effect to imports. The result from the Input-Output model shows that agriculture, forestry, and fishery sector is the only ones that meet this requirement. In this study, agriculture, forestry, fishery sector is divided into 11 sub-sectors (Appendix 1). The study also considers the relationship between 11 agriculture, forestry and fishery sub-sectors.

According to economic theory, the role of agriculture in economic growth has been emphasized by various studies since the 12th century [2,3]. Hwa performed a statistical analysis of the contribution of agriculture to economic growth. The author showed that existing the close relationship between agriculture and other sectors, it contributed to national and international economic growth. The most common use of the I/O model is to analyze the direct, indirect and spillover effects of the economy or a group of industries [4-7]. This study also attempts to show the interaction of eleven agriculture, forestry and fishery sub-sectors with other sectors surveyed in the model (Appendix 1).

W. Leontief put forward the linear function’s system for relationship between supply and demand of economy by sectors, solved at below:

?ⁿ_jXij + Yi = Xi                                                                                                   (1)

And        ?ⁿ_iXij + Vj = Xj                                                                                   (2)

Where: X_ij present sector j used product i as input; i,j = 1….n with n is number of sectors in input-output model; Yi is final product of product i; Xi is gross output of product i (total demand of product i) and Vj is value added of sector j.

Equation (3) shows: Total output = Intermediate demand (for production) + Final demand (for consumption)

Equation (4) shows: Total input = Intermediate input (for production) + Value added

Total output always equals to total input.

Put a_ij = X_ij/X_jand equation (1) we have:

?ⁿ_ja_ijX_j + Y_i = X_i                                                  (3)

Rewrite the equation (3) to matrix form:

A.X + Y = X                                                                                         (4)

With: A = (a_ij)_(nxn); Y = (Yi)_(nx1); X = (X_i)_(nx1). The equation (4) is Leontief’s standard, this equation can rewrite as follow:

X = (I – A)^-1.Y                                     

In this research the matrix A is divided by sub-matrixes including A^RR, A^RS, A^SRva A^SS

Where: R, S are industries; R is the industry is affected by increasing indirect tax; A^RR is the matrix of intermediate coefficients of r industry using its own product as input; A^RS is a matrix of intermediary coefficients for s industry using r product as input; A^SR is a matrix of intermediary coefficients for r industry using s product as input; A^SS is a matrix of intermediary coefficients for s industry using its own product as input

 We can rewrite Leontief’s relation:

                                      (5)

Or:

A^RR.X^R + A^RS.X^S + Y^R = X^R                                                                              (6)

A^SS.X^S + A^SR.X^R + Y^S = X^S                                                                                               (7)

From (6) and (7) we have:

XS = (I – A^SS)^-1.(A^SR.X^R + Y^R)                                                                         (8)

XR = (I – A^RR)^-1.(A^RS.X^S + Y^S)                                                                         (9)

Equation (8) and (9) shows that output of industry is not only based on the final demand but also depend on other sector’s productions. For example, ouput of R depend on S’s production by A^RS.X^S, or output of S (X^S) depend on R’s production by  A^SR.X^R.

Relationship between S and R can be shown:

X^S = (I – A^SS)-1.A^SR.X^R                                                                                      (10)

X^R = (I – A^RR)-1.A^RS.X^S                                                                                     (11)

Or

?X^S = (I – A^SS)^-1.A^SR.?X^R                                                                                  (12)

?X^R = (I – A^RR)^-1.A^RS.?X^S                                                                                 (13)

Equation (12), (13) show that the change in each industry can be led to the change in other industries. Matrix (I – A^SS)^-1.A^SR and (I – A^RR)^-1.A^RS show this relationship. This equation is applied to quantify the output of industries that are not directly affected by indirect tax increase are also reduced in the next production cycle.

In order to consider the effect of final demand of each industry to value added, we put:

B = =                (14)

                                                          (15)   

And

Or:

                       (16)

Equation (16) indicates the spillover effect of final demand of R and S on value added.

Appendix 2 shows that in the 11 subsectors of agriculture, forestry, and fisheries, there are two sectors that have the power of dispersion greater than the average, including livestock and aquaculture products (Appendix 2). However, the import spillover indexes of these two subsectors are also above the average level and the value-added spillover indexes are lower than the average. The crop sector has good value-added spillover index but a low output spillover index. Some input sectors of agriculture, forestry, and fishery such as feeds for cattle, poultry, and aquatic products, fertilizers and nitrogen compounds, pesticides and other chemicals used in agriculture have a low value-added spillover index. This may be due to the tax policy for this industry group. The input products of agriculture, forestry, and fisheries are not subject to VAT, meaning that those industries are not deducted input VAT. Thereby, intermediate costs of those sectors cannot be reduced and their value-added fall down more and more. Is this the reason why some industries have high spillover to the economy but the producers face difficulties? According to Appendix 3, the agriculture, forestry and fishery groups stimulate other sectors much better than other sectors simulating on them (Appendix 3). On average, one unit increase of the agriculture, forestry and fishery group will lead to an increase of 0.43 units for other sectors, while other sectors increased by one unit, the agriculture, forestry, and fishery group will increase 0.16 units. The group of crops, livestock, and fisheries has the highest stimulus to the economy. In addition, the sub-sectors including Products for preserving meat and meat products (sector 13); Aquatic products and seafood processing and preservation (sector 14); Vegetables processed (sector 15); Products of milling and flour production (sector 17); Feeds for cattle, poultry and aquatic products (sector 18); Products made from wood, bamboo (including beds, wardrobes, tables, chairs); from straw, parchment and plaiting materials (sector 18)have the largest spread to agriculture, forestry and fishery [7-10].

Appendix 4 shows that in order to meet the requirement of an increase in the output of 25 sectors (excluding 11 sub-sectors of agriculture, forestry, and fishery sectors), the annual crop output needs to increase the highest, followed by the livestock and aquaculture products (Appendix 4). In the opposite side, in order to meet the requirement of an increase in output of 11 sub-sector of agriculture, forestry, and fishery, the sectors (among remaining 25 sectors) including feeds for cattle, poultry and aquatic products, chemical fertilizers, nitrogen compounds, and other processing industries output have to increase highest. Annex 5 shows that the livestock and aquaculture products have the highest spillover effect of their final demand on other sectors' output among the 11 sub-sectors (Appendix 5). Moreover, these sub-sectors also have the highest power of dispersion. Moreover, Table 2 shows that change in inventory and household consumption have the highest spillover effect on value-added among final demand factors, while export has the lowest spillover effect. It suggests that demand management policies need to be directed towards factors that have high spillover to value-added. Agricultural, forestry and fishery products sold domestically are more profitable than export. Therefore, are the export-oriented policies a paradox? (Table 2).

The study shows that the current policy of prioritizing manufacturing industries is a paradox. It is because that these industries are basically outsourcing, the spillover effect of their final demand on value-added is trivial, whereas the final demand of agriculture, forestry, and fisheries spreads to value-added much better. In addition, the research also shows that the agricultural processing industry needs to be developed in abundant raw materials areas in order to increase the value-added content in the value chain of agricultural products. With the current economic structure, the demand for annual crop products is quite large. Therefore, instead of changing this structure, Vietnam needs to improve productivity and quality as well as linking agricultural production with manufacturing to improve the value-added content of these products. The subsidy for these products also needs to be taken into account, some developed countries with an advanced industry such as Japan and the United States have also introduced this policy, but the subsidy needs to be directly for the first stage of the value chain. The first of the value chains is the farmer, the subsidy needs to be substantive, unlike previous price stabilization programs. One of the reasons for the low value-added content in the value chain of agricultural, forestry and fishery products is because of so many intermediaries, especially associations which are called association. In many cases, the associations play a role as state management. The decisions of these associations have many times made the farmers suffer. The study also shows that two sub-sectors including livestock and aquaculture stimulate other sectors considerably. Unfortunately, according to the roadmap of import tax rates by 2020, these two industries have negative effective protection. In order to contribute to increasing the protection level for agriculture, forestry and fishery products, it is necessary to include input products of these sectors subject to the VAT rate of 0% as for foreign direct investment enterprises.

1. Vietnam GSO. Vietnam input-output table, 2012. Statistics Publisher House. 2014.
2. Hwa EC. The contribution of agriculture to economic growth: some empirical evidence. World Dev. 1988; 16: 1329-1339.
3. Cummings H, Murray D, Morris K, Keddie P, Xu W, Deschamps V. The Economic impacts of agriculture on the economy of Frontenac, Lennox & Addington and the United Counties of Leeds and Grenville. Socio-Economic Profile and Agriculture-Related Business Survey, Final Report, Ministry of Agriculture, Food and Rural Affairs. 2000.
4. Richardson HW. Input-output and regional economics. London: Weidenfeld and Nicolson. 1972.
5. Jensen RC, Mandeville TD, Karunaratne ND. Regional economic planning: generation of regional input-output analysis. London: Croom Helm Ltd. 1979.
6. Baumol J, Wolff N. A key role of Input-Output analysis in policy design. Reg Sci Urb Econ. 1994; 24: 93-114.
7. Trinh B. Measuring the effective rate of protection in Vietnam’s economy with emphasis on the manufacturing industry: an input-output approach. Depocen. 2010; 12.
8. Bromley DW, Blanch GE, Stoevener HH. Effects of selected changes in federal land use on a rural economy. Station Bulletin #604, Agricultural Experiment Station, Oregon State University. 1968.
9. Ciobanu C, Mattas K, Psaltopoulos D. Structural changes in less developed areas: an input–output framework. Regional Stu. 2004; 38: 603-614.
10. Czamanski S, Malizia EE. Applicability and limitations in the use of national input-output tables for regional studies. Reg Sci Ass Papers Proc. 1969; 23: 65-77.