1

Bank of Thailand’sMonthly Workshop

December 17, 2004

THE ROLE OF AGRICULTURAL SECTORIN THE DEVELOPMENT OF THE THAI ECONOMY:

IMPLICATIONS OF ECONOMIC FLUCTUATIONS

(A four-sector dynamic model analysis with government intervention)

Apirada Chinprateep

3

1. INTRODUCTION

1.1 Statement of Significance1.2 Objectives

4

Contribution/Roles of Agriculture

Johnston and Mellor (1961):1. supply of food2. labor3. size of market for industrial output4. supply of domestic savings5. exchange rate earnings

the policy environment that creates a mutual growth between agriculture/ rural and industries/ urban is needed.

2

5

GDP and Agricultural Growth(Lower in the 1990s)

1.92.73.62.7UMIC01.42.53.3HIC

2.14.23.64.1LMIC

2.53.03.24.5LIC

1.42.52.73.3World

90-20001980-9090-20001980-90

Agriculture GrowthGDP Growth

Source: World Bank 2002 6

Mundlak, Y., Larson, D.F. and Butzer, R. (2003)

• studied determinants of agricultural growth in Thailand, Indonesia, and the Philippines from 1960s on, as of data availability.

• concluded that policy driven investmentsin human capital and public infrastructure were important.

7

1.2 Objectives of this Study

• To study the agricultural sector(in the environment: Dynamic multi-sector GE with agricultural primary to manufacture)

• To model government intervention• To identify and evaluate an optimal output

tax level(s) - Does tax on agriculture twice than other sectors (is it the right

policy?) magnify or otherwise reduce the role of agriculture in the country’s growth contribution?

8

2. AGRICULTURAL DEVELOPMENT

Timmer(1988) summarized in 4 phases: 1. having the agricultural productivity per worker rises

(Mosher, 1966). 2. tapping the surplus (Johnston and Mellor, 1961). 3. facilitating integration of the agriculture sector into the

macro economy (via improved infrastructure and market-equilibrium linkages). Here, however, agriculture becomes much more vulnerable to fluctuations (Schuh, 1976).

4. if the third phase is successful experiencing agriculture quite similar to other sectors.

Otherwise experiencing serious problems of resource allocation

3

9

3. AN OVERVIEW OF THE THAI ECONOMY

10

Figure 1: The Trend of Three Economic Sectors VS GDP (in Million Baht) during the nation’s economic plans

0

1000000

2000000

3000000

4000000

5000000

6000000

72 74 76 78 80 82 84 86 88 90 92 94 96 98 00

4 0 7 8 6 . 04 9 9 1 9 . 07 3 2 3 3 . 08 4 7 3 5 . 09 4 0 6 3 . 09 2 4 6 0 . 09 9 9 7 0 . 0

1 1 9 6 3 8 . 01 3 4 1 4 8 . 01 5 3 9 6 0 . 01 6 2 3 9 0 . 01 5 6 0 9 8 . 0

1 8 4 7 5 2 . 01 7 3 6 4 2 . 01 6 7 0 2 6 . 01 7 7 5 3 7 . 02 0 4 5 2 1 . 0

2 5 2 3 4 6 . 02 7 9 9 4 7 . 02 7 2 9 3 5 . 0

3 1 7 0 8 5 . 03 4 8 1 2 7 . 0

3 2 9 8 7 8 . 0

3 9 2 4 9 6 . 0

4 6 9 4 2 6 . 0

5 1 0 4 0 0 . 05 4 1 8 6 4 . 0

6 2 0 1 8 2 . 0

5 5 3 3 3 5 . 0

Agr ic ultureManufac tureC ons truc tion

Serv ic e and OthersGDP

3th Plan(1972-1976)

5th Plan(1982-1986)

7th Plan(1992-1996)

4th Plan(1977-1981)

6th Plan(1987-1991)

8th Plan(1997-2001)

Un i t: m i l . Bah t

Agri .

M anu.

Serv . & Others

GDP

Cons truc tion

11

Figure 2: The Trend of Three Economic Sectors (percent of GDP) during the nation’s economic plans

0 .0

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

7 2 7 4 7 6 7 8 8 0 8 2 8 4 8 6 8 8 9 0 9 2 9 4 9 6 9 8 0 0

AGRICUL T URE(0 0 % )CONST RUCT ION (0 0 % )

M ANUF ACT URE(0 0 % )SERVICE&OT HERS(0 0 % )

3 th Pl a n (1 9 7 2 -1 9 7 6 )

5 th Pl a n(1 9 8 2 -1 9 8 6 )

7 th Pl a n(1 9 9 2 -1 9 9 6 )

4 th Pl a n(1 9 7 7 -1 9 8 1 )

6 th Pl a n(1 9 8 7 -1 9 9 1 )

8 th Pl a n(1 9 9 7 -2 0 0 1 )

12

4. REVIEW OF RELATED LITERATURE

4.1 Agricultural Role on Economic Growth and Some Related Government Policies

4.2 Business Cycles and Model Reviews 4.3 Dynamic Economic Modeling

4

13

5. THEORETICAL FRAMEWORK AND

MODEL SPECIFICATION5.1 (Step 1) Constructing conforming

- Thailand National Accounts Balance Sheet - A Social Accounting Matrix of a Base Year

5.2 (Step 2) Estimating the Economic Model

5.3 (Step 3) Examining Macroeconomic Fluctuations & Business Cycle Regularities VS Agriculture Movement

14

T h a i l a n d N a t i o n a l A c c o u n t s B a l a n c e S h e e t f o r 1 9 9 0 ( c u r r e n t b i l l i o n b a h t ) ( r e a l d a t a f o r t h e s o c i a l a c c o u n t i n g m a t r i x w i t h t h e b a s e l i n e c o n c e p t u a l f r a m e w o r k )

I n c o m e E x p e n d i t u r e

G D PG D P a t f a c t o r c o s t 1 8 9 1 . 2 G o v e r n m e n t c o n s u m p t i o n 2 0 5 . 4I n d i r e c t t a x e s l e s s s u b s i d i e s 2 9 2 . 3 P r i v a t e c o n s u m p t i o n 1 2 3 5( B u s i n e s s T a x ) G r o s s c a p i t a l f o r m a t i o n 9 0 3 I n d i r e c t t a x e s 3 1 2 . 7 E x p o r t 7 4 5 . 3 S u b s i d i e s 2 0 . 4 L e s s i m p o r t 9 0 9 . 5

S t a t i s c a l d i s c r e p a n c y 4 . 3T o t a l G D P 2 1 8 3 . 5 2 1 8 3 . 5

G N PT o t a l G D P 2 1 8 3 . 5 F i n a l c o n s u m p t i o n 1 4 4 0 . 4

P r i v a t e c o n s u m p t i o n e x p e n d i t u r e 1 2 3 5 G o v e r n m e n t 2 0 5 . 4

N e t f a c t o r i n c o m e p a y m e n t / t r a n s f e r - 2 7 . 4( N e t f r o m a b r o a d ) G r o s s s a v i n g 9 0 3

C u r r e n t t r a n s f e r s t o - 1 8 6 . 3 t h e r e s t o f t h e w o r l dS t a t i s c a l d i s c r e p a n c y - 1

T o t a l G N P 2 1 5 6 . 1 2 1 5 6 . 1

C a p i t a l A c c o u n t sD o m e s t i c s a v i n g 7 1 6 . 7 G r o s s c a p i t a l f o r m a t i o n 9 0 3N e t f o r e i g n s a v i n g 1 8 6 . 3

T o t a l 9 0 3 9 0 3

E x t e r n a l T r a n s a c t i o n sE x p o r t s o f g o o d s a n d s e r v i c e s 7 4 5 . 3 I m p o r t s o f g o o d s a n d s e r v i c e s 9 0 9 . 5N e t f a c t o r i n c o m e / c u r r e n t t r a n s f e r p a y m e n t 1 6 4 . 2 f r o m t h e r e s t o f t h e w o r l d( n o t i n c l u d i n g e x p l i c i t i n t h e S A M h e r e )

T o t a l 9 0 9 . 5

S o u r c e : - V a r i o u s N a t i o n a l I n c o m e a n d A c c o u n t T a b l e s a n d D a t a , N E S D B

- V a r i o u s E c o n o m i c a n d F i n a n c i a l S t a t i s t i c s D a t a , B a n k o f T h a i l a n d

15

Table 5.1.2.1a: Thailand 1990 SAM Layout

1 6 7 9 10

1 G ov ernm ent C ap ita l FE (inv est: in)To ta l (o f

R ow )

D om estic Investm ent

Interm ediate Inpu t (U se)

6 G ov ernm ent To tal G ov't Incom e

7 C ap ita l Priv ate S av ings

FE funds from Fore ign savings/

C ountry's Fore ign R eserve

Tota l Savings In

N et Investm ent Abroad (+)

9 FE (consum e:out)T o ta l FE C red its

10 T ota l (of C o lum n) T o ta l G ov't O utlay

To ta l Investm ent FE Ad justm ent

3

2

8

5

4R eturns to

Prim ary Factors

B P Surp lus (-)

To tal Industry O utpu t

To ta l Facto r Incom e

T ota l FE O utlays

Total C om m odity

Supp ly

To tal Institu tion

Incom e

C red it fo r Im ports (+)

D istribution o f Factor Incom e

Total Institu tion O utlay Total actual FE Earn ings

Priv ate C onsum ption

G ov't C onsum ption

Exports O utput

To tal C om m odity

O utlay

T ota l Industry O utlay

Total Facto r O utlay

Ind irect B usiness

Taxes (D om estic )

T rade (R O W ), "Im ports"

D om estic P roduction

(M ake)

Im ports

C om m odities

Factors

Institu tions

Industry Activ itiesT ransfer

8Industry

Activ ities C om m odities Facto rs Institu tionsT rade(R O W ),

"Exports"

2 3 4 5

16

Activities/Commodities• Agriculture1 (high manufacture-intermediate proportion) [12]:

Paddy, Cassava, Sugar Cane, Palm Nut and Oil Palm, Kenaf and Jute, Crops for Textile and Matting, Tobacco, Cattle and Buffalo, Swine, Poultry, Logging, and Other Forestry Products.

• Agriculture 2 (low manufacture-intermediate proportion) [17]:Maize, Other Cereals, Other Root Crops, Beans and Nuts, Vegetables, Fruits, Coconut, Coffee and Tea, Rubber, Other Agriculture Products, Other Livestock, Poultry Products, Silk Farming, Agricultural Services, Charcoal and Firewood, Ocean and Coastal Fishing, and In-land Water Fishing.

• Manufacturing sectors [93]:Slaughtering; Canning and Preserving of Meat; Dairy Products; Canning and Preserving of Fruits and Vegetables; Canning and Preserving of Fish and Seafood; Coconut and Palm Oil; Other Vegetable and Animal Oils; Rice Milling; Flour, Sagu Mild Products, and Tapioca Milling; Grinding Corn Flour and Other Grain Milling; Bakery and Other; Noodle and Similar Products; Sugar Refineries; Confectionery and Snack; Ice; Monosodium Glutamate; Coffee, Cocoa, and Tea Processing; Other Food Products; Fish Meal and Animal Feed; Distilling and Blending of Spirit; Breweries; Soft Drinks and Carbonated Water; Tobacco Processing; Tobacco Products; Spinning Weaving; Textile Bleaching; Printing and Finishing; Made-Up Textile Goods; Knitting; Wearing Apparels; Carpets and Rugs; Jute Mill Products; Tannery and Leather Finishing; Leather Products; Foot Wear; Except of Rubber, Saw Mill, and Wooden Construction Materials; Wood and Cork Products; Wooden Furniture and Fixture; Paper and Paper Board; Paper and Paperboard Products; Printing and Publishing; Basic Chemicals; Fertilizer; Pesticide and Insecticide; Petrochemical Products; Paint, Drug, and Medicine; Soap and Cleaning Preparations; Cosmetic Matches; Other Chemical Products; Petroleum Refinery and Gas Separated Plant; Other Coal and Petroleum Products; Rubber Sheet and Block Rubber; Types and Tubes; Other Rubber Products; Plastic Wares; Ceramic and Earthen Wares; Glass and Glass Products; Structural Clay Products; Cement; Concrete and Cement Products; Other Non-Metallic Products; Iron and Steel; Secondary Steel Products; Non-Ferrous Metal; Cutlery And Hand Tools; Metal Furniture and Fixture; Structural Metal Products; Other Fabricated Metal Products; Engine And Turbine; Agricultural Machinery and Equipment; Wood and Metal Working Machine; Special Industrial Machinery; Office Equipment and Machinery; Electrical Industrial Machinery and Appliances; Radio, Television Set, and Communication Equipment; Other Electric Appliances; Insulated Wire and Cable; Electric Accumulator and Battery; Other Electrical Apparatuses and Supplies; Ship Building; Railway Equipment; Motor Vehicle; Motorcycle, Bicycle, and Other Carriages; Repairing of Vehicle; Aircraft; Scientific Equipments; Photographic and Optical Goods; Watches and Clocks; Jewelry and Related Articles; Recreational and Athletic Equipment; Other Manufacturing Goods.

• Services and others [58]– Mining:

Coal and Lignite, Crude Oil and Natural Gas, Iron Ore, Tin Ore, Tungsten Ore, Other Non-Ferrous Metal Ore, Fluorite Ore, Natural Chemical and Fertilizer, Salt, Limestone, Stone Quarrying, Other Mining and Quarrying.

– Trade, construction, utilities, transportation, restaurant and hotel, business and education, recreation and insurance:Electricity; Pipe Line; Water Supply System; Residential Building; Construction; Non-Residential Building Construction; Public Works for Agriculture and Forestry; Non-Agricultural Public Works; Construction of Electric Plant; Construction of Communication Facilities; Other Construction; Wholesale Trade; Retail Trade; Restaurant and Drinking Place; Hotel And Lodging Place; Railways; Route and Non-route of Road Passenger Transport; Road Freight Transport; Land Transport Supporting Services; Ocean Transport; Coastal and Inland Water Transport; Water Transport Services; Air Transport; Other Services; Silo and Warehouse; Post and Telecommunication; Banking Service; Life Insurance Service; Other Insurance Service; Real Estate; Business Service; Public Administration; Sanitary and Similar Services; Education, Research, Hospital, Business, and Labor Associations; Other Community Services; Motion Picture Production; Movie Theater, Radio-Television, and Related Services; Library and Museum; Amusement and Recreation; Repairing not Elsewhere Classified; Personal Services; Unclassified.

5

17

Define Functions:1. Households

ˆ ˆ ˆˆ ( )k w k r x n T Eς•

= + − − + −

1, ( )

0

ˆ( ) 11

t j t n t

t

u ce dt

θρ

θ

−=∞ −

=

−

−∫

where goods , j = m,a1,a2,s

Subject to given K0, T0………. (1)

ˆ( ) ( )

jj

cc

a t L t=

( ) (0)ntL t e L=

ˆ( )ww

a t= ˆ

( ) ( )Kk

a t L t= ˆ

( ) ( )EE

a t L t=where , ,

18

2. Producers/ firms• i. Manufacturing firm (m):

• ii. Agricultural Intermediate producer (a1):

• iii. Agricultural producer (a2):

• iv. Service producer (s):

3

1

1ii

β=

=∑

21 2, , 1( ) ( ) ( )M

m m t t m t t a MY t MK a L G Y tαα α=&&&

, 1,2{ , } (0,1)i i Mα = ∈; 2

1

1ii

α=

=∑

231 21 1, 1,( ) 1 ( )a a t t a t tY t A K a L T G βββ β=

&&&&&, {1,2,3} (0,1)i iβ = ∈;

3

11i

iβ

=

=∑

where 1 1( ) ( )a M aY t Y t⊆

;

231 22 2, 2,( ) 2 ( )a a t t a t tY t A K a L T G βββ β=

&&&&&, {1,2,3} (0,1)i iβ = ∈ ;

11, ,( ) ( )s s t t s t tY t SK a L G δδ δ −−=

&&&(0,1)δ∈

19

Define Equilibrium:• Page 62-65, Chapter 5

20

Algebraic Form

• Appendix B

6

21

Proof: Size of Government & Taxes

• Appendix C

22

5.3.1 Detrending the Data

For t = 1,…, T.

cttt xxx += *

23

The filtering technique

Trend component is extracted by solving:

( ) ( )*

21* 2 * * * *

1 11 2

( )t

T T

t t t t t tx t t

Min x x x x x xλ−

+ −= =

− + − − − ∑ ∑

24

6. RESULTS

6.1 Calibration Result & Link to the Real Data

6.2 Cycle Regularities

6.3 Link 6.1 & 6.2 New Calibration Result (w/ some wiggles)

7

25

6.1.2 Calibration Result

• Comparative Dynamics– 6.1.2.1 Path of prices: The path and the direction of Ps

depend upon the factor intensity of sector s relative to sector m

If and ; , diminishing returns to imply:

rr

PP

s

sr &&=ε 0≤

sskk ˆ)0(ˆ < 0ˆ ≥k t∀

26

• sector s is relatively more capital-intensive than sector m, then Stopler-Samuelson “like” condition implies

s

s

PP& 0≤

rε 0≥

27

• Proposition 2: The path of is also involved with the factor intensity of sector srelative to sector m.

if and ,

is negative if s is capital-intensive in the relative comparison to sector m.

w

tkk

∀≥ ,0&

1//

<kkLL

&

&

s

sw

PP

ww &&

ε=ˆˆ

0≥

wε

28

- 6.1.2.2 Path of output supplies:Manufacturing output supply

Agricultural output supply

(-) (+) (-) (-) (+) (+,-)

Service output supply

=

( )( )

m

m

Y tY t

&,

,

( )( ) ( ) ( )( ) ( ) ( ) ( )( ) ( ) ( ) ( )

m Mk L Mm m mm m m

m m m m M

y tK t L t G tt t t SR tK t L t G t y t

ε ε ε

+ + + +

&& & &=

== 2,1,

, |iiag

iag

YY&

GG

rr

ww G

YrY

wY iagiagiag

&&&,,,

εεε ++

( )( )

s

s

Y tY t

& ( ) ( ) ( )( ) ( ) ( )( ) ( ) ( )

k Ls s ss s

s s s

K t L t G tt t SR tK t L t G t

ε ε

+ + +

&& &

8

29

6.1.2.3 Base model simulation:

30

1. Paths of home-goods price VS the capital rental rate (Ps&r)

31

1.1 Path of capital stock over time (k&t)

20 40 60 80 100t

2000

4000

6000

8000

10000

12000

14000

k K Per Effective Worker

32

1.2 Path of the capital rental rate over time (r&t)

20 40 60 80 100t

0.06

0.07

0.08

0.09

r Return to k per AL

9

33

1.3 Path of policy function VS capital stock (Ps&k)

2000 4000 6000 8000 10000 12000 14000k

0.85

0.9

0.95

1.05

1.1

1.15

p3 The Policy Function

34

1.4 Evolution of home-goods price over time (Ps&t)

20 40 60 80 100t

0.85

0.9

0.95

1.05

1.1

1.15

P3 Evolution of p3

35

2. Paths of wage rate per effective worker VS the amount of labor

(&L)

36

2.1 Path of the amount of labor in each sector (Lj&t)

20 40 60 80 100t

0.2

0.4

0.6

0.8

541.7 j LHjLdemandL1 = Solid

L21 = L DashL22 = M Dash

L3 = S Dash

10

37

2.2 Path of wage rate per effective labor (&t)

20 40 60 80 100t

450

500

550

600

650

700

w Wage Rate per AL

38

3. Paths of output supplies:

39

3.1 Output shares over time

20 40 60 80 100t

0.1

0.2

0.3

0.4

0.5

0.6

Share Output shares

22(Medium Dash)

j=1(Solid)

3(Small Dash)21(Large Dash)

40

3.2 Growth in per capita output

20 40 60 80 100t

-0.05

0.05

0.1

0.15

gwth Growth in Output per L

Y22 = M Dash

Y21 = L Dash

Y3 = S Dash

Y1 = Solid

11

41

3.3 Growth in labor demand

20 40 60 80 100t

-0.05

0.05

0.1

gwth Growth in LHjL�L demand

L3 = L Dash

L1 = Solid

L21 = M DashL22 = S Dash "

42

3.4 Growth in per capita capital demand

20 40 60 80 100t

0.02

0.04

0.06

0.08

0.1

0.12

gwth Growth in kHjLdemand per L

k1d = Solid

k3 = L Dash

k21 = M Dash

k22 = S Dash

43

3.5 Sector contribution to GDP growth

20 40 60 80 100t

1

2

3

4

5

pct Sector Contrib . to Nominal GDP Growth

Sector 1

Sector 2 = Large Dash

Sector 3 = Small Dash

44

Factor contribution to GDP growth

12

45

6.1.3 Validation: Contrasting Model Results to the Real Data

46

Figure 6.1.3a: Real GDP VS Model (billion 1988 baht)

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita SERV ('88 price)mBYY3 from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita MANU('88 price) mBYY1 from Model Case1

-3

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita GDP('88 price) mil BGDP from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita AGRI ('88 price) mBYY2 from Model Case1

47

6.1.4 Sensitivity Analysis

• to show various tax schemes and policy environment scenarios.

• In the model, agriculture provides a final good (food), an intermediate good to manufacturing (raw material), and it can either provide labor, or employ labor, likewise for capital.

48

- Case 1: Government & Intermediate (Tax agriculture the most, taxing agri1 = agri2)- Case 2: Government & No intermediate (M=0)- Case 3: Tax = weight & Intermediate - Case 4: No government & Intermediate - Case 5: Tax agriculture equal to its labor E &

Intermediate - Case 6: Tax manufacture equal to its labor E &

Intermediate

13

49

Table 6.1.4a: Simulation Sensitivity Results

50

Table 6.1.4a (continued1)

51

Table 6.1.4a (continued2)

52

• All in all, given government intervention and intermediate,

• to earn a maximum GDP level, maximum utility, maximized wage rate, and capital rental rate, with the least trade deficit at the steady state, – the most promising policy is the one where the

tax on agricultural sectors is set equal to their labor elasticity.

14

53

6.2 Examining the Main Stylized Features of Macroeconomic

Fluctuations and Business Cycle Regularities in Thailand

versus Agricultural Movement

54

• In contrasting the model results to the real data, there are stretches where the real data and the model separate.

• Most of these departures can be explained by unexpected medium-run or short-run shocks.

55

• These shocks, so this dissertation argues, can be classified into patterned shocks (e.g., seasonal) and sudden or unanticipated shocks.

56

– If the “cyclical” component of agriculture is successfully captured, we should be able to mimic this pattern and explain the departures from the calibrated model’s output.

– With this new series, departures between the real data and the calibrated series now imply that the shocks stem from non-agricultural sectors. This information will be useful for policy analyses.

15

57

-2

-1

0

1

2

3

-3

-2

-1

0

1

2

3

93 94 95 96 97 98 99 00 01 02 03 04

Agri. quarterly productManu. quarterly productServ.&O quarterly productQuarterly GDP (1988 Mil.Baht)

58

6.3 Estimating the Economic Model of Thailand with Some Wiggles

59

6.3.1 Calibration Result

-2

-1

0

1

2

93 94 95 96 97 98 99 00 01

Agri. quarterly productYY2 (model1) w/ wiggles

60

6.3.2 Validation: Contrasting Model Results to the Real Data (Revisited)

16

61

-3

-2

-1

0

1

2

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita GDP('88 price) mil BREVISED GDP from Model 1

-2

-1

0

1

2

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

90 92 94 96 98 00 02 04

YY2 (Model Case1) w/ wigglesPer capita AGRI ('88 price) mB

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita MANU('88 price) mBYY1 from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita SERV ('88 price)mBYY3 from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita SERV ('88 price)mBYY3 from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita MANU('88 price) mBYY1 from Model Case1

-3

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita GDP('88 price) mil BGDP from Model Case1

-2

-1

0

1

2

90 92 94 96 98 00 02 04

Per capita AGRI ('88 price) mBYY2 from Model Case1

62

7. CONCLUSION

• What do we learn from the model?

- The study shows that the agricultural sector should be levied at an efficient tax level, which is one that reflects the marginal productivity of public good that it absorbs, or, in other words, the elasticity of the public goods used in agricultural production.

63

• Noting that agriculture (along with the balanced-growth path) yields a high growth in the long-run and represents the majority of the people in the Thai economy, more tax distortion on this sector than on other sectors (e.g., doubling the tax on agriculture) may not be the right policy for national growth.

64

THANK YOU