Application to Indian Data the North India Wheat Region

For the north India wheat region, a two-commodity, four-input system was developed. The relevant variables are briefly defined and summarized in Table 11.1.

The system was estimated for alternative sets of traits. Table 11.2 reports the full set of estimates for trait set 1 utilizing 3SLS in the seemingly unrelated regression system. Cross-equation restrictions were applied where relevant. All equations included district dummy variables so this is a 'fixed effects' estimation.

Since this is a 'structural' model, the coefficients do not show the full effects of the independent variables. For example, extension affects MV adoption and has additional effects on yields and demand for factors.

Consider first the two MV adoption equations:

• Expected revenues as reflected in state yields times prices have the expected effects for both rice and wheat. An increase in traditional rice revenues stimulates MV adoption in wheat.

• Extension stimulates rice MV adoption, but not wheat MV adoption.

• Literacy stimulates MV adoption.

• Road infrastructure stimulates MV adoption.

• Irrigation investment stimulates MV adoption.

• The availability of new traits and the increased complexity of rice MVs stimulates rice MV adoption.

Next consider the area equations:

• Expansion of rice MV adoption has small negative impacts on wheat area, but wheat MV adoption has a positive impact on both wheat and rice areas. It appears that the higher yielding rice varieties tend to lead farmers to reduce acreage planted to rice, and shift to other summer crops. There is little substitution of other crops for wheat.

• Higher wheat revenues stimulate more area in both wheat and rice.

• Factor prices have few effects on area - except for wages for wheat, where higher wages stimulate more wheat area. (Note, there may be some endogeneity here.)

• Research, given MV adoption, tends to encourage substitution of other crops for rice and wheat.

• Extension stimulates more area in both crops.

• Literacy has little effect on area planted.

• Road infrastructure stimulates more area in both crops.

• Irrigation investment stimulates more area in both crops.

• Lagged area effects show significant adjustment costs.

Table 11.1. Variable definitions: north India wheat region.

Variable

Definition

Mean

1. Endogenous

PHYVRICE

Per cent of area planted to mod rice

0.28

PHYVWHT

Per cent of area planted to mod wheat

0.39

ARICE

Area planted to rice (kha)

64.6

AWHEAT

Area planted to wheat (kha)

169.9

QBullock

Quantity (bullock power) 150,489

QTractor

Quantity (tractor use)

2,879

QLabour

Quantity (labour)

65.941

QFert

Quantity (fertilizer)

2,709

YRICE

Yield (rice)

1.502

YWHEAT

Yield (wheat)

1.631

2. Exogenous

Prices (revenues)

MR2

Ratio: expected revenue trad rice/mod rice

0.89

MR3

Ratio: expected revenue wheat/mod rice

1.21

MR4

Ratio: expected revenue mod wheat/mod rice

1.14

MW1

Ratio: expected revenue trad rice/mod wheat

0.84

MW2

Ratio: expected revenue mod rice/mod wheat

0.74

MW4

Ratio: expected revenue trad wheat/mod wheat

0.94

WAGEOUT

Wage/P output

2.27

TRACOUT

Price of tractors/P output

3,352

FERTOUT

Price of fertilizer/P output

1,084

BULLOUT

Price of bullocks/P output

281

Technology

LGCRICE5

Rice research stock (Evenson et al., 1996)

19.75

LGCWHT5

Wheat research stock (Evenson et al., 1996)

7.37

EXT

Extension staff/farm

7.80

LITERACY

Per cent literate farmers

0.300

Infrastructure

IROADS

Index of change in roads

1.813

NIANCA

Net irrigated acreage/net cropped area

0.44

Weather

YEARRAIN

Rainfall (year)

782

JUNERAIN

Rainfall (June)

90

JUARAIN

Rainfall (July, August)

436

Rice traits

AGRQUAL

Leading varieties with improved agronomic quality

1.25

ABIOSTRESS

Leading varieties with ecology stress tolerance

2.85

DISINS

Leading varieties host plant disease, insect resistance 7.47

NLR

Number of landraces in leading varieties

3.05

mod, modern; trad, traditional mod, modern; trad, traditional

Table 11.2. Two-commodity system north India wheat region, 1956-1987

Per cent HYV

Area planted

Endogenous independent variables Yield

Demand for factors

Table 11.2. Two-commodity system north India wheat region, 1956-1987

Per cent HYV

Area planted

Demand for factors

Rice

Wheat

Rice

Wheat

Rice

Wheat

QBullock

QTractor

QLabour

QFert

1. Endogenous

PHYVRICE

-8.18

- 27.6

0.988

35,740

2,943

6,425

22,172

(1.35)

(2.16)

(9.59)

(1.87)

(3.36)

(1.00)

(3.51)

PHYVWHT

10.74

39.39

0.502

-44,884

-1,218

-12,053

-4,992

(2.26)

(4.07)

(8.23)

(2.99)

(2.09)

(2.38)

(1.01)

ARICE X lagged PHYVRICE

0.865

0.001

(50.37)

(1.78)

AWHT X lagged PHYVWHT

0.804

0.001

(37.7)

(1.52)

2. Exogenous

MR2

-1.09 (13.8)

MR3

0.121 (1.40)

MR4

-0.128

0.841

5.03

1.73

16,472

865

5,841

4,522

(1.43)

(8.97)

(1.85)

(0.32)

(1.91)

(2.60)

(2.01)

(1.56)

MW1

0.809 (8.89)

MW4

-1.42 (11.82)

WAGEOUT

-0.65

7.52

-27,401

847

-7,101

3,984

(0.60)

(3.25)

(7.91)

(6.29)

(6.08)

(3.48)

TRACOUT

- 0.001

- 0.002

4.54

-71.4

0.97

0.93

(0.41)

(0.59)

(0.71)

(2.88)

(0.45)

(0.44)

FERTOUT

- 0.002

0.002

19.88

0.610

3.21

-6.68

(0.64)

(0.27)

(1.69)

(1.34)

(0.81)

(1.73)

BULLOUT

- 0.008

-0.075

38.1

-2.31

24.9

-17.6

(0.54)

(2.81)

(0.91)

(1.42)

(1.77)

LGCRICE5

-61.21

-30.15

(4.08)

(0.99)

LGCWHT5

-732.40

-168.7

(6.80)

(4.31)

EXT

0.021

-0.015

1.99

1.36

(6.54)

(5.71)

(3.32)

(1.92)

LITERACY

0.191

0.413

-50.07

6.40

(1.20)

(2.64)

(3.96)

(0.24)

1 ROADS

0.074

0.012

3.04

0.63

(6.91)

(1.77)

(3.11)

(0.32)

NIANCA

0.128

0.208

0.529

22.62

(2.70)

(4.13)

(0.13)

(2.39)

YEARRAIN

JUNERAIN

JUARAIN

AGRQUAL

0.006

(3.05)

ABIOSTRESS

0.016

(1.81)

DISINS

0.037

(6.26)

NLR

0.033

(4.43)

YEAR

-0.023

0.026

13.80

14.61

(7.48)

(14.9)

(7.19)

(3.80)

0.637

80,399

-7,084

-25,873

-71,088

(0.11)

(1.68)

(3.81)

(1.60)

(4.50)

-0.977

83,859

6,743

70,172

-91.977

(2.76)

(1.37)

(2.82)

(3.39)

(4.53)

0.023

0.065

-1,987

134

-281

4,513

(8.18)

(10.16)

(1.81)

(3.14)

(0.76)

(12.47)

-0.581

0.225

-160,064

-10,018

-112,465

-110,622

(1.86)

(0.89)

(4.10)

(6.60)

(8.53)

(8.57)

0.282

0.049

-6,886

1,428

-3,067

3,482

(12.6)

(2.78)

(2.73)

(11.89)

(2.94)

(3.41)

0.822

0.556

-28,104

4,809

29,922

41,630

(8.75)

(6.05)

(2.24)

(9.81)

(7.04)

(9.99)

0.0002

-0.000

(8.10)

(1.27)

0.000

-0.000

(0.35)

(2.69)

0.000

0.000

(0.47)

(1.26)

0.005

(5.37)

0.025

(1.13)

0.015

(1.11)

-0.044

(2.56)

-0.022

0.064

-7,896

-77.6

-7.84

10,862

(0.83)

(2.45)

(1.31)

(0.33)

(1.31)

(5.45)

Next consider the yield effects:

• MV effects are high in both crops, but higher in rice.

• Area effects are small but positive. Expansion of area does not lead to lower yields.

• Research, given MV adoption, has little effect (research produced the MVs and this is its main contribution).

• Extension positively affects yields.

• Literacy has little effect.

• Road infrastructure positively affects yields.

• Irrigation investment increases yields.

• Rice traits have mixed effects. Varietal complexity (number of landraces) results in lower yield (but stimulated MV adoption). Insect resistance traits lead to higher yields (and higher adoption). Disease resistance effects are smaller.

Finally, consider the factor demand equations:

• Rice MV adoption stimulates more demand for all factors, especially for tractors and fertilizer.

• Wheat MV has input savings effects, especially for labour and bullocks.

• Revenue effects for wheat outweigh those for rice and have positive effects on factor demand.

• Factor prices have expected own price effects (except for bullocks). Labour and tractors are substitutes.

• Rice research holding MVs constant saves factors. Wheat research stimulates factor use.

• Literacy saves factors.

• Road infrastructure saves labour and bullocks and stimulates tractor and fertilizer demand.

• Irrigation investment stimulates tractor, labour and fertilizer demand and reduces bullocks demand.

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