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Table 5 Step-by-step computation of the economic benefit of IRG contribution

From: The impact of the international rice genebank (IRG) on rice farming in Bangladesh

Variable name

Variable description

Unit

Formula

Value

A

The average yield of modern rice varieties during the 2015 wet season

kg/ha

4964

B

Coefficient of ln_Definite_contribution in the Cobb–Douglas model

0.01

C

The marginal increase in yield due to a 1% increase in IRG contribution

%/ha

(exp(B)—1) * 100

0.99

D

The marginal increase in yield due to a 1% increase in IRG contribution

kg/ha

A * (C/100)

49.36

E

Average paddy price of modern varieties during the 2015 wet season

Tk/kg

16.60

F

The estimated increase in paddy price due to the increase in production

%

IGRMa

1.89

G

The estimated paddy price due to the increase in production during the 2015 wet season

Tk/kg

E—(E * F/100)

16.28

H

The estimated marginal increase in gross income due to a 1% increase in IRG contribution

Tk/ha

D * G

803.81

I

The estimated total input cost/kg of paddy during the 2015 wet season

Tk/kg

Cost and returnb

10.99

J

The estimated total input cost for 49.36 kg of paddy during the 2015 wet season

Tk/ha

D * I

542.43

K

The estimated marginal increase in net income due to a 1% increase in IRG contribution

Tk/ha

H—J

261.38

L

The estimated area cultivated by modern varieties during the 2015 wet season

000 ha

1946

M

The estimated marginal increase in net income (local currency) in Bangladesh due to a 1% increase in IRG contribution in 2015

Tk

K * L * 1000

508,620,707

N

The exchange rate of 1 US$ to Tk (2015)

Tk

77.87

O

The estimated marginal increase in net income in Bangladesh due to a 1% increase in IRG contribution in 2015

US$

M / N

6,531,455

P

Consumer price index in 2020 (base = 2015)

index

131.32

Q

The estimated marginal increase in net income in Bangladesh due to a 1% increase in IRG contribution in 2020

US$

O * (P/100)

8,576,973

  1. aIRRI Global Rice Model
  2. bThe total input cost/kg was computed using the cost and return data of RMS