This paper serves as preliminary study to investigate the relative impacts of various factors on acreage response of rice in Malaysia. The findings provide mixed signals which are different from other rice production countries. Hence, future studies are deemed essential to probe the issues with justifications by looking at the connection of Malaysian paddy production and economic theory, as well as implications to policymakers

Darham, Suryani

Idris, Nurjihan

Mohd Noh, Aswani Farhana

Tey, (John) Yeong-Sheng

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MPRA
Munich Personal RePEc Archive
Acreage response of rice: A case study in
Malaysia
(John) Yeong-Sheng Tey and Suryani Darham and Aswani
Farhana Mohd Noh and Nurjihan Idris
17. May 2009
Online at http://mpra.ub.uni-muenchen.de/15300/
MPRA Paper No. 15300, posted 21. May 2009 13:33 UTC
ACREAGE RESPONSE OF RICE: A CASE STUDY IN MALAYSIA 
 
 
by 
 
Tey (John) Yeong-Sheng1, Suryani Darham, Aswani Farhana Mohd Noh, and Nurjihan Idris 
 
 
Abstract 
 
This paper serves as preliminary study to investigate the relative impacts of various factors on 
acreage response of rice in Malaysia. The findings provide mixed signals which are different 
from other rice production countries. Hence, future studies are deemed essential to probe the 
issues with justifications by looking at the connection of Malaysian paddy production and 
economic theory, as well as implications to policymakers. 
 
 
Keywords: Acreage response, rice, paddy 
 
JEL code: Q11 
 
 
1.0 Introduction 
 
Malaysia has largely identified the need to increase her paddy production and hereafter rice 
production to feed her growing population. The need was addressed in the Third National 
Agricultural Policy (1998-2010) where eight granary areas were designated as permanent paddy 
producing areas to realise a minimum self-sufficiency level (SSL) for rice of 65 per cent. It was 
further emphasized in the Eighth Malaysian Plan (2001-2005) and the Ninth Malaysian Plan 
(2006-2010) to achieve rice SSL of 72 per cent and 90 per cent by 2005 and 2010 respectively.  
 
To boost rice production or supply response, it can be done in short/medium term by expanding 
acreage of planted area or in long term by increasing yield or improving efficiency of conversion 
from paddy to rice. Due to the urgency, the ideal immediate deed is to expand acreage of paddy 
planted area in Malaysia. Under such circumstance, farmers in other countries may have to worry 
about production costs but not in Malaysia. The Malaysian government has devoted splendid 
funding (incentives/subsidies) to encourage expansion of paddy plantation and production 
 
Instead of all the initiatives by the government, statistics and trend of paddy planted area suggest 
that there is no or minimal acreage response of rice in Malaysia. For example, the paddy planted 
area was at peak of 766,000 hectares in 1972 but it then decreased significantly to historic low of 
645,000 hectares in 2006. While there are more to investigate, this paper serves as preliminary 
                                                             
1 Corresponding author 
Email: tyeong.sheng@gmail.com 
Address: Institute of Agricultural and Food Policy Studies, Putra Infoport, Universiti Putra Malaysia, 43400 UPM 
Serdang, Selangor, Malaysia.  
study to investigate the relative impacts of various factors on acreage response of rice in 
Malaysia.  
 
2.0 Model Specification and Data 
 
A simplified acreage response function from Salassi (1995) can be represented by:  
 
A = f (P,X)          (1) 
 
  where  A is the planted acreage of the commodity,  
P is the price of the commodity, and  
X is a vector of variables representing supply shifters.  
 
This study extended the model similar like those applied in Mythili (2001), Mahmood et al. 
(2007), and Salassi (1995). While Salassi (1995) included government support in the response 
function, Mahmood et al. (2007) empirically showed that paddy planted area is a function of 
lagged paddy planted area, lagged paddy yield, and lagged paddy price. Considering that 
Malaysian paddy production is heavily subsidized by the government, the extended model used 
in this study can be expressed as: 
 
ttttt GOVSPTPDYYLDPDYPRCPDYAPLPDYAPL 4131211     (2) 
 
where  tPDYAPL  is paddy planted area (‘000 hectare),   
1tPDYAPL  is lagged paddy planted area (‘000 hectare),   
1tPDYPRC  is lagged domestic paddy price (RM/ton), 
1tPDYYLD  is lagged paddy yield (ton/hectare); and 
tGOVSPT  is government support (RM million). 
 
With the specification of Equation (2), the data for the identified variables were collected from 
IRRI (2008). The whole set of the data was then verified by using stationary tests. This 
procedure is particularly important to determine which estimation method to be used to estimate 
the equation. The result of the stationary tests would be presented in next section, followed by 
the applied estimation method. 
 
3.0 Results 
 
Table 1 presents the result of the stationary tests, using augmented Dickey-Fuller (ADF) test. 
Most of the computed ADF test-statistics were greater than the critical values (-2.9266 at 5 
percent significant level) at level, they suggested that the set of data had unit root problem. 
However, Durbin-Watson statistics those were smaller than 2 may have autocorrelation problem 
Hence, ADF test was further conducted and found that there was no unit root problem in the data 
set at the first difference (I(1)). 
 
Table 1: Augmented Dickey-Fuller test statistics of unit roots 
Variable Level First Difference 
PDYAPL -3.2627 -9.3732 
PDYPRC -0.3519 -6.6094 
PDYYLD -0.8938 -6.4537 
GOVSPT -0.8980 -6.9758 
Critical value a -2.9266 -2.9281 
Note: a 95 percent confidence level. 
 
Subsequently, Equation (2) extended with first order autoregressive error specification and was 
estimated via linear Ordinary Least Squares (OLS) in log-log form. The simplicity of log-log 
form would provide elasticity estimates in the equation directly, as presented in Table 2. It was 
found that all the variables were statistically significant. Lagged paddy planted area and 
government support were found to have positive relationship with paddy planted area while 
negative sign in lagged domestic paddy price and lagged paddy yield suggests that there is 
negative relationship between the two variables and paddy planted area.  
 
Table 2: Estimates of the acreage response of rice in Malaysia 
Variable Coefficient t-Statistic 
Intercept 1.2741 (2.9833)*** 
)log( 1tPDYAPL  0.5223 (6.4813)*** 
)log( 1tPDYPRC  -0.3036 (-6.5923)*** 
)log( 1tPDYYLD  -0.2449 (-3.1023)*** 
)log( tGOVSPT  0.2891 (6.6393)*** 
AR(1) -0.3526 (-2.0764)** 
R-squared 0.8276 
 Note: Statistically significant *** at 1 percent level and ** at 5 percent level  
 
4.0 Conclusions 
 
While this paper serves as preliminary study to investigate the relative impacts of various factors 
on acreage response of rice in Malaysia, the findings provide mixed signals which are different 
from other rice production countries. Hence, future studies are deemed essential to probe the 
issues with justifications by looking at the connection of Malaysian paddy production and 
economic theory, as well as implications to policymakers. 
 
References 
 
International Rice Research Institute. (2008). 
http://beta.irri.org/solutions/index.php?option=com_content&task=view&id=250 (accessed on 
28 December 2008). 
 
Mahmood, M.A., Sheikh, A D. and Kashif M. (2007). Acreage supply response of rice in Punjab. 
J. Agric. Res., 45(3). 231-236. 
Mythili G. (2001). A Note on Acreage Response for Major Crops in the Selected States, in 
Accelerating Growth through Globalisation of Indian Agriculture, (ed.) Kalirajan K.P. G. Mythili 
and U. Sankar, Macmillan India Ltd.  
 
Salassi, M.E.  (1995). The Responsiveness of U.S. Rice Acreage to Price and Production Costs. 
Journal of Agriculture and Applied Economics, 27(1995):386–99. 


Acreage response of rice: A case study in Malaysia

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Acreage response of rice: A case study in Malaysia

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