INTRODUCTION
Glutinous rice has been an important life crop for Thai people for a long time.
Apart from consumption, glutinous rice is deeply associated with Thai culture
and tradition. It is also important in terms of food security for farmer households
especially small farm holders in the Northeast. The area for growing glutinous
rice in Thailand is approximately 14 million Rai. Approximately 80% of the area
for growing glutinous rice in Thailand is in the Northeast (Kongritti,
2009). Despite huge effort on the part of research work and the government,
glutinous rice production in Thailand has not been increase according to the
genetic potential of varieties. Average glutinous rice yield is much below than
potential output, especially in the Northeast region. It has been found that
the average glutinous rice yield is 2,012.5 kilograms per hectare while the
country’s is 2,293.75 kg ha^{1} (OAE, 2011).
There are number of factors contributing to this yield gap. This is also due
to problems regarding soil quality, inappropriate use of input factors and the
fact that rainfall is the main factor in the cultivation. Studies have shown
that Thai farmers had been producing rice below the ultimate potential output
(Patmasiriwat and Isvilanonda, 1990; Sriboonchitta
and Wiboonpongs, 2000, 2004; Pochatan,
2005; Songsrirod and Singhapreecha, 2007; Srisompun
and Isvilanonda, 2012). The findings suggest there is scope to increase
their production efficiency. Increasing average rice yield under the present
technology could be achieved by improving the socioeconomic characteristics
and production management of farmers. In other words, technical efficiency of
rice production can be increased by improvements in farmer characteristics,
farm characteristics, environmental condition and agricultural practices (Songsrirod
and Singhapreecha, 2007).
Monitoring crop cultivation system and rice output from the past shows that
monoculture rice cultivation or ricerice cultivation for a long time results
in inefficient use of soil especially in dry seasons as there is not enough
water for crops. The system set up for growing crops during the intermediate
phase between late wet season and early winter is therefore very important.
This is because the moisture in the soil is enough for another type of crop
to grow (Pookpakdi, 1998; Ali et
al., 2012). Growing rotating crops is therefore needed to increase income
for farmers in rainfed area during dry season. This also shows one of the ways
to optimise benefits from the land efficiently (Boonngern
et al., 2011; Suprama et al., 2011).
From the above points, it can be seen that systemising crop cultivation is
necessary in improving productive efficiency under existing resources that one
or the community possesses (BorNgern, 2006). Farmers
can start by themselves or learn from their farmer friends who have used appropriate
factors of production and production systems and have not waited for external
help. Thus, this study aims to comparatively analyse the use of input factors
and the efficiency of the use of such input factors in a monoculture farm and
the appropriate combination of glutinous rice growing and other economic crops
systems in rainfed area. The study also includes the analysis of factors that
affect the productive efficiency level of farmers in the area. In order to be
able to come up with a way to develop productive efficiency and increase income
for farmers, we also need to know the efficiency by comparing production environments
and appropriate production systems. Results from the study are important for
farmers and relevant organisations in deciding the system for growing rice and
appropriate production plans which will enhance productive efficiency, improve
income and establish sustainability for rice farmers.
MATERIALS AND METHODS
Study area and data collection: The study collected data from farmers
who grow glutinous rice in rainfed area of Roi Et which is in the Northeast
of Thailand. The data used is from January to December, 2012. The data includes
that of farmers who grow glutinous rice in three different systems namely glutinous
rice monoculture, ricesweet corn and ricepeanut. All farmers grow RD6 glutinous
rice which is the most popular type of glutinous rice grown in Thailand. The
sample was selected through purposive sampling. Details of the selection process
are as follows:
Step 1: 
Select the district with the largest area that grows glutinous
rice in Roi Et which is Phon Thong District (Amphoe Phon Thong) 
Step 2: 
Select the subdistrict (Tambon) with areas that have at least 3 different
cropping systems for glutinous rice which is Tambon Wang Samran 
Step 3: 
Conduct purposive sampling for farmers in 3 different cropping systems
for glutinous rice namely rice monoculture, ricesweet corn and ricepeanut.
Thirty samples are selected from each system (Fig. 1) 
Step 4: 
Collect data using questionnaires featuring details in the production
process, management and the use of labour in each production activity, expenses
spent in buying input factors, outputs and returns as well as production
problems. Then, the data will be analysed with regards to factors that affect
the productive efficiency of glutinous rice production in different cropping
systems. Details are elaborated in the next section 
Analytical framework: Productive efficiency measure is important in
evaluating the capacity or productive efficiency of the production unit. It
allows us to know the state of the production unit. If it is not healthy, we
will be able to cure it. Hence productive efficiency of a production unit refers
to the comparison between the actual outcome that a production unit can produce
and the highest outcome estimated for production unit under certain factors
of production and technology. Efficiency measure is said to be an important
tool and is very beneficial in comparing capacity of a production unit whether
it is relevant to producers, businesses, agencies or various organizations.
Efficiency measure helps us to point out any inefficiency and correct them.
Total Economic Efficiency (EE) includes two main components; Technical Efficiency
(TE) which means the ability of the production unit to increase its output under
the same amount of resources and Allocative Efficiency (AE) which means the
ability of the production unit in using appropriate proportion of input factors
under conditions of existing price levels of input factors (Farrell,
1957).
Technical Efficiency is the ability of the production unit to improve production
techniques in order to increase output using the same factors of production
or reduced input factors resulting in the same amount of output. It may also
mean the development of productive efficiency level under existing technology
using the same amount of input factors but changing the way of input factors
are used. Changes may involve features and specific properties of each farmer
as well as the production’s management
systemusing the principle of technical efficiency and farm management.

Fig. 1: 
Sampling technique in study area 
Technical efficiency measure presented by Farrell (1957)
is the comparative measure of productive efficiency for production unit through
the evaluation of Frontier equation in order to calculate output using highest
possible comparison of interested production units. Then results will be compared
to outputs that we estimated in terms of the distance from the highest point
on the boundary line. Hence this study will evaluate the technical efficiency
of the use of input factors as one can tell differences between efficiencies
with regards to production environments, the use of factors of production and
different management production systems of farmers.
The evaluation of the efficiency regarding the use of input factors uses Stochastic
Production Frontier Model (Meeusen and van den Broeck, 1977;
Aigner et al., 1977; Battese
and Corra, 1977). Error term is distributed with halfnormal distribution.
This reflects the inefficiencies of farmers. Such model can be shown in Eq.
1:
where, Y_{i} is output of farmers in ith order, f (.) is the appropriate
production function. In this model, it is a CobbDouglas production function,
x_{i} is the vector of the amount of input factors for farmer in ith
order, β is the vector of the parameter that needs to be estimated, V_{i}
is the error resulting from uncontrollable factors such as natural disaster
and changeable climate and U_{i} is the value of farmers’ inefficiencies.
After the model is estimated using Maximum likelihood technique, one can calculate
technical inefficiency and technical efficiency of farmers in each income group.
Methods used in this estimation can be further studied by Kumbhakar
and Lovell (2000).
As for the equation format for Stochastic Production Frontier Model that is
used in this study, CobbDouglas production function is selected because it
is easy to estimate values. Estimation can be done by changing it into a linear
equation in Logarithmic terms. Coefficients of independent variables in the
CobbDouglas equation show the elasticity of output to each factor of production.
Moreover, the sum of coefficients (elasticity) of independent variables also
shows the returns to scale. This is beneficial in deciding whether to expand
the production and in adjusting the proportion of the use of factors of production
for the highest efficiency. Details are as in Eq. 2:
From Eq. 2, the dependent variable is the glutinous rice
output of each farmer (Y_{i}: kg per Rai). Independent variables are
the number of seeds (SEED_{i}: Kilograms per Rai), the amount of chemical
fertilizers used (FERT_{i}: kg per Rai), labour use (LAB_{i}:
hours per Rai), machine hours (MACH_{i}: hours per Rai) and a Dummy
Variable which reflects other two cropping systems namely ricesweet corn and
ricepeanut (CS_{1} and CS_{2}).
After Eq. 2 is estimated using Maximum likelihood technique,
technical efficiency for each farmer will result. These results can be compared
and calculated for average efficiency level for farmers in each cropping system.
In the last step, productive efficiency levels from Eq. 2
will be analysed in terms of factors that influence changes in the said efficiency
levels through calculations of variable relations through Simple Linear Regression
Model using Least Square Method. Factors considered include age of the household
leader (AGE), education level of the household leader (EDU), agricultural experience
of the household leader (EXP), proportion of hired labour to total labour (RLAB),
proportion of machines to total labour (RMACH), rice planting technique (PTEC);
PTEC = 0 for broadcasting technique and PTEC = 1 for transplanting technique,
stubble burning before ploughing (STB), farm size of glutinous rice area (SIZE)
and the proportion of agricultural income of a household (RFINC). Details of
these are shown in Eq. 3:
RESULTS AND DISCUSSION
The analysis of glutinous rice production equation using Stochastic Production
Frontier Model in Eq. 2 using Maximum Likelihood Technique
gives the estimation as stated in Eq. 4:
where, **means statistical significance at the confidence level of 95%, Log
likelihood = 21.71, values in parenthesis refer to tstatistic.
From Eq. 4, it has been shown that of the six estimated parameters,
two were found to be statistically significant in the CobbDouglas Model. Seeds
and chemical fertilizers are factors that affect glutinous rice output the most
in this study. With regards to the dummy variable which reflects different cropping
systems, it has been found that ricesweet corn is positively correlated to
output that is farmers in this type of cropping system receive higher output
than that of ricemonoculture while it is quite the opposite for ricepeanut.
For ricepeanut, the output is lower than that of ricemonoculture. However,
as parameters of the two variables are not statistically significant, one has
to consider in conjunction with technical efficiency of glutinousrice growing
technical efficiency level of glutinous rice cultivation in each cropping system
which will be explained in more detail.
When considering returns to scale of rice cultivation in rainfed area, it has
been found that the sum of coefficients of the estimate is 0.253. This means
glutinous rice cultivation in rainfed area exhibits decreasing returns to scale.
This means that the increase in factors of production by 1% results in the increase
in output of 0.253% only. This conforms to the study on previous returns of
glutinous rice cultivation in Thailand (Songsrirod and Singhapreecha,
2007; Pochatan, 2005; Srisompun
and Isvilanonda, 2012).
Once the estimation in Eq. 4 is calculated to find technical
efficiency level of glutinous rice cultivation, it is found that farmers in
the studied area still have low technical efficiency. Technical efficiency level
for glutinous rice cultivation equals to 0.7163 or 71.63%. This means that under
the current resources and technology, farmers in the area are producing 28.37%
lower than their highest potentials. Farmers can increase their productive efficiency
level through an improvement in particular economic, social and productive management
characteristics in the plantation. From the comparison of productive efficiencies
of glutinous rice production in 3 different cropping systems, it has been found
that average technical efficiency levels of farmers in each system are not very
different. Average technical efficiency level for farmers in ricemonoculture
cropping system is 72.25% while that for ricesweet corn and ricepeanut systems
are 71.93 and 70.79%, respectively. Even though the average output of glutinous
rice in the ricesweet corn system is the highest at 487 kg per Rai, the technical
efficiency level of glutinous rice cultivation is not very different from that
of farmers that grow glutinous rice in other different cropping systems. The
main reason why rice cultivation efficiencies are not so different in each system
is likely to be that farmers do not really consider the amount of fertilizers
left in the soil in the period of dryseason crop cultivation. During such period,
one should reduce the use of fertilizers in rice cultivation. Even though, farmers
still use fertilisers and other factors of production just like in ricemonoculture
cultivation. When farmers are divided into 3 groups according to their technical
productive efficiency level which are high (more than 0.80 or 80%), medium (0.500.80
or 5080%) and low (below 0.50 or 50%), it has been found that around 12% of
farmers have low technical efficiency level. Of that, 5 from 11 household are
farmers who grow rice in ricemonoculture system whereas most farmers of around
48% in every system have medium technical efficiency level and 40% are in high
efficiency level (Table 1).
Although, the comparison of glutinous rice productive efficiencies for each
system is not so different, the comparison of agricultural income of households
finds that farmers who grow rice in ricesweet corn and ricepeanut systems
have higher income than those who grow rice in ricemonoculture system. The
study of income of farmer households in ricesweet corn system has found that
the highest household income from agricultural sector is 48,657 baht per household
per year. Coming second is the ricepeanut system with the income of 32,318
baht per household per year whereas, ricemonoculture comes last with 29,553
baht per household per year. The analysis on the difference of income from agricultural
sector in rotating systems and glutinous ricemonoculture has shown that there
is a statistically significant difference at the confidence level of 95%. Households
that grow in rotating systems have higher income than those using a monoculture
system.
The result from the estimation of Eq. 3 which studies factors
that affect the change in technical efficiency level through the use of Simple
Linear Regression Model using Ordinary Least Square method is as stated in Eq.
5:
Where, *,**mean statistical significance at the confidence levels of 90 and
95%, respectively.
The first group concerns characteristics of household leaders. Normally, age
reflects agricultural experience of the household leader. This is because, in
Thailand, most farmers start growing rice after they are graduated from the
compulsory education (Grade 4 or Grade 6).
Table 1: 
Technical efficiency level and income from glutinous rice
cultivation for each cropping system 

Hence older farmers have more experience in terms of rice cultivation. The
result from the estimation of the correlation of the said factor and technical
efficiency level shows that there is a positive correlation. This means that
more rice cultivation experience results in higher technical efficiency level
in terms of glutinous rice cultivation. However this has no clear proof yet
as the coefficient of such variable has no statistical significance at the confidence
level of 90%.
The second group concerns the physical qualities of the farm as farmers have
changed their ways of rice cultivation a lot. In the past, human labour in the
household formed the main part of labour work. At present, hired labour is used
in almost every activity of the production. More farmers have changed their
status from ‘farmer’ to ‘rice field manager’. Hence hired
labour is an important factor that influences the change in productive efficiency
level of glutinous rice cultivation of farmers. This reasoning comes from the
coefficient of RLAB in Eq. 5 which is the positive value of
0.19 and has the statistical significance at the confidence level of 95%. Also,
nowadays, Thai farmers are entering into a society of the elderly and the average
age of farmers is 54 yearold and is increasing (Butso
and Isvilanonda, 2010). Young labourers are moving from agricultural sector
to industrial and service sectors with high income and stability. Hence there
are more hired labourers working in paddy fields than labourers from households.
With regards to cultivation size, it has been found that the coefficient for
farm size variable is 0.01. This means that farmers in larger cultivated area
have a tendency to have lower efficiency level. This contradicts the previous
study which found that farm size is not affects the change in efficiency level
(Pitipunya, 1995). Some studies state that larger farms
have a tendency to have higher efficiency than small farms (Srisompun
and Isvilanonda, 2012). The last variable in this group is the proportion
of machine labour. It has been found that the result of the analysis of the
coefficient has not statistical significance. Hence the proportion of machine
labour cannot explain the change of technical efficiency level of glutinous
rice cultivation.
The third group concerns the variable of glutinous rice cultivation plan. In
this group, glutinous rice cultivation method is the variable that can explain
the change in technical efficiency level for glutinous rice cultivation. Farmers
who use transplanting technique have a tendency to have higher efficiency level
than farmers who use broadcasting technique and stubble burning before ploughing
correlate in the same way as the change in efficiency level yet there is no
statistical significance from this variable. The financial status of the farm
is the variable that correlates to the change in technical efficiency level
at the confidence level of 90%. It has the coefficient of 0.09. This means that
the increase in the proportion of household income in the agricultural sector
for 1 unit will cause the technical efficiency level of glutinous rice cultivation
to increase by 0.09 units. Hence, households with higher proportion from the
agricultural sector have the tendency to have higher efficiency level than other
farms. Thus, there is an indirect influence which can be said that the cultivation
using rotating crop system with higher income from the agricultural sector is
an important factor that can result in higher technical efficiency level for
farmers.
CONCLUSIONS
This study has shown that farmers who grow glutinous rice in rainfed area in
Thailand still have low technical productive efficiency. This means that they
can produce lower than their highest potential level. The result of the study
from the production equation has found that fertilizers and seeds are important
factors in the change of glutinous rice output in the studied area. Moreover
the analysis of the sum of the coefficient of input factors also states that
the production of glutinous rice exhibits decreasing returns to scale. The comparison
of glutinous rice productive efficiency level in each system has found that
the average efficiency level is 0.7163% or the inefficiency level is 28.37%.
Technical efficiency level of glutinous rice cultivation for each level is not
very different yet farmers who grow rice in rotating crop systems have higher
net income from the agricultural sector than ricemonoculture. This conforms
to the result from the correlation analysis of the proportion of income from
the agricultural sector and the technical efficiency level which has found that
farmers who have increasing proportion of income from agricultural sector tend
to have increasing technical efficiency level in glutinous rice production.
This study thus suggests that even though the rotating cropping system does
not result in a difference in technical efficiency level of glutinous rice production,
it results in farmers having higher net income for the farm than that of glutinous
ricemonoculture. Hence rotating cropping system is crucial for the improvement
of income of farmer households in rainfed area. Relevant organizations should
encourage planning for rotating cropping system in order to improve income and
living standard of households in the agricultural sector in the rainfed area.
Furthermore, the analyses on the correlation of technical efficiency level
and farmer characteristics as well as 5 groups of production plan show that
apart from the income proportion from households, factors which influence the
change in efficiency level include the farm size, planting technique and the
proportion of hired labour. They affect the change in technical efficiency score
to the higher degree. This shows that households with higher proportion of hired
labour than household labour have a tendency to have higher efficiency level
than those with only household labourers. This can be used to nicely explain
the state of oldage agricultural labourers and the deficiency of young labourers.
This is because most household labourers are the elderly. Hence technological
development that saves human labour is now needed for the rice production sector.