1. Introduction
The Cambodian economy is largely dependent on the agricultural sector, which contributes 27% of national GDP (Gross Domestic Product), in which 65% of the labor force are engaged [
1]. Growth in the agricultural sector has played a crucial role in the development of Cambodia [
2]. Since 2004, garments, construction, agriculture, and tourism have driven Cambodia’s growth. Between 2010 and 2013, GDP climbed more than 7% annually [
3], and GDP per capita in purchasing power parity has increased from $2,462 (US Dollar) in 2010 to $3,056 in 2013 [
4]. However, although Cambodian’s per capita income is rapidly increasing, it still remains low compared to other nations in the region. Most rural households depend on agriculture and its related sub-sectors; and rice, fish, timber, garments and rubber are Cambodia’s major export products [
3].
Rice production is central to the Cambodian agricultural sector, and not only do the majority of Khmer farmers depend both directly and indirectly on the success of the rice crop each year, but as it is the main food staple, rice production is a big factor in the national effort to promote food security. It occupies more than 80% of total cultivated land and is the most important agricultural export commodity, as well as the main source of crop value added and the major driver of agricultural growth [
5]. Being one of the most important staple crops for human consumption, rice plays an unprecedented role in combating food insecurity. Furthermore, rice has become a key economic crop that dominates most agricultural economies in the world, particularly in developing countries like Cambodia.
Having similar characteristics to other agricultural crops, nowadays the growth of rice production yield seems to depend on three important aspects: (a) enlarging planting areas; (b) increasing input of material factors; and (c) raising productivity gradually [
6]. Due to the limitation of planting area and material input factors, along with the result of rapid population growth from 11.4 million in 1998 to 15.5 million in 2014 [
7,
8] and, thus, an increasing demand of land areas and material input factors for non-farm activities, raising productivity of rice production should be the most preferable factor among the three factors previously described.
Khmer farmers have been growing rain-fed rice for at least 2000 years, possibly longer in the case of upland rice [
9]. Today, rice production still serves as the foundation of Cambodian economy. Between 1980 and 2010, rice production yield has been doubled from 1.21 tons/ha to 2.97 tons/ha [
10]. However, productivity of Cambodian rice still has been relatively low compared to other Asian countries, such as Myanmar, Indonesia, Vietnam, Japan, South Korea, and China, where rice productivity in 2010 was recorded 4.12 tons/ha, 5.01 tons/ha, 5.32 tons/ha, 6.51 tons/ha, 6.51 tons/ha, and 6.55 tons/ha, respectively [
11]. Therefore, in order to raise the productivity of rice production in Cambodia, it is important to identify the core factors influencing it.
The main objective of this study was to measure the technical efficiency (hereafter, TE) of rice production in Cambodia. Additionally, the study was also trying to identify core influencing factors of TE in order to explain the possibilities of increasing productivity and profitability of rice by increasing efficiency at provincial level, as well as identify what technical progress policy should be recommended to help decision makers increase the rice productivity in Cambodia. The results of this study will be useful for both rice producers and policy makers in government and all other stakeholders along the rice value-chain including development agencies, non-government organizations (NGOs), and many other related parties working towards improving rice production and the agricultural sector at large.
The rest of this article is organized as follows:
Section 2 presents analytical frameworks and methodology for measuring rice production TE, while in
Section 3, the data and descriptive statistics of output and input variables is presented. The results are presented, compared, and discussed in
Section 4. Finally, concluding remarks are offered in
Section 5.
2. Methodology
In the economics literature, productivity refers to the amount of output(s) obtained from given levels of input(s) in an economy or a sector. It is an important topic of study, since productivity is one of the two fundamental sources of larger income streams; the other being savings, which permit more inputs for employment [
12]. Coelli and Rao [
13] argued that productivity is the ratio of the output(s) that it produces to the input(s) that it uses (Productivity = Output(s)/Input(s)). In other words, productivity is raised when growth in output(s) outpaces growth of input(s). Productivity growth without an increase in input(s) is the best kind of growth to aim for rather than attaining a certain level of output [
14]. Nevertheless, measuring the total input and total output is both conceptually and empirically difficult. Methods to estimate productivity and efficiency that are commonly and frequently implemented in most of today’s empirical works are data envelopment analysis (DEA) and stochastic frontier analysis (SFA), which are non-parametric approaches and parametric approaches, respectively.
Between DEA and SFA, which method should be chosen often depends on the application being considered. The SFA is recommended by Coelli [
15] for use in most agricultural applications. This method has the added advantage of permitting the conduct of statistical tests of hypothesizes regarding the production structure and the degree of inefficiency. However, if an application is using farm level data where measurement error, missing variables (e.g., data on an input is not available or not suitably measured), weather, etc. are likely to play a significant role, then the assumption that all deviations from the frontier
1 are due to inefficiency, which is made by DEA, may be a courageous assumption. Thus, only a small percentage of agricultural frontier applications have used the DEA approach for frontier estimation. However, DEA has a very large following in other professions, especially in the management science literature, and in applications to service industries where there are multiple outputs, such as banking, health, telecommunication and electricity distribution, including [
16,
17,
18,
19,
20], etc. Another benefit of the SFA approach is determinants of inefficiency, which allowed external factors affecting efficiency of firms to be determined where unavailable in the DEA approach. SFA, hence, was applied by a large number of papers in the recent years, particularly in agricultural research. For instance, the studies that have implemented the SFA approach include [
21,
22,
23,
24], etc. Furthermore, detailed discussion of the differences between DEA and SFA has been given in Coelli [
15]. Therefore, SFA was also being applied to the present study.
Productivity and efficiency studies have taken the attention of most economists and policy makers in recent years, since there is no meaningful welfare improvement and economic development can take place in the absence of productivity growth [
10]. Productivity is a basic and intuitive measure of performance. Furthermore, total factor productivity (TFP
2) is a method of measuring business performance. TFP is used both in competitive and regulated industries, such as electricity distribution companies [
26], for instance. It is a method of measuring productivity and growth, which is a productivity measurement involving all factors of production. Other traditional measures of productivity, such as labor productivity in a factory, fuel productivity in power stations, and land productivity (yield) in farming, are often called partial measures of productivity. These partial productivity measures can provide a misleading indication of overall productivity when considered in isolation [
27].
However, agricultural productivity and efficiency studies as well as rice production efficiency studies in Cambodia seem to be very poor. Most research works were conducted by the related government agencies, such as the National Institute of Statistics (NIS), the Ministry of Agriculture, Forestry and Fishery (MAFF), Cambodia Development Resource Institute (CDRI), Cambodia Agricultural Research and Development Institute (CARDI), etc. Thus, only a few research works were conducted by the scholars. Given the scarcity of literature on efficiency in Cambodia, the present study, therefore, seeks to augment literature and contribute in many ways to bridge the gap and supplement the shortage.
The objective of this study was achieved through the estimation and analysis of the stochastic production frontier model (hereafter, SFA model), originally proposed by Aigner, Lovell [
28], and Meeusen and Van den Broeck [
29]. The most commonly used package for estimation of SFA model is FRONTIER 4.1c (see Coelli [
30]). The general form of the SFA model:
where
indicates the natural logarithm function form;
and
denotes rice production output(s) and input(s) within period
t, respectively;
represents estimated coefficients;
is statistical random error, assumed to be normal distribution,
;
denotes technical inefficiency, assumed to be truncated normal distribution,
;
and
are assumed to be independent;
i = 1,2,…,
N;
N is number of measurement unit (
), i.e., total samples; and
t is time variable measured as year,
t = 1,2,…,
T.
The present study utilized the logarithmic form of translog production function, thus Equation (1) above can be written as:
The technical inefficiency effect can be expressed in following general form:
where
is the stochastic noises;
denotes exogenous variables that are factors affecting Cambodia’s rice production TE;
and
are estimated coefficients; if
is negative indicates positive relationship between affecting factor variables and TE of rice production, conversely, if
is positive shows negative relationship between TE and affecting factors.
Followed by Equations (2) and (3), the parameters estimation of SFA model can be achieved by applying the maximum likelihood estimation method, which estimates the likelihood function in terms of two variance parameters (see Coelli [
31]):
Gamma (
) takes values between zero and one (
), and reflects validity of the random disturbances (
,
) proportion. If
is closer to zero, it indicates that the gap between actual output and the maximum possible output mainly comes from other uncontrolled pure random factors, which makes the use of stochastic frontier model meaningless. In contrast, if
is closer to one, it shows that the gap comes mainly from the effects of one or more exogenous variables.
, indicates that using stochastic frontier production function model is more appropriate.
Rice production TE of every
can be estimated by the ratio of observed output relative to the potential output defined by SFA model, as follows:
TE value is always smaller or equal to one. When TE is equal to one, it indicates
in the samples is fully technically efficient. Therefore, the closer the TE value is to one, the higher TE of rice production.
Technical efficiency change (hereafter, TEC) of every
between period
t and
t+1 is the ratio of TE in period
t+1 to its TE in period
t, which can be expressed as the following formula:
3. Data and Descriptive Statistics
Data used for the present study were drawn from the document sets of the Royal Government of Cambodia (hereafter, RGC), namely “
Profile on Economics and Social” of 25 entire provinces in Cambodia (24 provinces and one municipality, Phnom Penh) from 2012 to 2015 (four-year dataset) [
32,
33]. These document sets were prepared by the Provincial Department of Planning of every province based on computer programs, namely the Commune Database (CDB) that provided derived data from village and commune data books that are annually documented and kept at communes/sangkats and with the village chiefs or village representatives that are members of the Planning and Budgeting Committee.
The SFA model was constructed by one output variable (i.e.,
quantity) and five input variables, including
land,
labor,
fertilizer,
pesticide, and
machinery. The output variable was the total provincial un-milled rice production
quantity (hereafter,
rice output), which was measured in tons.
Land input was the total area of rice actually harvested within the year, measured in hectares (ha). In many agricultural nations,
land always plays as an important input in production of agricultural crops like rice. Countries harvested larger areas of rice tend to be able to produce higher amounts of
rice output, for example, Thailand and Indonesia, where about 10–12 million hectares of rice was harvested annually compared to Cambodia that could harvest only 2–3 million hectares per year. Thus, production of rice in these two countries were, respectively, recorded at around 20 and 36 million tons (of milled rice) annually, compared to only around 4 million tons per year produced in Cambodia [
34]. Additionally, provinces of Cambodia that harvested more areas of rice were also able to produce more
rice output compared to provinces with lower rates of rice-harvested land. For instance, the province of Battambang and Prey Veng, where around 279 and 268 thousand hectares of rice area were, respectively, harvested in 2015, produced more than 798 and 803 thousand tons of
rice output (respectively), which was much higher compared to Phnom Penh suburbs that harvested only 11 thousand hectares and produced about 2 thousand tons within this year [
33]. Harvested area (i.e.,
land input), hence, was expected to have positive effects on provinces as well as total
rice output.
Labor input, on the other hand, measured as total farmers with rice farming as primary occupation (hereafter, rice farmers), unit in persons. According to the dataset from RGC [
32,
33], provinces with higher rates of rice farmers tended to produce higher amounts of
rice output, since rice remains as their provincial dominant crop as well as the dominant commodity. Thus,
labor input was also expected to have a positive effect on
rice output. Furthermore,
fertilizer input was measured as the total amount of chemical and organic fertilizer quantity use by total families cultivating rice (hereafter, rice families) in the province (unit in tons), while
pesticide input was also measured as the total amount of poison for insect and grass quantity (for both chemical and organic poisons) use by total rice families in the province, units in tons. Followed by the concept of the green revolution [
35], these two input variables were also expected to be positively related to
rice output. Additionally, another important input variable was determined as the variable of capital investment on agricultural
machineries, which was measured as the total amount of tractors, walking tractors (“
koryons” in Khmer language), and rice transplanting machines existing in the provincial territory. This input variable was also expected to have a positive effect on
rice output as well. Along with the global technological expansion, the development of agricultural sector was inevitably linked to the mechanization improvement as many works/tasks in agricultural production, particularly rice production in Cambodia (which normally is labor-intensive), could be completed faster and greater with the performances of these machineries.
Table 1 provides summary statistics of the output and inputs of rice production within entire 25 provinces in Cambodia from 2012 to 2015.
Output quantity of rice production in Cambodia was higher in 2015 than in 2012, which increased 8.4% on average from 290 thousand tons (2012) to 315 thousand tons (2015). Total area of rice actually harvested on average also increased around 8% from 134 thousand hectares in 2012 to 145 thousand hectares in 2015. Total rice families using quantities of chemical and organic fertilizers (i.e., fertilizer input), on the other hand, increased on average by 7%, while pesticide and machinery input (definition same as above) increased greatly between this period. Total rice families using quantity of poison for insects and grass increased by nearly 25% (three times larger than land and fertilizer input), while the total capital investment on agricultural machineries between this period increased by a huge percentage of 64.4%, indicating a huge improvement of mechanization in Cambodian agriculture, particularly in the rice production sector. Nevertheless, along with the improvement of agricultural mechanization, labor input which was measured as total people with rice farming as their primary occupation tended to slightly decrease by 8%, presenting the progression of transformation of labor forces out of agriculture to other higher productivity and profitability sectors, such as industries and services.
Figure 1 illustrates the percentage changes of input and output statistics of Cambodian rice production between the study period 2012–2015. A closer look at percentage changes within output and input variables from year to year indicated that from 2012 to 2013, there were no significant changed within both output and input variables. However, there was a massive change in inputs, particularly in
land and
fertilizer between 2013 and 2014, which caused
rice output to increase greatly. Unfortunately, the natural disasters (drought, flood, and insects) at the end of 2014 and in 2015 had destroyed a huge percentage of rice cultivated
land in most leading rice production provinces (totally reducing around 30% of 2014 production) and
fertilizer input was also decreased greatly (by more than 50%).
Rice output, therefore, also decreased by a great percentage of 20%. Conversely, development of capital investment in agricultural
machineries still continued to increase by 15%–20% per year, while implementation of
pesticide by farmers tended to increase 6%–9% annually as well.
Labor input, on the other hand, had the decreasing trend from year to year in the percentage of 2%–3%.
In the technical inefficiency model (3), there were seven influencing factors of rice production TE to be considered in the present study.
Disaster was measured as a percentage of rice production land damaged by floods, droughts, and insects to total rice production land actually harvested within the year. Apparently,
disaster always caused the lower of harvested land to cultivated land ratio. Thus, disaster was expected to have a negative effect on rice production TE.
Irrigation, on the other hand, measured as a percentage of provincial paddy land having or benefiting from irrigation systems (as well as paddy land located near water sources, such as rivers, lakes, ponds, etc.) to total provincial cultivated land within the year. Irrigation systems could cause the availability of rice cultivated land expansion by improving multi-cropping
3; hence, irrigation was stalwartly expected to have a positive relationship with rice production TE. Additionally,
production technique was measured as a percentage of families cultivating rice under the system of rice intensification (SRI) to total families cultivating rice. Under SRI, which introduced by MAFF with the support of CEDAC
4, various rice cultivation techniques with less utilization of modern inputs and inexpensive methods of planting in relatively dry areas could result in an average yield of 3.6 tons/ha, while, under a similar situation, the yield with traditional farming practice is only 2.4 tons/ha [
36]. Farmers cultivating rice under SRI were expected to have higher productivity than farmers using traditional techniques for cultivating rice. However, the percentage of families cultivating rice under this system still seems to be very low in Cambodia. Furthermore, farmers living in villages located closer to the center of district/khan might be able to get further and faster market information about rice; hence, this factor of
distant to information sources was measured as average distance from village center to the center of district/khan (in kilometers). Agricultural staff, on the other hand, might have played some crucial roles for providing technical support as well as technical knowledge of rice production to the rural farmers. Thus, the number of agricultural supporting staff existing in the province was expected to have positive effects on TE of rice production. The variable of
agricultural supporting staff was included in technical inefficiency model (3), measured as a percentage of agricultural staff included both government officers and NGOs staff (working on agricultural plans or projects) to total rice farmers existing in the province. Likewise, there are two main seasons in Cambodia, i.e., wet season and dry season. Greater availability of water resources during wet season have caused rice crops to be able to grow in every province of Cambodia. However, during dry season, only some provinces (as well as some parts of a province) where rice fields benefit from irrigation systems or are located near water sources could be able to cultivate rice crops. Dry season rice crops always provide higher yield of production, nonetheless it requires plenty of water and utilization of fertilizers, as well as higher commitments to for watching over it. However, rice production during the dry season in Cambodia was still highly dependent on availability of water resources during this season. Available land for cultivating rice during the dry season sometimes was in abundance due to the lack of water. Thus, the improvement of dry season rice was expected to have a positive effect on TE of rice production in Cambodia. The factor of
dry-season production measured as a percentage of dry season paddy land actually harvested to total available land for rice cultivation in dry season was correspondingly included in the model. The size of farm land owned by farmers was also expected to have a positive effect on rice production TE. The great percentage of rice farmers owning farm land less than one hectare, which might cause a limited ability for them to improve their rice production. This factor (
small-land farmers) measured as a percentage of families having paddy land smaller than one hectare altogether with families having no paddy land to total rice families. Conversely, some external factors, such as social, economic, demographic, as well as geographic perspectives of each province were omitted from the technical inefficiency model (3), due to insufficient availability of appropriated datasets during the study period. Furthermore, the present study utilized only a four-year dataset of the entire 25 provinces of Cambodia, which limited availability of including too many influencing factors into the model, as it might cause unexpected conflicts or correlations among factor variables. Moreover, provinces of Cambodia were a bit tiny in areas and normally the local governance as well as the economy are still under direct control of the central government in Phnom Penh (i.e., provincial local governments in Cambodia are not very independent from each other like the situation in other countries like China, for instance). Therefore, the present study assumed these external factors to be neutral to rice production TE. Thus, Equation (3) can be written as:
Table 2 presents descriptive statistics of Cambodian rice production efficiency’s influencing factors between 2012 and 2015. The percentage of rice land damaged by floods, droughts, and insects was lower in 2015 compared to 2012. Rice land damaged by disasters in 2012 was 18.8% in average, while, in 2015, disasters destroyed only 5.2% of rice production land on average (a decrease by 72.4%). However, flooding in the wet season of 2014 has still destroyed almost 30% of total rice cultivated land within the year. These percentages still remain huge, which ought to be considered by the RGC and the related agencies. Furthermore, from 2012 to 2015, there were also large percentage changes in rural farmers’
production techniques and amount of
agricultural supporting staff existing in the province.
Production techniques, which were measured as a percentage of families cultivating rice under SRI decreased greatly by 20% within three years, while percentage of
agricultural supporting staff (to total rice families) also decreased by around 17% during this period, indicating a lack of technical supporting techniques as well as technical improvement training for farmers with the purpose of improving the national rice production, particularly for small-land rural farmers, of which most of them are rice farmers. Although the percentage of
small-land farmers (farmers owning no rice cultivated land or having rice land smaller than one hectare) have been slightly reduced during the study period (less than 5%). In 2015,
small-land farmers in Cambodia still accounted for 39.8% on average, which was still the vast percentage. Moreover, during the dry season, available land for cultivating rice was still not fully cultivated yet. In the study period 2012–2015, on average, more than 30% of available dry season rice land was abundant annually. During 2012, on average, only 68.5% of the total available dry season rice production land had been actually cultivated, and this percentage became worse in 2013 (58.8%). Although the situation had been slightly improved in 2014, while this percentage slightly increased to 65.1%, water shortage during the dry season of 2015 had reduced the percentage of dry season actually cultivated land again to around 64.9%. Therefore, there is still a huge gap for Cambodian famers to improve their rice production during dry season as well as total production of rice.
Irrigation plays a very important role for rice production in Cambodia, particularly in the dry season. Between 2012 and 2015, irrigation systems were improved gradually by increasing the percentage of paddy land having irrigation systems from 21.7% in 2012 to 22.6% in 2015 (3.5% increased within three years). However, this irrigation rate still seems to be very low compared to other agricultural nations, especially its neighboring countries like Thailand, and Vietnam, since another nearly 80% of total cultivated land is still being used as the rain-fed agricultural land. These statistics revealed that irrigation systems in Cambodia still remain lacking, with shortages far behind its potential to improve national rice production. In many developed countries, irrigation systems are not only used for agriculture, but are also being used as natural disaster prevention devices. Global climate change has been affecting Cambodia in the latest decade. Natural disasters like floods and droughts occurred more frequently than previously. Sometimes, within a year, Cambodian people suffered from flood in wet season, and then suffered again from droughts in dry season. This could be the result of irrigation system shortage, which caused Cambodia to have no ability to deal with such frequently occurring disasters. What if Cambodia could build irrigation and water storage systems in order to store over-needed water resources during the wet season and keep them for utilization in agriculture during the dry season?
5. Conclusions
The aim of this paper was to estimate the TE of rice production in Cambodian and determine its main influencing factors by using the SFA model. The present study utilized a four-year dataset generated from the central government document “Profile on Economics and Social” of all 25 provinces between 2012 and 2015. The results indicated that the level of rice output in Cambodia varied according to the different level of capital investment in agricultural machineries, total rice actual harvested area, and technical fertilizer application within provinces. The mean TE of rice production is 0.784, which means that famers in this region produce rice 78.4% efficiently with best practices at the current level of production inputs and technology. This means that rice output has the potential of being increased by a further 21.6% at the same level of inputs if farmers had been technically efficient. However, during the study periods, the TE of rice production recorded a 7% decreasing rate. Takeo province was the most effective province nationwide, while another 60% of provinces still had TE below the average mean efficiency in 2015.
Three main conclusions emerged from the study’s results. First, based on decomposing the SFA model, enlarging capital investment at the provincial level into agricultural
machineries is the core input factor influencing rice production in Cambodia, while the expansion of total rice land actual
harvested area, and technical improvement of
fertilizer application range were the second and third core input factors, respectively. These results are not very surprising since they are straightforward techniques for increasing rice productivity in most developing countries in the world. Likewise, these results also confirmed the existing problems in Cambodian rice production sector, which were previously addressed by relevant studies [
1,
2,
5,
37,
38]. However, agricultural mechanization in Cambodia still faces numerous challenges including: (1) the national policy on agricultural mechanization is not yet prepared; (2) the structure of the Provincial Office of agricultural engineering is still weak; (3) inadequate skilled workforce at both national and provincial levels; (4) credit scheme for buying farm machinery and equipment is non-existent; (5) most of the workshops for repairing and maintenance of farm machinery and equipment are not available in the rural areas; (6) annual budget allocated for the implementation of agricultural mechanization activities fails at nationwide coverage; (7) less activities in research and development on agricultural machinery and equipment, and they exist mainly at the national level; (8) external support and cooperation with development partners is still missing; and (9) there are gaps in cooperation with the private sector dealing with farm machinery [
39]. Local manufacturers of farm machineries and equipment usually produce threshers, water pumps, locally made trucks for transportation, trailers, implements and spare parts such as cage wheels. Nonetheless, they can manufacture only simple machines that do not require sophisticated production processes or tools. Normally, they are still small scale and family owned with a few workers, and operate seasonally for supplying local markets [
40]. Thus, large-scale machineries, such as tractors, walking tractors (
koryons), etc., are still being imported from major countries including Belorussia, China, Japan, India, US and Thailand. This revealed the lack of ability as well as local technical experts for Cambodia to be able to manufacture large heavy-scale agricultural machineries by itself. Financial institutions (microfinances and commercial banks) are the major sources of credit for making machinery purchases for farmers. Conversely, due to Cambodia not yet having had any agricultural bank to support credit schemes for buying farm machinery and equipment, farmers have had to use their own savings or borrow from existing financial institutions or dealers to buy new machines, where often they are provided with relatively higher interest rates for loans (on average 24% per year) compared to neighboring countries like Vietnam (less than 1% per year).
Harvested area, on the other hand, had the highest elasticity among all input factors of rice production in Cambodia. It is clearly indicated that increasing
harvested area (i.e.,
land input) could cause the increase of rice output at a higher percentage than all other inputs. However, although the RGC has been trying to increase rice production by enlarging the total area of rice fields annually, this enlargement still remains far behind its enormous potential to increase rice productivity. Therefore, significant commitments and supported actions are required to address the problem.
Second, production techniques for rural farmers, technical skills and amount of agricultural supporting staff are the most important influencing factors of rice production in Cambodia. Although SRI has been introduced before 2008, the percentage of farmers cultivating rice under this system still seems to be low. Enlarging percentage of farmers cultivating rice under the SRI instead of traditional rice cultivating techniques by the widespread introduction of this system to rural farmers, together with the strengthening technical skills of agricultural supporting staff, and building up of stronger relationships between rural farmers and supporting staff, as well as the relationships between the related agencies, might be the best solution for this. Likewise, extra research and development in new production techniques of rice cultivation are still needed for improving rice productivity. Finally, the agricultural sector as well as rice production in Cambodia is always inevitably linked to development of irrigation systems and good water management practices. Nonetheless, several constraints in irrigation development still exist. Irrigation systems in Cambodia are still in development and do not provide coverage for the whole country due to a lack of supporting financial resources and technical experts. Moreover, most farmers’ paddy fields are small and lack road access systems for paddy fields far from the road. In addition, there is a lack of drainage systems for paddy fields and sometimes rainfall during harvesting, which also remain as constraints to progress. Development of irrigation systems and good water management practices are therefore of relevant magnitude to be heavily considered by policy makers for developing strategic policies geared towards enhancing rice production.
Therefore, the main factors affecting the output level of rice production in Cambodia appear to be capital investment in agricultural machineries as well as efficiency of machinery performance, actual harvested area, and fertilizer utilization, while irrigation and good water management, production techniques, and technical supporting staff serve as main factors affecting TE of rice production in Cambodia.
In conclusion, in addition to capital investment, and improving technical skills for both supporting staff and rural farmers in order to improve rice productivity in Cambodia, the present study recommends that the development of irrigation systems and good water management practices be strongly considered and bring about more effective actions by the central government as well as related agencies for preventing frequently occurring natural disasters and increasing actual harvested area, particularly in the dry season.