1. Introduction
Energy from fossil fuel and renewable sources are a vital resource for human development and agriculture. Globally 473 quads (1 quad = 10
15 BTU = 1.05 × 10
18 Joules [
1]) of fossil fuel and renewable energy used every year [
2], which is mainly due to population growth, urbanization and high level of resource consumption rates [
1]. Future demand for energy is projected to double every 32 years in response to a doubling of population\every 50–60 years [
2,
3]. Developing economies with a high rate of population growth are increasingly using fossil fuel in agriculture to meet growing demand for food and fiber [
1]. The global production of inorganic fertilizers, a vital input necessary for modern agriculture, has declined by 22%, and due to limited amount of fossil fuel, its availability is likely to decline further in the future [
1].
Cereals (rice, wheat and corn) make up about 80% of the global food production and the remaining comes from soybeans, roots and tubers (e.g., cassava, potato and sweet potatoes) [
4]. However, energy composition varies drastically between highly mechanized–high productivity system and high labor–low productivity system for the same crop. For example, energy input–output ratio of producing corn per ha is 1:4.11 in USA and 1:1.08 in Indonesia. Consequently, productivity of corn in USA is 5.46 times higher, estimated at 9400 kg/ha, as compared to only 1721 kg/ha in Indonesia [
1]. However, such high-energy consumption based food production system is not going to be sustainable. Worldwide cereal produced per capita has declined since 1984 and it seems that food supply is unlikely to be sustained in the future [
1]. Therefore, it is important to explore production technologies, which are not only capable of producing more food and profitable, but also energy efficient.
The agricultural economy of Bangladesh, dominated by cereal crop production, has also experienced a dramatic rise in the energy consumption over time owing to diffusion of the Green Revolution technology. For example, energy intensity in the agricultural sector in Bangladesh has increased from 1.78 in 2000 to 11.31 in 2008 [
5], thereby adding substantial pressure on the existing acute shortage of energy in the economy [
6]. Rahman and Kazal [
7] noted that energy use increases by 0.14% for every one percent increase in cereal output, at the farm level in Bangladesh. The government of Bangladesh has been trying to enhance other sources of food production since 1990s, which can generate high income for farmers and export earnings for the economy, e.g., fisheries and aquaculture. Fish alone accounts for 60% of daily protein intake and about 11% of the total population of Bangladesh are engaged in the fisheries sector either on a full-time or part-time basis [
8].
In recent years, freshwater prawn farming has become a major contributor to global aquaculture in terms of quantity and value of production [
9]. About 571,152 t of freshwater prawns were produced worldwide in 2013 and the sector is valued at USD 3 billion/year [
10]. The integrated culture of rice and prawn in inundated rice fields is a traditional practice in many Southeast Asian countries [
11,
12]. During the last two decades, integrated prawn-fish-rice farming has expanded in Asia, mainly due to export potential of freshwater prawn (
Macrobrachium rosenbergii) and its high market value [
13,
14].
Freshwater prawn cultivation in rice fields started in Bangladesh during the 1970s, gained momentum from the mid-1980s due to favorable agro-climatic conditions prevailing in the coastal regions [
3,
15]. The total area dedicated to prawn cultivation in Bangladesh was estimated at 275,509 ha in 2015/16 producing 239,798 t of shrimp/prawn with a yield level of 870 kg/ha [
8]. Approximately 1.15 million farmers are involved in prawn and shrimp production, of which 315,000 farmers (27%) are employed in prawn culture [
16]. Prawns and shrimps are considered as the 2nd largest export industry after garments. Bangladesh exported 40,728 t of prawns and shrimps valued at USD 459 million in 2015/16 [
8]. Although the country mainly practices low-intensity prawn farming system, it has great potential. For example, Ahmed and Flaherty [
17] noted that if the low-intensive prawn farming system could be expanded by only 50% of the potential area of 55,000 ha in the southwest region, the country could earn an additional USD 70 million of revenue annually.
About 60–70% of the freshwater prawn farming in the southwest region of Bangladesh is conducted within a
gher farming system that incorporates joint operation of three enterprises: freshwater prawn, carp and HYV Boro (dry winter season) rice [
15]. The locally used term
gher refers to the modification of rice fields by building higher dikes around the field and digging a deep canal inside the periphery to preserve water during the dry season [
18].
Gher farming is a unique indigenous innovation, which is suitable for the cultivation of prawn, fish, rice and dike crops. The widespread development of the
gher farming system in coastal regions of Bangladesh was likened to a ‘blue revolution’ [
19], which in turn refers to the rise of aquaculture as an important agricultural activity [
20].
A unique feature of the
gher farming system is the use of a wide variety of inputs, particularly diverse feed ingredients, some of which are sourced naturally. A number of papers on
gher farming exist, but those are mainly focused on its management aspects and/or food security [
13,
17,
21] and profitability and productivity of the system [
15,
22]. Only Rahman and Barmon [
6] examined the energy productivity and efficiency of the
gher farming system based on a cross-section data for the crop year 2006, which concluded that the system is sustainable in terms of energy use. However, there is no literature that has explored whether the system is performing well and is sustainable over time when evaluated in terms of energy use. This is because a production system can be considered sustainable over the long term if any net increase in energy output surpasses the net increase in energy input levels [
6]. Furthermore, the composition of energy used, i.e., the balance between renewable and fossil fuel based sources, is important to examine since the latter is becoming scarce over time [
23]. This is particularly important for the
gher farming system since it is a highly input intensive production technology. Marques et al. [
24] noted that integrating freshwater prawn farming with other farming activities has considerable potential as a means of increasing food production in a sustainable fashion.
Sustainability in agriculture is a complex concept with several dimensions to consider and its measurement is quite challenging [
25,
26]. Although several indicators were developed to measure agricultural sustainability, they do not cover all dimensions [
26]. For example, Sabiha et al. [
25] developed a composite indicator based approach using 17 indicators to capture multi-dimensional aspects of agriculture to measure only environmental sustainability. In this study, we applied a consistent method where all inputs and outputs of an agricultural production system are measured in energy units and examined its performance over time, which enabled us to incorporate the notion of the dynamics of sustainability as well.
Given this backdrop, sustainability of the gher farming system was evaluated in terms of energy use by examining various measures of energy performance. The specific aims of this study are to: (a) examine trends in basic energy performance measures of the gher farming system over time; (b) identify the drivers of energy productivity of the gher farming system; (c) identify the determinants of technical energy efficiency; and (d) most importantly, examine changes in Total Factor Energy Productivity (TFEP) and its key components: technical change (TC) and technical energy efficiency change (EEC) over time.
The specific contributions of our study to the existing literature is mainly on the methodology to compute TFEP, TC and EEC. Conventionally, TFEP and/or total factor energy efficiency (TFEE) analysis were conducted at the macro-level or regional level for an economy as a whole, where the output is specified as the Gross Domestic Product (GDP) and labor/employment, energy consumption and capital stock are used as inputs. The main approach applied is the non-parametric Data Envelopment Analysis (DEA) [
27,
28,
29,
30]. Although improvements were made in terms of measuring TFEP/TFEE using multi-stage Slack Based DEA model [
27] and improved calculations of TFEE using no-output growth or output growth models [
28], the basic approach suffers from two limitations. One is the well-known limitation of non-parametric DEA approach, i.e., all statistical noises and measurement errors are included as inefficiency, implying that energy efficiency scores derived may be biased. Second, the input and output variables used in the analysis are not measured in energy units. Except the energy consumption variable, all other variables are measured in different units and are subject to issues of aggregation (e.g., GDP is an aggregate measure) and/or construction procedures, e.g., construction of capital stock is open for interpretation because the correct value of this variable over time for an economy at a disaggregated scale can hardly be obtained. Although, units of measure do not pose any serious problem in DEA approach, it is desirable to specify variables that are not subject to the limitation of aggregation and/or construction problems. Such varied unit of measurement of variables necessitated the calculation of TFEE by making adjustments [
27,
29,
31,
32]. Therefore, all these issues can lead to biased measures of TFEE and/or TFEP consequently leading to biased policy prescriptions. We use the well-established concept of Total Factor Productivity (TFP), which is based on the theoretical foundation of underlying production function. Furthermore, we apply the parametric method for the analysis, specifically, stochastic input distance function approach, which can conveniently incorporate the specification of multi-output multi-input production technology and, therefore, do not require aggregation of outputs or inputs into single indices. This approach can separate statistical noise and measurement errors from inefficiency as well. Furthermore, we consistently measure all outputs and inputs in energy equivalent units actually used in the production process, implying that no proxy variables measured in different units are used. Therefore, the resulting TFEP index is of the Malmquist type index and the two associated components are TC and EEC (equivalent to TFEE), requiring no adjustments to obtain TFEE as done by the previous studies. The other contributions of our study to the existing literature are as follows. We provide information on the changes in common partial measures of energy performance over time of this unique farming system, which is relatively more robust than the conclusions drawn from cross-sectional studies undertaken at a point of time [
6]. We also identify significant drivers of energy productivity and technical energy efficiency and other performance measures, such as, scale economy and output jointness or complementarity amongst enterprises. Furthermore, the computation of TFEP, TC and EEC indices of the
gher farming system will provide information on whether there is net growth in productivity of this farming system and whether it can be sustained over time when evaluated in terms of energy use. This is because TFP indices capture the effect of improvements in technology in the form of R&D [
33]. Furthermore, higher TFEP is desirable because it implies higher output from the application of technology, better utilization of resources and leads to a reduction in poverty in rural areas [
34]. The results will also be useful for policy makers and relevant stakeholders aimed at enhancing food production and increasing income of the farmers without compromising sustainability of the system.
4. Conclusions and Policy Implications
The principal aims of this study were to evaluate trends in basic energy performance measures over time and to compute TFEP, TC and EEC indices of the gher farming system, which is operating in the coastal regions of Bangladesh, by utilizing a unique farm-level panel data of a cohort of 90 farmers covering a 14-year period (2002–2015). The purpose is to judge whether the gher farming system is sustainable over time when evaluated in terms of energy use. Results reveal that although the prawn-carp enterprise is highly inefficient in energy use, the high-energy efficient HYV rice enterprise offset the negative net energy balance of the former and makes the gher farming system as a whole energy efficient. However, substantial scope remains for improving the technical energy efficiency of gher farmers. Experience and education are the significant drivers of energy efficiency. The TFEP grew at the rate of 2.56% p.a. mainly driven by TC at the rate of 2.57% p.a. with negligible decline in EEC.
The key conclusion that emerges from this study is that the gher farming system demonstrated significant productivity growth driven by technical progress over time and, therefore, it is sustainable in the long-run when evaluated in terms of energy use. Gher farmers are becoming more prudent in the use of their input levels, particularly in the HYV rice enterprise, which had a dominant influence in improving net energy balance, thereby, leading to significantly improved performance of the gher farming system as a whole over time. Also significant increase in energy output of the HYV rice enterprise over time further contributed to overall sustainability of the gher farming system. An estimated 61% of total energy inputs are renewable, which is encouraging.
The following policy implications can be drawn from this study. First, a major thrust should be geared towards maintaining and/or improving productivity of the HYV rice enterprise. This can be achieved through R&D investment. The Bangladesh Rice Research Institute (BRRI) has a major role to play in this area to develop strains of HYV rice that are particularly suited to gher farming system. Second, measures should be undertaken to improve performance of the prawn enterprise through developing feed ingredients and production technologies. This is because the prawn enterprise seem to be stagnant in energy performance over time. The Bangladesh Fisheries Research Institute (BFRI) has an important role to play in this regard. Third, investment in education targeted at the gher farmers will significantly improve energy efficiency. An effective implementation of these policy measures will boost the sector and enable to sustain it in the long-run.