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Pathways towards low-carbon sustainable agriculture: how farmland size affects net carbon emissions
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Agriculture plays an indispensable role in the economic system of all countries, and the issue of agricultural carbon emissions has become a challenge to the sustainable development of the global economy. Against this backdrop, based on the data of 30 provinces, municipalities directly under the central government and autonomous regions (excluding Hong Kong, Macau and Tibet) in China from 2005 to 2019, this current study comprehensively uses the two-way fixed effect panel model and panel vector autoregressive (PVAR) model to explore the static and dynamic relationships between agricultural mechanization, large-scale operation and agricultural carbon emissions. Analysis show that agricultural mechanization and large-scale operation promote the agricultural carbon emissions, and increasing the level of urbanization will help curb the increase of agricultural carbon emissions. However, in a dynamic perspective, there is a two-way granger causality relationship between agricultural mechanization and agricultural carbon emissions. Agricultural mechanization is an important cause of agricultural carbon emissions and its promoting effect is sustainable, while the short-term effect of large-scale operation on agricultural carbon emissions is positive, and in the long run it helps reduce agricultural carbon emissions. Accordingly, the study recommends that the government should make the following efforts: firstly, speed up the research and development of agricultural machinery driven by clean energy; secondly, guide the effective transfer of land and encourage farmers to reduce the amount of agricultural chemical materials input while improving the use efficiency of pesticide chemical materials; thirdly, uphold the concept of ecological civilization in the process of promoting urbanization.
本文基于中国5 省100 村795 户农户的农业生产微观调查数据，运用生命周期评价法核算农户作物种植碳排放量，探讨农户土地转入规模、土地经营规模与作物种植碳排放强度之间的关系。研究发现，2018 年，中国农户作物种植碳排放强度为334.12 千克二氧化碳当量/亩，且区域差异明显；农户土地经营规模扩大能促进作物种植碳排放强度降低，但土地转入规模扩大会对土地经营规模扩大的减碳效应产生抑制。异质性分析表明，农户家庭成员平均受教育程度越高、对农业依赖性越低，土地转入规模对土地经营规模减碳效应的抑制就越弱；土地经营规模扩大的减碳效应和土地转入规模扩大对减碳效应的抑制作用主要发生在土地经营规模较小的农户群体中；从是否支付土地租金来看，支付土地租金的农户群体，其土地转入规模对作物种植碳排放的影响在统计意义上不显著；从不同作物种类来看，土地经营规模扩大的减碳效应和土地转入规模扩大对减碳效应的抑制作用主要发生在水稻种植上。机制分析表明，土地转入规模扩大主要通过增加化肥投入和促进种植结构主粮化抑制土地经营规模扩大的减碳效应。基于研究结论，本文提出应进一步重视土地经营规模扩大的减碳效应，但要关注土地转入规模扩大对减碳效应的抑制作用，引导科学施肥与合理调整种植结构，并将作物种植碳减排的政策重点放在小规模经营农户群体上。
Based on the micro-survey data of agricultural production of 795 farmers in 100 villages of five provinces of China, this article uses life cycle assessment method to calculate the carbon emissions of farmers’ crop planting, and explores the elationship between the scale of farmers’ land transfer-in, land operation scale and the carbon emissions intensity of crop planting. The results show that in 2018, the carbon emission intensity of Chinese farmers’ crop planting was 334.12kg CO2-eq/mu, with obvious regional differences. The expansion of farmers’land operation scale has generated carbon reduction effect, but it has been inhibited by land transfer-in scale. The heterogeneity analysis shows that the higher the average education level of household members and the lower their dependence on agriculture, the weaker the inhibition effect of land transfer-in scale on carbon reduction effect of land operation scale. The carbon reduction effect of the expansion of land operation scale and the inhibition effect of the expansion of land transfer-in scale mainly occurred in farmer groups with smaller land operation scale. From the perspective of whether to pay land rent, the impact of land transfer-in scale on carbon emissions of crop planting is not statistically significant for farmers who pay land rent. In terms of different crops, the carbon reduction effect of the expansion of land operation scale and the inhibition of the expansion of land transfer scale on the carbon reduction effect mainly occur in rice planting. The mechanism analysis shows that the expansion of land transfer-in scale mainly suppresses the carbon reduction effect of the expansion of land operation scale by increasing fertilizer inputs and adjusting planting structure. Based on the conclusions, the study proposes the necessity to pay more attention to the inhibition of the carbon reduction effect of the expansion of land transfer-in scale, guide scientific fertilization and rational adjustment of planting structure, and focus planting carbon emission reduction policies on smallholders.
China’s agricultural development urgently needs dynamic transformation and green transformation, from a traditional extensive mode of production to a moderately intensive mode of production that meets the requirements of the new era, with efficiency improvement as the guide to promote green, low-carbon, and sustainable development. Based on the micro-data of farmers in Hunan province from 2015 to 2020, this paper uses the data envelopment analysis method to measure the cost efficiency of rapeseed production and then decompose the cost-efficiency. The Tobit model is used to analyze the influencing factors and cost-efficiency differentials. First, there is considerable room for improvement in the overall cost efficiency of Chinese rapeseed production. The technical efficiency (TE), allocation efficiency (AE), and cost efficiency (CE) of rapeseed production in the survey area are 0.869, 0.701, and 0.609, respectively. Second, allocative efficiency is an important factor affecting the improvement of cost efficiency. The expansion of farmers’ operation scales does not necessarily improve their allocative efficiency, but increases their input of chemical fertilizer and other elements, which may lead to agricultural non-point source pollution. This is not conducive to sustainable environmental development. Third, the relationship between the cost efficiency of crop production and farmers’ operation scale is of an “inverted U-type” curve. That is to say, with the expansion of farmer operation scale, cost-efficiency shows an “increasing first and decreasing later” trend peaking at (6.67,13.33) hm². Fourthly, the distinguishing factors which affect cost efficiency show obvious similarities while reserving differences. Finally, we also suggest countermeasures and suggestions from the perspective of R & D investment, industrial support, regional exchange and cooperation, reasonable input of resource factors, and awareness of agricultural green production to promote green and low-carbon development of the rapeseed industry in China.
A change in agricultural land management scale leads to the recombination and adjustment of production factors, which have an important impact on agricultural carbon emissions. There are few studies on the connection between the scale of land management and agricultural carbon emissions. In this study, we empirically examined the relationship between planting scale and agricultural carbon emissions using the threshold model, which allows the data to endogenously generate several regimes identified by the thresholds. The results showed that from 2003 to 2018, carbon emissions from planting first increased and then decreased, reaching their highest in 2015. Across the whole country in the main rice- and wheat-producing regions, the scale of planting land has a threshold effect on agricultural carbon emissions, showing an inverted “U” shape. Carbon sinks and natural disasters significantly affected planting carbon emissions in the above three regions. The amount of fiscal support for agriculture significantly affects planting carbon emissions in the national and main wheat-producing regions, while peasants’ per capita income significantly affects planting carbon emissions in the main rice- and wheat-producing regions. This study provides policy makers with new ideas, in that continuously expanding the scale of agricultural land management is conducive to reducing agricultural carbon emissions.
Global climate change caused by Greenhouse gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the dynamic impacts of economic growth, renewable energy use, and agricultural land expansion on CO2 emissions in Peru. Time series data from 1990 to 2018 were utilized applying the autoregressive distributed lag (ARDL) bounds testing approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the coefficient of economic growth is positive and significant with CO2 emissions, indicating a 1% increase in economic growth is related to a 0.59% rise in CO2 emissions. Moreover, the coefficient of renewable energy use is negative and significant, implying that increasing renewable energy use by 1% results in a 0.52% reduction in CO2 emissions in the long run. Furthermore, the estimated long-run coefficient of agricultural land is positive and significant which reveals that agricultural land expansion by 1% is associated with an increase in CO2 emissions by 1.58% in the long run. The empirical findings reveal that economic growth and agricultural land expansion increase CO2 emissions while increased renewable energy use improves environmental quality by reducing CO2 emissions in Peru. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and canonical cointegrating regression (CCR). This article provides policy recommendations aimed at a low-carbon economy, promoting renewable energy use and climate-smart agriculture to achieve emission reduction and environmental sustainability.
ARTICLE INFO Keywords: Stra tegi c decisi on-ma ki ng Fa rm expa nsi on decisi ons Fina ncial an d non-fina ncia l influencing fa c-tors Fa rm er decisi on-ma ki ng Sensema king ABSTRACT The budget for the Common Agricu ltural Policy (CAP) is €365 bn (European Commission, 20 18) for 20 21-20 27 , with the ma jority allocated to farm ers through direct payme nts. Given the economic vulnerability of ma ny farm enterprises, and the concern about the sustainability of food supply for a growing worldwide population, these payme nts are provided to encourage food produ ction. Despite this economic vulnerability , ma ny farm ers do not appear to run their bu siness with the sole intention of profit ma ximisation. This paper explores various financial and non-financ ial influencing factors on the strategic farm expansion decision -ma king process of farm ers with the aim of assisting policyma kers and farm advisors to develop a deeper un derstanding of that process. As a result, agricu ltural policy ma y be more effectively formu lated and advisory services to farm ers ma y be improved. Semi-structured interviews were un dertaken with 27 farm ers wh o have un dertaken strategic farm expansion decisions. Subsequently, the interview find ings were presented to a focu s group to probe them in more detail. A wide range of financial and non-financ ial influencing factors on the strategic farm expansion decision-ma king process of farm ers em erge. An alysis of the influencing factors by the specific type of farm expansion decision un dertaken and by farm type provides further insights. It is proposed that these influencing factors act as a cue wh ich trigger a sensebreaking activity and cause the farm er to enter a process of sensema king, cu lminating in a strategic farm expansion decision be ing un dertaken.
A food system framework breaks down entrenched sectoral categories and existing adaptation and mitigation silos, presenting novel ways of assessing and enabling integrated climate change solutions from production to consumption.
This article addresses the question of whether subsidizing an entirely new agricultural technology for smallholder farmers can aid its adoption early in the diffusion process. Based on a theoretical framework for technology adoption under subjective uncertainty, we implemented a randomized field experiment among 1,200 smallholders in Uganda to estimate the extent to which subsidizing an improved grain storage bag crowds‐out or crowds‐in commercial buying of the technology. The empirical results show that on average, subsidized households are more likely to buy an additional bag at commercial prices relative to the households with no subsidy who are equally aware of the technology. This suggests that under certain circumstances, such as when there is uncertainty about the effectiveness of a new agricultural technology, and the private sector market for the technology is weak or nascent, a one‐time use of subsidy to build awareness and reduce risk can help generate demand for the new technology and thus crowd‐in commercial demand for it. In this context, a subsidy can allow farmers to experiment with the technology and learn from the experience before investing in it.
Multiplicative interaction models are widely used in social science to examine whether the relationship between an outcome and an independent variable changes with a moderating variable. Current empirical practice tends to overlook two important problems. First, these models assume a linear interaction effect that changes at a constant rate with the moderator. Second, estimates of the conditional effects of the independent variable can be misleading if there is a lack of common support of the moderator. Replicating 46 interaction effects from 22 recent publications in five top political science journals, we find that these core assumptions often fail in practice, suggesting that a large portion of findings across all political science subfields based on interaction models are fragile and model dependent. We propose a checklist of simple diagnostics to assess the validity of these assumptions and offer flexible estimation strategies that allow for nonlinear interaction effects and safeguard against excessive extrapolation. These statistical routines are available in both R and STATA .
In arid and populated areas or countries, water shortage and heavy carbon emissions are threatening agricultural sustainability with food security severely, and becoming a major issue. It is unclear whether improved farming systems can be developed to tackle those issues through a sustainable agriculture. Here three farming practices that have proven to be essential and successful, which were: (a) crop intensification through strip intercropping, (b) water harvesting through conservation tillage; and (c) carbon sequestration through improved crop residue management options, were integrated in one cropping system. We hypothesize that the integrated system allows the increase of crop yields with improved water use efficiency, while reducing carbon emissions from farming. The hypothesis was tested in field experiments at Hexi Corridor (37°96'N, 102°64'E) in northwest China. We found that the integrated system increased soil moisture (mm) by 7.4% before sowing, 10.3% during the wheat-maize co-growth period, 8.3% after wheat harvest, and 9.2% after maize harvest, compared to the conventional sole cropping systems. The wheat/maize intercrops increased net primary production by 68% and net ecosystem production by 72%; and when combined with straw mulching on the soil surface, it decreased carbon emissions by 16%, compared to the monoculture maize without mulch. The wheat/maize intercrops used more water but increased grain yields by 142% over the monoculture wheat and by 23% over the monoculture maize, thus, enhancing water use efficiency by an average of 26%. We conclude that integrating strip intercropping, conservation tillage as well as straw mulching in one cropping system can significantly boost crop yields, improve the use efficiency of the limited water resources in arid areas, while, lowering the carbon emissions from farming. The integrated system may be considered in the development of strategies for alleviating food security issues currently experienced in the environment-damaged and water-shortage areas.
Straw has been commonly incorporated to maintain soil fertility and crop productivity in China, but effects of long-term straw incorporation on crop yield, soil organic carbon (SOC) and total nitrogen (TN) have not been thoroughly evaluated. Thus, this study analyzed data collected in long-term (>10-year) trials across the major agricultural zones of China. Across the trials, relative to straw removal, straw return significantly increased crop yield, SOC and TN (by 7.0, 10.1 and 11.0 %, respectively). In some trials with winter wheat in northern China, straw return reduced yield by 0.6–7.1 %. The effects of straw return on SOC and TN were not significantly affected by experimental duration, land use type and cropping system, but positively and linearly related to the inputs of straw-C and -N, respectively. Interestingly, SOC and TN responses to straw return were decoupled in upland and upland-paddy soils in China, but not in paddy soils. Mean values of straw-C sequestration efficiency (7.7, 10.3 and 9.4 %, under corn, wheat and rice, respectively) indicate that 100 % straw return could increase SOC by 281.7 Tg C in 18 years (the mean experimental period of the considered studies) in China. Our analyses demonstrate that straw return is an effective practice for sustaining crop productivity and soil fertility in large parts of China, but site-specific factors should be considered.
The agricultural commodity market is sensitive to variations in weather and climate, which can disrupt supply and cause price fluctuations. Some of the key positive and negative impacts of climate change on agricultural commodities, using the examples of wheat and barley, are identified; of particular significance are temperature changes, water availability, and CO2 fertilization. Although they are not exempt from the negative impacts of climate change, higher latitude regions of production, including Canada and Russia, will benefit the most from climate change. The impacts on other important production regions, such as parts of Europe, the US, and Argentina, will be more mixed. Market stability in all regions will also be affected by changes in climate and weather extremes. To increase resilience to the effects of weather events and climate change on the agricultural commodity market, countries should diversify their sources of supply, encourage more countries to grow and export the relevant commodities, and support crop research and climate adaptation.
This paper is a review article on the impacts of technology adoption on agricultural productivity in smallholder agriculture in the sub-Saharan African region. The use of agricultural technologies determines how the increase in agricultural output impacts on poverty levels and environmental degradation. Experience and evidence from countries within and around the sub-Saharan African region indicate that returns to agricultural technology development could be very high and far reaching. The factors affecting technology adoption are assets, income, institutions, vulnerability, awareness, labour, and innovativeness by smallholder farmers. Technologies that require few assets, have a lower risk premium, and are less expensive have a higher chance of being adopted by smallholder farmers. There are certain traditional smallholder agricultural technologies in sub-Saharan Africa that also have their own merits. Some of these technologies are more efficient in their use of scarce production resources than modern technologies. Modern researchers should therefore seek to understand the rationale behind traditional smallholder farmer behaviour in technology use. This will make their future technological interventions in smallholder agriculture more effective.
Multiplicative interaction models are common in the quantitative political science literature. This is so for good reason.
Institutional arguments frequently imply that the relationship between political inputs and outcomes varies depending on the
institutional context. Models of strategic interaction typically produce conditional hypotheses as well. Although conditional
hypotheses are ubiquitous in political science and multiplicative interaction models have been found to capture their intuition
quite well, a survey of the top three political science journals from 1998 to 2002 suggests that the execution of these models
is often flawed and inferential errors are common. We believe that considerable progress in our understanding of the political
world can occur if scholars follow the simple checklist of dos and don'ts for using multiplicative interaction models presented
in this article. Only 10% of the articles in our survey followed the checklist.
High population growth and providing the food for this population have increased the amount of energy consumption in agricultural production systems. One of the most important issues for high energy consumption in recent century is the global warming where greenhouse gas (GHG) emission plays an important role. This study evaluated the energy balance between the input and output and the amount of GHG emission per unit area of wheat production in Iran. The total energy input and output were calculated as 31.5 and 44.6 GJ ha
1
, respectively, where the highest energy consumer was chemical fertilizer with share of 64% of total energy. Total GHG emission was 1118.94 kgCO
2eq
ha
1
in which chemical fertilizer and diesel fuel had the highest contributions. The results of regression analysis indicated that use of 10 MJ in forms of direct, indirect, renewable, and nonrenewable energy leads to 3.0, 0.4, 2.8, and 0.6 kg ha
1
growth in wheat yield, respectively. The results of farm size analysis indicated that very large farms have better energy ratio and less GHG emission in comparison with other farm size levels due to better management. The results of this study indicated a list of choices which are available to reduce energy use and GHG emission in wheat production.
This article analyzes the revolutionary impact the tractor had on rural America and examines the economic, technological, and institutional factors governing the machine s diffusion. Our simultaneous-equation regression model helps decipher the complex relationship between farm scale and diffusion. In addition, analyzing diffusion as a capital replacement problem reveals that the shift to the new technology was far more rapid than what has generally been thought and provides a new perspective on the long co-existence of both horses and tractors on farms.
Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society. Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of “carbon peak and carbon neutrality”. Therefore, taking straw incorporation as an example, this paper aims to investigate the impact of risk preferences on farmers’ low-carbon agricultural technology (LCAT) adoption. Based on a two-phase micro-survey data of 1 038 rice farmers in Jiangsu, Jiangxi, and Hunan provinces, this paper uses experimental economics methods to measure farmers’ risk aversion and loss aversion to obtain the real risk preferences information of the farmers. We also explore the data to examine the actual LCAT adoption behavior of farmers. The results revealed that both risk aversion and loss aversion significantly inhibit farmers’ LCAT adoption: more risk-averse or more loss-averse farmers are less likely to adopt LCAT. It is further found that crop insurance, farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’ LCAT adoption. Therefore, we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT, extending crop insurance, promoting appropriate scale operations, and strengthening governmental regulations to promote farmers’ LCAT adoption.
Both contemporary policy makers and scholars focus on the role of agricultural sector in better achieving carbon reduction and green transition. This paper empirically analyzes the impact and mechanism of agricultural green production technology (AGPT) on agricultural carbon emission intensity at the national level using the panel data of China's 31 provinces from 2000 to 2019 as well as the panel OLS method and spatial Durbin model. The results show that China's AGPTs adoption level have improved greatly and the agricultural carbon emission intensity has declined drastically in the period of 2000 to 2019. No-till planting and straw returning significantly inhibited agricultural carbon emission intensity, while water-saving irrigation had the opposite effect. Chemical fertilizers are substituted effect through zero-tillage planting and straw-return, thus reducing the agricultural carbon emission intensity. Water-saving irrigation serves as a supplement effect to chemical fertilizers application, inhibiting fertilizer's carbon increase effects. The role of AGPTs reduce carbon emissions is particularly dominant in main grain-producing areas. Straw-return played a significant negative spatial spillover effect on the agricultural carbon emission intensity of neighboring regions through technology dissemination across regions, and the spillover effect of zero-tillage planting and water-saving irrigation was not significant. According to local conditions, no-tillage planting and straw returning should be promoted, water-saving irrigation efficiency should be improved, and the input characteristics of high carbon elements in traditional agriculture should be gradually changed. A regional collaborative emission reduction mechanism should be established to achieve a long-term mechanism for agricultural carbon emission reduction and green development.
Agricultural carbon emissions have long attracted scholars' interest. In recent decades, China has gradually explored the path of agricultural specialization without large-scale operation based on agricultural machinery service outsourcing driven by structural transformation. To date, our understanding of the impact of China's unique agricultural specialization on agricultural carbon emissions remains scant. Nevertheless, this issue is important for promoting China's carbon emission reduction and exploring a path of agricultural transformation that is both competitive and sustainable. Based on China's provincial panel data from 2000 to 2019, this paper constructed a mediating model to test empirically the impacts of agricultural specialization on agricultural carbon emissions. The results showed that agricultural specialization exerted a significant positive effect on agricultural carbon emissions by increasing agricultural external inputs. Specifically, in addition to promoting increased mechanization, agricultural specialization caused an even greater, excessive application of chemical fertilizers, which largely follows metabolic rift theory and substitution and remittance effects. The farmland operation scale had no significant effect on agricultural carbon emissions due to the offset of its significant negative effect on chemicalization and significant positive effect on mechanization. This finding demonstrates that, in the context of smallholder farming, the moderate expansion of farm size can reduce agricultural environmental pollution, but it cannot be proved to reduce agricultural carbon emissions. These findings challenge China's current unique path of agricultural specialization from the perspective of carbon emission reduction and demonstrate the applicability of the theory of metabolic rift to the current path of agricultural development in China. Accordingly, corresponding short-term and long-term implications related to agrarian transition and agricultural carbon emissions are provided.
Farmers' participation in extension training and demonstration programs may unleash farmers' potential and enable them to adopt improved production techniques to bring about sustainable farm productivity improvement. This study applies Poisson model with the endogenous covariate in primary data from 469 farming households in the Mvomero district of Tanzania to determine the effect of the agricultural extension training and demonstration programs on the adoption intensity of rice production technologies practices (RPTPs). The study found that training and demonstration programs improved the adoption intensity of RPTPs by 64.4%, and governments and other stakeholders should invest more in them. Simultaneously, access to irrigation water improves RPTPs adoption intensity, implying that besides the extension programs, the provision of irrigation services is needed to promote rice production technologies and productivity improvement. Therefore, extension training and demonstration programs should incorporate farming training on RPTPs as a set of complementary innovations to guide the adoption of multiple technology practices.
Greenhouse gas (GHG) emissions and reactive nitrogen (Nr) releases are central environmental problems, which are closely linked to climate change, environmental ecology and crop production. Sustainable development of agriculture plays an important role in GHG emissions and Nr loss. The life cycle assessment (LCA) method was used to calculate the product and farm carbon footprints (CFs) and nitrogen footprints (NFs) in rice, wheat and maize production in China based on farm survey data. The results pinpointed that the CFs of rice, wheat and maize were 0.87, 0.30 and 0.24 kg/kg. Meanwhile, the computed NFs were 17.11, 14.26 and 6.83 g/kg, respectively. Synthetic nitrogen fertilizer applications and methane (CH4) emissions were dominant CF sources, while ammonia (NH3) volatilization was the main NF contributor. Moreover, significant decreases in CF and NF by 20%–54% and 33%–61%, respectively, were found in large-size farms (> 20 hm²) when compared to small-size farms (< 0.7 hm²). Furthermore, the significantly positive relationships between CF and NF indicated the potential for simultaneous mitigation in the regions with high agricultural inputs, like amounts of fertilizer. Based on our results, some effective solutions would be favorable toward mitigating climate change and eutrophication of the major cereal crop production in China, especially optimizing fertilizer use and farm machinery operation efficiencies, as well as developing large-size farms with intensive farming.
Low-carbon agricultural technology (LCAT) has a fundamental role for China to reach the carbon emissions peak in 2030 and achieve carbon neutrality in 2060. Using data obtained from questionnaires completed by 386 small farmers in Jianghan Plain, China, we construct a theoretical framework based on the theory of planned behavior and structural equation model to elicit the determinants affecting farmers’ adoption of LCAT. Three notable results emerge. (1) Farmers’ behavioral attitude (BA), subjective norm (SN), and perceived behavioral control (PBC) were correlated. (2) Farmers’ behavioral intention (BI) to adopt LCAT was significantly and directly affected by BA, SN, and PBC, and BA had the highest impact (0.62). (3) Farmers’ BA and BI both impose positively significant effects on behavioral response (BR) regarding LCAT, and the BI had the strongest impact (0.53). Based on these findings, future policy interventions to promote LCAT measures should focus on improving farmers’ knowledge of LCAT, upgrading the promotion tools of LCAT, and emphasizing the exchange of technical information among farmers.
As one of the main focuses of agricultural development research, changes in agricultural technology are a dynamic reflection of the economic environment. This paper uses the Meta-analysis method to conduct a comprehensive analysis of 77 empirical studies to reveal the influence factors, sources of heterogeneity, and influence effects of farmers on the adoption behavior of pro-environmental agricultural technology over time. The results show the following: (1) Influencing factors of farmer's pro-environmental agricultural technology adoption behavior are not completely homogeneous. Among the factors, age, farming population, family income, farm income ratio, number of plots, and land transfer have a regulating effect. Most of the observed heterogeneity relates to the research areas, funding levels and models used. (2) Age, off-farm income ratio, and land fragmentation have a significantly negative impact on farmers' adoption of pro-environmental agricultural technologies. We find no impact on household size, farming population, and village cadres. Farm income ratio, farmland protection policy awareness, land transfer, and government subsidies have significantly positive effects. (3) Over time, only land transfer has a significantly positive impact on the adoption of pro-environmental agricultural technologies by farmers, and the impact has gradually increased. The farming population, technical understanding, and number of plots have no significant impact, but their effects have weakened to varying degrees. Therefore, policymakers and other stakeholders need to consider geographical differences and farming systems, the technology needs of different farmers and affordable costs, in addition to focusing on common variables, when designing policies to encourage the adoption of agricultural technologies in China. Meanwhile, improve the development level of the land rental market, strengthen publicity, training, and subsidies, and increase farmers' information awareness.
Green agricultural technology has the potential to not only alleviate the degradation of soil fertility, but also to improve the agricultural productivity of smallholders. In this paper, taking straw incorporation as an example, experiments were conducted in Chinese villages to directly measure the time preferences of farmers, and an attempt was made to evaluate the contribution of time preferences to farmers' technology adoption behavior. Furthermore, this research aims to assess the moderating role of production scale between the farmer's time preferences and technology adoption. This study is a continuation of previous studies on factors influencing green agricultural technology adoption. The results show that time preferences significantly reduce technology adoption; in particular, farmers who are more present-biased have a lower proportion of technology adoption. This is because farmers with lower discount rates are more sensitive to future income. Further analysis indicates that compared with small-scale farmers, large-scale farmers are more likely to adopt green technology. It is posited that this occurs because large-scale farmers will gain more benefits by adopting green agricultural technology, and thus, they will be more sensitive to high profits in the future. Moreover, the increase of production scale can reduce the inhibitory effect of time preferences on farmers' technology adoption, which means that scale economies play a moderating role between the farmer's time preferences and their technology adoption. Overall, this research provides a micro foundation and policy recommendations for green agricultural technology promotion and sheds light upon how the government can formulate relevant policies to promote green agricultural development.
Agriculture is being encouraged to become carbon neutral, and agricultural land is being touted as a source of carbon sequestration. Yet making agricultural regions locally carbon neutral will involve an economic cost, with existing patterns of greenhouse gas emissions and spatial costs of abatement affecting that cost of achieving regional carbon neutrality. This study examines the economic cost of locally achieving carbon neutrality, using the illustration of Western Australia’s agricultural region. The cost to the region of achieving carbon neutrality via reforestation is estimated, as is the spatial allocation of farmland for sequestration. Social and political pressures that likely constrain how much farmland can be reforested are explicitly considered. Findings are subject to a sensitivity analysis and several caveats. The annual cost of regional carbon neutrality via proscribed regional reforestation, under current carbon offset prices, is estimated to range from AUD216 million to AUD250 million (i.e. under 3 per cent of the region’s gross value of agricultural production) which might suggest the challenge to be carbon neutral is within commercial reach. However, without other financial incentives, it likely involves farm business profits being reduced by around 15 per cent.
Purpose
The relationship between farm size and greenhouse gas (GHG) emissions has not been clearly defined. This paper aims to assess and compare the impact of farm size on greenhouse gas (GHG) emissions derived from wheat and maize production in the North China Plain (NCP), one of the most important agricultural regions in China.
Design/methodology/approach
A field survey through face-to-face interviews was conducted to collect the primary data, and life cycle assessment method, a worldwide comparable framework, was then adopted to characterize the farm-size effect on greenhouse gas (GHG) wheat and maize production in NCP.
Findings
It was confirmed that GHG emissions from N fertilizer production and use were the primary contributor to total carbon footprint (CF). As farm size increased, maize yield increased but wheat yield barely changed, while area-scaled and yield-scaled CF declined for both crops. These results were supposed to relate to utilize the inputs more efficiently resulting from increased application of modern agriculture methods on larger operations. It was also found maize not only had higher grain yields, but possessed much smaller CFs. More notably, the reduction of CF with farm size seemed to be more sensitive for maize as compared to wheat. To further mitigate GHG emissions, farm size should better be larger for wheat than for maize.
Originality/value
This study provides useful information guide for Chinese agriculture in increasing crop production, raising farm income and relieving environmental burdens caused by the misuse of agricultural resources.
The effects of agricultural green production technologies (AGPTs) on agricultural productivity and the environment have received increasing attention. With the panel data of agricultural production of mainland China from 2000 to 2017, this study investigates the role of AGPTs adoption rates in improving low-carbon efficiency by adopting a random-effects panel Tobit model. Results indicate that average adoption rates of AGPTs are less than 20% and unbalanced adoptions vary between the main and non-main grain-producing areas, as well as the northern and southern main grain-producing areas. Furthermore, AGPTs adoption reduces low-carbon efficiency at nationwide and main grain-producing areas. In the northern main grain-producing areas, water-saving irrigation and no-tillage seeding reduce low-carbon efficiency, while mechanized returning straw crushing promotes it. In the southern main grain-producing areas, deep tillage with fertilizer application and no-tillage seeding decrease low-carbon efficiency, while mechanized deep ploughing and scarification increases it. We also find that AGPTs can promote low-carbon efficiency through comprehensive mechanization level and mechanical input density. To improve low-carbon efficiency, we suggest that the improvement and diffusion of applicable AGPTs should be adapted to the local production conditions, and the agricultural machinery service, research and development system should be improved as well.
Improving farmers' knowledge of fertilizer use through agricultural training has been considered a prerequisite to scientific fertilizer management. However, empirical evidence of the effect of agricultural training on farmers' fertilizer management knowledge is inconclusive. Based on a randomized controlled experiment involving 687 farmers that mitigates selection bias in the data, this paper identifies the treatment effect of agricultural training on farmers' fertilizer management knowledge in Chinese rice production. Results indicate that the fertilizer management knowledge of field-guidance farmers improved by almost 40%. However, such knowledge acquisition did not occur for curriculum-trained farmers. We also find that there is no evidence of knowledge diffusion from trained farmers to exposed farmers in the same village.
This study contributes to (1) discovering that carbon dioxide (CO2) emissions are not directly influenced by modernisation; (2) attaining sustainable agriculture by incorporating renewable energy into the agriculture sector as an effective CO2 emissions mitigation measure; and (3) applying the environmental Kuznets curve (EKC) to test the relationships among attributes in Malaysia. Prior studies have not addressed the associations between the release of CO2 and economic development, renewable energy, urbanisation, and agriculture in Malaysia. Hence, the objective of the study is to investigate the relationships of the emissions of CO2 and economic development, renewable energy, urbanisation, and agricultural subsectors, such as crops, livestock, and fisheries, in Malaysia for the period 1978 to 2016. By the utilisation of the autoregressive distributed lag test for cointegration, CO2 emissions significantly increased due to economic growth and urbanisation but insignificantly increased due to livestock in the long term. Crops, fisheries, and renewable energy significantly reduced emissions in this period. Moreover, this study reveals that the association between emissions of CO2 and economic development is an inverted U. This finding indicates that CO2 emissions eventually decrease despite the increase in CO2 emissions and economic development in the long term upon reaching a specific level of growth. These findings are consistent for Malaysia in terms of the EKC hypothesis.
Poor soil fertility emanating from land degradation is one of the causes of low crop productivity in Sub-Saharan Africa. Therefore, the issues of food insecurity and poverty have become prevalent in these countries. It is however imperative to explore agricultural innovations such as mineral fertiliser to improve soil fertility of the arable lands in Africa including Nigeria. In this study, we analyse the adoption of mineral fertiliser and its economic impacts on the livelihoods of 400 rural farmers in Nigeria. We apply the endogenous switching regression and propensity score matching approaches in the empirical analyses. We find that the adoption of mineral fertiliser increases cassava yields and net revenues of rural farmers. The enhanced cassava yields and net revenues have implications on the transformation of rural economy by reducing food insecurity, minimising poverty, and improving the overall well-being of rural farmers. The results also show that farmer age and leasing negatively influence the adoption of fertiliser whereas farmer education, experience in cassava farming, household size, keeping of farm record, location differential, access to credit, membership of farmer association, and herbicides show positive effects. To achieve higher adoption of fertiliser among rural farmers, we recommend that agricultural policies could target the aforementioned key factors.
Using survey data of 375 family farms in five provinces of the Huang-Huai-Hai Plain, this paper conducts a comprehensive measurement of family farms' welfare within the framework of the capability approach theory. Furthermore, using an endogenous switching regression model and a multinomial treatment effects model, this paper evaluates the impact of the adoption or non-adoption of green control techniques on family farms' welfare and estimate the welfare effects of the degree and timing of adoption. This research finds that the average treatment effect on family farm welfare with and without adopting green control techniques is significant, at 0.084 and 0.046, respectively. Therefore, green control techniques help to improve the welfare level of family farms. Compared with family farms that do not adopt green control techniques, the welfare level of family farms adopting a high or low degree of green control techniques increases by 22.63% and 16.42%, respectively, and the welfare level of family farms given the early or late adoption of green control techniques increases by 5.87% and 7.57%, respectively. Therefore, the welfare effect of a high degree of adoption on family farms is greater, and the welfare level of family farms with late adoption is higher.
We investigate time discounting under risk. To this end, we modify a popular multiple price list (MPL) design to elicit time discounting. Structural estimations of model parameters yield several new insights. For one, we find present bias to persist under risk, contrary to some previous evidence from the psychology literature. We further confirm the robustness of inverse-S shaped probability weighting. This is important inasmuch as random choice predicts the opposite shape in our setup. We also show that correcting for probability weighting under risk impacts the assessment of discount rates. Those are systematically underestimated under the commonly used, more restrictive, expected utility.
Federal agricultural land use policies in the United States aimed at protecting soil health and water quality typically rely on persuading individual farmers to voluntarily adopt conservation practices. An expanding body of literature suggests that private sector intermediaries, such as crop advisers, are increasingly trusted sources of information for farmers about conservation practices and thus may be persuasive actors in the conservation-adoption realm. While previous studies have explored farmers’ perceptions of crop advisers facilitating conservation practice adoption and participating in conservation programs in agricultural landscapes, little research to date has explored crop advisers’ perceptions of this role, and few agricultural land use policies have explicitly included crop advisers as conservation partners. This study fills a critical void in the literature by evaluating the Saginaw Bay Regional Conservation Partnership Program, an innovative agricultural policy that relies on crop advisers to recruit farmers into the program and assist them with the adoption of conservation practices. Through a survey and interviews with crop advisers in the Saginaw Bay watershed in Michigan, USA, we explore crop advisers’ perceptions of their role in the program and of delivering conservation information to farmers. We found that crop advisers have positive attitudes towards land/water resources and conservation practices, believe they have an important intermediary role to play in facilitating conservation practice adoption, and believe their supervisors are supportive of them promoting conservation. However, difficulties in collaboration and communication between the private and governmental sectors – resulting from perceived differences, operational differences, and territoriality – present a key barrier to crop advisers increasing their intermediary role in the promotion and implementation of federal conservation programs. Future research and policy initiatives should explore how to address public-private territoriality and whether crop advisers should be incentivized to deliver information about conservation practices and/or assist in enrolling farmers in federal conservation programs.
Scaling up of farming operations by land use rights transfers has been a growing trend in China in recent years. However, little is known about the implications of this trend for greenhouse gas (GHG) emissions and soil organic carbon (SOC) stock changes. Using farm survey data from Shandong Province, a typical grain production region in China, we used a life cycle assessment (LCA) method to evaluate the impact of different farm scales on input use efficiency, grain production, SOC stock changes and GHG emissions. Large-scale farming operations (LSFO) enhanced input use efficiency by reducing fertilizer and pesticide consumption rates and energy use for irrigation. Compared with small household farming operations (SHFO), LSFO attained higher grain yield in wheat-maize and wheat-rice cropping systems. Compared with small farms, carbon footprints per unit area of large-scale farms were lower for wheat (17%) and maize (28%) in the wheat-maize cropping system and for wheat (14%) and rice (8%) in the wheat-rice cropping system. Moreover, LSFO reduced GHG emissions (7-21%) and enhanced SOC stocks (6-9%), compared with SHFO. This study highlights that in China, land use rights transfers to promote large-scale farming can help achieve cleaner grain production with less negative impact on the environment.
Land degradation is a serious global problem because it leads to losses in food production and thus jeopardizes food security worldwide, particularly in developing countries. Despite numerous efforts to introduce sustainable land management (SLM) strategies and practices, their adoption by the primary target group, small-scale farmers in developing countries, has been [s]low. This study assesses the problem for the case of Ethiopia. The aim was to analyze the underlying factors that affect the adoption of SLM technologies in the Upper Blue Nile Basin. A detailed survey of 300 households and 1010 farm plots was conducted. Data were analyzed by using both descriptive and econometric analyses. Results show that farmers’ adoption of interrelated SLM measures depended on a number of socio-economic and farm-related factors in combination with the characteristics of the technologies themselves. For example, plot size and the availability of labor, as well as the gender of the household head, affected which SLM technologies were adopted by certain types of households. The adoption of SLM measures depended on the adaptive economic capacity of the farmers, which can be quite diverse even within a small region and can differ from the adoption potential in other regions. Our results suggest that SLM policies and programs have to be individually designed for specific target groups within specific regions, which in turn means that “one size fits all” and “across the board” strategies—which are quite common in the field of SLM—should be abandoned by development agencies and policymakers.
High fertilizer use intensity is a serious issue throughout China, with adverse environmental and economic impacts. The lack of knowledge of Chinese farmers has been found to be the primary constraint. Using a propensity score matching (PSM) method to create a credible counterfactual analysis, this study examines the causal effects of two kinds of knowledge training approaches, traditional one-time training and in-field guidance, on the change of fertilizer use intensity of wheat farmers in China. The estimated results provide evidence that the traditional one-time training approach has a small effect on fertilizer use intensity reduction (only a 4% average), while the in-field guidance has a larger effect on fertilizer use intensity reduction (a 17% average). Moreover, we also found knowledge training has heterogeneous treatment effects. The reduction in fertilizer use intensity is larger for the farmers who are male and middle aged, have acquired a middle level of education, receive a lower share of off-farm income, collect a lower income, and operate a larger farm.
Water stress and soil infertility are the greatest constraining factors for higher agricultural productivity in drylands, prompting the current interest in soil and water conservation (SWC) practices in water-constrained regions. To provide a more comprehensive understanding of challenges surrounding the adoption of SWC practices in these regions, we used a joint analysis framework combining both multivariate and ordered probit models to analyze adoption-decisions for eleven on-farm SWC practices. Our case study, involving 500 farmers from a representative West African Sahelian zone, revealed that although the adoption of SWC practices is widespread in the West African drylands, there is still an important potential to improve and upscale their specific adoption rates. Almost all farmers (99%) used at least one of the eleven practices considered in this study, whereas specific adoption rates ranged from 5% for contour vegetation barriers to 87% for manure application. More than 70% of the farmers used up to three practices only, and less than 30% used between four to nine practices. Many practices are interdependent, with some practices being complementary and others substitutable. The analysis of the determinants of the adoption and the intensity of adoption revealed that SWC practices are labor-, knowledge- and capital-intensive. We found that the major drivers of farmers’ decisions to adopt, as well as to intensify the use of, most SWC practices are the presence of children (aged 6 to 14) in the household, land holding, land tenure, awareness and training on SWC and access to alternative – but non-agricultural labor constraining – cash sources such as remittance and cash farming. A higher number of migrating household members increases the probability of intensifying the use of SWC practices, but only when this is in line with the household’s land endowment and labor needs for farm activities. This comprehensive study will be of significance for a finer understanding of SWC practices in West African Sahel. More generally, it will likely help policy makers to upscale the adoption of sustainable SWC practices for the advance of climate-smart agriculture in developing drylands.
The carbon footprint (CFP) assessment of smallholders offers key information on the capacities and challenges for greenhouse gas (GHG) mitigation at farm scale. This allows prioritizing the practices that ensure both the food security of farmers and the low carbon impact associated to climate change. To tackle food security challenges and to maintain sustainable environment production, agroecological practices were planned for farmers in the Itasy region, Central Highlands of Madagascar. The project consisted of agroforestry and forestry systems, composting of organic matters, and system of rice intensification. The goals of this study were (i) to assess the CFP of farms in the Itasy region Central Madagascar, (ii) to assess the impact of agroecological practices adopted by farmers on farms CFP, and (iii) to compare the impact of Tier 1 and Tier 3 factors for carbon removal in woody biomass and in cropland soils on farms CFP. For these purposes, a survey of 192 representative farms was realized during the years 2012–2013. Agroecological practices integrated at farm scale reduced significantly farms CFP up to 364% in terms of land surface and up to 578% in terms of food production, suggesting an important GHG sequestration at farm scale. Main sources of GHG at farms scale were: nitrous oxide from soil management (25%), methane from rice cultivation (24%), livestock manure management (24%), and enteric fermentation (23%). Trees planted in agroforestry and forestry systems offered the highest GHG mitigation benefits. Tier 1 factors overestimated up to 7 times higher the farms CFP compared to Tier 3 factors. This study highlights that the integration of agro-ecological practices at farm scale offers significant GHG mitigation and carbon sequestration in Malagasy context, thus giving an alternative for climate change mitigation.
The excessive use of fertilizer has resulted in serious environmental degradation and a high health cost in China. Much research has focused on the technological innovation to improve fertilizer use efficiency in crop production, but the socioeconomic constraints are at present poorly understood. Here, we find that fertilizer use on a per-area basis sharply decreased with the increase of farm size; surprisingly, the crop yield is higher in large-scale farms compared to that in smallholder farms in China. High labor cost suggests a low machinery level in smallholder farms, which inhibit the application of precise fertilization technologies and management based on scientific knowledge. Meanwhile, the dependence of income from cropland is lower for smallholder farmers who have part-time jobs in urban areas compared to the professional farmers in large-scale farms. Therefore, compared to smallholder farms, large-scale farms are generally more sensitive to the increase of fertilizer price and would reduce their fertilizer use if withdrawing fertilizer subsidies that used to be considered as the key driver of fertilizer overuse. Considering the dominance of smallholder farms in China, increasing farm size should be integrated into the actions such as improving technological innovation and providing better information transfer to achieve the goal of no increase in Chinese fertilizer use.
The paper investigates the links between size, subsidies and performance for Slovenian farms. Slovenian farms have always been small and highly subsidized. A literature review is carried out for the period before accession to the European Union (EU), and new calculations with farm-level data are performed for 2004–2006, the period of adjustment to the EU's Common Agricultural Policy. Our analysis reveals that both pre- and post-accession farms’ performance measured in terms of technical efficiency is positively related to farm size in Slovenia. We find that small farms are less technically efficient but more allocatively efficient and profitable. The persistence of small farms in Slovenia may be associated with the provision of generous subsidies, which are negatively related to farms’ technical efficiency but positively related to their profitability. The decline in the number of medium-size farms which has been observed since the accession to the EU may be explained by the fact that medium farms cumulate all disadvantages in terms of performance: they are too small to be economically efficient, but they are too large to be profitable.
In this article, we analyze the impact of land fragmentation, farm size, land ownership and crop diversity on farm profit and efficiency of 90 groundwater irrigated farms in the hard rock areas of South India. As we hypothesize that these variables may impact both, farm profit and efficiency in alternative ways, we develop four different stochastic frontier and inefficiency effect models by shifting some of these variables from the inefficiency model into the profit function. The underlining reason is to know the impact of different combination of these structural variables on farm profit and efficiency. Our analysis shows that there exist high levels of inefficiency among the sample farms. Among the variables influencing efficiency, the most pronounced effects are observed with land fragmentation, land ownership and crop diversity. Land fragmentation is positively and significantly associated with inefficiency, whereas land ownership and crop diversity is negatively and significantly associated with inefficiency. In addition land fragmentation can also have a significant negative effect on farm profit. We further find that smaller farms appear to have lower inefficiencies than larger farms due to the more efficient use of inputs by the former category. Importantly, when a farmer owns a failed well, this also contributes to the inefficiency, since well failure increases cost of irrigation. Further the average profit efficiencies are higher for unfragmented farms, large farms, owner operated farms and farms with a diversified cropping pattern as compared with their counterparts. Knowledge on the factors influencing farm profit and efficiency is crucial for policy makers and extension agents for improving efficiency levels of the groundwater irrigated farms especially in water scarce regions of the country.
Threshold models have a wide variety of applications in economics. Direct applications include models of separating and multiple equilibria. Other applications include empirical sample splitting when the sample split is based on a continuously-distributed variable such as firm size. In addition, threshold models may be used as a parsimonious strategy for non-parametric function estimation. For example, the threshold autoregressive model (TAR) is popular in the non-linear time series literature. Threshold models also emerge as special cases of more complex statistical frameworks, such as mixture models, switching models, Markov switching models, and smooth transition threshold models. It may be important to understand the statistical properties of threshold models as a preliminary step in the development of statistical tools to handle these more complicated structures. Despite the large number of potential applications, the statistical theory of threshold estimation is undeveloped. The previous literature has demonstrated that threshold estimates are super-consistent, but a distribution theory useful for testing and inference has yet to be provided. This paper develops a statistical theory for threshold estimation in the regression context. We allow for either cross-section or time series observations. Least squares estimation of the regression parameters is considered. An asymptotic distribution theory for the regression estimates (the threshold and the regression slopes) is developed. It is found that the distribution of the threshold estimate is non- standard. Methods to construct asymptotic confidence intervals are introduced, using both a t-statistic and LR-statistic approach. Monte Carlo simulations are presented to assess the accuracy of the asymptotic approximations. The empirical relevance of the theory is illustrated through an application to the multiple equilibria growth model of Durlauf and Johnson (1995).
Collective property rights of rural land and the allocative efficiency of land transfer during urban-rural transition in China
- L Gao
- Y Ji
- Gao L.
Gao, L., & Ji, Y. (2022). Collective property rights of rural land and the allocative efficiency of land transfer during urban-rural transition in China. Chinese Rural Economy, 10, 24-40. in Chinese.
Study on carbon behavior mode and influencing factors in agricultural production—Investigation of farmers based on typical rural areas in Hubei Province
- B Li
- Q Mei
- Li B.
Li, B., & Mei, Q. (2017). Study on carbon behavior mode and influencing factors in agricultural production-Investigation of farmers
based on typical rural areas in Hubei Province. Journal of Huazhong Agricultural University (Social Sciences Edition), 6, 51-58+150.
(in Chinese).
Analyses of carbon reduction potential of low carbon technologies in China
- J Li
- J Xu
- Li J.
Li, J., & Xu, J. (2022). Analyses of carbon reduction potential of low carbon technologies in China. Issues in Agricultural Economy, 3,
117-135. (in Chinese).
Farm size, tenure security and land productivity: An empirical study based on plot-level survey data from four provinces in China
- H Qiu
- L Liu
- D Li
- C Zhang
- Qiu H.
Qiu, H., Liu, L., Li, D., & Zhang, C. (2017). Farm size, tenure security and land productivity: An empirical study based on plot-level
survey data from four provinces in China. Chinese Rural Economy, 06, 30-43. (in Chinese).
Can participating in agricultural technology training promote farmers to implement green production behavior? Based on the analysis of family endowment and ESR model
- X Wang
- J Zhang
- Q Tong
- Wang X.