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1 – 10 of 690This study aims to examine the impact of renewable energy consumption on agricultural productivity while accounting for the effect of financial inclusion and foreign direct…
Abstract
Purpose
This study aims to examine the impact of renewable energy consumption on agricultural productivity while accounting for the effect of financial inclusion and foreign direct investment in Brazil, Russia, India, China and South Africa (BRICS) countries during 2000–2020.
Design/methodology/approach
The study has used the latest data from World Bank and International Monetary Fund databases. The dependent variable in the study is agricultural productivity. Renewable energy consumption, carbon emissions, financial inclusion and foreign direct investment are independent variables. Autoregressive distributed lag (ARDL) approach was used to examine the short-run and long-run impact of renewable energy consumption, carbon emissions, foreign direct investment and financial inclusion on agricultural productivity.
Findings
The findings imply that consumption of renewable energy, carbon emissions and foreign direct investment have a positive impact on agricultural productivity while financial inclusion in terms of access does not seem to have any significant impact on agricultural productivity. Providing farmers, access to financial services can be beneficial, but its usage holds more importance in impacting rural outcomes. The problem lies in the fact that there is still a gap between access and usage of financial services.
Research limitations/implications
Policymakers should encourage the increase in the usage of renewable energy and become less reliant on non-renewable energy sources which will eventually help in tackling the problems associated with climate change as well as enhance agricultural productivity.
Originality/value
Most of the earlier studies were based on tabular analysis without any empirical base to establish the causal relationship between determinants of agricultural productivity and renewable energy consumption. These studies were also limited to a few regions. The study is one of its kind in exploring the severity of various factors that determine agricultural productivity in the context of emerging economies like BRICS while accounting for the effect of financial inclusion and foreign direct investment.
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Issahaku Haruna and Charles Godfred Ackah
Africa's business environment (BE) is characteristically unfriendly and poses severe development challenges. This study evaluates the impact of business climate on productivity in…
Abstract
Purpose
Africa's business environment (BE) is characteristically unfriendly and poses severe development challenges. This study evaluates the impact of business climate on productivity in sub-Saharan Africa (SSA).
Design/methodology/approach
Macroeconomic data for 51 sub-Saharan African economies from 1990 to 2018 are employed for the analysis. The seemingly unrelated regression model is used to address inter-sectorial linkages.
Findings
The study uncovers several findings. First, a high start-up cost substantially leads to productivity losses by limiting the funds available for investment in productivity-enhancing labour and technology and limiting the number of businesses that see the light of day. The productivity impacts of start-up costs are most enormous for industry, followed by services and agriculture. Second, economies with favourable financing environments tend to be more productive economy wide and sector wise. Third, high taxes and tax inefficiency lower productivity by reducing the resource envelope of firms, thus lowering investment amounts. Fourth, poor business infrastructure inflicts the most damage on productivity. Lastly, business administration and macroeconomic environments impact sectoral and economy-wide productivity.
Practical implications
SSA economies must strive to lower the cost of starting a business as high start-up costs injure productivity. One way of reducing start-up costs is to create a one-stop shop for registering and formalising a business. Another way is to automate business registration and administrative processes to reduce red tape and corruption.
Originality/value
The authors extend the body of knowledge by analysing sectoral and economy-wide productivity effects of various business climate indicators while accounting for inter-sectoral linkages, cross-sectional dependence and endogeneity.
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Joseph Ikechukwu Uduji, Nduka Vitalis Elda Okolo-Obasi, Justitia Odinaka Nnabuko, Geraldine Egondu Ugwuonah and Josaphat Uchechukwu Onwumere
The purpose of this paper is to critically examine the multinational oil companies’ (MOCs) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to…
Abstract
Purpose
The purpose of this paper is to critically examine the multinational oil companies’ (MOCs) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to investigate the impact of the global memorandum of understanding (GMoU) on mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta region of Nigeria.
Design/methodology/approach
This paper adopts an explanatory research design with a mixed method to answer the research questions and test the hypotheses. A total of 1,200 rural women respondents were sampled across the Niger Delta region.
Findings
Results from the use of a combined logit model and propensity score matching indicate a significant relationship between the GMoU model and mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta.
Research limitations/implications
This study implies that MOCs’ CSR interventions that improve women’s access to land and encourage better integration of food markets through improved roads and increased mobile networks would enable women to engage in cash crop production.
Social implications
This implies that improving access to credit through GMoU cluster farming targeted at female farmers would improve access to finance and extension services for women in cash crop production in the Niger Delta.
Originality/value
This research contributes to the gender debate in the agricultural value chain from a CSR perspective in developing countries and is rational for demands for social projects by host communities. It concludes that businesses have an obligation to help solve problems of public concern.
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Dongbei Bai, Lei Ye, ZhengYuan Yang and Gang Wang
Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate…
Abstract
Purpose
Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.
Design/methodology/approach
The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.
Findings
The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.
Practical implications
The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.
Originality/value
The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.
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Yan Han, Yanqi Sun, Kevin Huang and Cheng Xu
This study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the…
Abstract
Purpose
This study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.
Design/methodology/approach
Employing provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.
Findings
The results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).
Originality/value
This study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.
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Inder Sekhar Yadav and M. Sanatan Rao
This work examines the impact of institutional agricultural credit on crop productivity of some major crops such as paddy, cotton, wheat and pulses for small and marginal farmers…
Abstract
Purpose
This work examines the impact of institutional agricultural credit on crop productivity of some major crops such as paddy, cotton, wheat and pulses for small and marginal farmers across various social groups.
Design/methodology/approach
The cross-sectional field data on socio economic variables was collected from three Indian states from about 400 small and marginal farmers across various social groups using multi-stage stratified random and purposive sampling through a structured questionnaire by interviewing. The method of propensity score matching (PSM) was employed to calculate average treatment effect (ATE) and average treatment effect on the treated (ATET) by categorising sample farmers as treatment group and control group where crop productivity was considered as outcome variable and access to institutional credit was considered as treatment variable.
Findings
The PSM estimates reveal that ATE and ATET for all the selected crops are found to be significantly higher for the treated group vis-à-vis non-treated group suggesting that institutional agricultural credit has a statistically and significant positive impact on the crop productivity.
Research limitations/implications
Similar study can be extended for more crops and across regions in India for a universal coverage.
Originality/value
The agricultural credit policy of India has been to increase the access and availability of institutional farm credit. This has led to in general increase in the flow of formal farm credit to agricultural sector. However, the impact of institutional credit and crop productivity especially for small and marginal farmers across social groups is not well recognized in India using field data. Accordingly, this field data study contributes to the existing research by providing fresh evidence from field across social groups for both kharif and rabi crops using recent survey data from small and marginal farmers which has important policy implications.
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Elizabeth Moore, Kristin Brandl, Jonathan Doh and Camille Meyer
This study aims to analyze the short-, medium- and long-term impacts of natural-resources-seeking foreign direct investment (FDI) in the form of foreign multinational enterprise…
Abstract
Purpose
This study aims to analyze the short-, medium- and long-term impacts of natural-resources-seeking foreign direct investment (FDI) in the form of foreign multinational enterprise (MNE) land acquisitions on agricultural labor productivity in developing countries. The authors analyze if these land acquisitions disrupt fair and decent rural labor productivity or if the investments provide opportunities for improvement and growth. The influence of different country characteristics, such as economic development levels and governmental protection for the rural population, are acknowledged.
Design/methodology/approach
The study analyzes 570 land acquisitions across 90 countries between 2000 and 2015 via a generalized least squares regression. It distinguishes short- and long-term implications and the moderating role of a country’s economic development level and government effectiveness in implementing government protection.
Findings
The results suggest that natural resource-seeking FDI harms agricultural labor productivity in the short term. However, this impact turns positive in the long term as labor markets adjust to the initial disruptions that result from land acquisitions. A country’s economic development level mitigates the negative short-term impacts, indicating the possibility of finding alternative job opportunities in economically stronger countries. Government effectiveness does have no influence, presumably as the rural population in which the investment is partaking is in many developing countries, not the focus of governmental protectionism.
Research limitations/implications
The findings provide interesting insights into the impact of MNEs on developing countries and particularly their rural areas that are heavily dependent on natural resources. The authors identify implications on employment opportunities in the agricultural sector in these countries, which are negative in the short term but turn positive in the long term.
Practical implications
Moreover, the findings also have utility for policymakers. The sale of land to foreign MNEs is not a passive process – indeed, developing country governments have an active hand in constructing purchase contracts. Local governments could organize multistakeholder partnerships between MNEs, domestic businesses and communities to promote cooperation for access to technology and innovation and capacity-building to support employment opportunities.
Social implications
The authors urge MNE managers to establish new partnerships to ease transitions and mitigate the negative impacts of land acquisitions on agricultural employment opportunities in the short term. These partnerships could emphasize worker retraining and skills upgrading for MNE-owned land, developing new financing schemes and sharing of technology and market opportunities for surrounding small-holder farmers (World Bank, 2018). MNE managers could also adopt wildlife-friendly farming and agroecological intensification practices to mitigate the negative impacts on local ecosystems and biodiversity (Tscharntke et al., 2012).
Originality/value
The authors contribute to the debate on the positive and negative impact of FDI on developing countries, particularly considering temporality and the rural environment in which the FDI is partaking.
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Yayun Ren, Zhongmin Ding and Junxia Liu
The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the…
Abstract
Purpose
The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.
Design/methodology/approach
In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.
Findings
After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.
Originality/value
Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.
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Abbas Ali Chandio, Huaquan Zhang, Waqar Akram, Narayan Sethi and Fayyaz Ahmad
This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.
Abstract
Purpose
This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.
Design/methodology/approach
Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.
Findings
The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.
Research limitations/implications
This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.
Originality/value
To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.
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Abbas Ali Chandio, Uzma Bashir, Waqar Akram, Muhammad Usman, Munir Ahmad and Yuansheng Jiang
This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal…
Abstract
Purpose
This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal, Philippines, Pakistan, and Vietnam), employing a panel dataset from 2000 to 2018.
Design/methodology/approach
This study initially applies cross-sectional dependence (CSD), second-generation unit root, Pedroni, and Westerlund panel co-integration techniques. Next, it uses the augmented mean group (AMG) and common correlated effect mean group (CCEMG) methods to investigate the long-term impact of remittance inflows on AGP while controlling for several other important determinants of agricultural growth, such as cultivated area, fertilizers, temperature change, credit, and labor force.
Findings
The empirical findings are as follows: The results first revealed the existence of CSD and long-term co-integration between AGP and its determinants. Second, remittance inflows significantly boosted AGP, indicating that remittance inflows played a crucial role in improving AGP. Third, global warming (changes in temperature) negatively impacts AGP. Finally, additional critical elements, for instance, cultivated area, fertilizers, credit, and labor force, positively affect AGP.
Research limitations/implications
This study suggests that policymakers of emerging Asian economies should develop an exclusive remittance-receiving system and introduce remittance investment products to utilize foreign funds and mitigate agricultural production risks effectively.
Originality/value
This is the first empirical examination of the long-term impact of remittance flows on agricultural output in emerging Asian economies. This study utilized robust estimation methods for panel data sets, such as the Pedroni, Westerlund, AMG, and CCEMG tests.
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