Search results

This study aims to examine the impacts of climate change (CC), measured average annual rainfall, average annual temperature and carbon dioxide (CO₂e) on cereal production (CPD) in Bangladesh by using the annual dataset from 1988–2014, with the incorporation of cereal cropped area (CCA), financial development (FD), energy consumption (EC) and rural labor force as important determinants of CPD.

This study used an auto-regressive distributive lag (ARDL) model and several econometric approaches to validate the long- and short-term cointegration and the causality directions, respectively, of the scrutinized variables.

Results of the bounds testing approach confirmed the stable long-term connections among the underlying variables. The estimates of the ARDL model indicated that rainfall improves CPD in the short-and long-term. However, CO₂e has a significantly negative impact on CPD both in the short-and long-term. Results further showed that temperature has an adverse effect on CPD in the short-term. Among other determinants, CCA, FD and EC have significantly positive impacts on CPD in both cases. The outcomes of Granger causality indicated that a significant two-way causal association is running from all variables to CPD except temperature and rainfall. The connection between CPD and temperature is unidirectional, showing that CPD is influenced by temperature. All other variables also have a valid and significant causal link among each other. Additionally, the findings of variance decomposition suggest that results are robust, and all these factors have a significant influence on CPD in Bangladesh.

These findings have important policy implications for Bangladesh and other developing countries. For instance, introduce improved cereal crop varieties, increase CCA and familiarizes agricultural credits through formal institutions on relaxed conditions and on low-interest rates could reduce the CPD’s vulnerability to climate shocks.

To the best of the authors’ knowledge, this study is the first attempt to examine the short- and long-term impacts of CC on CPD in Bangladesh over 1988–2014. The authors used various econometrics techniques, including the ARDL approach, the Granger causality test based on the vector error correction model framework and the variance decomposition method.

This study aims to empirically examine the relationship between energy consumption and agricultural economic growth in Pakistan over the period from 1984 to 2016.

This study used the autoregressive distributed lag (ARDL) bounds testing approach to cointegration to investigate the long-run and short-run determinants of agricultural economic growth in Pakistan.

The results of the ARDL bounds testing approach to cointegration revealed that long-run linkage exists among the study variables. The findings of this paper showed that agricultural economic growth is positively affected by gas consumption and electricity consumption both in the long-run and short run. The long-run and short-run coefficients of gas consumption and electricity consumption were estimated to be 0.906, 0.421, 0.595 and 0.276, respectively. The estimated equation remains stable during the period from 1984 to 2016 as analyzed by the stability tests.

This study considers the relationship between energy consumption and agricultural economic growth in Pakistan by using an ARDL bounds testing approach to cointegration. The study has three contributions to economic literature:this study used different unit root tests to test stationarity of the variables such as ADF unit root test by Dicky and Fuller and P-P unit root test by Philip and Perron; the ARDL bounds testing approach to cointegration is applied to test the existence of long-run analysis between energy consumption and agricultural economic growth; and to check the robustness, the authors used the Johansen cointegration test to examine the long-run relationship between dependent and independent variables.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

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.

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.

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.

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.

This study aims to investigate the long-run relationship between financial inclusion and agricultural growth in Pakistan for the period of 1960–2018.

The autoregressive distributed lag (ARDL) approach, the Johansen co-integration test and the dynamic ordinary least squared (DOLS) method are used for the evaluation.

The results show that in both short- and long run, domestic credit has a significantly negative impact on the agricultural growth, while broad money and cropped area positively affected the agricultural growth in Pakistan in both cases.

The government and policymakers need to develop strategies that bring together agriculturalists on a single platform so that the government can clearly distinguish the interests of these farmers and can obtain precise information for allocating agricultural expenditure and easing access to credit for small-scale agriculturalists.

This is the first study to evaluate the impact of financial inclusion on the agricultural growth in Pakistan by using different econometric techniques, including the ARDL-bound approach, Johansen co-integration test and DOLS method.

The purpose of this paper is to explore and investigate the electricity consumption and production and its linkage to economic growth in Pakistan.

The authors used an augmented Dickey–Fuller unit root test to check the stationarity of the variables, while an autoregressive distributed lag (ARDL) bounds testing approach and causality test were applied to investigate the variables long-term association with the economic growth.

The study results show that electricity consumption in the agriculture, commercial and industrial sector has significant association with economic growth, while electricity consumption in the household and street lights demonstrate a non-significant association with the economic growth. Furthermore, results also exposed that electricity production from coal, hydroelectric, natural gas, nuclear and oil sources have significant association with the economic growth of Pakistan.

This study made a contribution to the literature regarding electricity consumption and production with economic growth in Pakistan by using an ARDL bounds testing approach and causality test. This study provides a guideline to the government of Pakistan that possible steps are needed to improve the electricity production and supply to fulfill the country demand.

This paper aims to examine the effects of CO₂ emissions, energy consumption, cultivated area and the labour force on the production of cereal crops in Pakistan from the period 1971-2014.

The study used the Johansen cointegration test, the autoregressive distributed lag (ARDL) approach and Granger causality test to estimate the long-run cointegration and direction of the relationship between the dependent and independent variables.

The outcomes of the Johansen cointegration test confirmed the existence of a long-term cointegrating relationship between the production of cereal crops, CO₂ emissions, energy consumption, cultivated area and the labour force. The results of the long-run coefficients of CO₂ emissions, energy consumption, cultivated area and labour force have a positive impact on cereal crops production. The long-run relationships reveal that a 1 per cent increase in CO₂ emissions, energy consumption, cultivated area and labour force will increase cereal crops production by 0.20, 0.11, 0.56 and 0.74 per cent, respectively. Moreover, the findings show that there is a bidirectional causality running from CO₂ emissions and cultivated area to cereal crops production. Moreover, there is a unidirectional causality running from energy consumption to cereal crops production.

The present study also fills the literature gap for applying the ARDL procedure to examine this relevant issue for Pakistan.

The purpose of this paper is to evaluate the impact of short-term loan (STL) vs long-term loan (LTL) on wheat productivity of small farms in Sindh, Pakistan.

The econometric estimation is based on cross-sectional data collected in 2016 from 18 villages in three districts, i.e. Shikarpur, Sukkur and Shaheed Benazirabad, Sindh, Pakistan. The sample data set consist of 180 wheat farmers. The collected data were analyzed through different econometric techniques like Cobb–Douglas production function and Instrumental variables (two-stage least squares) approach.

This study reconfirmed that agricultural credit has a positive and highly significant effect on wheat productivity, while the short-term loan has a stronger effect on wheat productivity than the long-term loan. The reasons behind the phenomenon may be the significantly higher usage of agricultural inputs like seeds of improved variety and fertilizers which can be transformed into the wheat yield in the same year. However, the LTL users have significantly higher investments in land preparation, irrigation and plant protection, which may lead to higher wheat production in the coming years.

In the present study, only those wheat farmers were considered who obtained agricultural loans from formal financial institutions like Zarai Taraqiati Bank Limited and Khushhali Bank. However, in the rural areas of Sindh, Pakistan, a considerable proportion of small-scale farmers take credit from informal financial channels. Therefore future researchers should consider the informal credits as well.

This is the first paper to examine the effects of agricultural credit on wheat productivity of small farms in Sindh, Pakistan. This paper will be an important addition to the emerging literature regarding effects of credit studies.

The purpose of this paper is to examine the effect of savings mobilization on access to credit among smallholder farmers’ in the Birim central municipality of Ghana.

A cross-sectional primary data set was used to estimate the factors influencing smallholder farmers’ access to credit and size of loan to be borrowed using the IV-Probit and IV-Tobit model.

The results of the study revealed that savings mobilization has a positive significant impact on access to credit and the total amount of credit one can borrow as well. Other control variables such as transaction cost and farm size depicted a negative significant impact on access to credit. Land ownership, member of an association, household size, years of farming experience and education also showed a positive significant impact on access to credit.

The paper only examined the savings effect on credit accessibility among smallholder farmers in one of the municipality’s in the Eastern region of Ghana. Future research should consider all or many municipality for an informed generalization of findings.

This paper provides evidence that smallholder farmers knowledge on the financial market is poor and it would require the policymakers or NGOs to organize financial management training programs so that the farmers high ignorance of the financial market will significantly reduce.

Although existing studies have examined smallholder farmers’ access to credit, the unique contribution of this paper is the analysis of the impact of saving mobilization on credit accessibility in Ghana, a major access to credit determinant in the financial market. In addition, those researchers who factored in savings as an access to credit determinant did not also consider the casual relationship between these two variables, thus, the present of endogeneity of which this paper does.

The purpose of this paper is to examine the effect of support price on wheat production in Pakistan during the period 1971–2016.

To capture the effect of support price on wheat production, the authors estimated the long-run linkage by using the ARDL bounds testing approach to cointegration.

This study confirmed the presence of a positive and long-term effect of area under cultivation, support price and fertilizer consumption on wheat production through ARDL bounds test. The results showed that both in the long run and short run, support price plays an important role in the enhancement of wheat production. The authors also found that the coefficients of the area under cultivation and fertilizer consumption variables were statistically significant and positive both in the long run and short run.

The use of the ARDL approach that examines the long-run and short-run effects of support price on wheat production in Pakistan makes the current study unique. An emerging economic literature suggests that only limited research has been conducted in this area.

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.

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.

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.

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.

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.