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Common Agriculture Police in the EU, direct payments, solvency and income

We employ agriculture data for all twenty-eight EU Member States. The data comes from the public Farm Accountancy Data Network (FADN) of the EU. In terms of methodology we employ panel regression and panel Vector Autoregression analysis (panel VAR) to take into account possible endogeneity issues.

The reported panel regressions, impulse response functions (IRFs) and variance decompositions (VDCs) show that agriculture income has been subdued due to negative shocks in direct payments and solvency. Our results do not support the hypothesis that higher direct payments would increase agriculture income. In addition, whilst solvency subdues agriculture income, investment asserts a positive impact on agriculture income.

Further research on the impact of direct payments of CAP on EU agriculture is warranted at a disaggregate level so as to examine whether there is variability in the underlying interlinkages at regional level

As a policy implication, and in light of the ongoing reform of the EU's CAP, we would propose to raise net value added in agriculture using targeted income support to small and medium-sized farms. The European Economic Recovery Plan (EERP) would be also supportive. In addition, further enhancing financial integration across the EU would provide funds for investment in agriculture.

As social implication, one would propose to raise investment in agriculture, that is through the European Economic Recovery Plan (EERP). The EERP is designed as a stimulus package set up to mitigate the consequences of the global financial crisis in the EU. Also, a way to boost agriculture income is through the credit channel of the on-going quantitative easing of the ECB, where unconventional monetary policy is aiming to support the growth prospect of the Euro area.

This study examines the impact of direct payments, which include all subsidies, of the EU's Common Agriculture Policy (CAP) on agriculture income as measured by the net value added. We also control for solvency. Despite the magnitude of CAP on the EU budget, few studies investigate the impact of direct payments on income in the aftermath of the financial crisis. This is surprising given the importance of agriculture for the economic recovery of the EU that remains anaemic more than a decade after the crisis.

This study aims to investigate the contingent roles real effective exchange rates (REERs) play in mediating the effects of oil revenue on the agriculture sector value-added in 25 major and minor oil-exporting (MIOEC) countries during the period of 1975–2014.

The panel autoregressive distributed lag (ARDL) estimator proposed by Pesaran et al. (1999) was relied upon to achieve the objectives of the study. This estimator involves a pool of small cross-sectional units over a long-time span that covers for 25 oil-exporting countries over 39 years (1975–2014).

This paper reveals the following findings. Firstly, oil revenue has a direct negative effect on agricultural value-added in the short- and long-term. This finding holds for full sample and subsamples of major oil-exporting (MAOEC) and MIOEC countries. Further assessment reveals that the magnitude of the impact is larger for MAOEC than that of the MIOEC. Secondly, the finding for the long-run effect shows that the contingent effect of real exchange rate on the nexus between oil revenue and agricultural value-added is negative and statistically significant at the conventional level for the full sample. This suggests that, in the long-run, the appreciation in real exchange rates exacerbate the negative marginal effects of oil revenue on agricultural value-added in all oil-exporting countries. However, when sub-samples of MAOEC and MIOEC are considered, the contingent effect disappeared (become insignificant) in MAOEC while it is positive and statistically significant in MIOEC. Thus, in the long-run, the appreciation in real exchange rates diminishes the negative marginal effects of oil revenue on agricultural value-added in MIOEC. While oil revenue has a direct negative effect, its effect is also moderated by the variations in REERs in MIOEC in the long-run. Finally, in the short-run, fluctuations in the real exchange rate do not matter for the nexus of oil revenue and agriculture sector in these countries whether minor or MAOEC countries.

This study contributes to the debate in the empirical literature on the Dutch disease effect and “oil curse”. Using the appropriate panel ARDL empirical framework, it provides evidence on how exchange rate variations in the oil-exporting countries influence the nature of the effects of the oil revenue on agricultural sectors in the long-run but not in the short-run. Contingent effects of REERs only appear to exist in MIOEC in the long-run.

Multifunctional agriculture, including value-added agriculture, has drawn the attention of different stakeholders (government, farmers) interested in maximising the potential of farming operations and strengthening rural communities. This preliminary study aims to investigate value-added agriculture, including the extent to which food growers consider, or are involved in, this aspect of multifunctional agriculture, from the perspective of orchard operators located in different Australian states.

Orchard operators were contacted through regional growers' associations and by mail. A total of 80, the large majority of whom are small orchardists, participated in the study, completing a questionnaire designed to collect both quantitative and qualitative data.

Overall, there is moderate interest among the participating orchard operators in adding value to food production. Respondents also indicate barriers in the form of added expenses, lack of time, knowledge, and markets, to sell value-added products.

This study has only provided preliminary data from a limited number of participants; future research could broaden the scope to gather the insights of more orchard operators or even study other rural food-growing sectors.

With increasing pressures on the farmland, the findings have several implications, in particular, the need to understand the cost-benefits involved in value adding activities and potential cost-savings strategies.

In the case of Australian agriculture, little has been discussed about the extent to which value-added food production is being considered among food growers, for instance, using commercial kitchens to process foods that do not sell as “premium.” The present study examines this unexplored dimension and seeks to provide useful preliminary information.

This study aims to provide an empirical investigation into rising capital flight and the role of institutional quality to mitigate its effect on the real sector in sub-Saharan Africa (SSA).

The study uses the system generalized method of moments and uses data spanning from 1989 to 2020 from 26 SSA countries.

The findings show that capital flight has no direct impact on the real sector while institutional quality adversely impacted the agricultural and industrial sectors. The study also found that institutional quality is unable to mitigate the effect of capital flight on the industrial sector.

This study investigates if institutional quality mitigates the impact of capital flight on the real sector proxied by industrial value-added and agriculture value-added.

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂ emissions, while GDP² reduces CO₂ emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂ emissions whereas a unidirectional long-term causality runs from GDP² and agriculture value-added to CO₂ emissions.

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

The main purpose of this study is to explore the presence of the EKC hypothesis in emerging economies. Additionally, the present study also explores the existence of the “resource curse hypothesis” (RCH), and the causal relationship among the variables that are considered for testing the presence of EKC and RCH hypothesis for a panel of selected emerging economies for the time period between 1990 and 2014.

The authors performed unit root test followed by cointegration test to test the existence of cointegrating relationship among the variables. Dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods are used to obtain long-run estimates of considered variables, and the Granger causality test is performed to test the directional causality.

The long-run estimates obtained from DOLS and FMOLS techniques support the presence of the EKC (inverted U-shape) and the RCH.

To the best of the authors’ knowledge, the present work is the pioneer study for EKC and RCH investigation in the context of emerging economies. The policy implication is that these economies should look forward to drafting new policies to reduce environmental degradation and promote sustainable development.

Introduction: Climate change and the limiting nature of fossil natural resources are compelling elements that have driven the search for environmentally friendly alternatives to the traditional economy. In this context, as the main pillar of bioeconomy, biomass can contribute to energy sustainability, temper effects of climate change, and make the use of natural resources more efficiently. Central and Eastern European (CEE) countries have a relatively common economic history of agriculture playing a pivotal role in the former centralized economy. Purpose: This chapter analyzed the importance of biomass produced from residues of crops in CEE countries. This analysis is regarded as incentive to take a deeper look at biomass in CEE countries with acknowledged agricultural potential. CEE countries have been part of the former European socialist bloc, with agriculture being a core component of the centralized economy. Even though their economies have been undergoing a lengthy transition process to the market economy, this sector of activity still holds a significant share. Therefore, CEE countries provide a suitable ground for our analysis. Methodology: The authors selected characteristics of the agricultural sectors and development, and assess their relationship with biomass production in the CEE countries, using an Ordinary Least Squares method. Then, the authors investigate the environmental implications of crop biomass production in a similar framework. Findings: The results reveal that the agricultural biomass sector contributes to economic development, and it does not have negative implications for environmental indicators. These results show that biomass production is a sustainable target to be pursued.

The empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes their estimates unreliable. This paper aims to investigate the relationships between climate change and agriculture and test the potential reverse causality and endogeneity of climatic variables to agriculture.

This study introduces a geographical instrument, longitude and latitude, for temperature to assess the impact of climate change on agriculture by estimating regression using IV-two-stage least squares method over annual panel data for 60 countries for the period of 1999-2011. The identification and F-statistic tests are used to choose and exclude the instrument. The inclusion of some control variables is supposed to reduce the omitted variable bias.

The study finds a negative relationship between temperature and agriculture. Surprisingly, the magnitude of the coefficient on temperature is mild, at least 20 per cent, as compared to previous studies, which may be because of the use of the instrumental variable (IV), which is also supported by an alternative robust measure when estimated across different regions.

The study provides strong implications for policymakers to confront climate change, which is an impending danger to agriculture. In designing effective policies and strategies, policymakers should focus not only on crop production but also on other agricultural activities such as livestock production and fisheries, in addition to national and international socio-economic and geopolitical dynamics.

This paper contributes to the growing literature in at least four aspects. First, empirical settings introduce an innovative geographical instrument, Second, it includes a wider set of control variables in the analysis. Third, it extends previous studies by involving agriculture value addition. Finally, the effects of temperature and precipitation on a single aggregate measure, agriculture value addition, are separately investigated.

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.

The study aims to identify the dynamic complexities and development points of the entrepreneurial ecosystem (EE) in the agricultural sector of Iran to improve production factors' productivity, including arable land, water resources and human capital.

First, the EE of the agricultural sector in Iran was designed following Isenberg's framework. Then, the main variables and interrelationships of the variables in each context of the ecosystem, called subsystems, were formulated using the system dynamics (SD) approach. Next, the model was simulated and validated. Afterward, different policy options were identified, embedded into the model structure and simulated. Finally, the best policy group was selected.

According to Isenberg's EE model, three groups of policies were identified and evaluated, including “entrepreneurship development financing and investment policy,” “agricultural ecosystem's supportive services development policy” and “production factors productivity development policy.” According to the simulation results, the best combination of the solution strategies was recognized. The presented SD-EE model has a generic nature in the agricultural sector and could be modified to be applied in different regions for policy-making purposes.

The main contribution of the study is twofold. First, Isenberg's EE framework is applied to structure the main subsystems and interrelationships of the subsystems in the agricultural sector that has previously received limited attention. Second, the research is the first to operationalize the basic theory of Isenberg's EE in practice applying a robust systemic modeling methodology like SD.