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The purpose of this paper is to estimate the determinants of rural and national poverty, of income distribution, and of agricultural growth in developing countries.

Data for all variables are from the 2008 World Development Report. The author applies the least‐squares estimation technique in a multivariate linear regression.

It is found, from different size samples, that: the percentage of the rural population living below the national rural poverty line in a developing country is dependent upon the logarithm of per capita purchasing power parity gross national income and the region in which it is located; it linearly depends on its per capita agriculture value added and its geographic location; agriculture value added growth linearly depends on the share of women in the agricultural labor force, whether the developing country is agriculture‐based, and whether it is located in Europe or Central Asia; and agricultural productivity linearly depends on the amount of arable and permanent cropland per agricultural person, the share of women in the agricultural labor force, and the share of agricultural employment in total employment.

Statistical results in this paper will assist governments in developing countries assess the magnitude of agricultural policy variables in an effort to use agriculture as an engine for economic development.

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.

The paper analyzes the response of agricultural value added to credit and real interest rate shocks in the West African Economic and Monetary Union (WAEMU) and make a short-term comparative effect analysis of credit granted to the agricultural sector on agricultural value added among member countries.

First, in order to estimate impulse response functions (IRFs) and study shocks, a panel VAR model is used. Second the paper uses an autoregressive distributed lag (ARDL) model with the associated error correction model to make a comparative analysis of the effect of agricultural credit on agricultural value added in the WAEMU.

Results shows that: (1) credit stimulates agricultural value added only in the medium and long term; (2) in the case of WAEMU, credit only becomes a means of lifting the constraint of capital underutilization after three years; (3) short-term credit granted to agriculture in WAEMU has a weak and differentiated effect on agricultural value added from one country to another.

It is imperative to implement a policy of lowering real short-term interest rates. Moreover, a monetary policy that favors direct financing of agriculture to the detriment of that oriented toward market financing is to be prioritized.

The originality of this paper is that it makes the link between macroeconomics and agriculture. It shows how the monetary instrument can be manipulated to improve the performance of agriculture. Actually, in WAEMU, the financing of agriculture is provided by the market. This paper proposes a new approach which is direct financing. The paper offers possibilities for the coordination of agricultural policies in the WAEMU.

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.

Agriculture is the major source of livelihood for the majority of population in Sub-Saharan Africa but its productivity is not only low it has started showing signs of decline since 2012. The purpose of this paper is to find out whether official development assistance for agriculture is effective.

The data for development assistance for agriculture are broken down into the major agricultural sectors in receiving countries. The empirical evidence is based on the two-step system, i.e. generalized method of moments, to assess the degree of responsiveness of agricultural productivity to development assistance.

There is a positive relationship between development assistance and agricultural productivity in general. However, when broken down into the major agricultural recipient sectors, there is a substitution effect between food crop production and industrial crop production. Better institutions and economic freedom are found to enable agricultural productivity growth, and to increase the effectiveness of development assistance. The structural economic transformation associated with agricultural development assistance is also found to be weak.

Allocation of development assistance for agriculture is primarily determined by need, although expected effectiveness also increases the assistance receipts. Agricultural assistance policies could focus more on building productive capacity to reduce the need while boosting effectiveness.

Breaking down data into agricultural recipient sectors and controlling for the potential spurious correlation under the assumption that more development assistance could be allocated, where agricultural productivity is already increasing due to some other factors.

This study aims to examine the effect of structural transformation on poverty alleviation in Sub-Saharan Africa (SSA) countries with a higher share of services as a percentage of gross domestic product (GDP). The study specifically focuses on the value-added share as a percentage of GDP in the agricultural, manufacturing, industrial, and service sectors using time series data from 1988 to 2019.

The study utilizes the autoregressive distributive lag (ARDL) bound test framework for estimation, based on the conclusions drawn from the augmented Dickey-Fuller and Phillips–Perron unit root tests, which provide evidence of a mixed order of integration.

The result reveals that agriculture value-added (AVA), manufacturing value-added (MVA), industrial value-added (IVA), and services value-added (SVA) have a positive and significant impact on poverty alleviation in both the short and long run. However, the agriculture sector is found to be more effective in reducing poverty compared to the other sectors examined in this study. Additionally, this study challenges the notion that SSA countries have undergone an immature structural transformation. Instead, it reveals a pattern of stagnant structural transformation, as indicated by the lack of growth in the industrial and manufacturing value-added shares of GDP.

To enhance productivity and reduce poverty, SSA economies should adopt a development strategy that prioritizes heavy manufacturing and industrial sectors, leading to a transition from the agricultural to the secondary and tertiary sectors.

The study contributes to the emerging literature on structural transformation by investigating which sector is more efficient in reducing poverty in SSA countries, using the value-added share as a percentage of GDP for agricultural, manufacturing, industrial, and service sectors. The study also aims to determine if SSA countries have experienced immature structural transformation due to the growing share in the service sector.

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.

This chapter does three things. First, it estimates regional gross domestic product (GDP) for three different geographical levels in Switzerland (97 micro regions, 16 labor market basins, and 3 large regions). Second, it analyzes the evolution of regional inequality relying on a heuristic model inspired by Williamson (1965), which features an initial growth impulse in one or several core regions and subsequent diffusion. Third, it uses index number theory to decompose regional inequality into three different effects: sectoral structure, productivity, and comparative advantage.

The results can be summarized as follows: As a consequence of the existence of multiple core regions, Swiss regional inequality has been comparatively low at higher geographical levels. Spatial diffusion of economic growth occurred across different parts of the country and within different labor market regions. This resulted in a bell-shaped evolution of regional inequality at the micro regional level and convergence at higher geographical levels. In early and in late stages of the development process, productivity differentials were the main drivers of inequality, whereas economic structure was determinant between 1888 and 1941. The poorest regions suffered from comparative disadvantage, that is, they were specialized in the vary sector (agriculture), where their relative productivity was comparatively lowest.