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Most agriculture-based economies in Africa are working on increasing their agricultural productivity and production following the African Union (AU) recommendations. However, it has been shown that increasing agricultural production without ensuring value-chain development may end up in welfare losses for farmers due to falling farm-gate prices. Little research has been conducted so far on the economy-wide effects of food value-chain development. This article contributes to filling this gap by analysing the effects of food-processing sector development on welfare in an agriculture-based economy, taking the example of Benin. We calibrate a Computable General Equilibrium (CGE) model to a comprehensive 2019 Social Accounting Matrix (SAM) for Benin. We introduce a novel welfare measure, accounting for changes in savings. Results show that enhancing the food-processing sector increases demand for agricultural raw materials and hence agricultural production and prices. Accordingly, the price of low-skilled labour increases. This primarily benefits low-income households, who derive most of their income from this factor. The overall income and welfare effects are pro-poor. Accordingly, income disparity as well as poverty incidence and gap decrease. We conclude, that the development of food-processing has the potential to make agricultural development in agriculture-based economies more pro-poor. [ABSTRACT FROM AUTHOR]

Although for decades, the Ministry of Agriculture, Forestry, and Fishery of Japan has formed agricultural policies based on food self-sufficiency as a vital factor in securing the domestic food supply, the impacts of agricultural self-sufficiency on the relationship between international and domestic markets are not well understood. Most previous literature on agricultural price transmissions applies conventional error correction and vector autoregression models. However, we employ the state-of-the-art technique, namely the time-varying parameter vector autoregression (TVP-VAR) connectedness model, as well as the dynamic conditional correlations based on the asymmetric Baba – Engle–Kraft – Kroner method to investigate the effectiveness of beef self-sufficiency and its inventory in stabilizing local beef prices in Japan. Our primary results indicate that the global beef price is the net transmitter of shocks, while the home-grown beef price in Japan is the net receiver of shocks. Furthermore, we find that high self-sufficiency in beef does not significantly protect local beef markets from global beef markets, but the imported beef inventory effectively alleviates the wholesale price volatility of imported beef. One policy implication is that the government should not take protectionist policies to enhance beef self-sufficiency, and import beef stocks could be accumulated to stabilize imported beef markets. [ABSTRACT FROM AUTHOR]

This research discusses the impact of climate change on inflation, as well as the limitations of existing econometric models in incorporating multiple climate-related variables in determining inflation. To address this limitation, the study introduces the climate condition index (CCI) for 153 countries covering the 1901–2021 period to investigate the relationship between climate and agricultural inflation. This index represents a weighted average of various climate variables, including cloud coverage, temperature, precipitation, vapor pressure, and wet day frequency. The weights are the long-term cointegration coefficients of the climate variables concerning the Agricultural Producer Price Index (APPI), which were obtained from separate vector error correction models (VECMs) constructed for each country. The study shows that climate change has a significant impact on agricultural prices globally, as evidenced by a median Granger causality p-value of 0.036 across 153 countries (CCI Granger causing APPI in 127 countries with a 90% confidence interval). The results align with panel vector autoregression and country-specific VECMs impulse responses, which indicate that climate conditions negatively impact agriculture in 142 countries, while 11 countries gain from climate change. The study's overall results suggest that climate change substantially affects agriculture globally. In light of the significant economic reliance on agricultural production, it is advisable for governments to consider the issue from the perspective of sustainable growth, while central banks should tackle it with a focus on the inflationary implications through green quantitative easing. [ABSTRACT FROM AUTHOR]

Agriculture plays a leading role in the economic growth and development process. Ensuring the continuity of production depends on the purchasing power of the producers. The sustainability of production and the development of the rural welfare index in favor of the producers will increase the driving role of the agricultural sector, which is also a resource for other sectors. This study determined the variables affecting the Domestic Terms of Trade of the greenhouse tomato producers in Antalya, Türkiye. The product price has been determined as the major factor affecting the Domestic Terms of Trade. In addition, it was concluded that a one-unit increase in the product price increases the Domestic Terms of Trade by 34.99 units. Interviews revealed that the continuity of consumption needs is more important than the continuity of production. It has been determined that the high and variable input costs cause erosion in the incomes of the producers. Agricultural policies will be more effective both in the short and long term when the aim is to improve the welfare and purchasing power of producers, rather than intervening in agricultural prices or reducing prices. [ABSTRACT FROM AUTHOR]

Hundreds of millions of people are now facing food insecurity as challenges from climate change, the aftereffects of the COVID‐19 pandemic, and strife and conflicts make availability of food at reasonable prices challenging. International trade has enabled the reallocation of agricultural products, essential for nutrition, from countries with supply markets to other points of demand and has been the subject of an increasing number of policy interventions by governments. In this paper, a multicommodity international trade network equilibrium model is constructed with the inclusion of nutritional minimal standards to support food security, accompanied by consumer subsidies, for which explicit formulae are provided. The theoretical and computational framework is based on variational inequalities. Numerical examples focusing on Ukraine and MENA (Middle Eastern and North African) countries and a staple commodity of wheat demonstrate the modeling and policy framework. [ABSTRACT FROM AUTHOR]

This study aims to analyze the drivers behind price changes in agricultural products in Türkiye from 2002 to 2021, considering the impacts of three crises of different causes which are the global food crisis, the Russia–Türkiye aircraft crisis, and the COVID-19 pandemic. The potential factors are categorized into four subgroups: governmental effects, agricultural inputs, macroeconomic indicators, and climatic conditions. The selected agricultural goods for price change measurement include wheat and maize representing subsistence goods, and olive oil and cotton as marketing goods. The autoregressive distributed lag (ARDL) model is applied to observe both the short- and long-term impacts of the variables on price developments. The results suggest that government effectiveness, regulatory quality, nitrogen use, water price, money supply, exchange rate, and GDP under the related categories are the most effective factors in price changes. Among the variables under the category of climatic conditions, significant values are obtained only in the analysis of the temperature impact on olive oil. The analysis also reveals the variable impact of crises on the prices of the chosen products, depending on the goods involved. The maize and wheat analyses yield particularly noteworthy results. In the long run, nitrogen use demonstrates a substantial positive impact, registering at 29% for wheat and 19.47% for maize, respectively. Conversely, GDP exhibits a significant negative impact, with 26.15% and 20.08%. Short-term observations reveal that a unit increase in the governmental effect leads to a reduction in inflation for these products by 17.01% and 21.42%. However, changes in regulatory quality result in an increase in inflation by 25.45% and 20.77% for these products, respectively. [ABSTRACT FROM AUTHOR]

Environmental issues, in particular climate change, have assumed increasing urgency, and have become even more acute with the Covid-19 pandemic and the globally rise of hunger and inequality. Despite this urgency, international demands and prices for agricultural and mineral commodities have been a driving force behind the expansion of the agricultural frontier (changes in land use), particularly with the increase in monocultures, extensive livestock farming and mineral extraction for export. This has generated debates, studies and reflections in Political Economy, Political Ecology, among other areas of knowledge, but has this urgency raised reflections and research on the importance of land and the agrarian issue? Based on some political (dis)agreements and measures, and in dialogue with international literature, this text seeks to contribute to the so-called Critical Agrarian Studies, formulating, conceptually and politically, a notion of "eco-agrarian issue", analyzing and critically interpreting agrarian extractivism in the Brazilian agricultural frontier. [ABSTRACT FROM AUTHOR]

Eradicating the high level of youth unemployment remains a global challenge, especially in sub-Saharan Africa. Youth involvement in agriculture, which could have lower unemployment, is low. Despite a high volume of literature on youth involvement in agriculture, agricultural graduates have received little research attention. Therefore, this study assessed agricultural graduate involvement in agribusiness enterprises to fill the research gap. Data were collected from 200 agricultural graduates who were randomly selected. Descriptive statistics and logistic regression were methods of data analysis. The results revealed that, unlike other youths, agricultural graduates had a positive opinion about agriculture. Although about half were involved in agribusiness, almost all of them were willing to engage in it if supplied with production resources, especially land and capital for start-ups. Family land, access to credit, perceived benefits, attitudes, location, and gender significantly influenced agricultural graduates' participation in agribusiness. To be self-employed and an employer, to be financially independent, to be food secure, due to access to land, due to access to credit, parental influence, satisfaction, and personal growth, and to continue the family business were the reasons why agricultural graduates became involved in agribusiness enterprises. On the other hand, lack of capital, lack of access to land, the risk involved in agriculture, poor agricultural pricing, poor agricultural support from the government, seeking a white-collar job, and peer influence were reasons why some agricultural graduates were not involved in agribusiness. Hence, agricultural graduates should be encouraged and supported with resources, especially arable land, and capital, by the government, development agencies, and financial institutions to ensure effective participation in agribusiness. [ABSTRACT FROM AUTHOR]

Seaborne shipping is the dominant mode of transport in international trade in agricultural products, and an increasing part of seaborne agricultural trade is carried in containers. Furthermore, the majority of world containers are moved through liner shipping services, that is, regular transport services provided by global shipping companies which comprise a dense network connecting ports and countries around the world. Using a theoretically consistent gravity equation and a novel identification strategy based on the use of intra‐national trade flows, this paper investigates the effect of liner shipping connectivity on international trade in agricultural products. The results show that liner shipping connectivity has a positive and statistically significative effect on agricultural trade. Moreover, this positive effect can be observed for the majority of the agricultural products analysed and is also identified for countries at different stages of development. These findings appear especially relevant in terms of the objective of increasing less developed countries' participation in global agricultural trade. [ABSTRACT FROM AUTHOR]

This paper determines the impact of Brent oil shocks on the price of shares of companies from the oil, agricultural and food industries that includes the period of the COVID-19 pandemic. For this purpose, they use a quantile regression approach and compare its findings with a standard Ordinary Least Squares (OLS) regression model. Moreover, in this research they use quantile regression, which enables them to analyze different quantiles of share prices of companies from the oil industry, the agricultural industry, and the food industry. They observe three different periods - a period of recession, a normal period and a period of expansion. Finally, empirical evaluations using quantile regression and OLS models show us that shocks from the oil market are more pronounced in companies from the oil industry compared to companies from the agricultural and food industries. The findings of this research provide important information for investors, economic policy makers, and other parties. [ABSTRACT FROM AUTHOR]

This study utilises structural gravity models to examine the impact of globalisation on distance in agricultural and processed food trade, the relative effects of international distance and home bias effects. The results show that larger internal distances lower domestic sales. The home bias effect is substantially larger in agricultural commodities compared to processed agricultural commodities. Omitted variable bias is observed in friction variables when the relative intra-national distance and home market bias are excluded. After controlling for relative intra-national trade costs and the home bias effect, globalisation does not lead to a smaller impact of distance on trade. Substantial heterogeneity exists when analysing individual commodities. [ABSTRACT FROM AUTHOR]

Scaling service operations is an effective way to promote modernization among small farmers. Exploring the factors influencing grain farmers' choices in selecting services is essential to promote the strong development of the agricultural production service market and improve the efficiency of agricultural operations in China. Based on the 2019 data on corn farmers in the China Rural Revitalization Survey (CRRS) database, and using the Double-Hurdle Model, the factors influencing the service selection behavior of corn farmers are explored, and the research conclusions are as follows: (1) agricultural service prices have a negative impact on the demand for agricultural services, which varies from service to service; (2) labor prices do not influence the demand for any kind of service; (3) land circulation rents have a negative impact on the demand for agricultural services, which varies from service to service; (4) a high family net income can significantly prompt the adoption of agricultural services, which varies from service to service; (5) small-scale farmers are more sensitive to changes in service prices than large-scale farmers; (6) the four economic factors have no effect on the sowing service market. Based on the above conclusions, this paper puts forward suggestions such as improving the market price mechanism for agricultural production services, and increasing subsidies related to agricultural production services. [ABSTRACT FROM AUTHOR]

An important task of China’s agricultural development is to achieve modernization in all respects. The rural revitalization strategy was first introduced in the report to the 19th National Congress of the Communist Party of China. This strategy now stands as the general guiding principle and central task of China’s agricultural initiatives in the new era and serves as a pivotal move toward advancing agricultural modernization. Taking into consideration the current situation of China’s agricultural development, the authors analyze the factors driving agricultural modernization and project the trajectory of agricultural modernization by 2035. The findings indicate that China has created a conducive institutional and development environment in production, consumption, industry, science and technology, trade, etc., thereby laying a solid foundation for its agricultural modernization. Projections suggest that by 2035, China will establish itself as the world’s preeminent nation in agricultural production and consumption, a powerhouse in agricultural industrialization and agricultural product trading, and a leading country in agricultural science and technology. However, China still faces tremendous challenges in terms of consumption structures, quality requirements, industrial development, format innovation, production methods, service functions, scientific and technological levels, and personnel structure. Therefore, on the path to agricultural modernization, China still needs to advance the structural reforms on the agricultural supply side, shift its agricultural production and operation methods, elevate its level of opening up in agriculture, and foster a deeper integration between urban and rural areas. [ABSTRACT FROM AUTHOR]

Using variation in crop prices induced by large swings in demand surrounding World War I, we examine the fertility response to crop revenue increases from 1910 to 1930. Our estimates indicate that agricultural price increases reduced fertility, explaining about 9% of the overall decline in fertility over the period. The effect persists years after the collapse of the war boom. Importantly, we show that fertility declines were concentrated in farm women and fertility declined along intensive and extensive margins. Combined, the pattern of estimates is consistent with agricultural women experiencing an increase in the opportunity cost of their time. [ABSTRACT FROM AUTHOR]

This study investigates the effect of agricultural trade openness on fruit prices in South Korea considering the quality improvement originating from agricultural trade policies by examining the U‐shaped relationship between agricultural openness and fruit prices. Utilising the autoregressive distributed lag (ARDL) model and annual data from the period 1988–2019, we find that while an increase of agricultural openness leads to a reduction in fruit prices, an increase of square of agricultural openness leads to a rise of fruit prices in the long‐run. In other words, our hypothesis of a U‐shaped relationship between agricultural openness and fruit prices is satisfied. This finding implies that determining the optimal amount of high‐quality fruit is important for fruit farmers' income. Additionally, Korea should divide the fruit consumer price index (CPI) into high‐quality and traditional fruit to solve the problem of an increase in fruit CPI without an actual increase in the price of traditional fruit. [ABSTRACT FROM AUTHOR]

Agricultural product prices are subject to various uncertainties, including unpredictable weather conditions, pest infestations, and market fluctuations, which can significantly impact agricultural yields and productivity. Accurately assessing and understanding price is crucial for farmers, policymakers, and stakeholders in the agricultural sector to make informed decisions and implement appropriate risk management strategies. This study used the ordered weighted average (OWA) operator and its extensions as mathematical aggregation techniques incorporating ordered weights to capture and evaluate the factors influencing price variation. By generating different vectors related to different inputs to the traditional formulation, it is possible to aggregate information to calculate and provide a new view of the outcomes. The results of this research can help enhance risk management practices in agriculture and support decision-making processes to mitigate the adverse effects of price. [ABSTRACT FROM AUTHOR]

An efficient machine learning-based framework for crop price prediction is proposed in this paper to assist the farmers in estimating their profit-loss beforehand. The proposed work is composed of four functional blocks, such as crop yield prediction, determination of supply, demand prediction and crop price prediction. The input datasets consist of the various field values, such as yield, remaining crop at the end of the year, import, demand and price of a crop. Various time series-based algorithms, such as autoregression, moving average, autoregressive moving average, autoregressive integrated moving average and exponential smoothing, are used to forecast the crop yield. The supply of the crop is determined as a sum of three variables, i.e., the predicted crop yield, residue and import values. The demand for the crop is predicted from a year alone as the demand has more correlation with year over other factors. The crop price from demand, supply and year is predicted using different approaches, which include the time series method, statistical approaches and machine learning techniques. Finally, these three techniques for price prediction are compared to determine the best model having minimum root-mean-square error value. In the proposed work, the decision tree regressor is found to be the best model, for predicting crop price, over others. The superiority of the proposed work over existing approaches, in terms of various aspects, is shown by simulation results. [ABSTRACT FROM AUTHOR]

The objective of this research was to analyze some socioeconomic and environmental variables (timber forest production, forest fires, the National Agricultural Consumer Price Index, the agricultural Gross Domestic Product, the planted agricultural area, the rural population, and the urban population ) that influence deforestation in Mexico, during the period 1990-2020. The analysis used an estimated multiple linear regression model built using the Ordinary Least Squares method. The statistical results indicated that the statistically significant variables were forestry production, the National Agricultural Consumer Price Index, and the agricultural Gross Domestic Product. [ABSTRACT FROM AUTHOR]

Non-tariff measures as hidden barriers to agricultural trade would not only result in production and welfare distortions due to the international relocation of activities along the agricultural value chain, but also yield subsequent consequences to both the scale and distribution of carbon emissions from the agri-food system. This paper estimates ad valorem equivalents of non-tariff measures using a gravity model in combination with detailed bilateral trade data of 2001-2019, and incorporates the estimations in the Global Trade Analysis Project model and a multi-regional input-output table of Eora26 to quantify economic and environmental impacts of non-tariff measures. We show that while tariff equivalents are on average positive for all types of non-tariff measures, there are substantial heterogeneities across countries and products. The extra trade barriers imposed by these measures would increase the scale of domestic agriculture-related sectors for most agriculture importing countries, and vice versa for major exporters. Meanwhile, they would reduce the global welfare at amount of 16 millions US dollars on average and in particular, the welfare of key imposers and targeting markets of non-tariff measures. Carbon emissions from the agri-food system tend to increase about 1% around the world, especially due to the larger food processing industry in developed countries. Our paper confirms that non-tariff measures lead to both welfare distortions and carbon emissions in the agri-food system. It thus calls for urgent needs to promote further reforms of the agricultural trade regime and the policy coordination across countries to facilitate agri-food system transformation with more integration and sustainability. [ABSTRACT FROM AUTHOR]

This paper shows that, first, the effects of monsoon rainfall shocks on agricultural yield in India are highly asymmetric: yield falls strongly after droughts, whereas excessive rainfall has only little effects. Second, our key novel finding is that the short‐lived yield loss after a widespread drought elicits a persistent decline (increase) in wages (food prices), which lasts for up to five years. Third, affiliation to the same National Sample Survey region (and thus to the same state) seems to be a key determinant of internal migration, whereas distance appears more relevant for food arbitrage trading. [ABSTRACT FROM AUTHOR]

Demand for food products, often from international trade, has brought agricultural land use into direct competition with biodiversity. Where these potential conflicts occur and which consumers are responsible is poorly understood. By combining conservation priority (CP) maps with agricultural trade data, we estimate current potential conservation risk hotspots driven by 197 countries across 48 agricultural products. Globally, a third of agricultural production occurs in sites of high CP (CP > 0.75, max = 1.0). While cattle, maize, rice, and soybean pose the greatest threat to very high-CP sites, other low-conservation risk products (e.g., sugar beet, pearl millet, and sunflower) currently are less likely to be grown in sites of agriculture-conservation conflict. Our analysis suggests that a commodity can cause dissimilar conservation threats in different production regions. Accordingly, some of the conservation risks posed by different countries depend on their demand and sourcing patterns of agricultural commodities. Our spatial analyses identify potential hotspots of competition between agriculture and high-conservation value sites (i.e., 0.5° resolution, or ~367 to 3,077km², grid cells containing both agriculture and high-biodiversity priority habitat), thereby providing additional information that could help prioritize conservation activities and safeguard biodiversity in individual countries and globally. A web-based GIS tool at https://agriculture.spatialfootprint. com/biodiversity/systematically visualizes the results of our analyses. [ABSTRACT FROM AUTHOR]

European farm households will face increasingly challenging conditions in the coming decades due to climate change, as the frequency and severity of extreme weather events rise. This study assesses the complex interrelations between external framework conditions such as climate change or adjustments in the agricultural price and subsidy schemes with farmers' decision-making. As social aspects remain understudied drivers for agricultural decisions, we also consider value-based characteristics of farmers as internal factors relevant for decision-making. We integrate individual learning as response to extreme weather events into an agent-based model that simulates farmers' decision-making. We applied the model to a region in Eastern Austria that already experiences water scarcity and increasing drought risk from climate change and simulated three future scenarios to compare the effects of changes in socio-economic and climatic conditions. In a cross-comparison, we then investigated how farmers can navigate these changes through individual adaptation. The agricultural trajectories project a decline of active farms between −27 and −37% accompanied by a reduction of agricultural area between −20 and −30% until 2053. The results show that regardless of the scenario conditions, adaptation through learning moderates the decline in the number of active farms and farmland compared to scenarios without adaptive learning. However, adaptation increases the workload of farmers. This highlights the need for labor support for farms. [ABSTRACT FROM AUTHOR]

We assess oil and agricultural price shocks in the financial markets of six EMEs (Brazil, Chile, Mexico, India, South Africa, and Turkey) using the GVAR. Positive oil price shocks provoke falls in all stock markets, devaluations in four domestic currencies, and tight monetary policies in two economies. The variance decomposition indicated that this shock is more influential in the stock markets, followed by the exchange rates. Compared to the oil price, shocks in agricultural prices caused appreciations in all domestic currencies. This shock is pervasive in all exchange markets in the first months, losing importance over time. The distinct responses to different commodities shocks point out that the kind of shock is relevant to comprehend its influence on EMEs. We detected relevant heterogeneities concerning the spreading of commodities shocks on domestic financial markets, especially in South Africa. [ABSTRACT FROM AUTHOR]

People’s daily life is significantly impacted by price changes in agricultural commodities. However, it is challenging to estimate the values of agricultural commodity futures due to the agricultural futures market’s complexity and the wide range of affecting variables. Predicting agricultural commodity prices correctly is crucial for avoiding market risk, raising agricultural revenue, and implementing macroeconomic government control. In order to provide a quick and accurate prediction system for agricultural output, this research proposes an unique method for predicting vegetable prices using neural networks. In this paper, several forms of data are considered on vegetable production, examined these data, and used Harris Hawks Optimization with Multi-layer Perceptron to forecast the future output of these vegetables. The present predictive model is evaluated with six performance metrics Precision, recall, f1-score, accuracy, MSE, MCC and kappa. [ABSTRACT FROM AUTHOR]

Agricultural producer service is an indispensable link in promoting agricultural modernization in developing countries, while agricultural pollution has become the largest source of pollution in many developing countries. Given that agricultural pollution is different from industrial pollution due to its endogenous characteristics, we linked agricultural pollution with the human capital level of labor and propose an endogenous model that reflects the agricultural pollution path, which is different from the traditional path. We studied the effects of government price subsidy, interest subsidy, and wage subsidy to agricultural producer service on agricultural pollution and other economic indicators by constructing a three‐sector general equilibrium model including agricultural producer service. We found that the rise of price subsidy for the agricultural producer service and the wage subsidy of the agricultural producer service sector would increase the output of agricultural sector and reduce the output of agricultural producer service under certain conditions, but aggravate agricultural pollution; at the same time, the rise of interest subsidy of the agricultural producer service sector would decrease the output of the agricultural sector, enhance the output of agricultural producer service conditionally, and decrease agricultural pollution. Preconditions of the three subsidies to improve national welfare have been obtained. [ABSTRACT FROM AUTHOR]

This research aimed to identify knowledge of farmers with good agricultural practices in maize crop, Kafer El Zayat, El Santa and Kotor districts were selected from El Gharbia governorate, In the same way, one village were selected from each district: El Dalgamon from Kafer El Zayat district, Natay from El Santa district and Damat from Kotor district, The total numbers of maize farmers in the selected three villages were 1790 farmers. A systematic random sample of 10% was taken to reach 179 respondents. A questionnaire was used to collect data for this research through personal interviews A different of statistical tools were used to analysis of research data: mean, standard deviation, simple and multiple correlation coefficients, and regression analysis (step- wise), percentage and frequencies. The main findings of the research were as follows: 78,8% of respondents had moderate and low knowledge level with good agricultural practices in maize crop, There were four independents variables significantly affected the degree of knowledge of farmers with good agricultural practices in maize crop and together explain 55,3% from its total variation which were: leadership (40,9%), extension communication (7,4%), respondent education (4,4%) and regenerative (2,6%) The main sources of respondents with good agricultural practices in maize crop were: family and relatives, production supplies dealers and agricultural guide, The most important problems faced the respondents were: high prices of chemical fertilizers (95%), high prices of agricultural pesticides (94>4%) and insufficiency of the annual courses disbursed by agricultural society (89,9%). [ABSTRACT FROM AUTHOR]

Agriculture is a leading sector that provides capital accumulation to sustain the economic development processes of developing countries' economies. The low supply and demand elasticity of agricultural products cause fluctuations in agricultural product prices and producer income. Therefore, the first negative reflection of price instability that may arise from fluctuations is generally observed in farmers. Hence, policymakers intervene in the agricultural sector to reduce the instability in agricultural product prices and protect agricultural producers against these effects, as well as the capital accumulation needed for growth and development. Based on this background, this study analyzes the causality relationship between agricultural producer protection (PP) and the macroeconomic variables of Brazil, Indonesia, India, Türkiye, and South Africa, which are referred to as the Fragile Five countries, using the panel bootstrap panel causality test developed by Kónya (2006) with the data between 2000 and 2020. The study findings differ among the countries in the sample. It was determined that there are causality relationships between agricultural PP and economic growth, economic development and inflation variables in all countries involved in this study. Although it is difficult to generalize the main findings of the study to all countries in the sample, it can be concluded that economic growth, economic development and inflation, and agricultural PP variables interact with one another. The study also concludes that the protective and supportive measures for agriculture, a significant sector for the macroeconomic performance indicators of the country's economies, are too important to be neglected. [ABSTRACT FROM AUTHOR]

Anticipating and understanding fluctuations in the agri-food market is very important in order to implement policies that can assure fair prices and food availability. In this paper, we contribute to the understanding of this market by exploring its efficiency and whether the local Hurst exponent can help to anticipate its trend or not. We have analyzed the time series of the price for different agri-commodities and classified each day into persistent, anti-persistent, or white-noise. Next, we have studied the probability and speed to mean reversion for several rolling windows. We found that in general mean reversion is more probable and occurs faster during anti-persistent periods. In contrast, for most of the rolling windows we could not find a significant effect of persistence in mean reversion. Hence, we conclude that the Hurst exponent can help to anticipate the future trend and range of the expected prices in this market. [ABSTRACT FROM AUTHOR]

Due to the increased imbalance between water supply and water demand since the 1980s, especially the increase in agricultural water usage, China has undergone four stages in reforming agricultural water price since 2006: initial stage, in-depth pilot stage, comprehensive promotion stage, and policy classification stage. The focus of policy has also shifted from so-called "extensive" to "intensive". From 2016 to 2020, over 28.7 million hectares of farmlands across the country have been reformed in the country. The comprehensive reform of agricultural water price is a systematic project, and this paper aims to explore a comprehensive, practical, and operational initial water rights accounting and distribution scheme for agriculture at county scale. The scheme can provide guidance for smooth implementation of the comprehensive reform of agricultural water price. We first provide a brief introduction to the current situation of the comprehensive reform of agricultural water price in China and then identify the key tasks in its implementation. An accounting method for the initial water rights of county agriculture is proposed based on the existing rigid constraint system of water resources. The initial agricultural water rights at the county level are allocated according to the priority-order of irrigation areas-beneficiary village groups-townships (and water users). Taking Huangchuan County as an example, the agricultural water rights of all irrigation areas in the county are allocated to the beneficiary villages and their subordinate towns. Completion of initial agricultural water right allocation in the county area is a priority as it not only helps to understand the base and reform process of the comprehensive reform of agricultural water price, but also facilitates follow-up reform work, such as the water-saving incentive mechanism. Our results can provide reference for comprehensive reform of agricultural water price in similar counties and regions and offer experience samples for the applied research of agricultural water right systems. [ABSTRACT FROM AUTHOR]

Czech farm-land had enjoyed considerable growth in value from 2008 to 2019. This paper identifies the main determinants of agricultural land prices variations and how these variations are influenced by urbanization, lease payments, and subsidies. These three factors were thoroughly examined for the existence of a unit root using the Augmented Dickey Fuller Test. The long-run relationship between farm-land value and these elements was estimated using the co-integration approach, specifically the Johansen procedure. The estimation confirms the existence of this long-run relationship. Short-run fluctuation in agricultural land prices is explained using the Error Correction Model. As the most important variable in the short-run performance of Czech agricultural land prices, the authors identified the influence of urbanization. This information could be used to help regulators avoid potential agricultural land value instabilities and volatility in the market and hence would contribute to sustainable land use. [ABSTRACT FROM AUTHOR]

Scientific evidence suggests that agriculture will be adversely affected by climate change globally in the near future, with the countries and small islands of South Asia projected to be amongst the most vulnerable. This study uses the ORANI-G-SL, a single-country, static computable general equilibrium model to investigate the economic impacts of climate change-induced agricultural productivity changes on Sri Lanka, as a South Asian case study. In comparison with a baseline scenario, the results show reductions in the output of most agricultural crops will cause increased consumer prices for these agricultural commodities, with a consequential decline in overall household consumption within next few decades. The projected decline in crop production and increases in food prices will enhance the potential for food insecurity. Thus, climate change will negatively impact the overall GDP and most of the macro and microeconomic variables of the Sri Lankan economy. These results highlight the need for future scientific research on climate change adaptation strategies and the importance of developing policy responses to counter adverse effects on agriculture and food security. [ABSTRACT FROM AUTHOR]

In addition to industry, transport, and waste management, the agricultural sector is also a major emitter of CO2 emissions. This article focuses on CO2 equivalent emissions from soil in the context of mineral nitrogen fertiliser management. The methodology itself consists of several successive phases, the first of which is to determine basic statistical characteristics for all EU countries, primarily in terms of mineral nitrogen fertiliser consumption, but also in terms of the area of crops grown. EU countries with similar cropping patterns were selected for comparison so that the results could be compared. The results show that there are quite significant differences in CO2 equivalent emissions between countries under similar conditions. At the same time, the values of the marginal increment of CO2 emissions as a function of mineral nitrogen fertiliser consumption were calculated. On the basis of the results of the selected countries, an upper limit in terms of CO2 emissions per hectare of arable land was also determined, and recommendations were made from a national perspective. The emissions themselves can be seen as a negative production externality that is not accounted for in the market mechanism and can thus also distort the price of agricultural production. The methodology used in this paper can be used to set an upper limit on CO2 emissions from soil due to the use of mineral nitrogen fertilisers and can then be used as an indicator for regulating and defining future agricultural policy instruments within the EU, where the objective is to reduce the level of CO2 emissions. [ABSTRACT FROM AUTHOR]

The research aimed to identify the behavior of the respondents towards improving and maintaining agricultural lands by identifying the degree of knowledge, implementation and attitudes of the respondents towards the practices of improving and maintaining agricultural lands and the research included six processes of adding agricultural gypsum, surface plowing, plowing under the soil, precise leveling by laser, disinfection of field irrigators,And clearing and smoothing field drains. The data were collected during the months of July and August 2022 AD By using the personal interview questionnaire form The field research was conducted on a sample of farmers, amounting to 224 respondents who were chosen by the simple random method, at a rate of 10% of the community. To display the results, the frequency tables and percentages were used, the arithmetic mean and standard deviation were used to analyze them, and the simple correlation coefficient was used to find the relationship between the behavior of the respondents and the studied independent variables., Stepwise regression analysis was used to determine the percentage of the contribution of the independent variables to the dependent variabl. The most important results were: •The behavior of the respondents in relation to the practices of improving and maintaining agricultural lands was average. •The respondents' knowledge of the total practices of improving and maintaining agricultural lands was average. •The respondents' implementation of the practices of improving and maintaining agricultural lands was low. •The attitude of the respondents towards the practices of improving and maintaining agricultural lands is neutral. •Seven of the independent variables combined explain 61% of the total variance that explains the total degrees of the behavior of the surveyed farmers related to the practices of improving and maintaining agricultural lands. For the soil in the region, high prices of agricultural gypsum, lack of availability of agricultural gypsum, high costs of accurate leveling of agricultural land with laser, high costs of plowing under the soil, high costs of disinfection operations for canals and drains, and lack of accurate laser leveling machines. [ABSTRACT FROM AUTHOR]

Contextualization: Nariño is the main pea-producing department in Colombia, with a predominance of family farming subsystems in farming activities, besides pea agriculture, such as potato cultivation, livestock, and small livestock breeding. Knowledge gap: Despite its importance, evidence of comprehensive studies that analyze the behavior of supply, demand and prices of pea market is scarce, limiting the design of sustainable development policies that consider the different socioeconomic contexts. Methodology: Based on this fact, a documentary research and statistical analysis of an inductive type was carried out. In the case of supply and demand of pea in the main marketplaces, central tendency, dispersion and network analysis were carried out; and finally, an ARIMA (1,0,1) model was constructed with the real price series. Results and conclusion: The results revealed a 91% concentration of production in regions such as Nariño, Cundinamarca, Boyaca, Antioquia, Huila, and Norte de Santander. Production in Nariño mainly supplies the "Corabastos" and Ipiales "Somos Todos" marketplaces, with a total average of 48679 t. The real price during 2009 to 2021 has shown a growth rate of 2,53%; however, projections for the first half of 2022 indicate a decrease of 3,89%. In this sense, studies of this type are crucial for defining rural development policies and making assertive decisions that will make markets more dynamic, ensuring the equitable participation of the entire region. [ABSTRACT FROM AUTHOR]

One of the controversial issues in the trade negotiations carried out with the World Trade Organization deals with agricultural supports related to production, which is claimed to disrupt the market system by creating an imbalance in supply and demand in the domestic market and to cause world trade contraction. In this context, the aim of this study is to examine the production effect of the deficiency payments and land-based direct supports widely used in Turkey. The study conducts a panel autoregressive distributed lag analysis for 11 selected agricultural products (wheat, corn, sunflower, seed cotton, paddy, soybean, canola, safflower, tea, dried beans, and olives) for the 2002-2019 period. The findings from the study are as follows: i) Increases in deficiency payments and land-based direct supports increase short and long run production. However, land-based direct supports have less of an effect on production. ii) While increases in input prices have a negative short run effect on production, the long run effect is the opposite. iii) Agricultural product price is not an important indicator for producers. This finding can be explained by the fact that farmers accept agricultural supports as a complement to the price variable in their production decisions. iv) Increases in the minimum wage added to the model based on Turkey's structural characteristics have a negative long run impact on production. v) No statistically significant relationship exists between the number of tractors used to represent agricultural mechanization and the amount of production. [ABSTRACT FROM AUTHOR]

Rice farming is one of the main sources of income in many rural areas in the Philippines. The purpose of this study is to model the different constraints that influence the level of rice farmers' income in Albuera, Leyte, Philippines. Survey data from an available sample of participants were gathered through a face-to-face interview consisting of the rice farmers' income and its determining constraints. Some descriptive measures were calculated to summarize the gathered variables and ordinary least square (OLS) regression analysis was employed to predict the significant constraints of farmers' monthly income. Results revealed that the rice farmers' monthly income is below the poverty line as the Philippine poverty threshold is concerned, that is, rice farmers in rural areas are considered "poor". The farmers have said that their rice production and income level are "affected" by the following constraints: "high prices of agricultural inputs", "inadequate capital", and "pest and diseases". Additionally, their rice production and income are moderately affected by "lack of credit facilities", "lack of technical services", and "weeds". Moreover, the two constructed statistical models showed that the following constraints are significant factors affecting the income level of rice farmers: "high prices of agricultural inputs", "lack of credit facilities", "high cost of transportation", "low educational attainment", and "land rent". Conclusively, farmers are in need of assistance from the local government concerning access to credit for capital, adoption of new technologies in farming, and other facilities that might improve their production. Furthermore, farmers must undergo some seminars and training to strengthen their knowledge of rice farming and improve their practices to increase their level of production, well-being, and monthly income. [ABSTRACT FROM AUTHOR]

Objective: To establish if the price of the main products of the Mexican agricultural sector is cointegrated with the production of the main producing states in five agricultural regions of Mexico. Design/Methodology/Approach: Thirty cointegration tests were carried out to determine if the prices of the main agricultural products in Mexico (corn kernel, sorghum kernel, and beans) influence the production of the main producing states in the five agricultural regions of Mexico. Results: In the northwestern region, the price does not influence the production of the main producing states of corn kernel, sorghum kernel, and beans. In the northeastern, central-western, and central regions, the price does influence the production of the main producing states of the said produce; meanwhile, in most of the states in the southern-southeastern region, the price does not affect the production of the main producing states. Study Limitations/Implications: The analysis did not include all states and their main products. Findings/Conclusions: The price influences production, but its influence is not even in the five regions of Mexico or in the main producing states of corn kernel, sorghum kernel, and beans. [ABSTRACT FROM AUTHOR]

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The demographic and economic growth in the northern region of the Mexican state of Baja California has led to increased water use and competition for this resource among diverse consumer sectors. The regional dynamism has made it increasingly difficult to meet the demand for water provision. The aim of this investigation was to allocate the water withdrawn from the Mexicali Valley and San Luis Río Colorado (SLRC) aquifers in a scenario of water scarcity among the various consumer sectors by municipality of the states of Baja California and Sonora, as well as to determine the price that would allow for a reduction in the amount of water taken from the aquifers. A spatial equilibrium model was formulated and validated, considering fixed supply and functions of demand. The 2019 results show that the total demand for water from municipalities in residential, commercial, industrial, agricultural and livestock sectors were 197.2, 21.7, 16.7, 758 and 5.7 hm³, with Tijuana standing out in the first three sectors, whereas Mexicali and SLRC were highlighted in the farming sector. Regarding the water price, the Tijuana, Tecate, and Ensenada municipalities pay a high tariff for its use, whereas Mexicali and SLRC pay the lowest tariffs. A 10 % reduction in water availability would be achieved if the price in the agricultural sector in Mexicali and SLRC increased by 20 and 22 %, respectively, over the base price. As the price rises, the demand in this sector for both municipalities would decrease by 2.6 %. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between oil, gold and steel prices observed over a period of ten years with the aim of presenting their situation and trends using statistical methods and time series over a longer period of time and their impact on agricultural development. The high share of agriculture in the basic macroeconomic aggregates of the Republic of Serbia conditions that agriculture has a significant role in the foreign trade of the Republic of Serbia, especially in exports. The negative trend of rising fuel prices per farmer reduces the average fuel consumption per hectare. Also, the growth of the price of steel is conditioned by the growth of the prices of agricultural machinery. [ABSTRACT FROM AUTHOR]

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Aim/Purpose This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendations for Researchers Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the dataset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India. [ABSTRACT FROM AUTHOR]

The article examines the types of risks and negative impacts posed by the Covid- 19 pandemic for the agricultural sector. It is determined that the main risks are: economic, environmental, social, informational, political, technological. It is investigated that investments in agriculture have their differences. They are primarily manifested in human performance, as in other sectors of the economy, in agriculture, they are also reflected in the natural potential, which under different conditions makes their operation more capital-intensive with long-term profits. It is estimated that over the last year, capital investment in the agricultural sector has fallen significantly, primarily due to restrictions imposed by the country’s leadership in 2020 and the stagnation of the entire industry. State regulation of the investment process in agriculture and other branches of the agro-industrial complex is carried out through state programs to support prices for agricultural products and income, the organization of state control and the system of national standards. High investment attractiveness of the industry is a key factor in increasing its competitiveness, ensuring high and sustainable economic growth, thanks to the transparent mechanism of investment in agriculture, it has a chance to start sustainable development, leading to innovation, which in turn provides transformation. in the modernization of technical, technological, and organizational base of agricultural production. The list of programs of state support of agricultural producers and the amount of funding is presented. It is highlighted that at the current stage of sustainable development of agriculture in the European Union, potential risks and threats include the following key factors: climate change and environmental change; reducing the diversity of the biosphere; high rates of population growth in European countries and growing demand for food; reducing the efficiency of agribusiness due to unforeseen factors (epidemics, socio-economic conflicts, etc.). The priority directions of the state institutional support of the investment climate in the agricultural sector in the near future are presented. It is determined that the main guidelines for domestic agricultural producers should be the programs that are currently of most interest to European investors. [ABSTRACT FROM AUTHOR]