Combating poverty through the development of agricultural production and providing rural people with new employment and income opportunities in agriculture has become one of the major concerns of both policymakers and scholars worldwide. In many developing countries, government policies have failed to achieve the desired poverty alleviation goals due to the lack of financial resources. Despite that, few comprehensive studies have so far unambiguously identified the effects of the exogenous factor of capital inflows on the level of poverty and agriculture development. In this paper, the authors attempt to shed light on the poverty–agriculture–capital trilemma pattern by revealing the impacts of six types of foreign capital inflows on the parameters of poverty reduction and agriculture development. The panel unit root test and pool mean group estimation techniques were employed for observing the short-term and long-term linkages between dependent and explanatory variables across fourteen developing economies of Latin America, Asia, and Eastern Europe. It was revealed that poverty reduction could be positively affected by an increase in the values of agricultural exports, foreign direct investment, foreign development assistance, and remittances received from migrant workers. The level of agriculture could be improved by deeper integration of developing economies to global food supply chains as either suppliers or consumers of food and agricultural products.
Over the past decades, both the quantity and quality of food supply for millions of people have improved substantially in the course of economic growth across the developing world. However, the number of undernourished people has resumed growth in the 2010s amid food supply disruptions, economic slowdowns, and protectionist restrictions to agricultural trade. Having been common to most nations, these challenges to the food security status of the population still vary depending on the level of economic development and national income of individual countries. In order to explore the long-run determinants of food supply transformations, this study employs five-stage multiple regression analysis to identify the strengths and directions of effects of agricultural production parameters, income level, price indices, food trade, and currency exchange on supply of calories, proteins, and fats across 11 groups of agricultural products in 1980–2018. To address the diversity of effects across developing nations, the study includes 99 countries of Asia, Europe, Latin America, the Middle East, and Africa categorized as low-income, lower-middle-income, and upper-middle-income economies. It is found that in low-income countries, food supply parameters are more strongly affected by production factors compared to economic and trade variables. The effect of economic factors on the food supply of higher-value food products, such as meat and dairy products, fruit, and vegetables, increases with the rise in the level of income, but it stays marginal for staples in all three groups of countries. The influence of trade factors on food supply is stronger compared to production and economic parameters in import-dependent economies irrelevant of the gross national income per capita. The approach presented in this paper contributes to the research on how food supply patterns and their determinants evolve in the course of economic transformations in low-income countries.
For a long time, the majority of China, which has the world's largest population, has been immobile and lived in rural areas. However, over recent decades, with the economic rise of China, rural labor has demonstrated a trend of moving to rapidly industrializing regions in search of higher income and better employment opportunities. Along with the labor cutback, out-migration introduces negatives to the sustainable development of rural areas, i.e., depopulation, the abandonment of rural settlements and agricultural lands, and the aging of the population, among others. Due to the threats of labor outflow to sustainability, studying the causes of China's rural out-migration can reveal lessons on how state policies can be designed to reduce the negative impacts of out-migration on rural communities. The purpose of this paper is to identify the major causes of migration movements among the rural areas of northern China that are considered to be the best-performing among the provinces of the country in terms of rural development, agricultural production, and the wealth of rural dwellers. A two-stage survey of a panel of experts involved: (1) respondents representing government officials and universities of the Heilongjiang, Jilin, and Liaoning provinces and the Inner Mongolia Autonomous Region, and (2) regional and district levels of administration, and research and public establishments of Heilongjiang Province. In stage three, drawing on the authors' own survey of 128 rural households in three counties of Heilongjiang Province, the major migration drivers have been identified, and the portfolio of a typical rural migrant has been developed. Some of the key findings are that migration intentions are fueled by the rural-urban income gap, poverty, a reduction of demand for labor in rural areas, underdeveloped infrastructure, the low quality of social services in rural settlements, and the low social standing of rural dwellers. The approach allows monitoring the dynamics of migration attitudes as responses to the policy interventions that are aimed at the sustainable development of rural areas.
The contemporary relevance of ensuring sustainable rural development is stipulated, on the one hand, by the growing economic and social backwardness of rural territories, and on the other hand by their ultimate importance for the nation in such issues as food security, preservation of soil and environmental resources, and the utilisation of agricultural, production and labour potentials. One of the key conditions of sustainable rural development is sufficient employment which provides rural inhabitants with a sustainable income which is competitive in comparison to urban territories. This paper includes an analysis of the current problems of rural development, based on the example of the Stavropol Region, one of the most agricultural regions of Russia; the paper addresses threats to sustainable rural development such as unemployment and depopulation, and substantiates the practicality of diversification of traditional rural sources of income by means of tourism and other alternative activities.
Th e paper aims at the overview of the main approaches of state support implemented by developed and developing countries and the assessment of their distorting infl uences on the trade with agricultural commodities. Th e current state of state support is analyzed on the examples of EU-27, the USA and Japan. Th e experiences of developing countries are summarized on the examples of China, Russia and the CIS countries. State support tools are grouped according to the WTO classifi cation. Th e alternative classifi cation is implemented in order to compare the distorting eff ects caused by the state support. Th e EPACIS model is implemented to analyze the eff ects of trade liberalization for the distribution of agricultural commodities and trade policies in developing countries. Th e model is adjusted in order to assess the eff ects of state support for the production and trade with agricultural commodities in developing countries, recently accessed the WTO (the case of Russia). Imitation calculations allow formulating policies for the developing agricultural markets depending on the degrees of their sensitivity to foreign trade regulations and domestic support.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.