Factors Affecting Rural Households’ Resilience to Food Insecurity in Niger

Access to finance to the rural households is a powerful intervention to facilitate the adoption of farm inputs and boost agricultural productivity in developing countries like Ethiopia. Credit constraints limit the ability of households to use inputs at optimal level and thereby stifles agricultural productivity. However, evaluation of the impact of credit constraints on agricultural technology adoption and productivity have faced methodological problems and most of the existing studies have failed to explicitly measure and analyze the amount of productivity loss and the magnitude increase in intensity of fertilizer adoption if the farm households are found credit unconstrained. This study has examined the possible effect of credit constraint on the intensity of fertilizer adoption and productivity among households who vary in their credit constraint status. The study used cross sectional farm household level data collected in 2013 from 1165 randomly sampled households. An endogenous switching regression model is used for analytical purpose so as to account for selection bias and heterogeneity problem. The result evidence that intensity of fertilizer adoption and agriculture productivity would be higher among farm households who are found to be credit unconstrained. The result revealed that factors that affect the intensity of fertilizer adoption and agriculture productivity among credit constrained farm households are different from their counterparts. Age and age square of the household head, primary cooperative membership, number of Oxen, ownership of TV, hired labor as dummy and use of manure have significant effect on the intensity of fertilizer adoption among credit unconstrained regimes. Whereas, household size, altitude of land, ownership of land, way of land cultivation, and being risk averse household have significant effect on the intensity of fertilizer adoption in the credit constrained regimes. The result shown that size of land has negative and significant effect on the intensity of fertilizer adoption in the constrained regime while it has positive and significant effect on the intensity of adoption in the unconstrained regime. Age and age square of the household head, TLU, hired labor as dummy are the factors that significantly affect the productivity in the unconstrained regimes. The number of oxen and distance of farm land from residence also affect the productivity. Land size has found the significant and negative effect on the productivity in the constrained regime, but it has the positive and significant effect in the credit constrained regime. The policy implication is that the policy makers should account the credit constraint heterogeneity among farm households when they design agricultural policy to increase intensity of fertilizer adoption and thereby boost productivity of agriculture.

The effects of climate change and groundwater salinity on farmers’ income risk

Reducing agricultural loss and food waste: how will nature fare?

The objective of this study was to evaluate the effect of food supply in garbage dumps on the reproductive fitness of Cattle Egret Bubulcus ibis and offspring losses. A total of 236 nests were monitored during two distinct periods of 2 years for each: 146 nests during a period without food supply in dumps (1998–1999) and 90 with food supply in dumps (2007–2008). The study was carried out in the colony of El-Kseur in the Lower Soummam Valley (northeast Algeria). For the entire study period, the mean of clutch size, average number of hatched chicks, productivity, and breeding success varied significantly between years (Kruskal–Wallis test: p < .05). Also, the average calculated losses for eggs, chicks, and total offspring vary significantly (Chi2 test: p > .0001). The clutch size and the number of hatched chicks per nest were highest during the period with food supply in garbage dump (respectively: 3.46 ± 0.86; 2.85 ± 1.11), compared to the period when cattle egrets feed in natural or agricultural habitats (3.04 ± 0.87; 2.54 ± 1.03). However, productivity and breeding success were highest during the period without food supply (respectively: 2.11 ± 1.16 fledging’s/nest; 0.70 ± 0.35) than in the period with food supply (1.14 ± 0.91; 0.35 ± 0.30). While egg losses were substantially similar between the two study periods, chick’s mortality (59.9%) and total offspring losses (36.7%) were higher during the period with food supply. The generalized linear mixed model (GLMM) analysis indicated a large negative effect of food supply in dumps on the productivity, on the chick’s losses; and a positive effect on the total offspring losses ( p < .001). Also, feed in dump garbage revealed a significant negative effect on the breeding success linear mixed model (LMM, p = .01). However, no significant effects (GLMM, p > .05) of food supply in dumps were noted on average clutch size, the mean number of hatched chicks per nest, and egg losses.

The major objective of this study is to analyze rural households’ capability to absorb the negative consequences of unexpected shocks using seven resilience blocs based on the framework of resilience analysis. Resilience index was defined as a function of agricultural inputs and technology, social safety nets, access to public services, access to food and income, access to assets, stability and adaptive capacity. The estimation of each bloc was made separately using different multivariate techniques, where the result becomes covariates in the measurement of resilience index. The estimation of resilience index was done using factor analysis and three factors were retained. Under the first factor, all blocs, except access to public services, are positively correlated with resilience. The negative correlation between access to public services and resilience is because observed variables like health services and education qualities decreases as households become poorer. In terms of importance to rural household’s resilience index, the result indicates that asset ownership play significant role followed by access to food and income, as well as social safety nets. These resilience blocs show the likelihood of recovering from any form of climatic shocks that a household experiences. In the second factor, access to public services becomes positive, which shows that it is a positive characteristic of resilience. Adaptive capacity is positive in the first factor and negative in the second factor. The third factor triggers hidden information of the resilience bloc as stability and adaptive capacity are positive, which likely tells common story in terms of food security situations. In conclusion, poor households have limited or no access to physical and financial assets, little education, and often suffer from human illness and livestock diseases/death. Poor households lack access to sufficient, high-quality land and other natural resources or to remunerative resources of income and agricultural production boosting activities. Therefore, it is recommended that households should have supplements with preconditions and options available to them in terms of capabilities and activities such as agricultural production boosting and income-generating activities, access to assets, improving the quality of public services, social safety nets and adaptive capacity.

Rice production in Nigeria is vulnerable to climate risks and rice farmers over time have experienced the risks and their respective impacts on rice farming. Rice farmers have also responded to perceived climate risks with strategies believed to be climate-smart. Farmers’ perception of climate risks is an important first step of determining any action to be taken to counteract the negative effects of climate change on agriculture. Studies on the link between perceived climate risks and farmers’ response strategies are increasing. However, there are limited studies on the determinants of rice farmers’ perception of climate events. The paper therefore examined climate change perception and uptake of climate-smart agriculture in rice production in Ebonyi State, Nigeria using cross-sectional data from 347 rice farmers in an important rice-producing area in Nigeria. Principal component analysis, multivariate probit regression model and descriptive statistics were adopted for data analysis. Perceived climate events include increased rainfall intensity, prolonged dry seasons, frequent floods, rising temperature, severe windstorms, unpredictable rainfall pattern and distribution, late onset rain, and early cessation of rain. Farmers’ socioeconomic, farm and institutional characteristics influenced their perception of climate change. Additionally, rice farmers used a variety of climate-smart practices and technologies to respond to the perceived climate events. Such climate-smart practices include planting improved rice varieties, insurance, planting different crops, livelihood diversification, soil and water conservation techniques, adjusting planting and harvesting dates, irrigation, reliance on climate information and forecasts, planting on the nursery, appropriate application of fertilizer and efficient and effective use of pesticides. These climate-smart agricultural measures were further delineated into five broad packages using principal component analysis. These packages include crop and land management practices, climate-based services and irrigation, livelihood diversification and soil fertility management, efficient and effective use of pesticide and planting on the nursery. High fertilizer costs, lack of access to inputs, insufficient land, insufficient capital, pests and diseases, floods, scorching sun, high labour cost, insufficient climate information, and poor extension services were the barriers to uptake of climate-smart agriculture in rice production. Rice farmers should be supported to implement climate-smart agriculture in rice production in order to achieve the objectives of increased rice productivity and income, food security, climate resilience and mitigation.

Aim: Agriculture entails majorly crop and animal production. Crop and Livestock production provide the major human caloric and nutrition intake. Assessing the impact of climate change on crop and livestock productivity, is therefore critical to maintaining food supply in the world and particularly in Nigeria. Different studies have yielded different results in other parts of the world, it is therefore, very important to examine the linkage between climate change and agricultural productivity in Nigeria.
 Study Design: The study utilized secondary data. The study utilize climate data from Nigerian Meteorology Station and Carbon emission, Crop and Livestock production data from FOASTAT.
 Place and Duration of Study: The study was carried in Nigeria and it covers the period between 1970-2016.
 Methodology: The data were used to estimate the empirical models. Data were analyzed using descriptive statistics, trend analysis, stationarity, Co-integration and Fully-Modified Least Squares regression.
 Results: The result of the research reveals that there is variation in the trend of the climatic factors examined and also variation in crop and livestock production over the period covered by the study in Nigeria. The finding also shows that rainfall, temperature and Carbon emission are the climatic factors that significantly affect crop and livestock production in Nigeria. Long term adverse impact of climate change on crop and livestock production index indicates threat to food availability to the country.
 Conclusion: The study concluded that climatic variables have significant effect on agricultural productivity in Nigeria. The study recommended the need to put in place measures that will reduce the negative effects of climate on agricultural production.

PurposeThe development of digital inclusive finance appears to be able to solve the difficulty of traditional finance, which cannot completely cover agriculture and farmers and provides better financial services and products to Chinese farmers. Thus, it improves the farmers' enthusiasm for agricultural production. The purpose of this paper is to clarify whether this goal is indeed being achieved.Design/methodology/approachThis paper theoretically analyzes the mechanism that influences the effect of digital inclusive finance on rural households' agricultural production decisions and conducts an empirical study based on a sample from the Chinese family database (CFD).FindingsFirst, the development of digital financial inclusion in general can encourage rural households to reduce agricultural production. Second, the negative effect of digital inclusive finance on households' agricultural output is realized by widening the gap between the efficiency of non-agricultural economic activities and the efficiency of agricultural production. The wider the gap is, the lower the enthusiasm of households for agricultural production. Third, the mediating effect of “digital financial inclusion – difference in efficiency – agricultural output” has a significant negative effect on households with low agricultural production efficiency, but not households with high agricultural production efficiency. Digital inclusive finance has no significant effect on the difference in efficiency between the two economic activities of high-efficiency households, but a greater difference in efficiency between the two economic activities corresponds to higher enthusiasm of households for agricultural production.Originality/valueTo the best of our knowledge, this paper is the first to analyze the impact of digital financial inclusion on Chinese farmers' agricultural production. The findings of this study can provide policy-related insights to help local governments promote the development of digital finance in China's agricultural economy.

Agricultural Credits and Agricultural Productivity: Cross-Country Evidence

Total factor productivity (TFP) analysis has been the focus of a large number of methodological and empirical studies over the past several decades. One remarkable gap in this literature is the omission of climatic variables as regressors in the models used to derive TFP measures. The purpose of this paper is to narrow this gap by developing climate-adjusted (CA) TFP measures. We combine information from the Climatic Research Unit with Food and Agriculture Organization data for 28 Latin American and Caribbean countries over a 52-year period (1961–2012) to estimate random parameter stochastic production frontier (SPF) models. The goal is to investigate the impact of climatic variability on TFP. The estimated coefficients from the SPF models are used to construct a climatic effects index across countries and over time. The average annual variation in climatic conditions is stronger at the end of the 2000s compared to earlier periods. Climatic variability has a negative effect on production in 20 of the 28 LAC countries analyzed, and this is more severe over Central America and the Caribbean. The average reduction in output across the region attributable to climatic variables is between 0.02 and 22.7% over the last decade compared to the period 1961–1999. The estimated average annual growth rate of CATFP (0.69%) is consistently lower than TFP (1.08%), confirming the adverse impact of climatic variability on agricultural output and productivity in LAC. The results show considerable variability across countries, and this points to the importance of accounting for climatic effects in analyzing TFP.

Nepal is one of the least developed countries in the world, with more than 80% of the population engaged in agricultural production and more than two-fifths of the population still living below the poverty line. Ensuring food security has always been a key national policy in Nepal. Using a nutrient conversion model and an improved resource carrying capacity model as well as statistical data and household questionnaires, an analysis framework for food supply balance is developed in this study, which quantitatively analyzes the balance of food supply and demand in Nepal from the perspectives of food and calories during the period 2000-2020. Nepal's agricultural production and consumption have increased significantly, and the diet has been relatively stable over the past two decades. The diet structure is stable and homogeneous, with plant products occupying the absolute position in overall dietary consumption. The supply of food and calories varies widely from region to region. Although the increasing supply level at the national scale can meet the needs of the current population, the food self-sufficiency level cannot meet the needs of the local population development at the county level due to the influence of population, geographical location, and land resources. We found that the agricultural environment in Nepal is fragile. The government can improve agricultural production capacity by adjusting the agricultural structure, improving the efficiency of agricultural resources, improving the cross-regional flow of agricultural products, and improving international food trade channels. The food supply and demand balance framework provided a reference for achieving balance between the supply and demand of food and calories in a resource-carrying land and provides a scientific basis for Nepal to achieve zero hunger under the framework of the Sustainable Development Goals. Furthermore, development of policies in order to increase agricultural productivity will be critical for improving food security in agricultural countries such as Nepal.

Research questions: Are there any benefits from increasing nonfarm employment on expenditures of agricultural production? Is there any impact of nonfarm employment on family labour use in agricultural production? and Is there any gain in the technical efficiency of production through nonfarm employment participation? Evidence from the rural livelihood literature shows that rural farm households engage in nonfarm employment to supplement their household income in developing countries. Therefore, it raises the question of whether nonfarm employment complements or competes with agricultural production due to a possible shift in farm household labour to nonfarm employment. The consequences of participation in nonfarm employment on agricultural production could be two-fold. On the one hand, the increased cash earnings from nonfarm employment could be used to purchase agricultural inputs to intensify production. On the other hand, agricultural production might be negatively affected due to a shortage of labour. Lately, the agriculture sector in Bangladesh is experiencing this scenario due to a high demand for labour during crop planting and harvesting periods. Therefore, the direction of the impact of nonfarm employment on agricultural production needs to be investigated, especially in an agricultural dependent country like Bangladesh. Moreover, the research in this area still inconclusive based on the mixed findings in different countries. Surprisingly, there is no study appears regarding the impact of nonfarm employment on agricultural production in Bangladesh. The Bangladesh Integrated Household Survey (BIHS) data 2015, collected by the International Food Policy Research Institute (IFPRI) has been used in this study. To overcome the endogeneity issues of nonfarm income and censored nature of agricultural input expenditures, IV Tobit model is used to identify the effects of nonfarm employment on the expenditures of major agricultural inputs. In addition, treatment effect models (Nearest Neighbour Matching, Propensity Score Matching, and Inverse Probability Weighted Regression Adjustment) have been used to check the robustness of the findings obtained by the IV Tobit estimation. IV 2SLS estimation is also used to identify the effects of nonfarm employment on the use of family labour in agricultural production. Finally, the impact of nonfarm employment on the technical efficiency of production is investigated using the Stochastic Frontier Production model. The results show that nonfarm income has a positive impact on the total crop expenditure as well as expenditures on major purchased agricultural inputs (equipment, seed, fertilizer, purchased labour). Also, the robustness checks confirm the findings obtained by IV Tobit model. The findings also show that an increase in nonfarm income is negatively associated with the use of male family labour in crop production. Moreover, the technical inefficiency in agricultural production decreases when nonfarm income increases. Overall, the findings of this study suggest that nonfarm employment exerts an income effect on agricultural production by reducing the liquidity constraint and intensifying major purchased inputs. Thus, introducing policies that would increase rural nonfarm employment opportunities to rural households complements agricultural production and that could be a means to increase food production, ultimately leading to food availability as well as food security.

Resilience capacity among the vulnerable farming households in Meki River catchment, Central Rift Valley of Ethiopia: Present situation and future prospects

The aim: quantitatively evaluate the response of climate change upon the sustainability of the agricultural production. The method: the paper selected two regions (Hubei and shan’xi province) which represented different climate environment, utilized modern statistic data, Principal Component Analysis and multivariate linear regression to quantitatively evaluate the influence of climate change upon agricultural production through isolating climate environment from arable area, land utilization and management and landform and so on. The conclusion: The study indicated that when environmental condition turned good to agriculture, the function of environmental condition to agriculture relatively decreased; the capability of agricultural society and production decreased too, and people could select the land to cultivate, where agricultural productivity is higher. And that when environmental condition turned bad to agriculture, the function of environmental condition to agriculture relatively increased; the capability of agricultural society and production increased, too; people could not put emphasis on the land where agricultural productivity is higher, whereas focused on productivity per capita.

This study focuses on analysis (1) money supply effect, previous period money supply, the level of SBI (Bank Indonesia Certificate), the exchange rate, and the economy on inflation in Indonesia (2) The effect of inflation, domestic investment, previous period domestic investment, foreign investment, previous period foreign investment, and economic labor in Indonesia. Time series data using the simultaneous analysis model equation of the Two-Stage Least Squared (TSLS) method. The results of the study concluded that (1) the money supply had a significant and positive impact on inflation, the money supply in the previous period had a significant and positive impact on inflation, the SBI rate had a significant and negative effect on inflation, the exchange rate had a significant and positive effect on inflation. Meanwhile, the national economy has no significant and positive effect on inflation. If the money supply increases, inflation will increase. If the money supply in the previous period increased, inflation would also increase. If the SBI interest rate rises, inflation will depreciate. If the exchange rate rises, inflation will appreciate. If the level of the national economy rises, inflation will appreciate. (2) Domestic investment, previous period domestic investment, foreign investment, previous period foreign investment, and labor have a significant effect on the economy in Indonesia, while the inflation rate has no significant effect on the economy in Indonesia