scholarly journals Consumption smoothing and price enhancement motives for grain storage: empirical perspectives from rural Ethiopia

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Wondimagegn Tesfaye ◽  
Gebrelibanos Gebremariam
Keyword(s):  
Panel Data ◽  
Climatic Factors ◽  
Consumption Smoothing ◽  
Technological Innovations ◽  
Grain Storage ◽  
Rural Ethiopia ◽  
Subsistence Economies ◽  
Storage Behavior ◽  
Economic Motives

Abstract Consumption smoothing and temporal price arbitrage are the two main economic motives for grain storage in semi-subsistence economies. Nonetheless, little has been documented on the determinants of households’ grain storage behavior. Using a rich panel data from maize producing households in Ethiopia, this paper investigates the determinants of households’ decision to store grain for consumption and/or for the market. We found that grain storage is mainly determined by climatic factors, technological innovations, and shocks. Grain storage for consumption and for the markets are not mutually exclusive decisions. While the decisions made by the households to store maize for consumption and for the markets are influenced by a host of similar factors, the effects of climatic factors and infrastructure are found to be heterogeneous.

Determinants of non-farm enterprise diversification in rural Ethiopia

2020 ◽  
Vol 14 (4) ◽  
pp. 495-513
Author(s):  
Precious Makhosazana Tshabalala ◽  
Shaufique Fahmi Sidique
Keyword(s):  
Panel Data ◽  
Empirical Evidence ◽  
Household Head ◽  
Household Size ◽  
Small Scale ◽  
Content Type ◽  
Access To Credit ◽  
Rural Ethiopia ◽  
Single Region ◽  
Region Data

Purpose This study aims to analyze the factors that determine non-farm enterprise diversification among farm households in Ethiopia. It extends the analysis by examining enterprises and using pooled data, which has the capacity to generate more accurate outcomes. The existing empirical evidence has focused on all non-farm activities, based on single period, single region data. Much of the existing empirical evidence is based on small-scale and location-specific sample surveys that do not demonstrate the characteristics of aggregate populations. Design/methodology/approach The empirical analysis was conducted using a quantitative method. To cater to the censoring nature of participating in non-farm enterprise activities, a panel data double-hurdle model is used to a representative sample of 3,594 Ethiopian rural households. Findings The study finds that the age of household head, household size, distance to the market, social capital and access to credit, are determinants for owning one or more non-farm enterprises. The level of income from these enterprises is then determined by the age and education level of the household head, household size, agricultural equipment, distance to markets and access to credit. Practical implications This study brings to light factors that influence households to participate in non-farm enterprises and the determining factors for the income level. Originality/value Non-farm activities are an important source of household income and a driver of development. This paper provides empirical evidence on factors that determine enterprise ownership using panel data.

scholarly journals Targeting the Vulnerable and the Choice of Vulnerability Measures: Review and Application to Pakistan

2010 ◽  
Vol 49 (2) ◽  
pp. 87-103 ◽  
Author(s):  
Takashi Kurosaki
Keyword(s):  
Panel Data ◽  
Poverty Reduction ◽  
Jel Classification ◽  
Consumption Smoothing ◽  
Data Set ◽  
Empirical Results ◽  
Poverty Risk ◽  
Rural Pakistan ◽  
Vulnerable Households

In this paper, the concept of vulnerability of the poor’s welfare and its practical measures are scrutinised in order to derive implications for targeting poverty reduction policies toward vulnerable households. As illustration, various measures of vulnerability proposed in the literature are applied to a panel data-set collected from rural Pakistan. The empirical results show that different vulnerability rankings can be obtained depending on the choice of the measure. By utilising these measures, we can identify who and which region is more vulnerable to a particular type of risk. This kind of information is useful in targeting poverty reduction policies. Since the nature of vulnerability is diverse, it is advisable to use the whole vector of various vulnerability measures. JEL classification: I32, I38. Keywords: Vulnerability, Poverty, Risk, Consumption Smoothing, Pakistan.

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