The strategic value of crop diversification in Zambia

Doctor of PhilosophyDepartment of Agricultural EconomicsVincent Amanor-BoaduThis study examines the profitability of crop diversification in Sub-Saharan Africa. Crop diversification means growing different crops or using different cropping systems. It has been shown to provide risk management advantages and to lead to cost reduction in the presence of scope economies. Some countries and economic development organizations are, therefore, promoting crop diversification. However, crop diversification has been shown to be associated with a reduction in productivity and profitability due to foregone efficiency benefits from economies of scale. As a result, some countries, such as Rwanda, have adopted crop specialization policies. In examining the effects of crop diversification on farm performance, previous research has employed various indices to quantify diversification. These indices are based on the number of crops grown and their relative abundance. Although the indices provide a good aggregate measure of diversification, they also assume homogeneity in diversification strategies among farmers who have the same number and relative abundance of crops even though the crops grown may be different. Using indices, therefore, ignores differences in economies of scope among heterogeneous or homogeneous crop combinations and their related profitability. It would seem that prior research has not explored the issue of crop diversification adequately because of crop diversification’s definitional constraints. Against this backdrop, the research problem that this study seeks to address is premised on the fact that different crop combinations may be associated with different performance outcomes. Therefore, this study recognizes diversification not in number of crops, but the types of crops in a farmer’s production ‘portfolio’. We call these portfolios farm enterprise structures. An enterprise structure is a combination of unique crop enterprises that make up the farm. The specific research question that the study addresses is: To what extent do enterprise structures influence profitability? The main objective of the study is to identify combinations of enterprise structures and their related profitability. Differences in enterprise structure profitability could improve our understanding of existing cropping patterns and help to identify ways of strategically design enterprise structures to achieve higher profitability given farmer’s realities. We use secondary data from Zambia’s 2015 Rural Agricultural Livelihood Survey (RALS). RALS is a country-wide survey of agricultural producers with a sample size of 7,934 randomly selected households. We utilize the Gaussian/Ordinary Least Squares (OLS) regression model to test the significance of the effect associated with adopting different enterprise structures, and to examine their contributions to profitability. The results show statistically significant differences in demographic, socio-economic and production characteristics among farmers pursuing different enterprise structures. The results also show regional variations in the distribution and profitability of enterprise structures. This is understandable because of differences in regional agro-ecological conditions. The results further show that enterprise structures significantly influence profitability to varying degrees, suggesting that some crop portfolios may have higher profitability than others even though they may have the same number of crops. Diversification recommendations based on enterprise structures are, therefore, likely to be more effective than those based on indices

Effect of buyer type on market participation of smallholder farmers in northern Ghana

Master of ScienceDepartment of Agricultural EconomicsVincent Amanor-BoaduTransaction costs, one of the most significant barriers to market participation, may vary by buyer type. Depending on who a farmer sells their produce to, they may alter their potential transaction costs consequently influencing their market participation. This study examines the effect of buyer type on smallholder market participation in Northern Ghana where poverty is still endemic and often exacerbated by fewer opportunities for commercialization such as limited access to markets. The analysis is based on data from the agriculture production survey conducted in 2013 and 2014 and the Population based Survey conducted in 2012 in northern Ghana. Analysis is performed using the Double Hurdle approach to control for self-selection bias, ensure more flexibility on the variables affecting the decision to sell and how much to sell as well as to provide unconditional effects of the variables on market participation. The results reveal greater market participation of cash crop producing farmers than those producing a lower value food crop - Maize. The results also show that farmers selling to aggregator-type middlemen and other buyers have a propensity to sell more. The aggregators and ‘other buyers’ buy in bulky, offer lower prices and are associated with lower transport, loading and offloading costs than consumers. Farm output, access to information and price also have a significant positive impact on intensity of market participation. These findings support policy initiatives such as supporting aggregator-type middlemen, increasing the provision of information, promotion of cash crops as well as supporting more interventions focusing on increasing production and yields

Crop Diversification Improves Technical Efficiency and Reduces Income Variability in Northern Ghana

Crop diversification is a climate smart agricultural technique which helps improve resilience for farmers in the face of volatile weather due to climate change. Previous research on its effect on technical efficiency shows contrasting results (positive and negative effects). Other literature show that crop diversification has a positive impact on income variability. Is it possible that choosing crop diversification involves a tradeoff between efficiency and resilience (income variability) for rural smallholder farmers? It is likely that merging these two separate sets of previous literature, one on the effects of crop diversification on technical efficiency, and another on its effect on income variability, can provide valuable insights on the decision making process faced by a farmer considering to adopt crop diversification. So essentially, the question we try to answer in this study is what is the effect of crop diversification on technical efficiency and income variability on the same farm household of northern Ghana? Without addressing this question, policy makers cannot tell for sure if crop diversification is a good CSA option for their farmers, and if it is, they still may not know how to promote its adoption effectively. To answer our research question, we use the Agricultural production data from northern Ghana and employ a Cobb Douglas stochastic input distance function for efficiency, and ordinary least squares for income variability. The results show evidence against ‘tradeoff’. Crop diversification significantly improves efficiency and reduces income variability in northern Ghana so farmers do not have to give up efficiency for income stability or vice versa. Thus crop diversification is an ideal CSA strategy for promoting agricultural growth and resilience in northern Ghana. The data we use in this study has a maximum three crops, so our results cannot be generalized to farmers who grow more than three crops

Market Participation and Farm Profitability: The Case of Northern Ghana

This study examines the effect of quantity sold (sales volume) on profitability of market participating smallholder farmers in northern Ghana. Market participation has been shown to be important for increasing incomes and improving production efficiency for farm households but still remains low in SSA. While agribusiness and development experts generally advocate for more intensive market participation, it is not clear if selling more results in more profits for smallholder farmers in remote markets that are prone to exorbitant transaction costs. The data used in this study is from the APS survey conducted in 2013 and 2014 in Northern Ghana which had a sample size of 527. The study is based on the theory of profit maximization, in which separability is inferred from observed market participation. OLS regression is used for empirical estimation after rejecting the hypothesis of endogeneity in the model. Mean gross margin/ kg across four groups of farmers ranked by quantity sold is also statistically examined. The results confirm the existence of economies of scale and also show that different crops have different effects on profitability. The results also show that although unambiguously positive, the relationship between quantity sold and profitability may not be linear

Crop diversification improves technical efficiency and reduces income variability in Northern Ghana

Crop diversification has been shown to help mitigate climate change effects for farmers. While previous research shows that crop diversification may increase or decrease technical efficiency in different regions, research on whether crop diversification involves a tradeoff between technical efficiency and income variability is limited. Using agricultural production data from Northern Ghana, this study uses the stochastic input distance function to examine the effects of crop diversification on technical efficiency. The study further explores effects of crop diversification on income variability using an ordinary least square regression to understand the nexus between technical efficiency and income variability in crop diversification. The results show evidence against a ‘tradeoff’ between technical efficiency and income stability for farmers in Northern Ghana. We find that crop diversification significantly improves efficiency and reduces income variability in Northern Ghana, so farmers do not have to give up efficiency for income stability or vice versa. This suggests that crop diversification could be an ideal Climate Smart Agricultural (CSA) strategy for promoting agricultural growth and resilience in Northern Ghana. While our data has a maximum of three crops, which could limit generalization of results to farmers who grow more than three crops, our results make a novel contribution to the literature on crop diversification

Strategic value of crop diversification among farmers: New insights and measurement

Previous literature has mostly used crop diversification indices to quantify the extent of crop diversification used by farmers. Indices are useful in assessing the number and proportion of crops in a farmer's portfolio. However, they often overlook the heterogeneity of the crops in their diversification strategy. Consequently, our comprehension of crop choice decisions and their potential to identify optimal diversification strategies is limited. This study introduces the enterprise structure (ES) approach for characterizing crop diversification to account for differences in the types of crops in a portfolio. Using nationally representative survey data from Zambia, we identified 33 ESs that were adopted by at least 30 households in the study area. We examined the effect of these 33 ESs on profitability and crop revenues, using a semi-log model. Our results reveal that ESs do affect profitability and revenue. The effect is different in each agroecological zone based on the crops contained in the ESs. That is, ESs with the same number but different types of crops may present different profitability and revenues. Particularly, Cassava ES significantly increased gross margin per hectare (GM_ha) by 77.89% compared to Maize ES, in agroecological zone III. Further, the results suggest that ESs with more crops may not be necessarily more or less superior to specialization. Based on the ES approach, clear recommendations on what crops can be included in a portfolio to increase profitability are provided

Uncovering the factors that affect earthquake insurance uptake using supervised machine learning

Abstract The escalating threat of natural disasters to public safety worldwide underlines the crucial role of effective environmental risk management tools, such as insurance. This is particularly evident in the case of earthquakes that occurred in Oklahoma between 2011 and 2020, which were linked to wastewater injection, underscoring the need for earthquake insurance. In this regard, from a survey of 812 respondents in Oklahoma, USA, we used supervised machine learning techniques (i.e., logit, ridge, least absolute shrinkage and selection operator (LASSO), decision tree, and random forest classifiers) to identify the factors that influence earthquake insurance uptake and to predict individuals who would acquire earthquake insurance. Our findings reveal that influential factors that affect earthquake insurance uptake include demographic factors such as older age, male gender, race, and ethnicity. These were found to significantly influence the decision to purchase earthquake insurance. Additionally, individuals residing in rental properties were less likely to purchase earthquake insurance, while longer residency in Oklahoma had a positive influence. Past experience of earthquakes was also found to positively influence the decision to purchase earthquake insurance. Both decision trees and random forests demonstrated good predictive capabilities for identifying earthquake insurance uptake. Notably, random forests exhibited higher precision and robustness, emerging as an encouraging choice for earthquake insurance modeling and other classification problems. Empirically, we highlight the importance of insurance as an environmental risk management tool and emphasize the need for awareness and education on earthquake insurance as well as the use of supervised machine learning algorithms for classification problems

Technical Efficiency and Technological Gaps of Rice Production in Anambra State, Nigeria

The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic frontier model in such cases, a stochastic meta-frontier (SMF) analysis is recommended to account for environmental factors between regions. It follows that differences in environmental factors between the upland and lowland regions in Anambra State, Nigeria, may result in farmers producing rice under different production and environmental conditions. Using the SMF model, this study, for the first time, determines technical efficiency (TE) and technological gap ratios (TGRs) of rice production from the upland and lowland regions in the Awka North Local Government Area of Anambra State, Nigeria. Our data are from a cross-section sample of randomly selected rice farmers. Results reveal that lowland regional rice producers are on average, significantly more technically efficient (91.7%) than their upland counterparts (84.2%). Additionally, mean TGRs associated with lowland rice farmers are higher (92.1%) than their corresponding upland producers (84.7%). While the upland rice producers are less technically efficient and further away from their full potential, results indicate that both sets of farmers do not use advanced technologies to match the industry’s potential. We suggest that agricultural policy should focus on providing regionally specific technologies, such as improved rice varieties that fit the working environment of the lagging area, to help rice farmers improve their resource efficiency and minimize technological gaps

How does who-you-sell-to affect your extent of market participation? evidence from smallholder maize farmers in Northern Ghana

AbstractThis study examines the effect of marketing channel choice on the extent of market participation, with the goal of helping farm managers and policymakers to identify ways of enhancing market participation outcomes. The study uses data from 383 smallholder maize farmers who were part of the respondents to the Agriculture Production Survey conducted in 2014 and the Population-Based Survey conducted in 2012 in Northern Ghana. Econometric analysis was performed using the double hurdle model to account for data censoring in a more flexible way. Findings indicate that smallholder farmers in Ghana sell larger maize quantities when they sell to aggregators than when they sell directly to consumers. By changing from selling to consumers to selling to aggregators, farmers can increase the amount of maize sold by 128.46 kg conditional on participation and by 43.41 kg unconditional on participation. This is potentially due to the scale advantages and non-pecuniary cost savings that aggregators present. The results imply that facilitating access to aggregator-type middlemen may improve market participation in markets where market infrastructure and institutions are not developed enough to substantially lower pecuniary and non-pecuniary marketing costs of selling directly to consumers