Money Metric and Ordinal Utility of Common Beans Consumption
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Published: Wed, 11 Oct 2017
Common bean Phaseolus vulgaris is a leguminous plant that originated from Mexico in the years 5500-7000 AD (CGIAR, 2007) and is primarily grown for its edible seeds. The plant belongs to the group of grain legumes that are grown worldwide on 12%-15% of the earth’s arable land (Vance, 2002). CGIAR (2015) explains that about 12 million metric tons of common beans are produced annually, with Latin America playing the major role (about 5.5 million metric tons). The crop is also largely produced by Brazil and Mexico. Africa ranks second in terms of production (produce 2.5 million metric tons). Major African producers include Kenya, Burundi, Congo, Uganda, and Rwanda (CGIAR, 2015).
For Malawi, common beans rank second to groundnuts in terms of area planted and quantity produced (Mazuma et al., 2004). In terms of gender, the crop is largely grown by women in Malawi. For the past 11 years, there has been an upward trend of common beans production in Malawi, with central region (Dedza) taking the major role (Birachi 2012). For instance, common beans production increased from 76,964 metric tons in 2004/05 to 182,596 metric tons in 2011/12, though it declined to 128,624 metric tons in 2012/13. The output per hectare also increased i.e. from 376 kilograms per hectare in 2004/05 to 596 kg/ha in 2010/11 (GoM, 2012). Currently, the popular bean varieties available in the markets in Malawi include Nanyati (cream mottled), Khaki/Mulanje (cream), Napilira/Kachinyata (red mottled), Phalombe/ Chimbamba/Thyolo (red kidney), Kaulesi (Purple/greyish), and mixed beans (various colours) (Chirwa & Phiri, 2007). These varieties mainly differ interms of grain size, grain quality, colour, cooking time and taste.
Although Malawi’s common bean production has been facing upward trends recently, they’re some challenges that prevent the production to reach its potential of 2000Kg/hectare. Apart from the production problems such as seed, inputs, pests and diseases, the other challenges include: inadequate promotion by intervention organizations and the government, lack of value adding efforts, lack of available and accessible markets, and low demand (emanates from the stagnant beans consumption/household/year of 14kg per on average (Birachi, 2012; USAID, 2011; GoM 2012).
Common beans are nutrition dense foods that play an important role in traditional meals of most societies of the world. They are utilized as food, feed and/or processed into various products, thus they serve multiple purposes. Common beans support over 200 million people in the sub-Saharan as a dominant staple, and 300 million people in the tropics as a source of proteins, complex carbohydrates and other valuable macronutrients (Larochelle, 2015). They act as a cheap nutrition option as compared to meat/milk and their amount of nutrients offered per calorie is remarkably high as compared to most foods (Larochelle et al., 2015). Common beans contain essential amino acids and proteins, complex carbohydrates, and soluble and insoluble dietary fibres. They also have low salt and fat content, no cholesterol and contain other dietary necessities (Mayaka, 2013). In addition, common beans are an excellent source of vitamins and minerals such as phosphorus, copper, magnesium and manganese. CGIAR (2007) reports that common bean is the most important grain legume in human diets in Malawi as it ranks second after maize as a source of calories.
Besides offering nutrition needs, common beans are also an important source of income for most farmers in the world. Millions of small scale farmers in Africa and Latin America rely on the production and sale of beans as a source of income (Katungi et al., 2009). Beans have high gross margins as compared to other crops and they mature earlier; they bring income earliest to smallholder farmers as compared to other crops hence acting as a bridging source of income (Birachi (2012). In addition, beans can be sold at various stages: as green leaves; as fresh pods: and as immature and/or dry grains. On the international market; common beans together with other dried legumes account for about 3.9% of Malawi’s exports. The increase in demand for protein meals and oil from the EU and US feed sectors (Gowda et al., 2009), offer a distinctive opportunity for Malawi to realize more gains from international trade of legumes.
Despite the country registering an economic growth of 6% recently (GoM, 2014), poverty in Malawi is still rampant. This can been largely attributed to the heavy reliance of the country on agriculture which is characterized by low labor productivity, soil degradation, inadequate and variable rainfall, declining farm size (on average less than a hectare land holding size per household), imperfect agricultural markets and poor infrastructure (CIAT, 2007). Malawi’s smallholder agriculture is largely rainfed and mostly characterized by Maize production. Although Maize production especially hybrid varieties, have been recognized as a panacea to improve productivity in the face of increasing population, they are not resilient enough in the face of inadequate rainfall and poor soil fertility and/or low fertilizer application. This pose a distinctive set of challenges that make the country prone to food insecurity, as most smallholder farmers are resource poor and their production base is not diversified enough to mitigate the effects of low maize production. WHO (2013) reports that the negative effects of the country’s heavy reliance on maize production trickles down to nutrition imbalances in diets of most poor households which lack proteins, vitamins and other nutrients (as 40 % of food expenditures on average is dedicated to staples). This is reflected in the persistence of malnutrition where about 46percent of children under five years of age are stunted and 12.8percent underweight (USAID, 2011).
Common bean is one of the legumes that has the potential of improving nutrition status of the nation and incomes of farmers. The crop has high nutritive value, is a cheap source of proteins, and has high gross margins as compared to most crops including Maize (Birachi, 2012). Production of common beans has increased at the slowest pace (about 2.5%/annum on average from 1961-2007) among the major legumes in Malawi such as soybeans, cowpeas and groundnuts (Katungi et al., 2009: GoM, 2012). Katungi and other (2015) report that one of the contributing reasons to this phenomena is the low common beans consumption present in the country which contributes to low demand, and act as a disincentive to increased common beans production among farmers (Katungi et al., 2015). Household beans consumption has remained at an average of 14.9Kg/year for the past 15 years (GoM, 2012: FAOSTAT, 2009). Literature has presented us the factors that shape market demand for beans (Chirwa & Phiri, 2007: CIAT, 2007; Mkanda et al., 2007) but it hasn’t presented the factors that determine the importance of common beans to households. Furthermore, there is an information gap on factors explaining expenditure shares of common beans to total household food expenditure and the overall importance of common beans to household food security.
The current gaps in knowledge on common bean consumption will make interventions that aim at improving common beans production, farmer’s income and nutritional security by increasing consumption almost futile as policy makers fail to make evidence based decisions about how and who to target to achieve these goals. The lack of an evidence-based policy making framework reduces the potential of common beans to reduce poverty and improve nutrition across the nation. Moreover, the organizations such as feed the future Malawi and others that aim at building excellent functioning markets or reviving poor functioning markets of legumes such as common beans, will not fruitfully accomplish the mission without comprehensive information on the demand and more especially factors that determine the expenditure patterns and importance of common beans to households.
This research will inform policy makers and intervention organizations that are working at marketing and consumption levels of common bean value chain on factors that drive consumers’ share of expenditure on common beans relative to total household expenditure as well as determinants of consumer ranking of common beans. Hence, the research will not only address the current gaps that exist in literature in as far as common beans consumption is concerned, but it will also help policy makers frame more robust and beneficially-specific projects that will improve household incomes, nutrition statuses and food security.
The information from this study will also be of great importance to specific intervention organizations such as Feed the future Malawi, CIAT, CGIAR and USAID who identified legumes such as common bean as having the strongest business case, great opportunity for nutrition and gender benefits, and best opportunities for innovation and leveraging other USG, donor and government resources (USAID, 2011; CIAT, 2007: CGIAR, 2012). More specifically, the information from this study will help Malawi’s feed the future objective of investing and transforming the common bean value chains with the aim of building excellent functioning domestic markets that will stimulate the production and improve the consumption of common beans. In addition, the information from the study will be of great importance to key value chain players in the beans sector, by reducing their risk averseness in conduction various marketing functions.
The main objective of the study is to assess the factors that explain the money metric and ordinal utility of common beans consumption in Lilongwe district.
- To assess the difference in expenditure share of common beans in household monthly income by wealth quantiles and residential area
- To assess how socioeconomic factors, demographic factors, location factors and price of beans affect expenditure share of common beans in household’s monthly food expenditure
- To assess how socioeconomic factors, demographic factors, location factors and price of beans affect rank of importance of common beans to household’s food security
- Socioeconomic factors, demographic factors, location factors and price of beans do not affect expenditure share of common beans in household’s monthly food expenditure
- Socioeconomic, demographic and location factors do not affect rank of importance of common beans to household’s food security
Do socioeconomic factors, demographic factors, location factors, and price of beans explain the importance of common beans to household’s food security?
Ordinal utility theory assumes utility is immeasurable and can only be ranked; that is, consumers can rank choices from the most desirable to the least desirable. This contrasts cardinal utility which assumes utility is directly measurable using numerical values that can be comparable and based on a benchmark or scale. Nicholson (2012) explains that in consumer demand theory, cardinal utility is almost useless, and ordinal utility on the other hand is realistic, provides a sufficient theoretical basis for analyzing the connection between utility and market. In this research, the rank of the importance of common beans to household food security express the ordinal utility of common beans.
Since utility according to ordinal theory cannot be measured, economists have devised ways of indirectly measuring utility. In the simplest sense, economists consider utility to be revealed in different payments that people make for different goods (Varian, 1992). The amount of money that consumers spend on the consumption of some good at given prices expresses the money metric utility (Tian, 2013). The money metric utility function is simply a monotonic transformation of the utility function itself (Varian, 1992). Tian (2013) explains that the expenditure share of goods in total income express the money metric utility since consumers spend to make themselves better off. According to Blackorby & Donaldson (1988), money metric utility is a particular normalization of a household’s utility function, and represents its preferences directly. This research uses the expenditure share for common beans in household’s food expenditure to explain the money metric utility of common beans in Lilongwe district of Malawi.
Levin and Milgrom (2004) assume consumers are rational decisional makers and their choice sets of consumption goods mainly depend on prices and income. Their idea is that consumers choose a vector of goods that maximizes there utility subject to a budget constraint. Katzner (2014) adds commodity attributes in the theory of consumer demand by defining the preference of a consumer as a function of affordability and the characteristics of the commodity. His argument concurs with Lancaster (1966) who in his new approach of consumer demand theory explains that utility derived from a good is not as a result of the direct consumption, but rather the characteristics of the good and the individual. Nicholson further includes the characteristics of the environment in the utility function in his microeconomic theory. This research extends from Lancaster’s theory and Nicholson’s microeconomic theory and defines utility (either expressed in preference ordering or income spent on goods) as a function of the socioeconomic factors, demographic factors, location factors and the price of the good itself.
Senhui et al. (2015) studied the factors that influence beef, poultry and seafood consumption frequency in the US. Using the negative binomial count-data model, they found out that age, education, gender, race, family size, health, and the safety associated with consumption significantly influenced the frequency of consumption of beef. The frequency of poutry consumption was significantly influenced by age, gender, race and health. The frequency of consumption of sea food was significantly influenced by education, health, family size, meatsick and the safety associated with the consumption. Lucia et al. (2000) studied the factors that affect dry beans consumption in the US. Through the descriptive analysis, their results revealed that dry beans consumption was higher for households in the lower income quintiles than for those in the higher income quantile. Dry beans consumption was also high among males than females. In addition, dry beans consumption was also found to positively vary with age. Their analysis also showed that beans consumption was also largely dependent of the race i.e. people of Hispanic Mexican origin were the largest consumers of dry beans.
Idalinya et al. (2011) studied the determinants of farm household food expenditure and implications for food security and nutrition in rural Kenya. In their analysis of household expenditure shares of goods and services using the Tobit model, they found out that: the determinants of expenditure share on food include household income, hunger days per year, household residents (adult equivalent), farming system practiced, and number of males aged 1-18 (dependants); the determinants of expenditure share on education include hunger days per year, number of household residents, and farming system practiced; the determinants of expenditure share on extra social activities included household income, gender of household head, number of females aged 1-18 (dependants), and the farming system practiced; the determinants of expenditure share of health and transport include age of the household head and the farming system practiced: and the determinants of clothing and other expenditures include hunger days per year and farming system practiced. Their overall assessment indicated that the major determinants of expenditure patterns in most households are household size, household income, and the occupation of the household head. Their expenditure elasticities of food items indicated that foods with high protein status (e.g. meat and beans) have a luxurious status and are less affordable by low income farmers.
Kostakis (2012) studied the determinants of food consumption in Greece. As part of the analysis, he modelled the determinants of proportion of food expenditure. The results from the OLS and quantile regression revealed that household income, gender of the household head, retirement, perception of prices of food, number of children in the household, and whether the house was rented or not. Yimer (2011) studied the determinants of food consumption expenditure in Ethiopia and using a double hurdle model and Tobit model separately; concluded that household size, dependency ratio, education of the household head, employment status, gender and income were the significant factors explaining consumption and expenditure on teff, maize, wheat, and sorghum. Globler & Sekhampu (2013) and Davis et al. (1983) also found out through multiple regression and double logarithmic function form respectively that age of the household head, household income and household size are the determinants of food expenditures in households.
Meng et al. (2014) studied consumer’s food shopping choice in Ghana. As part of their analysis, they assessed the determinants of household food purchase frequency at each food outlet type (supermarkets, open-air markets, and hawkers). The shopping frequency at each food outlet was measured on a scale from one to five with the increasing number indicating more frequent shopping in a certain outlet type (i.e., 1=almost never, 2=once a month, 3=every other week, 4=once a week, 5=more than once a week). Through the ordered logit model, their study revealed that marital status, age, household structure, income, occupation, attained education level, and location had significant effect in determining the food shopping frequency.
Kim & Ahn (2014) studied consumers’ preferences for the food preparation time and identified Factors Influencing Time -saving food consumption Pattern in Korea. There dependent variable included three types of lifestyles namely time0-saving, time-indifferent and time-spending. Using an ordered logit model, their study revealed marriage, monthly household income, whether the consumer earns high level of income, age, education, number of family members, housewife, and residence as the determinants of time-saving lifestyle
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