Gbemisola Oseni

Agricultural Production, Dietary Diversity, and Climate Variability

Abstract Nonseparable household modelsoutline the interlinkage between agricultural production and household consumption, yet empirical extensions to investigate the effect of production on dietary diversity and diet composition are limited. While a significant literature has investigated the calorie-income elasticity abstracting from production, this paper provides an empirical application of the nonseparable household model linking the effect of exogenous variation in planting season production decisions via climate variability on household dietary diversity. Using degree days, rainfall and agricultural capital stocks as instruments, the effect of production on household dietary diversity at harvest is estimated. The empirical specifications estimate production effects on dietary diversity using both agricultural revenue and crop production diversity. Significant effects of both agricultural revenue and crop production diversity on dietary diversity are estimated. The dietary diversity-production elasticities imply that a 10 per cent increase in agricultural revenue or crop diversity result in a 1.8 per cent or 2.4 per cent increase in dietary diversity respectively. These results illustrate that agricultural income growth or increased crop diversity may not be sufficient to ensure improved dietary diversity. Increases in agricultural revenue do change diet composition. Estimates of the effect of agricultural income on share of calories by food groups indicate relatively large changes in diet composition. On average, a 10 per cent increase in agricultural revenue makes households 7.2 per cent more likely to consume vegetables, 3.5 per cent more likely to consume fish, and increases the share of tubers consumed by 5.2 per cent.

No Condition is Permanent Middle Class in Nigeria in the Last Decade

Abstract The economic debate on the existence and definition of the middle class has become particularly lively in many developing countries. Building on a recently developed framework called the Vulnerability Approach to Middle Class (VAMC) to define the middle class, this paper tries to estimate the size of the Nigerian middle class in a rigorous quantitative manner and to gauge its evolution over time. Using the VAMC method, the middle class group can be defined residually from the vulnerability analysis as those for which the probability of falling into poverty is below a certain threshold. The results show the size of the Nigerian middle class from is around 20 percent of the total population in 2012/13. However, the rate has been slower than expected given the high growth rates experienced in the country over the same period. The results also paint a heterogeneous picture of the middle class in Nigeria with large spatial differences. The southern regions have a higher share and experienced more growth of the middle class compared with the northern regions.

Can Agricultural Households Farm Their Way Out of Poverty

This paper examines the determinants of agricultural productivity and its link to poverty using nationally representative data from the Nigeria General Household Survey Panel, 2010/11. The findings indicate an elasticity of poverty reduction with respect to agricultural productivity of between 0.25 to 0.3 percent, implying that a 10 percent increase in agricultural productivity will decrease the likelihood of being poor by between 2.5 and 3 percent. To increase agricultural productivity, land, labor, fertilizer, agricultural advice, and diversification within agriculture are the most important factors. As commonly found in the literature, the results indicate the inverse-land size productivity relationship. More specifically, a 10 percent increase in harvested land size will decrease productivity by 6.6 percent, all else being equal. In a simulation exercise where land quality is assumed to be constant across small and large holdings, the results show that if farms in the top land quintile had half the median yield per hectare of farms in the lowest quintile, production of the top quintile would be 10 times higher. The higher overall values of harvests from larger land sizes are more likely because of cultivation of larger expanses of land, rather than from efficient production. It should be noted that having larger land sizes in itself is not positively correlated with a lower likelihood of being poor. This is not to say that having larger land sizes is not important for farming, but rather it indicates that increasing efficiency is the more important need that could lead to poverty reduction for agricultural households.

Land measurement bias and its empirical implications : evidence from a validation exercise

We investigate how land size measurements vary across three land measurement methods (farmer estimated, GPS, and compass-and-rope) and the effect of land measurement error on the inverse farm size relationship and input demand functions. Our findings indicate that self-reported measurement bias leads to overreporting for small plots and underreporting for large plots. The error is nonlinear, is not resolved by trimming of outliers, and results in biased estimates of the inverse land size relationship. Input demand functions that rely on self-reported land measures underestimate the effect of land on input utilization, including fertilizer and household labor.