Hedonic Pricing of Rice Attributes, Market Sorting, and Gains from Quality Improvement in the Beninese Market

Abstract

Latent class analysis is applied to a hedonic price model to examine the presence of heterogeneity in consumer valuation of quality attributes in the Beninese rice market. Three classes of consumers are found in proportions of 5, 56, and 39 percent. We employ a partial equilibrium model and find modest gains in consumer surplus from an increase in head rice and reduction in chalkiness. The results provide evidence of market sorting, which should be taken into consideration in upgrading rice value chains. Also, it is important to assess potential gains from quality improvement to determine priorities for research and development.

Pricing Rice Quality Attributes and Returns to Quality Upgrading in Sub-Saharan Africa

“…Preference for parboiled rice has been observed in Benin (Naseem et al, 2013), and therefore, parboiling of rice using improved technology is seen as a viable means to increasing the competitiveness of domestic rice value chains (Akoa Etoa et al, 2016). Similarly, consumer preference for rice sold in urban markets to that sold in rural ones has been observed for two classes of consumers in the Beninese market (Ndindeng et al, 2021b). The results reveal negative implicit prices for impurities, amylose content, and imported rice.…”

“…Future reduction in amylose content in the Philippines was expected to yield a BCR of 9 and IRR of 29. Ndindeng et al (2021b) have found rather small gains in consumer surplus if there is an increase in head rice and a reduction in chalkiness. The hedonic price model in both studies is the consumer goods characteristics model (CGCM) of Ladd and Suvannunt (1976).…”

“…Studies that have estimated hedonic prices of rice quality attributes include Unnevehr (1986) for Thailand, Indonesia, and the Philippines, Naseem et al (2013) for Benin, Cuevas et al (2016) for the Philippines, and more recently Ndindeng et al (2021b) for Benin. Like the current study, Unnevehr (1986), Cuevas et al (2016), andNdindeng et al (2021b) use data obtained from laboratory analyses of rice samples, but they employ only parametric methods to estimate their models.…”

“…Like the current study, Unnevehr (1986), Cuevas et al (2016), andNdindeng et al (2021b) use data obtained from laboratory analyses of rice samples, but they employ only parametric methods to estimate their models. Using similar approaches, Unnevehr (1986) and Ndindeng et al (2021b) estimate the impacts on consumer surplus of grain quality improvement, but Unnevehr (1986) goes even further to calculate the associated returns, which she finds to be substantial. From the breeding efforts prior to her study, improvement in head rice recovery had a benefit-cost ratio (BCR) of 49 and internal rate of return (IRR) of 61% for the Philippines and Indonesia combined, while reduction in amylose content for rice in Indonesia had a BCR of 8 and IRR of 37.…”

Integrated Research for Development Approach to Upgrade the Whole Rice Value-chain in Sub-Saharan Africa: Contribution of Africa Rice Center after NERICA (New Rice for Africa)

“…Collaborations of the Japanese scientists with economists are also actively implemented and several joint articles have been published (e.g. Arouna et al 2021a, Arouna et al 2021b, Diagne et al 2013a, Diagne et al 2013b, Fiamohe et al 2018, Ndindeng et al 2021b.…”