Food Demand in Russia: Heterogeneous Consumer Segments over Time

Abstract

The Russian food system has undergone substantial changes. However, knowledge on how economic transition has affected the structural parameters of food demand is lacking. Based on a two-stage LES-LA/AIDS model and annual panel data from the Russia Longitudinal Monitoring Survey (1995-2010), we provide a comprehensive set of food demand elasticities for Russia along two dimensions. First, we estimate demand parameters for three characteristic time periods in order to trace changes during transition. Second, to account for the Russian population's diversity, we derive elasticities for five different consumer segments. These groups are established by a cluster analysis based on households' food purchases. Our findings suggest that demand for food is far from satiated in Russia. We find generally high unconditional expenditure and own-price elasticities for food. Both expenditure and own-price elasticities show slight decreases in absolute terms over time. Low expenditure elasticities for staple foods like bread or cereals and high values for luxury goods such as meat, alcohol and tobacco suggest considerable changes in the composition of food baskets with further income growth. Results indicate that food production at home loses in importance while more affluent households in particular increase their demand for food consumption away from home.

Empirical Evidence of Changing Food Demand and Consumer Preferences in Russia

“…Specifically, Marshallian own-price elasticity estimates are negative, statistically significant, and fall in the range of −1.11 for fats/oil to −0.88 for dairy, pointing to the fact that despite the lack of substitutes for these aggregately defined food commodities, Russian consumers are generally price-sensitive. Our own-price elasticities of demand for cereals (−1.11) and dairy (−0.88) are similar to those provided in other studies (e.g., Burggraf et al, 2015;Hovhannisyan and Shanoyan, 2019;Staudigel and Schröck, 2015). However, our own-price elasticity for meats (−1.03) is larger in absolute value vis-à-vis the respective estimates in Goodwin et al (2002), Staudigel and Schröck (2015), and Hovhannisyan and Shanoyan (2019), due perhaps to our inclusion of pre-committed consumption and addressing of price endogeneity.…”

“…Our own-price elasticities of demand for cereals (−1.11) and dairy (−0.88) are similar to those provided in other studies (e.g., Burggraf et al, 2015;Hovhannisyan and Shanoyan, 2019;Staudigel and Schröck, 2015). However, our own-price elasticity for meats (−1.03) is larger in absolute value vis-à-vis the respective estimates in Goodwin et al (2002), Staudigel and Schröck (2015), and Hovhannisyan and Shanoyan (2019), due perhaps to our inclusion of pre-committed consumption and addressing of price endogeneity. Our income elasticity varies from 0.62 for dairy to 1.05 for other food and non-food products and services, which agrees with the Engel's law and the findings from Zhen et al (2013).…”

“…Nevertheless, the extent to which these recent consumption changes are tied to shifting consumer tastes and preferences rather than being reflective of sheer consumer response to changing economic circumstances under stable preferences has not received adequate research interest. Previous studies have almost exclusively focused on estimating the structure of demand for various food products based on an implicit assumption of fixed and exogenously given consumer preferences, where consumption changes are fully attributed to consumer response to changing opportunity set (e.g., Burggraf et al, 2015;Elsner, 1999;Hovhannisyan and Shanoyan, 2019;and Staudigel and Schröck, 2015). However, structural changes can have significant effects on food preferences, the omission of which can result in inaccurate price and income effects, ultimately leading to erroneous policy implications.…”

“…Evidence suggests that these unpredictable supply forces are indeed some of the most important drivers behind agricultural price volatility (Gilbert, 2010). Despite this reality, literature on food demand in Russia has overlooked this particular source of price variation because of limited data, thus relying only on demand factors for the identification of structural demand parameters (Shiptsova, Goodwin, and Holcomb, 2004;Staudigel, and Schröck, 2015). This creates an endogeneity bias given that the error terms in the commodity demand equations reflect both unobserved demand and supply effects and can generate inconsistent parameter estimates and economic effects, ultimately leading to erroneous policy recommendations (Hovhannisyan and Bozic, 2017).…”

Household behavior with respect to meat consumption in the presence of BSE and CWD

“…The evidence of richness or ability of big data sets to determine heterogeneity across households and over time even for a small portion of the population, such as vegetarians, was illustrated by Lusk (2017). Many researchers have used household data across time in a panel format to look at demand for different goods (Myae & Goddard, 2010; Staudigel & Schrock, 2015; Verbeke & Ward, 2001; Yang & Goddard, 2011a).…”