Dynamic food demand in urban China

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Dynamic Food Demand in Urban ChinaAbstract:Purpose -The purpose of this paper is to investigate dynamic food demand in urban China, with use of a complete dynamic demand system -DLES-LA/DAIDS, which pushes forward the techniques of demand analysis.Design/methodology/approach -We employ a transitionary demand process and develop a new approach of complete demand system with a two-stage dynamic budgeting: an additively separable dynamic linear expenditure system (DLES) in the first stage and a linear approximate dynamic almost ideal demand system (LA/DAIDS). Employing provincial aggregate data (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) from the China urban household surveys (UHS), we estimated the demand elasticities for primary food products in urban China.Findings -Our results indicate that most primary food products are necessities and price-inelastic for urban households in China. We also found that the dynamic model tends to yield relatively smaller expenditure elasticities in magnitude than the static models do due to dynamic adjusting costs, such as habit formation, switching costs, and learning process. .Practical implications -The research contributes to the demand analysis methodologically, and can be used for better projections in policy simulation models.Originality/value -This paper methodologically releases the restrictive assumption of instant adjustment in static models and allows consumers to make a dynamic decision in food consumption. Empirically, we introduce a new complete dynamic demand model and carry out a case study with the use of urban household data in China.

Meat consumption and democratic governance: A cross-national analysis

“…These findings are consistent with the current literature (e.g. Gallet, 2011a;2011b;Tian and Yu, 2015;Zhou, Yu and Herzfeld, 2015;Chen et al, 2015) and meat consumption statistics. The FAO statistics show that the global per capita meat consumption reached 42.4 kg per year in 2011, which represents a relatively high level 2 .…”

A Bite of China: Food consumption and carbon emission from 1992 to 2007

“…With the accelerated growth in household income, food consumption has increased significantly and the composition of foods consumed in China has changed considerably in the past several A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT 5 decades (Gale Jr, 2002;Kearney, 2010;Zhou et al, 2015). On the one hand, total energy intake has increased from 1742 kcal per capita per day in 1950 to 2386 kcal per capita per day in 2000 (Du et al, 2002).…”

Prediction of pork supply via the calculation of pig population based on population prediction model

“…Within this field of agricultural commodity price forecasting, there are roughly two categories, static prediction and dynamic prediction. In static prediction, based on the cobweb theory [1,2] , according to the historical data of agricultural products such as pork, pork supply, scholars screen out the causes (influencing factors) that affect the fluctuation of pork supply [3,4] , and find out the fluctuation of pork supply and price through theoretical analysis [5][6][7][8] . In dynamic prediction, scholars mainly use linear regression prediction and nonlinear prediction method to predict pork supply and price fluctuations.…”