Dynamic Demand Analysis and the Process of Adjustment

2007 ◽  
pp. 27-50
Author(s):  
Jacques Girod
2017 ◽  
Vol 63 ◽  
pp. 268-276 ◽  
Author(s):  
Tien Duc Pham ◽  
Son Nghiem ◽  
Larry Dwyer

2007 ◽  
pp. 145-152
Author(s):  
R. Khaldi ◽  
B. Dhehibi ◽  
Z. Rached

2015 ◽  
Vol 7 (1) ◽  
pp. 27-44 ◽  
Author(s):  
De Zhou ◽  
Xiaohua Yu ◽  
Thomas Herzfeld

Purpose – The purpose of this paper is to investigate dynamic food demand in urban China, with use of a complete dynamic demand system – dynamic linear expenditure system-linear approximate dynamic almost ideal demand system (DLES-LA/DAIDS), which pushes forward the techniques of demand analysis. Design/methodology/approach – The authors employ a transitionary demand process and develop a new approach of complete demand system with a two-stage dynamic budgeting: a strongly separable DLES in the first stage and a LA/DAIDS in the second stage. Employing provincial aggregate data (1995-2010) from the China urban household surveys, The authors estimated the demand elasticities for primary food products in urban China. Findings – The results indicate that most primary food products are necessities and price inelastic for urban households in China. The authors also found that the dynamic model tends to yield relatively smaller expenditure elasticities in magnitude than the static models do due to the friction effect of dynamic adjusting costs, such as habit formation, switching costs, and learning process. However, the dynamic effects on own price elasticities are inconclusive due to the add-up restriction. 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 relaxes the restrictive assumption of instant adjustment in static models and allows consumers to make a dynamic decision in food consumption. Empirically, the authors introduce a new complete dynamic demand model and carry out a case study with the use of urban household data in China.


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