scholarly journals Discriminating among alternative habit formation schemes in single-equation demand models

1981 ◽  
Vol 13 (3) ◽  
pp. 399-409 ◽  
Author(s):  
Richard D. Green ◽  
Rulon D. Pope ◽  
Tim T. Phipps
Keyword(s):  
Habit Formation ◽  
Single Equation ◽  
Demand Models

Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?

2019 ◽  
Vol 26 (3) ◽  
pp. 461-474
Author(s):  
Tzu-Ming Liu
Keyword(s):  
Word Of Mouth ◽  
Habit Formation ◽  
Critical Role ◽  
Tourism Demand ◽  
Demand Model ◽  
Dynamic Panel Model ◽  
Empirical Results ◽  
Demand Models ◽  
Lagged Dependent Variable ◽  
Time Lagged

The effects of habit formation/persistence (HFP) and word of mouth (WOM) each play a critical role in influencing tourists’ decisions regarding whether to visit tourism destinations and therefore tourism policies and tourism management resource allocations. Nevertheless, in previous tourism demand studies, the two effects have been represented by the same time-lagged dependent variable, which makes the variable have an ambiguous meaning and biases the empirical results. The purpose of this study is to solve the ambiguity of a lagged dependent variable in tourism demand. We used economic theories regarding internal habits and external habits to clarify the meanings of HFP and WOM and revised the tourism demand model into a spatial dynamic panel model (SDPM). The empirical results suggested that an SDPM is a more accurate model for modeling tourism demand. The effects of variables in an SDPM are more consistent with theoretical expectations.

Habit Formation in Food Consumption

2011 ◽  
pp. 769-790
Author(s):  
Sven - Olov Daunfeldt ◽  
Jonas Nordström ◽  
Linda Thunström
Keyword(s):  
Food Consumption ◽  
Functional Form ◽  
Habit Formation ◽  
Empirical Studies ◽  
Econometric Models ◽  
Demand Analysis ◽  
Empirical Literature ◽  
Future Research ◽  
Demand Models ◽  
Static Version

This article summarizes the empirical literature on habit formation in food consumption in order to analyze the hypothesis that food consumption is habit forming. It reviews the main econometric models used to study habits in food consumption and describes the most commonly used demand models and departs from the static version of the models. It describes how these models can be extended to dynamic versions incorporating habit formation. The focus is on the functional form of the models rather than estimation. The empirical studies reviewed in this article generally find habit formation in food consumption, implying that dynamics is an important factor in food demand analysis. Finally, it summarizes the results and discusses fruitful areas for future research.

An Examination of Demand Functions for Beef, Pork, and Broilers

1979 ◽  
Vol 8 (2) ◽  
pp. 299-311
Author(s):  
John F. Yanagida ◽  
Roger K. Conway
Keyword(s):  
Empirical Research ◽  
Single Equation ◽  
The Other ◽  
Total Output ◽  
Demand Functions ◽  
Response System ◽  
Demand Models ◽  
Short Run ◽  
Production Cycles

Empirical research on single equation, competitive demand models has employed either price dependent or quantity dependent forms. The price dependent models assume that total output is predetermined in the short-run due to the role of past prices and to production cycles as the case of the livestock industry (Heien). On the other hand, quantity dependency can be described as a supply response system.

Factors for Habit Formation of Physical Activity

2017 ◽  
Vol 1 (2) ◽  
pp. 21-27
Author(s):  
Yoongu Lee ◽  
Yong-Jin Yoon ◽  
Sibak Sung
Keyword(s):  
Physical Activity ◽  
Habit Formation

PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Rusmadi Suyuti
Keyword(s):  
Information System ◽  
Real Time ◽  
Travel Demand ◽  
Urban Traffic ◽  
Road User ◽  
Traffic Information ◽  
Estimation Methods ◽  
Traffic Counts ◽  
Real Time Traffic ◽  
Demand Models

Traffic information condition is a very useful  information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.  

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