Demand Sensitivity to Time

2021 ◽  
pp. 183-201
Author(s):  
Mohammad Kaviyani-Charati ◽  
Bahareh Kargar
Keyword(s):  
2019 ◽  
Vol 11 (1) ◽  
pp. 23-35
Author(s):  
Christos Karpetis ◽  
Stephanos Papadamou ◽  
Eleftherios Spyromitros ◽  
Erotokritos Varelas

Purpose The purpose of this paper is to investigate, both theoretically and empirically, the relationship between optimism (pessimism) – as reflected by animal spirits – and money demand by taking into account transaction costs. Design/methodology/approach Inspired by the theoretical model of money demand by Teles et al. (2016) the authors incorporate the optimism (pessimism) effects in the money demand. Then, using the consumers’ confidence indicator as a proxy indicator of optimism/pessimism, they estimate the money demand in a panel data framework. Findings The theoretical framework suggests that the optimism (pessimism) effects on money demand are positive (negative). Empirical evidence for 11 Eurozone countries divided in two groups (i.e. core and periphery) confirms the theoretical considerations. Practical implications It appears that periphery countries with a higher sensitivity to the recent financial crisis present lower real money demand sensitivity to consumption expenditures and higher real money demand sensitivity to consumer confidence index. Moreover, in such countries, money demand changes present higher persistence over time. Thus, the authors observe differing attitudes concerning money demand across Eurozone citizens that should be taken into account by monetary policymakers (i.e. the ECB). Originality/value The authors introduce, in the vast literature on money demand, both theoretically and empirically the role of optimism (pessimism). Differences across core and periphery Eurozone countries identified.


Author(s):  
Wanshu Nie ◽  
Benjamin F. Zaitchik ◽  
Matthew Rodell ◽  
Sujay V. Kumar ◽  
Kristi R. Arsenault ◽  
...  

2015 ◽  
Vol 42 (8) ◽  
pp. 544-551 ◽  
Author(s):  
Wei Fan

The purpose of this paper is to present bi-level optimization models and develop a genetic algorithm (GA) based method to solve the optimal congestion pricing toll design problem and to determine the second-best link-based optimal toll locations and toll levels simultaneously. The upper-level subprogram is to maximize the toll revenue collected while explicitly accounting for the toll booth setting up and operating cost, given certain toll level constraints. The lower-level subprogram is a traditional user equilibrium problem with elastic demand. The proposed GA model is applied to the Sioux Falls network, which has 76 links and 24 origin–destination pairs, assuming homogeneous users. Comprehensive numerical results including solutions achieved under continuous tolling and discrete tolling schemes, tolling on optimized links and tolling on heuristically selected most congested links are carefully presented and compared. The impact of value of time and the elastic demand sensitivity are also comprehensively investigated.


2019 ◽  
Vol 87 (2) ◽  
pp. 750-791 ◽  
Author(s):  
Alessandro Bonatti ◽  
Gonzalo Cisternas

Abstract We study the implications of aggregating consumers’ purchase histories into scores that proxy for unobserved willingness to pay. A long-lived consumer interacts with a sequence of firms. Each firm relies on the consumer’s current score–a linear aggregate of noisy purchase signals—to learn about her preferences and to set prices. If the consumer is strategic, she reduces her demand to manipulate her score, which reduces the average equilibrium price. Firms in turn prefer scores that overweigh past signals relative to applying Bayes’ rule with disaggregated data, as this mitigates the ratchet effect and maximizes the firms’ ability to price discriminate. Consumers with high average willingness to pay benefit from data collection, because the gains from low average prices dominate the losses from price discrimination. Finally, hidden scores—those only observed by the firms—reduce demand sensitivity, increase average prices, and reduce consumer surplus, sometimes below the naive-consumer level.


1978 ◽  
Vol 15 (1) ◽  
pp. 82-92 ◽  
Author(s):  
Mario J. Picconi ◽  
Charles L. Olson

The authors postulate that the firm pursues a present value profit maximization goal in determining its advertising strategy. Advertising is included in the profit function nonlinearly as a factor cost and as a demand stimulant. On the basis of optimal control theory, an optimal advertising-sales ratio decision rule is formulated with respect to the brand's demand parameters. Reliably collected data on sales and advertising expenditures on a bimonthly basis were used to obtain empirical estimates of the brand parameters. A simultaneous estimation of the demand parameters of all the competing brands was performed to harness efficiently the information inherent in the system of brand demand equations. Comparing the firm's behavior on brand advertising with the derived decision rule ratio suggests the potential usefulness of such analytical models for improving the productivity of advertising expenditures and for determining the change in advertising policy which would be appropriate in the event of changes in a brand's demand sensitivity.


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