Monotone Comparative Statics for Directed Search Models

2015 ◽  
Author(s):  
Michael Choi
Keyword(s):  
Comparative Statics ◽  
Directed Search ◽  
Monotone Comparative Statics ◽  
Search Models

A NOTE ON MONOTONE COMPARATIVE STATICS FOR MONETARY DIRECTED SEARCH MODELS

2019 ◽  
pp. 1-10 ◽  
Author(s):  
Michael Choi
Keyword(s):  
Money Demand ◽  
Comparative Statics ◽  
Directed Search ◽  
Matching Function ◽  
Market Outcomes ◽  
Monotone Comparative Statics ◽  
Search Models ◽  
Search Intensity ◽  
Monotone Methods ◽  
The Impact

This note uses monotone methods to derive two sets of comparative statics results for monetary directed search models. First, it characterizes the impact of a higher inflation rate or a higher cost of using credit on market outcomes, regardless of the choice of matching function. Second, the seller-to-buyer ratio, output level, and money demand increase as the matching function becomes more efficient in a log-supermodular sense. I also consider an extension with endogenous search intensity and show that search intensity and trade volume always decrease in the nominal interest rate.

The Neglect of Monotone Comparative Statics Methods

2010 ◽  
Vol 41 (2) ◽  
pp. 177-193 ◽  
Author(s):  
Carol Horton Tremblay ◽  
Victor J. Tremblay
Keyword(s):  
Comparative Statics ◽  
Monotone Comparative Statics

scholarly journals Monotone Comparative Statics for Models of Politics

2006 ◽  
Vol 50 (1) ◽  
pp. 214-231 ◽  
Author(s):  
Scott Ashworth ◽  
Ethan Bueno de Mesquita
Keyword(s):  
Comparative Statics ◽  
Monotone Comparative Statics

scholarly journals Order on types based on monotone comparative statics

2020 ◽  
Vol 189 ◽  
pp. 105082
Author(s):  
Takashi Kunimoto ◽  
Takuro Yamashita
Keyword(s):  
Comparative Statics ◽  
Monotone Comparative Statics

M♮-Convexity and Its Applications in Operations

2021 ◽  
Author(s):  
Xin Chen ◽  
Menglong Li
Keyword(s):  
Comparative Statics ◽  
Optimization Models ◽  
Optimal Solutions ◽  
Monotone Comparative Statics ◽  
Stochastic Inventory ◽  
Fundamental Properties ◽  
Stochastic Inventory Model ◽  
Lattice Programming ◽  
Discrete Convex Analysis ◽  
Preservation Property

A new approach for structural analysis of operations models with substitutability structures. In many operations models with substitutability structures, one often ends up with parametric optimization models that maximize submodular objective functions, and it is desirable to derive structural properties including monotone comparative statics of the optimal solutions or preservation of submodularity under the optimization operations. Yet, this task is challenging because the classical and commonly used results in lattice programming, applicable to optimization models with supermodular objective function maximization, do not apply. Using a key concept in discrete convex analysis, M♮-convexity, Chen and Li establish conditions under which the optimal solutions are nonincreasing in the parameters and the preservation property holds for parametric maximization models with submodular objectives, together with the development of several new fundamental properties of M♮-convexity. Their approach is powerful as demonstrated by applications in a classical multiproduct stochastic inventory model and a portfolio contract model.

Sign in / Sign up

Export Citation Format

Share Document