Relaxed Optimization: How Close Is a Consumer to Satisfying First-Order Conditions?

2021 ◽  
pp. 1-45
Author(s):  
Geoffroy de Clippel ◽  
Kareen Rozen
Keyword(s):  
Portfolio Choice ◽  
Consumer Choice ◽  
Goodness Of Fit ◽  
Order Conditions ◽  
Choice Data ◽  
Reference Class ◽  
Progressive Taxation ◽  
First Order ◽  
Budget Sets

Abstract We propose relaxing the first-order conditions in optimization to approximate rational consumer choice. We assess the magnitude of departures with a new, axiomatically-founded measure that admits multiple interpretations. Standard inequality tests of rationality for any given reference class of preferences can be conveniently re-purposed to measure goodness-of-fit with that class. Another advantage of our approach is that it is applicable in any context where the first-order approach is meaningful (e.g., convex budget sets arising from progressive taxation). We apply these ideas to shed new light on existing portfolio-choice data.

scholarly journals Priestley duality for MV-algebras and beyond

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Wesley Fussner ◽  
Mai Gehrke ◽  
Samuel J. van Gool ◽  
Vincenzo Marra
Keyword(s):  
Large Class ◽  
Order Conditions ◽  
Enriched Environment ◽  
Priestley Duality ◽  
Distributive Lattices ◽  
First Order ◽  
Dual Spaces ◽  
Binary Operations ◽  
New Perspective ◽  
Mv Algebras

Abstract We provide a new perspective on extended Priestley duality for a large class of distributive lattices equipped with binary double quasioperators. Under this approach, non-lattice binary operations are each presented as a pair of partial binary operations on dual spaces. In this enriched environment, equational conditions on the algebraic side of the duality may more often be rendered as first-order conditions on dual spaces. In particular, we specialize our general results to the variety of MV-algebras, obtaining a duality for these in which the equations axiomatizing MV-algebras are dualized as first-order conditions.

scholarly journals Constraints in models of production and cost via slack-based measures

2021 ◽  
Author(s):  
Caroline Khan ◽  
Mike G. Tsionas
Keyword(s):  
Power Generation ◽  
Stochastic Frontier ◽  
Inequality Constraints ◽  
Order Conditions ◽  
Flexible Functional Forms ◽  
Cost Share ◽  
First Order ◽  
Stochastic Frontier Models ◽  
Endogenous Variables ◽  
Functional Forms

AbstractIn this paper, we propose the use of stochastic frontier models to impose theoretical regularity constraints (like monotonicity and concavity) on flexible functional forms. These constraints take the form of inequalities involving the data and the parameters of the model. We address a major concern when statistically endogenous variables are present in these inequalities. We present results with and without endogeneity in the inequality constraints. In the system case (e.g., cost-share equations) or more generally, in production function-first-order conditions case, we detect an econometric problem which we solve successfully. We provide an empirical application to US electric power generation plants during 1986–1997, previously used by several authors.

A Framework for Choice Modeling in Usage Context-Based Design

2010 ◽  
Author(s):  
Lin He ◽  
Christopher Hoyle ◽  
Wei Chen ◽  
Jiliang Wang ◽  
Bernard Yannou
Keyword(s):  
Data Collection ◽  
Product Design ◽  
Consumer Choice ◽  
Choice Model ◽  
Consumer Preferences ◽  
Choice Modeling ◽  
Product Performance ◽  
Choice Data ◽  
Modeling Framework ◽  
Usage Context

Usage Context-Based Design (UCBD) is an area of growing interest within the design community. A framework and a step-by-step procedure for implementing consumer choice modeling in UCBD are presented in this work. To implement the proposed approach, methods for common usage identification, data collection, linking performance with usage context, and choice model estimation are developed. For data collection, a method of try-it-out choice experiments is presented. This method is necessary to account for the different choices respondents make conditional on the given usage context, which allows us to examine the influence of product design, customer profile, usage context attributes, and their interactions, on the choice process. Methods of data analysis are used to understand the collected choice data, as well as to understand clusters of similar customers and similar usage contexts. The choice modeling framework, which considers the influence of usage context on both the product performance, choice set and the consumer preferences, is presented as the key element of a quantitative usage context-based design process. In this framework, product performance is modeled as a function of both the product design and the usage context. Additionally, usage context enters into an individual customer’s utility function directly to capture its influence on product preferences. The entire process is illustrated with a case study of the design of a jigsaw.

scholarly journals The holistic work engagement: A study In indonesia oil palm industry

2018 ◽  
Vol 7 (4.9) ◽  
pp. 1
Author(s):  
Nopriadi Saputra ◽  
Sasmoko . ◽  
Sri Bramantoro Abdinagoro
Keyword(s):  
Human Resource Development ◽  
Work Engagement ◽  
Oil Palm ◽  
Goodness Of Fit ◽  
Measurement Model ◽  
Validity And Reliability ◽  
First Order ◽  
Confirmatory Factor ◽  
Order Construct ◽  
Oil Palm Industry

Industry 4.0 encourages organizations to implement holistic framework in human resource development. It is imperative to align concept of work engagement into holistic framework. This study aims to conduct confirmatory factor analysis on holistic work engagement concept and was conducted on 477 supervisors and managers from Indonesia oil palm industry. The data was analyzed by using Lisrel 9.30 and the result explains that the measurement model of holistic work engagement has adequate validity and reliability. The measurement model of the higher order construct has better goodness of fit than first order one. 

scholarly journals Revealed Preferences over Risk and Uncertainty

2020 ◽  
Vol 110 (6) ◽  
pp. 1782-1820 ◽  
Author(s):  
Matthew Polisson ◽  
John K.-H. Quah ◽  
Ludovic Renou
Keyword(s):  
Portfolio Choice ◽  
Efficiency Index ◽  
Revealed Preferences ◽  
Choice Data ◽  
Risk And Uncertainty ◽  
Infinite Domains ◽  
Disappointment Aversion ◽  
Rank Dependent Utility ◽  
Using Data ◽  
Budgetary Choice

We develop a nonparametric method, called Generalized Restriction of Infinite Domains (GRID), for testing the consistency of budgetary choice data with models of choice under risk and under uncertainty. Our test can allow for risk-loving and elation-seeking attitudes, or it can require risk aversion. It can also be used to calculate, via Afriat’s efficiency index, the magnitude of violations from a particular model. We evaluate the performance of various models under risk (expected utility, disappointment aversion, rank-dependent utility, and stochastically monotone utility) using data collected from several recent portfolio choice experiments. (JEL C14, D11, D12, D81)

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