Journal articles on the topic 'Utility theory Econometric models'
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1
Lewbel, Arthur. "Demand Systems With and Without Errors." American Economic Review 91, no. 3 (June 1, 2001): 611–18. http://dx.doi.org/10.1257/aer.91.3.611.
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Revealed preference theory assumes that each consumer has demands that are rational, meaning that they arise from the maximization of his or her own utility function. In contrast, econometric or statistical demand models assume that each consumer's demands equal a rational systematic component derived from a common utility function, plus an individual-specific, additive error term. This paper reconciles these differences, by providing necessary and sufficient conditions for rationality of statistical demand models given individual consumer rationality. (JEL D11, D12, C30, C43)
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Zenina, Nadezda, and Arkady Borisov. "Transportation Mode Choice Analysis Based on Classification Methods." Scientific Journal of Riga Technical University. Computer Sciences 45, no. 1 (January 1, 2011): 49–53. http://dx.doi.org/10.2478/v10143-011-0041-2.
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Transportation Mode Choice Analysis Based on Classification MethodsMode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods - decision trees, discriminant analysis and multinomial logit. Experimental results have demonstrated satisfactory quality of classification.
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Basmann, Robert L. "A Theory of Serial Correlation of Stochastic Taste Changers in Direct Utility Functions." Econometric Theory 1, no. 2 (August 1985): 192–210. http://dx.doi.org/10.1017/s0266466600011130.
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Methods of maximum-likelihood search (eg., Hildreth-Lu) for single equations models with autocorrelated disturbances are not easily extended to the multi-equation systems encountered in econometric studies of consumer demand. The obstacle is the large dimension of the space of independent serial correlation coefficients to be partitioned and searched. This paper treats stochastic disturbance vectors in demand/expenditure systems as functions of random disturbances in consumer utility functions. It specifies marginal utilities to be products of a systematic function and a nonnegative random disturbance. Under this specification, three hypotheses that readily come to mind in the context of consumer theory drastically reduce the number of independent elements of serial covariance matrices. This in turn makes practicable the extension of maximum-likelihood search methods in the estimation of parameters of large demand systems.
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Bhatta, Bharat P. "Theoretical, methodological and practical issues of choice models." International Journal of Entrepreneurship and Economic Issues 1, no. 1 (February 26, 2018): 21–37. http://dx.doi.org/10.32674/ijeei.v1i0.4.
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This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa.
Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation
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Juhl, Sebastian. "Measurement Uncertainty in Spatial Models: A Bayesian Dynamic Measurement Model." Political Analysis 27, no. 3 (November 9, 2018): 302–19. http://dx.doi.org/10.1017/pan.2018.35.
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According to spatial models of political competition, parties strategically adjust their ideological positions to movements made by rival parties. Spatial econometric techniques have been proposed to empirically model such interdependencies and to closely convert theoretical expectations into statistical models. Yet, these models often ignore that the parties’ ideological positions are latent variables and, as such, accompanied by a quantifiable amount of uncertainty. As a result, the implausible assumption of perfectly measured covariates impedes a proper evaluation of theoretical propositions. In order to bridge this gap between theory and empirics, the present work combines a spatial econometric model and a Bayesian dynamic item response model. The proposed model accurately accounts for measurement uncertainty and simultaneously estimates the parties’ ideological positions and their spatial interdependencies. To verify the model’s utility, I apply it to recorded votes from the sixteen German state legislatures in the period from 1988 to 2016. While exhibiting a notable degree of ideological mobility, the results indicate only moderate spatial dependencies among parties of the same party family. More importantly, the analysis illustrates how measurement uncertainty can lead to substantively different results which stresses the importance of appropriately incorporating theoretical expectations into statistical models.
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Hill, Brian. "A Non‐Bayesian Theory of State‐Dependent Utility." Econometrica 87, no. 4 (2019): 1341–66. http://dx.doi.org/10.3982/ecta15916.
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Many decision situations involve two or more of the following divergences from subjective expected utility: imprecision of beliefs (or ambiguity), imprecision of tastes (or multi‐utility), and state dependence of utility. This paper proposes and characterizes a model of uncertainty averse preferences that can simultaneously incorporate all three phenomena. The representation supports a principled separation of (imprecise) beliefs and (potentially state‐dependent, imprecise) tastes. Moreover, the representation permits comparative statics separating the roles of beliefs and tastes, and is modular: it easily delivers special cases involving various combinations of the phenomena, as well as state‐dependent multi‐utility generalizations covering popular ambiguity models.
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Chade, Hector, Jan Eeckhout, and Lones Smith. "Sorting through Search and Matching Models in Economics." Journal of Economic Literature 55, no. 2 (June 1, 2017): 493–544. http://dx.doi.org/10.1257/jel.20150777.
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Toward understanding assortative matching, this is a self-contained introduction to research on search and matching. We first explore the nontransferable and perfectly transferable utility matching paradigms, and then a unifying imperfectly transferable utility matching model. Motivated by some unrealistic predictions of frictionless matching, we flesh out the foundational economics of search theory. We then revisit the original matching paradigms with search frictions. We finally allow informational frictions that often arise, such as in college-student sorting. (JEL C78, D82, D83, I23, J12)
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Assaf, Matheus, and Pedro Garcia Duarte. "Utility Matters." History of Political Economy 52, no. 5 (October 1, 2020): 863–94. http://dx.doi.org/10.1215/00182702-8671855.
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The present-day standard textbook narrative on the history of growth theory usually takes Robert Solow’s 1956 contribution as a key starting point, which was extended by David Cass and Tjalling Koopmans in 1965 by introducing an intertemporal maximization problem that defines the saving ratio in the economy. However, the road connecting Solow to the Ramsey-Cass-Koopmans model is not so straightforward. We argue that in order to understand Koopmans’s contribution, we have to go to the activity analysis literature that started before Solow 1956 and never had him as a central reference. We stress the role played by Edmond Malinvaud, with whom Koopmans interacted closely, and take his travel from the French milieu of mathematical economics to the Cowles Commission in 1950-51 and back to France as a guiding line. The rise of turnpike theory in the end of the 1950s generated a debate on the choice criteria of growth programs, opposing the productive efficiency typical of these models to the utilitarian approach supported by Malinvaud and Koopmans. The Vatican Conference of 1963, where Koopmans presented a first version of his 1965 model, was embedded in this debate. We argue that Malinvaud’s (and Koopmans’s) contributions were crucial to steer the activity analysis literature toward a utilitarian analysis of growth paths.
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Starmer, Chris. "Developments in Non-Expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk." Journal of Economic Literature 38, no. 2 (June 1, 2000): 332–82. http://dx.doi.org/10.1257/jel.38.2.332.
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This article reviews recent developments in the economic theory of individual decision making under risk. Since the 1950s it has been known that individual choices violate the standard model of expected utility in predictable ways. Considerable research effort has now been devoted to the project of developing a superior descriptive model. Following an overview of non-expected utility theories which distinguishes between “conventional” and “non-conventional” approaches, the paper seeks to assess these alternative models in terms of empirical success (using laboratory and field data) and theoretical usefulness. The closing sections reflect on some new directions emerging in this literature.
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Chung, Hui-Kuan, Paul Glimcher, and Agnieszka Tymula. "An Experimental Comparison of Risky and Riskless Choice—Limitations of Prospect Theory and Expected Utility Theory." American Economic Journal: Microeconomics 11, no. 3 (August 1, 2019): 34–67. http://dx.doi.org/10.1257/mic.20170112.
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Prospect theory, used descriptively for decisions under both risk and certainty, presumes concave utility over gains and convex utility over losses; a pattern widely seen in lottery tasks. Although such discontinuous gain-loss reference-dependence is also used to model riskless choices, only limited empirical evidence supports this use. In incentive-compatible experiments, we find that gain-loss reflection effects are not observed under riskless choice as predicted by prospect theory, even while in the same subjects gain-loss reflection effects are observed under risk. Our empirical results challenge the application of choice models across both risky and riskless domains. (JEL C91, D12, D81)
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Helzner, Jeffrey. "On the Application of Multiattribute Utility Theory to Models of Choice." Theory and Decision 66, no. 4 (March 23, 2008): 301–15. http://dx.doi.org/10.1007/s11238-008-9099-x.
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Erfanian, Elham, and Alan R. Collins. "Charges for Water and Access: What Explains the Differences Among West Virginian Municipalities?" Water Economics and Policy 04, no. 04 (October 2018): 1850017. http://dx.doi.org/10.1142/s2382624x18500170.
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Examining both spatial and non-spatial econometric analyses with a dataset of 125 municipal water utilities, we investigate utility cost and community factors that explain variation in residential user charges and monthly access charges for water. The results of water charges model are consistent with the theory of water cost determination as water source, debt, and economies of size plus scale influence residential consumer charges for water. Both models (water charges and minimum monthly access) displayed positive spillover effects, although the only variable in either model with a significant indirect effect is water charges on minimum monthly access charges. Based upon model results, ground water use by utilities lowers water charges and is estimated to save residential customers in West Virginia over $3.6 million annually. West Virginia households typically pay far below the OECD standard of 3 to 5% of household income for municipal water, which may explain why socioeconomic factors do not influence minimum monthly charges for access.
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Fumagalli, Roberto. "THE FUTILE SEARCH FOR TRUE UTILITY." Economics and Philosophy 29, no. 3 (October 15, 2013): 325–47. http://dx.doi.org/10.1017/s0266267113000291.
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In traditional decision theory, utility is regarded as a mathematical representation of preferences to be inferred from agents’ choices. In the recent literature at the interface between economics, psychology and neuroscience, several authors argue that economists could develop more predictive and explanatory models by incorporating insights concerning individuals’ hedonic experiences. Some go as far as to contend that utility is literally computed by specific neural areas and urge economists to complement or substitute their notion of utility with some neuro-psychological construct. In this paper, I distinguish three notions of utility that are frequently mentioned in debates about decision theory and examine some critical issues regarding their definition and measurability. Moreover, I provide various empirical and conceptual reasons to doubt that economists should base decision theoretic analyses on some neuro-psychological notion of utility.
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Cheng, Long, Xuewu Chen, Ming Wei, Jingxian Wu, and Xianyao Hou. "Modeling Mode Choice Behavior Incorporating Household and Individual Sociodemographics and Travel Attributes Based on Rough Sets Theory." Computational Intelligence and Neuroscience 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/560919.
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Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxing county which contains information on both household and individual travel behaviors for model estimation and evaluation. The knowledge is presented in the form of easily understood IF-THEN statements or rules which reveal how each attribute influences mode choice behavior. These rules are then used to predict travel mode choices from information held about previously unseen individuals and the classification performance is assessed. The rough sets model shows high robustness and good predictive ability. The most significant condition attributes identified to determine travel mode choices are gender, distance, household annual income, and occupation. Comparative evaluation with the MNL model also proves that the rough sets model gives superior prediction accuracy and coverage on travel mode choice modeling.
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Hamada, Mahmoud, Michael Sherris, and John van der Hoek. "Dynamic Portfolio Allocation, the Dual Theory of Choice and Probability Distortion Functions." ASTIN Bulletin 36, no. 01 (May 2006): 187–217. http://dx.doi.org/10.2143/ast.36.1.2014149.
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Standard optimal portfolio choice models assume that investors maximise the expected utility of their future outcomes. However, behaviour which is inconsistent with the expected utility theory has often been observed. In a discrete time setting, we provide a formal treatment of risk measures based on distortion functions that are consistent with Yaari’s dual (non-expected utility) theory of choice (1987), and set out a general layout for portfolio optimisation in this non-expected utility framework using the risk neutral computational approach. As an application, we consider two particular risk measures. The first one is based on the PH-transform and treats the upside and downside of the risk differently. The second one, introduced by Wang (2000) uses a probability distortion operator based on the cumulative normal distribution function. Both risk measures rank-order prospects and apply a distortion function to the entire vector of probabilities.
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Baillon, Aurélien, and Han Bleichrodt. "Testing Ambiguity Models through the Measurement of Probabilities for Gains and Losses." American Economic Journal: Microeconomics 7, no. 2 (May 1, 2015): 77–100. http://dx.doi.org/10.1257/mic.20130196.
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This paper reports on two experiments that test the descriptive validity of ambiguity models using a natural source of uncertainty (the evolution of stock indices) and both gains and losses. We observed violations of probabilistic sophistication, violations that imply a fourfold pattern of ambiguity attitudes: ambiguity aversion for likely gains and unlikely losses and ambiguity seeking for unlikely gains and likely losses. Our data are most consistent with prospect theory and, to a lesser extent, α-maxmin expected utility and Choquet expected utility. Models with uniform ambiguity attitudes are inconsistent with most of the observed behavioral patterns. (JEL D81, D83, G11, G12, G14)
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Quiggin, John. "Production under uncertainty and choice under uncertainty in the emergence of generalized expected utility theory." Theory and Decision 92, no. 3-4 (February 28, 2022): 717–29. http://dx.doi.org/10.1007/s11238-022-09875-y.
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AbstractInterest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. The development of generalized expected utility models raised the question of whether such models could be used in the analysis of applied problems such as those involving production under uncertainty. Finally, the revival of the state-contingent approach led to the recognition of a fundamental duality between choice problems and production problems.
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Epper, Thomas, and Helga Fehr-Duda. "Comment on “Risk Preferences Are Not Time Preferences”: Balancing on a Budget Line." American Economic Review 105, no. 7 (July 1, 2015): 2261–71. http://dx.doi.org/10.1257/aer.20130420.
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In a recent experimental study of intertemporal risky decision making, Andreoni and Sprenger (2012) find that subjects exhibit a preference for intertemporal diversification, which is inconsistent with discounted expected utility theory. It was claimed that their results are also at odds with models involving probability weighting, such as rank-dependent utility and cumulative prospect theory. Here we demonstrate, however, that rank-dependent probability weighting explains intertemporal diversification if decision makers care about portfolio risk. Moreover, we provide a unified account of all of Andreoni and Sprenger's key findings. (JEL C91, D81, D91)
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Xie, Chi, Jinyang Lu, and Emily Parkany. "Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks." Transportation Research Record: Journal of the Transportation Research Board 1854, no. 1 (January 2003): 50–61. http://dx.doi.org/10.3141/1854-06.
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Among discrete choice problems, travel mode choice modeling has received the most attention in the travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem in which multiple human behavioral patterns reflected by explanatory variables determine the choices between alternatives or classes. The capability and performance of two emerging pattern recognition data mining methods, decision trees (DT) and neural networks (NN), for work travel mode choice modeling were investigated. Models based on these two techniques are specified, estimated, and comparatively evaluated with a traditional multinomial logit (MNL) model. For comparison, a unique three-layer formulation of the MNL model is presented. The similarities and differences of the models' mechanisms and structures are identified, and the mechanisms and structures in the models' specifications and estimations are compared. Two performance measures, individual prediction rate and aggregate prediction rate, which represent the prediction accuracies for individual and mode aggregate levels, respectively, were applied to evaluate and compare the performances of the models. Diary data sets from the San Francisco, California, Bay Area Travel Survey 2000 were used for model estimation and evaluation. The prediction results show that the two data mining models offer comparable but slightly better performances than the MNL model in terms of the modeling results, while the DT model demonstrates the highest estimation efficiency and most explicit interpretability, and the NN model gives a superior prediction performance in most cases.
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Kedia, Ashu Shivkumar, Krishna Bhuneshwar Saw, and Bhimaji Krishnaji Katti. "FUZZY LOGIC APPROACH IN MODE CHOICE MODELLING FOR EDUCATION TRIPS: A CASE STUDY OF INDIAN METROPOLITAN CITY." TRANSPORT 30, no. 3 (October 2, 2015): 286–93. http://dx.doi.org/10.3846/16484142.2015.1081279.
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Urban population in India has increased significantly from 62 million in 1951 to 378 million in 2011 in six decades. It is estimated to reach 540 million by the year 2021. This reflects on likely pressure on urban transportation system. The situation necessarily calls plans for balanced personal and public transport system. Mandatory trips bear more importance in this regard owing to their higher share in urban trips. Mode share and their choice behaviour in estimation of such trips play vital role in analysing and boosting sustainable transportation. Logit modelling approach is the conventional method generally adopted for analysing mode choice behaviour, which is based on the principle of random utility maximization derived from econometric theory. However, such models cannot address uncertainity prevailing in the choice decisions. On the contrary, fuzzy logic bypasses the binary crisp derivations of the inputs and accepts multivalued inputs in linguistic expressions, which make possible to resemble the human behaviour closely. Therefore, the attempt here is to develop fuzzy logic based mode choice model for education trips, which constitutes a good share in mandatory trips by covering various income groups of Indian society.
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Diecidue, Enrico, Haim Levy, and Moshe Levy. "Probability Dominance." Review of Economics and Statistics 102, no. 5 (December 2020): 1006–20. http://dx.doi.org/10.1162/rest_a_00890.
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The most commonly employed paradigms for decision making under risk are expected utility, prospect theory, and regret theory. We examine the simple heuristic of maximizing the probability of being ahead, which in some natural economic situations may be in contradiction to all three of the above fundamental paradigms. We test whether this heuristic, which we call probability dominance (PD), affects decisions under risk. We set up head-to-head situations where all preferences of a given class (expected utility, original or cumulative prospect theory, or regret theory) favor one alternative yet PD favors the other. Our experiments reveal that 49% of subjects' choices are aligned with PD in contradiction to any form of expected utility or prospect theory maximization; 73% are aligned with PD as opposed to preferences under risk aversion and under original and cumulative prospect theory preferences; and 68% to 76% are aligned with PD contradicting preferences under regret theory. We conclude that probability dominance substantially affects choices and should therefore be incorporated into decision-making models. We show that PD has significant economic consequences. The PD heuristic may have evolved through situations of winner-take-all competition.
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Cerroni, Simone, Sandra Notaro, and Roberta Raffaelli. "Beliefs and preferences for food-safety policies: a discrete choice model under uncertainty." European Review of Agricultural Economics 46, no. 5 (November 14, 2018): 769–99. http://dx.doi.org/10.1093/erae/jby038.
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Abstract Outcomes of food policies are highly uncertain. Therefore, the public’s support for these policies depends on individuals’ beliefs and the provision of scientific information. Using data collected from a discrete choice experiment survey, we explore whether new information regarding a food-safety policy influences respondents’ support, while controlling for risk and time preferences. Additionally, we examine if support depends on whether information is perceived as either good or bad news. Results from the estimation of parametric error component logit models, based on expected utility theory and rank dependent utility theory, suggest that good and bad news affects preferences and welfare measures.
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Ginevičius, Romualdas, and Algirdas Krivka. "APPLICATION OF GAME THEORY FOR DUOPOLY MARKET ANALYSIS." Journal of Business Economics and Management 9, no. 3 (September 30, 2008): 207–17. http://dx.doi.org/10.3846/1611-1699.2008.9.207-217.
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The paper provides the analysis of game theory models application to identify duopoly market equilibrium (quantities sold and market prices), to evaluate and compare the results of enterprises in a market. The purpose of the analysis is to determine to what extent theoretical models correspond to real life, that is how reliable they are in supporting and estimating decisions of duopoly companies, fortifying market prices and quantities sold, evaluating company's competing positions and possibilities for decision co‐ordination. To describe discrete strategies equilibrium the “Prisoner's Dilemma” model is applied to a hypothetic market entrance game with possible side payments. Further analysis of the market entrance game incorporates mixed strategies based “Matching Pennies” model in case discrete strategies equilibrium does not exist. Continuous strategies are described analyzing hypothetic duopoly by applying Cournot, Stackelberg and Bertrand models. The first and the second mover advantage issues are raised comparing outcomes of dynamic Stackelberg and Bertrand games for a leader and a follower. Stability and utility of cartel agreement for its participants is mathematically supported with the help of a multi‐step repeated Cournot game. Having described, compared and applied the main game theory models to artificial duopoly market situations, the author passes over to the comparative analysis of the models’ weaknesses and problems related to their practical application.
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Bhattacharya, Debopam. "The Empirical Content of Binary Choice Models." Econometrica 89, no. 1 (2021): 457–74. http://dx.doi.org/10.3982/ecta16801.
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An important goal of empirical demand analysis is choice and welfare prediction on counterfactual budget sets arising from potential policy interventions. Such predictions are more credible when made without arbitrary functional‐form/distributional assumptions, and instead based solely on economic rationality, that is, that choice is consistent with utility maximization by a heterogeneous population. This paper investigates nonparametric economic rationality in the empirically important context of binary choice. We show that under general unobserved heterogeneity, economic rationality is equivalent to a pair of Slutsky‐like shape restrictions on choice‐probability functions. The forms of these restrictions differ from Slutsky inequalities for continuous goods. Unlike McFadden–Richter's stochastic revealed preference, our shape restrictions (a) are global, that is, their forms do not depend on which and how many budget sets are observed, (b) are closed form, hence easy to impose on parametric/semi/nonparametric models in practical applications, and (c) provide computationally simple, theory‐consistent bounds on demand and welfare predictions on counterfactual budge sets.
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Li, Dewei, Yufang Gao, Ruoyi Li, and Weiteng Zhou. "Hybrid Random Regret Minimization and Random Utility Maximization in the Context of Schedule-Based Urban Rail Transit Assignment." Journal of Advanced Transportation 2018 (December 18, 2018): 1–28. http://dx.doi.org/10.1155/2018/9789316.
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Route choice is one of the most critical passenger behaviors in public transit research. The utility maximization theory is generally used to model passengers’ route choice behavior in a public transit network in previous research. However, researchers have found that passenger behavior is far more complicated than a single utility maximization assumption. Some passengers tend to maximize their utility while others would minimize their regrets. In this paper, a schedule-based transit assignment model based on the hybrid of utility maximization and regret minimization is proposed to study the passenger route choice behavior in an urban rail transit network. Firstly, based on the smart card data, the space-time expanded network in an urban rail transit was constructed. Then, it adapts the utility maximization (RUM) and the regret minimization theory (RRM) to analyze and model the passenger route choice behavior independently. The utility values and the regret values are calculated with the utility and the regret functions. A transit assignment model is established based on a hybrid of the random utility maximization and the random regret minimization (RURM) with two kinds of hybrid rules, namely, attribute level hybrid and decision level hybrid. The models are solved by the method of successive algorithm. Finally, the hybrid assignment models are applied to Beijing urban rail transit network for validation. The result shows that RRM and RUM make no significant difference for OD pairs with only two alternative routes. For those with more than two alternative routes, the performance of RRM and RUM is different. RRM is slightly better than RUM in some of the OD pairs, while for the other OD pairs, the results are opposite. Moreover, it shows that the crowd would only influence the regret value of OD pair with more commuters. We conclude that compared with RUM and RRM, the hybrid model RURM is more general.
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Chambers, Christopher P., Federico Echenique, and Nicolas S. Lambert. "Recovering Preferences From Finite Data." Econometrica 89, no. 4 (2021): 1633–64. http://dx.doi.org/10.3982/ecta17845.
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We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying “true” preference. Our conditions are weak and, therefore, valid in a wide range of economic environments. We develop applications to expected utility theory, choice over consumption bundles, and menu choice. Our framework unifies the revealed preference tradition with models that allow for errors.
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Sobel, Joel. "Interdependent Preferences and Reciprocity." Journal of Economic Literature 43, no. 2 (May 1, 2005): 392–436. http://dx.doi.org/10.1257/0022051054661530.
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Experiments, ethnography, and introspection provide evidence economic agents do not act to maximize their narrowly defined self interest. Expanding the domain of preferences to include the utility of others provides a coherent way to extend rational choice theory. There are two approaches for including extended or social preferences in strategic models. One posits that agents have extended preferences, but maintains the conventional assumption that these preferences are stable. Prominent examples of this approach permit agents to exhibit concern for status, inequality, and social welfare. The other approach permits the strategic context to determine the nature of individual preferences. Context-dependent preferences can capture the possibility that agents are motivated in part by reciprocity. They may sacrifice personal consumption in order to lower the utility of unkind agents or to raise the utility of kind agents. This paper surveys the evidence in favor of social preferences and describes the implications of the leading theoretical models of extended preferences. It presents behavioral assumptions that characterize different types of social preferences. It investigates the extent to which social preferences may arise as the limit of evolutionary processes. It discusses the relationship between norms of reciprocity and social preferences in repeated interactions.
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Wieland, Thomas. "Spatial Shopping Behavior in a Multi-Channel Environment: A Discrete Choice Model Approach." REGION 8, no. 2 (August 4, 2021): 1–27. http://dx.doi.org/10.18335/region.v8i2.361.
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Spatial impacts of online shopping are discussed frequently in retail geography. Here, online shopping is mostly regarded as a central driver of competition for physical retailing and its locations, such as town centers or malls. Due to its high popularity, cross-channel shopping is sometimes considered to be a support for physical retailing. However, traditional retail location theory does not consider shopping channels other than in-store shopping. Furthermore, although online shopping is far too important to be neglected in examining consumer spatial shopping behavior, there is an obvious lack in the previous literature towards incorporating multi- and cross-channel shopping into store choice models. The present study aims to identify the main drivers of store choice on the basis that both in-store and online shopping alternatives are available, as well as the opportunity for cross-channel shopping. Taking into account previous literature on both physical store choice and multi-channel shopping, hypotheses on the impact of different shopping transaction costs (such as travel time, delivery charges, or uncertainty with respect to the stores' assortment) were derived. Based on a representative consumer survey, real past shopping decisions in three retail sectors (groceries, consumer electronics [CE], and furniture) were collected. The econometric analysis of empirical store choices was performed using a nested logit model which includes both physical and online stores. The results confirm several assumptions of classical retail location theory as well as previous findings from single-firm studies and stated choice experiments on multi-channel shopping behavior. Travel time to physical stores reduces consumer utility and store choice probability, respectively. Consumer sensitivity towards travel time decreases with decreasing purchase frequency of the desired goods. Delivery charges also decrease the likelihood of choosing a store. The impact of cross-channel integration on store choice (assuming the reduction of consumer transaction costs) is considerably lower than expected and differs between retail sectors. While furniture retailers profit from enabling cross-channel shopping, there is no such competitive advantage found for grocery and CE retailers. The positive effect of assortment on condition of diminishing marginal utility is confirmed for grocery stores and CE stores, but not for furniture stores. From a theoretical perspective, this study shows that multi- and cross-channel shopping behavior does not contradict the main thoughts of classical retail location theory. From a practical perspective, the study is a contribution as store choice models play a significant role in both business location planning and governmental land use planning.
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Barseghyan, Levon, Francesca Molinari, Ted O’Donoghue, and Joshua C. Teitelbaum. "Estimating Risk Preferences in the Field." Journal of Economic Literature 56, no. 2 (June 1, 2018): 501–64. http://dx.doi.org/10.1257/jel.20161148.
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We survey the literature on estimating risk preferences using field data. We concentrate our attention on studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We review a number of models of risk preferences—including both expected utility (EU) theory and non-EU models—that have been estimated using field data, and we highlight issues related to identification and estimation of such models using field data. We then survey the literature, giving separate treatment to research that uses individual-level data (e.g., property-insurance data) and research that uses aggregate data (e.g., betting-market data). We conclude by discussing directions for future research. ( JEL C51, D11, D81, D82, D83, G22, I13)
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Barberis, Nicholas C. "Thirty Years of Prospect Theory in Economics: A Review and Assessment." Journal of Economic Perspectives 27, no. 1 (February 1, 2013): 173–96. http://dx.doi.org/10.1257/jep.27.1.173.
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In 1979, Daniel Kahneman and Amos Tversky, published a paper in Econometrica titled “Prospect Theory: An Analysis of Decision under Risk.” The paper presented a new model of risk attitudes called “prospect theory,” which elegantly captured the experimental evidence on risk taking, including the documented violations of expected utility. More than 30 years later, prospect theory is still widely viewed as the best available description of how people evaluate risk in experimental settings. However, there are still relatively few well-known and broadly accepted applications of prospect theory in economics. One might be tempted to conclude that, even if prospect theory is an excellent description of behavior in experimental settings, it is less relevant outside the laboratory. In my view, this lesson would be incorrect. Over the past decade, researchers in the field of behavioral economics have put a lot of thought into how prospect theory should be applied in economic settings. This effort is bearing fruit. A significant body of theoretical work now incorporates the ideas in prospect theory into more traditional models of economic behavior, and a growing body of empirical work tests the predictions of these new theories. I am optimistic that some insights of prospect theory will eventually find a permanent and significant place in mainstream economic analysis.
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Li, Jinlu, and Shuanglin Lin. "EXISTENCE AND UNIQUENESS OF STEADY-STATE EQUILIBRIUM IN A GENERALIZED OVERLAPPING GENERATIONS MODEL." Macroeconomic Dynamics 16, S3 (June 9, 2011): 299–311. http://dx.doi.org/10.1017/s1365100510000878.
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Galor and Ryder [Journal of Economic Theory 49 (1989), 360–375] establish conditions for the existence of equilibrium in a Diamond-type overlapping-generations (OLG) model. Although theoretically appealing, these conditions are implicit and not convenient to apply. This paper provides explicit and easily applied conditions for the existence and uniqueness of steady-state equilibrium, with which one only needs to check the first derivatives of the production and utility functions and their interactions, with no need to solve the optimization problem. Our theorems on the existence and uniqueness of steady-state equilibrium can be applied to a larger class of OLG models that do not require second-order differentiability of the production and utility functions. We present examples to show how to check the existence and uniqueness of equilibrium.
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Tanaka, Tomomi, Colin F. Camerer, and Quang Nguyen. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam." American Economic Review 100, no. 1 (March 1, 2010): 557–71. http://dx.doi.org/10.1257/aer.100.1.557.
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We conducted experiments in Vietnamese villages to determine the predictors of risk and time preferences. In villages with higher mean income, people are less loss-averse and more patient. Household income is correlated with patience but not with risk. We expand measurements of risk and time preferences beyond expected utility and exponential discounting, replacing those models with prospect theory and a three-parameter hyperbolic discounting model. Comparable risk parameter estimates have been found for Chinese farmers, using our method. (C83, D12, O12, P38)
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Cubitt, Robin, Gijs van de Kuilen, and Sujoy Mukerji. "Discriminating Between Models of Ambiguity Attitude: a Qualitative Test." Journal of the European Economic Association 18, no. 2 (April 1, 2019): 708–49. http://dx.doi.org/10.1093/jeea/jvz005.
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AbstractDuring recent decades, many new models have emerged in pure and applied economic theory according to which agents’ choices may be sensitive to ambiguity in the uncertainty that faces them. The exchange between Epstein (2010) and Klibanoff et al. (2012) identified a notable behavioral issue that distinguishes sharply between two classes of models of ambiguity sensitivity that are importantly different. The two classes are exemplified by the α-maxmin expected utility (MEU) model and the smooth ambiguity model, respectively; and the issue is whether or not a desire to hedge independently resolving ambiguities contributes to an ambiguity-averse agent's preference for a randomized act. Building on this insight, we implement an experiment whose design provides a qualitative test that discriminates between the two classes of models. Among subjects identified as ambiguity sensitive, we find greater support for the class exemplified by the smooth ambiguity model; the relative support is stronger among subjects identified as ambiguity averse. This finding has implications for applications that rely on specific models of ambiguity preference.
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Ballandonne, Matthieu, and Goulven Rubin. "Robert Solow’s Non-Walrasian Conception of Economics." History of Political Economy 52, no. 5 (October 1, 2020): 827–61. http://dx.doi.org/10.1215/00182702-8671843.
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The neoclassical synthesis has been defined as a bridge between Keynes-ian theory and Walrasian general equilibrium theory. The aim of this article is to show that founders of the neoclassical synthesis were not homogenous in their appraisal of the importance of Walrasian theory. To do so, we focus on Robert Solow’s contributions as a case study and examine the history of his lifelong criticism of what he called “axiomatics.” According to Solow, the axiomatic approach aims at founding economics on one general and complex model based on first principles or axioms. In contrast, Solow advocated the use of a diversity of simple and partial models, which have practical utility, are realistic in their crucial assumptions, consider institutions and the evolving nature of the economy, and rely on common sense microfoundations. We conclude by suggesting that Solow can be characterized as Cournotian.
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Jamison, Julian C. "WELL-BEING AND NEUROECONOMICS." Economics and Philosophy 24, no. 3 (November 2008): 407–18. http://dx.doi.org/10.1017/s0266267108002046.
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Neuroscience can contribute to economics by inspiring new models, helping to distinguish models that have similar implications for readily available data, and guiding interpretations of decision-making processes by policy-makers. However, there is an additional less straightforward role for it to play: augmenting, along with survey data and other non-revealed-preference sources, assessments of well-being. The need for such augmentation lies in the slightly bizarre stance taken by modern economic theory, namely that economics is concerned only with choices and not with welfare per se. It is shown that this is neither historical nor at all necessary, even within the standard paradigm. Although neuroscience is by no means a panacea for determining true utility, which ultimately remains a subjective concept, it provides a uniquely useful complementary dataset.
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Tang, Tianpei, Hua Wang, Xizhao Zhou, and Hao Gong. "Understanding Electric Bikers’ Red-Light Running Behavior: Predictive Utility of Theory of Planned Behavior vs Prototype Willingness Model." Journal of Advanced Transportation 2020 (February 17, 2020): 1–13. http://dx.doi.org/10.1155/2020/7097302.
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To date, electric bikers’ (e-bikers’) red-light running (RLR) behavior is often viewed as one of the main contributors to e-bike-related accidents, especially for traffic scenarios with high e-bike ridership. In this paper, we aim to understand e-bikers’ RLR behavior based on structural equation modeling. Specifically, the predictive utility of the theory of planned behavior (TPB), prototype willingness model (PWM), and their combined form, TPB-PWM model, is used to analyze e-bikers’ RLR behavior, and a comparison analysis is made. The analyses of the three modeling approaches are based on the survey data collected from two online questionnaires, where more than 1,035 participant-completed questionnaires are received. The main findings in this paper are as follows: (i) Both PWM and TPB-PWM models could work better in characterizing e-bikers’ RLR behavior than the TPB model. The former two models explain more than 80% (81.3% and 81.4%, respectively) of the variance in e-bikers’ RLR behavior, which is remarkably higher than that of the TPB model (only 74.3%). (ii) It is also revealed that RLR willingness contributes more on influencing the RLR behavior than RLR intention, which implies that such behavior is dominated by social reactive decision-making rather than the reasoned one. (iii) Among the examined psychological factors, attitude, perceived behavioral control, past behavior, prototype perceptions (favorability and similarity), RLR intention, and RLR willingness were the crucial predictors of e-bikers’ RLR behavior. Our findings also support designing of more effective behavior-change interventions to better target e-bikers’ RLR behavior by considering the influence of the identified psychological factors.
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Kulkarni, Ankur A. "Games and teams with shared constraints." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2100 (July 10, 2017): 20160302. http://dx.doi.org/10.1098/rsta.2016.0302.
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Energy systems of the future are envisaged to encompass multiple interacting autonomous entities. The theory of games provides the foundations for the design and analysis of such systems. This paper reviews models and results that would be of use for such analysis. Classically, games have involved players whose strategies are coupled only through the dependence of utility functions on strategies of other players. However, in many practical settings in the energy domain, system-level limitations bind the choices players can make. In 1965, Rosen ( Econometrica 33 , 520–534 ( doi:10.2307/1911749 )) pioneered the study of a class of games where there is a common constraint, called a shared constraint , that couples the strategies available to the players. We discuss how this seemingly benign extension has important ramifications, ranging from the very definition of an equilibrium concept, to other key issues such as existence, uniqueness and efficiency of equilibria. We show how the presence of a shared constraint naturally leads to notions of a price and forms the motivations for more recent models. Although most of the paper has the character of a survey, occasionally we also prove new results. This article is part of the themed issue ‘Energy management: flexibility, risk and optimization’.
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Lakatos, Zsolt. "Do larger boards improve shareholder value creation? – Effects of the board size on business performance in Eastern Central Europe." Society and Economy 42, no. 3 (September 2020): 245–79. http://dx.doi.org/10.1556/204.2020.00007.
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AbstractThe aim of this study is to analyse the impact of board size on a firms' operational and market performance at the largest East Central European listed non-financial, non-public utility firms. The literature debates the effects of the size of the board. While the resource dependency theory supports a positive effect, the agency theory supports a negative impact on firm value. This question is rarely investigated in two-tiered corporate governance models. This paper estimates the effects of management board and supervisory board size, between 2007 and 2016. The results indicate that the effect of management board size depends heavily on the size of the observed company. In both fixed effects and GMM-type dynamic panel regression models, using Tobin's Q, market-to-book ratio, total shareholder value and ROA as firm performance measures, increase in management board size has a significant positive impact on firm performance; however, in the case of larger firms, the effect is significantly negative. Moreover, the increase in the ratio of outside directors has a positive impact on the firm's performance in all dynamic panel regression models and this effect is even more significant in Tobin's Q and market-to-book ratio models. This can indicate the effective monitoring role of the supervisory board.
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Britz, Wolfgang. "Implementing an Approximation of Cumulative Prospect Theory into Mixed Linear Programming – an Application to Bio-Economic Modelling at Farm-Scale Considering Crop Insurance." German Journal of Agricultural Economics 71, no. 4 (August 26, 2022): 184–203. http://dx.doi.org/10.30430/gjae.2022.0244.
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Many empirical studies have found Cumulative Prospect Theory (CPT) superior in depicting risk behavior compared to the expected utility approach and literature now offers also CPT related parameter estimates for European farmers. CPT combines two segments of utility functions, a convex, risk loving one for losses and a concave, risk averse one for gains, and assigns subjective weights to the pay-offs according to their cumulative probabilities. So far, no implementation of CPT into constrained optimization problems exists, allowing for instance, the simulation of risk management under CPT in farm-scale programming models. To close this gap, we propose to combine endogenous sorting of the pay-offs based on integer variables with a piece-wise linear approximation of the value function using SOS2 (Special Ordered Sets of Type 2) variables. The SOS2 variables are required to deal with the convexity of the loss segment of the utility function. The integer sorting assigns the weights to the pay-offs according to their cumulative probabilities, it requires that all pay-offs are equally likely. Simulating optimal uptake levels of variants of a hypothetical crop insurance product with an evolved bio-economic model at farm-scale serves a proof of concept. The model considers adjustments in the cropping plan and allows for partial insurance coverage, in opposite to existing studies which evaluate the uptake of crop insurance at fixed crop choices and depict coverage as a yes-no decision. The approximation error of the approach is found as negligible small and the numerical burden compared to optimization under risk neutrality as still acceptable. The proposed approximation approach is quite general and applicable for any utility function increasing in the pay-off value and does not require its differentiability. It can also be applied without probability weighting. The empirical application underlines that the approach generates the expected behavior when a risk reducing strategy, here crop insurance, is considered under CPT. Insured acreage generally increases with higher strike levels where more frequently occurring but lower crop damages are covered, and with reduced cost of the insurance products. Using crop insurance as a risk management strategy is found to interact with other measures such as adjustments in cropping shares. This underlines the usefulness of an approach which allows to optimize interacting risk management strategies at farm-scale under CPT, considering resource and other relevant constraints.
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Berent, Tomasz, Bogusław Bławat, Marek Dietl, Przemysław Krzyk, and Radosław Rejman. "Firm's default — new methodological approach and preliminary evidence from Poland." Equilibrium 12, no. 4 (December 31, 2017): 753–73. http://dx.doi.org/10.24136/eq.v12i4.39.
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Research background: Bankruptcy literature is populated with scores of (econometric) models ranging from Altman’s Z-score, Ohlson’s O-score, Zmijewski’s probit model to k-nearest neighbors, classification trees, support vector machines, mathematical programming, evolutionary algorithms or neural networks, all designed to predict financial distress with highest precision. We believe corporate default is also an important research topic to be identified with the prediction accuracy only. Despite the wealth of modelling effort, a unified theory of default is yet to be proposed.
Purpose of the article: Due to the disagreement both on the definition and hence the timing of default, as well as on the measurement of prediction accuracy, the comparison (of predictive power) of various models can be seriously misleading. The purpose of the article is to argue for the shift in research focus from maximizing accuracy to the analysis of the information capacity of predictors. By doing this, we may yet come closer to understanding default itself.
Methods: We critically appraise the bankruptcy research literature for its methodological variety and empirical findings. Default definitions, sampling procedures, in and out-of-sample testing and accuracy measurement are all scrutinized. In an empirical part, we use a double stochastic Poisson process with multi-period prediction horizon and a comprehensive database of some 15,000 Polish non-listed companies to illustrate the merits of our new approach to default modelling.
Findings & Value added: In the theoretical part, we call for the construction of a single unified default forecasting platform estimated for the largest dataset of firms possible to allow testing the utility of various sources of micro, mezzo, and macro information. Our preliminary empirical evidence is encouraging. The accuracy ratio amounts to 0.92 for t = 0 and drops to 0.81 two years ahead of default. We point to the pivotal role played by the information on firm’s liquidity (alternatively in profitability) and — in contrast to Altman’s tradition — hardly any contribution to predictive power of other financial ratios. Macro data is shown to be critical. It adds, on average, more than 10 p.p. to accuracy ratio. In the future, we hope to integrate listed and non-listed firms data into one model, ideally at higher frequency than annual, and include the information on firm's competitiveness position.
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Liu, Shixu, Jianchao Zhu, Said M. Easa, Lidan Guo, Shuyu Wang, Haoyu Wang, and Yijian Xu. "Travel Choice Behavior Model Based on Mental Accounting of Travel Time and Cost." Journal of Advanced Transportation 2021 (December 21, 2021): 1–21. http://dx.doi.org/10.1155/2021/4219396.
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This paper analyzes the utility calculation principle of travelers from the perspective of mental accounting and proposes a travel choice behavior model that considers travel time and cost (MA-TC model). Then, a questionnaire is designed to analyze the results of the travel choice under different decision-making scenarios. Model parameters are estimated using nonlinear regression, and the utility calculation principles are developed under different hypothetical scenarios. Then, new expressions for the utility function under deterministic and risky conditions are presented. For verification, the nonlinear correlation coefficient and hit rate are used to compare the proposed MA-TC model with the other two models: (1) the classical prospect theory with travel time and cost (PT-TC model) and (2) mental accounting based on the original hedonic editing criterion (MA-HE model). The results show that model parameters under deterministic and risky conditions are pretty different. In the deterministic case, travelers have similar sensitivity to the change in gain and loss of travel time and cost. The prediction accuracy of the MA-TC model is 3% lower than the PT-TC model and 6% higher than the MA-HE model. Under risky conditions, travelers are more sensitive to the change in loss than to the change in gain. Additionally, travelers tend to overestimate small probabilities and underestimate high probabilities when losing more than when gaining. The prediction accuracy of the MA-TC model is 2% higher than the PT-TC model and 6% higher than the MA-HE model.
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Camerer, Colin, George Loewenstein, and Drazen Prelec. "Neuroeconomics: How Neuroscience Can Inform Economics." Journal of Economic Literature 43, no. 1 (February 1, 2005): 9–64. http://dx.doi.org/10.1257/0022051053737843.
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Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the “black box” of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems (“executive function”) interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, “dual-process” models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are “rationally” neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in “theory of mind”, correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information. Who knows what I want to do? Who knows what anyone wants to do? How can you be sure about something like that? Isn't it all a question of brain chemistry, signals going back and forth, electrical energy in the cortex? How do you know whether something is really what you want to do or just some kind of nerve impulse in the brain. Some minor little activity takes place somewhere in this unimportant place in one of the brain hemispheres and suddenly I want to go to Montana or I don't want to go to Montana. (White Noise, Don DeLillo)
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Stamatopoulos, Theodoros V. "Cash Holdings in the Global Hotel Industry: Do Managers Act With Bounded Rationality When They Cannot Find Optimal Solutions?" Contemporary Economics 16, no. 4 (December 31, 2022): 443–59. http://dx.doi.org/10.5709/ce.1897-9254.493.
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The purpose of this paper is to contribute the relevant literature solving the puzzle of the excessive corporate cash. There are serious reasons to develop the falsifiable hypothesis “managers in the global hotel industry, act with bounded rationality in holding cash, when they cannot find optimal solutions”. First, it is explained why it is logical to have deviations from the neoclassical expected utility theory, coming not to be fully rational behavior. Second, it is shown that in complex and uncertain hotel industry’s environment, the decision making is better explained through the bounded rationality hy- pothesis (BRH), involving a search for alternatives, satisficing (satisfy + suffice), and adapting aspirations. Along with behavior-based economic theory, it seems that BRH can complete the trade-off and peck- ing order optimization-based models, that prevail the relevant literature, within the current economic “paradigm”. From a global sample of panel data of hotel industry for the period 2001-2018, the paper detects bounded rational behavior statistically, by not rejecting the null of relevant variables’ equal means in the tails of the cash distribution, and econometrically, by similarly estimated parameters to unrestricted and restricted models. Having found strong evidence in favour of the BRH for the “prof- itability” factor, balanced evidence for both boundedly and fully rational managers’ behavior, for the “value” and “investments” factors, while, no-evidence for the BRH in the case of the “size” factor. Thus, the complementarity of optimal with Simon’s satisficing solutions in the relevant cash management can benefit both investors and policy makers.
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Franke, Jurgen, Benedikt M. Potscher, and Ingmar R. Prucha. "Dynamic Nonlinear Econometric Models: Asymptotic Theory." Journal of the American Statistical Association 94, no. 446 (June 1999): 652. http://dx.doi.org/10.2307/2670192.
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de Jong, Robert M. "DYNAMIC NONLINEAR ECONOMETRIC MODELS—ASYMPTOTIC THEORY." Econometric Theory 16, no. 1 (February 2000): 127–30. http://dx.doi.org/10.1017/s0266466600001079.
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Benedikt Pötscher and Ingmar Prucha are two exceptional econometricians who combine an extraordinary knowledge of the statistics and econometrics literature with great analytical skills. Both are excellent mathematicians, and the comment that can be heard among mathematicians that econometricians are “self-made mathematicians” definitely does not apply to them. Therefore, given the task of writing an overview of asymptotic theory for minimization estimators for dependent processes, one could hardly imagine a better choice of writers for such a task. The result is a remarkable book that deserves to receive attention from an audience that is broader than experts in the field only.
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Zhang, Wei-Bin. "A neoclassical growth model with endogenous birth and mortality rates." Ekonomski anali 66, no. 231 (2021): 99–125. http://dx.doi.org/10.2298/eka2131099z.
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This study examines dynamic interdependence between different socio-cultural groups? birth rates, mortality rates, populations, wealth accumulation, and the allocation of time between work, leisure, and childcare. It emphasises the role of changes in human capital, technology, and preferences on birth and mortality rates and time allocations. The economic mechanism of wealth and income distribution is based on the Walrasian general equilibrium theory, and wealth accumulation is based on the Solow growth model. The paper uses a utility function proposed by Zhang (2015) to describe the behaviour of households. It also models group and gender differences in human capital, the propensity to have children, the propensity to use leisure time, and the efficiency of childcare. The paper uses differential equations to describe the dynamics of group differences in wealth, income, birth rates, mortality rates, and populations. I simulate a model to show the motion of the system and identify the existence of an equilibrium point. I also examine the effects on the dynamics of the economic system of changes in the propensity to have children and the propensity to save, and in gender differences in the propensity to use leisure, in human capital, and in emotional involvement in childcare.
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BROWN, DAVID P., and MICHAEL R. GIBBONS. "A Simple Econometric Approach for Utility-Based Asset Pricing Models." Journal of Finance 40, no. 2 (June 1985): 359–81. http://dx.doi.org/10.1111/j.1540-6261.1985.tb04962.x.
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Phillips, P. C. B. "Partially Identified Econometric Models." Econometric Theory 5, no. 2 (August 1989): 181–240. http://dx.doi.org/10.1017/s0266466600012408.
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This paper studies a class of models where full identification is not necessarily assumed. We term such models partially identified. It is argued that partially identified systems are of practical importance since empirical investigators frequently proceed under conditions that are best described as apparent identification. One objective of the paper is to explore the properties of conventional statistical procedures in the context of identification failure. Our analysis concentrates on two major types of partially identified model: the classic simultaneous equations model under rank condition failures; and time series spurious regressions. Both types serve to illustrate the extensions that are needed to conventional asymptotic theory if the theory is to accommodate partially identified systems. In many of the cases studied, the limit distributions fall within the class of compound normal distributions. They are simply represented as covariance matrix or scalar mixtures of normals. This includes time series spurious regressions, where representations in terms of functionals of vector Brownian motion are more conventional in recent research following earlier work by the author.
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Amador, Francisco Javier, and Elisabetta Cherchi. "Econometric Effects of Utility Order-Preserving Transformations in Discrete Choice Models." Networks and Spatial Economics 11, no. 3 (May 29, 2010): 419–38. http://dx.doi.org/10.1007/s11067-010-9134-7.
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Andrews, Donald W. K. "Chi-Square Diagnostic Tests for Econometric Models: Theory." Econometrica 56, no. 6 (November 1988): 1419. http://dx.doi.org/10.2307/1913105.
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