scholarly journals What Have We Learned from Structural Models?

2017 ◽  
Vol 107 (5) ◽  
pp. 287-292 ◽  
Author(s):  
Richard Blundell

A structural economic model is one where the structure of decision making is incorporated in the model specification. Structural models aim to identify three distinct, but related, objects: (i) structural “deep” parameters; (ii) underlying mechanisms; (iii) policy counterfactuals. The ability to provide counterfactual predictions sets structural models apart from reduced-form models. The focus is on studies that allow a better understanding of the mechanisms underlying observed behavior and that provide reliable insights about policy counterfactuals. Emphasis is given to models that minimize assumptions on the structural function and on unobserved heterogeneity and approaches that align structural and “reduced form” moments.

2014 ◽  
Vol 65 (2) ◽  
Author(s):  
Klaus B. Beckmann ◽  
Lennart Reimer

AbstractThis paper is concerned with methods for analysing patterns of conflict. We survey dynamic games, differential games, and simulation as alternative ways of extending the standard static economic model of conflict to study patterns of conflict dynamics, giving examples for each type of model.It turns out that computational requirements and theoretical difficulties impose tight limits on what can be achieved using the first two approaches. In particular, we appear to be forced to model the outcome of conflict as being decided in a single final confrontation if we employ non-linear contest success functions.A simulation study based on a new model of adaptive, boundedly rational decision making, however, is shown not to be subject to this limitation. Plausible patterns of conflict dynamics emerge, which we can link to both historical conflict and standard tenets of military theory.


2000 ◽  
Vol 1719 (1) ◽  
pp. 94-102 ◽  
Author(s):  
Krishnan Viswanathan ◽  
Konstadinos G. Goulias ◽  
Paul P. Jovanis

Recent developments in information technologies, providing new ways to disseminate and use information, may help alleviate congestion, reduce user cost and time, and enhance safety. This influence of technology use, however, is mediated by telecommunication and information technology ownership and use. A multivariate probit model specification is used to determine how these parameters influence traveler decision making when one is confronted with information about traffic problems before making a trip to work or school, en route to or from work or school, and before making a trip from work or school. Addressed is the key relationship between telecommunication and information technology ownership and use with travel decisions when information about traffic problems is available. Data from the Puget Sound region for 1997 are used in the analysis. The results suggest technology ownership and use influence travel decision making in different ways for each stage of travel—before leaving home, en route, and returning home.


2018 ◽  
Vol 9 (2) ◽  
pp. 55
Author(s):  
Jonathan E. Leightner

This paper estimates the change in China's exports and the change in US exports due to a one dollar increase in China's foreign reserves. The statistical technique used produces reduced form estimates that capture the influence of omitted variables without having to construct and estimate complex structural models. I find that in August 2000 China's accumulation of 621 million dollars of foreign reserves is correlated with China's exports increasing by 151 million and the US's exports falling by 628 million dollars. In contrast, in November 2016, China spending 69 billion dollars of its foreign reserves supporting the value of the yuan is correlated with China's exports falling by 4.77 billion and the US's exports rising by 2.42 billion. Donald Trump's accusation that China is suppressing the yuan exchange rate to help Chinese exports at the expense of US exports did not fit the facts between August 11, 2015 and December 31, 2016.


Econometrica ◽  
2019 ◽  
Vol 87 (3) ◽  
pp. 699-739 ◽  
Author(s):  
Stéphane Bonhomme ◽  
Thibaut Lamadon ◽  
Elena Manresa

We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural models of wages and worker mobility. We establish identification in short panels, and develop tractable two‐step estimators where firms are classified in a first step. Applying our method to Swedish administrative data, we find that log‐earnings are approximately additive in worker and firm heterogeneity. Our estimates imply the presence of strong sorting patterns between workers and firms, and a small contribution of firms—net of worker composition—to earnings dispersion. In addition, we document that wages have a direct effect on mobility, and that, beyond their dependence on the current firm, earnings after a job move also depend on the previous employer.


2019 ◽  
Vol 57 (4) ◽  
pp. 835-903 ◽  
Author(s):  
Arthur Lewbel

Over two dozen different terms for identification appear in the econometrics literature, including set identification, causal identification, local identification, generic identification, weak identification, identification at infinity, and many more. This survey: (i) gives a new framework unifying existing definitions of point identification; (ii) summarizes and compares the zooful of different terms associated with identification that appear in the literature; and (iii) discusses concepts closely related to identification, such as normalizations and the differences in identification between structural models and causal, reduced form models. ( JEL C01, C20, C50)


2019 ◽  
Vol 15 (10) ◽  
pp. 20190542 ◽  
Author(s):  
Takao Sasaki ◽  
Benjamin Stott ◽  
Stephen C. Pratt

The study of rational choice in humans and other animals typically focuses on decision outcomes, but rationality also applies to decision latencies, especially when time is scarce and valuable. For example, the smaller the difference in quality between two options, the faster a rational actor should decide between them. This is because the consequences of choosing the inferior option are less severe if the options are similar. Experiments have shown, however, that humans irrationally spend more time choosing between similar options. In this study, we assessed the rationality of time investment during nest-site choice by the rock ant, Temnothorax albipennis . Previous studies have shown that collective decision-making allows ant colonies to avoid certain irrational errors. Here we show that the same is true for time investment. Individual ants, like humans, irrationally took more time to complete an emigration when choosing between two similar nests than when choosing between two less similar nests. Whole colonies, by contrast, rationally made faster decisions when the options were more similar. We discuss the underlying mechanisms of decision-making in individuals and colonies and how they lead to irrational and rational time investment, respectively.


1970 ◽  
Vol 7 (3) ◽  
pp. 333-337 ◽  
Author(s):  
Joseph N. Fry ◽  
Frederick H. Siller

A field study employing a shopping simulation compared the purchasing behavior of working and middle class housewives. Explanations of behavioral differences were sought through an analysis of the respondents’ personal attributes. Substantial variation was found in the nature of decision making by social class, even when observed behavior was similar.


2015 ◽  
Vol 4 (4) ◽  
pp. 52-74 ◽  
Author(s):  
David S. Bathory

Within the field of Economics there is great interest in predicting the future. In creating Economic Models the rationale has been to create fixed equations that can account for all variables associated with the issues of capital, labor, wages, prices, tariffs and taxes but few models explored the human variable. Probability Statistics bases decision making models upon mathematical predictions. Game Theory is an economic model that begins to explain the rationale of human decision making, but fails to account for flawed thinking and pathology. Relational Dynamics attempts to provide a means of understanding the strategies used in communication and decision making. Within humanity, not all decisions are made rationally and to account for illogical choices, psychology has provided theories of pathology to explain human idiosyncrasies. This paper will explore personality disorders as described by the DSM V and Relational Dynamics in an attempt to understand how pathology influences relationships, decision making and behavioral economics.


2017 ◽  
Vol 114 (40) ◽  
pp. 10618-10623 ◽  
Author(s):  
Cristian Buc Calderon ◽  
Myrtille Dewulf ◽  
Wim Gevers ◽  
Tom Verguts

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.


2014 ◽  
Vol 926-930 ◽  
pp. 3722-3727
Author(s):  
Wei Meng

This paper compares Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory. Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory are all methods to study factors’ structure problem. Some steps of the two methods can completely replace each other and complement each other. This paper puts forward an integrated method of Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory that includes competing model specification, model fitting, model assessment, model modification and result explain.


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