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Books on the topic 'Structural Equations Estimation Model'

Author: Grafiati

Published: 18 April 2022

Last updated: 25 April 2022

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1

Seiichi, Katayama. Estimation of structural change in the import and export equations: An international comparison. Kobe, Japan: Institute of Economic Research, Kobe University of Commerce, 1985.

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2

Hodoshima, Jiro. Identification and estimation in linear simultaneous equations models with structural change under limited information: Gains by homoskedasticity. Louvain-la-Neuve: CORE, 1985.

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3

Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer Verlag, 1988.

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4

Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer-Verlag, 1988.

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5

Krishnakumar, Jayalakshmi. Estimation of Simultaneous Equation Models with Error Components Structure. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-45647-3.

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6

Bock, Hans Georg. Model Based Parameter Estimation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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7

Inverse problem theory: Methods for data fitting and model parameter estimation. Amsterdam: Elsevier, 1987.

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8

Boorman, D. B. A review of the flood studies report rainfall-runoff model parameter estimation equations. [s.l.]: Institute of Hydrology, 1985.

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9

Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Detailed solutions of the examples in Excel and the R software environment are included. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate and graduate students studying in the field of "Economics", the curriculum of which includes the disciplines "Econometrics"," Econometric Modeling","Econometric research".

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10

1975-, Sims Robert, and Ueltschi Daniel 1969-, eds. Entropy and the quantum II: Arizona School of Analysis with Applications, March 15-19, 2010, University of Arizona. Providence, R.I: American Mathematical Society, 2011.

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11

Bollen, Kenneth A., Sophia Rabe‐Hesketh, and Anders Skrondal. Structural Equation Models. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0018.

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This article explains the use of factor analysis types of models to develop measures of latent concepts which were then combined with causal models of the underlying latent concepts. In particular, it offers an overview of the classic structural equation models (SEMs) when the latent and observed variables are continuous. Then it looks at more recent developments that include categorical, count, and other noncontinuous variables as well as multilevel structural equation models. The model specification, assumptions, and notation are covered. This is followed by addressing implied moments, identification, estimation, model fit, and respecification. The penetration of SEMs has been high in disciplines such as sociology, psychology, educational testing, and marketing, but lower in economics and political science despite the large potential number of applications. Today, SEMs have begun to enter the statistical literature and to re-enter biostatistics, though often under the name ‘latent variable models’ or ‘graphical models’.

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12

Inverse Problem Theory and Methods for Model Parameter Estimation. SIAM: Society for Industrial and Applied Mathematics, 2004.

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13

Rannacher, Rolf, Willi Jäger, Hans Georg Bock, Thomas Carraro, Johannes P. Schlöder, and Stefan Körkel. Model Based Parameter Estimation: Theory and Applications. Springer, 2015.

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14

Jäger, Willi, Hans Georg Bock, and Thomas Carraro. Model Based Parameter Estimation: Theory and Applications. Springer, 2013.

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15

Model Based Parameter Estimation Contributions in Mathematical and Computational Sciences. Springer, 2012.

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16

Fund, International Monetary, ed. Time-series estimation of structural import demand equations: A cross-country analysis. Washington, D.C: International Monetary Fund, 1997.

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17

Heim, John J. An Econometric Model of the US Economy: Structural Analysis in 56 Equations. Palgrave Macmillan, 2018.

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18

Heim, John J. An Econometric Model of the US Economy: Structural Analysis in 56 Equations. Palgrave Macmillan, 2017.

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19

MutheÌn, Bengt. LISCOMP: Analysis of linear structural equations with a comprehensive measurement model : A program for advanced research. 2nd ed. Scientific Software, 1988.

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20

Makatjane, Katleho, and Roscoe van Wyk. Identifying structural changes in the exchange rates of South Africa as a regime-switching process. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/919-8.

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Exchange rate volatility is said to exemplify the economic health of a country. Exchange rate break points (known as structural breaks) have a momentous impact on the macroeconomy of a country. Nonetheless, this country study makes use of both unsupervised and supervised machine learning algorithms to classify structural changes as regime shifts in real exchange rates in South Africa. Weekly data for the period January 2003–June 2020 are used. To these data we apply both non-linear principal component analysis and Markov-switching generalized autoregressive conditional heteroscedasticity. The former approach is used to reduce the dimensionality of the data using an orthogonal linear transformation by preserving the statistical variance of the data, with the proviso that a new trait is non-linearly independent, and it identifies the number of regime switches that are to be used in the Markov-switching model. The latter is used to partition the variance in each regime by allowing an estimation of multiple break transitions. The transition breakpoints estimates derived from this machine learning approach produce results that are comparable to other methods on similar system sizes. Application of these methods shows that the machine learning approach can also be employed to identify structural changes as a regime-switching process. During times of financial crisis, the growing concern over exchange rate volatility, including its adverse effects on employment and growth, broadens the debates on exchange rate policies. Our results should help the South African monetary policy committee to anticipate when exchange rates will pick up and be prepared for the effects of periods of high exchange rates.

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21

Kenny, Paul D. Populism and Patronage. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198807872.003.0009.

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This chapter tests the theory through a quantitative analysis of populist electoral success. It conducts a statistical analysis of the performance of populist candidates in all democracies across Asia, Europe, the, and Australasia. This analysis shows that as subnational units gain autonomy, the electoral performance of populist politicians is enhanced in patronage democracies but not in non-patronage democracies. This finding suggests that there exists a pathway to populist success that is distinctive to patronage democracies. To deal with the high number of cases in which populists receive no votes, the main analysis is a “double-hurdle” model. To control for the endogeneity of these decentralizing processes to party-system stability, the chapter employs an instrumental variables (IV) estimation strategy, in which autonomy is instrumented for by a number of structural features of a polity (area, population, and territorial contiguity). The model also holds up to this IV estimation.

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22

Lattman, Eaton E., Thomas D. Grant, and Edward H. Snell. Pushing the Envelope. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199670871.003.0014.

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Direct electron density determination from SAXS data opens up new opportunities. The ability to model density at high resolution and the implicit direct estimation of solvent terms such as the hydration shell may enable high-resolution wide angle scattering data to be used to calculate density when combined with additional structural information. Other diffraction methods that do not measure three-dimensional intensities, such as fiber diffraction, may also be able to take advantage of iterative structure factor retrieval. While the ability to reconstruct electron density ab initio is a major breakthrough in the field of solution scattering, the potential of the technique has yet to be fully uncovered. Additional structural information from techniques such as crystallography, NMR, and electron microscopy and density modification procedures can now be integrated to perform advanced modeling of the electron density function at high resolution, pushing the boundaries of solution scattering further than ever before.

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23

Darrigol, Olivier. Models, structure, and generality in Clerk Maxwell’s theory of electromagnetism. Edited by Karine Chemla, Renaud Chorlay, and David Rabouin. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198777267.013.12.

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This article examines the gradual development of James Clerk Maxwell’s electromagnetic theory, arguing that he aimed at general structures through his models, illustrations, formal analogies, and scientific metaphors. It also considers a few texts in which Maxwell expounds his conception of physical theories and their relation to mathematics. Following a discussion of Maxwell’s extension of an analogy invented by William Thomson in 1842, the article analyzes Maxwell’s geometrical expression of Michael Faraday’s notion of lines of force. It then revisits Maxwell’s honeycomb model that he used to obtain his system of equations and the concomitant unification of electricity, magnetism, and optics. It also explores Maxwell’s view about the Lagrangian form of the fundamental equations of a physical theory. It shows that Maxwell was guided by general structural requirements that were inspired by partial and temporary models; these requirements were systematically detailed in Maxwell’s 1873 Treatise on electricity and magnetism.

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24

Bažant, Zdenek P., Jia-Liang Le, and Marco Salviato. Quasibrittle Fracture Mechanics and Size Effect. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192846242.001.0001.

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Many modern engineering structures are composed of brittle heterogenous (a.k.a. quasibrittle) materials. These materials include concrete (an archetype), composites, tough ceramics, rocks, cold asphalt mixtures, and many brittle materials at the microscale. Understanding the failure behavior of these materials is of paramount importance for improving the resilience and sustainability of various engineering structures including civil infrastructure, aircraft, ships, military armors, and microelectronic devices. This book provides a comprehensive treatment of quasibrittle fracture mechanics. It first presents a concise but rigorous and complete treatment of the linear elastic fracture mechanics, which is the foundation of all fracture mechanics. The topics covered include energy balance analysis of fracture, analysis of near-tip field and stress intensity factors, Irwin's relationship, J-integral, calculation of compliance function and deflection, and analysis of interfacial crack. Built upon the content of linear elastic fracture mechanics, the book presents various fundamental concepts of nonlinear fracture mechanics, which include estimation of inelastic zone size, cohesive crack model, equivalent linear elastic fracture mechanics model, R-curve, and crack band model. The book also discusses some more advanced concepts such as the effects of the triaxial stress state in the fracture process zone, nonlocal continuum models, and discrete computational model. The significant part of the book is devoted to the discussion of the energetic and statistical size effects, which is a salient feature of quasibrittle fracture. The book also presents probabilistic fracture mechanics, and its consequent reliability-based structural analysis and design of quasibrittle structures. Finally, the book provides an extensive review of various practical applications of quasibrittle fracture mechanics.

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