scholarly journals Model-Implied Instrumental Variable—Generalized Method of Moments (MIIV-GMM) Estimators for Latent Variable Models

Psychometrika ◽  
2013 ◽  
Vol 79 (1) ◽  
pp. 20-50 ◽  
Author(s):  
Kenneth A. Bollen ◽  
Stanislav Kolenikov ◽  
Shawn Bauldry
Keyword(s):  
Method Of Moments ◽  
Instrumental Variable ◽  
Latent Variable ◽  
Generalized Method Of Moments ◽  
Latent Variable Models

scholarly journals A new method of moments for latent variable models

2018 ◽  
Vol 107 (8-10) ◽  
pp. 1431-1455
Author(s):  
Matteo Ruffini ◽  
Marta Casanellas ◽  
Ricard Gavaldà
Keyword(s):  
Method Of Moments ◽  
Latent Variable ◽  
Latent Variable Models ◽  
New Method

Heteroskedasticity- and Autocorrelation-robust F and t Tests in Stata

2018 ◽  
Vol 18 (4) ◽  
pp. 951-980 ◽  
Author(s):  
Xiaoqing Ye ◽  
Yixiao Sun
Keyword(s):  
Method Of Moments ◽  
Instrumental Variable ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Type I ◽  
Variance Estimators ◽  
Normal Approximations ◽  
Chi Squared ◽  
Smoothing Parameters ◽  
Type Ii Errors

In this article, we consider time-series, ordinary least-squares, and instrumental-variable regressions and introduce a new pair of commands, har and hart, that implement more accurate heteroskedasticity- and autocorrelation-robust (HAR) F and t tests. These tests represent part of the recent progress on HAR inference. The F and t tests are based on the convenient F and t approximations and are more accurate than the conventional chi-squared and normal approximations. The underlying smoothing parameters are selected to target the type I and type II errors, which are the two fundamental objects in every hypothesis testing problem. The estimation command har and the postestimation test command hart allow for both kernel HAR variance estimators and orthonormal-series HAR variance estimators. In addition, we introduce another pair of new commands, gmmhar and gmmhart, that implement the recently developed F and t tests in a two-step generalized method of moments framework. For these commands, we opt for the orthonormal-series HAR variance estimator based on the Fourier bases because it allows us to develop convenient F and t approximations as in the first-step generalized method of moments framework. Finally, we present several examples to demonstrate these commands.

Trust, Investment, and Business Contracting

2015 ◽  
Vol 50 (3) ◽  
pp. 569-595 ◽  
Author(s):  
James S. Ang ◽  
Yingmei Cheng ◽  
Chaopeng Wu
Keyword(s):  
Method Of Moments ◽  
Instrumental Variable ◽  
Generalized Method Of Moments ◽  
Investment Decisions ◽  
High Tech ◽  
Dynamic Panel ◽  
Firm Level ◽  
Moments Estimators ◽  
And Control ◽  
Time Invariant

AbstractHow does trust affect business contracting at the firm level? We analyze the case of foreign high-tech companies investing in China, where the risk of expropriation of their intellectual property is high. We find that firms mitigate this type of risk by taking local trustworthiness into account when making investment decisions. Firms prefer to invest in regions where local partners and employees are considered more trustworthy; they are also more likely to establish joint ventures and to make greater research and development investments. We employ instrumental variable regressions and dynamic panel generalized method of moments estimators to alleviate endogeneity concerns and control for time-invariant heterogeneity.

Right-Wing Authoritarians Aren't Very Funny: RWA, Personality, and Creative Humor Production

2020 ◽  
Author(s):  
Paul Silvia ◽  
Alexander P. Christensen ◽  
Katherine N. Cotter
Keyword(s):  
Young Adults ◽  
Latent Variable ◽  
Latent Variable Models ◽  
Openness To Experience ◽  
Rasch Models ◽  
Right Wing ◽  
Right Wing Authoritarianism ◽  
Humor Appreciation ◽  
Negative Effect

Right-wing authoritarianism (RWA) has well-known links with humor appreciation, such as enjoying jokes that target deviant groups, but less is known about RWA and creative humor production—coming up with funny ideas oneself. A sample of 186 young adults completed a measure of RWA, the HEXACO-100, and 3 humor production tasks that involved writing funny cartoon captions, creating humorous definitions for quirky concepts, and completing joke stems with punchlines. The humor responses were scored by 8 raters and analyzed with many-facet Rasch models. Latent variable models found that RWA had a large, significant effect on humor production (β = -.47 [-.65, -.30], p < .001): responses created by people high in RWA were rated as much less funny. RWA’s negative effect on humor was smaller but still significant (β = -.25 [-.49, -.01], p = .044) after controlling for Openness to Experience (β = .39 [.20, .59], p < .001) and Conscientiousness (β = -.21 [-.41, -.02], p = .029). Taken together, the findings suggest that people high in RWA just aren’t very funny.

scholarly journals Looking behind the choice of organic: A cross-country analysis applying Integrated Choice and Latent Variable Models

Appetite ◽  
2021 ◽  
pp. 105591
Author(s):  
Ching-Hua Yeh ◽  
Monika Hartmann ◽  
Matthew Gorton ◽  
Barbara Tocco ◽  
Virginie Amilien ◽  
...  
Keyword(s):  
Latent Variable ◽  
Latent Variable Models ◽  
Country Analysis ◽  
Cross Country

Using information from singletons in fixed-effects estimation: xtfesing

2020 ◽  
Vol 20 (4) ◽  
pp. 965-975
Author(s):  
Laura Magazzini ◽  
Randolph Luca Bruno ◽  
Marco Stampini
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Panel Data Regression ◽  
Data Regression ◽  
Method Of Moments Estimator ◽  
Fixed Effects Estimation

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

Does Bank Profitability Stimulate Economic Growth in the Arab Region?

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Omar Ghazy Aziz
Keyword(s):  
Financial Development ◽  
Method Of Moments ◽  
Positive Impact ◽  
Generalized Method Of Moments ◽  
Arab Countries ◽  
Return On Assets ◽  
Bank Profitability ◽  
Arab Region ◽  
Return On Equity ◽  
The Impact

AbstractThis study empirically investigates the impact of bank profitability, as a complementary measure of financial development, on growth in the Arab countries between 1985 and 2016. Using a generalized method of moments (GMM) estimation to test the impact of the bank profitability on growth, this study utilises two variables in the econometric model which are return on assets and return on equity. This study reveals that both variables of bank profitability are positive and significant. This confirms that the bank profitability, beside other financial development variables, has positive impact on the growth. This study points out some important implications based on this result.

scholarly journals Gaussian Processes Proxy Model with Latent Variable Models and Variogram-Based Sensitivity Analysis for Assisted History Matching

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4290
Author(s):  
Dongmei Zhang ◽  
Yuyang Zhang ◽  
Bohou Jiang ◽  
Xinwei Jiang ◽  
Zhijiang Kang
Keyword(s):  
Sensitivity Analysis ◽  
Gaussian Processes ◽  
Latent Variable ◽  
History Matching ◽  
Latent Variable Models ◽  
High Dimensional ◽  
Model Parameters ◽  
Variable Model ◽  
Assisted History Matching ◽  
Proxy Models

Reservoir history matching is a well-known inverse problem for production prediction where enormous uncertain reservoir parameters of a reservoir numerical model are optimized by minimizing the misfit between the simulated and history production data. Gaussian Process (GP) has shown promising performance for assisted history matching due to the efficient nonparametric and nonlinear model with few model parameters to be tuned automatically. Recently introduced Gaussian Processes proxy models and Variogram Analysis of Response Surface-based sensitivity analysis (GP-VARS) uses forward and inverse Gaussian Processes (GP) based proxy models with the VARS-based sensitivity analysis to optimize the high-dimensional reservoir parameters. However, the inverse GP solution (GPIS) in GP-VARS are unsatisfactory especially for enormous reservoir parameters where the mapping from low-dimensional misfits to high-dimensional uncertain reservoir parameters could be poorly modeled by GP. To improve the performance of GP-VARS, in this paper we propose the Gaussian Processes proxy models with Latent Variable Models and VARS-based sensitivity analysis (GPLVM-VARS) where Gaussian Processes Latent Variable Model (GPLVM)-based inverse solution (GPLVMIS) instead of GP-based GPIS is provided with the inputs and outputs of GPIS reversed. The experimental results demonstrate the effectiveness of the proposed GPLVM-VARS in terms of accuracy and complexity. The source code of the proposed GPLVM-VARS is available at https://github.com/XinweiJiang/GPLVM-VARS.

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