Bias corrected generalized method of moments and generalized quasi-likelihood inferences in linear models for panel data with measurement error

Sankhya B ◽  
2012 ◽  
Vol 74 (1) ◽  
pp. 126-148 ◽  
Author(s):  
Zhaozhi Fan ◽  
Brajendra C. Sutradhar ◽  
R. Prabhakar Rao
Keyword(s):  
Measurement Error ◽  
Panel Data ◽  
Method Of Moments ◽  
Linear Models ◽  
Generalized Method Of Moments

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).

scholarly journals Determinants of Basmati Exports from Pakistan: A Panel Data Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 12-18
Author(s):  
Muhammad Munwar Hayat ◽  
Raheela Khatoon
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Generalized Method Of Moments ◽  
Trading Partner ◽  
Dummy Variable ◽  
Export Competitiveness ◽  
The Impact

This paper aims to estimate the impact of different factors of basmati exports from Pakistan to its trading partner. Results are obtained by using the Generalized Method of Moments (GMM) model and panel data methodology with a sample of 22 countries for the period of 2003-2019. To estimate the impact of different variables on basmati exports Generalized Method of Moments (GMM) model is used on the panel dataset. The results revealed that the inflation rate of Pakistan has a negative and significant effect on the export competitiveness of Pakistani basmati. The exchange rate of Pakistan has a positive and significant impact on the basmati export, the population of Pakistan has a negative and significant impact on basmati export. Basmati production in Pakistan also has a significant and negative impact on basmati export. The Gross Domestic Product (GDP) of Pakistan has a significant and positive impact on the basmati export while the GDP of the trading partner has a significant and negative impact on the basmati export. The dummy variable for joint border also has a positive and significant impact on basmati exports of Pakistan.

Book Reviews

2013 ◽  
Vol 51 (3) ◽  
pp. 886-888
Keyword(s):  
Inverse Problem ◽  
Empirical Likelihood ◽  
Method Of Moments ◽  
Linear Models ◽  
Choice Model ◽  
Generalized Method Of Moments ◽  
Problem Formulation ◽  
Distribution Functions ◽  
Binary Response ◽  
Quadratic Loss

Provides a conceptual and empirical understanding of basic information theoretic econometric models and methods. Discusses formulation and analysis of parametric and semiparametric linear models; method of moments, generalized method of moments, and estimating equations; a stochastic-empirical likelihood inverse problem—formulation and estimation; a stochastic empirical likelihood inverse problem—estimation and inference; Kullback–Leibler information and the maximum empirical exponential likelihood; the Cressie–Read family of divergence measures and empirical maximum likelihood functions; Cressie–Read minimum power divergence (MPD) type estimators in practice—Monte Carlo evidence of estimation and inference sampling performance; family of MPD distribution functions for the binary response-choice model; estimation and inference for the binary response model based on the MPD family of distributions; and choosing the optimal divergence under quadratic loss. Judge is a professor at the University of California, Berkeley. Mittelhammer is Regents Professor of Economic Sciences and Statistics at Washington State University.

scholarly journals The Effect of COVID-19 Pandemic on Corporate Dividend Policy in Indonesia: The Static and Dynamic Panel Data Approaches

Economies ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Georgina Maria Tinungki ◽  
Robiyanto Robiyanto ◽  
Powell Gian Hartono
Keyword(s):  
Panel Data ◽  
Dynamic Model ◽  
Method Of Moments ◽  
Capital Market ◽  
Dividend Policy ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Positive Signal ◽  
Dynamic Panel ◽  
The Capital Market

This research examines the effect of the crisis due to the COVID-19 pandemic on dividend policy in Indonesia. The purposive sampling method was used to collect data from corporates listed on the IDX from 2014 to 2020 and analyzed using static and dynamic panel data approaches. The fixed-effect models (FEM) were selected for the static panel data regression. Meanwhile, the first difference-generalized method of moments (FD-GMM) and system-generalized method of moments (SYS-GMM) were used for determine the robustness of the estimated dynamic panel data. The results showed that the crisis due to the pandemic led to higher dividend distribution on SYS-GMM. Furthermore, companies maintained the dividend level as a positive signal for investors which lifted the sluggish trade condition in the capital market. Profitability and previous year dividends positively affect dividend policy robustly. Furthermore, the results showed that age affects dividend policy on FD-GMM. Financial leverage has a robust effect, and firm size has an effect on FD-GMM in different directions, while investment opportunity does not affect dividend policy. Statistically, the FEM selected that violates the best linear unbiased estimation was proven to form parameters that were not much different from the estimates produced by the dynamic model, both from the coefficient of influence direction and significance, and the omitted variable bias occurs as evidenced in the robust test with dynamic model was solved. This research is also used as a reference for considering investors’ investment decisions in the new normal condition. Therefore, dividend policy can be considered as a positive signal to investors with the ability to stock trading activities in the capital market.

scholarly journals Estimation in linear errors-in-variables models with unknown error distribution

Biometrika ◽  
2020 ◽  
Vol 107 (4) ◽  
pp. 841-856
Author(s):  
Linh H Nghiem ◽  
Michael C Byrd ◽  
Cornelis J Potgieter
Keyword(s):  
Parameter Estimation ◽  
Measurement Error ◽  
Method Of Moments ◽  
Phase Function ◽  
Generalized Method Of Moments ◽  
Error Distribution ◽  
Outcome Variable ◽  
Model Parameters ◽  
Errors In Variables ◽  
Error Distributions

Summary Parameter estimation in linear errors-in-variables models typically requires that the measurement error distribution be known or estimable from replicate data. A generalized method of moments approach can be used to estimate model parameters in the absence of knowledge of the error distributions, but it requires the existence of a large number of model moments. In this paper, parameter estimation based on the phase function, a normalized version of the characteristic function, is considered. This approach requires the model covariates to have asymmetric distributions, while the error distributions are symmetric. Parameters are estimated by minimizing a distance function between the empirical phase functions of the noisy covariates and the outcome variable. No knowledge of the measurement error distribution is needed to calculate this estimator. Both asymptotic and finite-sample properties of the estimator are studied. The connection between the phase function approach and method of moments is also discussed. The estimation of standard errors is considered and a modified bootstrap algorithm for fast computation is proposed. The newly proposed estimator is competitive with the generalized method of moments, despite making fewer model assumptions about the moment structure of the measurement error. Finally, the proposed method is applied to a real dataset containing measurements of air pollution levels.

scholarly journals Governance quality impact on health economics in selected countries: The panel data approach

2015 ◽  
Vol 4 (2) ◽  
pp. 148-154
Author(s):  
Parvaneh Salatin ◽  
Naahid Noorpoor
Keyword(s):  
Panel Data ◽  
Health Economics ◽  
Life Expectancy ◽  
Least Squares ◽  
Method Of Moments ◽  
Generalized Method Of Moments ◽  
Generalized Least Squares ◽  
Middle Income ◽  
Middle Income Countries ◽  
Governance Quality

The purpose of this paper is investigating the theoretical relationship between the effectiveness of governance quality on health economics in selected middle-income countries, using panel data. The Results of the estimation by using the Method of Generalized Least Squares (GLS) & Generalized Method of Moments (GMM) in selected countries for the period 2002-2011 show that governance quality has positive & significant effect on the life expectancy as an index showing the health economics in the group of the selected countries.

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