Alternative Over-Identifying Restriction Test in GMM Estimation of Panel Data Models

Hayakawa, Kazuhiko

doi:10.2139/ssrn.2250624

Cited by 6 publications

(4 citation statements)

References 87 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Instrumental variables might be too much in the estimation and should be checked against this proliferation problem. The related test is the diagonal J or Sargan/Hansen test (Hayakawa, 2019).

J_{diag} = N \overset{truê}{g} {((), {\overset{truê}{β}}_{opt})}^{' {\overset{S}{true}}^{- 1} \overset{truê}{g}} ({\overset{β}{true}}_{opt}),

where

J_{diag}

is the product of optimal GMM parameter estimation and efficient weight matrix.…”

Section: Methodsmentioning

confidence: 99%

The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?

Koçak

Bağlıtaş

2022

Sustainable Development

View full text Add to dashboard Cite

This paper explores the economic, social, and technical dynamics affecting municipal solid waste (MSW) per capita in organisation for economic co-operation and development (OECD) countries from 2003 to 2018. Static and dynamic panel data methods are followed for empirical analysis. According to the estimation results, there is an inverted-U-shaped relationship between economic growth and MSW. The turning point income level, where technological and structural effects occur, is calculated in the range of $20,000-$34,000. Human development and energy efficiency have mitigating effects on MSW. Energy efficiency and human development are critical for sustainable MSW management. Credit expansion has an increasing effect on MSW generation. Financial development draws attention as a negative indicator in sustainable waste management targets. All models confirm that income inequality has an increasing effect on MSW generation. In addition, poverty reduction is associated with an increase in MSW generation. Thus, income inequality and poverty reduction are a major constraint for sustainable MSW management. After all, the empirical findings of this paper can guide authorities in designing waste management policies.

show abstract

“…Instrumental variables might be too much in the estimation and should be checked against this proliferation problem. The related test is the diagonal J or Sargan/Hansen test (Hayakawa, 2019).

J_{diag} = N \overset{truê}{g} {((), {\overset{truê}{β}}_{opt})}^{' {\overset{S}{true}}^{- 1} \overset{truê}{g}} ({\overset{β}{true}}_{opt}),

where

J_{diag}

is the product of optimal GMM parameter estimation and efficient weight matrix.…”

Section: Methodsmentioning

confidence: 99%

The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?

Koçak

Bağlıtaş

2022

Sustainable Development

View full text Add to dashboard Cite

show abstract

“…The subsequent approach to measuring the impact of innovation is the approximation si the application of the GMM panel estimation approach where the past variable can serve as instruments, and the number of instruments grows before the end of the study period. This is called sequential moment conditions (Hayakawa, 2019). The study applies the Generalized Method of Moments (GMM) to estimate the subsequent equations four and five.…”

Section: Modelmentioning

confidence: 99%

Evaluating technological innovation impact: an empirical analysis of the offshore wind sector

Shi

Dou

et al. 2022

Environ Sci Pollut Res

View full text Add to dashboard Cite

This study analyses the drivers that impact innovation on offshore wind energy for a select group of countries, applying the quantile and GMM approaches for a period between 2010-2019. The OLS results from the quantile analysis say the log of trademark, Carbon emissions, offshore wind capacity, and electricity from renewable energy are significant and impact on innovation regarding offshore wind energy. Generally, the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity test reveals the variables have a constant variance, confirming the robustness of the findings. The quantile regression depicts that at 25 th and 75 th quantiles levels, the log of trademark, the log of trade flows, the log of scientific and technical journals quantile coefficients is significantly different from zero and exhibit varied effects on the explained variable patent.Similarly, the analysis applied the IV-GMM estimation in ivreg2 to identify the over restrictions, the Hansen J statistic, and give the robust moment of conditions analysis. The findings are consistent with prior analysis with the log of trademark, the log of offshore wind capacity, the log of carbon emissions, Scientific and technology journals, the log of patent, electricity from renewables to be significant and impact on innovation.The robustness was done on the GMM models, by applying the Huber-White-Sandwich estimator of the variance of the GMM linear models approximators. The ivreg2 robust analysis revealed that the estimates are efficient for homoskedasticity and Statistics robust to heteroskedasticity.Ultimately, the interaction term ''cross'' came out significant in the analysis. Signifying the importance of the interaction variables in scaling innovation. This study will sever as a reference document for policy formulators regarding scaling up innovation for offshore wind energy.

show abstract

“…Parte da popularidade do MGM se deve ao Teste J, uma vez que não há testes similares igualmente versáteis para outros métodos de estimação. Não obstante, a baixa potência do Teste J em diversos tipos de má especificação do modelo foi reporda, por exemplo, em [56,57].…”

Section: Teste Junclassified

Estimating Artificial Neural Networks with Generalized Method Moments

Aguiar

Cunha

2015

Advances in Computational Intelligence

View full text Add to dashboard Cite

Artificial Neural Networks (ANN) started being developed in the decade of 1940. However, it was during the 1980's that the ANNs became relevant, pushed by the popularization and increasing power of computers. Also in the 1980's, there were two other two other academic events closely related to the present work: (i) a large increase of interest in nonlinear models from econometricians, culminating in the econometric approaches for ANN by the end of that decade; and (ii) the introduction of the Generalized Method of Moments (GMM) for parameter estimation in 1982. In econometric approaches for ANNs, the estimation by Quasi Maximum Likelihood (QML) always prevailed. Despite its good asymptotic properties, QML is very prone to an issue in finite sample estimations, known as overfitting. This thesis expands the state of the art in econometric approaches for ANNs by presenting an alternative to QML estimation that keeps its good asymptotic properties and has reduced leaning to overfitting. The presented approach relies on GMM estimation. As a byproduct, GMM estimation allows the use of the so-called J Test to verify the existence of neglected nonlinearity. The performed Monte Carlo studies indicate that the estimates from GMM are more accurate than those generated by QML in situations with high noise, especially in small samples. This result supports the hypothesis that GMM is susceptible to overfitting. Exchange rate forecasting experiments reinforced these findings. A second Monte Carlo study revealed satisfactory finite sample properties of the J Test applied to the neglected nonlinearity, compared with a reference test widely known and used. Overall, the results indicated that the estimation by GMM is a better alternative, especially for data with high noise level.

show abstract

Alternative Over-Identifying Restriction Test in GMM Estimation of Panel Data Models

Cited by 6 publications

References 87 publications

The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?

The path to sustainable municipal solid waste management: Do human development, energy efficiency, and income inequality matter?

Evaluating technological innovation impact: an empirical analysis of the offshore wind sector

Estimating Artificial Neural Networks with Generalized Method Moments

Contact Info

Product

Resources

About