Relevant bibliographies by topics / Generalized method of moments estimation

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Academic literature on the topic 'Generalized method of moments estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Generalized method of moments estimation"

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Kuersteiner, Guido M., and Laszlo Matyas. "Generalized Method of Moments Estimation." Journal of the American Statistical Association 95, no. 451 (September 2000): 1014. http://dx.doi.org/10.2307/2669498.

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Andrews, Donald W. K. "Consistent Moment Selection Procedures for Generalized Method of Moments Estimation." Econometrica 67, no. 3 (May 1999): 543–63. http://dx.doi.org/10.1111/1468-0262.00036.

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Wooldridge, Jeffrey M. "Applications of Generalized Method of Moments Estimation." Journal of Economic Perspectives 15, no. 4 (November 1, 2001): 87–100. http://dx.doi.org/10.1257/jep.15.4.87.

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I describe how the method of moments approach to estimation, including the more recent generalized method of moments (GMM) theory, can be applied to problems using cross section, time series, and panel data. Method of moments estimators can be attractive because in many circumstances they are robust to failures of auxiliary distributional assumptions that are not needed to identify key parameters. I conclude that while sophisticated GMM estimators are indispensable for complicated estimation problems, it seems unlikely that GMM will provide convincing improvements over ordinary least squares and two-stage least squares--by far the most common method of moments estimators used in econometrics--in settings faced most often by empirical researchers.
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Hu, Yi, Xiaohua Xia, Ying Deng, and Dongmei Guo. "Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/324904.

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Generalized method of moments (GMM) has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample performance is not very well. In order to improve the finite sample performance of generalized method of moments estimators, this paper studies higher-order mean squared error of two-step efficient generalized method of moments estimators for nonlinear models. Specially, we consider a general nonlinear regression model with endogeneity and derive the higher-order asymptotic mean square error for two-step efficient generalized method of moments estimator for this model using iterative techniques and higher-order asymptotic theories. Our theoretical results allow the number of moments to grow with sample size, and are suitable for general moment restriction models, which contains conditional moment restriction models as special cases. The higher-order mean square error can be used to compare different estimators and to construct the selection criteria for improving estimator’s finite sample performance.
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Wilhelm, Daniel. "OPTIMAL BANDWIDTH SELECTION FOR ROBUST GENERALIZED METHOD OF MOMENTS ESTIMATION." Econometric Theory 31, no. 5 (October 2, 2014): 1054–77. http://dx.doi.org/10.1017/s026646661400067x.

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A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or bandwidth) so that the resulting point estimate is optimal in a certain sense. We derive an asymptotically optimal bandwidth that minimizes a higher-order approximation to the asymptotic mean-squared error of the estimator of interest. We show that the optimal bandwidth is of the same order as the one minimizing the mean-squared error of the nonparametric plugin estimator, but the constants of proportionality are significantly different. Finally, we develop a data-driven bandwidth selection rule and show, in a simulation experiment, that it may substantially reduce the estimator’s mean-squared error relative to existing bandwidth choices, especially when the number of moment conditions is large.
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Chatelain, Jean-Bernard. "Improving consistent moment selection procedures for generalized method of moments estimation." Economics Letters 95, no. 3 (June 2007): 380–85. http://dx.doi.org/10.1016/j.econlet.2006.11.011.

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Nghiem, Linh H., Michael C. Byrd, and Cornelis J. Potgieter. "Estimation in linear errors-in-variables models with unknown error distribution." Biometrika 107, no. 4 (May 21, 2020): 841–56. http://dx.doi.org/10.1093/biomet/asaa025.

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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.
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Hall, Alastair R., Atsushi Inoue, Kalidas Jana, and Changmock Shin. "Information in generalized method of moments estimation and entropy-based moment selection." Journal of Econometrics 138, no. 2 (June 2007): 488–512. http://dx.doi.org/10.1016/j.jeconom.2006.05.006.

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Lynch, Anthony W., and Jessica A. Wachter. "Using Samples of Unequal Length in Generalized Method of Moments Estimation." Journal of Financial and Quantitative Analysis 48, no. 1 (February 2013): 277–307. http://dx.doi.org/10.1017/s0022109013000070.

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AbstractThis paper describes estimation methods, based on the generalized method of moments (GMM), applicable in settings where time series have different starting or ending dates. We introduce two estimators that are more efficient asymptotically than standard GMM. We apply these to estimating predictive regressions in international data and show that the use of the full sample affects inference for assets with data available over the full period as well as for assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones.
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Seo, Myung Hwan, Sueyoul Kim, and Young-Joo Kim. "Estimation of dynamic panel threshold model using Stata." Stata Journal: Promoting communications on statistics and Stata 19, no. 3 (September 2019): 685–97. http://dx.doi.org/10.1177/1536867x19874243.

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In this article, we develop a command, xthenreg, that implements the first-differenced generalized method of moments estimation of the dynamic panel threshold model that Seo and Shin (2016, Journal of Econometrics 195: 169–186) proposed. Furthermore, we derive the asymptotic variance formula for a kink-constrained generalized method of moments estimator of the dynamic threshold model and provide an estimation algorithm. We also propose a fast bootstrap algorithm to implement the bootstrap for the linearity test. We illustrate the use of xthenreg through a Monte Carlo simulation and an economic application.
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Dissertations / Theses on the topic "Generalized method of moments estimation"

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CUNHA, JOAO MARCO BRAGA DA. "ESTIMATING ARTIFICIAL NEURAL NETWORKS WITH GENERALIZED METHOD OF MOMENTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=26922@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
As Redes Neurais Artificiais (RNAs) começaram a ser desenvolvidas nos anos 1940. Porém, foi a partir dos anos 1980, com a popularização e o aumento de capacidade dos computadores, que as RNAs passaram a ter grande relevância. Também nos anos 1980, houve dois outros acontecimentos acadêmicos relacionados ao presente trabalho: (i) um grande crescimento do interesse de econometristas por modelos não lineares, que culminou nas abordagens econométricas para RNAs, no final desta década; e (ii) a introdução do Método Generalizado dos Momentos (MGM) para estimação de parâmetros, em 1982. Nas abordagens econométricas de RNAs, sempre predominou a estimação por Quasi Máxima Verossimilhança (QMV). Apesar de possuir boas propriedades assintóticas, a QMV é muito suscetível a um problema nas estimações em amostra finita, conhecido como sobreajuste. O presente trabalho estende o estado da arte em abordagens econométricas de RNAs, apresentando uma proposta alternativa à estimação por QMV que preserva as suas boas propriedades assintóticas e é menos suscetível ao sobreajuste. A proposta utiliza a estimação pelo MGM. Como subproduto, a estimação pelo MGM possibilita a utilização do chamado Teste J para verifificar a existência de não linearidade negligenciada. Os estudos de Monte Carlo realizados indicaram que as estimações pelo MGM são mais precisas que as geradas pela QMV em situações com alto ruído, especialmente em pequenas amostras. Este resultado é compatível com a hipótese de que o MGM é menos suscetível ao sobreajuste. Experimentos de previsão de taxas de câmbio reforçaram estes resultados. Um segundo estudo de Monte Carlo apontou boas propriedades em amostra finita para o Teste J aplicado à não linearidade negligenciada, comparado a um teste de referência amplamente conhecido e utilizado. No geral, os resultados apontaram que a estimação pelo MGM é uma alternativa recomendável, em especial no caso de dados com alto nível de ruído.
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 overfiting. 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 overfiting. 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 overfiting. 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.
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Burk, David Morris. "Estimating the Effect of Disability on Medicare Expenditures." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/2127.

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We consider the effect of disability status on Medicare expenditures. Disabled elderly historically have accounted for a significant portion of Medicare expenditures. Recent demographic trends exhibit a decline in the size of this population, causing some observers to predict declines in Medicare expenditures. There are, however, reasons to be suspicious of this rosy forecast. To better understand the effect of disability on Medicare expenditures, we develop and estimate a model using the generalized method of moments technique. We find that newly disabled elderly generally spend more than those who have been disabled for longer periods of time. Also, we find that increases in expenditures have risen much more quickly for those disabled Medicare beneficiaries who were at the higher ends of the expenditure distribution before the increases.
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Liu, Xiaodong. "Econometrics on interactions-based models methods and applications /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180283230.

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Ruzibuka, John S. "The impact of fiscal deficits on economic growth in developing countries : Empirical evidence and policy implications." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/16282.

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This study examines the impact of fiscal deficits on economic growth in developing countries. Based on deduction from the relevant theoretical and empirical literature, the study tests the following hypotheses regarding the impact of fiscal deficits on economic growth. First, fiscal deficits have significant positive or negative impact on economic growth in developing countries. Second, the impact of fiscal deficits on economic growth depends on the size of deficits as a percentage of GDP – that is, there is a non-linear relationship between fiscal deficits and economic growth. Third, the impact of fiscal deficits on economic growth depends on the ways in which deficits are financed. Fourth, the impact of fiscal deficits on economic growth depends on what deficit financing is used for. The study also examines whether there are any significant regional differences in terms of the relationship between fiscal deficits and economic growth in developing countries. The study uses panel data for thirty-one developing countries covering the period 1972- 2001, which is analysed based on the econometric estimation of a dynamic growth model using the Arellano and Bond (1991) generalised method of moments (GMM) technique. Overall, the results suggest the following. First, fiscal deficits per se have no any significant positive or negative impact on economic growth. Second, by contrast, when the deficit is substituted by domestic and foreign financing, we find that both domestic and foreign financing of fiscal deficits exerts a negative and statistically significant impact on economic growth with a lag. Third, we find that both categories of economic classification of government expenditure, namely, capital and current expenditure, have no significant impact on economic growth. When government expenditure is disaggregated on the basis of a functional classification, the results suggest that spending on education, defence and economic services have positive but insignificant impact on growth, while spending on health and general public services have positive and significant impact. Fourth, in terms of regional differences with regard to the estimated relationships, the study finds that, while there are some regional differences between the four different regions represented in our sample of thirty-one developing countries - namely, Asia and the Pacific, Latin America and the Caribbean, Middle East and North Africa, and Sub-Saharan Africa – these differences are not statistically significant. On the basis of these findings, the study concludes that fiscal deficits per se are not necessarily good or bad for economic growth in developing countries; how the deficits are financed and what they are used for matters. In addition, the study concludes that there are no statistically significant regional differences in terms of the relationship between fiscal deficits and economic growth in developing countries.
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Badinger, Harald, and Peter Egger. "Spacey Parents and Spacey Hosts in FDI." WU Vienna University of Economics and Business, 2013. http://epub.wu.ac.at/3924/2/wp154.pdf.

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Empirical trade economists have found that shocks on foreign direct investment (FDI) of some parent country in a host country affect the same parent country´s FDI in other hosts (interdependent hosts). Independent of this, there is evidence that shocks on a parent country´s FDI in some host economy affect other parent countries´ FDI in the same host (interdependent parents). In general equilibrium, shocks on FDI between any country pair will affect all country-pairs´ FDI in the world, including anyone of the two countries in a pair as well as third countries (interdependent third countries). No attempt has been made so far to allow simultaneously for all three modes of interdependence of FDI. Using cross-sectional data on FDI among 22 OECD countries in 2000, we employ a spatial feasible generalized two-stage least squares and generalized moments estimation framework to allow for all three modes of interdependence across all parent and host countries, thereby distinguishing between market-size-related and remainder interdependence. Our results highlight the complexity of multinational enterprises´ investment strategies and the interconnectedness of the world investment system (authors' abstract).
Series: Department of Economics Working Paper Series
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Ruzibuka, John Shofel. "The impact of fiscal deficits on economic growth in developing countries : empirical evidence and policy implications." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/16282.

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This study examines the impact of fiscal deficits on economic growth in developing countries. Based on deduction from the relevant theoretical and empirical literature, the study tests the following hypotheses regarding the impact of fiscal deficits on economic growth. First, fiscal deficits have significant positive or negative impact on economic growth in developing countries. Second, the impact of fiscal deficits on economic growth depends on the size of deficits as a percentage of GDP - that is, there is a non-linear relationship between fiscal deficits and economic growth. Third, the impact of fiscal deficits on economic growth depends on the ways in which deficits are financed. Fourth, the impact of fiscal deficits on economic growth depends on what deficit financing is used for. The study also examines whether there are any significant regional differences in terms of the relationship between fiscal deficits and economic growth in developing countries. The study uses panel data for thirty-one developing countries covering the period 1972- 2001, which is analysed based on the econometric estimation of a dynamic growth model using the Arellano and Bond (1991) generalised method of moments (GMM) technique. Overall, the results suggest the following. First, fiscal deficits per se have no any significant positive or negative impact on economic growth. Second, by contrast, when the deficit is substituted by domestic and foreign financing, we find that both domestic and foreign financing of fiscal deficits exerts a negative and statistically significant impact on economic growth with a lag. Third, we find that both categories of economic classification of government expenditure, namely, capital and current expenditure, have no significant impact on economic growth. When government expenditure is disaggregated on the basis of a functional classification, the results suggest that spending on education, defence and economic services have positive but insignificant impact on growth, while spending on health and general public services have positive and significant impact. Fourth, in terms of regional differences with regard to the estimated relationships, the study finds that, while there are some regional differences between the four different regions represented in our sample of thirty-one developing countries - namely, Asia and the Pacific, Latin America and the Caribbean, Middle East and North Africa, and Sub-Saharan Africa - these differences are not statistically significant. On the basis of these findings, the study concludes that fiscal deficits per se are not necessarily good or bad for economic growth in developing countries; how the deficits are financed and what they are used for matters. In addition, the study concludes that there are no statistically significant regional differences in terms of the relationship between fiscal deficits and economic growth in developing countries.
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Naylor, Guilherme Lima. "O impacto das instituições na renda dos países : uma abordagem dinâmica para dados em painel." Master's thesis, Instituto Superior de Economia e Gestão, 2021. http://hdl.handle.net/10400.5/21704.

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Mestrado em Econometria Aplicada e Previsão
As diferenças nos níveis de renda entre os países vêm sendo estudadas há muito tempo na economia. O capital humano, a produtividade, as instituições e outros fatores foram tidos como determinantes para as discrepâncias verificadas. Este trabalho segue a linha institucionalista ao procurar medir e relacionar o modo como as instituições impactam o nível de renda dos países.Primeiro, faz-se necessário rever brevemente a literatura sobre os modelos de crescimento econômico. Posteriormente, delimita-se o conceito de instituição e descreve-se seu processo de evolução ao longo do tempo. Esse preâmbulo é importante, pois fornece base teórica para os modelos econométricos estimados, que visam a medir os efeitos de diferentes características das instituições sobre o nível de renda dos países. O método escolhido para a análise é a estimação de modelos dinâmicos, por meio da abordagem do estimador do Método dos Momentos Generalizados de Sistema de Blundell e Bond.
Differences in income levels between countries have long been studied in economics. Human capital, productivity, institutions and other factors were taken as determinants for the discrepancies found. This work follows the institutionalist line in seeking to measure and relate how institutions impact the income level of countries.First, it is necessary to briefly review the literature on economic growth models. Subsequently, the concept of institution is delimited and its evolution process over time is descripted. This preamble is important because it provides a theoretical basis for the estimated econometric models, which aim to measure the effects of different characteristics of institutions on the income level of countries. The method chosen for the analysis is the estimation of dynamic models, using the Blundell & Bond Generalized Method of Moments System estimator approach.
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Lai, Yanzhao. "Generalized method of moments exponential distribution family." View electronic thesis (PDF), 2009. http://dl.uncw.edu/etd/2009-2/laiy/yanzhaolai.pdf.

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Augustine-Ohwo, Odaro. "Estimating break points in linear models : a GMM approach." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/estimating-break-points-in-linear-models-a-gmm-approach(804d83e3-dad8-4cda-b1e1-fbfce7ef41b8).html.

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In estimating econometric time series models, it is assumed that the parameters remain constant over the period examined. This assumption may not always be valid when using data which span an extended period, as the underlying relationships between the variables in these models are exposed to various exogenous shifts. It is therefore imperative to examine the stability of models as failure to identify any changes could result in wrong predictions or inappropriate policy recommendations. This research proposes a method of estimating the location of break points in linear econometric models with endogenous regressors, estimated using Generalised Method of Moments (GMM). The proposed estimation method is based on Wald, Lagrange Multiplier and Difference type test statistics of parameter variation. In this study, the equation which sets out the relationship between the endogenous regressor and the instruments is referred to as the Jacobian Equation (JE). The thesis is presented along two main categories: Stable JE and Unstable JE. Under the Stable JE, models with a single and multiple breaks in the Structural Equation (SE) are examined. The break fraction estimators obtained are shown to be consistent for the true break fraction in the model. Additionally, using the fixed break approach, their $T$-convergence rates are established. Monte Carlo simulations which support the asymptotic properties are presented. Two main types of Unstable JE models are considered: a model with a single break only in the JE and another with a break in both the JE and SE. The asymptotic properties of the estimators obtained from these models are intractable under the fixed break approach, hence the thesis provides essential steps towards establishing the properties using the shrinking breaks approach. Nonetheless, a series of Monte Carlo simulations conducted provide strong support for the consistency of the break fraction estimators under the Unstable JE. A combined procedure for testing and estimating significant break points is detailed in the thesis. This method yields a consistent estimator of the true number of breaks in the model, as well as their locations. Lastly, an empirical application of the proposed methodology is presented using the New Keynesian Phillips Curve (NKPC) model for U.S. data. A previous study has found this NKPC model is unstable, having two endogenous regressors with Unstable JE. Using the combined testing and estimation approach, similar break points were estimated at 1975:2 and 1981:1. Therefore, using the GMM estimation approach proposed in this study, the presence of a Stable or Unstable JE does not affect estimations of breaks in the SE. A researcher can focus directly on estimating potential break points in the SE without having to pre-estimate the breaks in the JE, as is currently performed using Two Stage Least Squares.
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Liang, Yitian. "Generalized method of moments : theoretical, econometric and simulation studies." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/36866.

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The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three aspects of the GMM technique. First, I derive the prooves to study the asymptotic properties of the GMM estimator under certain conditions. To my best knowledge, the original complete prooves proposed by Hansen (1982) is not easily available. In this thesis, I provide complete prooves of consistency and asymptotic normality of the GMM estimator under some stronger assumptions than those in Hansen (1982). Second, I illustrate the application of GMM estimator in linear models. Specifically, I emphasize the economic reasons underneath the linear statistical models where GMM estimator (also referred to the Instrumental Variable estimator) is widely used. Third, I perform several simulation studies to investigate the performance of GMM estimator under different situations.
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Books on the topic "Generalized method of moments estimation"

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Generalized method of moments. Oxford: Oxford University Press, 2005.

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Lee, Myoung-jae. Methods of moments and semiparametric econometrics for limited dependent and variable models. New York: Springer, 1996.

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McFadden, Daniel. A method of simulated moments for estimation of discrete response models without numerical integration. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1987.

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László, Mátyás, ed. Generalized method of moments estimation. Cambridge [England]: Cambridge University Press, 1999.

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Matyas, Laszlo, ed. Generalized Method of Moments Estimation. Cambridge University Press, 1999. http://dx.doi.org/10.1017/cbo9780511625848.

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Karakoç, Ekrem. Cross-National Test of the Theory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198826927.003.0003.

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The previous chapter posed the primary research question and offered a new theory that encompassed two interrelated arguments. This chapter produces three hypotheses derived from the new theory offered in Chapter 2. Chapter 3 tests these arguments in a large-N study using multivariate statistical analysis. The first section discusses the operationalization of our main dependent and independent variables. It will also briefly outline a set of control variables and what the literature predicts regarding their effect on spending and inequality. These factors range from economic factors (globalization, inflation, female labor participation, economic development), political factors (partisanship, electoral systems, election cycle), and demographic factors. To correct for problems associated with the nature of panel data models, such as endogeneity, heteroskedasticity, and autocorrelation, it uses the Arellano-Bond estimation, which uses the Generalized Method of Moments. The rest of the chapter presents the results and offers its interpretation and conclusion.
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Sauter, Roger M. A method for estimation of generalized linear models when explanatory variables contain meaurement error. 1989.

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Geological Survey (U.S.), ed. Adjusted maximum likelihood estimation of the moments of lognormal populations from type 1 censored samples. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1988.

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Adjusted maximum likelihood estimation of the moments of lognormal populations from type 1 censored samples. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1988.

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Geological Survey (U.S.), ed. Adjusted maximum likelihood estimation of the moments of lognormal populations from type 1 censored samples. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1988.

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Book chapters on the topic "Generalized method of moments estimation"

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Hansen, Lars Peter. "Generalized Method of Moments Estimation." In The New Palgrave Dictionary of Economics, 1–10. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2486-1.

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Hansen, Lars Peter. "Generalized Method of Moments Estimation." In The New Palgrave Dictionary of Economics, 1–10. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-349-95121-5_2486-2.

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Hansen, Lars Peter. "Generalized Method of Moments Estimation." In The New Palgrave Dictionary of Economics, 5201–11. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2486.

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Hansen, Lars Peter. "Generalized method of moments estimation." In Macroeconometrics and Time Series Analysis, 105–18. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230280830_13.

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Ziegler, Andreas. "Generalized method of moment estimation." In Generalized Estimating Equations, 119–31. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0499-6_8.

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de Aguiar, Alexandre Street, and João Marco Braga da Cunha. "Estimating Artificial Neural Networks with Generalized Method Moments." In Advances in Computational Intelligence, 391–99. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19222-2_33.

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Qin, Jing. "Generalized Method of Moments." In Biased Sampling, Over-identified Parameter Problems and Beyond, 129–38. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4856-2_7.

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Wansbeek, Tom J. "Generalized Method of Moments." In International Series in Quantitative Marketing, 453–91. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53469-5_15.

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Gaspard, J. P., and Ph Lambin. "On a Generalized-Moments Method." In Springer Series in Solid-State Sciences, 72–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-82444-9_7.

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Prucha, Ingmar R. "Instrumental Variables/Method of Moments Estimation." In Handbook of Regional Science, 1–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-36203-3_90-1.

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Conference papers on the topic "Generalized method of moments estimation"

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Song, Eunhye, and Yi Dong. "GENERALIZED METHOD OF MOMENTS APPROACH TO HYPERPARAMETER ESTIMATION FOR GAUSSIAN MARKOV RANDOM FIELDS." In 2018 Winter Simulation Conference (WSC). IEEE, 2018. http://dx.doi.org/10.1109/wsc.2018.8632275.

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Bakkali, Mohammed, Alex Stephenne, and Sofiene Affes. "Generalized Moment-Based Method for SNR Estimation." In 2007 IEEE Wireless Communications and Networking Conference. IEEE, 2007. http://dx.doi.org/10.1109/wcnc.2007.416.

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Wang, Ning, and Julian Cheng. "Estimating the Nakagami-m Fading Parameter by the Generalized Method of Moments." In ICC 2011 - 2011 IEEE International Conference on Communications. IEEE, 2011. http://dx.doi.org/10.1109/icc.2011.5962898.

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Mosalaosi, M., and T. J. O. Afullo. "Parameter estimation for linear regression models in powerline communication systems noise using Generalized Method of Moments (GMM)." In 2016 Progress in Electromagnetic Research Symposium (PIERS). IEEE, 2016. http://dx.doi.org/10.1109/piers.2016.7735775.

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Kusrini, Dwi Endah, Brodjol S. S. Ulama, and Mutiah Salamah Chamid. "Generalized Method of Moment Estimation Method Lagrange Multiplier Test for Simultaneous Spatial of Dynamic Panel Data." In 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/assehr.k.210508.108.

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Egorov, G. V., V. V. Kozlyakov, and B. N. Stankov. "An Analysis of Practical Use Experience of Ultimate Hull Girder Strength Criterion and Some Features of Hulls Ductile Collapses." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28224.

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Follow-up to the survey report [1], containing in-depth study of this problem, basically, since 1965, in the present report the almost 100-year’s experience of usage of the ultimate plastic strength criterion (U.S.C) in the Russian and Ukrainian practice of design of hulls of ship of different destination is reviewed. On the basis of comparison of results of computational and experimental estimations of an ultimate bending moments (Mult) and characteristics of their variability the expediency of usage of the (Mult) lower boundary by Boobnov-Papkovich-Shimansky method with a more precise estimation of carrying capacity of longitudinals by the generalized method of C. Smith is substantiated. These recommendations may be used also for estimation of the hull ultimate strength of FPSO (Floating Production Storage and Off-loading Units), the structure of which is similar to the hulls of modern tankers with the double bottom and double sides.
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Nair, N. V., and B. Shanker. "Implementation of Generalized Method of Moments." In 2009 IEEE Antennas and Propagation Society International Symposium (APSURSI). IEEE, 2009. http://dx.doi.org/10.1109/aps.2009.5171540.

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Dault, D., and B. Shanker. "A penalty method for the Generalized Method of Moments." In 2014 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. IEEE, 2014. http://dx.doi.org/10.1109/aps.2014.6905408.

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Dault, D., and B. Shanker. "Smooth current mappings for the Generalized Method of Moments." In 2014 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. IEEE, 2014. http://dx.doi.org/10.1109/aps.2014.6905409.

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Herraiz, Joaquín L., Miguel A. Morcillo, and Jose M. Udias. "Dynamic PET imaging with the generalized method of moments." In The Fifteenth International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, edited by Samuel Matej and Scott D. Metzler. SPIE, 2019. http://dx.doi.org/10.1117/12.2534837.

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Reports on the topic "Generalized method of moments estimation"

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Wilhelm, Daniel. Optimal bandwidth selection for robust generalized method of moments estimation. Cemmap, March 2014. http://dx.doi.org/10.1920/wp.cem.2014.1514.

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Lynch, Anthony, and Jessica Wachter. Using Samples of Unequal Length in Generalized Method of Moments Estimation. Cambridge, MA: National Bureau of Economic Research, October 2008. http://dx.doi.org/10.3386/w14411.

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Druska, Viliam, and William Horrace. Generalized Moments Estimation for Panel Data. Cambridge, MA: National Bureau of Economic Research, March 2003. http://dx.doi.org/10.3386/t0291.

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Gallant, Ron, Raffaella Giacomini, and Giuseppe Ragusa. Generalized method of moments with latent variables. Institute for Fiscal Studies, October 2013. http://dx.doi.org/10.1920/wp.cem.2013.5013.

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Clarke, Paul S., Tom M. Palmer, and Frank Windmeijer. Estimating structural mean models with multiple instrumental variables using the generalised method of moments. Institute for Fiscal Studies, August 2011. http://dx.doi.org/10.1920/wp.cem.2011.2811.

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Burnside, Craig, and Martin Eichenbaum. Small Sample Properties of Generalized Method of Moments Based Wald Tests. Cambridge, MA: National Bureau of Economic Research, May 1994. http://dx.doi.org/10.3386/t0155.

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Glynn, Peter W., and Donald L. Iglehart. Estimation of Steady-State Central Moments by the Regenerative Method of Simulation. Fort Belvoir, VA: Defense Technical Information Center, August 1985. http://dx.doi.org/10.21236/ada161435.

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Neely, Christopher J. A Reconsideration of the Properties of the Generalized Method of Moments in Asset Pricing Models. Federal Reserve Bank of St. Louis, 1994. http://dx.doi.org/10.20955/wp.1994.010.

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Eisenhauer, Phillipp, James Heckman, and Stefano Mosso. Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments. Cambridge, MA: National Bureau of Economic Research, October 2014. http://dx.doi.org/10.3386/w20622.

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Over, Thomas, Riki Saito, Andrea Veilleux, Padraic O’Shea, Jennifer Sharpe, David Soong, and Audrey Ishii. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, June 2016. http://dx.doi.org/10.36501/0197-9191/16-014.

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This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions. The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter. This report also provides: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant. The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web-based application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted peak discharge records by streamgage are provided at http://dx.doi.org/10.3133/sir20165050 for download.
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