Questions tagged [generalized-moments]

generalized-moments stands for the econometric technique of "generalized method of moments", a method of quadratically combining multiple "generalized moments", or "estimating equations", to obtain parameter estimates, their standard errors, and test statistics in single and multiple-equation, cross-sectional, time-series, and panel data models.

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Can you use GMM to overcome time-variant omitted variable bias resulting from FE?

I am looking at a FE model on the effects of R&D expenditure on labour productivity but not sure how to address the possible endogeneity resulting from time varying omitted variable bias. I cannot ...
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GMM panel data model in R - no individual effects

I need to estimate the coefficients of a particular dynamic panel data model. \begin{equation} \ln(y_{i,t})=\alpha_0+\beta ln(y_{i,t-1})+\theta_t+ \varepsilon_{i,t} \end{equation} Currently, I'm ...
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Regression specification: what if one regressor is function of another

Consider the following regression model $$ Y_i=D_{i}(\alpha_1+\beta_1 X_i)+(1-D_i)(\alpha_2+\beta_2 X_i)+\epsilon_i $$ where $D_i$ is a binary variable. Suppose the researcher has an i.i.d. sample $\{...
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OLS as a GMM Estimator - Objective functions

Suppose we have a linear model $Y = X'\theta_0 + \epsilon$, where $Y$ is a 1-dimensional random variable and $X$ is $k$-dimensional, with the specification that $E[\epsilon X] = 0$. Then we can write ...
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Orthogonality conditions in system-GMM

It is not very clear to me a detail about the orthogonality conditions in system-GMM estimation. Suppose x is our endogenous variable. We instrument x with its lagged differences. The inference is ...
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Is using a fixed random seed in production okay?

I have a dataset and am trying to use GMM to cluster it. The algorithm works well but when I run it multiple times I get different results. While the clusters produced in each run are valid my users ...
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Is a GMM model suitable for regression with interaction term?

For my dissertation I am looking at regressing net capital outflows against financial openness and GDP per capita like in Reinhardt, Ricci and Tressel (2013). To deal with potential endogeneity in ...
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ARSV model estimation with (constrained) generalized method of moments in R

I am trying to perform the estimation of the following Autoregressive Stochastic Volatility model $$ y_t=\sigma_t u_t = exp(w_t/2)u_t \\ w_t = \omega + \phi w_{t-1} + \eta_t $$ in R via the function <...
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Using the method of moments or GMM to estimate the parameters of a specific problem

Given $(X_t)_{t \in \mathbb{Z}}$ an AR(1) process: $$X_t = c+ \phi X_{t-1} + \epsilon_t, \quad \epsilon_t\sim WN(0,\sigma^2)$$ We can show that $E(X_t) = \frac{c}{1- \phi}$ and $E(X_t^2) = \frac{\...
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question on finding the efficient GMM estimator

Trying to solve exercise 24 (page 468) from 13th chapter in Hansen's Econometrics book. For this model how can the efficient GMM estimator be found? I am confused as the model is different from the $...
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When the number of training samples is less than the feature vectors’ dimension

When the number of training samples is less than the feature vectors’ dimension, we should use a linear support vector machine (SVM) instead of a GMM classifier. Explain why the GMM classifier will ...
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BIC in Mclust package in r

I'm trying to use Mclust in r to cluster my data. The below is the plot of mclustBIC. From what I've researched, mclust now chooses the model with the highest BIC. However, my data have extremely low ...
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Panel ARDL : Cross-section invariant variable & CCEMG?

I'm working with panel ARDL estimation these days and a question came to mind while looking at available data. Can I use a variable that is cross-section invariant (the same across cross-sections, ...
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How to decompose the variance of log book-to-market ratio into components using GMM in Vuolteenaho (1999)?

I'm reading Vuolteenaho(1999). In this article, the author investigates whether the variation in stock market valuation level is driven by expected future cash-flows or by expected returns. In part V....
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Covariance Matrix Estimation for the Generalized Method of Moments

I am solving and empirical exercise on the Generalized Method of Moments. It's a classical application/test of a famous model in Economics. There are 2 parameters $(\beta, \gamma)$ to be estimated ...
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What does mean to have the number of used observations greater than the sample size in the Generalized Method of Moments(GMM) result?

I specified my model as follow: The result below gives a value of the Sargan test around 0.3, which is good according to Roodman. However, the number of used observations is greater than the sample ...
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Efficiency of IV vs GMM

I am trying to understand how IV/just identified GMM and overidentified GMM compare when it comes to efficiency. The way I understand it, we are able to identify the vector of coefficients in IV and ...
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what is allometry in geometric morphometrics, using procD.lm function

I want to test whether there is an allometry in family groups in "larvalMorph" dataset. I performed a simple allometry model and I want to make pairwise comparisons between family groups. <...
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Consistent but inefficient GMM

Consider the following linear model $$y_t = x_t' \beta +u_t$$ where $t =1,...,T$ and $x_t = (x_{1t} x_{2t} ... x_{kt})'$ , $ \beta$ is $k \times 1$ vector of unknown coefficients, $u_t$ is an iid ...
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Discuss that method of moment estimation is inefficient

Discuss that method of moment estimation is inefficient. Then model is Consider the following linear model $$y_t = x_t' \beta +u_t$$ where $t =1,...,T$ and $x_t = (x_{1t} x_{2t} ... x_{kt})'$ , $ \...
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When is the Optimal weighting matrix in GMM singular?

currently I am trying to estimate a simple linear regression: \begin{equation} y_t = X \beta + \varepsilon_t, \end{equation} where I try to find 4 coefficients and one specific predictor is an ...
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Question on GMM

Consider the following linear model $$y_t = x_t' \beta +u_t$$ where $t =1,...,T$ and $x_t = (x_{1t} x_{2t} ... x_{kt})'$ , $ \beta$ is $k \times 1$ vector of unknown coefficients, $y_t$ is an iid ...
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When should I prefer a parametric estimator to generalized method of moments?

The title is hopelessly broad, so let me focus on a concrete example. Consider the paper Identification of and Correction for Publication Bias by Andrews and Kasy. My question concerns the subsection ...
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What is the difference between GMM-style instruments and IV-style instruments in GMM estimation via xtabond2 or plm?

My question refers to the implementation of GMM estimators, e.g., in the package xtabond2 for Stata or package plm in ...
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Can the Arellano Bond model accommodate lags of explanatory variables?

The standard type of equation I've seen for the Arellano-Bond is y_it = r* y_it-1 + B*x_it + e_it. The endogenous variable y is a function of y at previous times, x at the current time, and an ...
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GMM regression and instruments count with xtabond2

I have to perform a difference GMM regression on my panel data. It's not important that it works, but if it does not I need robust motivation for why not. My panel data is divided in two bigger groups,...
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How to Remove Fixed Effects to Reduce Heterogeneity?

When discussing GMM estimation, Toni Whited and Luke Taylor suggest to reduce heterogeneity by ''eliminating fixed effects,'' see here on Taylor's slides (slide 36): My question: I'm not quite sure ...
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an alternative to GMM?

Dear StackExchange Users, I am currently working on my PhD thesis and one of the chapter deals endogeneity in the data. I have N the number of individual (here country) = 11 and T the time dimension = ...
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gmm function in R does not work due to singular variance-covariance matrix

We want to test the CAPM asset pricing models using the GMM procedure. The model is as follows: $$ R_{i,t} - R_{f,t} = \alpha_i + \beta_i(R_{m,t} - R_{f,t}) + \epsilon_{it}$$ The pricing errors at ...
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Choice between static and dynamic panel regression

I have a panel dataset with countries as individuals observed per year. My analysis concerns a macroeconomic study and as often happens in these cases (I would not be wrong but they are commonly ...
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Stopped by zero step from line search - R stops optimization early

I am trying to minimize an objective function, $J(\theta)$, with respect to $\theta$, a 19-dimensional parameter vector. $J(\theta)$ is a smooth nonlinear function so I have tried various gradient-...
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What does stata's laglimit mean?

I just saw an explanation to xtabond2 here ...
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How do I estimate time specific unobservable variables with panel data?

I have a problem that deals with human capital. I assume that wages $W_{it}$ are determined by the level of human capital $K_{it}$ and the market clearing rental rate that applies to all workers $R_{t}...
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What are the "moment conditions" in the GMM method? Also: GMM vs IV vs 2SLS?

I keep seeing talk of 'moment conditions' or 'moment equations', but don't exactly understand the context. Consider a very standard regression model: $$y_i = \beta x_i + u_i $$ where $u_i$ is an ...
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Surprising nonlinear variance-based scale est (bias adj) for Laplace Distribution competes with MLE?

Background: Using the quantile function (inverse cumulative distribution) for the Laplace distribution supplied with uniform random deviates (per the RAND() spreadsheet function), I examined an ...
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An intro document to IV-GMM method

I am looking for an introduction on Instrumental variable-generalized method of moments (IV-GMM), but cannot find more than the following: https://fmwww.bc.edu/EC-C/S2014/823/EC823.S2014.nn02.slides....
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GMM model with R

I am trying to run a GMM model, based on the Fama-Macbeth technique for robust s.e. (use this method for correction in auto-correlation and conditional heteroskedasticity). I am using R, after I have ...
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Python : GMM estimators in dynamic panel

I am trying to fit a GMM model in Python so I was wondering if someone knows if there is an equivalent of xtabond2 / stata or pgmm / R in Python. I've searched but I couldn't find anything similar.
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please guide me xtabond2

This is my first experience for GMM. help me, please. I should examine the relationship between X and Y across US states over the period 1993–2015 using the System GMM estimator. The lagged DVs, ...
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Why can a biased estimate still be statistically significant?

For example, I conduct an OLS regression and a regressor turns out to be statistically significant. When I conduct the same regression but with a GMM to account for serial correlation - I get a ...
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How to Test Linear Hypotheses about Parameters in Simulation-Based Indirect Inference

Setup: I have a model that produces a vector of aggregate outcomes, $\theta$, based on parameters, $\beta$. The relationship $\theta=\Theta(\beta)$ is stochastic and analytically intractable, but I ...
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Dynamic panel data model with AR(2) process in the errors

I set up the following dynamic panel data model: $$y_{it}=\alpha y_{it-1}+x_{it}^T\beta+v_{it}$$ Additionally, I have the process in the errors: $$v_{it}=\rho_1u_{it-1}+\rho_2u_{it-2}+\epsilon_{it}$$ ...
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Singular covariance matrix in GMM?

I understand that typically the covariance matrix should not be singular (see e.g. this discussion here: Could the covariance matrix of the moment conditions in GMM be ill-conditioned?) But in the ...
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System of equations GMM - time series (HAC) in RStudio [closed]

So I have a system of equations made up with some time series, to be estimated with a Generalised Moments Method model. Sth like: PREM[t] = phi_0+phi_1*PREM[t-1]+phi_2*IR[t-1]+phi_3*INAD[t-1]+phi_4*U[...
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Comparison of GMM and ML estimators for regression with correlated errors

Consider a linear model with normally distributed, autocorrelated errors \begin{aligned} y&=X\beta+\varepsilon \\ \varepsilon&\sim N(0,\sigma^2_{\varepsilon}) \text{ and autocorrelated.} \end{...
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Simultaneous GMM estimation: standard errors of common coefficients

So I am estimating a production function based on Wooldridge (2009) GMM adaptation of preexisting semi-parametric, 2-stage techniques. One of the upsides of GMM is simultaneous instead of sequential ...
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Use of Weighting Matrix (GMM)

While conducting estimation via the Generalised Method of Moments, or GMM, I understand that we need to minimise the following expression: $Q_n(\theta)=g_n(\theta)'W_ng_n(\theta)$ Where $g_n(\theta)$...
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Naming of mathematical elements in GMM?

I'm struggling with the naming of different elements in GMM. There doesn't seem to be consistency in the literature. What do we even call the moment integrand $g$? I take a stab below with help from ...
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OLS - Predeterminedness and moment condition

I'm having trouble validating if following procedure to test for predeterminedness is plausible. Given the linear model: $y_t=\beta_1+\beta_2x_{1t}+\beta_3x_{2t}+\epsilon_t$ Having $x_{2t} = y_{t+1|...
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5 votes
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What's the point in using identity matrix as weighting matrix in GMM?

What is the point of using the identity matrix as weighting matrix in GMM? GMM is the minimizer of the distance $g_n(\delta)'\hat{W}g_n({\delta})$, where $g_n = \frac{1}{n}\sum_ix_i\epsilon_i$. If we ...
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