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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Number of instruments in GMM (using pgmm in R)
Number of instruments used in GMM model (pgmm function in R)
I performed a GMM (Generalized Methods of Moments) analysis in R using the ...
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Sargan test results = 1 in system GMM
I am having difficulties understanding my diagnostic test results for my twoways effects two-step model system GMM, which I performed in R.
The results of my Sargan test (test for overidentification ...
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Does PLM package (PGMM function) use Windmeijer-corrected cluster-robust errors? [closed]
I am performing a GMM analysis using the pgmm function in the plm package in R. I read a lot about different errors (nonrobust, ...
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Problems with GMM (Generalized Methods of Moments) in R
I am interested in performing an analysis using a GMM model for a panel dataset.
I am conducting the analysis in R, using the pgmm package. My code is the following:...
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How do deal with multicollinearity, endogeneity and interpret the interaction terms in a panel dataset?
The model
ŷ = b0 + b1X1 + b2X2 + b3X1X2
ŷ =company financial performance metric
X1 = carbon emissions
X2 = carbon assurance
X1X2 = interaction term
The issues:
Let’s say:
• X1 + X2 are related (but ...
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Dynamic panel data model with treatment
Consider a simple dynamic panel model with a single lag: $$y_{it} = \alpha_i + x_{it}'\beta + \rho y_{i,t-1}+\epsilon_{it}$$
Now assuming that $x_{it}$ is most ordinary covariates, this can be ...
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GMM and Instruments
I am using GMM for my research work. Previously, I have used ivreg command in stata in which we manually specify the instrumental variable for the endogeneous variable. I was just curious and ...
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System GMM yields invalid results while Difference GMM is correct
While studying about GMMs I generated the following dataset to experiment with.
...
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Which model should I use for determinants of NPLs
I am working on a subject called The determinants of NPLs in a country (NPL = non performing loans).
My data is a dynamic panel data of 15 years and i got my data yearly.
The dependent variable is npl ...
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How to understand the binary latent variable z in GMM model?
GMM(Gaussian Mixture Model) itself is a mixture of Gaussian with each having the proportion of $\pi_k$, $$\sum_{k=1}^{K}\pi_k=1$$this is easy to understand. But when introducing the latent, I don't ...
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Estimation of panel data
I am estimating the effect of certain bank characteristics on the bank lending in monetary policy in the euro area. Therefore I am looking at different bank characteristics (size, liquidity and ...
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GMM efficiency vs IV efficiency condition
Let the true model be
$$
Y = X_1\beta_1 + X_2\beta_2 + u
$$
but $X_2$ is omitted, so we estimate
$$
Y = X_1\gamma_1 + e
$$
by a valid instrument $Z$, so $\gamma_1$ is the 2SLS estimator.
Assume now, $...
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Proving uniform convergence of moment restriction score function in GMM asymptotic normality proof
I am asked in a homework question to prove asymptotic normality for the generalized method of moments estimator. The assumptions (which i think are necessary to solve this particular subproblem) given ...
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How to build the covariance matrix with different weighted moments via GMM [closed]
I have two sets of moment conditions, one is IV moment with N observations but the second moment only has N_1 observations, N_1<N.
How to build the covariance matrix? Appreciate for any replies!
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Fitting a 3D GMM in a 3D space is equivalent to fit a gaussian in each 1D coordinate?
I have a 3D data set data represents positions in X,Y,Z space. The positions are generated by a Poisson model. I would like to filter out outlier positions, i.e., positions that are farther than the ...
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Clustered vs. GMM-based standard errors: which ones to use in asset pricing?
This question was posted on Quantitative Finance Stack Exchange a while ago. While it was received positively there and generated a reasonable amount of views, no answers have been posted. Thus I am ...
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Maximum likelihood vs generalized method of moments
I am trying to understand how maximum likelihood (MLE) and generalized method of moments (GMM) are related to each other. In particular, I often see people saying that MLE can be written in terms of ...
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Understanding well some definitions of identification in econometrics
In the context of parametric models with $\Theta$ being the parametr space and
$$\mathbf P :=\{ P_\theta : \theta \in \Theta \}$$
assume that $P$ denote the true distribution of the observed data $X$ ...
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How to understand rank condition?
In GMM estimator, rank assumption says $E[z_ix_i]$ has full rank of $k$, where $z_i$ is a $l\times 1$ vector of instrument variables, and $x_i$ is a $k\times 1$ vector of endogenous variables, and $k\...
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Central cross moments of independent random varibales
The central cross-moments of a random vector $[X_1, X_2,\dots, X_n]$ is
$$ \mu_X(n_1,n_2,\dots,n_n) =E[(X_1-E[X_1])^{n_1}(X_2-E[X_2])^{n_2}\dots(X_n-E[X_n])^{n_n}]$$
I wish to know if $\mu_X(1,1,\dots,...
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Draw conditional samples from GMM
I have a dataset with 4 numerical features and class labels for each data point. I have implemented a GMM classifier to predict the class of each training sample.
Now I would like to generate new data ...
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How do Measure "Robustness" in Statistics?
I am an MBA Student taking courses in Statistics.
Our prof was comparing two different methods of estimating the parameters for a regression model: General Method of Moments (GMM) and Maximum ...
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Is there a formula for estimating confidence intervals for indirect inference estimates?
Indirect inference is usually deployed to estimate parameters $\theta$ of simulation models, i.e. models for which likelihood is unknown or intractable but that can be "run forward" ...
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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 ...
Adam3s
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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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686
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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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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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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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337
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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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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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1
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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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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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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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686
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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, ...
