Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [two-step-estimation]

Models in which a complicated function of data is estimated in the first step, and plugged again into another estimation model of primary interest in the second step

Models in which a complicated function of data is estimated in the first step, and plugged again into another estimation model of primary interest in the second step. Examples include:

  1. Heckman labor supply model estimated in two steps
  2. Murphy-Topel variance estimator for models with regressors generated in the first step
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Inverse Mills ratio after OLS

Short version of the question: Is it possible to create a dependent variable in the first step of the Heckman Selection model such that it is possible to obtain the values for the calculation of the Inverse Mills Ratio for the second step by OLS? If…
Rob123
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Instrumental variable Tobit in R

I have a data generating process of the form: res1 <- rnorm(N); res2 <- res1*0.5 + rnorm(N) x <- z[,1]*2 + res1; ys <- x*b + res2; d <- (ys>0); #dummy variable y <- d*ys; (blatantly stolen from an old RHelp thread, where the question…
RoyalTS
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Question about inverse in a two-step estimator as a joint GMM-estimators approach

I'm reading Newey & McFadden - Large sample estimation and hypothesis testing (in the Handbook of Econometrics, Volume 4, 1994, page 2178). My model which I'm interested in has some former estimation done before the estimation of the primary model…
Druss2k
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Fitting a fixed effect model to the residuals from a mixed effects model

In some statistical analyses (ie genetics), it may makes sense to perform a two-step regression analysis. In this analysis, the dependent variable is regressed against several independent variables. The residuals are taken from this first…
Andrew Marderstein
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About Identification in a 3 equation SEM

I got this example and I was wondering about a certain statement: $$ \begin{aligned} (I) \ y_1 &= \alpha_{12}y_2 + \alpha_{13}y_3 + \beta_{11}z_1 + u_1 \\ (II) \ y_2 &= \alpha_{21}y_1 + \beta_{21}z_1 + \beta_{22}z_2 + \beta_{23}z_3 u_2 \\ (III) \…
Druss2k
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Heckman sample selection vs. OLS

If the mills ratio of a Heckman selection model (with/without exclusion restriction) is not significant, shall I prefer to estimate my model with OLS instead? Or is it better to use the estimates from the heckman model although there seems to be no…
Steven
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Two step regression using group effects and DAG

Consider the following model $$y_i = \sigma_{c(i)} + \mathbf x_i^\top\beta + u^y_i $$ $$\sigma_{c} = z_c\lambda + \eta_c$$ where for all $i$ $$\mathbb E[u^y_i \lvert x_i] = 0$$ Data is given for a random sample $\{y_i,\mathbf x_i,z_{c(i)}\}_{i=1}^N$…
Jesper for President
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How to correct for generated regressor bias?

Dear Stack Exchange heroes, For my thesis I am writing a paper on the financial crisis. In my model, I use two regressions, which look like this: $$CONF = α + β_1 DEF_t + β_2 DIV_t + β_3 INF_t + β_4 IP_t + β_5 CONS_t + β_6 TBILL_t + β_7 URATE_t +…
Alexander Wolff
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Regression estimate of a non-negative variable

I have to estimate linear weight $\beta$ for regression $Y \sim \mathbf{X}$, where $Y$ are non-negative samples. If I perform vanilla regression (lets assume ridge regression) it will find $\beta$ such that most of estimated $\hat{Y}$ are…
avi
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Two-Step Procedure to account for multicollinearity

Suppose the estimation equation is $$ y=\beta _{0}+\beta _{1}x_{1}+\beta _{2}x_{2}+\varepsilon $$ where $\varepsilon $ is a disturbance and $x_{1}$ and $x_{2}$ are highly correlated regressors. In a seminar, the presenter showed the results of…
Aristide Herve
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Heckman selection model: probit selection & logit outcome

I have a situation where I think I need to use a Heckman selection model to correct for endogeneity. I am interested in studying the effect of firm's market entry mode on its performance. Factors that influence a firm's performance could also be…
Rnovice
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2SLS or IV with a tobit distribution in the first stage

I would like to use a two stage least squares approach (2SLS), where the first stage would benefit from a Tobit specification. I cross posted this on stackoverflow because there might be quite some coding involved. I have some sample data as…
Tom
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Using random intercepts in a multilevel model as dependent variables in a linear model

I have a mixed model with 3 levels: individual, city, and state, and so I get random intercepts for both cities and states. I understand that since cities are nested in their state, their intercepts are comparable only within that state. Now I want…
blueprint
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Interaction Term in Fuzzy RD

I'm hoping someone can help me understand the intuition behind the interaction term in a fuzzy RD model. The setup is as follows: $x$ = rating variable with discontinuity at $x = k$ $D$ = dummy=1 if $x > k$ $T$ = treatment variable; the probability…
bsauce
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Goodnes of Fit Measure for Heckman Selection Model

I am working with a two-step heckman selection model. In the first step the selection occurs based on a probit model, in the second step the mean equation is fitted with a linear model where the inverse mills ration is included. Technically I assume…
Michael L.
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