chan1142
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What is the difference between two stage least squares and instrumental variable regression?
16 votes

The meaning of the words first Some people use the word "IV estimator" to refer to any estimator that uses instrumental variables. To them, IV estimators contain 2SLS, LIML, k-class estimators, and ...

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Why excluding intercept is dangerous if there is no literature back up in DID setting?
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6 votes

The Stata outputs say that you did not omit the intercept. No worries about the intercept. The _cons row is for the intercept. As you know, Stat's xtreg ..., fe will give you identical coefficient ...

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Is this an an endogeneity/simultaneity problem?
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6 votes

Let us consider Situation 1. Let us assume that $\rho$ is observed. If it does not work when $\rho$ is observed, there is no reason why it (using a proxy of $\rho$ as instrument) should work when $\...

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OLS bias in demand estimation: the bias always underestimate the demand's elasticity?
6 votes

Weak instruments combined with slight instrumental endogeneity can lead to a larger bias than OLS. As Nox's answer shows, the probability limit of the IV estimator is $\beta_1 + cov(z,u)/cov(z,x)$. ...

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Durbin Watson Test for an AR(1) process
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5 votes

Nerlove and Wallis (1966) result Nerlove and Wallis (1966) have discussed this issue. Their Equation (3) derives the probability limit of the Durbin-Watson statistic as: $$\mathrm{plim}\, d^* = 2 \...

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Confusion over homoskedacity assumption
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5 votes

Intuitive explanation might help. (i) $E[u]=0$ vs $E[u|x]=0$: Imagine partitioning the population by the value of $x$ so that each slice of population has the same value of $x$ in it. You can then ...

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Which measure to check in analysis (p-values or $R^2$)?
5 votes

R-squareds and p-values give different information. For example, suppose that you regress birth weight on mother's smoking. The p-value tells us whether the association is indeed nonzero (in the ...

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heteroskedasticity OLS model prediction
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4 votes

You can also statistically test heteroskedasticity (e.g., White's test: regress squared residuals from OLS on $\hat{y}$ and $\hat{y}^2$, or if you have a simple model, regress $\hat{u}^2$ on $x$ and $...

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If my IV (denoted Z) equals 1, my endogenous var D always equals 1; is this a problem?
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4 votes

Let $\hat{\pi}_0$ and $\hat{\pi}_1$ be the first stage coefficients. That is, $\hat{D} = \hat\pi_0 + \hat\pi_1 Z$. When $Z_i D_i = Z_i$ (if $Z_i=1$ then $D_i=1$), we can show that $\hat\pi_0 + \hat\...

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Can I add a variable that varies only with time in Least Squares Regression model with a time-fixed effects term?
3 votes

Your model has $\beta_3 * t$, which is a linear time trend, not time dummies. If that's correct, you are controlling for only a linear trend. Because oil prices do not have a perfect linear trend, you ...

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model design - fixed effects model for paired differences
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3 votes

The constant term in your final FE model has no specific meaning without further restrictions. For Stata, it is only chosen such that the (sample) mean of the estimated individual effects add up to 0. ...

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Linear Probability Model Instead of Logit in Fixed Effects Regression
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3 votes

FE logit requires the idiosyncratic errors to be IID across $i$ and $t$, quite a strong assumption. Also the regressors should be strictly exogenous, but it's the same for linear FE models. In your ...

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Is inconclusive region in durbin watson a problem?
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3 votes

There are cases error serial correlation is a disaster. For example, if your model is $y_t = \beta_0 + \beta_1 y_{t-1} + u_t$, then serial correlation in $u_t$ means correlation of $y_{t-1}$ and $u_t$ ...

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conditional mean and conditional median
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3 votes

In Alecos Papadopoulos's answer, both the conditional mean and the conditional median are linear in $X$. In the following example, the conditional mean is linear in $X$ while the conditional median is ...

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Using a Logit model to predict unknown outcome
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3 votes

If I understood you correctly, $\Lambda(x_i'\hat\beta)$, where $\Lambda(x) = e^x / (1+e^x)$. You can use predict in both R and Stata. Try in Stata: clear all *** Generate data set obs 10 set seed 1 ...

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General question about IV
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3 votes

In general, if $c_1$ is endogenous, you need instruments for $c_1$ as well. Example: Even when $x_1$ is exogenous, if $c_1$ is endogenous and $x_1$ and $c_1$ are correlated, then OLS (which is the IV ...

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How to choose instruments for GMM estimation?
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3 votes

As jmbejara says, better to be more specific, but let me guess. You have a linear model $y = \beta_0 + \beta_1 x_1 + \cdots + \beta_{10} x_{10} + u$, where $x_1, x_2, \ldots, x_{10}$ are endogenous. ...

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When to use dynamic panel data models
2 votes

The issue OP raises has always bothered me. Now I think it all depends on the purpose of the study and whether we want to control for $y_{it-1}$ or not. There are examples against dynamic models. As ...

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Synthetic control question on donors
2 votes

Welcome. Do you mean: if $x^*_{k,it}$ are the panel variables, then $x_{1,i} = \min_t x^*_{1,it}$, $x_{2,i} = \max_t x^*_{2,it}$, etc.? Usually people use averages over time or values at certain ...

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Why don't economists do regression diagnostics?
2 votes

This is a very thoughtful question. I think it is related with (i) the purpose and (ii) the sample size. Econometrics is very often concerned with causality (rather than prediction or forecast). For ...

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Interacting covariates with the instrument in the first stage
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2 votes

Short answer: No. Your model is $Y=\alpha + \beta X + \varepsilon$. Even when $X$ is exogenous, if you regress $Y$ on $X$, $W_1$ and $W_2$, then the OLS estimator is inconsistent (for $\beta$) unless $...

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influence of growing foreign demand for local products on the net exports in a fixed exchange rate regime
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2 votes

Yes, $IM$ increases in the equilibrium, but, no, $IM$ cannot increase more than $X$ does. Logical explanation: "$\Delta X < \Delta IM$ in the equilibrium" means that $A$'s GNP decreases. When GNP ...

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Why does instrument exogeneity imply conditional mean zero?
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2 votes

No, you're right, $Cov[Z_i,u_i]=0$ does not imply $E[u_i|Z_i]=0$ in general. If the author defined "instrument exogeneity" as $Cov(Z_i,u_i)=0$ previously, he/she is being careless here. "Instrument ...

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Regression - Testing for autocorrelation in the presence of heteroscedasticity
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2 votes

General remarks: The BG test under homoskedasticity can be done using the bgtest command in the lmtest package of R. The $(n-p)R_{aux}^2$ version mentioned in link works only under homoskedasticity. ...

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Regression with Dummy Variables
2 votes

That is natural and you are not missing anything. Let $y=\alpha + \beta z + u$. Your prediction of $y$ given $z=1$ is $\hat{y} = a + b$, where $a$ and $b$ are the OLS estimates. The prediction error (...

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Housing econometrics: interpretation of a quadratic variable
2 votes

That can happen and is not odd. For your model the partial effect of a change in $x_1$ on the average price equals $\beta_1 + 2\beta_2 x_1$ (use calculus for simple derivation). Thus, $\beta_1$ ...

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Predicting $y$ when response variable is $\ln(y)$
2 votes

Point prediction and CI are different. For point prediction, we are better off by correcting the bias as much as possible. For CI, what is required from the beginning is that the probability equals $...

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Number of observations in different panel data regressions
2 votes

It is conventional to report both the total number of observations (1000 in your case) and the number of groups (500 in your case). If you want or are allowed to report only one number as the number ...

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Interpreting correlation between fixed effect and explanatory variable
2 votes

You have done two different things. Your fixed-effects model captures the within-group over-time functional relationship between $debt_{it}$ and $y_{it}$ (that is, how much average difference in $y_{...

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Fixed effects, first differences interpretation
2 votes

The biggest difference between (1) and (3) is that (3) has incidental linear trends while (1) has common time effects. Differencing (1) gives (1a) $\Delta \log(uclms_{it}) = (\theta_t - \theta_{t-1}) ...

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