7 votes
Accepted

Why we need to add firm and year relating independent variables in two-way fixed effect model?

Consider the following regression specification where, $t$ is time, $c$ is the firm, $y$ is an outcome and $x$ is a variable of interest. $$ y_{c,t} = \alpha + \beta x_{c,t} + \varepsilon_{c,t} $$ ...
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  • 8,737
6 votes
Accepted

What is a good proxy for government quality?

Using corruption is part of it but a bit restrictive way to measure government "quality". You may use aggregate indicators as the one developed by the Worldwide Governance Indicators (WGI) project ...
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  • 6,652
5 votes

Robust Standard Errors in Fixed Effects Model (using Stata)

Use -areg- in Stata, and the standard errors will come out as in the textbook. Specifically, the command ...
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4 votes

Robust Standard Errors in Fixed Effects Model (using Stata)

I'm still not sure if I'm doing something wrong. However, it is useful to note that I get the same results in R. ...
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  • 9,107
4 votes
Accepted

Difference-in-differences with long time horizon and repeated treatments

This question is related to a post I addressed on CrossValidated. The "generalized" difference-in-differences (DiD) estimator is amenable to settings with multiple groups and multiple ...
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4 votes
Accepted

How to justify the treatment and control groups for Difference-In-Difference with staggered implementation of laws?

[W]hy do they need to write down "adopted a leniency law at some later point of time"? Because in Korea case, the word "our sample period" means "1995-2002" already. ...
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4 votes

Fixed effects vs first difference

I do not think the premise is correct. Following Brüderland and Volker in Best & Wolf The SAGE Handbook of Regression Analysis and Causal Inference [square brackets have my remarks]: Both ...
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  • 41.6k
4 votes

How to use panel data for a time series machine learning problem?

This is a question that crosses all over the place, each of these techniques are different. Here are some very loose guidelines. As a baseline, recall that in econometrics you may have performed ...
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3 votes

How to perform unbalanced panel data regression in R?

Here the solution would depend on what you want to accomplish. Note the problem is not just that the series is unbalanced, for an ordinary unbalanced panel data-set where firms have different number ...
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3 votes

A question about Fixed effects estimation

Having read up on your question it seems the fixed effect is fixed. If this is indeed the case it will have zero variance and hence zero covariance with any variable.
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  • 26k
3 votes

In panel data application, when using Fama and MacBeth regression is preferable over the fixed or random effect model? thought

I cannot precisely answer your questions because I do not know which exactly regressions you want to perform as @jmbejara says and which papers are you referring to that use Fama-MacBeth regression. ...
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3 votes
Accepted

Pesaran's CCEP estimator in eviews

The technique described in the question is almost correct. Consider a panel data set consisting of three cross-sections ($a$, $b$, and $c$) and three time-periods ($1$, $2$, and $3$). Let y denote the ...
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  • 884
3 votes

Robust Standard Errors in Fixed Effects Model (using Stata)

To understand the issue let's review what is the so call robust variance-covariance matrix estimates (VCE) and the implied "robust" standard errors. The robustness is meant to allow for violations of ...
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3 votes
Accepted

Linear Probability Model Instead of Logit in Fixed Effects Regression

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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  • 1,889
3 votes
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model design - fixed effects model for paired differences

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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  • 1,889
3 votes

Up-to-date survey of panel data models

As rightly pointed out by @1muflon1@ "Panel data is nowadays quite a big field - usually you will have separate chapters for panel IV, panel logit/probit, panel time series etc". But if you ...
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  • 6,652
3 votes
Accepted

How to choose between fixed and random effects using economic intuition?

Here is an example where just from an economic perspective fixed effects are better than random effects. Suppose you have panel data and you want to regress earnings $y$ on some observable ...
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  • 6,652
3 votes

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

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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  • 1,889
3 votes

Replicate Blundell and Bond (2000) results using R

3. How do we recover parameters from production function estimates (INCOMPLETE ANSWER - will be updated with how to do this in R once I have time to figure it out, or if somebody else knows...) ...
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  • 101
3 votes
Accepted

Converting monthly data to quarterly

I've seen them summed somewhere but I cannot exactly remember where. Ultimately I don't think that it makes much difference. The quarterly sum is just the average multiplied by three. Since local ...
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3 votes
Accepted

Interpretation of coefficients in a regression with a lagged dependent variable

tldr If $\mathbb{E}[\varepsilon_{i,t}|X_{i,t-1}, Y_{i,t-1}] = 0$ then the coefficient $\beta_2$ is equal to: $$ \frac{\partial \mathbb{E}[\ln Y_{i,t}|X_{i,t-1}= x_{i,t-1}, Y_{i,t-1} = y_{i,t-1}]}{\...
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  • 8,737
3 votes
Accepted

When I should concern if the number of observation varies quite a bit?

The number of observation changes likely because there are missing observations for some controls. Unless you suspect that statistics might systematically not collect data for some firms (e.g. maybe ...
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  • 41.6k
3 votes
Accepted

Clustering of standard errors in Fixed Effects models

Consider the following specification: $$ Y_{i,g} = X_{i,g}\beta + u_{i,g} $$ Where the residuals have different mean across groups and have within group correlation: $$ \begin{align*} &\mathbb{E}(...
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  • 8,737
3 votes

Pooled OLS, fixed effects and random effects yield very similar results

$$y_{it} =\beta_0 +\beta_1 x_{1it} + ...+\beta_k x_{k_it}+\alpha_i +u_{it} $$ The random effects assumption is that $E[\alpha_i +u_{it}|X]=0$ where $X$ denotes all independent variables at all time ...
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2 votes
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Panel data, simple rearrangement?

By stnadard OLS regression results, in the simple regression $$y_t = \alpha + \beta z_t + v_t, \;\;\;t=1,...,T$$ we have that $$\hat \beta = \frac {\sum_{i=1}^T (z_t - \bar z)(y_t-\bar y)}{\sum_{i=...
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2 votes

Interpreting correlation between fixed effect and explanatory variable

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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  • 1,889
2 votes
Accepted

When does the "stationary" problem become and issue with panel data?

The data sample is so small that formal testing for stationarity would be essentially worthless. Inspect visually your individual series for any obvious trend. This would be the case where even with a ...
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2 votes

Fixed Effects Estimation and Inconsistency

You can't identify the effect of oil price when Year FE are applied, since the world oil price is perfectly correlated with year Fixed Effects. You can't identify the democracy indicator if you ...
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  • 1,262
2 votes

Testing for heteroskedasticity in panel data vs time series?

You can regress residual squares (from RE or FE depending on your estimation) on $X_{it} \hat\beta$ and its square using the clustered standard errors (the ...
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  • 1,889
2 votes

How to perform unbalanced panel data regression in R?

It would be helpful to provide a reproductible example. In the paper Panel Data Econometrics in R: The plm Package, the authors explicitly mention that economic panel datasets often happen to be ...
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