Questions tagged [fixed-effects-model]

In biostatistics, fixed-effects may mean population-average effects. In econometrics, fixed-effects may represent the observed quantities in terms of explanatory variables that are treated as if the quantities were non-random.

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Including Fixed Effects in a LASSO/Elastic Net regression model (in R)

So this is a question has vaguely been asked before (see 1 and 2) but I have not been able to find a conclusive answer for anywhere. Essentially I have panel data for 300 US firms between 2012-2020 ...
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Lagged dependent variables: Is it safe to ignore bias over a long time horizon?

Suppose I have a Poisson model which investigates the effect of a county level policy on robbery counts. Here is the basic specification: $$ \text{log}(y_{it}) = \theta y_{i,t-1} + \sum_i\text{County}...
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Weak instrument test with fixed effects

I am trying to estimate a model with an IV strategy using fixed effects and standard errors clustered at the unit level. (I'm planning to implement this with the xtivreg command in Stata.) Could you ...
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Difference-in-difference in Stata with more periods [closed]

I want to set up a difference-in-difference regression to analyze the effect of top 20% ESG-rated firms on stock performance in different time-frames during the COVID-19 pandemic. However, I am new at ...
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Sinusoidal unit-specific time trends

Suppose I have a panel dataset with monthly observations over 10 years. I have a simple dummy intervention, where some policy is put in place around the Spring in every year and only affects some ...
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Applying Fixed Effects in a Difference-In-Differences Estimation using Least Square Dummy Variable Approach in R

I am trying to do a difference-In-differences (DiD) regression with fixed effects. The regression is meant to estimate the impact of participating in a televised Sports Event on the Social Media ...
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How should I interpret a Two-way-fixed-effects-regression?

I have problems with the interpretation of a Two-way-fixed-effects-model. I understood both the interpretation of the single individual effect and the single time effect in a fixed-effects-model. But ...
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Level of Aggregation for Event Study (Staggered DiD) Analysis

This might be a bit basic, but I'm struggling to determine the ideal level of aggregation of the data for an Event Study analysis. I wish to study if a specific policy affected fertility in certain ...
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Demeaning with respect to controls, make my dependent variable much smoother

I recently posted this question, about my dependent variable which looks as in the picture below, leading to the question in the link, about what type of regression to use. My regression always ...
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How do get rid of (1 not defined because of singularities) in R? [duplicate]

I'm analyzing data in R, I'm trying to see how some variables affect test scores (Value) of different countries. In the data, since there is different time periods for different countries I need to ...
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What are the assumptions of conducting a mediation analysis using structural equation modelling

What are the core assumptions when doing mediation analysis in structural equation modelling? I am estimating the classic mediation model using SEM in panel data in Stata with fixed effects (image ...
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How does adding country dummies relate to adding a variable that is fixed at the country level

I have firm level data from different countries (the data is completely fictional!). Let us assume that I am trying to estimate the following relation: $$ Sales_i = investment_i + country + u_i$$ <...
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Get Loglikelihood for bife

I want to calculate a fixed-effects model with bife. However, the logLik(model) function does not seem to work here. I know how to calculate it by hand but wonder why it is not working. Especially ...
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Clustering standard errors at individual and/or organisation level with fixed effects

So, I have a relatively large panel dataset (26,000 observations) with data on speech by individuals belonging to political parties. The data is grouped by individual-week (i.e. an observation for ...
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Can you combine IV regression w/ panel data fixed-effects regressions? If yes, can you explain how its done in practice and why its useful?

all the information is basically stated in the question, but I don't understand fully how you can combine an IV regression with a panel data fixed-effects regression and why you would do this. I hope ...
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Time invariant instruments in fixed effects models

I am running a fixed effects model of this kind $$y_{i,t}=\beta_0+\beta_1x_{i,t}+\gamma_i+\lambda_t+\varepsilon_{i,t}$$ Where $y_{i,t}$ is my outcome variable of interest, $x_{i,t}$ is an endogenous ...
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Panel Data anaysis with fixed effect model

I'm analysing a panel data including European banks through a certain time interval (2015-2019). I want to measure the effects of certain financial characteristics (size, leverage etc.) on the amount ...
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Which formula to choose for a mixed model / multilevel model

I'm trying to write a mixed model on repeated data, but I am having a hard time writing the formula. My database is composed of results of schools for different exams. Each line contains a result from ...
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Clustering the panel identifier in panel data: how can I say this correctly in my report?

I have panel data and I want to make clear in my write up that I clustered the standard errors at the individual level due to within individual correlation across waves, is this the correct way to ...
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Is a three-way fixed effects model equivalent to a triple difference estimator?

I have a conceptual question about the fixed effects model and the difference-in-differences (DD) estimator. Since a two-way fixed effects model is equivalent to a DD estimator, I was wondering if ...
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Quasi-Poisson Regression with non-integer count data

I am trying to run a fixed-effects Poisson Quasi Maximum Likelihood estimator on 3-dimensional(year, country, industry) unbalanced Panel data. The dependent variable is the number of patents(non-...
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1answer
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Understanding Random Effects in Linear Mixed Models

I am trying to understand why random effects are useful (in Linear Mixed Models). Specifically, why are they necessary and why can't we just used fixed effect dummy variables instead? For example, if ...
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R: difference in interpreting estimates of plm and LSDV model?

What is the difference in the estimates of plm and least squares dummy variable (LSDV) models? And how does the interpretation of the variables differ in general? Imagine the following ...
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R glm() does not converge / huge standard errors: collinearity? [duplicate]

I am trying to run a fixed effects logit-regression in R using glm() as follows glm(binary_outcome ~ as.factor(region)*as.factor(birth_cohort) + as.factor(region)*as.factor(gender)+as.factor(...
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On the use of the sampling year as fixed-effect

I have my database in temporal blocks (so I have my occurrence sites into the year of sampling of a few years with maximum 7 years). In order to fix the complete separation problem that I also have, ...
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How to go about nested random effects if model yields convergence problems?

I've built a mixed effects logistic regression model using glmer(). I'm trying to measure clause transitivity (2 possibilities: transitive/intransitive) Each observation is a clause and clauses are ...
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Explain fixed effects and random effects in terms of intercept and slope

I would like to find the easiest graphical way of explaining fixed effects and random effects models. I am pretty sure that I got the point for a pooling model and the fixed effects (which seems to be ...
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Caveats regarding the choice of the elementary panel model

Lets compare three panel most basic models: pooled, random effects, fixed effects. I observe common belief, that the fixed effect model estimation is "less biased", than in the other models. ...
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Fixed-effects Poisson estimator using quasi-maximum likelihood

I am trying to run a fixed-effects Poisson Quasi Maximum Likelihood estimator on 3-dimensional(year, country, industry) Panel data. The dependent variable is the number of patents(non-negative and non-...
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fixed effects models

Take the case of panel data with a time dimension in years and a cross-sectional dimension in plants (production units of firms). Each firm has many plants. I understand I cannot include plant fixed ...
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Fixed effect OLS with normalized coefficients in R

I want to estimate the following fixed effects regression: $$ Y_i = \gamma_{m}+ \lambda_b + \delta_{gb}D_{igb}+\varepsilon_i, $$ where $\gamma_m$ is municipality fixed effect, $\lambda_b$ is birth ...
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What exactly is controled for in a model with country, industry, and year fixed effects?

I don't have much experience with panel data so I apologize in advance if this sounds ridiculous. I am currently writing a thesis investigating the impact of political risk on managerial risk-taking. ...
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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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Panel regression with moving averages

Suppose I have a panel fixed effects regression of the form $$ Y_{it} = + \beta X_{it} + \alpha_i + \alpha_t + u_{it} $$ where Y is the outcome, X is a set of controls, ai and at constants for each ...
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1answer
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Two-way fixed effects and collinearity

I am modeling the relationship of an independent variable $(x_t/z_i),$ where $t$ indexes time and $i$ individual with an outcome $y_{it}$. The log transformation of $(x_t/z_i)$ is prohibitively ...
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How can I generate longitudinal data with correlated individual effects and serially correlated error term in R/Rstudio?

I would like to generate longitudinal data with correlated individual fixed effects (correlation with the explanatory variable) and serially correlated error term in R/Rstudio. The data generating ...
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non linear model with fixed effect and instrumental variables

I encountered a project which has binary outcomes and repeated observations of the same individual, but the panel is short (T is small), so it seems that the only ...
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1answer
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Time effects with dummy variable - regression

I am doing a multiple regression analysis and I wanted to inspect the time effect by using factor(Year) in R. However, I got the following summary results: Do you ...
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What is the difference between conditional and unconditional fixed effects?

What is the difference between unconditional and conditional (fixed effects negative binomial) regression models? A similar question was asked for quantile regression here: What is the difference ...
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Repeated Measures analysis of variance

I am new user of R software. I have 2 types of experiments. I want to analyze data from 10 jujube varieties and harvested fruits at 4 maturity stages. The effect of varieties is fixed while that of ...
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1answer
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Pooled cross-sectional data or Fixed Effects?

Note: Apologies in advance for mistakes in terminology and understanding of the methods, I am a novice at this. I would like to compare the mental health of different groups of immigrants (by region-...
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Fixed effects and seasonality

I am looking at historical hourly electricity demand data over multiple years and trying to regress it with hourly temperature data to understand the true relationship. I am curious if the hour of the ...
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22 views

Using random effects for a between-subjects variable to assess variability in a mixed model

I want to use a mixed model to test random effects for between subject factors. Similar questions have been covered before, with answers that it can be done using lme4. (See here and here for some ...
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1answer
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What is the mathematical model formula to a gam model fit using two fixed effects and interactions?

I am fitting a qGAM model via the qgam package in R; modelling the median of my response Y along covariates. It is of the form: ...
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Theoretical explanation of using time-fixed effects

I am currently sitting on an understanding issue. I did some regressions (pooled OLS) on my panel data and hold for time fixed effects. However, I am confused about the interpretation of the time ...
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1answer
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Random effect accounting for main effect?

Situation: I'm analyzing results from an experiment with a hierarchical structure. There are two groups A and B, multiple subjects within each group, and multiple measurements within each subject. ...
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1answer
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Regression model for a 2x3 mixed design with repeated measures?

Edited: I have a mixed (2x3) design setup where the between-subjects factor is "gender"(2 levels) and the within-subjects factor is "group"(3 levels). The main IV of interest is ...
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1answer
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Do unbalanced observations contribute to identification in fixed effects models?

I am quite confused on how to interpret my regression results. I want to estimate the effect of tariff changes $\tau_{st}$ in sector $s$, period $t$ on firm $i$ employment. I have two time periods (4 ...
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1answer
79 views

Treat year as a fixed effect, random effect, or covariate?

I have a dataset of fish species from different sites within a harbour collected over 17 years. The dataset consists of 1,042 sampling transects collected at 6 specific locations where fish were ...
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1answer
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Difference-in-difference and panel data models

I understand that according to the observations you have (two independent cross-sections in two or more time periods or the same individuals observed in two different periods), then difference-in-...

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