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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semPower: Accounting for Clustered Standard Errors in SEM Power Analysis with Fixed Effects Model
I am planning to analyse clustered data with a structural equation model and as I am planning on submitting my project as a registered report, I am first trying to do an in-depth power analysis (it is ...
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Should I adjust for inflation in a staggereded DiD with money as outcome and if so, how?
This question is currently making my head spin, and I haven't been able to find a discussion on it so far:
Suppose I am interested in the effect of an intervention, such as a healthcare reform, on a ...
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What happens when there is no variation within a category in panel data?
I have a dataset with multiple rows per individual. Each row represents the number of items sold by an employee on a given day. Suppose I have thousands of employees, and each of them has roughly five ...
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Two-Way Fixed Effects Model in R - Error - Multicollinearity
I am trying to build a two way fixed effects model (entity-specific and time-specific fixed effects). However, when I run the fixed effects code in R, I get the following error message:
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Which test statistic to report for (G)LMMs with categorical variables with >2 levels and/or interactions?
When building a glmm model with a binary outcome variable in R using the lme4 package I usually use something like the following structure:
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Equivalence between Mundlak and FE estimator: what with the generalized residuals of the control function?
I want to model the effect of an endogenous (left-censored) explanatory variable on a continuous outcome variable using an unbalanced panel dataset. For this, I use a control function approach.
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How to run a nested logit model with fixed effects in R or Stata?
I would like to run a nested logit model with panel data in R or Stata, but I am not sure how to proceed. I want to understand which factors influenced a person's choice to work full time, work part ...
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When your key independent variable is a difference between x1 and x2, do you control for x1 and x2?
I am trying to estimate the effect of difference in ranks between two people (i and j) on an outcome Y using a linear regression. My independent variable of interest is the $\beta$ coefficient on $(...
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Intuition behind twoway fixed effects
Let us assume we have the following linear regression model:
$$
w_{it}=\alpha_i+v_t+\varepsilon_{it}
$$
where $w_{it}$ represents wage of an individual $i$ at time $t,$ $\alpha_i$ is an individual ...
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How to show mathematically that random effects are more efficient than fixed effects?
I have read in several places now that random effects estimators are more efficient than fixed effects estimators, in particular here
I’ve searched this site and Google and couldn’t find this result. ...
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Interpreting regressions with multiple year and month dummy variables
I have a dependent variable measuring some event, say for each person, I have them in a dataset for a certain amount of months until they die, and they exit the data set. I define my dummy variable = ...
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Continuous variables as fixed effects
We are running a fixed effects regression to investigate the effect of different variables on weekly healthcare consumption. The data is comprised of several thousand time series, where each time ...
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Demeaning binary variable
I was confused regarding fixed effects regression model. Suppose I have a panel dataset with data on firms across several years. Introducing firm fixed effects and estimating deviations from means (...
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Fixed effects regression for unbalanced panel data (sample size, interaction term, statistical significance)
I have a highly unbalanced panel data set (n= 70 firms, T= 5-3000 observations per firm, N= 15000 observations overall). I specified a fixed effect regression with time and entity fixed effects. I ...
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Adding fixed effects in STATA
I wanted to include country fixed effects in my regression model. So this is the STATA code:
encode country, g(country_number)
regress lifeexp logGDPpercap i.country_number
The final estimation would ...
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R squared after including fixed effects
I have a regression model where the dependent variable is the difference in income between adjacent towns i and j. The independent variables are also differences in other parameters between these two ...
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ANOVA degrees of freedom
I'm running the following test
anova(fixed_model, random_model, test="LRT")
and I get the following results.
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Using feols() vs plm() vs lm() in panel regressions in R
I am using panel data at the district level. My outcome variable is the share of employed individuals in a given district. I am regressing this variable on a binary treatment dummy called "treat&...
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Adding fixed effects in regressions with cross-sectional data
I am working with cross-sectional data that spans 8 years. The data is at the individual level and the treatment variable is at the district level.
I am regressing individual-level outcome (whether an ...
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I want to know if my use of fixed effects (PLM) is correct
I have a panel dataset (Young Lives Dataset) which follows children from age 8-22 in five different rounds. I am using information about the children's time-use in rounds 2-4, when they are still ...
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Which model for panel data with non-random observation numbers per person?
I did an experiment where I randomly assigned participants to control and treatment group. All performed a task in which they had to illustrate images and then select one image in the end to be payoff ...
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Staggered diff-in-diff - interpretation
Reading a great study by D’Andrea and Limodio (2020), on the effects of expansion of broadband in Africa on fintech adoption and credit markets. They use a staggered diff-in-diff, taking advantage of ...
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What is interpretation of `V1 ~ V2 + (V3|V4)` in a mixed effects model?
My question is directly linked to the popular lmer cheat sheet. There was one situation that I didn't see mentioned in that cheat sheet and I wanted to know if it was a valid scenario or something ...
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Can you use country and year fixed effects in a regression with a gender dummy variable?
Perhaps a basic question but I would appreciate some explanation on this topic :)
I have a dataset covering approximately 30,000 loan applications. Besides characteristics of the loan (e.g., interest ...
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Which observations should I use for my panel data analysis?
I am currently working on my Master's thesis and for this I would like to examine the impact of the geographical location of Mutual Funds on their performance. For this I have panel data of mutual ...
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Unstable/inconsistent coefficients in OLS regression
General question:
What does it mean when the results of an OLS regression (or fixed effects regression) are unstable (i.e., the coefficients change and become significant or insignificant) considering ...
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My independent variable of interest changes sign and becomes statistically significant when I add year and country fixed effects to the model
I have a dataset that covers loan applications from the year 2012 to 2017. It also includes information on the borrower (e.g., age, income, employment status) and information on the loan (loan ...
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Hausman Test and RE results in Stata
I was interested in doing a panel regression so I read around on the topic and found that there are two ways to go about it. You can either do a fixed effect regression or a random effects regression ...
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Estimating treatment effect using panel data and absorbing binary treatment
I have a panel dataset of a large N and T = 24. I want to estimate the effect of a treatment (in this case, taking on a certain type of credit product) on Y which is an individuals credit score. I ...
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excluding meaningful zeros as robustness check in FE OLS?
I'm estimating a regression utilizing power plant data and drought data. A lot of the generators contain (meaningful) 0 values.
I utilize a IHS tranformation and my main regression residuals can be ...
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Q-Q Residual Plots with unusual kinks for both FE OLS and Logistic Regression
I have a dataset on power plant generation, which can be found here.
I use both a FE OLS and a Logit Model (no/some generation)
...
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Logistic Regression with fixed Effects and Interaction Term
I am trying to fit a logistic regression model in order to analyze if the fuel type has an influence on how powerplants respond to droughts (e.g. are Nuclear Powerplants more likely to shut down (...
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How to keep time-varying but entity-invariant variables in a panel regression fixed effects model?
I am working with a panel dataset that spans 2000Q1 to 2020Q3 and captures quarterly capital flows to 35 different Emerging Market Economies (EMEs). Along with the capital flows data, I have several ...
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Why are FGLS standard errors so low when estimating linear regression on panel data?
I am currently writing my master thesis an the effect of academic publication on anomaly returns. The idea is that in finance literature anomaly - factors/portfolios are proposed. After the factor is ...
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Which groups/time periods to compare in staggered Difference in Difference (DiD) with unit and time fixed effect logistic regression model?
I am trying to build a logistic regression with staggered DiD (for not yet treated) that incoporates unit and time fixed effect.
I am stuck with the logic of building the model as I am trying to ...
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How does a fixed-effects regression improve on a pooled OLS regression with non-normal residuals, heteroskedasticity and autocorrelation?
I am running a pooled OLS regression as a benchmark model on a panel data set of online forum member activity. The aim of the model is to understand the relationship between exposure to hate speech ...
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DID with Panel data (FE) - insignificant results
I run a DID with Panel data (FE) in Stata. I have two groups, Treatment Group (N=75); Control group (N=54). And have a time series of 6, 3 pre treatment and 3 post treatment. I am getting ...
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What is the algorithm to specify a fixed effects design matrix?
I have a procedure for generating the design matrix of an experiment that uses only fixed effect predictors.
The procedure depends on knowing the relationship between all pairs of predictors in the ...
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Fixed Effects Regression Model (with entity and time fixed effects)
I have run a simple linear fixed effects model to understand the relationship between exposure to hate speech and its adoption online. Model 1 is a simple entity fixed effects model with no covariates,...
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Do I want the linear regressions fixed, random or marginal effects as the "adjusted values"?
my apologies ahead of time if it's not as clear as I would like it to be. I'm using a linear mixed effect (nlme package) to determine the association between a modularity score (on a range of -1 to 1)...
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How to perform two-way fixed effect Difference in Difference test?
I am doing a research on the effect of Covid on fundraising success. I already implemented logisitc regression models with Covid as interaction variable but my supervisor wants me to use DiD.
I asked ...
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Poisson fixed effects model in pglm estimating time-invariant predictor
I am analyzing panel data on various municipalities (id_mun) over several years using the pglm package in R. My dataset contains a variable "treatment" which is continuous but is time-...
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Fixed Effects Regression with unbalanced panel data set
I have a panel data set that captures forum member's online behaviour for a period of five years at monthly intervals (t = 63). The total number of forum members in the data set is around 12,000. ...
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Implementing fixed effects regression with lag independent variables
I am running a regression model to identify the relationship between exposure to hate speech and the adoption of hate speech on a prominent forum, controlling for a host of other variables. ...
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Converting a Fixed-Effect Model to Mixed-Effect Model
I am studying the relationship between an experiment's predictors and its design matrix. For this particular question, I am curious how I can convert a design matrix developed for a Fixed Effect model ...
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How best to regularize high-cardinality fixed effects?
Let's say that I have data in the 10s-100s of millions of observations. This data is clustered across hundreds, thousands, or even millions of entities (in a B2B context, these might be corporate ...
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Can I compare Fixed effect regression with IV regression.?
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How can I analyze the causal effect of variable X on Y using cross-sectional data? I have employed IV regression, but now I want to test the effect of X on Y specifically for individuals belonging ...
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Experimental (Panel) Data: combination of fixed and random effects for regression models
I am seeking your advice on regression models using experimental (panel) data. I have around 230 individuals who have participated in four rounds of an experiment.
The dependent variable is ...
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Error: singular matrix 'a' in solve for categorical variables as fixed effects in bife-package in R
I am estimating a panel logit model, which looks like this:
$logit(P(event_it = 1)) = β₀ + β₁X_{i,t-1} + µ₁Z_i + α_i + ε_{i,t}$
where:
$P(event_it = 1)$ represents the probability of a flood occurring ...
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Difference-in-differences using R 'fixest' package for multiple treatments
I'm not sure if this is a question for StackOverflow or CrossValidated, as the question relates both to coding and statistics.
I have a panel data with information about sewage and water privatization ...
