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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Given a specific value for a variable, how do you find the predicted value of a fixed effects multivariate regression?

I have specified the following model in R: model <- lm(yield ~ N + N^2 + P + K + S + factor(year) + factor(variety), data=data) As shown above, I ...
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implement i.year i.id FE from stata in python [closed]

When I have to control for fixed effects (time and id) in Stata, I usually run the regression with i.year and i.id (these are my var names). Now, I have to use python for a different project because ...
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What is the proper way to compute predicted probabilities in a fixed-effects logistic regression?

Predicted probabilities are quite helpful to interpret the output of logistic regressions. One can compute a predicted probability as follows: $$ P = \frac{exp(\beta + \beta_0)}{1 + exp(\beta + \...
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How do you interpret null coefficients in a fixed effects regression?

I'm trying to understand how the Covid vaccination status is affected by vaccination camps run by the factories (units) that employ them. My independent variables is the number of vaccination camps ...
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Possible censored data and Tobit regression

I want to study the impact of highways on deforestation. I am using annual data on forest cover. I define my deforestation/forest loss variable as a change in forest cover and if the change is zero or ...
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Suggest ways to represent additive fixed effects?

The dataset I'm working with has additive fixed effect where each term is significant. I want to plot the model fit with one of the factors temp here on the x-axis ...
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Suitable econometric specification for my data

I'm playing around with my dataset and as a start, I want to understand whether the absenteeism and vaccination rates for employees across a large number of factories with separate units is dependent ...
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Why include fixed effect in cross sectional ols?

Consider repeated cross-sectional data that contains observations in 10 provinces from 2011 to 2015. Each observation is an individual, but the same person is not observed each year, instead, ...
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How do you interpret Beta coefficients for Fixed Effects Panel Data Models?

Let's say we have House Prices across different cities (Bristol, Brighton, London, Glasgow) across time (Monthly data from 2016-2020) and we're trying to predict it using unemployment and crime. t = ...
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Can I add 3 fixed effect (firm, industry, year) in one Fixed effect panel model in R?

I am using the formula below to estimate the fixed effect panel model in R model_fe <- plm(formula = y~ x, data, index = c("firm ID", "year"),model = "within", effect =...
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plm/fixed effects models: fixef function error - wrong effect argument

I am using the plm function to analyze a large dataset with 120,000 IDs over three years. My specification looks the following: ...
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How to formally test which fixed effects to use with panel data?

I am using panel data consisting of macroeconomic variables on country level and for the time period between 2009 and 2019. I have a balanced panel data set. I performed a Chow test, a Hausman test ...
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Year-specific fixed-effects model in R

Does someone know, how I can translate this formula of fixed-effects in R? Here is the explanation of the single variables: Thank you in advance!
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Alpha and Interaction Term in a Fixed Effects Model

I am trying to replicate a study - I pasted the text of one of their models below. I get results in R with a long format. However, it seems like I don't understand fixed effects models enough to ...
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generate marginal residuals of a continuous variable by using linear mixed effect model

I was going to generate the marginal residuals of a variable by using linear mixed model in R. The marginal residuals are the residuals after adjusting for the fixed effects in the linear mixed model. ...
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Is it normal when including an interaction effect as a fixed effect in a mixed effect model the p-value of the main effect change drastically?

I conducted a randomized crossover study in which I had two within subject factors; condition and Time. When running a repeated measures ANOVA the analysis shows significant main effect of condition ...
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Random Effect in twin study of both MZ and DZ twin pairs

I am a bit stuck with the use of linear mixed models and its random effects in a twin study analysis. What I have is microbiome data for twins that are from MZ twin pairs and DZ twin pairs, so no ...
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Sufficient conditions for equivalence between regression on individual or group average data

I have often hear that running a regression on individual or (properly weighted) aggregated data should give the equivalent results, for example in this question or in Mostly Harmless Econometrics, ...
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My regression becomes insignificant when I add time fixed effects? [duplicate]

I have observations on a policy index and foreign direct investment for 30 countries, for 2001 and 2010. I want to explore the relationship between the two variables. I run an OLS regression and find ...
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Nested Individuals within a group - meaning?

I am reading "DID Intro" by Stata Corp LLC. It is recently updated, early April 2022. On page 7, it explains how Stata runs a panel-data difference-in-differences regression. My question is ...
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Can introducing time fixed effects variable into a PanelOLS decrease overall and between R^2?

I am trying to find if there is a relationship between the number of people employed by the tech industry within a city and wages in that city. I ran two Linear Regressions on my data. The first one ...
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Fixed Effects Model with non stationary variables

I'm in a bit of a pinch. I want to make a panel regression model, with N=22 and T=28. I guess this makes it a moderate panel (if not a long one). Not too big a N, but a fairly large T for Panel Data ...
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Missing Intercept in Fixed effect model output

I am running a fixed effect model using the fixest package due to the large number of fixed effects my regression is calculating. My study seeks to determine how the import share of a country by good ...
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Struggle with use of event study approach with non-firm data

I am attempting to use event study combined with difference in difference analyses to assess the parallel trend assumption in an individual level analyses of the impact of COVID on monthly income. The ...
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Help with Modeling Random Effects Model Interaction

I am having some trouble determining the correct modeling strategy for my research. I have a sample of approximately 500 movie observations nested within approximately 250 franchises. The average ...
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How to handle rank deficiency in a generalized linear model?

I am trying to understand if my model is sound even if there is rank deficiency. I am performing a generalized linear model with a binomial (or binary) distribution. My model has the fixed effect of ...
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Fixed effect instrumental variable (IV) regression with available diagnostic tests

May I please know an R package and code to run fixed effect instrumental variable (IV) regression with available diagnostic tests (e.g., weak instrument test, exogeneity test (using Wu-Hausman), ...
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County-level data fixed effect

I am using county-level data in my dissertation, and I received the below comment regarding analysis from my supervisor; "you mention that you use county-year FE. Since the outcome variable is ...
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Estimating time invariate variablies in difference-in-differences with fixed effects

I am using the following fixed effects model that has intercept and slope coefficient that vary across individuals. $Y_{it}$ - dependent vector variable for monthly income for individual i at time t. ...
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Intuition for using different fixed effects in the same table

I am new to econometrics and I am a bit confused about when to use different fixed effects. Ths picture below is from a paper I was recently reading. The 4 different fixed effects are used under ...
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Can you use GMM to overcome time-variant omitted variable bias resulting from FE?

I am looking at a FE model on the effects of R&D expenditure on labour productivity but not sure how to address the possible endogeneity resulting from time varying omitted variable bias. I cannot ...
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What pre-/post-treatment cohorts should I include in a generalised diff-in-diff with treatment on cohort level?

I analyse an educational policy that shortened mandatory schooling. The rollout of the reform happened over 3 subsequent years in different states ($c=0$ is the last graduation cohort pre-reform, $c=3$...
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Stata automatically omits all posiitve or all negative outcomes during poisson panel fixed effectes regression

I am trying to run a poisson fixed panel effects regression using xtpoisson on Stata where my outcome variable is a binary variable. For a majority of my units, the outcome variable = 0 for the entire ...
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Panel data mediation analysis

For my research I need to conduct a mediation analysis on panel data, my data setup is as follows: It is an (unbalanced) panel dataset including about 50 countries and 14 years. I have one dv, one iv ...
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Controlling for covariates in fixed effects regression

I have a panel dataset of students with their test scores and certain characteristics like student gender and parents' education. Let's call the main regressor of interest "x". If I control ...
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How to write out glm equation when there is a relationship between the independent variables?

We measured species abundance and corresponding temperature, rainfall, and pH across 500 sites. I want to run a regression measuring species abundance to abiotic variables. I am having a hard time ...
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Interacted Fixed Effect intuition

I am slightly confused about what drives the coefficient estimates when we have unit-by-time fixed effects? For example, suppose we have data on US counties, and we control for counties fixed effect ...
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Year fixed effect in time series data

I am following one country (USA) over time (2005-2010). In this time series analysis, I want to put a year or a time fixed effect to take into account the variation in the outcome that takes place ...
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How to interpret a regression with both time and individual fixed effects?

Let's say we have the following regression $Y = \alpha + \beta X + \gamma W + u$ the way I interpret $\beta$ is "the effect of $X$ on $Y$ keeping $W$ constant". Now let's say that I have ...
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Coefficients interpretation after recovering raw coefficients from a regression which used orthogonal regressors

I have an unbalanced panel of 747 observations and 15 years. After testing for Pooled, FE and RE, FE is the "best" model. However, I have multicollinearity problems. I can either remove one ...
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2 votes
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Firth's regression with many fixed effects

I've got a sample (n=7000) with a binary dependent variable with many 0s and only a few 1s (150 total) and therefore want to run a Firth's biased reduced regression to estimate the probability of the ...
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Difference-in-difference regression with pooled cross sectional data - fixed effects

I'm trying to estimate a difference-in-difference model with pooled cross-sectional data. The dataset consists of rental prices in one city for the years of 2011-2021 and includes a wide range of ...
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2 votes
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Meaning of & intuition behind predictors being fixed in linear regression [duplicate]

My question is a bit naive. I'm trying to get the exact & clear meaning of the phrase "predictor variables are fixed and not random in linear regression". According to my understanding, ...
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Model for repeated time-series data?

I have multiple time-series data measuring the same response over time for one subject. It is the same experiment that is replicated multiple times to get a more robust estimation... I am interested ...
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Fixed/Random Individual (site-specific) Effect, Fixed/Random Time Effect - Panel Data

I am wondering if the following conclusions are true: fixed individual effects (location-specific fixed effects), do not allow for location-specific variation, but they do allow for time-specific ...
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Multicollinearity with fixed effects

I have a dataset with N=90,000 observations, where each observation is a respondent in a survey. Respondents vary across multiple countries (50) and years (8). Each respondent was only surveyed once, ...
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Results from a Hausman Test

If the results I get from running a Hausman test in STATA is Prob > chi2 = 0.4504 does this mean I should use a FE or a RE?
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Interaction in Fixed-effect-models?

Is it possible to have the interaction of a time-constant continuous variable with a time-varying binary treatment in Fixed effect models? The outcome is a continious variable and I am doing a panel ...
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Panel Data- FE vs RE

I am trying to understand the different Panel Data models and I am getting confused by the different terms that people use, i.e., Random effect models and Random effects estimators and Fixed effect ...
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Why is there no panel quantile regression with two-way fixed effects yet?

I have been learning the quantile regression model recently, and my understanding is (possibly wrong) that quantile regression is essentially extracting the subsamples corresponding to a certain ...
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