Questions tagged [panel-data]

Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.

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Applying machine learning techniques to panel data

I have a panel data in which I observe 1500 companies and many individuals work for those companies for multiple periods. I have explanatory variables at both individual (e.g. race, age, education) ...
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Test whether cross-sectional dependence in panel data follows known (network/spatial) structure

I want to test whether cross-sectional dependence in one specific variable (y) in panel data format follows a known structure (W) (e.g. network, spatial dependence), after controlling for individual ...
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Panel regressions with an interaction term between a time dummy variable and a time invariant variable

I have estimated the coefficients of the following equation, using the fixed-effect model: $Y_{it}=\alpha _i+ \rho _t + \beta _1 X_{it}+\beta _2 C_i*D_t+\epsilon_{it}$ I have observations from 1980 ...
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4k views

Difference-in-difference in panel data

Under which conditions should we expect the difference-in-difference estimate to be equal to the equivalent panel data model? Strictly speaking, whenever we have a experiment that offers a well ...
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Avoiding adjustments for time-varying controls in difference-in-differences (DID)?

In difference-in-differences (DID) analysis, it seems like a "folk theorem" that one should be very wary of adjusting for time-varying controls. The reason, eminently plausible, is that ...
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Average Marginal Effects from Chamberlain-Mundlak Device CRE Probit

I am trying to calculate the average marginal effects for the Chamberlain-Mundlak Correlated Random Effects probit model. The ultimate goal is to get something equivalent to the AME from the fixed ...
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When to use longitudinal (panel) weights vs cross-section weights in complex surveys

I'm currently working with a longitudinal dataset, the Kauffman Firm Survey. The survey tracks about 5000 firms starting from 2004 - 2009. Firms die out over the years. It has both cross-sectional ...
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822 views

What are the advantages of a random effects model versus a pooled OLS regression with cluster–robust standard errors?

Both models allow for explanatory variables that are time-invariant. I had thought that the advantage of a random effects model might be related to the fact that random effects models mitigate ...
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Longitudinal mixed model: What random effects are possible?

I'm faced with analyzing the following design: In a longitudinal study, the muscle tissue of about 25 subjects are analyzed at 8 timepoints. Specifically, 7 measurements are taken during a race ...
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ROC curves for repeated measures

I am trying to model ROC curves for a longitudinal dataset where participants were measured between 1-13 times. Time is not of interest but the fact that the measurements are autocorrelated an issue. ...
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565 views

Is this longitudinal data too complicated for GLMM or GEE?

After writing this post, I've realized that I am running around in circles, chasing my tail. Any help approaching this problem would be greatly appreciated, as I think I just need to bounce ideas ...
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Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
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Structural equation model with very small samples

I have two sets of a longitudinal data that I hypothesize to measure same latent construct.I am trying to test this hypothesis using Structural equation modelling technique. Basically, I am trying to ...
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Why two-step dynamic panel data estimator is better then one-step?

Could someone please give an explanation of why two-step dynamic panel data estimator is better then one-step? Can't quiet understand it... For example, from ...
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How to correct for heteroskedasticity in fixed effects panel regression with correction for clustered standard error?

I am a student at RSM and I have a question regarding my regression analysis for my thesis as I have encountered issues I do not know how to deal with. I have performance data (dependent variable) of ...
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593 views

Dynamic panel data with large $T$

Given a data set with $N=2634$ and $T=92$, I want to estimate a dynamic model. My first though was to use a classic System GMM estimator, however digging through the literature it turned out that ...
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Dynamic panel data model with AR(2) process in the errors

I set up the following dynamic panel data model: $$y_{it}=\alpha y_{it-1}+x_{it}^T\beta+v_{it}$$ Additionally, I have the process in the errors: $$v_{it}=\rho_1u_{it-1}+\rho_2u_{it-2}+\epsilon_{it}$$ ...
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Fixed effects in linear model

I am fitting a linear model on some panel data $$y_{it} = \sigma_{cr} + x_{it}^\top\beta + \mu_i + \delta_t+ \epsilon_{it}$$ where $\mu_i$ is individual fixed effect (in the sense used in ...
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Simple trend analysis with unbalanced & short panel data

I have the following (unbalanced) panel data: yearly sustainability ratings (ESG) of ca. 2000 individual firms over a 11-year period. The average observations per firm only covers 5.3 periods. These ...
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291 views

Machine Learning for Causal Inference with Panel Data: Possible to combine ML estimators with additive/linear terms to derive diff-in-diff estimator?

My question is motivated by the following. First consider the non-panel case, where we have two groups, the treated group ($g=t$) and the comparison group ($g=c$), and are trying to estimate an ...
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673 views

How can I control for time-varying unobserved heterogeneity with panel data?

I'm just beginning to learn econometrics, and I just learned about the fixed effects estimator, and the first-difference estimator. It's quite straightforward that those techniques allow me to control ...
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Choosing between two available packages for multinomial logit on panel data in R

There are two available packages for estimating multinomial logit models in R, namely mnlogit and mlogit. I am wondering whether someone who used both can share his experience. Which one is better / ...
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Can I get away with using GLM models on “pseudo-panel” big N small time=T data?

Suppose I have a kind of panel data set, where we track the investment totals of a great many customers, which may be highly variable, and is measured on a monthly basis over the course of 7-10 years. ...
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How to properly use generalized method of moments (GMM) estimation with plm in R?

In the context of panel data analysis my key independent variable wage affects the response not immediately but rather over time. Therefore I would like to use some ...
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996 views

Which is the best approach? Difference in Difference with Heterogeneous Effects

I am interested in the performance of two competing approaches to estimate a treatment effect, for which one would expect heterogeneous effects. The point of origin is a treatment conducted from ...
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2k views

Which logistic model is appropriate for longitudinal data?

I have data in longitudinal or clustered format (please see the example below). My response variable is dichotomous. I want to examine which factors explains why a subject in the dataset gets Y=1. In ...
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579 views

Longitudinal data analysis where meaning and metric of response variable varies over time

Determining what factors predict change over time is a topic of investigation in many fields and there are a variety of readily implemented methods for analysing repeated measures in the same metric. ...
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810 views

How to deal with attrition problem in panel data

I'm trying to test a certain "treatment effect" with panel survey data, and facing a problem with potential attrition bias. There are some observations from the baseline years missing in the follow-up ...
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307 views

How to use glmnet with panel data?

I would like to use regularization from the package glmnet on my panel data. I have the following data: country - year - gdp - population - water usage, so for each country, I have a year in which the ...
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How to use lagged dependent variables (panel data) in practice?

Working with a panel data set with a daily time series structure I was told to include a lagged dependent variable. The dependent variable is daily electricity consumption of a medium size sample (>...
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3k views

R plm strange error when using pgmm

I have a data.frame that looks like this: ...
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Unbalanced panel data: Fixed effects?

I have an unbalanced panel dataset with N=10 firms and T=61 days. Because one variable had values outside the theoretical range I had to constrain my dataset, which left me with only 239 observations. ...
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292 views

Longitudinal paired analysis

I need your advice regarding a complicated design. I am testing data regarding new eye drops that suppose to decrease some quantitative measure. For every subject, one eye is randomly assigned with ...
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255 views

Panel data model for exports and exchange rates

Suppose I have 4 years worth of monthly panel data on: exports of widgets $y$ from home country to 12 different nations (in US dollars) nominal exchange rates $x$ for those 12 countries (in US ...
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59 views

Adjusting for experimentally-caused panel attrition when evaluating treatment effects

This question involves a questionable hypothetical scenario, but please bear with me. Suppose I ran an experiment in a coffee stand where the treatment was playing country music instead of the usual ...
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121 views

Parametric segmented or piecewise regression with heteroscedastic errors

I am fitting longitudinal data with an increase in variance over time. The standard physiological model is a bi- or tri-linear model with variable breakpoints. The estimated parameters are used to ...
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261 views

Inverse probability weighted estimation of censored longitudinal data in R?

I'm looking for a package for estimating the mean of a longitudinal response under monotone dropout using a "state-of-the-art" method based on GEEs, in R (AIPW ...
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506 views

Lag Selection Modelling 'Pseudo' Panel Data

I have what I would call a pseudo panel, where my dependent variable varies over time and space (regional death counts), but my x variable of interest does not (national wage time series). Basically, ...
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Fitting panel data with both variable and constant coefficients using R

I'm working with panel data and want to fit a model of the form: $y_{ij} = \alpha_{i} + \beta_{1i} x_{1ij} + \beta_{2i} x_{2ij} + \beta_{3} treatment_{ij} + \epsilon_{ij}$ The data consist of (...
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Random Forests / adaboost in panel regression setting

Tools such as random forests or adaboost are powerful at solving cross-sectional binary logistic problems or prediction problems where there are many weak learners. But can these tools be adapted to ...
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Panel Data: In a fixed effects model, does auto-correlation introduce bias?

Given a panel of countries over time, a fixed effects estimator makes sense to control for country-specific effects. My intuition tells me that if the dependent variable is correlated with lags of the ...
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Simulate Arellano-Bond

I have fitted a dynamic panel data model with Arellano-Bond estimator in gretl, here is the output: ...
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1answer
86 views

Is a DID model appropriate?

Suppose I have 3 groups (US states). One group has always had a "treatment" throughout the time period (always had a specific legal prohibition). One group never had the "treatment"...
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1answer
37 views

How to train Prediction model for longitudinal data, with large number of time points?

Given a longitudinal data, that has date (in month-year format) as one of the independent variables and other independent variables being Gross metric tonnes, Tensile strength(UTS), weight per unit ...
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1answer
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How to choose between FE and BE model

I am reading the book: Baum, C. F. (2006). An Introduction to Modern Econometrics Using Stata (Stata Press, ed.). In particular Chapter 9 treats panel data and explains the Fixed Effect (FE) ...
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1answer
125 views

Lagged independent variable's coefficient changes when higher lags are included

I'm running a TSCS analysis with the plm library in R with which I want to explain students' performances. The data consist of approximately 1100 units and has 25 points of measurement - panel data ...
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140 views

Fixed Effects: Group level variables but individual level outcomes

tl;dr: In fixed effects and first difference estimation, does having sets of individuals where the change in $X_{it}$ over time is identical lead to estimation problems? When using fixed effects (FE) ...
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1answer
196 views

Clustered standard errors and time dummies in panel data

Assume a simple linear regression model, I have $i$ firms and $t=17$ periods $$Y_{it}=\alpha + \beta_2 T_2 + \beta_3 T_3 + \cdots + \beta_{16} T_{16} + \gamma_i + \varepsilon_{it}$$ In this case, $t=...
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203 views

What machine learning and deep learning models are used for longitudinal studies (panel data)?

As the title suggests, I have a longitudinal database (also called panel data). (I have over 100.000 observations. The time period is X years. This means that for every year I have the values of the ...

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