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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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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 ...
Dom's user avatar
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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 ...
Economist1111's user avatar
9 votes
2 answers
6k 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 ...
user30474's user avatar
7 votes
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On the defense of "change from baseline" even in randomized trials - can anyone question points in this article?

Many times I read a strong criticism on the change-from-baseline (adjusted for baseline or not) both in randomized and non-randomized. Several people advised "don't even think of reporting the ...
abrakadabros's user avatar
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320 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 ...
Cedric Standaert's user avatar
7 votes
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671 views

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 ...
Student's user avatar
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507 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 ...
Yakkanomica's user avatar
7 votes
2 answers
1k 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 ...
Kevin Kang's user avatar
7 votes
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2k views

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 ...
dimitriy's user avatar
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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 ...
SJDS's user avatar
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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 ...
iinception's user avatar
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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 ...
Robert's user avatar
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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 ...
Mark's user avatar
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6 votes
1 answer
665 views

Combining cross-sectional data with panel data

Let's say I want to regress crop yield as a function of rainfall and temperature. I collected data across 20 locations and 10 years and construct a model regressing yield on rainfall and temperature ...
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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 ...
Luisa's user avatar
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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 ...
Sonali D Bhavsar's user avatar
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355 views

How to split longitudinal data into training and testing sets

I'm trying to model the likelihood a customer will be delinquent on their loan by next month based on their most current data at the time. Currently, I have longitudinal data and am having some ...
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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 ...
the_scheining's user avatar
5 votes
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806 views

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 ...
COOLSerdash's user avatar
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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. ...
Jennifer McConnell's user avatar
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603 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 ...
user3708129's user avatar
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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 ...
user1665355's user avatar
5 votes
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3k views

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 ...
Ram Ahluwalia's user avatar
5 votes
1 answer
774 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 ...
Gerald's user avatar
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4 votes
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Should inverse probability weighting be used in two-way fixed-effects panel regression?

Let's assume a (balanced) panel data set with two measurement points $t_0$ and $t_1$, where $t_0$ may be considered as the baseline. Some of the ID's are treated at $t_1$, i.e. $D=1$, the assignment ...
jay.sf's user avatar
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4 votes
0 answers
875 views

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-...
Laura's user avatar
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4 votes
0 answers
77 views

How to adress the -0.71 correlation artefact in the pre-post analysis of change from baseline in non-randomized trials?

Let me make some introduction first. It's well known, that in randomized trials, in the pre-post trials, by the formal pharmaceutical regulatory guidelines, both raw post and change scores should be ...
Three Standard Deviations's user avatar
4 votes
1 answer
687 views

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) ...
robertspierre's user avatar
4 votes
0 answers
194 views

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: $$v_{it}=\rho_1u_{it-1}+\rho_2u_{it-2}+\epsilon_{it}$$ ...
marco11's user avatar
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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 ...
Jesper for President's user avatar
4 votes
0 answers
659 views

Coefficient of Ratio + Ratio of Coefficients: Inconsistency

I have regression results about the effect of a treatment on two outcome variables, $N$ and $D$. The coefficient on $N$ is positive. The coefficient on $D$ is negative. These results suggest that the ...
ABC's user avatar
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4 votes
0 answers
436 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) ...
Phil's user avatar
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4 votes
1 answer
690 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=...
user6441253's user avatar
4 votes
0 answers
1k views

Appropriate multiple imputation method for longitudinal data (R package mice)

I'm analyzing a dataset from a longitudinal study aimed at finding if a set of predictors is associated with the trajectories of an outcome, which is measured each day for seven days. The dataset is ...
Emanuele Giusti's user avatar
4 votes
1 answer
4k views

Difference-in-Discontinuities Design

Recently I came across the paper written by Grembi et al. (2016) and thought the methodology employed by them, Difference-in-Discontinuities Design (a combination of Regression Discontinuity and ...
user196456's user avatar
4 votes
0 answers
262 views

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 / ...
splinter's user avatar
  • 141
4 votes
0 answers
225 views

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. ...
Lepidopterist's user avatar
4 votes
0 answers
1k views

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 ...
Mamba's user avatar
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4 votes
0 answers
2k 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 ...
Tartan Leaves's user avatar
4 votes
0 answers
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 ...
FKG's user avatar
  • 300
4 votes
0 answers
628 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. ...
Richard Border's user avatar
4 votes
0 answers
938 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 ...
Wright's user avatar
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4 votes
0 answers
482 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 ...
Snowflake's user avatar
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4 votes
0 answers
2k views

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 (>...
Aki's user avatar
  • 517
4 votes
0 answers
3k views

R plm strange error when using pgmm

I have a data.frame that looks like this: ...
user avatar
4 votes
0 answers
2k views

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. ...
Peder vd B's user avatar
4 votes
0 answers
434 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 ...
user41883's user avatar
4 votes
0 answers
302 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 ...
dimitriy's user avatar
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