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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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LASSO Regression using Panel Data

I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction ...
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How to compute measures of dispersion and statistical significance of the impacts of a panel Spatial Durbin model (SDM)?

I ran a panel Spatial Durbin model (SDM) and computed the summary measures of impacts (direct, indirect and total). Now, I would like to get measures of dispersion for the impacts estimates as well as ...
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Difference-in-difference: common trend

I'm new to this concept, and I'm referring to the book Mastering Metrics by Angrist. It states that an important assumption of Difference-in-Difference is the common trend assumption. I'm a little ...
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Using longitudinal income data to predict cross-sectional outcome measure

I have the following data: income data measured yearly from 2004 to 2011 in households occupied by adolescents a single variable denoting households where parents have divorced (divorced vs non-...
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Prediction values [on hold]

I don´t have a model, just values of exports as a percentage of gross domestic product for 28 countries, from 2007 to 2018. I want to make a prediction for 2019 in R Studio. It´s a panel data, but don´...
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Conditional expectation in Basic Linear Unobserved Effects Panel Data Model

I want to see that $ E[u_t|X_t,c] \Rightarrow E[X_t' u_t]$ in a Panel Data Models
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Detecting trend in panel data, smoothing techniques and outlier detection

I'm conducting an analysis on a Landsat scene to detect trends for change detection phenomena (forest disturbances) over a time series of 20 years. I identified on the image the pixels that are ...
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Poisson Regression in R with individual fixed-effects and month/year fixed-effects

I'd like to use a fixed-effect Poisson Regression model to examine whether opting into 2 different schemes (specified as dummies in my model) can lead to increased exercise. I have longitudinal data,...
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nested logit with individual level fixed effect (panel data)

As is stated in the title, I have several questions concern the combination of nested logit and panel data. 1, Can we run nested logit with the individual fixed effect? this is useful when one has ...
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Small N Small T Panel Data - options?

I have Panel data for 21 counties over 11 years. Most literature seems based on either small T and large N or small N and large T. I tried applying a fixed effects model (one-way, individual) to the ...
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Setting up a 3-dimensional panel with interaction term

I am a new member and this is the first time I am posting a question here. I have yet to familiarise myself with writing equation here. Apologies for the poor representation of my equation. I have a ...
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Arellano Bond estimator

I am trying to estimate an equation in levels with the lagged dependent variable on the right hand side. I am looking at using arellano bond estimator for this. My issue is that I am looking for ...
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Panel data analysis with low sample and high seasonality

I have a panel data sample with 40 companies from 5 different countries. My client collected data from the companies for a period of approx. 17 months. At month 3 or 4 from the start of the data ...
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Panel data regression - normality and testing issues

Im doing an event study using panel data regression with abnormal returns for 15 events and 38 stocks as the dependent variable, and different multiples (P/E, B/M etc.) as the independent variable. I ...
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Dimension Reduction on Data with both Spatial and Non-Spatial Variables to Train a Logistic Regressor for Cross Sectional Time Series Data

I need some help on how to process and analyse a study of mine. I'm running a study on mice to look at the effect of diet on cells over a series of time. My mice are divided into two groups, one group ...
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How to adjust for spatial autocorrelation in panel regression in R

I am running a panel regression with two-way fixed effects, the outcome variable being the number of conflicts in each district each month. My calculation of Moran's I seems to indicate that the ...
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What machine learning and deep learning models are used for longitudinal studies (panel data)?

As the title suggets, 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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How to recover fixed effects in two-way panel regression after within transformation

Individual effects only When I want to estimate a fixed effects model without time effects of the form $y_{it} = \mu_i + x_{it} \beta + u_{it}$, I can estimate the coefficients $\beta$ and $\mu_i$ ...
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r plm time and individual fixed effects - “twoways” vs. factor(index) time

I have an unbalanced panel with weekly data and want to do a panel regression with both, individual and time fixed effects. Following the code in https://www.princeton.edu/~otorres/Panel101R.pdf my ...
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Are fitted.values available in pglm?

I am using the pglm function in R to fit a Poisson fixed-effects model. According to the documentation, the pglm object should have fitted.values. However, fitted.values(model-name) returns "NULL". ...
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Hausman test showing different results between R and Stata

I ran a Hausman test to compare random and fixed effects regression for a panel dataset in both R and Stata and found that the two are showing different results. The troubling thing is that the Stata ...
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Missing values while using fixed effects model

I have household-level panel data from two time periods. I found out that a good portion of my households have missing values in some variables that I need to control for, in the second time period. ...
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Difference-in-differences with individual-level panel data

Main Idea I want to estimate the effect of a treatment that affected a group of individuals that are scattered over a larger geographic area in a short matter of time (a week) via DID. I have reason ...
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Is the panel (PLM in R) approach appropriate when observations within panels vary in location and number between time steps?

Setup: We have 10 connected but distinct wetlands within a study area. The wetlands are not totally independent, there is some exchange of water and organisms between them. Perhaps comparable to ...
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Treatment evaluation: Measuring statistically / clinically significant change in level over time

I am conducting a treatment evaluation. I am using an interrupted time series design (generalised linear mixed model; 42 monthly measurements per patient [18 pre-treatment, 24 post-treatment). I have ...
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Longitudinal CFA/SEM with autocorrelated/autoregressed indicators (in R, better with lavaan)

The problem is, I am trying to fit a multilevel factor model to highly autocorrelated (in fact, autoregressive) indicators. More specifically, I have multiple measurements (60-70) per person (5-10 ...
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Standard errors in fixed effects regression using R

For my master thesis, I want to examine the relationship between consumer credit loans and house prices in Norway after a policy change in mortgages from 2017. To do this I've set up a pooled (...
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Can you have multiple observations for specific case-time in two way fixed panel regression?

I am studying impact of 'temperate zone' and 'time' (month) on X. There are total of 12 'temperate zones'. However the data is collected at much smaller scale (say city). So for example, temperate ...
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Prediction Interval for linear model with fixed effects

I've got a panel data and I'm using a linear model with fixed effects for individuals and time, along with other covariates to explain the variation in a dependent variable. I'm clustering my standard ...
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Correct Specification for Censored Data

I have some construction data, which shows the starting year of unfinished and finished projects but don’t have any information on the completion time of finished projects. If I had data on the ...
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Fixed effects - correcting for autocorrelation and heteroskedasticity, panel data analysis in R

I have a datset of 25 counties over 11 years, with response variable unemployment ( in %), and 6 explanatory variables (proportion with high school, some economic indicators, etc). After some tests ...
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Minimum Sample Size with the Panel Data; Firms and Obeservations

I'm working on the panel analysis with the data of 20 firms in two nations (10 for each nation). It is an annual data which covers the time period from 1980 to 2015. As it is my first time to deal ...
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How many missings are too many to impute data with the AMELIA II package?

I have a very large longitudinal dataset. I only want to impute 3 variables individually using the AMELIA package in R. The problem is that some individuals have a lot of missing values, so I want to ...
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How to prove FD and FE will give the same estimates when T = 2

We simply use the time-demeaning of Ti observations in time for each cross-section i and FE is equivalent to an FE on balanced panel.How to prove it?
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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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How to deal with circular causality

Often in time series and panels, the "dependent" and "causal" variable don't share purely that relationship. There is a fair bit of reverse causality as well. ,e.g. x causes y, but then either y ...
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Not testing for stationarity in a panel data set

Currently, I am analyzing a panel data set (different individuals over time) using panel data models with the lagged dependent variable as an explanatory variable. In this case the stationarity ...
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Dummy variable reference category

As part of my thesis, I am exploring the effect of firm owner type on research and development, which is a ratio. I have a dummy variable of company owner type with 10 categories e.g. Bank, ...
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panel IRF and FEVD from panel vector autoregression in r

The package panelvar in r can estimate panel vector autoregression models. It can also produce IRFs and FEVDs the aggregate endogenous variables. How can I get IRF and FEVDs for panel units/...
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How to find a “difference” type of estimator for B1?

Suppose the panel data model is given by: FRit = bo + b1*BTit + b2*Zi + eit; where Zi is not observed, i = 1; :::; n and t = 1; 2; 3: In this model we have three waves or we have three cross-...
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how to prove B1 as a consistent estimator in panel data

$Yi=a+ B_1*X_i+ B_2*Z_i+\epsilon_i$, and suppose that $Zi$ is unobservable and not correlated with $X_i$. Is the OLS estimator of $B_1$ consistent by regressing $Y_i$ on a constant a and $X_i$? I ...
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Why does pglm give different results thans log-plm?

I'm looking to regress a fixed-effects model on count data. My initial approach was to take the log of regressor on R's plm package. Then I found out about the pglm package, which enables general ...
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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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Modelling dynamic panel data

I have a question about a dynamic panel data model. Consider the panel data model: $y_{it} = \alpha_i + x'_{it}\beta + \delta y_{i,t-1} + \epsilon_{it}$. This cannot be estimated because $\alpha_i$ is ...
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Difference-in-differences model with time-fixed effects only

Assume that we have a panel data set with individuals' income (Y) over multiple years and a certain event (POST) in one year that is hypothesized to affect Y for a subgroup of these individuals (TREAT)...
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Interpreting log coefficients in differences model (time series/panel)

I am struggling with the interpretation of coefficients in $\delta(\log y)=\alpha+\beta\delta(\log x)$ Usually in a $y=\alpha+\beta x$ model, $\beta$ represents change in $y$ corresponding to unit ...
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1answer
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How to test whether a statistically significant coefficient is driven by observations in certain periods in panel data?

I estimated a fixed effects model as follows using a unbalanced panel with 10 years of observations. $y_{it}=\beta x_{it}+\delta_i+\gamma_t+\epsilon_{it}$ The coefficient of interest is $\beta$. I ...
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1answer
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Splitting panel data into subgroups

I have a (an unbalanced) panel dataset of individuals over different periods of time (one time period = one month). I'm attempting to analyse the effect on the level of activity of the individuals of ...
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Do small odds ratios observed at multiple time points equate to a large odds ratio when averaged across time points?

I am testing the relative odds of two groups, placebo vs active treatment, guessing that they received active treatment. These guesses were made at four time points, 4, 8, 12, and 24 weeks into a ...
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Reorganized Panel data in R

I am currently working on a fixed effect model, and have a dataset (csv file) in the form of the following (represents two city over three years): year feature1 feature2 2000 10 14 2001 12 13 2002 13 ...