Tagged Questions

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

learn more… | top users | synonyms (2)

2
votes
0answers
12 views

Aggregating forcast to higher spatial level

I am working on a project doing out of sample estimates of wheat yields at the village level in STATA. I am using a short panel 3 years and a sample of ~3000 villages. We are estimating a RE model and ...
0
votes
0answers
7 views

Marginal effect calculation after logistic regression with panel dataset using R

I would like to perform a logit regression with a panel dataset, I know that the pglm package does the job, however, does anyone know if there is a standard package in R that allows me to calculate ...
3
votes
0answers
26 views

Recommendation for books/notes for linear mixed effect models for longitudinal data?

I'm a beginner in data analysis who needs to learn (say in a period of 2 to 3 weeks or so) the key ideas and techniques in the linear mixed effect models for longitudinal data. I'll apply them in ...
0
votes
0answers
12 views

Missing Values in Dependent Variable and the Question on Tobit model (Panel Data)

I would appreciate some help and guidance on this issue. I have a panel data that looks like this. What I want to do is use the FDIflow variable as a dependent ...
1
vote
0answers
20 views

Alternative specific conditional logitstic regression with clustering on in individual in panel data: scientifically and computationally reasonable?

My scientific interest is to calculate the price elasticity for an overall set of products (books) in a panel dataset of observations over a 3 year period and I was wondering whether asclogit ...
1
vote
1answer
70 views

Hausman test after xtregar negative chi2

I'm performing a Hausman test on panel data to determine whether to choose Random Effects or Fixed Effects for my analysis with AR(1). After performing the test I get a negative $\chi^2$ statistic ...
1
vote
0answers
9 views

Fixed effects in panel data, correlations/coefficients don't add up

I am doing a regression on panel data for firms. The dependent variable is the Marginal revenue product of labour (RPL), i.e. labour productivity, and the independent variable is the average wage of ...
0
votes
0answers
9 views

Multilevel model when treatment occurs at intersection of non-nested groups?

I'm formulating a multilevel model in which my binary treatment happens in certain country-years. In other words, the treatment is at the intersection of certain countries (group 1) and certain years ...
1
vote
0answers
23 views

Likelihood function for MANOVA

I'm trying to get a handle on MANOVA and Repeated Measures ANOVA. My confusion is around what the likelihood function looks like. Here's how I would formulate the likelihood function Notation: The ...
1
vote
1answer
23 views

How to estimate model where instrument is correlated with dependent variable

I have the following problem: I would like to estimate the effect of price variation caused by uncertainty on an outcome variable. P is my price, X is the variable measuring uncertainty and Y is the ...
0
votes
1answer
19 views

Time-variant & Time invariant & Time-related

In Longitudinal study, What are "Time-variant covariates", "Time invariant covariates" and "Time-related covariates"? and what is differences between them?
3
votes
0answers
18 views

Goodness of fit for a spatial panel with fixed effects and both spatial lag and spatial error

On a dataset, I performed spatial panel regressions with fixed effects, and with both a spatial lag and a spatial error (both are significant), using package splm in R (Millo and Piras 2012 Journal of ...
5
votes
5answers
136 views

What's the difference between time-series econometrics and panel data econometrics?

This question may be very naive, but the way I'm taught econometrics I'm very confused if there's a difference between time-series and panel data method. Regarding time series, I've covered topics ...
1
vote
1answer
35 views

Too many significant dummy variables in fixed-effect panel model

I am doing panel analysis of state drug policies. My data set includes 50 states and ten time points. I am using one-way state fixed-effect models, controlling for heteroskedasticity and ...
0
votes
0answers
10 views

Including non-linearity to the first difference

I have an issue running the First diffeerence estimation. After running it with all the controls I got a really low RESET test, and thus would like to add a non linear term to my model. In order to do ...
0
votes
0answers
38 views

Request for reference for longitudinal data analysis which is mathematically well-written

I'm a person with graduate level mathematics and some undergraduate statistics background, who'll have to study some basic longitudinal data analysis. I've studied the basics of correlation and ...
1
vote
0answers
44 views

In a longitudinal analysis, is it valid to adjust for a covariate as change-score and also include the baseline covariate value?

We have a situation where we want to test the association between X and Y, but the change in X from baseline is more interpretable. There are several possibilities I see for setting up the model. But ...
3
votes
1answer
42 views

Nonstationary panel data, spurious regression

I would like a more detailed explanation of this quote: "Unlike the single time series spurious regression literature, the panel data spurious regression estimates give a consistent estimate of ...
1
vote
0answers
12 views

How to model dynamic relationships in panel data when units exhibit heterogeneous variance

So I'm taking a look at a dataset of about 200 individuals, each with a number of variables measured 50 times longitudinally. A lot of these variables are subjective, and scored on a scale of 0-100, ...
2
votes
0answers
22 views

Discrete Choice Models

for mulitnomial (or mixed) logit models, when the choice set is too large, either strategic sampling or random sampling of the choice set can be used. My question would be: Is that also true in ...
0
votes
0answers
9 views

pggls function in R - weird results

I need to estimate a panel model. I have run the "normal" fixed effects model using plm in R and also wfe. I also wanted to try pggls considering its tolerance of heteroskedasticity and ...
1
vote
0answers
28 views

Analysis of a longitudinal study where interventions are received at different time points

I have a data set of university students. The university has 8 different assisting programs, mostly like scholarships, for needy students to help them concentrate on their studies. Since it costs a ...
0
votes
0answers
32 views

Organizing data using time series multivariate regression?

I am trying to understand how I can organize the following data since none of what I learned in my undergrad econometrics course works. I am running out of ideas. I am trying to measure how the ...
1
vote
1answer
48 views

Modelling Fixed effects in panel data regression models

I was given the following equation: $$\sigma_{it} = \beta_0 + \beta_1 x_i + \beta_2y_i + \beta_3vs_{it} + \beta_4vm_{it} + \sum_{i=1} \gamma_i \alpha_i + \sum_{t=1} \omega_t \phi_t + \epsilon_{it}$$ ...
2
votes
1answer
36 views

Longitudinal data analysis with a single group

I need you assistance with finding the right model to analyze longitudinal data with a single group. My data comes from the ophthalmic field, i.e. eyes. I have n subjects. For each subject, one eye ...
0
votes
0answers
22 views

What to use when chi-square independence assumption is violated

I'm trying to describe the characteristics of the sexual partners of each participant. There are multiple partners per participant. All of the variables in my analysis are categorical, so originally I ...
0
votes
0answers
13 views

pooled OLS VS multiple linear regression

somebody help me to understand the difference between pooled OLS vs multiple linear regression. i learned panel data analysis consists of three: 1. pooled OLS 2.fixed 3. random my understanding ...
1
vote
0answers
24 views

Longitudinal data: baseline effect versus random intercept 2

My question follows this post: Longitudinal data: baseline effect versus random intercept The topic is very interesting and I have two further questions, one very practical and another about ...
1
vote
0answers
32 views

How can I model this problem?

Genetic algorithms are a kind of evolutive approach to problem solving where solutions are randomly generated and crossed with each other as to produce other solutions. With each generation or ...
0
votes
1answer
49 views

Measuring longitudinal data where individuals have missing observations

We have a longitudinal panel of X users with their online spending patterns and are trying to measure certain metrics within the panel. We have time series information about the users such as their ...
0
votes
1answer
44 views

Does it make sense to add random coefficients to a fixed effects (fixed-intercepts) model?

If you have panel data, and you fit a model like $$ y_{it} = \alpha_i + X_{it}'\beta + \epsilon_{it} $$ then you have $E[\hat\beta] = \beta$ if you can make an argument that $E[\epsilon]=0$. This is ...
5
votes
2answers
184 views

Longitudinal data: baseline effect versus random intercept

The variable $Y$ is measured at time points $t_1$, $\ldots$, $t_9$ for each of five objects. Also available for each object is the value of $Y$ at time $t_0 = 0$ (baseline). Thus, the sample size is ...
0
votes
0answers
16 views

Should I standardize response variables in a panel regression?

Suppose I have the following Data $Y_{it}$ = price of one foreign currency in one US dollar, at time t, where i= different countries[Australia, Japan] $X_{it}$=employment rate and other explanatory ...
0
votes
0answers
16 views

Longitudinal design: how to take into account baseline measures

I have a (small) data set of 15 subjects randomly assigned to one of two groups. All subjects were measured at 7 time points. Ideally, I would like to answer if the groups differ at certain time ...
0
votes
0answers
21 views

Linear model with longitudinal data, predicting difference

I have a set of data for 2 visits in patients and I would like to see whether there is a effect of a difference of one variable on another. So, lets say, my variables are A, B, age + gender. I want ...
2
votes
1answer
83 views

Is subtracting individual means in pre-processing an appropriate alternative to dummy variables for fixed effects panel data estimation?

Is subtracting individuals means during pre-processing of panel data exactly equivalent to including dummy variables for fixed effects estimation? If not, what are the differences, and is there some ...
6
votes
2answers
133 views

Propensity Score Matching with time-varying treatment

The basic propensity score matching procedure works with cross-section data (ie collected at a certain point in time). The popular psmatch2 command uses a dummy variable indicating that an ...
3
votes
1answer
87 views

2-stage panel model - am I doing it right?

I ran a 2-stage fixed-effects panel model in R. The goal is to find the effect of strategic alliance participation on firm performance. Alliance participation is not random - firms self-select (and ...
1
vote
1answer
51 views

R plm: understand pmodel.response

I need help in understanding the pmodel.response function from the R package plm. So far I have interpreted this as a way to get ...
0
votes
0answers
36 views

Panel data models when some regressors are non-stationary - I(1)

My model is $$ Y_{it}=X_{it}'\beta+\varepsilon_{it} $$ where $Y_{it}$ is a vector of weekly observations of a dependent variable and $X_{it}$ is a vector of explanatory variables (also weekly) with ...
0
votes
0answers
21 views

Which panel to pick when there is overdispersion in longitudinal data?

This question relates to a previous question I asked a while ago that unfortunately remained unanswered. I hope someone can give me an answer or a suggestion / comment that could help me out. I am ...
2
votes
1answer
16 views

conditional independence in repeated measures design

How the responses are independent when conditioned on random effect in repeated measure analysis (linear mixed model)?
0
votes
0answers
23 views

when to use panel time-series regression vs seeming unrelated regression

I am a bit confused on whether or not I have to use a fixed-effect panel time-series method or SUR (seemingly unrelated regression). To get a background of what I am trying to do, I have 10 panels of ...
0
votes
0answers
45 views

Panel data forecasting from Arellano-Bond GMM estimation

I want to come up with predictions of final energy demand per capita (fe) for a panel of countries. Explanatory variables are GDP per capita (gdp) and population density (pop) -- all variables are ...
4
votes
1answer
76 views

Difference-in-differences with no pre-treatment?

The typical difference-in-differences estimator (as fixed effects) fits a model of the form $$ y_{it} = \alpha_i + \delta T_{it} + X_{it}'\beta + \epsilon_{it} $$ where $T$ is some treatment that ...
0
votes
0answers
26 views

wrong reported Total Sum of Squares in time fixed effects with plm (twoways)

I was sent here from Stackoverflow because this is more a statistics question. I hope I am in the right place now! The summary command of a plm regression with the (factor="twoways") argument reports ...
1
vote
1answer
43 views

Modelling Issues in panel regression

I came across a paper that uses a panel data of US states (from 2000-2010) with the following model: $y_{it}=b_{1}x_{it} +b_{2}x_{it}*D_{it}+other vars + \alpha_{t} + \gamma_{i}$ where, $x$ and $y$ ...
0
votes
1answer
46 views

Removing Time-Series Variance from Panel Data

We are working with panel data. But we want to study only the cross-section part of the panel data. So can anybody please tell me how to do any kind of data transformation, so that I can remove the ...
2
votes
0answers
43 views

Is two years enough for panel data analysis?

I have around 800 companies for only two years period. However, around 200 of them have only one year observation. Is it still possible to conduct panel data analysis with such data Thank you
0
votes
0answers
31 views

Regression inconsistent results?

I have a question regarding the findings in an article which I don't fully grasp. The authors examined the relationships between variables measured at different time points. They found that a ...