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.

learn more… | top users | synonyms

1
vote
0answers
12 views

Multilevel model with repeated data and time fixed effects?

I am using pooled cross sectional survey data to estimate prefernce for redistribution. I have 33 countries for 6 survey rounds covering the periods 2000-2013. I would like to estimate the effects ...
0
votes
0answers
8 views

Weighting supercedes fixed effects?

I came across a surprising "result" when analyzing some data and I'm wondering if it is actually a known result, and why it works. I have a dataset that has been partitioned into ...
2
votes
1answer
36 views

Panel data estimation for country-fixed, time-varying share of y

I want to estimate the following equation using a panel data set with countries $i$ and years $t$, preferably in R: $$ y_{it} = \beta_1 \cdot x_{1,it} + \beta_2 ...
0
votes
0answers
9 views

Panel model Estimation - 5 and 10 years Break [migrated]

I am trying to estimate the relationship between inequality and growth in a panel data of 22 countries for the period from 1985 to 2010, using fixed-effect and random effect. I want to use 5-year and ...
1
vote
0answers
27 views

Intuition behind fixed effects

Im trying to explain the intuition behind fixed effects to a group of people with no background in (formal) regression analysis. Explaining the intuition behind Diff-in-Diff estimation of the impact ...
0
votes
0answers
11 views

Feasible Multinomial Logit with large number of fixed effects

Is there a way to run something similar to a multinomial logit model with a large number of fixed effects that converges in a reasonable amount of time (I am using Stata)?
1
vote
1answer
51 views

Hausman test for panel data

I am performing a Hausman test to decide whether to use fixed effects or random effects model. The results I get are as follows: ...
0
votes
0answers
21 views

Bayesian fixed effects model and invariant variables

Within a fixed effects approach, the effects of invariant variables cannot be estimated. Their effects are captured by the fixed effects. However, when I estimate following Bayesian fixed effects ...
1
vote
1answer
84 views

Fixed effects or Random effects model?

I am trying to understand the difference between fixed and random effects modelling. The panel data I have is in the form of basic longitudinal panel time series. I know that I can use the Hauseman ...
5
votes
1answer
56 views

Real motivation for using mixed effect models, and when to use them and when not to

My question might sound naïve, but despite my internet search, I wasn't able to find a satisfactory answer. I've been introduced to linear regression, linear fixed effect and linear mixed effect ...
0
votes
0answers
13 views

Analysis of clustered data

I have records of $multiple$ visits from many different patients in several different clinics (i.e. visits nested within patients nested within clinic) and plan to perform an analysis that takes into ...
0
votes
0answers
6 views

FE Model: independence of residual and firm specific component

I'm estimating a fixed effects model and want to consider Petersen's (2009) suggestion: "The components of X (μ and ν) and ε (γ and η) have zero mean, finite variance, and are independent of each ...
1
vote
1answer
51 views

Fixed Effects and Dynamic Panel Data

I have a theoretical model that suggests I should estimate the following regression using longitudinal data: $s_{it} = \eta_{i} + \beta_0 x_{it} + \beta_1 x_{it}^2 + \epsilon_{it}$ where $x_{it} ...
3
votes
1answer
58 views

Can I do panel regression if all my covariates are time-invariant?

We have a data set where our outcome of interest varies over 10 years, but the explanatory variable of interest and all of the potential confounders are time-invariant. I am quite certain that a panel ...
1
vote
0answers
25 views

Confidence interval for psychometric binomial GLM model on more than one subject in R

I'm trying to estimate the confidence interval of a psychometric curve (binomial probit GLM), for a population (now only two subjects). Suppose I've subject "a" and subject "b", which performs ...
2
votes
1answer
76 views

Year-fixed effects in a pre-post OLS regression analysis

Let's say I have panel data for the period 2000-2009 and I run a pre-post OLS regression analysis where the pre-period is 2000-2004 and the post-period 2005-2009. Does it make sense to use year*period ...
0
votes
0answers
128 views

How to apply heteroskedasticity and autocorrelation tests to panel data in eviews 8?

I am trying to test for heteroskedasticity and/or autocorrelation in my fixed effects panel regression in Eviews 8. There do not appear to be the necessary tests available. The Breusch-Pagan LM test ...
2
votes
1answer
49 views

Interpret effect of adding random effects to ordinal regression (R - ordinal package - clmm)

I know there are already lots of questions around this topic (especially this one and this one) but I haven't really seen anything that directly helps me (It will be obvious I'm not a great ...
3
votes
1answer
33 views

Bins and Year Fixed Effects

I am trying to understand the difference between two regression models. Before more complex models are run (ie. quantile) I split an key independent variable into bins to see if the relationship is ...
3
votes
0answers
14 views

Fixed parameter estimates of parent factors in a nested design

Summary: What is happening with parameter estimates of factors that are the 'parents' of nested factors? Data: My analysis involves testing the effect of different parameter settings for automatic ...
2
votes
2answers
68 views

Endogeneity justification

I'm using a fixed-effects model to analyze car prices based on product's characteristics during a five year period. Steel price is used among others explanatory variables. How to justify possible ...
0
votes
0answers
11 views

Help with fixed effects regression: adding variables turns regressors insignificant [duplicate]

after composing my model for estimating the relationship between the old-age dependency ratio (share of elderly, i.e. 65+ who are dependent on the working population) and GDP per capita, I stumbled ...
0
votes
0answers
32 views

Two basic questions on hierarchical/multilevel modeling re: specific term interpretation and when to use in general

Suppose a hierarchical model with varying intercepts and varying slopes, with a single individual-level predictor $x$ and a single cluster-level predictor $z$. After inserting the level 2 equations ...
0
votes
0answers
36 views

Using R : linear model (lm) - Fixed Effect Model - Vary intercept by different factor than the coefficient

I am having a problem setting up a panel data model (Fixed Effects) At the moment I am running the following code: ...
0
votes
1answer
62 views

Is this logit model a multilevel model, and what is the correct way to model it?

I am analyzing a sample of about 6000 actions carried out by about 500 multinational companies in about 80 countries during a 6 year period. Actions are carried out randomly, and are not longitudinal ...
0
votes
1answer
9 views

fixed-effect nested factors in R with only SOME combinations present

I have a large data wth numerical response and two categorical factors: date and site. There are about 350 dates and 25 sites, but not all sites have observations on every single date (most have only ...
1
vote
0answers
95 views

Panel data with N < T heteroscedasticity and autocorrelation. Should I include country dummies?

I have panel data of $N=18$ countries with $T=72$ months. Heteroskedasticity and autocorrelation are present in the dataset. I was working in Stata with xtreg fixed ...
3
votes
1answer
62 views

Hausman test FE vs. RE in case that FE is not consistent

I have a twin panel data and want to estimate simple wage equation (interest in return to education). I use fixed effects(first differencing) to account for family background.(Based on: Ashenfelter ...
0
votes
0answers
19 views

Interpreting fixed effect result

I've estimated my fixed effect model and a selection of the results are as follows; R-sq: within = 0.6827 between = 0.3321 overall = 0.4672 F test that all u_i=0: F(50, 499) = ...
3
votes
1answer
63 views

Using year fixed effects on data with yearly observations

I have a panel data set with yearly observations of various firms over a period of 5 years. I am running a fixed effects model in Stata using xtreg. Is it ...
2
votes
2answers
188 views

Time-invariant variables not being removed in Fixed Effects model. And feasibility of addional time dummies in Fixed Effect/Random modelling

I am working with severely unbalanced Panel Data of a nations Fisheries where I have individual data from all deliveries made by every single vessel. Thus far I have reshaped the data so that every ...
7
votes
1answer
451 views

How to use the Hausman test for gender discrimination?

I am trying to estimate the gender wage gap for male and female office workers in a large Swedish company to test whether there is gender discrimination. The Hausman test rejects the null that the ...
1
vote
2answers
74 views

Panel data methods

My dataset is following: firms=1000, time period=10 years, countries=20, industries=15. I declare in STATA: xtset firmid year I want to control for the ...
5
votes
1answer
178 views

Dealing with hierarchical (panel, multi-level) data and fixed effects in LASSO?

The question pretty much explains itself. When running a Lasso regression on a lot of indexed (say by time and location) explanatory variables, is it best practice to transform all data using a ...
0
votes
0answers
21 views

To demean or to use dummies in maximum likelihood

I have a dynamic panel data with T=20 and N=1500 and I use a maximum likelihood estimation (more precisely its a VAR). Using a dummy variable approach to account for fixed effects introuduces an ...
0
votes
0answers
51 views

Fixed Effects at Different Entity and Time Levels

This is a project I'm working on. I have MONTHLY values of X for employees of firms and I want to know how these affect YEARLY values of Y for those firms. The Y values are the same for all ...
0
votes
1answer
78 views

How to perform regression with a sensitivity analysis in R

Without using non-base packages like plm, how can I perform a fixed effects regression in R with a sensitivity analysis for one or several other variables? Some ...
1
vote
0answers
63 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 ...
0
votes
0answers
110 views

What is the difference between FE-PCSE and xtreg, fe in Stata? [closed]

Here is a very simple question: On country-level data, I am running two different fixed effect model, using Stata command, but I don't know why not only the estimation of standard errors, but also ...
1
vote
0answers
82 views

group fixed-effects, not individual-fixed effects using plm in R

I am analyzing some data to evaluate the impact (causal effect) of a program that is delivered at group level (a village). The outcome of interest is measured at the individual level (individuals ...
1
vote
1answer
307 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
42 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 ...
3
votes
0answers
39 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 ...
1
vote
1answer
99 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
23 views

within-MZ twin model using sem in Stata

I'm working with some twin data and would like to estimate something exactly akin to xtreg using sem in Stata. The structure of the data is pretty generic: there's a family id, there's a within family ...
0
votes
0answers
26 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
1answer
62 views

Modelling Fixed effects in panel data regression models

I was given the following equation: $$\sigma_{it} = \beta_0 + \beta_1 x_i + \beta_2y_i + \beta_3vs_{it} + \beta_4vm_{it} + \sum_{i=1} \gamma_i \alpha_i + \sum_{t=1} \omega_t \phi_t + \epsilon_{it}$$ ...
1
vote
0answers
99 views

cluster-robust standard errors are smaller than unclustered ones in fgls with cluster fixed effects

I'm currently working on some experimental data. The experimental design consists of two treatments. In each treatment, 20 subjects are randomly matched in pairs and participate to a simple game. The ...
2
votes
1answer
99 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 ...
3
votes
1answer
145 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 ...