Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

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.

0
votes
1answer
22 views

R: GMM Estimators in a dynamic panel

I put up a fixed effects regression using panel data with a time lag of the dependant variable, so somthing like this: ...
0
votes
0answers
20 views

interpreting the coefficient of an interactive term with fixed effects

I have the following longitudinal panel investment regression: investment depends on macroeconomic uncertainty $U_t$; firm-fixed effects $\alpha_i$; the interaction between uncertainty $U_t$ and ...
0
votes
0answers
9 views

Binary dependent variables and panel data

I'm examining how the reduction in the number of scientists working in a firm could affect the relationship between firms and universities, labs and research organizations. My dependent variables are ...
0
votes
0answers
18 views

Time dummies in Linear Panel Data Models and Unobserved Effects Models

Wooldridge (2002, p. 129) says that with (independently) pooled cross sections over time (where different random samples are collected at different points in time - no individuals are observed more ...
0
votes
0answers
22 views

Interpretation of a residuals vs fitted values plot

My objective is to predict the taxi demand depending on location and time. I transformed the data to be more or less normally distributed and centered & scaled it. Then, I ran a linear regression ...
0
votes
1answer
24 views

How to apply fixed effects in R?

In this example they just want to know if the announcement decreases the trading assets ratio. What are fixed effect in application here? Meaning of quarter and companies fixed effect? How they keep ...
1
vote
0answers
30 views

Is fixed effects (within estimator) estimated using OLS?

In a paper I submitted to a journal, I estimated a fixed effects panel model with regional fixed effects. The reviewer of my paper in his comments said my estimation was bad because I "simply used OLS ...
0
votes
1answer
38 views

Transformation of data in mixed models (lme4)

I am trying to fit the following model where I'm measuring fungal growth (length) in Petri dishes that were kept at 0C, room temperature, and 50C (Treatment). ...
2
votes
0answers
30 views

Model that takes grouping factor into account is a significantly better fit, but no significant differences between groups…unusual?

I'm dealing with a dataset that comprises ~30 groups of observations. In each group, we measured independent and dependent variables a certain number of times. If I plot the relationship between ...
0
votes
1answer
20 views

Need help with fixed and random effect negative binomial models in R [closed]

This is my first time asking a question here. I am trying to develop a relationship between number of accidents on a road segment and some geometric and traffic variables. I have total 7 years of data ...
1
vote
1answer
33 views

Constant and fixed effects in all sample versus subsamples

I have a panel regression for countries. There are two groups of countries, rich ($k=1$) and poor ($k=0$). The equation is: $$ Y_{ikt} = c_k + \lambda_{kt} + X_{it}\beta{k} + e_{ikt} $$ $\lambda_{kt}...
0
votes
0answers
22 views

Equation for Cross-Sectional Pooled Data or Panel Data with Multiple Group Dummies

I am trying to write the correct specification for the following models in a setting where the administrative structure consists of provinces, districts, and neighborhoods, in that order. A cross-...
0
votes
0answers
17 views

Bootstrap and Prediction Confidence Interval

I have a question about how to use bootstrap to generate the confidence intervals for my model predictions. I do not care about the confidence intervals of the single parameters of the model (indeed, ...
1
vote
0answers
29 views

When and why should we use Tobit Regression model?

I am trying to find out determinants of corporate cash holdings for a panel dataset of 1696 firms over a period of 21 years. The dependent variable is the ratio of 'Cash and Cash Equivalents' to '...
0
votes
1answer
40 views

Interpreting Regression Coefficient

I am using panel data and I have a very simple regression equation of the following form: $y_{st} = \alpha_s + \beta_t + \gamma F_{st} + \epsilon$ Where, $y_{st}$ is my dependent variable (...
1
vote
1answer
28 views

Can I report fixed and random effects outcomes in one paper?

I am a health economist working with panel data for a paper I am working on, I use Hausman tests to determine if I should use fixed or random effects estimators in my analysis, for some outcomes ...
2
votes
0answers
54 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 ...
0
votes
1answer
14 views

ANOVA: Non-significant main effect with significant post-hoc test?

I need some help in interpreting a situation in a 4-way ANOVA where a given factor does not show up as significant in the omnibus model, but the post-hoc comparison between categories of that variable ...
0
votes
1answer
34 views

Predicting Dependent Variable with Fixed Effects Model

I am currently working testing the effects of aid on inequality. I am using panel data, and the model looks something like the following: ...
0
votes
0answers
30 views

How to formulate the regression model in R for trials in agriculture over multiple years?

I'm working in a research facility for agriculture where we do a lot of trials that continue over several years. For the example below i tried to find out how to formulate the regression model so ...
0
votes
2answers
43 views

How can I interpret intercept when my dependent variable is in log form?

My model consists of both log independent and dependent variables, and percentage share, as well as number of people and etc. My dependent variable is log(GPD per capita in USD), my statistic package ...
1
vote
0answers
13 views

Subtracting fixed effect term for visualization

Suppose that I run a fixed effect model $$y_{ij}=\beta_0+\beta_1x_{ij}+d_i+\epsilon_{ij}$$ where $d_i$ is the fixed effect model for group $i$. Now that I want to show the data, is it appropriate ...
0
votes
1answer
29 views

Panel regression with multiple fixed effects and heterogeneity

For a research project I am supposed to estimate a panel regression model on a dataset with user data over observation time (the sample is assumed to represent general population). The supervisor is ...
2
votes
0answers
31 views

Standard error implications when combining IPTW and difference-in-differences

My question is about combining Inverse Probability of Treatment Weighting (IPTW) with a difference-in-difference regression with two periods (pre and post treatment). Basically, I first computed the ...
1
vote
1answer
57 views

Understanding whether to use two-way effects [duplicate]

Using plmtest, I find that individual effects are significant (p: 7.327e-05); time effects are not significant (p: 0.1263); and two-way effects are significant (p: 0.0001197). Based on these results,...
0
votes
0answers
6 views

Mixed effect model for data with paired/unpaired data

I have tested individuals on the number of parasites (ranging from 1 till 3) they have. For each parasite I described the severity of infection (ranging from 0.5 till 3). As an example, here a part of ...
0
votes
0answers
24 views

Degrees of freedom using nlme

I'm having a very similar issue to this post: Degree of freedom with mixed model , using nlme package? But unfortunately the post does not contain a real answer. I am not understanding how the nlme ...
1
vote
0answers
19 views

R | Large-Sample Fixed-Effects Interaction using plm

How can I model Interactions with fixed effects for a large sample using plm? I have a panel data set with > 100,000 observations and I am trying to model a dummy-interaction with one of two fixed ...
0
votes
0answers
10 views

lme4 How to interpret a random slope effec while there is no fixed effect?

I have a question regarding the interpretation of multi-level models. This is my first model: m1 = lmer(Y ~ x1 + x2 +(1| class), REML = FALSE, data=dataset) In ...
1
vote
0answers
22 views

Proving First Difference is more efficient than OLS

I am trying to prove that the First Difference method is asymptotically more efficient than OLS when the error term follows a random walk. Assume the following model $$\begin{align}y_i&= \mathbf{...
0
votes
1answer
237 views

Clustered standard errors are completely different in R than in STATA

I'm trying to reproduce a study in R. Here are its core elements: study wants to measure the effect of a transit strike on highway delay independent variables: strike: binary dateresidual: ...
0
votes
0answers
8 views

Should geographic location always be included as a random model effect?

Under what sort of experimental conditions and/or objectives might someone be justified in modeling geographical location as a fixed effect (assuming that most times location is included as a random ...
0
votes
0answers
25 views

moderators, control variables and time-fixed effects for panel data using plm package

I have panel data that consists of 33 companies, 70 CEOs and 30 years. I want to measure the effects CEO narcissism (=x) has on the internationalization (= y) of companies. the fixed effects model is ...
0
votes
0answers
33 views

Regression with varying weights within fixed effect units

I'm running a regression where within the fixed effect groups, the weights are not constant. However, since there are many fixed effects, I would like to use an estimation method as implemented for ...
0
votes
0answers
15 views

The Within estimation with multiple Fixed Effects

I'm trying to understand the logic of the within-interpretation with multiple fixed effects. I already found a helpful post (Fixed Effects and Within Variation) for the case with individual fixed ...
1
vote
1answer
191 views

OLS, Fixed effects or Random effects Model?

I am a little bit confused about type of model to apply because my type of data. I am interesting in get regression parameters for time (dependent variable) with independent variables= sex + age+ ...
0
votes
0answers
14 views

standard error adjustment in pooled panel regression with time fixed effect

I am fitting a pooled-panel cross-sectional regression with a time fixed-effect: \begin{align} Y_{i,t}=a_t+X_{i,t}b+e_{i,t}. \end{align} But I have $E(e_{i,t}e_{j,t})\ne0$ for $i\ne j$, $E(e_{i,t}e_{i,...
0
votes
0answers
19 views

Analysing change over time

I have a panel data set with 5 ways. I'm working with the dependent variable X and the independent variables X1, X2 and X3. I'm interested in only the change of my variables on an individual level: E....
0
votes
0answers
21 views

Cook's Distance for FE Panel modell in R

My question is strongly related to this one, but I would need a more specific answer. I am running a FE regression with year dummies using the standard plm package ...
0
votes
0answers
39 views

same variable as both random and fixed effect in mixed models

Let's say I have a variable with 6 levels, for example, different tasks which are just a subset of all possible tasks. I am interested in differences between the tasks so should add it as a fixed ...
1
vote
0answers
19 views

How can I evaluate with R the interaction between a within-subject effect and a continuous variable at the subject level?

Scenario: 62 subjects did a selection task composed of 128 items, that can be divided into four conditions, because each item has a cue and a target (also other options but thats not of interest in ...
0
votes
0answers
22 views

lagged explanatory variable interpretation

I'm using a conditional fixed effects ordered logit model (blow-up and clusete namely) and a panel dataset to estimate the effect of a life-event (x) on ones preferences (y). My explanatory variable ...
1
vote
1answer
38 views

glmer categorical fixed effects estimate missing? -R

I posted a question recently regarding general linear mixed effects models, and I think I may have finally specified the glmer model correctly. I am interested in finding any differences in home range ...
0
votes
0answers
45 views

Fixed Effects for fractual response variable with many zero observations

I am investigating the impact of some independent variables on educational expenditure shares, which is given as the proportion of $\frac{educational\_expenditure_i}{total\_expenditures_i}$. The ...
0
votes
0answers
22 views

What is the difference between HAC and PCSE?

I have data consist of 88 companies in 5 year (440 observations) and used 3 independent variables with 3 control variables (total 6 variables). I have already test the best model for my data and the ...
0
votes
0answers
7 views

Absorbing continues-categorical variable interaction term and predicting ex-post

Is there a way of absorbing categorical and continuous variables and then predicting them, because I can not create so many dummy variables in any software somehow I have to obtain the coefficients on ...
2
votes
0answers
38 views

Wikipedia says that “The random effects model is a special case of the fixed effects model”. Why?

I understand that the assumption made in a fixed effects model is that there is a basic understanding of the included parameters, e.g. there is a proven theory or previous experiments have shown non-...
2
votes
0answers
41 views

“ANOVA on a non-random non-Normal sample from a Normal Population”

How can I run ANOVA or tests for statistical significance on a bi-modal sample that came from a normal population? Context: I was tasked with running an ANOVA to see if genotypes (treatments / ...
0
votes
0answers
20 views

Which regression model in appropriate when dependent variables are at individual level and independent variables at national level?

This is actually a panel data where dependent variables are in binary figures y1 ... y4 exhibiting thousands of entries for a single country. On the other hand few independent variables are on the ...
0
votes
0answers
26 views

HLM, MLM, LMM: How to approach this problem? (in R)

I'm trying to do a HLM analysis on a current project. Basically is data collected from surveys where each person gives a "grade" (as integer) to an specific business X. Also, this business belongs to ...