Questions tagged [tobit-regression]

Tobit regression is used to estimate a linear regression model when the dependent variable is censored, i.e. when it is only observed over an interval of its support.

Filter by
Sorted by
Tagged with
0
votes
0answers
11 views

Difference-in-difference regression and random-effects Tobit model

I have a question about the difference-in-differences (DID) model. In general, we use random-effects Tobit model to fit the censored panel data (in Stata command: xttobit...). But to my knowledge, ...
0
votes
0answers
33 views

Tobit model with truncated data

I would like to examine the impact of institutional ownership on M&A deal size, as in Andriosopoulos & Yang (2015). However, I am in doubt which regression method to use for measuring this ...
0
votes
0answers
10 views

Asking: interpret tobit regression to estimate willingness to pay from payment card

I have a research question, that I have to evaluate the Willingness to pay data for conservation. My input data in the type of payment card : $0, <\$2, \$2-\$4, \dotsc, >\$10$. I use middle ...
1
vote
0answers
18 views

Predictive Margins After Mixed-Effect Tobit

I'm hoping to get advice on the difference between two predictive margins outputs after running a mixed-effect tobit regression (in Stata 16.0). Here is a sample output (modified from my actual case),...
1
vote
0answers
12 views

2-stage selection model with censoring: Heckman selection model with second stage censoring

I am seeking to get some insights on the application of two-part Tobit-type models to a distribution with potentially selection (from 0 into +ve) and upper truncation (censoring of data at 100%). ...
0
votes
0answers
27 views

Difference-in-difference using tobit regression with mediation (controlling for fixed effects)

I want to conduct a mediation analysis in a difference-in-difference setting. I want to determine which element of the policy was effective. My difference-in-difference is based on a matched sample ...
0
votes
0answers
63 views

How to estimate high dimension fixed effects (HDFE) in a Tobit model?

I'm searching for a possibility to estimate a Tobit model with a high number of individual fixed effects. To be more precise, my goal is to estimate the individual determinants of the number of hours ...
0
votes
0answers
13 views

$\ln(y)_{ij} = \beta_1 \ln(x_1)_{ij} + \beta_2 \ln(x_2)_{ij} + \epsilon$ for censored data, what would be the elasticity of $y$ w.r.t $x_1$?

Suppose we wish to estimate $$ ln(y)_{ij} = \beta_1ln(x_1)_{ij} + \beta_2 ln(x_2)_{ij} + \epsilon $$ If the data was not censored, then the elasticity of $y$ w.r.t $x_1$ would be $\beta_1$. However, ...
0
votes
0answers
20 views

Hurdle model: different results for 2nd stage and truncated regression

I am trying to estimate a hurdle ('zero inflated') model using the R package mhurdle to model farmers' participation & participation intensity in environmental schemes. For understanding, I have ...
1
vote
2answers
69 views

A workaround for using linear models (rather than Tobit) with censored data?

I have a left censored dependent variable where many of the observations have a value of zero. The data is clustered (multiple measurements over time for each person). I initially decided to use a ...
0
votes
0answers
38 views

Estimation of censored regression model

I am refreshing my knowledge with respect to econometric modelling in general. I came across page 201 of the book 'Enjoyable Econometrics by Philip Franses' and I had some difficulties interpreting ...
3
votes
0answers
23 views

Multiple regression for left-censored independent and dependent variables

I am interested in developing a predictive multiple regression model which predicts a concentration of one compound based on the measured concentrations of several other compounds. Both the dependent ...
1
vote
0answers
15 views

Unbiased estimation of regression coefficients conditional on a range of the dependent variable

I am interested in the relationship between a set of explanatory variables and a particular outcome variable for values of the outcome above a certain cutoff. Can I simply regress the outcome on the ...
0
votes
0answers
36 views

Conditional heteroscedasticity for the tobit model in Layman's terms

I have been using the crch package for modelling censored data with the tobit model. I noticed early on that the errors (by far) are not normally distributed by ...
0
votes
0answers
57 views

Question about a type 3 tobit model MLE

I am struggling a bit with the derivation of the MLE for this question about tobit models,. I have seen derivations of type II and type I MLEs online, but I was hoping someone could give me some ...
0
votes
1answer
20 views

Question about deriving probabilities in the Tobit model

In the Tobit model: Why do you divide by σ when deriving the probability that y = 0? Is it something to do with the assumption that ε is distributed N(0,σ^2) and not N(0,1)? If this is the case why ...
6
votes
1answer
243 views

What is really the Scale or Sigma parameter of a tobit regression?

In this most upvoted CV answer on that topic the "scale" parameter (aka "sigma" in Stata) thrown in a tobit regression output is explained to be "the estimated standard deviation of the residuals". (...
0
votes
0answers
15 views

how to remove the heteroscedasticity of latent variable in tobit model? by using SAS software

i have done a tobit model. when using white test to test heteroscedasticity of latent, the outcome is significant. after search related questions in stackexchange, i found "inverse hyperbolic sine" ...
1
vote
1answer
118 views

Hurdle model vs left censored model

When dealing with response variables that have lots and lots of zeros, is there a clear argument for when hurdle models are preferred and when left censored or tobit models are preferred?
1
vote
1answer
46 views

Picking from Logistic vs Survival Model

I have a health data set for measuring the effectiveness of a drug. (Age, Gender(0,1), Morbidity(1,2,3), Dosage(0,1), Group (a,b), Effect (Not effective =0, effective = 1), and Time (days needed for ...
1
vote
1answer
108 views

How to get rid of zero standard error values, missing t-values and p-values

I was running a couple of Tobit regressions on SAS. Surprisingly, I found that estimates from one model show 0 standard errors, missing (.) t-values and p-values. Why did this happen? What does this ...
1
vote
0answers
249 views

Comparing the output and fit of an OLS and a Tobit model, and comparing Tobit models

I am trying to estimate a quite complicated model (many variables with different structures), with a limited dependent variable, which ranges from 0-100% with about 45% of the sample having an ...
2
votes
0answers
186 views

Censored Regression/Tobit: coefficients decrease drastically when non-normal distribution is assumed

I am trying to use a Tobit/ censored regression model to estimate the effect of a certain political condition on a tax. Our dependent variable is zero-inflated because in most of our observations this ...
3
votes
0answers
200 views

My Tobit model gives all infinite standard deviations

I am trying to do a Tobit estimation (in R) because my dependent variable ranges from 0-100 with many values at a 100. ...
1
vote
1answer
84 views

standard error estimate in CRCH

[Disclosure: I previously posted this over at stackoverflow, but I think that was the wrong place as I got no response. I've since deleted that post.] I need to run a regression on censored data, and ...
1
vote
0answers
132 views

Censored regression with right censored data

I'm kind of new to Stats and R in general and I'm looking to clear some doubts. I'm trying to use Censored regression models to do the analysis of my qPCR data. The response variable is continuous (Ct ...
1
vote
0answers
139 views

Tobit model: Left and right censoring

In my data, my outcome variable days.to.event is conceptually left censored at 0 days and right censored at 30 days. However, since the ...
1
vote
1answer
127 views

Tobit model with flexible censoring point in R

I am currently writing my MSc thesis and I am using a Tobit model. My data consists of fleet and sales data. The censored dependent variable is quantity and this quantity is higher than the fleet ...
1
vote
1answer
181 views

How many parameters should I report in an AIC table for a tobit model?

I am considering using a tobit model in R to estimate velocity of a number of animals moving north across a landscape. I am working with simulated data, so when an ...
1
vote
0answers
287 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 '...
1
vote
0answers
18 views

How to model if a company is mentioned in a review (volume) and how it is mentioned (valence)?

I am working with social media data of Brand A and would like to model what features of posts of Brand A are linked to if a competitor (Brand B) is mentioned in the comments of different posts of ...
0
votes
0answers
586 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 ...
2
votes
1answer
59 views

validity of tobit estimates after multiple imputation

I want to estimate tobit marginal effects using multiply imputed data, however I see that tobit is not among the estimation commands supported by Stata's MI prefix - I understand that the validity of ...
1
vote
1answer
874 views

Two intercepts for Tobit regression in R using VGAM

I'm fitting a Tobit regression left censored at 0 using the vglm function from the VGAM package. But, after fitting the model, I'm getting two intercepts? Is this a problem with the function? If not, ...
0
votes
0answers
245 views

Can I use a two-limit tobit model to drop certain outliers?

I am implementing a Tobit model, since my dependent variable (educational expenditure shares) is left-censored at 0. Below you'll find a swarmplot of the dependent variable and the explanatory ...
0
votes
0answers
22 views

Are there problems with estimating regressions of longitudinal data by year?

I am studying the behavior of 900 firms for a period of 10 years. The data is a balanced panel. Multivariate analysis consists of Tobit estimations for each year and probit estimations for each year. ...
2
votes
1answer
260 views

Confidence intervals for the coefficients of a Tobit model

Given a linear regression model for a dependent variable that is left-censored at 0 (i.e., a Tobit model), how can I calculate confidence intervals for the coefficients? Ideally, you would provide ...
0
votes
1answer
154 views

Inverse Gamma Posterior variance derivation in Tobit model

I have a doubt about the posterior distribution of the variance parameter for the Tobit model as provided by Koop, Poierier, Tobias (2007) in "Bayesian Econometrics Methods" page 221. Posteriors for ...
0
votes
1answer
629 views

Using PROC QLIM OUTPUT to get predicted values from a two-step Tobit model

I am fitting a two-step Tobit model through PROC QLIM in SAS. The first step of the model is a probit model for whether someone "responds" (e.g. makes a donation). The second step of the model is ...
1
vote
1answer
260 views

Probability Density Function in a Tobit Model

I have been taught the following derivation of the tobit model from a latent underlying variable model: Suppose: $y*=$ latent variable (e.g. utility) $y=max[0,y*]$ And $$y* = \mathbf X\beta + u,\...
2
votes
0answers
446 views

Confidence interval of the panel data model

I have a panel of $m$ individuals over $n$ periods of time. I am estimating decision making rules of people $Y=\beta_0+\beta_1X + ...+\epsilon$. I have reasons to believe that $\beta_1$ are very ...
0
votes
0answers
66 views

goodness of fit in regression/ models include a significant number of insignificant variables

I have performed analyses using two different regression models, multi-nominal regression and Tobit regression. In the first model I measured the impact of 9 variables on choosing travel mode while ...
2
votes
1answer
2k views

likelihood function for Tobit

I am trying to sort out the likelihood function for a two-limit Tobit model (data censored from above and below). To start off, suppose you have data censored from below at zero. The log-likelihood ...
0
votes
1answer
261 views

Predicted probabilities - Tobit/probit - differences

For long I have been a silent reader of your forum, but now I have to ask you for your expertise, as I haven't found an answer to my question yet. Short to my back story: My aim is to calculate the ...
1
vote
0answers
448 views

In R, can I include random effects in a censored regression?

I am comparing the consumption of algae given a treatment (5 levels) each at a unique site (N = 20). I deployed the same amount of algae at each site and assessed algal consumption by recording the ...
1
vote
0answers
217 views

Omitting the Inverse Mills Ratio and corresponding coefficient from a model?

I have a question with regard to the inverse mills ratio as part of my type II Tobit model (Heckman model). The residuals of my Probit and OLS are not significantly correlated (r = 0,000666; p-value ...
3
votes
0answers
750 views

Tobit model (or survival analysis) for imputation of censored data in R

I have some data with missing values. For the missing observations I know a range, in which the true values are. I want to use a tobit model to predict the variable with these missing values. The ...
3
votes
1answer
2k views

Implementing a hurdle/Zero-inflated Poisson model in R with right-censored count data

I'm trying to fit a hurdle/zero-inflated (I haven't decided yet) model on microbiological water quality data that is also right-censored: either the water sample is contaminated with bacteria or not, ...
0
votes
0answers
282 views

Using tobit for a positively skewed variable

I have a continuous dependent variable which is positively skewed. The relevant data is panel data. Can we run a Tobit regression on this dependent variable?
8
votes
1answer
3k views

Exact difference between two-part models (e.g., Cragg) and Tobit type 2 models (e.g., Heckman)

I want to run a regression where the DV is the amount of funding (in USD) obtained by startups. Naturally the DV contains a lot of zero's (~55%) and has a continuous distribution for y>0. In general ...