Why include lagged variables?

Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process.

What is the explanatory variable in a study?

❖ The variable that is used to explain or predict the response variable is called the explanatory variable. It is also sometimes called the independent variable because it is independent of the other variable. In regression, the order of the variables is very important.

Should you include lagged dependent variable?

It makes sense to include a lagged DV if you expect that the current level of the DV is heavily determined by its past level. In that case, not including the lagged DV will lead to omitted variable bias and your results might be unreliable.

How do you know if a variable is explanatory or response?

Explanatory vs response variables The difference between explanatory and response variables is simple: An explanatory variable is the expected cause, and it explains the results. A response variable is the expected effect, and it responds to explanatory variables.

How to introduce lag time variables in panel data?

3- Data in Stata for panel data is settled up monthly, yearly and so on, but I don´t know how to proceed with Triennial data. You don’t need to create new lag variables. Stata has time-series operators which can be used in your modeling commands directly.

How to create a lag variable in Stata 5?

Stata 5: How do I create a lag variable? Create lag (or lead) variables using subscripts. You can create lag (or lead) variables for different subgroups using the by prefix. For example,

How are regressions with time series variables affected?

1. Regressions with time series variables involve two issues we have not dealt with in the past. First, one variable can influence another with a time lag. Second, if the variables are non-stationary, the spurious regressions problem can result. The latter issue will be dealt with later on. 2. Distributed lag models have the dependent

What happens if your data is not panel data?

Note that Stata will verify that your data really is panel data with three year intervals, and if it finds data that do not fit the pattern, it will give you an error message and refuse to proceed. If that happens, you have to go back and fix your data (or change your understanding of what your data is, if you had it wrong.)