Note that the dependent variable evolve with the time. Independent variables that you consider are static for a certain period with the Likert’s Scale. Generally, time series data should go with another variable’s data that should also evolve with the time. Running a regression of a time series date with the Likert’s Scale could be biased, since there would be a problem of generalisation in research. The results can be meaningful only for one-time only for the period in which the data for independent and dependent variables are lying together.
However, if the independent variables are available with time-span of time-series dependent variable, the regression can be possible. But, there is something for thought that normally, measuring the Likert’s Scale variables with time-evolvement is difficult, because Likert’s Scale variables are subject to human perceptions. Hope this will help you to decide what to in your studies. Good luck.
Consider: is it possible to have a significant correlation between the rate of change in diesel prices for the period 1960-2018 (dependent variable) and the skills of the drivers (1- very bad ... 7 - professional, excellent skills). :) :) :)
If you are exploring the same population, on the same issues Likert’s Scale over a period of time.
Thank you all for your comments and I agree with all. Just to give you a background, I asked the participants' perceptions if they think the independent variables i put together affected the dependent variable (1 - strongly disagree, ... , 3 - neither nor, ..., 5 -strongly agree). I then used a one sample t-test on the likert scale data only to see if the mean values are significantly different from the neutral value to make my conclusions. I hope the direction i am going is appropriate. Any more suggestions?