# Panel data regression of crowdfunding projects

I never did something with panel data before, and could use some help.

I have data of 173 crowdfunding projects, measured at four different time points, with %funded, if the project contains a video, and the amount of comments and updates.

I want to know, in particular, the effect of the increase in updates on %funded, and the project having a video or not.

OLS, random, fixed everything is kind of new for me, could someone point me in the right direction?

Thank you!

edit:

I have decided to use change in %funded as my DV, and change in number of updates, the goal amount (constant), whether it contains a video (0/1) or whether it is featured (0/1) as my IVs. I've done the hausman test, which recommends the random effects model.

    Random-effects GLS regression                   Number of obs      =       519
Group variable: project                         Number of groups   =       173

R-sq:  within  = 0.1407                         Obs per group: min =         3
between = 0.2628                                        avg =       3.0
overall = 0.2149                                        max =         3

Wald chi2(6)       =    116.26
corr(u_i, X)   = 0 (assumed)                    Prob > chi2        =    0.0000

------------------------------------------------------------------------------
cfunded_w |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
goal_w |  -.0001171   .0000382    -3.06   0.002    -.0001921   -.0000422
cupdates_w |   7.712477   1.019072     7.57   0.000     5.715134    9.709821
video |    9.30539   2.987579     3.11   0.002     3.449842    15.16094
staffpicked |   6.385104   6.595511     0.97   0.333     -6.54186    19.31207
|
|
_cons |   9.231501   2.746575     3.36   0.001     3.848312    14.61469
-------------+----------------------------------------------------------------
sigma_u |  14.286375
sigma_e |  18.899747
rho |  .36362048   (fraction of variance due to u_i)
------------------------------------------------------------------------------


I want to know more about the effects for each different time period (out of three)? adding if time<2 for example gives an error: insufficient observations

could someone enlighten me or point me in the right direction?

Should I just make three different Time Dummies and put T2, T3 in the regression when estimating for T1?

Thank you!