i am analysing a firm panel where I am regressing the number of high skilled employees on three dummies and some control variables. One of them is investment (in Euros). I am using a Poisson fixed effects regression and Stata 13. The coefficient for investment is 9.60e-11, which is basically zero (0.000 when I round coefficient to three decimals, same for the confidence interval and standard error) and I am wondering what this means and how to interpret it? If there is no relationship between the variables it should not be statistically significant or am I mistaken?
Code:
xtpoisson highskill investict product_inno process_inno lnturnover lnavwages collective lnexportshare investment i.year, fe vce(robust) note: 224 groups (224 obs) dropped because of only one obs per group note: 10180 groups (49161 obs) dropped because of all zero outcomes Iteration 0: log pseudolikelihood = -120765.5 Iteration 1: log pseudolikelihood = -108313.47 Iteration 2: log pseudolikelihood = -108273.22 Iteration 3: log pseudolikelihood = -108273.22 Conditional fixed-effects Poisson regression Number of obs = 53,130 Group variable: idnum Number of groups = 9,405 Obs per group: min = 2 avg = 5.6 max = 12 Wald chi2(18) = 161.63 Log pseudolikelihood = -108273.22 Prob > chi2 = 0.0000 (Std. Err. adjusted for clustering on idnum) ------------------------------------------------------------------------------- | Robust highskill | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------+---------------------------------------------------------------- investict | .0256531 .010968 2.34 0.019 .0041561 .04715 product_inno | -.0059202 .0283482 -0.21 0.835 -.0614816 .0496412 process_inno | .035324 .0168719 2.09 0.036 .0022557 .0683923 lnturnover | .2225503 .038659 5.76 0.000 .1467802 .2983205 lnavwages | .0048915 .0269775 0.18 0.856 -.0479835 .0577664 collective | -.0064905 .0217641 -0.30 0.766 -.0491475 .0361664 lnexportshare | .0113623 .0076189 1.49 0.136 -.0035705 .0262951 investment | 9.60e-11 2.14e-11 4.50 0.000 5.42e-11 1.38e-10 | year | 2008 | .0124656 .0145073 0.86 0.390 -.0159682 .0408995 2009 | .0502652 .0342328 1.47 0.142 -.0168299 .1173603 2010 | .0917918 .0202746 4.53 0.000 .0520543 .1315292 2011 | .156842 .0540877 2.90 0.004 .0508321 .2628518 2012 | .2284362 .0607472 3.76 0.000 .1093738 .3474985 2013 | .2258726 .0640781 3.52 0.000 .1002819 .3514634 2014 | .271107 .067284 4.03 0.000 .1392328 .4029813 2015 | .2600914 .0546444 4.76 0.000 .1529904 .3671923 2016 | .2684858 .0528786 5.08 0.000 .1648456 .3721261 2017 | .3187303 .0638673 4.99 0.000 .1935527 .443908 2018 | .3404339 .0668107 5.10 0.000 .2094874 .4713804 -------------------------------------------------------------------------------
Thanks,
Helen
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