serial correlation in panel data

[Alexander123]

Hi,

I'm analysing panel data using 49 different countries and a time span between 2001-2006. I have three dependent variables: debt market capitalization/GNP equity market capitalization/GNP and number of listed firms per millions inhabitants. I also have various independent and control variables: civil law dummies, dummy for if the one share one vote principle is present in a given country, LogGNP, LogGNP per capita, Lag1GDP growth, rule of law and number of antidirector rights present in a country (variable that doesn't change over time). Hypothesis: civil law countries have higher: debt and equity market cap and more listed firms per million inhabitants. When I run my regressions my results are fine and quite significant, but it has a durbin watson value of around 0, indicating strong serial correlation. When I try to remove the serial correlation using first differences, my coefficients and results change a lot and all but one or two become very insignificant. Should I always remove serial correlation and are there perhaps other ways to do it that fit my data better? I've added one of my datasets to this message.

Kind regards,

Alexander