Yes, if the panel data sample is small, it will affect the reliability. The smaller the sample, the less the reliability of the statistical inference. This is generally the case in statistical inference. The larger the sample the less the standard error of the parameter estimators.

• http://articles.mercola.com/sites/articles/archive/2016/08/16/antibiotic-use-in-poultry.aspx

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Article Cross-sectional and Panel Data Analyses of an Incompletely O...

One thing that you should also consider is that you have to make sure that your results are not sensitive to (i) the time period and (ii) the panel members you select. If that is the case, then (in addition to regular effects) you should include some specific variables (e.g., a crisis dummy variables for years 2008-1013) to correct for the heterogeneity coming from the changing of the scope of the panel. 

In panel data analysis, the number of observations plays a crucial role in determining the statistical power, precision of estimates, robustness of results, and validity of assumptions. Larger numbers of observations generally lead to more reliable and stable results, while smaller sample sizes may increase uncertainty and susceptibility to bias. Increasing the number of observations enhances the reliability and robustness of panel data analysis.