Complexity Explorer Santa Few Institute

Newman, Mark EJ. "Power laws, Pareto distributions and Zipf's law."Contemporary physics 46.5 (2005): 323-351.  A very clear review article.  Includes around a dozen examples of empirical power laws.  Discusses basic mathematical properties of power laws. [pdf]

Clauset, Aaron, Cosma Rohilla Shalizi, and Mark EJ Newman. "Power-law distributions in empirical data." SIAM review 51.4 (2009): 661-703. [pdf]  This is the definitive paper on testing for power-law behavior in empirical data. Code in r, matlab, and python is available at http://tuvalu.santafe.edu/~aaronc/powerlaws/.  Power-law data can be found at: http://tuvalu.santafe.edu/~aaronc/powerlaws/data.htm. And binned power-law data can be found at: http://tuvalu.santafe.edu/~aaronc/powerlaws/bins/.

Alstott, Jeff, Ed Bullmore, and Dietmar Plenz. "powerlaw: a Python package for analysis of heavy-tailed distributions." (2014): e85777.  [html]  Code at: https://github.com/jeffalstott/powerlaw and documentation at https://pypi.python.org/pypi/powerlaw.  I've not tried this yet, but it looks like a great resource.

Adamic, Lada A. "Zipf, power-laws, and pareto-a ranking tutorial." Xerox Palo Alto Research Center, Palo Alto, CA. (2000).  [html]  A very useful, short tutorial.

Limpert, Eckhard, Werner A. Stahel, and Markus Abbt. "Log-normal Distributions across the Sciences: Keys and Clues On the charms of statistics, and how mechanical models resembling gambling machines offer a link to a handy way to characterize log-normal distributions, which can provide deeper insight into variability and probability—normal or log-normal: That is the question." BioScience 51.5 (2001): 341-352.  [pdf]

Gabaix, Xavier. Power laws in economics and finance. No. w14299. National Bureau of Economic Research, 2008. [pdf]