Analyzing Energy Firms' Distribution Policies In A Post-JGTRRA Environment

Open Access
Roth, Nathan Chad
Area of Honors:
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Joseph Randall Woolridge, Thesis Supervisor
  • James Alan Miles, Honors Advisor
  • James Alan Miles, Faculty Reader
  • Distributions
  • Dividends
  • Buybacks
Corporations establish business models and create strategic initiatives aimed at maximizing shareholder value. In doing so, firms have a decision as to multiple forms of capital allocation, comprised of, in their simplest breakdown: dividends, share repurchases, capital expenditures, and debt repayments. The extent of each relies on a number of factors, including the prevailing tax benefits and investment opportunities, and becomes especially prudent in firms with heavy cash flows; such as the case in the energy sector (ex-utilities). When parity amongst capital gains and dividends exists and growth is rampant, the balance between distribution policy and capital deployment becomes a much more complex and intriguing puzzle. The inherent goal of this paper is to analyze a time period under the aforementioned conditions, specifically June 2003 - December 2007, post-Bush tax cuts, in order to decipher whether any clear signal exists as to why firms established their respective distribution and investment policies, and whether said policies had statistically different outcomes for these companies. I found that while both total and aggregate dividends increased, the likely basis behind this was a recovery in net cash flows rather than tax policy. Further, distribution switching was not pronounced, as dividends did increase at a significant rate, but the breakdown of distributions shifted heavily towards repurchases. Lastly, while there was too much noise for a robust result, I saw that management acted too cautiously and thus inefficiently when determining uses of cash flows. These conclusions come at the hands of both qualitative and quantitative analysis of firm and industry actions by creating a linear regression model that accounts for allocations, margins, and sensitivity to oil prices and the broad market.