An increase in energy resource development activity during the past decade has contributed to a corresponding rise in related legislation and research.1Policymakers and investigators, for example, have intensified their efforts toward gaining a clearer understanding of the socioeconomic consequences and ramifications of energy development activity.Although an expanding body of literature in this area is becoming increasingly more comprehensive, several issues remain relatively unclear.One of the most apparent ambiguities is the distribution of benefits from energy resource development to impacted residents, especially longtimers (Murdock and Schriner, 1978).The lack of information on the development benefits received by local residents may be attributed to the complex and paradoxical effects of energy-related industries. Energy resource development, for example, may offer substantial economic benefits to local residents (e.g., enhanced employment opportunities) yet concurrently subject them to substantially increased costs (e.g., inflationary effects, increased infrastructural and service costs) (Lovejoy, 1977; Little, 1977;Cortese and Jones, 1977).Similarly development may increase local resident per capita income but simultaneously intensify income inequality within the community (Betz, 1972;Summers and Clemente, 1976).The focus of this article is to examine the effects of energy development on local residents in impacted areas.Specifically, we address shifts in the distribution of income and education, two important indicators of mobility and well-being.Although income distribution has been the subject of numerous impact studies (Pulver et al., 19821, the methodological approach i n this article is unique. First, we compare changes, controlling for population growth, in aggregate measures of median income and median education between impacted and corresponding nonimpacted counties. This multicounty comparison is conspicuously absent in most previous studies. Secondly, we illustrate shifts in inequality by utilizing Lorenz curves.Gini coefficients are also calculated to provide single indicators of inequality. This technique is a fundamental improvement over aggregate measures since it offers insight into distributional changes. Finally, we offer suggestions which may be useful in conducting future research on the effects of development on social and economic inequality in energy-impacted areas.