This dissertation is about how social comparisons leading to envy and pride impact decisions. We, humans, may feel envious and proud for different reasons. One view is that comparing our performance with others' can give us a useful signal about our productivity and skill, and then envy and pride just help us to learn from such experience. The other plausible view is that envy and pride may reflect changes in social status, where dominance in social group is the ultimate objective. In Chapter 1 we report the results of fMRI experiment in which subjects faced simple decision problem in both private and social environments without strategic interactions. The analysis of behavioral and neural data provides evidence for subjects performing social comparisons exhibiting envy and pride while evaluating outcomes of decisions. This effect is even stronger if decision-makers bear relatively more responsibility for the resulting difference in outcomes. In Chapters 2 and 3 we explore social comparisons in strategic situations focusing on 3-person ultimatum game, first in purely behavioral and then in fMRI experiments. In the former we find evidence for responders exhibiting envy and pride. In Chapter 3 we focused on neural basis of rejections of low but positive amounts of money by responders. We show that the involvement of negative emotions in rejections of such low but positive offers is not due to their unfairness, but rather reflects negative reputational signal that the actual acceptance can send to others about the responder. Finally, we implicated nucleus accumbens in the decision process behind responders' decision on low but positive offers. This is an area, shown elsewhere to track subjective value of rewards, and that exhibited envy and pride effects documented in chapter 1. From the methodological standpoint Chapters 1 and 3 show how an economist can test an economic model on both behavioral and neural data. Such tests of economic theory are more credible in our view despite the necessity of making additional assumptions related to the use of neural data.