Evaluating policy is a challenging experience that requires intricate knowledge and clever use of statistical and economic techniques. The confounding thing about policy change is that it neither happens over night nor in a setting where other environmental elements remain static. Consequently, figuring out the impact of a specific change on the observed outcome change becomes a serious metrological challenge. However several standard techniques have emerged to access the effectiveness of specific policy discussion. A broad discussion of a few of these approaches is helpful in understanding the logic of how to think about evaluating policy. Most famous techniques for policy impact measurement often referred to as "Gold Standard" in impact evaluation is Randomized Control Trails (RCT). Medicine and pharmaceutical research is the best example of RCT method. The standard metrological technique is to select a group of respondents on whom the drug is likely to work. The drug is then administered to a randomly selected subset of that group. The RCT approach here is to administer an intervention to a randomly selected group of recipients from amongst a group of potential beneficiaries to judge the effect of the intervention exactly. The RCT administrator can convince the policy maker to make his/her choice of beneficiary units randomly rather than by aligning it to some other rule.