section_path: Methodology/Empirical research
section_name: Empirical research
paragraph_text: Empirical research
  
  Economic theories are frequently tested empirically, largely through the use of econometrics using economic data. The controlled experiments common to the physical sciences are difficult and uncommon in economics, and instead broad data is observationally studied; this type of testing is typically regarded as less rigorous than controlled experimentation, and the conclusions typically more tentative. However, the field of experimental economics is growing, and increasing use is being made of natural experiments.
  
  Statistical methods such as regression analysis are common. Practitioners use such methods to estimate the size, economic significance, and statistical significance ("signal strength") of the hypothesised relation(s) and to adjust for noise from other variables. By such means, a hypothesis may gain acceptance, although in a probabilistic, rather than certain, sense. Acceptance is dependent upon the falsifiable hypothesis surviving tests. Use of commonly accepted methods need not produce a final conclusion or even a consensus on a particular question, given different tests, data sets, and prior beliefs.
  
  Experimental economics has promoted the use of scientifically controlled experiments. This has reduced the long-noted distinction of economics from natural sciences because it allows direct tests of what were previously taken as axioms. In some cases these have found that the axioms are not entirely correct.
  
  In behavioural economics, psychologist Daniel Kahneman won the Nobel Prize in economics in 2002 for his and Amos Tversky 's empirical discovery of several cognitive biases and heuristics. Similar empirical testing occurs in neuroeconomics. Another example is the assumption of narrowly selfish preferences versus a model that tests for selfish, altruistic, and cooperative preferences. These techniques have led some to argue that economics is a "genuine science".