Economics got on just fine before the attack of the econometricians and their data mining and publication bias:
From ‘The Scientific Illusion in Empirical Macroeconomics’, Lawrence H. Summers , The Scandinavian Journal of Economics, Vol. 93, No. 2, Proceedings of a Conference on New Approaches to Empirical Macroeconomics. (June 1991), pp. 129-148.
A baser reason for holding out against the latest empirical is in Most Published Research Findings Are False, John Ioannidis says that:
There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims. However, this should not be surprising. It can be proven that most claimed research findings are false
Ioannidis goes on the say that
- The truth of a research claim is true may depend on study power and bias, the number of other studies on the same question, and, the ratio of true to no relationships among the relationships probed in each scientific field; and
- a research finding is less likely to be true when the studies conducted in a field are smaller, when effect sizes are smaller, when there is a greater number and lesser preselection of tested relationships, where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.
Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Ioannidis also says that for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias.
Now let The Guardian finish matters with “False positives: fraud and misconduct are threatening scientific research: High-profile cases and modern technology are putting scientific deceit under the microscope”:
Cases of scientific misconduct tend to hit the headlines precisely because scientists are supposed to occupy a moral high ground when it comes to the search for truth about nature.
The scientific method developed as a way to weed out human bias. But scientists, like anyone else, can be prone to bias in their bid for a place in the history books.
Increasing competition for shrinking government budgets for research and the disproportionately large rewards for publishing in the best journals have exacerbated the temptation to fudge results or ignore inconvenient data.
Massaged results can send other researchers down the wrong track, wasting time and money trying to replicate them. Worse, in medicine, it can delay the development of life-saving treatments or prolong the use of therapies that are ineffective or dangerous.
Malpractice comes to light rarely, perhaps because scientific fraud is often easy to perpetrate but hard to uncover.
Utopia, you are standing in it! 
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