Economic enquiry is inherently related to complex statistical analysis- the kind of research that generates tons of data that is then analysed to churn out the figures policy experts like to quote and build policies around.
However, for all its rigorous analysis, Economic research is restrictive in the diversity of evidence it primarily analyses. Theoretical enquiry is often dismissed as a valid form of evidence due to the subjectivity that is evident in its collection and analysis. Paldam(2021) shows how in recent years, due to this apparent constraint of qualitative data, the proportion of theoretical papers being published has fallen significantly from 59.5% to 33.6%. 'Theory Fatigue' as he terms it, is the fall in interest and prevalence of theoretical papers in research. The reasons are varied; as a layman, or even a professional outside the fields of economics, it is easier to understand and interpret numbers in relation to theoretical evidence which often requires intense knowledge and time investment. Additionally, with the massive rise in research and publication of Economic research, it is a prevalent practice for reputed journals to favour studies rejecting what we know as ordinary knowledge- or in other words, that reject the null hypothesis. With statistical analysis, it becomes easier for researchers to bend the results to their favour, to fulfil the 'publication bias' that might increase chances of publication, even at the cost of the integrity of research.
However, deeper analysis provide much support to the argument of using theoretical studies as a part of Economic enquiry. Scott( 1991) aptly describes the importance of "contextualising" the situation through the use of the "evidence of experience"- something not found often in statistical analysis. Its purpose is to ground the research in real-life- to not reduce human suffering and knowledge to numbers and to try to understand the story that the data is trying to convey. Much of Dreźe’s analysis (Sense and Solidarity: Jholawala economics for everyone) credits knowledge to two sources- experience and research. Instead of seeing these as separate sources, he considers these as complementary sources which supplement the knowledge provided by the other.
Defending the integrity of subjective research, Dreźe sites the multiple uncertainties that can plague statistical analysis- unreasonable assumptions, omission of important data points, lack of representative data samples and coding errors. That is not to let theoretical enquiry off the hook, but simply to emphasise the fact that theoretical enquiry cannot be dismissed on the mere ground of possibility of error. Indeed there is immense benefit to including qualitative methods on enquiry in Economic research. Methods to reduce bias in such enquiries involves thinking about experience through multiple perspectives- including as many viewpoints as possible when conducting the study. This not only includes multiple researchers to eliminate the risk of researcher’s bias, but also multiple respondents to ensure more democratic and inclusive analysis that is less prone to individual bias.
Hence, while statistical data is an essential part of Economic enquiry, it certainly isn’t the only one and probably not the best either, making it worthwhile to look towards experience as a humbling and persuasive form of evidence.
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