Poverty Eradication – Definition, Debates, etc.

[oped of the day] The new gold standard in development economics?

Note4Students

From UPSC perspective, the following things are important :

Prelims level : Nothing much

Mains level : RCT application

Context

Development economics has changed a lot during the last two decades mostly due to the extensive use of ‘randomised control trials’ (RCT). 

RCTs

    • Used in developing economies – RCTs are used to assess long-run economic productivity and living standards in poor countries.
    • Evolution of RCT – The concept of RCT is quite old; instances of RCTs can be traced back in the 16th century. 
    • The statistical foundation of RCT was developed by British statistician Sir Ronald Fisher, about 100 years ago, mostly in the context of the design of experiments.

Quotes

    • Prof. Banerjee thinks RCTs “are the simplest and best way of assessing the impact of a program”.
    • Prof. Duflo refers to RCTs as the “tool of choice”.

Use in clinical trials

    • Evaluation of performance – For an unbiased evaluation of the treatment, its performance needs to be compared with some ‘control’, which may be ‘no treatment’ at all or an ‘existing treatment’ other than the treatment under study.
    • Allocating patients – The next task is to allocate the patients among two treatments/interventions at hand. Patients might prefer some treatment to the other. 
    • No prior knowledge – Prior knowledge of the treatments to be applied to them might induce a ‘selection bias’ due to unequal proportions of patients opting-out from the study. 
    • ‘Randomisation’ – it is a procedure used to prevent this by allocating patients using a random mechanism — neither the patient nor the doctor would know the allocation.
    • ‘Control’ and ‘randomisation’ together constitute an RCT. 

Application in early trials: ART

    • In 1995, statisticians Marvin Zelen and Lee-Jen Wei illustrated a clinical trial to evaluate the hypothesis that the antiretroviral therapy AZT reduces the risk of maternal-to-infant HIV transmission. 
    • A standard randomisation scheme was used resulting in 238 pregnant women receiving AZT and 238 receiving standard therapy (placebo). 
    • It is observed that 60 newborns were HIV-positive in the placebo-group and 20 newborns were HIV-positive in the AZT-group. 
    • Thus, the failure rate of the placebo was 60/238, whereas that of AZT was only 20/238, indicating that AZT was much more effective than the placebo.

Benefits of RCT

    • Overcoming heterogeneity – Drawing such an inference, despite heterogeneity among the patients, was possible only due to randomisation.
    • Easy comparability – Randomisation makes different treatment groups comparable and also helps to estimate the error associated with the inference.
    • Anonymity – It ensures that allocation to any particular treatment remains unknown to both patient and doctor. Such ‘blinding’ is central to the philosophy of clinical trials and it helps to reduce certain kinds of bias in the trial.

Applications of RCT

    • Agriculture – The early applications of RCTs were mostly within the agricultural field. 
    • RCT got its importance in clinical trials since the 1960s. Almost any clinical trials nowadays without RCT were being considered almost useless.

Use for social causes

    • Social scientists slowly found RCT to be interesting, doable, and effective. 
    • Social policies – Numerous interesting applications of RCTs took place in social policy-making during the 1960-90s. Eventually, RCTs took control of development economics since the mid-1990s. 
    • About 1,000 RCTs were conducted by the three Nobel Laureates in 83 countries such as India, Kenya, and Indonesia to study various dimensions of poverty, including microfinance, access to credit, behavior, health care, immunisation programs, and gender inequality. 

Success stories

    • Finland’s Basic Income experiment (2017-18) – 2000 unemployed Finns between ages 25-58 were randomly selected across the country and were paid €560 a month instead of basic unemployment benefits. 
    • Results from the first year data didn’t have any significant effect on the subjects’ employment in comparison with individuals who were not selected for the experimental group. 

Criticism of RCT

    • Chances of dilution – In order to conduct RCTs, the broader problem is being sliced into smaller ones. Any dilution of the scientific method leaves the conclusions questionable. 
    • Economists such as Martin Ravallion, Dani Rodrik, William Easterly, and Angus Deaton are very critical of using RCTs in economic experiments.
    • Limitations of blinding – such kind of ‘blinding’ are almost impossible to implement in economic experiments as participants would definitely know if they get any financial aid or training. Thus, randomisation must have much less impact there.

Importance of randomisation

    • Unless randomisation is done, most of the standard statistical analyses and inference procedures become meaningless.
    • Earlier social experiments lacked randomisation and that might be one reason that statisticians such as Sir Ronald Fisher were unwilling to employ statistics in social experiments. 
    • “RCT or no RCT” may not be just a policy decision to economics; it is the question of shifting the paradigm. 
    • As randomisation dominates development economics, economic experiments are becoming more and more statistical.

Conclusion

Harvard economist Lant Pritchett criticises RCTs on a number of counts but still agrees that it “is superior to other evaluation methods”.

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