NDA vs UPA: Data-driven study decodes growth in two eras; check insightful analysis

BJP-led govt nurtured fast-paced growth and spurring economic activity in remote locations that were ‘neglected’ under the UPA 1 and UPA 2

BJP-led govt nurtured fast-paced growth and spurring economic activity in remote locations that were ‘neglected’ under the UPA 1 and UPA 2
BJP-led govt nurtured fast-paced growth and spurring economic activity in remote locations that were ‘neglected’ under the UPA 1 and UPA 2

Constituencies under BJP govt have more ‘green spots’ of growth as  recorded across the country

Here is an insightful analysis of the growth rate under the Congress-led UPA I, UPA II, and BJP-led NDA era, based on hardcore data analysis, which compares the growth charts in the last 10-15 years, with specific attention to Parliamentary constituencies and also district to sub-district levels and also concludes, which era ‘got the better of whom’ in terms of growth.

Shamika Ravi, a member of the Economic Advisory Council to the Prime Minister, has taken a deep dive and done a comprehensive analysis by mixing two data sets. Her research titled ‘Politics in Action’ has collated day-time satellite data for built-up areas under Parliamentary constituencies and compared it with data sourced from the Election Commission, to map the growth under UPA and NDA governments.

BJP-led NDA wins the comparison hands down, as it is found to have nurtured fast-paced growth and spurring economic activity in remote and far-off locations, ‘neglected’ under the UPA 1 and UPA 2.

The day-time satellite imagery data studied growth rates from the Parliamentary constituency to sub-district levels and found an 18 percent higher growth rate under the Modi government.

The day-time satellite imagery data captured the built-up surface area, under Parliamentary constituencies, at extremely high resolution. The growth of built areas including roads, buildings, commercial establishments, and other units of infrastructure was studied to conclude a ‘high growth rate’.

When the average growth was compared across Parliamentary constituencies, it was found to be 3.3 percent annualized growth in the NDA rule (2015-2023) as compared to 2.8 percent during the UPA rule.

On the question of ‘which Parliamentary constituency grew the most’, the research found that growth was more widespread under the Modi govt as more ‘green spots’ of growth were recorded across the country, North in particular.

It further found that year 2015-2020 saw the fastest growth in some of the most backward and underdeveloped parts of the country.

“Under NDA, the highest built-up area growth happened in the least developed parts of the country. Those constituencies, rural and remote, recorded the highest annualized growth,’ the research found.

Comparing the growth at district levels, the research found that it was 21 percent higher under the Modi government as compared to UPA 2 while it was 31 percent higher in comparison to UPA 1.

At the sub-districts level also, 31 percent greater growth was recorded under NDA, compared to UPA – II while 21 percent higher growth under NDA was recorded, as compared to UPA- I.

Overall, the study finds that economic activity, under the Modi government was more focused on the least developed parts of the country, which either lagged or remained of least priority, during UPA 1 or UPA 2 rule.

On the inequality factor too, the study finds that the NDA government was more effective in bringing economic dynamism in backward regions.

Economist Shamika Ravi further said that the day-time data, used for drawing the ‘comparison chart’, is irrefutable as it maps the real-time changes on the ground.

“District and sub-district level data, over last 10 years, was studied to see changes under different regimes, with extremely localized analysis,” she added.

[With Inputs from IANS]

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1 COMMENT

  1. Pappu is still undeveloped inspite of so many BJP policies of nutrition, education, free ration….etc.. and Pappu also jobless.
    Conclusion
    BJP is an utter failure !!

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