New Delhi, Aug 21 : The government on Tuesday extended the deadlines for various Goods and Services Tax (GST) returns for taxpayers registered in flood-hit Kerala, Mahe in Puducherry and Kodagu in Karnataka.

It also extended the last date for filing GST summary sales returns or Form GSTR-3B for all classes of taxpayers across the country for the period of July to August 24.

"In light of the inconvenience faced by the people of Kerala due to the flood situation, the GST returns (GSTR-3B) for the month of July can now be filed by October 5, and the returns for the month of August can now be filed by October 10," Finance Minister Piyush Goyal tweeted.

The deadline for Form GSTR-1 (sales return) for the quarter July to September has been extended to November 15 for taxpayers having a turnover up to Rs 1.5 crore, the Finance Ministry said in a release.

For those with turnover above Rs 1.5 crore, the Form GSTR-1 has to be filed by October 5 for the month of July and October 10 for the month of August.

The Finance Ministry has also exempted the relief material coming from foreign countries for distribution in flood-ravaged Kerala from the customs duty and the GST.

"The government is committed to help Kerala in this time of devastation. We have made all the relief materials coming from foreign countries for the Kerala flood relief exempt from customs duty as well as GST," Goyal told reporters here.

The government also extended the last date for filing GST summary sales returns or Form GSTR-3B for the month of July to August 24 for all classes of taxpayers.

"In order to facilitate filing of easy GST returns, the government has extended the due date of filing GSTR-3B return to August 24, 2018. We are committed to ensuring that GST is a Good and Simple Tax," the Minister said in another tweet.

 

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Bengaluru: The Vartha Bharati–Sankalp election analysis has shown a high level of accuracy in predicting the outcome of the recent Karnataka Assembly by-elections held in May 2026, correctly calling winners in both constituencies and closely estimating vote share trends.

The by-elections were held in Bagalkot and Davanagere South, drawing significant political attention as both seats were seen as key tests for the ruling Congress and opposition BJP.

According to the analysis, Vartha Bharati–Sankalp had made three major projections ahead of the results the winning party, vote share percentages, and margin of victory.

In both constituencies, the platform accurately predicted that the Congress would emerge victorious. The outcome matched the projections, with Congress candidates winning in Bagalkot and Davanagere South.

In terms of vote share, the predictions were largely in line with the final results. In Bagalkot, the BJP’s vote share was forecast in the range of 40 to 46 per cent, while the actual figure stood at 42.9 per cent. The Congress vote share, however, exceeded expectations, with the party securing 55.4 per cent against a projected range of 43 to 48 per cent.

The margin of victory in Bagalkot turned out to be significantly higher than anticipated. While the projection had placed the margin between 2,000 and 3,500 votes, the final margin was around 22,332 votes.

In Davanagere South, the predictions also remained largely accurate. The Congress vote share was projected between 43 and 51 per cent, and the final figure stood at 43.9 per cent. The BJP was expected to secure between 42 and 50 per cent but ended with 40.3 per cent.

The analysis had also identified the role of SDPI as a potential spoiler in the constituency. While its vote share was estimated around 6 per cent, the party eventually secured around 12 per cent of the vote.

The margin of victory in Davanagere South was predicted to be between 1,500 and 2,600 votes. The actual margin was higher at around 5,708 votes, though the contest remained relatively close as anticipated.

Overall, the performance of Vartha Bharati–Sankalp stood out for correctly identifying the winning parties in both seats and maintaining close accuracy in vote share estimates, with only limited deviations in specific cases.