Lok Sabha Question No. 2399 (UNSTARRED), answered on 2024-12-10
Subject: Rural Self Employment Training Institute Scheme
Ministry: RURAL DEVELOPMENT
Asked by: Shri Chavda Vinod Lakhamshi

## GOVERNMENT OF INDIA MINISTRY OF RURAL DEVELOPMENT

## DEPARTMENT OF RURAL DEVELOPMENT

## LOK  SABHA

## UNSTARRED QUESTION NO. 2399 ANSWERED ON 10/12/2024

## RURAL SELF EMPLOYMENT TRAINING INSTITUTE SCHEME

2399. SHRI CHAVDA VINOD LAKHAMSHI:

## Will the Minister of RURAL DEVELOPMEN

- (a) whether the Government  is implementing the Rural Self Employment  Training  Institutes  (RSETI)  Scheme  as  a  subscheme of National Rural Livelihood Mission (NRLM) in Gujarat, particularly  in  the  districts  of  Bhuj,  Abdasa,  Gandhidham, Rapar,  Mandvi  and  Anjar  of  Kutch  LokSabha  Constituency,  if so, the details thereof;
- (b) whether  skill  and  entrepreneurship  development  training  is being provided free of cost to rural poor youth, if so, the details thereof; and
- (c) whether the principles of social inclusion have been adequately observed keeping in view the welfare of marginalised sections, particularly SC, OBC and tribal youth, if so, the details thereof and if not, the reasons therefor?

## ANSWER

## MINISTER OF STATE IN THE MINISTRY OF RURAL DEVELOPMENT (SHRI KAMLESH PASWAN)

(a)  to  (c):      Yes.  Government  is  implementing  the  Rural  Self Employment Training Institute (RSETI) scheme as a sub-scheme of National Rural Livelihood Mission (NRLM)  across the country including  Kutch  District  of  Gujarat.  The  RSETI  Kachchh/  Kutch (Bhuj) covers Bhuj,  Abdasa,  Gandhidham,  Rapar,  Mandvi  and  Anjar of  Kutch  LokSabha  Constituency. The RSETI  provides free of cost skill and entrepreneurship development training to rural poor youth.  The  details  of  Scheduled  Castes  (SCs),  Other  Backward Classes (OBCs) and Tribal youths trained and settled since 2014-15 till  2024-25  (upto  October  2024) under  RSETI  in  Bhuj,  Abdasa,

Gandhidham, Rapar, Mandvi and Anjar of Kutch LokSabha Constituency are given as below:

| Category                  | Category                                          | SC   | SC      | OBC   | OBC   | ST   | ST   |
|---------------------------|---------------------------------------------------|------|---------|-------|-------|------|------|
| Financial Year 2014-15    | TrainedSettledTrainedSettledTrainedSettled 350 79 | 183  |         |       | 79    | 44   | 9    |
| 2015-16                   | 209                                               |      | 97      | 271   | 46    | 38   | 12   |
| 2016-17                   | 353                                               |      | 217     | 130   | 225*  | 13   | 66*  |
| 2017-18                   | 196                                               | 416* | 121     | 214*  |       | 6    | 27*  |
| 2018-19 2019-20           | 292                                               | 199  | 109 182 | 76 38 | 0     | 4    | 1* 0 |
| 2020-21                   | 231                                               | 83   |         | 85    |       |      |      |
| 2021-22                   | 145                                               | 157* | 126     |       |       | 1    | 2*   |
| 2022-23                   | 264                                               | 175  | 129     | 125   |       | 0    | 3*   |
|                           | 326                                               | 190  | 248     | 107   | 1     |      | 1    |
| 2023-24                   | 340                                               | 208  | 185     | 164   | 2     |      | 0    |
| 2024-25 (up to Oct. 2024) | 245                                               | 94   | 210     | 62    | 0     |      | 0    |

*  The  data  include  the  candidates  of  the  previous  year  also. Hence settled data is more than the trained data

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