impact evaluation of prime minister's employment generation program

7/25/2019 Impact Evaluation of Prime Minister's Employment Generation Program

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Summer Training Program 2014

Reserve Bank of India, Delhi

IMPACT ASSESSMENT OF PMEGP

DHRUV JAIN

RURAL PLANNING AND CREDIT DEPARTMENT

RESERVE BANK OF INDIA, DELHI


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ACKNOWLEDGEMENT

2

I would like to convey my gratefulness to the Regional Director Mr. Deepak Singhal,

Reserve Bank of India-Delhi, for giving me the opportunity to work on this project. The

skills and knowledge which I have gained throughout my practical training I perceive as

very valuable component in my future career development.

I take this opportunity to express my profound gratitude and deep regards to my mentor,

Mr. Sunil Jolly for his exemplary guidance, monitoring and constant encouragement

throughout the course of this project. The blessing, help and guidance given by him from

time to time shall carry me a long way in the journey of life on which I am about to

embark. Also a special word of thanks to Ms. Vandana Maheshwari , for her valuable

comments, suggestions and direction.

My thanks and appreciation to the HR staff mainly Mr. Tarun Chandra for being willing to

help us throughout the course of my training.

I am thankful to all the respondents for their time, information and cooperation.

I would also like to thank the following people for their constant support and time.

Mr. Vijay Khanduja (LDM, Canara Bank)

Mr. Debashish Ganguli (Bank of Baroda)

Mr. Dushyant Dash (LDM, Canara Bank)

Mr. Mohanty (AGM, PNB)

Mr. Raj Kumar Kalra, (LDM Office, PNB)

Lastly, I thank the almighty, my family and friends for their constant encouragement

without which this assignment would not be possible.

Dhruv JainDelhi School of Economics


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EXECUTIVE SUMMARY

3

The following report is based on a study conducted in Delhi to gauge the impact of the

government sponsored scheme PMEGP on its beneficiaries. It encourages self

employment ventures, especially among traditional artisans and unemployed youth,

relating to manufacturing and service sector by providing them credit linked subsidy.

A sample of 35 projects was drawn from the list of beneficiaries given loan in 2012-13 and

results were drawn based on this random sample. The impact of the scheme is evaluated

based on different aspects of development: economic, financial and social.

The key findings of the study are as follows-

1) Employment Generated

In the sample of 35 projects, the total employment generation is 85 and the

average employment per project is 2.57

22 are New Projects, suggesting that the scheme promotes

Entrepreneurship.

2) Migration

86% of the interviewed beneficiaries are Non Migrants.

Even the Migrants in the sample came long before the scheme was

introduced. Thus we cannot say that the scheme catalyses Migration.

3)

Income Generation

One unit of subsidy increases the annual income by four times.

This is irrespective of the category of the beneficiaries. The impact of

education, years of experience and training is statistically insignificant even

if the coefficients have correct signs.

4) Targeting, Access and Reliance

17% of the projects are run by previously unemployed youth. There is no

rationing based on category of the applicant. The average score to the reliability of the scheme as a source of employment

generation, as per the self-reporting of the interviewees, is 8.2

5) Social Mobility

Social Mobility is slow in the short run because the respondents have

prioritized re-capitalizing of the business over immediate consumerism.

However, it will gain momentum in the long run.


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TABLE OF CONTENTS

4

S No. Topics Page No.

1. Overview of the Scheme-PMEGP 5

2. Objective of the Study 9

3. Methodology 10

4. Descriptive Statistics 12

5. Econometric Analysis of the Sample 14

6. Impact on Income 16

7. Impact on Financial Inclusion 18

8. Impact on Social Mobility 19

9. Case Studies 20

10. Insights from Self Reporting 24

11. Issues Identified under PMEGP 25

12. Conclusion 29

13. Appendix A- Questionnaire 30

14. Appendix B- Self Reporting 32

15. Appendix C- Asset Index 33

16. Appendix D- Status of PMEGP (2012-14) 34

17. Appendix E- Sample 38

18. Bibliography 39


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OVERVIEW OF THE SCHEME-PMEGP

5

Figure 1

Prime Ministers Employment Generation Programme (PMEGP) is a credit linked

subsidy programme which was introduced by the Government of India (by merging two

schemes operational till 31.03.2008 - Prime Ministers Rojgar Yojana (PMRY) and Rural

Employment Generation Programme (REGP)) for generation of employment

opportunities through establishment of micro enterprises in rural as well as urban areas.

PMEGP will be a central sector scheme to be administered by the Ministry of Micro, Smalland Medium Enterprises (MoMSME). The Scheme will be implemented by Khadi and

Village Industries Commission (KVIC), a statutory organization under the administrative

control of the Ministry of MSME as the single nodal agency at the National level. At the

State level, the Scheme will be implemented through State KVIC Directorates, State Khadi

and Village Industries Boards (KVIBs) and District Industries Centres (DICs) and banks.

The Government subsidy under the Scheme will be routed by KVIC through the identified

Banks for eventual distribution to the beneficiaries / entrepreneurs in their Bank

accounts. The Implementing Agencies, namely KVIC, KVIBs and DICs will associate

reputed Non Government Organization (NGOs)/reputed autonomous institutions/SelfHelp Groups (SHGs) and other relevant bodies in the implementation of the Scheme,

especially in the area of identification of beneficiaries, of area specific viable projects, and

providing training in entrepreneurship development.

Figure 2

PrimeMinister's

Rojgar Yojana

RuralEmploymentGenerationProgramme

PrimeMinister's

Employment

GenerationProgramme

Ministry ofMSME

State KVICDirectorates

State Khadi andVillage Industries

Boards

DistrictIndustries

Centres

Khadi and VillageIndustries

Commission


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6

Objective of the Scheme-

1. To generate employment opportunities in rural as well as urban areas of the

country through setting up of new self-employment ventures/ projects/ microenterprises.

2. Bringing together widely dispersed traditional artisans/ rural and urban

unemployed youth and giving them continuous and sustainable self-employment

opportunities to the extent possible, at their place to arrest migration.

3. To increase the wage earning capacity of artisans and contribute to increase in the

growth rate of rural and urban employment.

Quantum and Nature of Financial Assistance-

Categories of beneficiaries under

PMEGP

Beneficiarys

contribution

(of project cost)

Rate of Subsidy (of project cost)

Area (location of project/unit) Urban Rural

General Category 10% 15% 25%

Special (including SC / ST / OBC

/Minorities/Women, Ex-servicemen,

Physically handicapped, NER, Hill and

Border areas etc.

05% 25% 35%

Table 1

Note: (1) The maximum cost of the project/unit admissible under manufacturing sector is Rs.25 lakh.

(2) The maximum cost of the project/unit admissible under business/service sector is Rs.10 lakh.

(3) The balance amount of the total project cost will be provided by Banks as term loan

Eligibility Conditions of Beneficiaries-

1.

Any individual, above 18 years of age2. There will be no income ceiling for assistance for setting up projects under PMEGP.

3. Assistance under the Scheme is available only for new projects sanctioned

specifically under the PMEGP.

4. Self Help Groups, Charitable Trusts, Production Co-operative Societies and

Institutions registered under Societies Registration Act,1860 are also eligible for

assistance under PMEGP.

5. Existing Units (under PMRY, REGP or any other scheme of Government of India or

State Government) and the units that have already availed Government Subsidy


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7

under any other scheme of Government of India or State Government are not

eligible.

Identification of beneficiaries-

The identification of beneficiaries will be done at the district level by a Task Force

consisting of representatives from KVIC/State KVIB and State DICs and Banks. The Task

force would be headed by the District Magistrate / Deputy Commissioner / Collector

concerned. The Bankers should be involved right from the beginning to ensure that

bunching of applications is avoided. However, the applicants, who have already

undergone training of at least 2 weeks under Entrepreneurship Development Programme

(EDP) / Skill Development Programme (SDP) / Entrepreneurship cum Skill Development

Programme (ESDP) or Vocational Training (VT) will be allowed to submit applications

directly to Banks. However, the Banks will refer the application to the Task Force for its

consideration. Exaggeration in the cost of the project with a view 6 only to availing higher

amount of subsidy should not be allowed. KVIC will devise a score card in consultation

with SBI and RBI, and forward it to the District Level Task Force and other State/District

functionaries. This score board will form the basis for the selection of beneficiaries. This

score card will also be displayed on the websites of KVIC and Ministry. The selection

process should be through a transparent, objective and fair process.

Bank Finance-

1. The Bank will sanction 90% of the project cost in case of General Category of

beneficiary/institution and 95% in case of special category of the

beneficiary/institution, and disburse full amount suitably for setting up of the

project.

2. Bank will finance Capital Expenditure in the form of Term Loan and Working

Capital in the form of cash credit. Project can also be financed by the Bank in the

form of Composite Loan consisting of Capital Expenditure and Working Capital.

The amount of Bank Credit will be ranging between 60-75% of the total project

cost after deducting 15-35% of margin money (subsidy) and owners contribution

of 10% from beneficiaries belonging to general category and 5% from beneficiaries

belonging to special categories. This scheme will thus require enhanced allocations

and sanction of loans from participating banks. This is expected to be achieved as

Reserve Bank of India (RBI) has already issued guidelines to the Public Sector

Banks to ensure 20 % year to year growth in credit to MSME Sector.

3. Though Banks will claim Margin Money (subsidy) on the basis of projections of

Capital Expenditure in the project report and sanction thereof, Margin Money

(subsidy) on the actual availment of Capital Expenditure only will be retained and


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excess, if any, will be refunded to KVIC, immediately after the project is ready for

commencement of production.

4. Working Capital component should be utilized in such a way that at one point of

stage it touches 100% limit of Cash Credit within three years of lock in period ofMargin Money and not less than 75% utilization of the sanctioned limit. If it does

not touch aforesaid limit, proportionate amount of the Margin Money (subsidy) is

to be recovered by the Bank/Financial Institution and refunded to the KVIC at the

end of the third year.

5. Rate of interest and repayment schedule

Normal rate of interest shall be charged. Repayment schedule may range between

3 to 7 years after an initial moratorium as may be prescribed by the concerned

bank/financial institution. It has been observed that banks have been routinely

insisting on credit guarantee coverage irrespective of the merits of the proposal.This approach needs to be discouraged.

Negative List of Projects

1. Any industry/business connected with Meat(slaughtered),i.e. processing, canning

and/or serving items made of it as food, production/manufacturing or sale of

intoxicant items like Beedi/Pan/ Cigar/Cigarette etc., any Hotel or Dhaba or sales

outlet serving liquor, preparation/producing tobacco as raw materials, tapping of

toddy for sale.

2.

Any industry/business connected with cultivation of crops/ plantation like Tea,

Coffee, Rubber etc. sericulture (Cocoon rearing), Horticulture, Floriculture, Animal

Husbandry like Pisciculture, Piggery, Poultry, Harvester machines etc.

3. Manufacturing of Polythene carry bags of less than 20 microns thickness and

manufacture of carry bags or containers made of recycled plastic for storing,

carrying, dispensing or packaging of food stuff and any other item which causes

environmental problems.

4. Industries such as processing of Pashmina Wool and such other products like hand

spinning and hand weaving, taking advantage of Khadi Programme under the

purview of Certification Rules and availing sales rebate.5. Rural Transport (Except Auto Rickshaw in Andaman & Nicobar Islands, House

Boat, Shikara & Tourist Boats in J&K and Cycle Rickshaw.


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OBJECTIVE OF THE STUDY

9

The study aims to evaluate the impact of PMEGPon its beneficiaries. The objective of the

scheme is to generate employment especially for unemployed youth and traditional

artisans and help provide them with a reliable and sustainable source of income. In this

study I intend to gauge the impact of this scheme on both economic and social

parameters.

The dual objectives of an employment generation scheme are those of poverty reduction

and arresting migration. The concept of poverty1 is broader than merely income.

According to Amartya Sen, freedom is the primary goal of development; freedom is also

the principal means of development. It is the enhancement of freedoms that allow people

to lead lives that they have reason to live (Sen, 1999). Development is the process of

expanding human freedom. It also means the removal of major sources of lack of freedoms

such as poverty, all types of discrimination and inequalities, neglect of public facilities,lack of economic opportunities, social exclusion, state policies that limit freedom and so

on. Thus employment generation coincides with the objective of enhancing freedom and

choices. Also rural to urban migration leads to spatial inefficiencies (Wang, 2005) which

has policy implications. Thus arresting migration becomes of paramount importance.

Keeping this in mind, I evaluate the performance of the scheme based on the following

broad concepts:

(i) Employment Generation

(ii)

Expansion of Income Generation Capability(iii) Standard of Living

(iv) Financial Inclusion (inclusion in the banking structure- savings and investment

choices)

(v) Effect on Migration

(vi) Social Mobility (education, housing and health)

(vii) Targeting

(viii) Rationing (gender, caste, income)

1See Sens Capability Approach and Social Justice
http://www.fas.harvard.edu/~phildept/sen.htmlhttp://www.fas.harvard.edu/~phildept/sen.htmlhttp://www.fas.harvard.edu/~phildept/sen.html


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METHODOLOGY

10

In this section, I describe the methodology used to evaluate the impact of PMEGP which

aims to expand the capabilities2via employment generation. The steps followed for this

evaluation as depicted in the following flowchart.

Figure 3

STEP 1: Review of the Scheme and stating the Maintained Hypothesis

The first step towards an impact evaluation is the review of the theory and existing data if

any. This includes studying the scheme, master circulars on the topic (Circular, 2008)3,

performance reports by the various authorities4etc. Based on the objective of the scheme

I calibrated the various parameters5on which the scheme should be evaluated. Keeping in

mind the economic theory, I proposed the maintained hypothesis on the relationship

between the key dependent variables and the various explanatory variables which are

part of the study. This will be covered more extensively in the section on Econometric

Analysis.

2Senscapability approach is a moral framework. It proposes that social arrangements should be primarilyevaluated according to the extent of freedom people have to promote or achieve functionings they value.3(Circular, 2008) RBI/2008-09/211RPCD.PLNFS.BC. No.41 /09.04.01/2008-2009

4Performance reports can be accessed fromhttp://www.kviconline.gov.in/pmegp/pmegpweb5Refer the Objective section.
http://www.kviconline.gov.in/pmegp/pmegpwebhttp://www.kviconline.gov.in/pmegp/pmegpweb


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METHODOLOGY

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STEP 2: Collection of Data using a uniform recall period

Preparation of the Questionnaire: After studying what the scheme is all about andwhat are its objectives, we move onto the preparation of the set of questions we

would like to know to be able to evaluate the impact of the scheme on the

beneficiaries. This is again a decisive step as this is the stage where we define what

would be the data well get to analyze. A comprehensive questionnaire6 enables

one to make accurate judgments. We used a uniform recall period for both

economic and social parameters. This uniform recall period is one of pre scheme

regime and post scheme regime(1 year after the project was started)7. I have also

prepared a Self-Reporting form8which records the ratings of the respondents on

various administrative issues related to the scheme.

Routine gathering of data and statistics: This step includes two sub-steps. There

are two types of data that needs to be collected.

o Contact Details of the Beneficiaries- This involved contacting the KVIC office/

Circle Offices of Punjab National Bank, Bank of Baroda, Canara Bank. After

obtaining the contact details, a random sampling was done to pick out

households scattered all over Delhi so that the sample is more representative.

The data received was for the year of 2012-2013.

o Conducting Surveys- This involved visiting the beneficiaries, either their homes

or workplace and getting their response on the questionnaire. Respondents for

whom we did not have the addresses, were contacted telephonically and theirresponses were registered via telephonic interviews9.

STEP 3: Data Analysis

Based on the surveys conducted, the data was then analyzed in two ways.

(i) Subjective Analysis- In this section, different cases as observed during the field

visits have been summarized based on their individual experiences. It gives us a

micro view of the success/ failure of the scheme under consideration.

(ii) Econometric Analysis- In this section, quantitative analysis of the data is done.

All the cases are analyzed together to give a macro view of the impact of thescheme i.e. what has been the impact of the scheme on an overall basis. For this

purpose STATA 12is used. I have assumed that there are no time fixed effects.

6 Refer Appendix A for the complete questionnaire7 This is done to avoid differences in growth rates observed for two beneficiaries, mainly on account of

greater business-running time.8 Refer Appendix B for the Self Reporting Form9 Some researchers argue that telephonic interviews are better than face to face interviews because of

minimum interviewee bias, low hawthorne effect and greater efficiency.


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DESCRIPTIVE STATISTICS

12

A random sample of 35 projects/ beneficiaries was taken from the list of those who were

disbursed loans under PMEGP in 2012-13 period. The sample was drawn such that it

consists of beneficiaries from across all the districts of Delhi (keeping in mind the rural

areas as well) and across banks so that it is a representative sample. I have also kept inmind the ratio of male to female applicants and proportions of various categories in the

population data while selecting the sample. This section gives the descriptive statistics of

the sample taken.

1. The average incomeearned before the loan is taken is 0.93 Lacs per annum.

2. The average income earned after the loan is taken is 4.5 Lacs per annum.

An increase in the average income earned is a crude indicator of the income

augmenting effectof the scheme.

3. The average loan amount is 5.4 Lacs.

4.

The average subsidy received is 1.2 Lacs.

5. The average education of the applicants in the sample is 11 years.

6. The proportion of females in the sample is 37% which is close to the population

figure of 32% for the year 2012-13.

7. The profile of respondents based on the category is as following:

Figure 4

8. Majority of the applicants (69%) took loan to start a new project. This suggests

that the scheme promotes entrepreneurship and provides self employment

opportunity. However we do find few respondents (31%) who took the loan to

expand their already existing project. This is against the guidelines of the scheme

as it is strictly stipulated that all sanctions will be given for New Projects.

9. Majority of the loans are taken for manufacturing purposes.


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DESCRIPTIVE STATISTICS

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10.The proportion of migrants in the sample is 14% suggesting that the most of the

beneficiaries are residents of Delhi and that the scheme cannot be attributed to as

a cause of migration because even the migrants in the sample were those who

came years ago even before the scheme was introduced.

Figure 5

11. The majority of the respondents have undertaken projects that are providing them

with a regular source of income. This coincides with the objective of the scheme in

promoting ventures that provide a sustainable and continuous source of income.

Only projects like beauty parlors, boutiques, cyber caf etc which are prone to

unforeseen demand fluctuations10 or projects that involve supply side seasonal

restrictions, show a boom bust revenue cycles.

Figure 6

12. The average employment generated per project is 2.52 which is way below the

target of 8 person per project as set by the KVIC for the year 2012-13.

10 This can be due to increase in competition or lack of innovation in services. Also technological innovation

and easy access to internet facilities in the smart phones have made projects like cyber cafs non viable.


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ECONOMETRIC ANALYSIS OF THE SAMPLE

14

I begin the econometric analysis of the impact evaluation by stating our identification

strategy. I have used a uniform recall period to record the income in the pre scheme

regime and post scheme regime (one year after the disbursement). Since this is a

sufficiently narrow time frame, any change in the growth of income can be safely assumedto be a result of the income augmenting effectof the scheme.

We now look at the theoretical aspects of the impact of a credit linked subsidy. Firstly, if

we believe that the scheme leads to an expansion of income generation frontier, the

change in income as a result of this intervention should be positively related to the

amount of subsidy granted. Secondly, income before the intervention and income after the

intervention should be positively related. This is because, income before the scheme is a

proxy variable for the motivation of the beneficiary, which otherwise cannot be measured.

Economic theory postulated that economic agents would like to maintain a minimum

standard of living and this is usually rigid downwards. Thus people with higher income

before the scheme can be assumed to be as likely (if not more) as people previously

unemployed, to well utilize their funds in order to achieve the desired objective. I have

also constructed an asset index11to determine whether the subsidy leads to any upward

social mobility. If the scheme is indeed having a positive impact in all aspects of the lives

of the beneficiaries then it might as well get captured in upward social mobility and access

to good quality health, education and housing facilities. It is at this stage that I point out

the shortcoming of this analysis which is the lack of data on the beneficiaries12with the

authorities.

We estimate the following Regression equations-

1)INCA=+1INCB+2Subs+3D1+4D2+5D3+6 Edu+

2)=+1Subs+2D1+3D2+4D3+5 Edu+

3)=+1Subs+2D1+3D2+4D3+5 Edu+

: Change in Income D1: Category Dummy D2 : Training Dummy

: Asset-Index D3 : Purpose Dummy Edu: Years of Education

Subs: Subsidy INCA: Income After INCB: Income Before

11Refer Appendix C for the construction of the Asset Index12Banks delete the details of those beneficiaries whose loan has been repaid. For our purpose this data was

extremely important because it would have given us sufficiently broad data frame. However, any limitations

in this context are only because of lack of proper data storage and management on behalf of the authorities.


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ECONOMETRIC ANALYSIS OF THE SAMPLE

15

The following table presents our Maintained Hypothesis (Gujarati, 5th edition)13on the

key relationships between our dependent variables14 and the various explanatory

variables15.

Variable Expected Sign

of Coefficient

(Reg1)

Expected Sign

of Coefficient

(Reg2)

Expected Sign

of Coefficient

(Reg3)

INCB Positive . .

Subs Positive Positive Positive

Edu Positive Positive No Relation

D1

No Relation No Relation No Relation

D2

Positive Positive No Relation

D3

Negative* Negative* No Relation

Table 2

* Since the omitted category is Expansion

Ideally, we are likely to expect a positive relationship between the amount of subsidy and

income after the scheme otherwise the objective of the scheme fails. We may also expect a

positive impact of education level on the income after the scheme/change in income,

because higher education signals a better ability to plan the project, internalizing any

exogenous factors related to the business. We also expect an upward social mobility with

increase in the amount of subsidy via expansion of income generation frontier.

13Hypothesis about the causal relationship that is theoretically true.14 Variables on the left hand side of the regression equation. They are function(s) of the outcomes of an

intervention.15Variables used to explain an intervention or causal relationship.


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IMPACT ON INCOME

16

1. We use the first regression specification and present the following results.

Table 3

A scatter plot of income before the loan and income after the loan shows that there is a

positive relationship between the two. The above regression results show that a 1 unit

increase in the subsidy granted leads to a 4.14 unit increase in the annual income of the

beneficiary. This is a strong result suggesting that the scheme has a positive income

augmenting effect. The coefficients of income before and subsidy are positive andstatistically significant, in accordance with the theory. The impact of education on income

after the scheme is a perverse result but its coefficient is statistically insignificant. We see

that the category dummies with general as the omitted category have statistically

insignificant coefficients. We did expect training to influence income generation capacity

but the results are contrary. However the coefficient is statistically insignificant.

2. We use the second regression specification and present the following results.

We look at the impact of the subsidy on the change in income as a robustness test for our

evaluation. The scatter plot shows an upward trend between the change in income andsubsidy. This positive relationship indicates that the scheme is successful in augmenting

the income of the beneficiaries.


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IMPACT ON INCOME

17

Figure 7

The following regression (specification 2) shows that 1 unit of subsidy will lead to a 6.3

units of change in income. The change in income measures how quickly the scheme will be

able to create an income augmenting effect. The change in income as a result of the scheme

is not dependent on the level of education suggesting that the effect of the scheme is not

biased in favor of the well educated. No causal relationship is observed between the two.

Even category dummies have statistically insignificant coefficients.

Table 4


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IMPACT ON FINANCIAL INCLUSION

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Financial Inclusion (Rangarajan, 2006) is defined as the process of ensuring access to

financial services and timely and adequate credit where needed by vulnerable groups

such as weaker sections and low income groups at an affordable cost.

In arriving at the impact in a broader sense, we look at aspects of the scheme that has

promoted financial inclusion. The banks necessitate the beneficiaries to open an account

with them, if they dont have one.

We can see the number of savings accounts have gone up indicating greater access to

banking facilities to those who otherwise did not have an account previously. However

one must exercise caution at this point. Merely the opening of accounts, in no way implies

that people have started to save more. On the contrary, the respondents claimed that their

savings are low and in some cases zero because of increased expenses, inflation and need

for constant re-capitalization of the business. Financial investments like FDs, LICs, and

Mutual Funds are very uncommon among the surveyed beneficiaries. This observation isnot surprising, given our narrow data frame because many businesses have a long

gestation periods before there is any substantial saving. Moreover, education level and

financial literacy play an important role in shaping the savings behavior of the individual.

To conclude, it can be said that no major achievement towards financial inclusion has

been seen suggesting that concerted efforts need to be taken to achieve this goal.

Pre Scheme Post scheme

Savings Acc 25 33

Financial Investment 3 9

0

5

10

15

20

25

30

35

No.ofApplicants

Figure 8


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IMPACT ON SOCIAL MOBILITY

19

Social mobility is defined as movement of individuals, families, households, or other

categories of people within or between layers or tiers in anopen system of social

stratification16. The movement can be in a downwardor upwarddirection. A positive

impact of the scheme will be reflected in upward social mobility. I have measured thisusing a uniform recall period to collect data on various parameters like health services,

education of children, housing, and durable goods that reflect the standard of living.

I also constructed an Asset Index17to see the relative change in the standard of living with

respect to the pre intervention regime.

The results on social mobility are in tandem with the economic theory. The theory claims

that while social mobility is slow in the short run, it will catch up in the long run under the

conditions of a sustainable income generation. The sample data suggest that the social

mobility is slow. This is attributed to the narrow data frame of the study. The respondentswere more interested in recapitalizing their business and investing their savings in their

business and not indulge in immediate consumerism. Theory suggests that it takes a

reasonable amount of time before people move to the higher rung of the social strata.

Demand for health services (private/public) are subject to individual preferences. In our

sample not much switch has been observed from public to private. Housing is another big

investment and we have not seen any change (from rented to own) in the sample. These

results should be dealt with caution. It is only over time that any conclusions can be made.

If anything, the schemes positive impact on expanding the income generation frontier will

be instrumental in bringing about a change in the long run. We do observe more volatility

in the education of the children. In the sample many respondents have moved to private

education for their children after an increase in their income due to the scheme. This is

more evident for boys and suggests a female bias. The most volatile component of social

mobility is the standard of living as mimicked by consumer durables like television,

washing machine, laptop etc and wealth (car, real estate etc). The assets index captures

this volatility by dividing the consumer durables into two categories- fast moving and

medium moving assets and including change in wealth which is moves slowly. The sample

suggests that the movement on average is extremely sluggish. From the estimation of the

third regression equation we are able to conclude that the relationship between social

mobility and amount of subsidy is very weak and there does not appear to be a significantcausal effect.

16Open stratification systems are those in which at least some value is given to theachieved status characteristics in a

society.

17Refer Appendix C for the construction of the Asset Index
http://en.wikipedia.org/wiki/Open_system_(systems_theory)#Social_scienceshttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Achieved_statushttp://en.wikipedia.org/wiki/Achieved_statushttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Social_stratificationhttp://en.wikipedia.org/wiki/Open_system_(systems_theory)#Social_sciences


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CASE STUDIES

20

In this section we present some case studies that brings the diverse experiences of the

beneficiaries. In a credit linked subsidy scheme like PMEGP, it was realized that success or

failure of the projects were subjective based on various factors which differed from case to

case. Thus with the help of the following success and failure stories a glimpse of the

impact of PMEGP on peoples life is described.

Dr. Deepali Bhardwaj, a

dermatologist applied for a

PMEGP loan from Bank of Baroda

in 2011 to buy a machine that

would be used to manufacture

her face packs on a large scale.

Her work her seen a dream run

after the loan. From a humble

income of 50K per month to

around 5 Lacs a month at

present, she exemplifies how far

one can go with a PMEGP loan.

She has seen tremendous change

in her life after this endeavor

succeeded. She talks of how this loan has helped her achieve more financial stability and a

greater appetite to risk in order to achieve her bigger dreams.

Mr. Sunil Kumar, a graduate who previously worked as a computer operator took a

PMEGP loan from Punjab National

Bank in 2012 to manufacture an

electronic chip used in a set top box.

His earnings from his earlier job was

around 8K per month. He now runs

his own business and has employed

6 people under him. His monthly

income is around 35K per month

and this is just the beginning for

him. He feels that with time it going

to get better as he establishes him in

the market. He has not planned any

expensive purchases as yet as he is

keen on recapitalizing his business.


21/39

CASE STUDIES

21

Mrs. Kavita C Raksha took a PMEGP

loan from Punjab National Bank Kalkaji,

to buy an oven for her bakery which she

runs along with her husband. She took aloan of 5 Lacs and now her monthly

income has gone up by 125%. This is a

tremendous change. The couple has

been living a righteous life and believes

that hard work and is their biggest

wealth. Even at a ripe age of 72, they

have been able to make a difference in

their lives just by their spirit. They serve

as a role model for the youngergeneration.

Mr. Pravesh took a PMEGP loan from

Canara Bank in 2012. He was previously

unemployed and decided to start his own

cardboard manufacturing plant. Hereceived 22 Lacs from the bank. His

monthly income from the project is

around 80K in the peak season and 35K

in the slack season. He has been able to

purchase a car from his savings. He feels

that the scheme has helped in achieving

a better standard of living and income.

He also appreciated the trainings and

found them useful to his work. This is

another example to show how the

scheme has promoted entrepreneurship in the youth who were previously unemployed.

Another similar story is that of Mr. Lokesh Kumar, who got the loan form Punjab National

Bank in 2012. He also took the loan for the same reason. Although his manufacturing unit

is also doing well, he complaints that the discrepancy between the expected loan amount

and the actual loan amount led to problems in starting his business in the first place.


22/39

CASE STUDIES

22

Mrs. Babita Bhatt, is a resident of Janakpuri.

She started making her cushions and

bedcovers from her home. In 2012, she took

a PMEGP loan to scale it up. Earlier she couldearn around 15K per month from her work.

After taking up the loan she bought more

machines, hired more labor and even rented

a place to start her project. Now she earns

around 35K per month, which is an

improvement of more than double. She

pointed out the need for contingency funds

as there are phases in the business when

need for immediate funds become vital. Shealso complaints that the amount she got from

the bank was half of what she expected.

Mr. Manoj Kumar took a PMEGP

loan in 2012 to expand his

garment shop. However due tohealth issues, he was unable to

work for a few months. Hence he

could not reap the potential

benefits from his expanded unit,

resulting in unanticipated interest

burden with no substantial

income generation from the new

unit. This led to losses as the

scheme warranted timely interestpayments. Even lump sum

prepayment option that could

have saved him further interest

was not allowed. Thus the scheme proved to be a major liability to the beneficiary.

Although he does feel that the scheme is good for those who are committed to utilize the

funds diligently.


23/39

CASE STUDIES

23

Ms. Radhika, who had been running a beauty parlor in Pitampura for more than 5 years,

took the loan from Canara Bank in 2012 to

scale it up with better products and services

as a conscious effort to attract morecustomers. Even though she invested the loan

money in her parlor with the hope that a re-

launch might give her the required

momentum but as time passed by she found

it increasingly difficult to break even because

of increasing competition from other parlors

in her locality. She cites her lack of planning

and market competition as the major reason

for her failure. This example highlights howsome businesses are prone to a boom-bust

pattern of growth. Contrary to her case is

that of Mrs. Shaheen Parveen, who took the

loan in 2012 for the same reason. She was

previously earning 10K per month. After

successfully re-launching her parlor she saw an increase in her income of about 50%. She

even employs 3 full time workers in her parlor. Here we juxtapose a success story with a

failure just to drive the point that the most important thing that crucially determines the

success of the scheme is individuals plan for his/her project.

Mr. Siraj applied for loan under

PMEGP to open up a cyber cafe.

Since it is not a part of the

negative list it has been

sanctioned by the bank. However,

the bank manager feels that a

cyber cafe wouldnt fetch enough

or to say wont be a successful

venture given the new era of

smart phones which have reduced

the need for a cyber cafe

tremendously. Since the loan has

been sanctioned, the person will now be opening up a cyber cafe which most likely

wouldnt be profitable and thus the loan taken would be futile adding more to the debt

than to his income. Siraj took the PMEGP loan in 2012. Initially he saw regular customers

but with time the numbers have declined. He now faces a slack in his business due to

investment in a venture that now faces a demand crunch.


24/39

INSIGHTS FROM SELF REPORTING

24

In order to compare the overall experience (with the scheme) of the beneficiaries on a

unilinear scale, I drafted a self reporting form18 that allows the respondents the scheme

on various key aspects like loan delivery, time taken in processing, usefulness of the

trainings, reliance of the scheme, income augmenting effect etc.

I present the average ratings19of 35 respondents on the key aspects of the scheme:

Figure 9

The respondents believe that the scheme is well designed and has a strong vision.

They believe that the scheme is reliable and that they can suggest their peers about

the same.

That the scheme is successful in having a positive income augmenting effect is

validated by a high self reporting score of 8.06.

However the area in which the scheme slacks is its effective implementation by the

banks. On an average the respondents suggest that the experience with the banks

can be made more user-friendly.

Processing time is the biggest issue that the respondents have talked about. They

feel that this is the biggest challenge to the effectiveness of the scheme.

Aspects of application process and loan delivery also need improvement.

18Refer Appendix B for self reporting form19On a scale of 0-10, 0 is the lowest score and 10 is best score.


25/39

ISSUES IDENTIFIED UNDER PMEGP

25

1. Issues related to the Banks and KVIC/KVIB

Time Taken in Processing

a)

On an average, the sample data shows that the time taken in processing the

application and disbursement of loan to the beneficiary by the banks has been

very long. The average score to the time taken in processing, as per the self-

reporting of the interviewees, is 4.7 (on a scale of 1 to 10)

b) Some banks have asked the applicants to demonstrate their capability to utilize

the funds well by asking them to show their work place. The problem that the

respondents have pointed out with this is that the rent cost incurred by them is

usually a significant proportion of the loan amount. To elaborate; In the case of

Mr. Sunil Kumar, the bank asked him to show his factory at the time he applied

for the loan. The monthly rent of the factory was 10000. The bank took 3months to disburse his loan by which time he had already spent 30K on the

rent of his factory from which he had not earned a single rupee. He got 3 Lacs

from the bank but had already wasted 10% of this amount on the rent. This is a

significant loss to the beneficiaries since the rent cost is very high and the time

taken in processing usually eats up the scarce capital.

c) Some respondents also point out that the time taken in the process dwindles

the need for the loan amount. Given the competitive nature of many

businesses, time taken is loan delivery is equivalent to lesser probability of

successfully capturing the market because every second loss is the loss of

opportunity to capitalize on the first movers advantage (In oligopolistic

competition players having the first move enjoy higher profits). The more time

it takes in the sanctioning and disbursement more is the likelihood of

somebody replacing you from the industry. Also for those seeking the loan to

expand their already existing projects, this becomes more crucial. If someone

needs to stock up his inventories in a window of 2 months and he gets the loan

in 4 months time, then the need for that money is greatly reduced.

Suggestion- Speedy processing and notification using an online-portal which also

explains the grounds for which loan request is rejected. This saves transportation,rent and time costs of the applicants.

Interest Calculation and Payments

a) A no. of respondents have pointed out that Banks do not clarify the

installments (amount and dates) beforehand. The data collected shows that

while some respondents have faced a progressively decreasing trend in

interest payments, some have continued to pay the same amount for years and


26/39


26

in few cases the interest payments have increased with time. The problem that

people face with this is one of lack of awareness. Those who are less educated

are not aware of the options of interest payments that suit their earning

potential. The banks try to make advantage of this in order to recover it loan intime. Less informed applicants are not able to bargain their convenient interest

payments and are thus distressed with interest burden.

b) Some respondents have pointed out that their interest payments began the

very next month after they took the loan while other have pointed out that the

banks gave them a lee way of 6 months before their first interest payment. This

is surprising and antithetical in principle and practice because those who have

taken the loan are not in a position to face immediate interest burden as all

their capital in invested in fixed assets or working capital.

c)

Also a very common grievance is one of the non availability of Pre -paymentoption. Many respondents have pointed out that the loan locks them down for

a period of 5 years and they are thus unable to borrow from the banks for any

further need of funds. Even if they have the capacity to clear their outstanding

dues before the duration of the loan repayment, the banks do not allow them to

pre pay their dues. In few cases this has resulted in unnecessary borrowings

(for fixed capital) from the moneylenders who charge usurious interest rates.

In case of Mr. Bhim Rao, loan was taken for his namkeen shop. However he

suffered from partial paralysis and hence could no longer work. He wanted to

repay his loan as soon as possible but was not allowed.

d)

In general, respondents are less happy with the way/formula in which interest

is calculated and feel that the banks charge them interest on the entire

principle including the subsidy.

Suggestion- A Uniform Interest Calculation procedure should be followed across

Banks.

Amount of the Sanctioned Loan

a) One of the major issues with PMEGP is one of discrepancy between the

expected loan amount and actual (disbursed) loan amount. The majority ofapplicants have claimed that they applied for higher loan amount and have

received a lower sanctioned amount. This discrepancy has significant negative

impact on the project outcomes and success of the scheme in general. If the

amount applied for, is significantly greater than the actual loan then the

prospects of the success of the project are greatly reduced. For example, in the

case of Mr. Kamal Kumar, the applied amount was 5 Lacs and the sanctioned

amount was 2.5 Lacs. A 50% reduction in the amount will not only lead his


27/39


27

project unviable but also he was not able to purchase working capital at all. As

a result he had to borrow money from the market in order to purchase variable

inputs; an amount on which he has to pay more interest and will not get any

subsidy. While, in the case of Mrs. Satto devi, the sanctioned loan was so belowher expectations that she did not avail of it at all.

b) Respondents feel that the way in which the financial viability of the projects is

done by the authorities is not very sensitive to the ground realities and is very

opaque. They feel that a higher loan amount is imperative to the success of

their project. As I have pointed out in the econometric analysis that there is a

significant positive impact of the amount of subsidy and the income after the

project; we can see that the difference between the two gets captured by the

low rate of growth of income after the loan.

c)

Since the willingness to pay of the borrowers cannot be demonstrated ab-initio, this leads to the honest and hardworking people paying up the price (in

terms of smaller sanctions in related businesses) in lieu of the defaulters. This

is a popular phenomenon called Adverse Selection (Akerlof, 1970)20 and can

only be tackled through a signaling effect21 from the borrower which in this

case is difficult as the loan is an unsecured one.

d) The interviews have lead to the conclusion that the authorities should either

sanction the expected loan amounts or if the deduction is more than 20% of

the expected loan amount, then the loan should not be sanctioned at all. This

hold good only for those applicants who are staring off a new project. This is

necessary because a lower amount will not be successful in generating a

sufficient flow of income given the fact that many businesses have a minimum

gestation period of 3-4 months.

Suggestion- The discrepancy between the expected and the actual loan amount

needs to be evaluated more subjectively keeping in mind the ground realities of

the nature of the project. Creation of a Contingency Funds for a genuine need of

the beneficiary will go a long way in generating stable and successful project.

20 It refers to a market process in which undesired results occur when buyers and sellers have asymmetric

information(access to different information)

21Signaling is the idea that one party (termed theagent) credibly conveys some information about itself to another

party (theprincipal)
http://en.wikipedia.org/wiki/Information_asymmetrieshttp://en.wikipedia.org/wiki/Information_asymmetrieshttp://en.wikipedia.org/wiki/Agent_(law)http://en.wikipedia.org/wiki/Agent_(law)http://en.wikipedia.org/wiki/Agent_(law)http://en.wikipedia.org/wiki/Principal_(commercial_law)http://en.wikipedia.org/wiki/Principal_(commercial_law)http://en.wikipedia.org/wiki/Principal_(commercial_law)http://en.wikipedia.org/wiki/Principal_(commercial_law)http://en.wikipedia.org/wiki/Agent_(law)http://en.wikipedia.org/wiki/Information_asymmetrieshttp://en.wikipedia.org/wiki/Information_asymmetrieshttp://en.wikipedia.org/wiki/Information_asymmetries


28/39


28

2.

Issues related to the Beneficiaries

Lack of Planning

An aspect of PMEGP that merits some attention is the choice of projects that are

sanctioned loans. Since the sanction is done on the basis of a negative list, any

project outside the list becomes eligible for it. For example the proposal of a cyber

caf, although viable will not be very successful given the age of smart phones and

cheap internet access. Also aspects such as unanticipated increase in the market

competition in projects which do not offer any special service is a part of the

repercussions lack of planning involving product differentiation. This is seen very

clearly in projects like Beauty Parlors and Boutiques. Thus it is important to

subjectively assess the projects at the application stage itself and sanction loans

only to those that can stand the test of the market. Otherwise the loan becomes

more of a burden for the borrower or worse an NPA.

Willingness to Pay

Since it is not possible to measure motivation of a borrower; in the wake of an

unsecured loan, the banks face a high possibility of defaults. In the case of Mr. Amit

Yadav, the bank is not able to recover the loan as yet and the person bought a fridge

from the loan money. If we want to tackle such issues we need to ensure that

repayment system is designed in a way that there is no incentive for the borrower

to default. This can be done by giving some bonuses to those who clear their dues

in time. Those who are borrowing for expanding their existing businesses are morelikely to be motivated to utilize the funds well while first time borrowers who want

to start a new project are less likely to be using the funds well.

Propensity to indulge in Risky Ventures

There is a tendency for people to experiment with the loan because of an absence

of effective recovery mechanism. This is called the problem of Moral hazard

(Stiglitz, 1984)22.

22A moral hazard is a situation in which a party is more likely to take risks because the costs that could result will not

be borne by the party taking the risk.


29/39

CONCLUSION

29

In conclusion I would like to say that the Prime Ministers Employment Generation

Programme is indeed a big step towards creating self employment ventures for the

unemployed with focus on the youth and traditional artisans. One of the objectives of the

scheme is to help create sustainable and continuous income flow for the beneficiary. Afterstudying the scheme closely, I come to the conclusion that achievement of this objective is

contingent upon the projects that individuals undertake. Any credit link subsidy is like an

opportunity that provides the initial big pushbut the onus lies on the individual to make

the best use of this opportunity. Thus we can say that the scheme is conceptually designed

in a way to provide the income augmenting effect. The study also finds that the scheme

promotes entrepreneurship and development. The scheme provides the loan to both rural

and urban population in order to arrest migration from the rural to the urban sector.

There is no cause- effect relationship between the scheme and migration. If anything,, the

scheme would inhibit it. The key objective of this scheme is employment generation. I findthat this objective has been under-achieved. The KVICs target for the year 2012-13 was 8

people per project and a total employment target of over 2500. The sample data finds an

average employment per project of only 2.56, which is way below the target. Simple

extrapolation would suggest that the estimates from the population data will be close to

the sample estimates. Thus, either there is a over-ambitious target set by the KVIC or the

loans are being given to the projects without keeping in mind their employment

generation spillover. This issue needs to be solved so that the outcomes are in tandem

with the objective. Another objective was to support artisanship. The sample data was

unable to include them because of the mere absence of such projects in the population

data. The scheme is without any bias towards the weaker sections of the social strata. The

only criterion followed in the sanctioning of the loan is the projects economic and

technical viability. Thus there is equal opportunity for both men and women irrespective

of their category. Although social mobility observed from the sample is slow in the short

run, it can be attributed to the narrow data frame of the study. However, I am hopeful of an

upward social mobility in the long run. Thus the scheme is successful in having a positive

impact by providing the big pushto all the motivated beneficiaries.


30/39

APPENDIX A

30

The following Questionnaire was used for the survey:

FOR THE BENEFICIARY PMEGP

1)

Name:___________________________________________________________________________________

2) Age:_____________________________________________________________________________________

3) Special Category (SC/ST/OBC/PH):_____________________________________________________________

4) Address:_________________________________________________________________________________

________________________________________________________________________________________

5) Contact no.:______________________________________________________________________________

6) Gender: MALE FEMALE

7) Migrant: YES NO If yes, from where________________________________________

8) Reason for Migration_______________________________________________________________________

9) Educational Qualification____________________________________________________________________

10)Technical Qualification:_____________________________________________________________________

11)From where did you come to know about PMEGP-

12)A)Newspaper Ad B)Campaign C)Bank D)Peers E)Broker

F)Other________________

13)How did you get the loan? DIRECT INDIRECT (Any payments involved)

14)Any Training obtained under PMEGP: YES NO

15)Occupation before PMEGP enrolment__________________________________________________________

16)Income before enrolment under PMEGP (Rs. per month):__________________________________________

17)Purpose of Loan- New Project (Previously unemployed) Change of Occupation

Expansion of already existing project

18)Bank from which loan is obtained?____________________________________________________________

19)When did you apply for the Loan?_____________________________________________________________

20)When was the PMEGP loan sanctioned?:_______________________________________________________

21)Amount of loan money received from the bank:__________________________________________________

22)Amount of Subsidy:________________________________________________________________________

23)What was the percentage subsidy you were entitled to under the scheme?____________________________

24)Any collateral offered?______________________________________________________________________

25)Name of the project________________________________________________________________________

26)Nature of Business unit: Manufacturing unit Service Unit Business Unit

27)Type of Project: Individual Project Group Project

28)Nature of Income Flow: Seasonal Regular

29)Income from project (Rs. per month):__________________________________________________________

30)Other Sources of Income(if any):______________________________________________________________

31)Other source of financing for the project YES NO

Source of Finance Tick Percentage

Bank

Relatives

Non-banks/money lenders

Other

32)Any infrastructural support/ tool kits provided______________________________________

33)Do you use your Savings A/c: YES NO

34)Financial Investment: YES NO

35)If yes, nature of investment:___________________________________________________________


31/39

APPENDIX A

31

SOCIAL INDICATORS

35) Marital Status: Married Unmarried Divorced

36) No. of

children(Boys):______________________________(Girls):____________________________

37)Sex of Household Head Male Female

38)

Anything else you want to share(Bottlenecks/Current problem):______________________

S. no. Social Indicators Before PMEGP After PMEGP

1. No. of children vaccinated B: G: B: G:

2. Children going to private school B: G: B: G:

3. Children going to public school B: G: B: G:

4. Own house/ rented

Health Services Public/Govt

Hospital

Private Hospital Local Dispensary Others

Water No water

supply within

500 yards

Community hand

pump/tube/well/bore

well/tank

Community

Tap

Private hand

pump/ tube

well bore/well

Private

piped

Water

Sanitation Open

Defecation

Community Private

Status of

Children in a

Household

Working

Children &

notAttending any

School/

Working Children but

attending School/ NFE/

Children not

working as well

as not attendingany Classes

Children not

working and

attendingSchool

Regularly

Type of Stove Wooden kerosene LPG Coal

Assets Present Baseline Endline

1. Television

2.

Refrigerator

3.

Mobile

4.

Air-cooler

5. Air-conditioner

6. Cycle

7. Scooter/Motorcycle

8. Car

9. Laptop/computer

10. Land in village(acre)

11. Shop/factory


32/39

APPENDIX B

32

The following Self Reporting form was used for the survey:

SELF REPORTING

Name(Optional)___________________________ Scheme____________________________

On a scale of 1-10 Rate the following :

1) Application Process of Scheme 1 2 3 4 5 6 7 8 9 10

2) Loan Delivery 1 2 3 4 5 6 7 8 9 10

3) Experience with the bank 1 2 3 4 5 6 7 8 9 10

4) Time taken in processing 1 2 3 4 5 6 7 8 9 10

5) How helpful was the 1 2 3 4 5 6 7 8 9 10 0

training(if any) ?

6) Were you satisfied with the

amount of loan sanctioned? YES NO

7) How successful is the scheme 1 2 3 4 5 6 7 8 9 10

in increasing your income

8) How reliable do you find 1 2 3 4 5 6 7 8 9 10

this scheme as a means to

increase/support income

generating opportunities?

9) How would you rate the 1 2 3 4 5 6 7 8 9 10

scheme (Overall)?

() ___________________________ ____________________________

1-10 :

1) 1 2 3 4 5 6 7 8 9 10

2) 1 2 3 4 5 6 7 8 9 10

3) 1 2 3 4 5 6 7 8 9 10

4) 1 2 3 4 5 6 7 8 9 10

5) ( )? 1 2 3 4 5 6 7 8 9 10 0

6) ?

7) 1 2 3 4 5 6 7 8 9 10

8) 1 2 3 4 5 6 7 8 9 10

9) 1 2 3 4 5 6 7 8 9 10


33/39

APPENDIX C

33

Construction of the Asset Index

An Asset Index was created to look at the change in standard of living of the PMEGP

beneficiaries.

We classified the consumer durables purchased by the beneficiaries and investments in

fixed capital (like purchase of shop) into 3 categories. These categories are

I. Fast Moving Assets- Television, Refrigerator, Mobile, Cooler

II. Medium Moving Assets-Air Conditioner, Laptop, Motorcycle/Scooter

III. Slow Moving Assets- Car, Purchase of Shop, Renovation/Construction.

Each of these assets are scored on the basis of change in their holding. To be more clear, if

a person did not own a TV before the loan but bought a TV with his increased income in

the post scheme regime, we give him a positive score.

The scoring of various assets are as follows:

i. All fast moving assets are given a score of +1

ii. All medium moving assets are given a score of +2

iii. Renovation/Construction is given a score of +3

iv. Purchase of a new Car is given a score of +5

v. Purchase of Shop/Home/Factory is given a score of +10

After scoring all the assets we construct the Individual asset index by summing the score

of all the assets in that particular asset class (Fast/Medium/Slow)

Once we have constructed the Individual Asset Indexes for the 3 asset classes, we obtain

the final Asset Index as follows:

= Ii /3, where i is the asset class

For Example:

If the Fast Moving Index is 2, the Medium Moving Index is 2 and the Slow Moving Index is

8, then the asset index is (2+2+8)/3=4.


34/39

APPENDIX D

34

Status of PMEGP (2012-14) in Delhi

A. No. of Applications (District wise)

We notice major improvements over the year in the no. of applications from North

West, North and East Delhi. Central and New Delhi have not shown much increase

in volume of applications. South Delhi continues to be the leader in the no. of

applications.

(2012-13) (2013-14)

B. Data on No. of Application/No. of Sanctioned Loans/No. of Disbursed Loans

There has been an increase in the no. of applications over the year implying more

awareness about the scheme but there has not been a significant improvement in

the no. of sanctioned loans. However the no. of disbursed loans has increased

implying that the rejection rate at the level of the Banks has gone down.

Figure 10

0

200

400

600

800

1000

1200

Applications Sanctioned Disbursed

2012-13

2013-14


35/39

APPENDIX D

35

C. Data on No. of Rejected Loans/ No. of Incomplete applications/ No. of loans

returned/ No. of applications with unknown status

While the no. of applications has increased in 2013-14, the rejection rate is higher

for 2013-14 than for 2012-13. Also the no. of returned loans has doubled and can

be attributed to less than expected loan amount sanctioned by the banks.

Figure 11

D.

Gender wise data on No. of Applications/No. of Sanctioned LoansWe see an increase in the no. of applications of both men and women. However the

no of male applicants are considerably higher in both the years vis-a-vis the no. of

female applicants. Also the sanction rate for males is better than for females. This

indicates a better chance of getting the loan for male applicants. Although over the

year the sanction rate for females has improved significantly.

Figure 12

050

100

150200250300350400450500

No. of

rejected

loans

No. of

incomplete

applications

No. of loans

returned

No. of

application

(unknown

status)

2012-13

2013-14

0

200

400

600

800

1000

1200

No. of Male

Applicants

No. of

sanctions

(male)

No. of

Female

applicants

No. of

sanctions

(female)

2013-14

2012-13


36/39

APPENDIX D

36

E. Profile of Applicants based on Category

The majority of applicants belong to General category. SC and OBC applicants are

far behind. ST and PH applications are negligible. Over the year we have seen an

increase in the no. of applications from the General category, while a decline in the

no. of applications of the SC category. This is contrary to the expectations because

the subsidy provided by the scheme is greater for the SC and ST categories.

F. Rationing Based on Category

The no. of sanctioned loans for General category have doubled over the year.However there has not been much improvement of the sanction rate for SC and ST.

Even though sanction rate for the OBCs have tripled but this is because the no. of

applications are low in volume.

No. of

sanctions

(gen)

No. of

sanctions

(SC)

No. of

sanctions

(ST)

No. of

sanctions

(OBC)

No. of

sanctions

(PH)

2012-13 58 14 0 11 1

2013-14 104 18 0 31 1

0

2040

60

80

100

120

Pe

rcentage

Sanctioned Loans


37/39

APPENDIX D

37

G. Performance of PMEGP (official data)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

2 Delhi 160 368.98 1280 13 13 4 4 4 11 8.40 4 2.83 16 2.50 0.77 1.25 0 0.71 2.02

Proj. MM

No.of

Appli.

Recomm

ended

by

DLTFC

No.of

Appli.

Forward

ed to

banks

MM

(Rs.lakhs)

Emp.

(Nos)

No. of

applicat

ions

placed

before

DLTFC

No.of

Appli.

Consid

ered

by

banks

Achievement % to target

EDP

given

No.of Appli.

Sanctioned by

banksAverag

e MM

per

project

(Rs.lakh

)

Estimate

d

average

project

cost

(Rs.lakh)

MM

(Rs.lakh)Employ.

No.of

Proj

NORTH ZONE

Sr.

NOState/Div/UT

Disbursement m ade by

nodal branches

MM

(Rs.lakh)

Empl.

(Nos)

No.of

Proj.

No.of

Proj.

B.E. TARGET-2012-13

No.of

Appli.

Received

KVIC

Appli-

cations

reje-

cted by

Banks

PMEGP- PERFORMANCE -2012-13

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

2 Delhi 161 368.98 1288 832 832 256 159 159 40 26.66 40 26.66 128 24.84 7.23 9.94 28 0.67 1.91

No.of

Proj

MM

(Rs.lakh)

NORTH ZONE

No.of

Appli.

Forwar

ded to

banks MM

No. of

applicat

ions

placed

before

DLTFC

No.of

Appli.

Recom

mended

by

DLTFC

Emp.

(Nos)

B.E. TARGET-2012-13

No.of

Appli.

ReceivedNo.of

Proj.

M. M (Rs.

in lakhs)

Sr.

NOState/Div/UT

Disbursement made by nodal

branchesAchievement % to target

No.of

Proj.

No.of

Appli.

Conside

red by

banksEmpl.

(Nos)

No.of Appli.

Sanctioned by

banks Average

MM per

project

(Rs.lakh

)

Estimat

ed

averag

e

project

cost

(Rs.lak

h)

EDP

givenMM

(Rs.lakh)Proj.

KVIB

Employ.

Appli-

cations

reje-

cted by

Banks

PMEGP- PERFORMANCE -2012-13

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

2 Delhi 321 737.96 2568 845 845 260 163 163 51 35.06 44 29.49 144 13.71 4.00 5.61 28 0.67 1.92 0

PMEGP- PERFORMANCE -2012-13 (As on 26.11.2012 )

No.of

Appli.

Considered

by

banks

B.E. TARGET-2012-13

TOTAL

No.of

Appli.

Forward

ed to

banks

No. of

applicat

ionsplaced

before

DLTFC

No.of

Appli.

Recommende

d by

DLTFC

No.of

Appli.

ReceivedNo.of

Proj.

NORTH ZONE

Disbursement made by

Nodal branches

Proj.Emplo

y.

Average

MM perproject

(Rs.lakh)MM

Sr.NO

Empl.

(Nos)

No.of Appli.

Sanctioned by

banks

EDPgivenM.M (Rs.in

lakhs)

Emp.

(Nos)

State/Div/UT

Appli-

cations

rejectedby

Banks (

in nos)

Estimated

average

project

cost

(Rs.lakh)

Achievement % to

target

No.of

Proj

MM

(Rs.lakh)

No.of

Proj.

MM

(Rs.lakh)


38/39

APPENDIX E

38

The following people were part of the sample for the study selected randomly from the

populationdata (KVIC, 2012-13, 2013-14). Here are some of their details.

Name Category Contact No. Bank Project Knowledge about PMEGP Income After(Rs. Per month)

Jitendra Singh Gen 8802366065 BoB Flour Mill Newspaper Ad 10000

Nawab Ansari OBC 9350779811 BoB Invertor Manufacturing Broker 14500

Manoj Kumar Gen 9212550124 BoB Garment Shop Peers 11000

Bhim Rao ST 8802356317 BoB Namkeen Shop Peers 5000

Parvesh Gen 9873787874 Canara Cardboard Roll Bank 75000

Radhika Gen 9210607133 Canara Radhika Beauty Parlor Bank 6000

Vi nod Kumar Ge n 9312228263 Canara N S Enterpri se s, Pri ntings Campai gn 28000

Ajay Kumar SC 9211232584 Canara P lastic Manufacturing Newspaper Ad 15000

Dheeraj Ladwal SC 9650614252 PNB Websi te designing and Photography Peers 23000

Manoj Kumar Gen 9811750995 PNB Embroidery work Peers 50000Amit Yadav OBC 8860494372 PNB Bought a fridge Peers 7500

Siraj ul Haq OBC 9310523384 PNB Cyber Caf 7000

Srishti Mehta Gen 9899404721 BoB Tea manufacturing and assemblying Newspaper Ad 20000

Rakesh Jain Gen 9210842497 Canara Art and Craft/Soft Toys etc. Peers 23000

Prashant Goel Gen 9212563713 Canara Silver Dora making Newspaper Ad 13000

Dhanesh Raj Gen 9250593233 Canara Hardware, Computer Services Campaign 25000

Arun Dutt Gen 9811327046 Canara Flour Mill Peers 25000

Sunita SC 7827284142 Canara Stitching Work Peers 10000

Geeta Sharma Gen 7503539378 Canara Hosiery, Leggings Newspaper Ad 17500

Kavita C Raksha Gen 8800738990 PNB Bakery Peers 22500

Rizwana Begam SC 8527755464 BoB Shirt and Jeans Making Peers 5500Gaurav Ahuja Gen 8750503880 PNB Service Unit Bank 18000

Pinki SC 9210881249 PNB Stiching Suits Peers 42500

Vi kram Sharma Ge n 9711128182 PNB Compute r Hardware and Software Pe ers 17500

Sushma ST 9871854959 PNB Stiching Suits Campaign 15000

Lokesh Kumar OBC 9810668753 PNB Wooden moulding Peers 60000

Sudesh Rani SC 8287362718 PNB Beauty Parlor Newspaper Ad 22000

Gaurav Bomibatra Gen 8800486510 PNB Printing Press Bank 13000

Shaheen Parveen Gen 9990984618 PNB Beauty Parlor Bank 20000

Suni l Kumar Ge n 9990516159 PNB Wire Maki ng/ El ectronics Newspape r Ad 30000

Sultan Gen 9211337044 PNB Photocopy Shop Newspaper Ad 10000

Kamal Kumar SC 9871184240 PNB Watch Making Newspaper Ad 20000

Babita Bhatt Gen 9990951027 PNB Stitching Work Peers 35000

Deepali Bhardwaj Gen 9560550000 BoB Skin and Hair Clinic Peers 500000

Mahipal Singh SC 8860777270 BoB Shoes Manufacturing ans Sales Newspaper Ad 12000


39/39

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Mechanism. QJE.

Circular, M. (2008). Prime Minister's Employment Generation Programme (PMEGP).

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Gujarati, D. (5th edition). Basic Econometrics.The McGraw Hill.

KVIC. (2012-13, 2013-14). Case Forwadings.

Rangarajan, C. (2006). The committee on Financial Inclusion.

Sen, A. (1999). Development as Freedom.

Stiglitz, J. (1984). Equilibrium unemployment as a worker discipline device.AER.

Wang, J. V. (2005). Aspects of the rural-urban transformation of countries. Journal of

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impact evaluation of prime minister's employment generation program

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