1

factors determining expectations from

the new government after 2014 lok sabha

elections

2

project report

ug 3rd year,

dept. of economics,

jadadavpur university.

PROJECT TEAM-

Kritika Hamirwasia

Sukanya Paul

Madhurima Dutta

Sourabh Saha

Payel Das

Sharoni Goswami

PROJECT MENTOR-

Dr. Ajitava Raychaudhuri

Professor and Coordinator, Centre for Advanced Studies

Dept. of Economics

Jadavpur University

3

abstract

This project deals with factors determining the expectation of

individuals from the new government after 2014 Lok Sabha elections. We

have tried to assess the various factors that influence the expectations on

citizens before casting their votes. We have studied a few articles in

which similar surveys were conducted and have tried to incorporate a

few other things which we have merged into our project. For this purpose

we have prepared a questionnaire in which respondents were asked

about the basic information and questions related to the study that

influence their expectation regarding the new governance.

A regression analysis, using the Software STATA 11, has been used to

derive the results. These results are found to vary with socio-economic

factors, such as, respondents' age, gender, annual family income and

educational qualification. This is the subject matter of the project.

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ACKNOWLEDGEMENTS

This project is a final product of a year-long effort of various individuals. It would

have been impossible for the group to have completed the project without significant

contributions from various people. Hence the project is incomplete without extending

our heartfelt regards and gratitude for the same to all of them.

Firstly, we would like to acknowledge the Department of Economics, Jadavpur

University, the Head of Department- Prof. S. Mitra and all other professors in the

department for giving us the opportunity and exposure of compiling such a study as a

part of the undergraduate programme.

Words are inadequate to express our gratitude to Prof. Ajitava Raychaudhuri

whose vast knowledge and experience were instrumental in our comprehension of the

methodology and analysis of this project. This study would not have been possible

without his immense contribution and patient explanations.

Lastly, we acknowledge the effort and time spared by the respondents to fill in

the questionnaire so as to enable us to gather the data required for the analysis of the

project and attainment of our objectives. We are indebted to them, for without their

co-operation, this project would never have materialized into a reality.

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CONTENTS

INTRODUCTION PAGE:6

REFERENCES AND RELATED STUDIES PAGE:8

DATA COLLECTION AND METHODOLOGY PAGE:11

DATA ANALYSIS AND INFERENCES PAGE:16

CONCLUSION PAGE:36

BIBLIOGRAPHY AND REFERENCES PAGE:39

SPECIMEN QUESTIONNAIRE PAGE:40

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introduction

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The Lok Sabha elections of 2014 was predicted to be a new wave of change in the

political scenario of the country. It was expected to bring with it a new regime of

governance and policies under the umbrella term "Achhe Din" or "Good Days". As

expected, the people of India brought in a new tide of change through their choices and

there was a change in the government after a period of ten years. However, along with

great power, comes great responsibility. Having received an overwhelming majority in

Parliament, the new government is, was and shall probably continue to be under certain

amount of pressure to fulfill promises made to the people. Nonetheless, they will strive

to live up to the expectations of the masses who are the invisible hand behind their

landslide victory.

Governance under different political scenario is one of the primary factors that

influence the socio-economic structure of India. It is one of the most basic building

blocks of the social structure and economic framework of the country during the

minimum five year governance period. Thus a drastic change in the same is not only

followed by major after effects but is also pre-empted by a large number of factors.

The objectives of this project are-

To study the factors that influenced the expectations of individuals from the New

Government elected in 2014 General elections.

To analyze the differences in expectations from the new government of different

people across six regions across the city of Kolkata.

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references

and

related studies

9

Voting is the main form of political participation in liberal democratic societies. From a

sociological perspective, the study of voting behavior focuses primarily on explaining who

votes and how they vote. The analysis of voting patterns invariably dwells upon the

determinants of why people vote as they do and how they arrive at the decisions they make.

Early research pioneered by Paul F. Lazarsfeld and others (1967) concluded that voting

depends primarily on socio-economic factors or people’s location in social systems—their

social class, occupation, gender, race, age, religion, ethnicity, family history of voting behavior

(political socialization) and membership in voluntary associations such as trade unions,

recreational clubs, political parties and civic organizations.

Political scientists have concentrated on the influence of political factors such as issues,

political programmes, electoral campaigns, party loyalty (people’s sense of identification with

particular political parties) and voter’s feelings about particular candidates, etc.

A number of different (not mutually exclusive) approaches (models) have been used to

explain voting behavior. The major approaches may be distinguished as structural, ecological,

social-psychological, rational-choice and radical.

This approach has suggested two main sources of influence which structure political

alignments:

Sectoral cleavages which separate people into groups with different interests and

priorities, e.g., public sector and private sector, and

Dominant ideological messages which are conveyed mainly through the media and

form ‘political consciousnesses’.

SOURCE- Survey by London School of Economics

Accessed on- 1/4/15

The International Foundation for Electoral Systems conducted a poll in Ukraine before

the 2014 elections to find out the opinions of the voters and their expectations from the

various leaders. These included questions on expected government stability(58% expected

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instability), unemployment (50% expected unemployment), poverty(51% expected

poverty),inflation (56% expected inflation) and corruption (47% expected corruption). There

were also questions pertaining to expectation of Ukraine joining EU as well as comparative

expectations of performance of various electoral candidates such as Viktor Yanukovych and

Yulia Tymoshenko.

Source-International Foundation for Electoral Systems

Accessed on- 7/4/2015

Similar polls were conducted about the possibility of having an Obama government in

USA . Nearly two thirds of those questioned in a CNN/ Opinion Research Corp. survey said that

Obama would be able to change the country for the better, 25% saying he wouldn’t be able to

change it at all and 9% indicating that the change would be for the worse. Also, 76% said that

conditions in the country would improve in the following four years with the remaining 24%

saying that it would not be likely.

SOURCE-CNN Opinion Research Corp.

ACCESSED ON- 7/4/15

It should also be noted that opinion polls were conducted about expectations from the

new government after 2014 general elections by organizations like CNN-IBN, who took calls of

voters from across the city to ask their opinions who expressed expectations regarding various

factors including price stability and job opportunities.

SOURCE- CNN IBN

ACCESSED ON- 7/4/15

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data collection

and

methodology

12

Data for this study has been collected from an average of approximately forty five

individuals per region across six regions of Kolkata. The questionnaire for the collection of data

was designed in a manner to capture the factors influencing the votes of individuals for the

2014 elections and expectations from the new governance. It consisted of primary questions

regarding the said individuals as well as specifically directed questions pertaining to the area of

study. The data collection(survey) period extended over two months, from 1st December,2014

to 30th January, 2015. A specimen questionnaire has been attached to this project at the end.

The method used for analyzing this data is ordered probit regression . Ordered probit is

a generalization of the popular probit analysis to the case of more than two outcomes of an

ordinal dependent variable. The respondents were asked to rate each category on a scale of 1

to 5, where 1 denoted the least importance and 5 denoted the highest importance. The levels

1 to 5, which express the degree of importance, are called order of the categorical variable. In

other words, it is not only a categorical variable, but it is also an ordered categorical variable.

Here, we have regressed various independent variables such as annual family income,

gender, number of family members, number of voting members etc on various dependent

variables such as growth & development, decrease in crime rate, rapid construction of

infrastructural facilities, stronger rupee against dollar etc. Thus we have a regression model,

Yi*= β0 + ∑k

j=1 βj xi j + ui

Where yi* is not observed. It is commonly called a “latent” variable. What can be

observed is an ordered variable yi* defined by

Yi = 1 if yi* ≤ ϒ 1

= 2 if ϒ 2 ≤ yi* ≤ ϒ 1

=…..

=5 if yi* ≤ ϒ 4

This can be further illustrated as follows-

Assume Y has more than two ordered categories (for instance, Low, Medium, High)

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FIG 1: CUMULATIVE DENSITY FUNCTION OF THE VARIABLE Y

We now need two cut-points to divide the curve into three sections

Stata will estimate these as µ1 and µ2 by the maximum likelihood procedure

FIG 2: CUT POINTS µ1 AND µ2 MARKED OUT ON THE CURVE

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Interpretations of the various results is as follows-

• If Xi β < µ1 then predict Yi = Low

• If µ1 < Xi β < µ 2 then predict Yi = Medium

• If Xi β > µ 2 then predict Yi = High

FIG 3: GRAPHICAL ILLUSTRATIONS OF THE THREE POSSIBLE RESULTS WHEN THE VALUE OF XI Β LIES IN ONE OF

THE THREE ZONES.

After this, we would like to know the effects of changes in any of the explanatory

variables on the probabilities of any observation belonging to any of the groups. Using the

aforementioned, the probability ordering and log likelihood function are created. Maximizing

the log likelihood, one can estimate the marginal probability in elasticity form for various

probability orders with respect to each of the independent regressors. We do not report the

log likelihood estimators but report the marginal probability elasticities for the lowest

probability, instead of reporting all five probability orderings. All the elasticities are calculated

at the mean values of the concerned explanatory variable. These effects are given by

= βj φ (Zi) for the probit model

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Where Zi = β0 + ∑kj=1 βj xi j

and φ (.) is the density function of the standard normal.

In this project we have however used marginal effect analysis instead of marginal

elasticity analysis, though they are based on similar concepts. Marginal effect shows the

change in probability of giving lowest rank to the dependent variable with respect to change in

the independent variable, that is when independent variable changes by one unit over the

mean value, there is a higher probability of people to lowest rank(rank 1, displaying least

expectation) to the dependent variable if the sign is positive and lower probability of people to

give lowest rank to the dependent variable when the sign is negative.

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data analysis

and

inferences

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This project studied the influence of a number of factors influencing expectations from

the new government in various fields across six regions of Kolkata.

The regions are:

New Alipore

Baranagar

Jadavpur

Jodhpur Park

Bapujinagar

Southern Avenue

The following location dummies are assigned to them:

NEW ALIPORE D1 BARANAGAR D2

JADAVPUR D3 JODHPUR PARK D4

BAPUJINAGAR D5 SOUTHERN AVENUE D6

The independent variables taken into consideration are:

Gender

Age

Education Level

Occupation

Job Character

Number of family members

Number of voting members

Annual family Income

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Possession of Voter ID

Casting of vote in 2014

These independent variables were cardinally measured as follows:

GENDER Female-0, Male-1

AGE Numerically measured in number of years

EDUCATION LEVEL Less than primary education-1, Primary education-2, High school education(class XII)-3, Graduate-4 and Post graduate and higher-5

OCCUPATION Private sector-0, Govt. sector-1 NO. OF FAMILY MEMBERS Numerically measured NO. OF VOTING MEMBERS Numerically measured

ANNUAL FAMILY INCOME Less than 20,000-1; 20,001 to 50,000-2; 50,001 to 1,00,000-3;1,00,001 to 2,00,000-4; 2,00,001 to 5,00,000-5;5,00001 to 10,00,000-6; 10,00,001 to 20,00,001-7; more than 20,00,001-8

POSSESSION OF VOTER ID No- 0, Yes-1 CASTING OF VOTE IN 2014 No- 0, Yes-1

We have studied the expectations from the new 2014 Government in the following

fields. The abbreviations used for them for the remainder of the project are mentioned

alongside:

Growth and Development GD

Larger Job Opportunities LO Stability in Prices SP

Decrease in Crime Rate CR Better Government Health facilities at Cheap Cost

HF

Quality Education at all Levels QE More Schemes for the Elderly ES Fall in Undesirable Delays in Decision DM

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Making

Rapid Construction of Infrastructure (like roads, flyovers, rail networks, ports, power plants, etc)

CI

Better relations with India's Neighbours PR Stronger Rupee against Dollar RD

Less Corruption in the Government CG

ANALYSIS OF MOST IMPORTANT FACTORS AFFECTING THE SURVEY AND A

COMPARATIVE STUDY OF THEIR AVERAGES ACROSS THE SAMPLED AREAS:

MEAN OF INDEPENDENT VARIABLES

NEWALIPORE

BARANAGAR AREA

JADAVPUR AREA

JODHPUR PARK AREA

BAPUJINAGAR AREA

SOUTHERN AVENUE AREA

OVERALL

AGE 33.08 41.97826 27.25641 49.06977 34 45.16667 38.43396

EDUCATION LEVEL

4.02 4.152174 2.74359 4.534884 3.733333 3.809524 3.856604

NO. OF FAMILY MEMBERS

4.74 4.369565 4.153846 3.465116 3.422222 3.904762 4.026415

NO. OF VOTING MEMEBERS

4.22 3.652174 3.794872 2.744186 2.911111 3.166667 3.430189

ANNUAL FAMILY INCOME

5.54 5.021739 4.717949 6.72093 6.177778 5.5 5.622642

TABLE 1 :MEAN VALUES OF VARIABLES ACROSS SIX REGIONS

The table shows the mean values across the sampled regions. The following inferences

can be drawn about the same:

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INFERENCES:

1) The Mean Annual Family Income is the highest in JODHPUR PARK AREA. Therefore,

JODHPUR PARK is the richest area in our survey. According to mean annual income: JODHPUR

PARK>BAPUJINAGAR>NEW ALIPORE>SOUTHERN AVENUE>BARANAGAR>JADAVPUR.As, we

move from Jodhpur Park area to Jadavpur Area, we move from richer regions to lesser rich

regions.

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MAP 1: AVERAGE ANNUAL FAMILY INCOME IN THE SIX REGIONS

2)According to mean Education level: JODHPUR PARK>BARANAGAR>NEW

ALIPORE>SOUTHERN AVENUE>BAPUJINAGAR>JADAVPUR. Therefore, as we move from

JODHPUR PARK to JADAVPUR we move from high educated region to a less educated region.

MAP 2: SHOWING AVERAGE EDUCATION LEVEL IN THE 6 REGIONS

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3)According to mean Age: JODHPUR PARK>SOUTHERN AVENUE> BARANAGAR>

BAPUJINAGAR>NEWALIPORE>JADAVPUR. Therefore, in our sample JODHPUR PARK has more

aged people than the rest and JADAVPUR region has the least mean age in our sample, so

JADAVPUR consists of less aged people.

MAP 3: AVERAGE AGE IN THE 6 REGIONS

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4)According to mean NO. OF VOTING MEMEBERS: NEWALIPORE> JADAVPUR>

BARANAGAR> SOUTHERN AVENUE> BAPUJINAGAR> JODHPUR PARK. In our sample, number of

voting members in a family is more in NEWALIPORE region and least in JODHPUR PARK region.

MAP 4: SHOWING NUMBER OF VOTING MEMBERS IN THE 6 REGIONS

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CORRELATION CO-EFFICIENTS OF THE INDEPENDENT VARIBLES:

The following table shows the co –efficient of correlation between the independent

variables (not location dummies).

gender age status educat~l jobcha~r nooffa~r noofvo~s annual~e voterid vot~2014

gender 1

age 0.0607 1

s tatus -0.3148

-0.5588

1

educationl~l 0.0269 0.3707 -0.2182

1

jobcharacter -

0.2215

-0.108 0.0802 -0.2462 1

nooffamily~r -0.0659

-0.2262

0.4034 0.0051 0.0229 1

noofvoting~s 0.0127 -0.2347

0.4768 -0.0646 -0.0152 0.8243 1

annualfami~e -0.1106

0.0653 -0.0206

0.3926 -0.0045 0.1401 0.0512 1

voterid 0.2454 0.0825 -0.0519

0.1116 -0.1239 0.0951 0.2014 -0.1046 1

votedin2014 0.1163 0.0383 0.0392 -0.076 -0.0366 0.1149 0.1755 -0.2254 0.4274 1

TABLE 2: CORRELATION CO-EFFICIENTS OF THE INDEPENDENT VARIABLES

It suggests that either number of voting members or number of family members be

dropped while running regressions as the high correlation would lead to a problem of multi

collinearity.

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Composition of population in regions based on job characteristic (based

on surveyed individuals)

In D1, individuals in other types of jobs> individuals in business> consultants> individuals in

clerical jobs> consultants> executives> teachers.

In D2, number of teachers> Individuals involved in clerical jobs> individuals involved in

business>executives=consultants>individuals involved in other job forms.

FREQUENCY

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

JOB CHARACTER

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

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In D3, number of individuals in other job forms> number of individuals in business>

executives> teachers> consultants.

In D4, Individuals involved in business> individuals in other business> consultants> teachers>

executives

JOB CHARACTER

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

27

In D5, number of individuals in other job forms> individuals involved in business>

teachers>executives> individuals involved in clerical work.

In D6, number of individuals in other job forms> number of individuals in business> teachers>

executives> number of individuals involved in clerical work.

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

CLERICAL

EXECUTIVE

TEACHING

CONSULTANT

BUSINESS

OTHERS

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REGRESSION ANALYSIS

The following table shows the estimated values of the parameter attached to the

independent variables. The regression lines exhibit the best regression run after dropping of

certain variables. These values are significant at 10% level of significance if followed by a single

*, 5% level of significance if followed by two * and 1% level of significance if followed by three

* respectively.

VARIABLES GD LO SP CR HF QE ES DM PR CG RD CI

D1 0.925***

1.103***

0.129 0.741***

0.148 0.627**

-0.606*

*

0.401* -0.072 -0.072 0.169 0.424*

D2 0.113 -0.024 0.085 0.601*

*

0.303 0.583*

*

-0.078 0.13 0.168 0.746*

**

0.082 0.018

D3 0.632*

*

0.844*

**

0.186 0.317 0.485* 1.225*

**

0.609*

*

0.573*

*

1.311*

**

-0.283 0.778*

**

1.220**

* D4 0.438* 0.692*

**

-0.106 0.853*

**

0.413 0.822*

**

0.073 0.496*

*

0.650*

**

0.737*

**

0.381 0.361

D5 0.663**

1.304***

0.701***

-0.124 0.25 1.634***

0.199 0.484* 0.450* 0.275 0.701***

0.760***

D6 (omitte

d)

(omitte

d)

(omitte

d)

(omitte

d)

(omitted) (omitte

d)

(omitte

d)

(omitte

d)

(omitte

d)

(omitte

d)

(omitte

d)

(omitte

d)

GENDER -0.118 -0.089 -0.217 0.039 -0.271 -0.044 -0.297* 0.111 (omitte

d)

-0.182 0.082 (omitte

d) AGE -5E-05 0.003 -0.002 -

0.012**

-0.005 -0.003 0.007 -0.002 -0.004 -0.011**

-0.002 -0.007

STATUS (omitted)

-0.061 -0.032 (omitted)

-0.096 (omitted)

(omitted)

(omitted)

0.061 (omitted)

(omitted)

(Omitted)

EDUCATION

0.039 -0.009 0.111 -0.066 (omitted) 0.220**

(omitted)

(omitted)

0.099 0.087 0.058 0.235**

OCCUPATION

0.24 0.133 0.337* 0.231 (omitted) (omitted)

0.051 -0.032 (omitted)

0.059 0.098 0.194

JOB CHAR 0.123***

(omitted)

0.035 0.122***

0.052 0.074* 0.01 0.082* 0.051 -0.026 0.081* 0.023

N.O. FAMILY

(omitted)

(omitted)

(omitted)

(omitted)

(omitted) 0.002 -0.025 (omitted)

-0.035 (omitted)

(omitted)

(omitted)

N.O.VOTING

-0.056 0.005 -0.057 0.017 0.032 (omitted)

(omitted)

0.019 (omitted)

(omitted)

0.053 0.013

AN. FAM. INC

0.065 -0.049 -0.079 0.061 -0.1601805*

**

-0.045 -0.019 0.022 (omitted)

(omitted)

0.013 -0.026

VOTER ID -0.061 -0.143 -0.176 -0.314* -0.213 -0.364 -0.219 -0.515 0.265 -0.404 -0.377 0.072

VOTED IN

'14

0.031 0.056 0.076 (omitte

d)

(omitted) 0.461*

*

0.265 0.293 0.252 0.348 0.217 0.128

P>CHI2 0.001 0 0.052 0 0.008 0 0.001 0.064 0 2E-04 0.033 4E-04

TABLE 4: REGRESSION COEFICIENTS FOR 12 DEPENDENT VARIABLES (IN ACCORDANCE TO BEST REGRESSION) . STATA HAS

CONSIDERED D6( SOUTHERN AVENUE) TO BE BASE REGION.

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INFERENCES Difference in location: In the area D5, that is, in Bapuji Nagar, as compared to the base region D6 (Southern

Avenue), people have higher expectation about improved Growth & Development (GD), Larger

job opportunities (LO), Stability in Prices (SP), Better Health facilities at cheaper cost (HF),

Quality education all levels (QE), More Schemes for Elderly (ES), Fall in Undesirable Delays in

Decision Making (DM), Better Foreign Relations (PR), Less Corruption in Government (CG),

Strong Rupee against Dollar (RD), Construction of Infrastructure (CI) {as indicated by the

positive sign of the co-efficient}, whereas lower expectation is noticed regarding Decrease in

crime rate (CR) {indicated by the negative sign of the co-efficient}.

Similarly, in comparison to the base region D6, for other areas, like D1, lower

expectations have been recorded relating to ES, PR and CG; in D2, people have lower

expectation about LO and ES ; in D3, lower expectation has been shown about CG; in D4, less

expectation has been seen about SP, whereas higher expectation has been seen about all

other factors.

Education:

Looking through the details of each of the parameters, the mean educational level is the

second lowest in the Bapuji Nagar area and lower than that of the base region too. Hence the

people here have higher expectation about Quality education at all levels. It must be noted

that this is only an attempt to explain the results and the existence of other reasons for such

results is highly possible.

Gender:

On the basis of gender, men have higher expectations about Growth & Development

(GD), larger job opportunities (LO), Stability in Prices (SP), Better health facilities at cheaper

cost (HF), Quality education at all levels (QE), More Schemes for Elderly (ES), Less Corruption in

Government (CG) as compared to women but less to Decrease in crime rate (CR), Fall in

Undesirable Delays in Decision Making (DM), Strong Rupee against Dollar (RD) than women.

Consequently, it can be added that women have higher expectation about decrease in crime

rate(CR) which seems quite logical especially considering the present high level of crime rate

against women.

30

Age:

Going on to age, younger individuals have higher expectations about GD, SP, HF, QE, CR,

DM, PR, CG, RD and CI; while older individuals are seen to have higher expectations regarding

LO and ES.

Educational Level:

Analyzing the educational level attained by an individual, a less educated person has

shown higher expectation about LO and CR, whereas, a more educated person has shown

higher expectations regarding to other parameters like, GD, SP, QE, PR, CG, RD and CI.

Occupation:

Moving to occupation of individuals, an individual associated with the government

sector show higher expectation relating to DM; while those associated with the private or

other sector have higher expectation about GD, LO, SP, CR, ES, CG, RD, CI.

Number of Family Members:

As number of members in family increase, higher expectation about QE is seen as

compared to smaller families, while families with less number of members have higher

expectation pertaining to ES and PR compared to larger families.

Number of Voting Members:

Looking to the number of voting members in family, as the number increases,

expectation regarding LO, CR, HF, DM, RD, CI is higher, while as it decreases, expectation

regarding GD and SP is higher.

Annual Family Income:

It can be seen that as annual family income rises, higher expectation is seen about

Growth& Development, Decrease in Crime rate, DM and RD as indicated by the sign of positive

coefficients. Moreover, with the rise of annual family income, people have shown lower

expectations about on Larger job opportunities (LO), SP, Better health facilities at cheaper cost

31

(HF), Quality education at all levels (QE), ES and CI. The reasons for these expectations cannot

be explained without carrying out a post analysis survey.

Possession of Voter ID Card:

People possessing voter id card have displayed higher expectation pertaining to PR and

CI; and lower expectation pertaining to GD, LO, SP, CR, HF, QE, ES, DM, CG and RD.

Voted in 2014:

If we consider voting in 2014 as a basis, we see that people who have not voted in 2014

have higher expectations regarding GD, LO, HF, QE, ES, DM, PR, CG, RD, CI than those who

have.

For the other regressions, where the variable isn’t mentioned, those variables have been

dropped.

MARGINAL EFFECT ANALYSIS

The following table shows marginal effects. It thus shows the change in probability of

giving lowest rank to the dependent variable with respect to change in the independent

variable. That is when independent variable changes by one unit over the mean value, there is

a higher probability of people to state least expectation(rank 1) pertaining to the dependent

variable (say GD) if the sign is positive and lower probability of people to display least

expectation relating to the dependent variable when the sign is negative.

The marginal effects have only been calculated for those independent variables for

which the regressions of the dependent variables have found to be significant. However,

conclusions drawn from this table is restricted to the sample and cannot said to be holding

true for the population as they are not found to be significant.

32

TABLE 5: MARGINAL EFFECTS ON EXPECTATIONS REGARDING 12 DEPENDENT VARIABLES FOR UNIT CHANGE OF

PARAMETERS ABOUT THEIR MEAN

INFERENCES

The marginal effects have only been calculated for those independent variables for

which the regressions of the dependent variables have found to be significant. However,

conclusions drawn from this table is restricted to the sample and cannot said to be holding

true for the population as they are not found to be significant.

We can now analyze the effects as follows-

DIFFERENCE IN LOCATION:

Stata by default has taken D6 to be the base region. as we move from D6 to D1, we see-

people have less probability to have least expectation about GD, LO, CR and QE,DM and CI

(inferred from the negative sign of the marginal effect). Similarly, people have ,more

probability to have least expectation relating to ES (inferred from positive sign).

As we move from D6 to D2- people have less probability to put least importance on GD,

LO, CR, CG and QE, implying D2 people show higher expectations about these factors than

those in D6.

INDEPENDENT

VARIABLES

GD LO SP CR HF QE ES DM

PR CG RD CI

D1 -0.008 -0.019 -0.020 0.046 0.262 -0.244 -0.179

D2 -0.005 -0.015 -0.016 -0.043 -0.466

D3 -0.003 -0.012 -0.019 -0.090 -0.305 -0.287 -0.758 -0.366 -0.473

D4 -0.005 -0.023 -0.022 -0.061 -0.261 -0.334 -0.417

D5 -0.008 -0.121 -0.261 -0.233 -0.362 -0.303

AGE 0.001 1.388

OCCUPATION -0.003 0.593

EDUCATION LEVEL

0.016 -1.952

JOB CHARACTER

-0.001 -0.003 -0.005

ANNUAL FAMILY

INCOME

0.006 -1.130 -0.990

VOTER ID 0.011

VOTED IN 2014 -0.034

33

As we move from D6 to D3-people have lower probability to display least expectation

relating to GD, LO, HF, QE, ES, DM, PR, RD and CI implying people in D3 show higher

expectation about these factors than those in D6

As we move from D6 to D4- people have lower probability to show least expectation

about GD, LO, CR, QE, DM and PR implying people show higher expectation regarding these

factors in D4 than in D6. Similarly, people have higher probability to display least expectation

about CG.

As we move from D6 to D5- people have lower probability to show least expectation

about SP, QE, DM, PR, RD and CI implying that people in D5 display higher expectation

pertaining to these factors than those in D6.

AGE:

People of higher age have higher probability of giving higher rank to CR and CG, implying

higher expectations for decreased crime rate for older individuals.

OCCUPATION:

As we move from government to non- government sector, people have lower

probability to show least expectation for SP, implying non- government sector employees have

higher expectation for stability in prices. The converse holds true for ES.

EDUCATION LEVEL:

With rise in education people, people have higher probability to show least expectation

to QE.

ANNUAL FAMILY INCOME:

As annual family income rises, people have higher probability to display least

expectation about HF. Thus, richer people display lesser expectation about HF. The converse is

true for DM and RD.

VOTER ID :

People having a voter id card (number 1) have higher probability of having least

expectation to HF than those who do not have a voter ID ( number 0).

34

VOTED IN 2014:

People who have voted in 2014 (number 1) have lower probability to show least

expectation about QE than the ones who have not voted in 2014 (number 0).

Summary tables for regression and marginal analysis:

VARIABLE

S

GROWTH

AND DEVELPOM

ENT

(GD)

LARGER JOB

OPPORTUNITIES

(LO)

STABIL IT

Y IN PRICES

(SP)

DECRASE

IN CRIME RATE

(CR)

BETTER

HEATLTH FACIL ITIE

S AT

LOW COST

(HF)

QUAL ITY

EDUCATION AT

ALL

LEVELS

(QE)

MORE

SCHEM ES FOR THE ELDERLY

(ES)

FALL IN

UNDESIRABLE

DELAYS IN

DECISION MAKING

(DM)

BETTER

RELATION WITH

INDIA'S

NEIGHBOURS

(PR)

LESS

CORRUPTION IN

GOVERNM

ENT (CG)

STRONG

ER RUPEE

AGAINST

DOLLAR

(RD)

RAPID

CONSTRCUTION OF

INFRASTRUC T

URE

(CI)

D1 + + + + + + - + - - + +

D2 + - + + + + - + + + + +

D3 + + + + + + + + + - + + D4 + + - + + + + + + + + +

D5 + + + - + + + + + + + +

D6 (omitted) (omitted) (omitted)

(omitted)

(omitted)

(omitted)

(omitted)

(omitted)

(omitted)

(omitted)

(omitted)

(omitted)

GENDER

- - - + - - - + (omitted)

- + (omitted)

AGE - + - - - - + - - - - -

STATUS (omitted) - - (omitted)

- (omitted)

(omitted)

(omitted)

+ (omitted)

(omitted)

(Omitted)

EDUCA-

TION + - + - (omitte

d) + (omitte

d)

(omitted

) + + + +

OCCUP-ATION

+ + + + (omitted)

(omitted)

+ - (omitted)

+ + +

JOB CHAR

- (omitted) + + + + + + + - + +

N.O. FAMILY

(omitted) (omitted) (omitted)

(omitted)

(omitted)

+ - (omitted)

- (omitted)

(omitted)

(omitted)

N.O.VOTI-NG

- + - + + (omitted)

(omitted)

+ (omitted)

(omitted)

+ +

AN. FAM.

INC

+ - - + - - - + (omitted)

(omitted)

+ -

VOTER ID

- - - - - - - - + - - +

VOTED

IN '14 + + + (omitte

d)

(omitte

d) + + + + + + +

SUMMARY TABLE 1- CAUSAL RELATIONSHIP BETWEEN EXPECTATIONS AND INDEPENDENT VARIABLES

35

SUMMARY TABLE 2: CAUSAL RELATIONSHIP BETWEEN PROBABILITY OF HAVING LOWEST EXPECTATION (RANK 1)FROM

THE NEW GOVERNMENT ABOUT THE VARIOUS FACTOR FOR A UNIT CHANGE OF THE INDEPENDENT VARIABLES ABOUT

THEIR MEAN.

The above table shows the causal relationship between the higher or lower probability

of an individual of having lowest expectation (rank 1) regarding various factors from the new

government with a unit change in the independent variables about their mean. A '+' (plus) sign

implies that there is a higher probability of an individual to have least expectation(rank 1) from

the government about a said factor with a one unit increase in the independent variable. The

converse holds true for ' - ' (minus) sign.

VARIABLES GROWTH AND DEVELOPMENT (GD)

LARGER JOB OPPRTUNITIES (LO)

STABILITY IN PRICES (SP)

DECREASE IN CRIME RATE (CR)

BETTER HEALTH FACILITIES AT LOWER COST (HF)

QUALITY EDUCTAION AT ALL LEVELS (QE)

MORE SCHEMES FOR THE ELDERLY (ES)

FALL IM UNDESIRABLE DELAYS

IN DECISIO

N MAKING

(DM)

BETTER RELATIONS WITH INDIA'S NEIGHBOURS (PR)

LESS CORRUPTION IN GOVENRMENT (CG)

STRONGER RUPEE AGAINST DOLLAR (RD)

RAPID CONSTRUCT

ION OF INFRASTRUCTURE (CI)

D1 - - - + + - - D2 - - - - - D3 - - - - - - - - - D4 - - - - - - - D5 + - - - - - AGE + + OCCUPATION - + EDUCATION LEVEL

+ - JOB

CHARACTER - - -

ANNUAL

FAMILY INCOME

+ - -

VOTER ID + VOTED IN 2014 -

36

conclusion

37

This project deals with the varying expectations of individuals from the new

government. It aims to illustrate how these expectations vary not only due to demographic

factors like age and gender but are also influenced by other factors such as income and

possession of voter ID cards. It is most significantly noticed that even the geographical region

in which an individual resides plays an important influence in their expectations from the new

government and the relative weightage of importance given to these expectations.

Important inferences that we drew from this study is the following groups of individuals

have high expectations from the new government in various fields like GD, LO and PR-

men as compared to women,

younger individuals as compared to older ones,

those who did not vote in 2014 as compared to those who did.

It was also inferred that individuals living in all other surveyed regions except Southern

Avenue, showed a lower probability of having least expectation from the new government in

various field including QE, GD and LO. This may imply that individuals living in regions other

than Southern Avenue have higher expectations from the new government. It must however

be noted that these marginal results were not found to be significant, hence they hold true for

the sample but may not hold true for the population.

Significant results of the project include-

younger individuals have higher expectations from the new government than older

people (negative causality for all except LO and ES). This could be explained by the

overwhelming support that could be seen among the young generation for a change in

the Central government before the elections, in hope of improvement in governance.

female respondents have shown higher expectations from the new government than

male respondents (negative causality for all except LO and ES). Higher expectations

among women regarding factors like stability in prices and decrease in crime rate may

be as a result of hope of change in the problems faced by them directly in daily life.

people with higher levels of education seem to show higher expectations from the new

government than those with lower educational qualification (positive causality except

LO and CR). This may be because more educated individuals might have greater

awareness and better comprehension of the political and socio-economic situation of

the country as well as the manifesto promises by the various parties.

38

It must be noted that these justifications for the conclusions are merely

possibilities. The actual reasons cannot be unambiguously determined without a follow-

up post survey.

The analysis of this project suggests that slightly differentiated approaches should be

undertaken by political parties wishing to contest elections on the basis of factors including-

target geographical area,

target section of population,

target income group.

Such targeted policy formation or electoral campaigns would benefit the parties

involved as well as take a keener look into the actual requirements of the people instead of

having an umbrella policy or strategy cover for all individuals. This would allow the nation to

prosper and the government to live up to the requirements and expectations of the people

who voted them into power with exceedingly high trust, hope and optimism.

39

Bibliography and references

The following articles and material has been referred to in the analysis and study

of this project report:

http://www.ifes.org/~/media/Files/Publications/Survey/2012/Ukraine_2012_Su

mmary_of_Findings.pdf

Survey by London School of Economics, EACEA 2010/03, 2013, 234p.

http://www.yourarticlelibrary.com/essay/voting-behaviour-various-appro

http://ibnlive.in.com/videos/527482/its-counting-day-on-tuesday-what-are-your-

expectations-from-the-new-delhi-government.html

http://azdailysun.com/news/national/poll-finds-great-expectations-and-

optimism-await-obama/article_8ec6d0d3-e84c-59e8-ab8b-bcc18929126e.html

sites.google.com/site/eeconometrics-models/ordered-probit-and-logit-models

Introduction to Econometrics,3rd Edition- G.S. Maddala

An Analytical Study: India's Exports- Sugata Marjit and Ajitava Raychaudhuri

40

Sample questionnaire

NAME: ____________________________________

GENDER: Male

Female

AGE: __________________________________

STATUS IN FAMILY:

EDUCATIONAL LEVEL (highest level attained):

Less than primary education

Primary education

High school education( Class XII)

Graduate

Post Graduate and higher

ADDRESS: __________________________________

OCCUPATION (Govt./ Pvt.):

Government

Private

Others

If others ,specify ______________

41

IF PRIVATE SECTOR,TYPE OF JOB:

Clerical

Executive or Officer

Teaching

Consultant

Business

Others

If others ,specify ______________

IF GOVERNMENT/PUBLIC SECTOR, TYPE OF JOB:

Clerical

Executive or Officer

Teaching

Consultant

Others

If others ,specify ______________

NUMBER OF MEMBERS IN FAMILY: ______________

NUMBER OF VOTING MEMBERS IN FAMILY:_______

FAMILY INCOME (RANGE):

DO YOU HAVE A VOTER ID CARD (YES/NO):

Yes

No

DID YOU VOTE IN 2014 ELECTIONS? (YES/NO):

42

Yes

No

RANK YOUR EXPECTATIONS FROM THE NEW GOVERNMENT(CENTRAL GOVERNMENT) Circle one response for each of the following items:

Ranks Least Not much Somewhat High Almost certain

Growth and

development

1 2 3 4 5

larger job opportunities

1 2 3 4 5

stability in prices

1 2 3 4 5

Decrease in

Crime Rate

1 2 3 4 5

Better government

health facilities at cheap cost

1 2 3 4 5

Quality education at all

levels

1 2 3 4 5

More schemes for elderly

1 2 3 4 5

Fall in Red tapism

1 2 3 4 5

Rapid construction of infrastructure

(like roads, flyovers, rail network, ports, power plants

etc.)

1 2 3 4 5

Better relations with India’s neighbours

1 2 3 4 5

- A strong rupee against dollar

1 2 3 4 5