How Inflation Affect the Consumer in india

CHAPTER-1

OVERVIEW

NSVKMS/MBA/SEM-IV/MRP-II 1

1.1 Introduction:

In economics, inflation is a rise in the general level of prices of goods and services in an

economy over a period of time. When the price level rises, each unit of currency buys

fewer goods and services; consequently, inflation is also erosion in the purchasing power

of money – a loss of real value in the internal medium of exchange and unit of ac in the

economy. A chief measure of price inflation is the inflation rate, the annualized

percentage change in a general price index (normally the Consumer Price Index) over

time.

Inflation can have many effects that can simultaneously have positive and negative

effects on an economy. Negative effects of inflation include a decrease in the real value

of money and other monetary items over time; uncertainty about future inflation may

discourage investment and saving, or may lead to reductions in investment of productive

capital and increase savings in non-producing assets. e.g. selling stocks and buying gold.

This can reduce overall economic productivity rates, as the capital required to retool

companies becomes more elusive or expensive. High inflation may lead to shortages of

goods if consumers begin hoarding out of concern that prices will increase in the future.

Positive effects include a mitigation of economic recessions, and debt relief by reducing

the real level of debt.

Economists generally agree that high rates of inflation and hyperinflation are caused by

an excessive growth of the money supply. Views on which factors determine low to

moderate rates of inflation are more varied. Low or moderate inflation may be attributed

to fluctuations in real demand for goods and services, or changes in available supplies

such as during scarcities, as well as to growth in the money supply. However, the

consensus view is that a long sustained period of inflation is caused by money supply

growing faster than the rate of economic growth.

Today, most mainstream economists favor a low steady rate of inflation. Low (as

opposed to zero or negative) inflation may reduce the severity of economic recessions by

enabling the labor market to adjust more quickly in a downturn, and reduce the risk that a

liquidity trap prevents monetary policy from stabilizing the economy. The task of


http://en.wikipedia.org/wiki/Monetary_policy

http://en.wikipedia.org/wiki/Liquidity_trap

http://en.wikipedia.org/wiki/Recessions

http://en.wikipedia.org/wiki/Deflation

http://en.wikipedia.org/wiki/Mainstream_economists

http://en.wikipedia.org/wiki/Economic_growth

http://en.wikipedia.org/wiki/Scarcity

http://en.wikipedia.org/wiki/Demand

http://en.wikipedia.org/wiki/Real_versus_nominal_value

http://en.wikipedia.org/wiki/Money_supply

http://en.wikipedia.org/wiki/Hyperinflation

http://en.wikipedia.org/wiki/Debt_relief

http://en.wikipedia.org/wiki/Recession

http://en.wikipedia.org/wiki/Hoarding

http://en.wikipedia.org/wiki/Good_(economics)

http://en.wikipedia.org/wiki/Inflation#Effects

http://en.wikipedia.org/wiki/Inflation#Negative

http://en.wikipedia.org/wiki/Inflation#Positive

http://en.wikipedia.org/wiki/Consumer_Price_Index

http://en.wikipedia.org/wiki/Price_index

http://en.wikipedia.org/wiki/Inflation_rate

http://en.wikipedia.org/wiki/Purchasing_power

http://en.wikipedia.org/wiki/Price_level

keeping the rate of inflation low and stable is usually given to monetary authorities.

Generally, these monetary authorities are the central banks that control the size of the

money supply through the setting of interest rates, through open market operations, and

through the setting of banking reserve requirements.


http://en.wikipedia.org/wiki/Reserve_requirements

http://en.wikipedia.org/wiki/Open_market_operations

http://en.wikipedia.org/wiki/Interest_rate

http://en.wikipedia.org/wiki/Central_bank

http://en.wikipedia.org/wiki/Monetary_authority

1.2 History of inflation:

Inflation originally referred to increases in the amount of money in circulation. For

instance, when gold was used as currency, the government could collect gold coins, melt

them down, mix them with other metals such as silver, copper or lead, and reissue them

at the same nominal value. By diluting the gold with other metals, the government could

issue more coins without also needing to increase the amount of gold used to make them.

When the cost of each coin is lowered in this way, the government profits from an

increase in seignior age. This practice would increase the money supply but at the same

time the relative value of each coin would be lowered. As the relative value of the coins

becomes less, consumers would need to give more coins in exchange for the same goods

and services as before. These goods and services would experience a price increase as

the value of each coin is reduced.

From second half of the 15th century to the first half of the 17th, Western Europe

experienced a major inflationary cycle referred to as "price revolution", with prices on

average rising perhaps six fold over 150 years. It was thought that this was caused by the

increase in wealth of Habsburg Spain, with a large influx of gold and silver from the

New World. The spent silver, suddenly spread throughout a previously cash starved

Europe, caused widespread inflation. Demographic factors also contributed to upward

pressure on prices, with European population growth after depopulation caused by the

Black Death pandemic.

By the nineteenth century, economists categorized three separate factors that cause a rise

or fall in the price of goods: a change in the value or resource costs of the good, a change

in the price of money which then was usually a fluctuation in the commodity price of the

metallic content in the currency, and currency depreciation resulting from an increased

supply of currency relative to the quantity of redeemable metal backing the currency.

Following the proliferation of private bank note currency printed during the American

Civil War, the term "inflation" started to appear as a direct reference to the currency

depreciation that occurred as the quantity of redeemable bank notes outstripped the

quantity of metal available for their redemption. The term inflation then referred to the

devaluation of the currency, and not to a rise in the price of goods.


http://en.wikipedia.org/wiki/American_Civil_War

http://en.wikipedia.org/wiki/American_Civil_War

http://en.wikipedia.org/wiki/Bank_note

http://en.wikipedia.org/wiki/Commodity

http://en.wikipedia.org/wiki/Value_(economics)

http://en.wikipedia.org/wiki/Black_Death

http://en.wikipedia.org/wiki/Commercial_revolution

http://en.wikipedia.org/wiki/Commercial_revolution

http://en.wikipedia.org/wiki/New_World

http://en.wikipedia.org/wiki/Silver

http://en.wikipedia.org/wiki/Gold

http://en.wikipedia.org/wiki/Habsburg_Spain

http://en.wikipedia.org/wiki/Price_revolution

http://en.wikipedia.org/wiki/Western_Europe

http://en.wikipedia.org/wiki/Seigniorage

http://en.wikipedia.org/wiki/Nominal_value

This relationship between the over-supply of bank notes and a resulting depreciation in

their value was noted by earlier classical economists such as David Hume and David

Ricardo, who would go on to examine and debate to what effect a currency devaluation

(later termed monetary inflation) has on the price of goods (later termed price inflation,

and eventually just inflation).


http://en.wikipedia.org/wiki/Monetary_inflation

http://en.wikipedia.org/wiki/David_Ricardo

http://en.wikipedia.org/wiki/David_Ricardo

http://en.wikipedia.org/wiki/David_Hume

1.3 Inflation in India:

India has been the cynosure for the past few years in the global economic arena owing to

its changing inflation patterns. Between the fiscal year 2004-05 and 2007-2008, India

had experienced an average growth rate of more than 9%, but the global crunch pinched

the economy so hard that the economy gave in to the adverse external shocks and few

sectors experienced a slump. Inflation in India 2009 stands at 11.49% Y-o-Y. The

inflation rate is referred to the general rise in prices, taking into consideration the

common man's purchasing power. Inflation is mostly measured in CPI.

In 2008 industry bodies, policy makers were all worried with the steadily-mounting

inflation. The middle of the year augmented the tension as the majority of the population

was wary of a double-digit inflation but things changed within few months. Inflation in

India actually fell below 1% during the third week of March, 2009. The moderate

inflation is the desirable of all too much of it or too less of it, in every way worries the

policy makers.

Understanding in the right manner inflation is such a situation when too many people

chase too few goods and too few services, which automatically makes the prices of the

goods and services high because of the high demand. At the same time, when inflation

falls below the desired mark (in the negative territory), then too few people chase too

many goods and too many services, making the prices of the goods and services under-

priced.

The India inflation is actually measured by the Y-o-Y variation in the Wholesale Price

Index. While the inflation as measured by WPI is at present at a very low level, the

inflation measured by the Consumer Price Index is at elevated levels of 9 to 10%.1

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

1 http://business.mapsofindia.com/inflation/


2009 10.45 9.63 8.03 8.70 8.63 9.29 11.89 11.72 11.64 11.49 13.51 14.97

2008 5.51 5.47 7.87 7.81 7.75 7.69 8.33 9.02 9.77 10.45 10.45 9.70

2007 6.72 7.56 6.72 6.67 6.61 5.69 6.45 7.26 6.40 5.51 5.51 5.51

2006 4.39 5.31 5.31 5.26 6.14 7.89 6.90 5.98 6.84 7.63 6.72 6.72

1.4 Calculation of inflation:


Some economists assert that India’s method of calculating inflation is wrong as there are

serious flaws in the methodologies used by the government.2

India uses the Wholesale Price Index (WPI) to calculate and then decide the

inflation rate in the economy.

Most developed countries use the Consumer Price Index (CPI) to calculate

inflation.

1.4.1 Wholesale Price Index (WPI)

WPI was first published in 1902, and was one of the more economic indicators available

to policy makers until it was replaced by most developed ries by the Consumer Price

Index in the 1970s.

WPI is the index that is used to measure the change in the average price level of goods

traded in wholesale market. In India, a total of 435 commodities data on price level is

tracked through WPI which is an indicator of movement in prices of commodities in all

trade and transactions. It is also the price index which is available on a weekly basis with

the shortest possible time lag only two weeks. The Indian government has taken WPI as

an indicator of the rate of inflation in the economy.

1.4.2 Consumer Price Index (CPI)

CPI is a statistical time-series measure of a weighted average of prices of a specified set

of goods and services purchased by consumers. It is a price index that tracks the prices of

a specified basket of consumer goods and services, providing a measure of inflation.

CPI is a fixed quantity price index and considered by some a cost of living index. Under

CPI, an index is scaled so that it is equal to 100 at a chosen point in time, so that all other

values of the index are a percentage relative to this one.

Economists Shunmugam and Prasad say it is high time that India abandoned WPI and

adopted CPI to calculate inflation.2 http://www.rediff.com/money/2007/jun/07infla.htm


India is the only major ry that uses a wholesale index to measure inflation. Most ries use

the CPI as a measure of inflation, as this actually measures the increase in price that a

consumer will ultimately have to pay for.

1.4.3 How is WPI (Wholesale Price Index) calculated?

In this method, a set of 435 commodities and their price changes are used for the

calculation. The selected commodities are supposed to represent various strata of the

economy and are supposed to give a comprehensive WPI value for the economy.

WPI is calculated on a base year and WPI for the base year is assumed to be 100. To

show the calculation, let’s assume the base year to be 1970. The data of wholesale prices

of all the 435 commodities in the base year and the time for which WPI is to be

calculated is gathered.

Let's calculate WPI for the year 1980 for a particular commodity, say wheat. Assume

that the price of a kilogram of wheat in 1970 = Rs 5.75 and in 1980 = Rs 6.10

The WPI of wheat for the year 1980 is,

(Price of Wheat in 1980 – Price of Wheat in 1970)/ Price of Wheat in 1970 x 100

i.e. (6.10 – 5.75)/5.75 x 100 = 6.09

Since WPI for the base year is assumed as 100, WPI for 1980 will become 100 + 6.09 =

106.09.

In this way individual WPI values for the remaining 434 commodities are calculated and

then the weighted average of individual WPI figures are found out to arrive at the overall

Wholesale Price Index. Commodities are given weight-age depending upon its influence

in the economy.

1.4.4 How is inflation rate calculated?


If we have the WPI values of two time zones, say, beginning and end of year, the

inflation rate for the year will be,

(WPI of end of year – WPI of beginning of year)/WPI of beginning of year x 100

For example, WPI on Jan 1st 1980 is 106.09 and WPI of Jan 1st 1981 is 109.72 then

inflation rate for the year 1981 is,

(109.72 – 106.09)/106.09 x 100 = 3.42% and we say the inflation rate for the year 1981

is 3.42%.

Since WPI figures are available every week, inflation for a particular week (which

usually means inflation for a period of one year ended on the given week) is calculated

based on the above method using WPI of the given week and WPI of the week one year

before. This is how we get weekly inflation rates in India.

1.4.5 Characteristics of WPI

Following are the few characteristics of Wholesale Price Index:

WPI uses a sample set of 435 commodities for inflation calculation

The price from wholesale market is taken for the calculation

WPI is available for every week

It has a time lag of two weeks, which means WPI of the week two weeks back

will be available now


CHAPTER 2

RESEARCH

METHODOLOGY


2.1 RESEARCH OBJECTIVES

To find out middle class people views about inflation and price rise in the

economy.

To find out effect of inflation on the family budget of middle class people North

and central Gujarat.

To find out the effect of inflation on the different consumption object of middle

class income group.

To find out change in the saving of the people.

To find out people view on steps taken by government to control the inflation.


2.2 SOURCES OF DATA

For systematic research, information is required from different sources of data.

Primary Data:

Primary data may be described as those data that have been observed and recorded

by the researcher for the first time to their knowledge. We have collected primary

data through close ended questionnaire method, filled by consumers and retailers.

Secondary Data:

Secondary data means the data which are readily available from different sources.

We have gathered these data from the websites, books and magazines.

2.2.1 Research methodology for Primary Survey

The research methodology adopted for primary survey is given below:

Research Approach:

For gathering primary data, we have used survey approach, which is widely

used method for data collection and best suited for quantitative descriptive type

of research survey.

Research Instrument:

For our research we have used questionnaire, which is the most, common

instrument used to collect the primary data. A questionnaire consists of the set

of questions presented to the respondents for their answers.

Questionnaire design:

Our prime objective of making questionnaire design is such that we want to find

the effect of the inflation on the consumption people, Like we want to measure

consumers their effort to match with inflation, and use of their saving and

investment option to them.


For fulfilling our objective we make questionnaire design on the basis of

following methods of measuring advertising effectiveness.

o Likert semantic scale.o Dichotomous Questionso Filter or Contingency Questionso Rank Order Scaling

Sampling plan:

Here for research purpose sampling plan is prepared. This plan called for three

decisions.

I. Sampling unit

II. Sample size

III. Sampling procedure

o Sampling unit (who is to be surveyed?)

The sampling units are the generally common people who normally buying

good and services in routine life but they are falling in the income group of

71000 to 300000.

o Sample size (No. People should be surveyed)

For the purpose of research two hundred people of common class people

across Gujarat. Each and every Consumer is contacted with various

occupations like service person, businessman, professional and farmers.

o Sampling procedure (how should the respondents chosen?)

To obtain representative center sample of the population should be drawn. Thus

here non-probability, convenient sampling method is used for consumer.


2.3 ANALYSIS OF RESEARCH:

Statistical Tool: Chi-Square

Chi-square is used with the help of applying SPSS software. In test we make

certain hypothesis and by applying T-Test and check the hypothesis on the bases

of choosing appropriate factor. So this way we try to analyze the data collected

through survey and try to present a clear picture of effectiveness of Radio FM

advertisement on listeners, Experts and focus group.

Researcher had made certain hypothesis for better research for example

Ho: inflation affects the Sugar and Jaggary is independent to Family income

H1: inflation affects the Sugar and Jaggary is dependent to Family income

Ho: inflation affects the Edible oil is independent to sex

H1: inflation affects the Edible oil is dependent to sex

Annova table: The Analysis Of Variance (or ANOVA) is a powerful and common statistical procedure in the social sciences. It can handle a variety of situations. We have used about the different situation of one between groups factor here and two between groups factors in the next section.

Reliability: Analysis Reliability analysis allows you to study the properties of measurement scales and the items that make them up. The Reliability Analysis procedure calculates a number of commonly used measures of scale reliability and also provides information about the relationships between individual items in the scale. Interclass correlation coefficients can be used to compute interpreter reliability estimates.

Correlation: Correlations measure how variables or rank orders are related.


CHAPTER 3

LITERATURE

REVIEWS


Chapter 3 Literature reviews

Topic: Evaluating Core Inflation Measures for India

Author: Motilal Bicchal, Naresh Kumar Sharma and Bandi Kamaiah

Abstract:

This paper discusses in some detail various existing approaches of measuring core

inflation, evaluating their potential advantages and disadvantages. Then a variety of

measures of core inflation for India based on three methods are constructed. Among

these measures, three are based on conventional ex-food and energy principle and one

measure that exclude fifteen of most volatile components are constructed. While

constructing exclusion based indices of core inflation, measures are constructed such that

only a small weight remains excluded from the index of the core inflation. The other two

core measures are variations of ‘Neo-Edgeworthian Index’ are constructed by

reweighting 69 disaggregated components series of WPI. Then another class of core

measures are computed based on weighted exponential smoothing which was primarily

developed by Cogley (2002). Estimates of core inflation based on their indices are then

Calculated for 1995 to 2007 (on monthly basis).

Conclusion:

Since the inception of the term core inflation, there is neither a commonly accepted

theoretical

definition nor an agreed method of measuring it. Because of the fact that it is

unobservable, it has to be estimated. One of the objectives of this paper was to review

existing theoretical approaches of measuring core inflation. We, then, constructed several

measures of core inflation for India. Among these measures, three are based on popular

ad hoc exclusion principle and one measure that excludes fifteen of most volatile

components. While constructing exclusion based core indices, we determined that it

should be done such that small amount of weight is excluded in constructing the core

index. The other two core measures, which are variations of ‘Neo-Edgeworthian Index’,

were constructed by reweighting 69 disaggregated components series of WPI. Further,

another class of core measures was constructed based on weighted exponential

smoothing which was primarily developed by Cogley (2002).


Topic: Inflation Targeting in India: Issues and Prospects

Author: Raghbendra Jha

Abstract:

Inflation targeting (henceforth IT) has emerged as a significant monetary policy

framework in both developed and transition economies. Some authors have argued that

for transition economies undergoing sustained financial liberalization and integration in

world financial markets IT is an attractive monetary policy framework. The present

paper evaluates the case for IT in India. It begins by stating the objectives of monetary

policy in India and argues that inflation control cannot be an exclusive concern of

monetary policy with widespread poverty still present. The rationale for IT is then spelt

out and found to be incomplete. The paper provides some evidence on the effects of IT in

developed and transition economies and argues that although IT may have been

responsible for maintaining a low inflation regime it has not brought down the inflation

rate itself substantially. Further, the volatility of exchange rate and output movements in

transition ries adopting IT has been higher than in developed market economies. I then

discuss India’s experience with using rules-based policy measures (nominal targets) and

discuss why India is not ready for IT. I show that even if the Reserve Bank of India

(RBI) wanted to, it could not pursue IT since the short-term interest rate (the principal

policy tool used to affect inflation in ries working with IT) does not have significant

effects on the rate of inflation. The paper concludes by listing monetary policy options

for India at the current time.

Conclusion:

This paper has argued that the primary objective of Indian monetary policy, at least in

the medium term, has to be the attainment of higher economic growth. Moreover, since

India has high inflation aversion, this objective does not conflict with that of short term

stabilization.

Monetary policy in India has to be conducted against this background. This paper has

argued that the multi-objective formulation pursued by the RBI has merit and that such

monetary policy should be pursued to maintain stable interest and inflation rates and a

slightly undervalued currency in order to engineer higher export led growth.


A second policy measure is weighted towards real exchange rate appreciation (more in

line with IT) and would involve relatively larger current ac deficits. Real appreciation, in

turn, could be secured by nominal appreciation or by permitting higher inflation. Both

policies would lead to low inflation rates and reduced inflows of foreign capital and,

therefore, lower accumulation of reserves at given rates of sterilization. Policy packages

that use import liberalization would, like real appreciation, permit higher absorption via

higher current ac deficits but without penalizing exports. The optimal package for India

is a judicious combination of these two broad sets of policies with greater emphasis on

fiscal consolidation and import liberalization, rather than real exchange rate appreciation

via nominal appreciation or inflation. These are essential elements of an appropriate

monetary policy regime for India.


Topic: Inflation Determination with Taylor Rules: A Critical Review

Author: John H. Cochrane

Abstract:

The new-Keynesian, Taylor-rule theory of inflation determination relies on explosive

dynamics. By raising interest rates in response to inflation, the Fed does not directly

stabilize future inflation. Rather, the Fed threatens hyperinflation or deflation, unless

inflation jumps to one particular value on each date. However, there is nothing in

economics to rule out hyperinflationary or deflationary solutions. Therefore, inflation is

just as indeterminate under “active” interest rate targets as it is under standard fixed

interest rate targets. Inflation determination requires ingredients beyond an interest-rate

policy that follows the Taylor principle.

Conclusion:

Practically all verbal explanations for the wisdom of the Taylor principle — the Fed

should increase interest rates more than one for one with inflation — use old-Keynesian,

stabilizing, logic: This action will raise real interest rates, which will dampen demand,

which will lower future inflation. New-Keynesian models operate in an entirely different

manner: by raising interest rates in response to inflation, the Fed threatens hyperinflation

or deflation, or at a minimum a large “non-local” movement, unless inflation jumps to

one particular value.


Topic: inflation theory: a critical Literature review and a new Research agenda

Author: Alfredo Saad-Filho

Abstract:

Marxian analyses of inflation tend to fall under three broad categories, those that

emphasize primarily the role distributive conflicts, monopoly power, or state intervention

on the dynamics of credit money. This article reviews these interpretations, and indicates

how they can be integrated. The proposed approach, based on the 'extra money' view,

departs from the circuit of capital and the endogeneity of credit money in order to

explain inflation in inconvertible paper money systems.

Conclusion:

TheyThis article has analyzed critically the three best known Marxian theories of inflation.

They argue, in different ways, that inflation is a historically specific phenomenon, but its

form can be abstractly determined from the broad features of modem capitalism.

However, beyond a certain point concrete studies become necessary in order to

contextualize the analysis. Different alternatives are proposed in order to overcome the

difficult dilemmas imposed by the attempt to explain inflation in inconvertible money

systems, while preserving the endogeneity and non-neutrality of money. They are also

heavily dependent on the context of the analysis.


Topic: exchange rate regimes and inflation – Only hard pegs make a difference

Author: Michael Bleaney and Manuela Francisco

Abstract:

Previous research has suggested that pegged exchange rates are associated with lower inflation than floating rates. In which direction does the causality run? Using data from a large sample of developing ries from 1984 to 2000, we confirm that “hard” pegs (currency boards or a shared currency) reduce inflation and money growth. There is no evidence that “soft” pegs confer any monetary discipline. The choice between soft pegs and floats is determined by inflation: when inflation is low, pegs tend to be chosen and sustained, and when inflation is high, either floats are chosen or there are frequent regime switches.

Conclusion:

The theoretical analysis suggested that pegs would be associated with lower inflation

than floats, provided that the costs of devaluation were significant. Whether the costs of

devaluation represent a major deterrent to inflation in any given form of peg is an

empirical question. In our empirical work we distinguish hard pegs (a shared currency or

a currency board) from other forms of peg (soft pegs), on the grounds that the obstacles

or disincentives to devaluation are much higher for hard pegs.


Topic: Inflation and Growth: In Search of a Stable Relationship

Author: Michael Bruno and William Easterly

Abstract:

Are inflation and growth inversely associated, directly associated, or not associated? Is

the empirical inflation growth relationship primarily a long-run relationship across ries, a

short run relationship across time, or both? Like a bickering couple, inflation and growth

just cannot seem to decide what their relationship should be.

Conclusion:

The early empirical literature on inflation and growth found little in the way of a

relationship between the two. The growth literature detected a relationship between

inflation and growth only after ries kindly provided some discrete high inflation crises in

the 1980s. And even then it was still unclear whether there was a long-run or a short-run

relationship because the empirical relationships were weak with long-period averages

and strong with short-period averages. Despite extensive counseling by the new growth

literature, the indecisive couple of inflation and growth cannot decide whether they

belong together in the short run or in the long run.


CHAPTER 4

ANALYSIS


4.1 Demographics:

a. Gender:

168

32

Gender

MaleFemale

Gender: - Male respondents: 168, Female Respondents: 32

b. Occupation:

92

51

13

44

Occupation

ServiceBusinessProfessionalFarmenr

Occupation: - Service: 92, Business: 51, Professionals: 13, Farmers: 44


c. Family Income:

71000-150000 151000-300000 more than 3000000

20

40

60

80

100

120

78

111

11

Family Income

Income: - 71000-150000: 78, 151000-300000: 111, more than 300000: 11

d. No. of person in Family

8

67

99

26

No. of Family member

1 to 23 to 45 to 6more than 6

Family Members: - 1-2: 8, 3-4: 67, 5-6: 99, More than 6: 26


e. No. of Service person in 2008 and in 2009:

0 to 23 to 4

020406080

100120140160180200

2008

2009

196

4

194

6

20082009

Service person in 2008: - 0-2: 196, More than 2: 4

Service Person in 2009: -0-2: 194, More than 2: 6

f. No. of Children Studying:

181

19

No. of Children studying

1 to 2more than 2

No of Children studying: 1-2: 181, More than 2: 19


4.2 How inflation affect the consumer?

4.2.1 Sex

Effect of inflation * Sex Cross tabulation

SexTotalMale Female

effect of inflation

strongly agree 81 15 96agree 75 14 89neutral 10 1 11disagree 2 2 4

Total 168 32 200

Findings:

Here 96 people are strongly agree that inflation affects to the buying behavior of people

out of total surveyed people among them 81 are male & 15 are female. Out of total

surveyed people 89 are agree that inflation affects to the routine life of people among

them 75 are male & 14 are female. Out of total surveyed people 4 are disagree. To sum

up approx. 70% of total people are males and remaining are females.

4.2.2 Occupation

Effect of inflation * Occupation Cross tabulation

Occupation

TotalService BusinessProfessional Farmer

effect of inflation

strongly agree

36 23 8 29 96

agree 47 25 5 12 89neutral 9 1 0 1 11disagree 0 2 0 2 4

Total 92 51 13 44 200

Findings:


Out of total surveyed persons 96 are strongly agree that includes service people,

businessmen, Professional & Farmers and in number they are 36, 23, 8 & 29

respectively. In the same way persons who are agree are 89 that includes service people,

businessmen, Professional & Farmers and in number they are 47, 25, 5 & 12respy. Only

few peoples are neutral & disagree among total observed people.

4.2.3 Family income

Effect of inflation * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

effect of inflation

strongly agree

41 48 7 96

agree 26 59 4 89neutral 7 4 0 11disagree 4 0 0 4

Total 78 111 11 200

Findings:

Out of total people 78 are fall under the income between 71000 to 150000 where as 111

persons fall under the income between 151000 to 300000 and remaining 11 are from

more than 3 lacs. In the slab of 71 to 150 thousand 41 are agree 26 are agree 7 are neutral

& 4 are disagree. In the slab of 151 to 300 thousand 48 are agree 59 are agree 4 are

neutral & no one is disagree. In the slab more than 300 thousand 7 are agree 4 are agree

& no one is from neutral & disagree.

4.2.4 No of member in family


Effect of inflation * No of person in family Cross tabulation

No of person in family Total1-2 3-4 5-6 more than

6effect of inflation

strongly agree

4 32 43 17 96

agree 2 32 46 9 89neutral 0 3 8 0 11disagree 2 0 2 0 4

Total 8 67 99 26 200

Findings:

Out of total people 8 are fall under such family that consists less than 2 member where as

67 persons fall under such family that consists family member between 3 to 4 and 99

3are fall under such family that consists less than 2 member income between 151000 to

300000 and remaining 11 are from more than 300000. In the slab of 71 to 150 thousand

41 are agree 26 are agree 7 are neutral & 4 are disagree. In the slab of 151 to 300

thousand 48 are agree 59 are agree 4 are neutral & no one is disagree. In the slab more

than 300 thousand 7 are agree 4 are agree & no one is from neutral & disagree.

4.2.5 No of service person in 2008


Effect of inflation * No of service person in 2008 Cross tabulation

No of service person in 2008 Total

0-2 3-4

effect of inflation


Total 196 4 200

Findings:

In above table No of service person in family and effect of inflation on consumption, it is

given that 94 respondents from less than 2 persons earning in family strongly agree that

inflation affects their consumption where as 87 people are agree with that. While 4

people are disagree. Where as a family consist of 3 to 4 earning persons believe that

inflation doesn’t affect very largely to the buying behavior of people.

4.2.6 No of service person in 2009

Effect of inflation * No of service person in 2009 Cross tabulation

No of service person in 2009 Total

0-2 3-4

effect of inflation


Total 194 6 200

Findings:


In above table No of service person in family and effect of inflation on consumption, it is

given that 94 respondents from less than 2 persons earning in family strongly agree that

inflation affects their consumption where as 87 people are agree with that. While 4

people are disagree. Where as a family consist of 3 to 4 earning persons believe that

inflation doesn’t affect very largely to the buying behavior of people.

4.3 How inflation affect most to the different consumption object?


Mode:

Particular

Food

Education

Clothes

Transportation

LPG

Entrainments

Phone light bill

Mode 1 2 2 4 6 6 7

Findings:

From the mode calculation of data which shows that food expense are mostly affected by

the inflation in the economy because the food is basic necessity for every consumer.

After food the measure affected object are clothes and education expenses. After that the

transportation expenses are affected most. At last the entertainment expense, LPG

consumption and phone bill consumption is affected.

Median

Particular

Food

Education

Clothes

Transportation

LPG

Entrainments

Phone light bill

Median 1 3 2 5 5 6 5

Findings:

From the median calculation of data which shows that food expense are mostly affected

by the inflation in the economy because the food is basic necessity for every consumer.

After food the measure affected object are clothes and education expenses. After that the

transportation expenses are affected most. LPG consumption and phone bill consumption

is affected. At last the entertainment expense is effected by inflation the middle class

people give more priority to the basic necessity while entertainment expense are having

secondary importance.

4.4 How you allocate your family budget for cereals and pulses in year 2008?


4.4.1 SEX:

Cereals & pulses * Sex Cross tabulation

Sex TotalMale Female

cereals & pulses

6-10 % 36 10 4610-15 % 104 21 125more than 16 %

28 1 29

Total 168 32 200

Findings:

Here cross tabulation is between budget allocation of cereals & pulses and sex of

respondents, majority of males allocate 10 to 15 % to cereals & pulses while 28 of male

allocate more than 16%. Twenty one female allocate 10 to 15 % to cereals & pulses

while 1 of female allocates more than 16%.

4.4.2 Occupation:

Cereals & pulses * Occupation Cross tabulation

Occupation TotalService Business Professional Farmer

cereals & pulses

6-10 21 13 1 11 4610-15 58 34 8 25 125more than 16

13 4 4 8 29

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of cereals & pulses and occupation of

respondents, 58 people doing service allocate 10-15 % and 13 people allocate more than

16 %. 34 people doing business allocate 10-15 % and 4 people allocate more than 16 %.

25 people doing agro work allocate 10-15 % and 8 people allocate more than 16 %.

4.4.3 Family income:

Cereals & pulses * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

cereals & pulses

6-10 % 26 20 0 4610-15 % 46 68 11 125more than 16 %

6 23 0 29

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of cereals & pulses and income of

respondent, 46 people from income slab of 71 to 150 thousand allocate 10-15 % and 6

people allocate more than 16 %. 68 people from the income slab of 151000-300000

allocate 10-15 % and 23 people allocate more than 16 %, 11 people from the income

having more than 3lakh allocate 10 to 15 % and 8 person allocate more than 16 %.

4.5 How you allocate your family budget for cereals and pulses in year 2009?


4.5.1 Sex:

Cereals & pulses * Sex Cross tabulation


cereals & pulses 0-5 2 1 36-10 6 2 810-15 82 24 106more than 16 78 5 83

Total 168 32 200

Findings:

Here cross tabulation is between budget allocation of cereals & pulses and sex of

respondents, majority of males allocate 10 to 15 % to cereals & pulses that is 82 while 78

of male allocate more than 16%. Twenty four female allocate 10 to 15 % to cereals &

pulses while five of female allocate more than 16%.

4.5.2 Occupation:

Cereals & pulses * Occupation Cross tabulation

Occupation TotalService Business Profession

alFarmer

cereals & pulses

0-5 1 2 0 0 36-10 4 0 0 4 810-15 44 30 4 28 106more than 16

43 19 9 12 83

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of cereals & pulses and occupation of

respondents, forty four people doing service allocate 10 to 15 % and forty three people

allocate more than 16 %. Thirty people doing business allocate 10 to 15 % and nineteen

people allocate more than 16 %. Twenty eight people doing agro work allocate 10 to 15

% and twelve people allocate more than 16 %.


Cereals & pulses * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

cereals & pulses

0-5 3 0 0 36-10 6 2 0 810-15 50 52 4 106more than 16 19 57 7 83

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of cereals & pulses and income of

respondents, fifty people from income slab of 71 to 150 thousand allocate 10 to 15 % and

nineteen people allocate more than 16 %. Fifty two people from the income slab of 1.5 to

3 lacs allocate 10 to 15 % and fifty seven person allocate more than 16 %,

4.5.4 Family members:


Cereals & pulses * No of person in family Cross tabulation


6cereals & pulses

0-5 0 2 1 0 36-10 0 4 4 0 810-15 4 31 61 10 106more than 16

4 30 33 16 83

Total 8 67 99 26 200

Findings:

In the above cross tabulation between family member of respondent and their budget

allocation to cereal and pulses. Thirty one and thirty respondents with 3-4 family

members allocate 10-15%, more than sixteen percentages respectively. While in family

of 5-6 member sixty one and thirty three allocate 10-15% and more than 16%. While

family with more than six family member sixteen respondents allocate more than sixteen

percentages.

4.6 How you allocate your family budget for grocery in year 2008?


4.6.1 Sex:

Grocery * Sex Cross tabulation


Grocery 6-10 13 0 1310-15 115 30 145more than 16 40 2 42

Total 168 32 200

Findings:

Here cross tabulation is between budget allocation of Grocery and sex of respondents,

majority of males allocate 10 to 15 % to Grocery that is one hundred fifteen while forty

of male allocate more than 16%. Thirty female allocate 10 to 15 % to Grocery while two

of female allocate more than 16%.

4.6.2 Occupation:

Grocery * Occupation Cross tabulation

Occupation Total Service Busines

sProfessional

Farmer

Grocery 6-10 6 2 1 4 13 10-15 63 39 9 34 145 more

than 1623 10 3 6 42

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of Grocery and occupation of

respondents, sixty three people doing service allocate 10 to 15 % and twenty three people

allocate more than 16 %. Thirty nine people doing business allocate 10 to 15 % and ten

people allocate more than 16 %. Thirty four people doing agro work allocate 10 to 15 %

and six people allocate more than 16 %.


Grocery * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Grocery 6-10 6 6 1 1310-15 64 75 6 145more than 16

8 30 4 42

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of Grocery and income of

respondents, sixty four people from income slab of 71 to 150 thousand allocate 10 to 15

% and eight people allocate more than 16 %. Seventy five people from the income slab

of 1.5 to 3 lakh allocate 10 to 15 % and thirty person allocate more than 16 %,

4.7 How you allocate your family budget for grocery in year 2009?


4.7.1 Sex:

Grocery * Sex Cross tabulation


Grocery 0-5 0 2 26-10 4 2 610-15 71 18 89more than 16 93 10 103

Total 168 32 200

Findings:

Here cross tabulation is between budget allocation of Grocery and sex of respondents,

majority of males allocate 10 to 15 % to Grocery that is seventy one while ninety three of

males allocate more than 16%. Eighteen females allocate 10 to 15 % to Grocery while

ten of female allocate more than 16%.

4.7.2 Occupation:

Grocery * Occupation Cross tabulation


sProfessional

Farmer

Grocery 0-5 0 2 0 0 2 6-10 3 2 0 1 6 10-15 37 20 9 23 89 more

than 1652 27 4 20 103

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of Grocery and occupation of

respondent, thirty seven people doing service allocate 10 to 15 % and fifty two people

allocate more than 16 %. twenty people doing business allocate 10 to 15 % and twenty

seven person allocate more than 16 %. Twenty three people doing agro work allocate 10

to 15 % and twenty allocate more than 16 %.


Grocery * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Grocery 0-5 2 0 0 26-10 4 1 1 610-15 49 38 2 89more than 16 23 72 8 103

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of Grocery and income of

respondents, forty nine people from income slab of 71 to 150 thousand allocate 10 to 15

% and twenty three people allocate more than 16 %. Thirty eight people from the income

slab of 1.5 to 3 lakh allocate 10 to 15 % and seventy two person allocate more than 16 %,

4.8 How you allocate your family budget for edible oil in year 2008?


4.8.1 Sex:

Edible oil * Sex Cross tabulation


Edible oil 0-5 54 6 606-10 110 26 13610-15 4 0 4

Total 168 32 200

Findings:

Cross tabulation is between budget allocation of edible oil and sex of respondents, 54

males allocate 0 to 5 % to edible oil while 110 of males allocate 6 to 10 %. Six female

allocate 0 to 5 % to edible oil while 26 of females allocate 6 to 10%.

4.8.2 Occupation:

Edible oil * Occupation Cross tabulation


Edible oil

0-5 30 10 4 16 606-10 60 39 9 28 13610-15 2 2 0 0 4

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of edible oil and occupation of

respondents, thirty people doing service allocate 0 to 5 % and sixty people allocate 6 to

10 %. Ten people doing business allocate 0 to 5 % and thirty nine persons allocate 6 to

10 %. Sixteen people doing agro work allocate 0 to 5 % and twenty eight allocate 6 to10

%.


Edible oil * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Edible oil 0-5 16 43 1 606-10 60 66 10 13610-15 2 2 0 4

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of edible oil and income of

respondent, sixteen people from income slab of 71 to 150 thousand allocate 0 to 5 % and

sixty people allocate 6 to 10 %. Forty three people from the income slab of 1.5 to 3 lakh

allocate 0 to 5 % and sixty six people allocate 6 to 10%.

4.9 How you allocate your family budget for edible oil in year 2009?


4.9.1 Sex:



Edible oil 0-5 59 7 666-10 102 24 12610-15 5 0 516-20 2 1 3

Total 168 32 200

Findings:

Cross tabulation is between budget allocation of edible oil and sex of respondents, 59

males allocate 0 to 5 % to edible oil while 102 of males allocate 6 to 10 %. Seven

females allocate 0 to 5 % to edible oil while 24 of females allocate 6 to 10%.

4.9.2 Occupation:



Edible oil

0-5 35 16 3 12 666-10 53 31 10 32 12610-15 3 2 0 0 516-20 1 2 0 0 3

Total 92 51 13 44 200

Findings:


Here cross tabulation is between budget allocation of edible oil and occupation of

respondent, thirty five people doing service allocate 0 to 5 % and fifty three people

allocate 6 to 10 %. Sixteen people doing business allocate 0 to 5 % and thirty one

persons allocate 6 to 10 %. Twelve people doing agro work allocate 0 to 5 % and thirty

two allocate 6 to10 %.

4.9.3 Income:


Income Total

71000-150000

151000-300000

more than 300000

Edible oil

0-5 15 46 5 666-10 58 63 5 12610-15 2 2 1 516-20 3 0 0 3

Total 78 111 11 200

Findings:

Here cross tabulation is between budget allocation of edible oil and income of

respondent, fifteen people from income slab of 71 to 150 thousand allocate 0 to 5 % and

fifty eight people allocate 6 to 10 %. Forty six people from the income slab of 1.5 to 3

lakh allocate 0 to 5 % and sixty three people allocate 6 to 10%.

4.10 How you allocate your family budget for Vegetables and Fruits in year 2008?


4.10.1 Sex:

Vegetables and fruits * Sex Cross tabulation


Vegetables and fruits

0-5 69 4 736-10 99 26 12510-15 0 2 2

Total 168 32 200

Findings:

From the above cross tabulation we have found that, from 200 respondents around 62 %

are allocating 6-10 % from their total expenditures. 37 % respondents are allocating 0-5

% for their vegetables and fruits. And remains 1 % respondents allocate between 10-15

% from their total budget. From 62 % who are allocating for 6-10 %, 99 are male and 26

are female respondents.

4.10.2 Occupation:

Vegetables and fruits * Occupation Cross tabulation



0-5 40 18 4 11 736-10 50 33 9 33 12510-15 2 0 0 0 2

Total 92 51 13 44 200

Findings:

From the total respondents 46% are doing service, 25 % are doing Business, 6 % are

professionals and 22 % remains are farmers.



Vegetables and fruits * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000


0-5 16 52 5 736-10 60 59 6 12510-15 2 0 0 2

Total 78 111 11 200

Findings:

From the total 200 respondents 39 % people are belongs to 71000-150000 yearly family

income. Another 55 % belongs to 151000-300000 yearly family income and around 5 %

belongs to more than 300000 rupee family income. From 62 % respondents who

allocating 6-10 % budget for vegetables and fruits, 60 respondents are belongs to 71000-

150000 range of yearly family income and 52 respondents belongs to 151000-300000

range of yearly family income.

4.11 How you allocate your family budget for Vegetables and Fruits in year 2009?

4.11.1 Sex:





0-5 64 5 696-10 102 27 12910-15 2 0 2

Total 168 32 200

Findings:



% for their vegetables and fruits. And remains 1 % respondents allocate between 10-15

% from their total budget. From 65 % who are allocating for 6-10 %, 102 are male and

27 are female respondents.

4.11.2 Occupation:




0-5 40 19 3 7 696-10 50 32 10 37 12910-15 2 0 0 0 2

Total 92 51 13 44 200

Findings:






Income Total

71000-150000

151000-300000

more than 300000


0-5 16 52 5 736-10 60 59 6 12510-15 2 0 0 2

Total 78 111 11 200

Findings:




allocating 6-10 % budget for vegetables and fruits, 60 respondents are belongs to 71000-

150000 range of yearly family income and 52 respondents belongs to 151000-300000

range of yearly family income.

4.12 How you allocate your family budget for Milk & related products in year 2008?

4.12.1 Sex:


Milk * Sex Cross tabulation


Milk 0-5 16 2 186-10 150 30 18010-15 2 0 2

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures. 9 % respondents are allocating 0-5 %

for their vegetables and fruits. And remains 1 % respondents allocate between 10-15 %

from their total budget. From 60 % who are allocating for 6-10 %, 150 are male and 30


4.12.2 Occupation:

Milk * Occupation Cross tabulation


Milk 0-5 8 1 2 7 186-10 82 50 11 37 18010-15 2 0 0 0 2

Total 92 51 13 44 200

Findings:




Milk * Income Cross tabulation


Income Total

71000-150000 151000-300000

more than 300000

Milk 0-5 9 7 2 186-10 69 102 9 18010-15 0 2 0 2

Total 78 111 11 200

Findings:




allocating 6-10 % budget for milk and related products, 69 respondents are belongs to

71000-150000 range of yearly family income and 102 respondents belongs to 151000-

300000 range of yearly family income and 9 respondents belongs to more than 300000.

4.13 How you allocate your family budget for Milk & related products in year 2009?

4.13.1 Sex:


Milk * Sex Cross tabulation


Milk 0-5 16 2 186-10 150 30 18010-15 2 0 2

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures. 9 % respondents are allocating 0-5 %

for their vegetables and fruits. And remains 1 % respondents allocate between 10-15 %

from their total budget. From 60 % who are allocating for 6-10 %, 150 are male and 30


4.13.2 Occupation:

Milk * Occupation Cross tabulation


Milk 0-5 8 1 2 7 186-10 82 50 11 37 18010-15 2 0 0 0 2

Total 92 51 13 44 200

Findings:




Milk * Income Cross tabulation


Income Total

71000-150000 151000-300000

more than 300000

Milk 0-5 9 7 2 186-10 69 102 9 18010-15 0 2 0 2

Total 78 111 11 200

Findings:




allocating 6-10 % budget for milk and related products, 69 respondents are belongs to



4.14 How you allocate your family budget for LPG in year 2008?

4.14.1 Sex:

LPG * Sex Cross tabulation



LPG 0-5 127 15 1426-10 41 17 58

Total 168 32 200

Findings:



% for their vegetables and fruits. From 60 % who are allocating for 0-5 %, 127 are male

and 15 are female respondents.

4.14.2 Occupation:

LPG * Occupation Cross tabulation


LPG 0-5 65 35 12 30 1426-10 27 16 1 14 58

Total 92 51 13 44 200

Findings:


professionals and 22 % remains are farmers. From total 200 respondents 142 are

allocating 0-5 % and 58 respondents are allocating 6-10 %.


LPG * Income Cross tabulation


Income Total

71000-150000 151000-300000

more than 300000

LPG 0-5 42 91 9 1426-10 36 20 2 58

Total 78 111 11 200

Findings:




allocating 0-5 % budget for LPG, 42 respondents are belongs to 71000-150000 range of

yearly family income and 92 respondents belongs to 151000-300000 range of yearly

family income and 9 respondents belongs to more than 300000.

4.15 How you allocate your family budget for LPG in year 2009?

4.15.1 Sex:


LPG * Sex Cross tabulation


LPG 0-5 135 22 1576-10 33 10 43

Total 168 32 200

Findings:



% for their vegetables and fruits. From 78 % who are allocating for 0-5 %, 135 are male

and 22 are female respondents.

4.15.2 Occupation:

LPG * Occupation Cross tabulation


LPG 0-5 77 38 11 31 1576-10 15 13 2 13 43

Total 92 51 13 44 200

Findings:





LPG * Income Cross tabulation


Income Total

71000-150000 151000-300000

more than 300000

LPG 0-5 54 92 11 1576-10 24 19 0 43

Total 78 111 11 200

Findings:




allocating 0-5 % budget for LPG, 54 respondents are belongs to 71000-150000 range of

yearly family income and 92 respondents belongs to 151000-300000 range of yearly

family income and 11 respondents belongs to more than 300000.

4.16 How you allocate your family budget for Phone & Electricity bills in year 2008?

4.16.1 Sex:


Phone and Electricity bills * Sex Cross tabulation


Phone an 0-5 118 30 1486-10 50 2 52

Total 168 32 200

Findings:



% for their Phone and Electricity bills. From 74 % who are allocating for 0-5 %, 118 are

male and 30 are female respondents.

4.16.2 Occupation:

Phone and Electricity bills * Occupation Cross tabulation


Phone and ele.

0-5 68 34 10 36 1486-10 24 17 3 8 52

Total 92 51 13 44 200

Findings:





Phone and Electricity bills * Income Cross tabulation


Income Total

71000-150000 151000-300000

more than 300000

Phone and ele.

0-5 60 78 10 1486-10 18 33 1 52

Total 78 111 11 200

Findings:




allocating 0-5 % budget for Phone and Electricity bills, 60 respondents are belongs to



4.17 How you allocate your family budget for Phone & Electricity bills in year 2009?

4.17.1 Sex:


Phone and Electricity bills * Sex Cross tabulation

Sex Total

Male FemalePhone and Ele.

0-5 129 29 1586-10 39 2 4110-15 0 1 1

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures and 1 % is allocating 10-15 % from

their total expenditures. 79 % respondents are allocating 0-5 % for their Phone and

Electricity bills. From 79 % who are allocating for 0-5 %, 129 are male and 29 are

female respondents.

4.17.2 Occupation:

Phone and Electricity bills * Occupation Cross tabulation


Phone and ele.

0-5 78 34 11 35 1586-10 14 17 1 9 4110-15 0 0 1 0 1

Total 92 51 13 44 200

Findings:



allocating 0-5 %, 41 respondents are allocating 6-10 % and 1 respondent is allocating 10-

15 %.


Phone and Electricity bills * Income Cross tabulation


Income Total

71000-150000

151000-300000

more than 300000

Phone and ele.

0-5 60 89 9 1586-10 18 21 2 4110-15 0 1 0 1

Total 78 111 11 200

Findings:




allocating 0-5 % budget for Phone and Electricity bills, 60 respondents are belongs to

71000-150000 range of yearly family income, 89 respondents belongs to 151000-300000

range of yearly family income and 9 respondents belongs to more than 300000.

4.18 How you allocate your family budget for Transportation in year 2008?

4.18.1 Sex:

Transportation * Sex Cross tabulation



Transportation 0-5 131 24 1556-10 31 6 3710-15 2 0 216-20 4 2 6

Total 168 32 200

Findings:



their total expenditures. 77 % respondents are allocating 0-5 % for and 3 % are allocating

16-20 % for transportation. From 77 % who are allocating for 0-5 %, 131 are male and


4.18.2 Occupation:

Transportation * Occupation Cross tabulation


Transportation

0-5 75 38 10 32 1556-10 15 9 1 12 3710-15 2 0 0 0 216-20 0 4 2 0 6

Total 92 51 13 44 200

Findings:



allocating 0-5 %, 37 respondents are allocating 6-10 %, 2 respondents are allocating 10-

15 % and 6 respondents are allocating 16-20 %.


Transportation * Income Cross tabulation


Income Total

71000-150000

151000-300000

more than 300000

Transportation

0-5 53 92 10 1556-10 19 17 1 3710-15 2 0 0 216-20 4 2 0 6

Total 78 111 11 200

Findings:




allocating 0-5 % budget for Phone and Electricity bills,53 respondents are belongs to

71000-150000 range of yearly family income, 92 respondents belongs to 151000-300000

range of yearly family income and 10 respondents belongs to more than 300000.

4.19 How you allocate your family budget for Transportation in year 2009?

4.19.1 Sex:


Transportation * Sex Cross tabulation


Transportation 0-5 146 24 1706-10 12 3 1510-15 4 0 416-20 6 5 11

Total 168 32 200

Findings:




16-20 % for transportation. From 77 % who are allocating for 0-5 %, 131 are male and


4.19.2 Occupation:

Transportation * Occupation Cross tabulation

Occupation Total

Service Business Professional

Farmer

Transportation

0-5 80 40 12 38 1706-10 7 3 1 4 1510-15 2 1 0 1 416-20 3 7 0 1 11

Total 92 51 13 44 200

Findings:






4.19.3 Family Income:

Transportation * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Transportation

0-5 59 104 7 1706-10 8 6 1 1510-15 3 0 1 416-20 8 1 2 11

Total 78 111 11 200

Findings:




allocating 0-5 % budget for Phone and Electricity bills,59 respondents are belongs to

71000-150000 range of yearly family income, 104 respondents belongs to 151000-


4.20 How you allocate your family budget for Education in year 2008?

4.20.1 Sex:


Education * Sex Cross tabulation


Education 0-5 21 6 276-10 44 0 4410-15 27 5 3216-20 76 21 97

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures and 16 % are allocating 10-15 % from

their total expenditures. 14 % respondents are allocating 0-5 % for and 48 % are

allocating 16-20 % for Education. From 48 % who are allocating for 16-20 %, 76 are


4.20.2 Occupation:

Education * Occupation Cross tabulation


Education

0-5 10 11 2 4 276-10 24 9 4 7 4410-15 16 9 1 6 3216-20 42 22 6 27 97

Total 92 51 13 44 200

Findings:







Education * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Education 0-5 13 13 1 276-10 11 29 4 4410-15 6 22 4 3216-20 48 47 2 97

Total 78 111 11 200

Findings:




allocating 16-20 % budget for Education, 48 respondents are belongs to 71000-150000

range of yearly family income, 47 respondents belongs to 151000-300000 range of

yearly family income and 2 respondents belongs to more than 300000.

4.20.4 No. of Children Studying in Family:


Education * No of Children studying Cross tabulation

No of Children studying Total1-2 More than 2

Education 0-5 26 1 276-10 42 2 4410-15 26 6 3216-20 87 10 97

Total 181 19 200

Findings:

97 respondents are allocating their 16-20 % expenditure behind Education. From that 97

respondents 87 has 1-2 children studying in family and 10 respondents has more than 2

children studying in family.

4.21 How you allocate your family budget for Education in year 2009?


4.21.1 Sex:

Education * Sex Cross tabulation


Education 0-5 24 6 306-10 32 2 3410-15 37 7 4416-20 75 17 92

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures and 22 % are allocating 10-15 % from

their total expenditures. 15 % respondents are allocating 0-5 % for and 46 % are

allocating 16-20 % for Education. From 46 % who are allocating for 16-20 %, 75 are


4.21.2 Occupation:

Education * Occupation Cross tabulation

OccupationTotalService Business Professional Farmer

Education

0-5 15 9 2 4 306-10 20 9 1 4 3410-15 25 7 5 7 4416-20 32 26 5 29 92

Total 92 51 13 44 200

Findings:






4.21.3 Family Income:

Education * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Education 0-5 17 9 4 306-10 4 27 3 3410-15 10 32 2 4416-20 47 43 2 92

Total 78 111 11 200

Findings:




allocating 16-20 % budget for Education, 47 respondents are belongs to 71000-150000



4.21.4 No. of Children Studying in Family:


Education * No of Children studying Cross tabulation

No of Children studying Total1-2 More than 2

Education 0-5 27 3 306-10 32 2 3410-15 41 3 4416-20 81 11 92

Total 181 19 200

Findings:

92 respondents are allocating their 16-20 % expenditure behind Education. From those

92 respondents 81 has 1-2 children studying in family and 11 respondents have more

than 2 children studying in family.

4.22 How you allocate your family budget for Entertainment in year 2008?


4.22.1 Sex:

Entertainment * Sex Cross tabulation


Entertainment 0-5 122 19 1416-10 40 11 5110-15 1 1 216-20 5 1 6

Total 168 32 200

Findings:




16-20 % for Entertainment. From 70 % who are allocating for 0-5 %, 122 are male and


4.22.2 Occupation:

Entertainment * Occupation Cross tabulation

Occupation Total

Service Business Professional Farmer

Entertain

ment

0-5 61 40 8 32 141

6-10 29 8 4 10 51

10-15 1 0 1 0 2

16-20 1 3 0 2 6

Total 92 51 13 44 200

Findings:







Entertainment * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Entertainment

0-5 54 80 7 1416-10 19 28 4 5110-15 0 2 0 216-20 5 1 0 6

Total 78 111 11 200

Findings:




allocating 0-5 % budget for Entertainment, 54 respondents are belongs to 71000-150000



4.22.4 No. of persons in family:


Entertainment * No of person in family Cross tabulation


6Entertainment

0-5 4 44 75 18 1416-10 4 20 19 8 5110-15 0 1 1 0 216-20 0 2 4 0 6

Total 8 67 99 26 200

Findings:

141 Respondents are allocating 0-5 % of total expenditure for Entertainment. From that

141 respondents 4 persons has 1-2 family members, 44 persons has 3-4 family members,

75 persons has 5-6 family members and 18 people has more than 6 family members in

the family. 51 respondents allocate 6-10 % expenditure.

4.23 How you allocate your family budget for Entertainment in year 2009?


4.23.1 Sex:

Entertainment * Sex Cross tabulation


Entertainment 0-5 140 29 1696-10 26 2 2810-15 2 1 3

Total 168 32 200

Findings:



their total expenditures. 85 % respondents are allocating 0-5 % for Entertainment. From

85 % who are allocating for 0-5 %, 140 are male and 29 are female respondents.

4.23.2 Occupation:

Entertainment * Occupation Cross tabulation


Entertainment

0-5 76 45 9 39 1696-10 14 6 4 4 2810-15 2 0 0 1 3

Total 92 51 13 44 200

Findings:



allocating 0-5 %, 28 respondents are allocating 6-10 %, and 3 respondents are allocating

11-15 %.



Entertainment * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Entertainment

0-5 73 88 8 1696-10 4 21 3 2810-15 1 2 0 3

Total 78 111 11 200

Findings:








Entertainment * No of person in family Cross tabulation


No of person in family Total1-2 3-4 5-6 more than 6

Entertainment

0-5 6 59 86 18 1696-10 2 8 11 7 2810-15 0 0 2 1 3

Total 8 67 99 26 200

Findings:





4.24 How you allocate your family budget for other items in year 2008?


4.24.1 Sex:

Others * Sex Cross tabulation


Others 0-5 80 14 946-10 67 16 8310-15 17 0 1716-20 4 2 6

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures, 9 % are allocating 10-15 %, and 6 %


% for Other items. From 42 % who are allocating for 0-5 %, 84 are male and 14 are

female respondents.

4.24.2 Occupation:

Others * Occupation Cross tabulation


Others 0-5 36 20 6 32 946-10 42 22 7 12 8310-15 10 7 0 0 1716-20 4 2 0 0 6

Total 92 51 13 44 200

Findings:




allocating 0-5 %, 83 respondents are allocating 6-10 %,17 respondents are allocating 11-



Others * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Others 0-5 45 44 5 946-10 25 53 5 8310-15 4 12 1 1716-20 4 2 0 6

Total 78 111 11 200

Findings:









Others * No of person in family Cross tabulation


Others 0-5 4 28 49 13 946-10 3 29 39 12 8310-15 1 9 6 1 1716-20 0 1 5 0 6

Total 8 67 99 26 200

Findings:

94 Respondents are allocating 0-5 % of total expenditure for Entertainment. From that 94

respondents 4 persons has 1-2 family members, 28 persons has 3-4 family members, 49

persons has 5-6 family members and 13 people has more than 6 family members in the

family. 83 respondents allocate 6-10 % expenditure.

4.25 How you allocate your family budget for other items in year 2009?


4.25.1 Sex:

Others * Sex Cross tabulation


Others 0-5 139 28 1676-10 20 4 2410-15 7 0 716-20 2 0 2

Total 168 32 200

Findings:


are allocating 6-10 % from their total expenditures, 3 % are allocating 10-15 %, and 1 %

is allocating 16-20 % from their total expenditures. 42 % respondents are allocating 0-5

% for other items. From 84 % who are allocating for 0-5 %, 139 are male and 28 are

female respondents.

4.25.2 Occupation:

Others * Occupation Cross tabulation


Others 0-5 73 42 11 41 1676-10 13 8 1 2 2410-15 5 0 1 1 716-20 1 1 0 0 2

Total 92 51 13 44 200

Findings:




allocating 0-5 %, 24 respondents are allocating 6-10 %,7 respondents are allocating 11-



Others * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Others 0-5 67 94 6 1676-10 7 14 3 2410-15 3 2 2 716-20 1 1 0 2

Total 78 111 11 200

Findings:









Others * No of person in family Cross tabulation


Others 0-5 4 55 88 20 1676-10 2 10 8 4 2410-15 1 1 3 2 716-20 1 1 0 0 2

Total 8 67 99 26 200

Findings:






4.26 ANOVA table for Income of family and allocation of budget 2008 (Sig. Level 5 %)

Sum of Squares df

Mean Square F Sig.

cereals & pulses

Between Groups 3.764 2 1.882 5.313 .006Within Groups 69.791 197 .354Total 73.555 199

Grossary Between Groups 1.854 2 .927 3.731 .026Within Groups 48.941 197 .248Total 50.795 199

Edible oil Between Groups 2.068 2 1.034 4.404 .013Within Groups 46.252 197 .235Total 48.320 199



Milk Between Groups .347 2 .174 1.862 .158Within Groups 18.373 197 .093Total 18.720 199

LPG Between Groups 3.763 2 1.881 9.905 .000Within Groups 37.417 197 .190Total 41.180 199

Phone an Between Groups .536 2 .268 1.390 .251Within Groups 37.944 197 .193Total 38.480 199

Transportation Between Groups 3.157 2 1.578 3.964 .021Within Groups 78.438 197 .398Total 81.595 199

Entertainment Between Groups .666 2 .333 .766 .466Within Groups 85.689 197 .435Total 86.355 199

Education Between Groups 3.577 2 1.789 1.436 .240Within Groups 245.418 197 1.246Total 248.995 199

Others Between Groups 1.354 2 .677 1.185 .308Within Groups 112.521 197 .571Total 113.875 199

Findings:

The above table shows the results of allocation of budget like milk and related products, phone and electricity bills, entertainment, education and others accept the null hypothesis. So, there is no significant relationship between Income of family and allocation of budget. But the factors like cereals and pulses, Grocery, Edible oil,


Vegetables and fruits, LPG, Transportation rejects the null hypothesis, and hence, there is a significant relation among them.

4.27 ANOVA Table: Income of family and budget allocation 2009 (Sig. Level 5 %)

Sum of Squares

df Mean Square

F Sig.

cereals & pulses Between Groups 8.530 2 4.265 11.890 .000Within Groups 70.665 197 .359Total 79.195 199

Grocery Between Groups 9.509 2 4.754 14.578 .000Within Groups 64.246 197 .326Total 73.755 199




Milk Between Groups 2.323 2 1.161 11.628 .000Within Groups 19.677 197 .100Total 22.000 199

LPG Between Groups 1.392 2 .696 4.236 .016Within Groups 32.363 197 .164Total 33.755 199

Phone an Between Groups .038 2 .019 .105 .900Within Groups 35.717 197 .181Total 35.755 199

Transportation Between Groups 10.926 2 5.463 10.409 .000Within Groups 103.394 197 .525Total 114.320 199

Education Between Groups 8.418 2 4.209 3.490 .032Within Groups 237.562 197 1.206Total 245.980 199

Entertainment Between Groups 1.130 2 .565 3.365 .037Within Groups 33.090 197 .168Total 34.220 199

Others Between Groups 1.972 2 .986 2.993 .052Within Groups 64.903 197 .329Total 66.875 199


Findings:

The above table shows the results of allocation of budget like phone and electricity bills and others accept the null hypothesis. So, there is no significant relationship between Income of family and allocation of budget. But the factors like cereals and pulses, Grocery, Edible oil, Vegetables and fruits, Milk and related products, LPG, Transportation, Education and Entertainment rejects the null hypothesis, and hence, there is a significant relation among them.


4.28 Reliability test for food products affected by inflation with the help of

Cronbach's Alpha model:

Reliability Statistics

Cronbach's Alpha N of Items.728 5

Findings:

This is a model of internal consistency, based on the average inter-item correlation. The

value is greater than 0.7 so there is internal consistency and also inter item correlation in

them.


4.29 How cereals and pulses are affected by inflation?

4.29.1 Sex:

Cereals and Pulses * Sex Cross tabulation


Cereals and Pulses

Highly affected 98 8 106Affected 39 13 52Average affected 28 9 37Low affected 3 2 5

Total 168 32 200

Findings:

From 200 respondents 53 % are highly affected by inflation in the case of cereals and

pulses. 26 % are affected by inflation. From 53 % respondents who are highly affected,

98 are male and 8 are female respondents.

a. Chi Square test: (Sig. Level 5%)

Ho: inflation affects the Cereals and Pulses is independent to sex

H1: inflation affects the Cereals and Pulses is dependent to sex

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 12.820(a) 3 .005

a. 6 cells (37.5%) have expected less than 5. The minimum expected is .33.

The significance level is .005 and that is lower than the significance level we have

assumed in the case. So reject the null hypothesis.


4.29.2 Occupation:

Cereals and Pulses * Occupation Cross tabulation

Occupation TotalService Business Professiona

lFarmer

Cereals and Pulses

highly affected

50 26 9 21 106

affected 24 12 4 12 52average 14 12 0 11 37low affected 4 1 0 0 5

Total 92 51 13 44 200

Findings:

From 53 % respondents who are highly affected, 50 are doing service, 26 are doing

business, 9 are professionals and 21 are farmers.


Ho: inflation affects the Cereals and Pulses is independent to Occupation

H1: inflation affects the Cereals and Pulses is dependent to Occupation


Pearson Chi-Square 8.593(a) 9 .476a. 6 cells (37.5%) have expected less than 5. The minimum expected is .33.

Findings:

Accept the null hypothesis because it is more than .05 in this case. People views are

same in this case. Different people have different views regarding inflation. From 53 %

respondents who are highly affected, 50 are doing service, 26 are doing business, 9 are

professionals and 21 are farmers.



Cereals and Pulses * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Cereals and Pulses

highly affected

25 71 10 106

affected 30 21 1 52average 21 16 0 37low affected 2 3 0 5

Total 78 111 11 200


Ho: inflation affects the Cereals and Pulses is independent to Family income

H1: inflation affects the Cereals and Pulses is dependent to Family income



a. 5 cells (41.7%) have expected less than 5. The minimum expected is .28.

Findings:

Reject the null hypothesis because it is lower than the .05 in this case. From 200

respondents 53 % are highly affected by inflation in the case of cereals and pulses. 26 %

are affected by inflation.


4.30 How sugar & jaggary are affected by inflation?

4.30.1 Sex:

Sugar and Jaggary * Sex Cross tabulation


Sugar and Jaggary

highly affected 77 7 84affected 49 10 59average 30 11 41low affected 11 4 15very low affected

1 0 1

Total 168 32 200


Ho: inflation affects the Sugar and Jaggary is independent to sex

H1: inflation affects the Sugar and Jaggary is dependent to sex



Findings:

Accept the null hypothesis because in this case the significance level is more than the

defined significance level. People views are matching in this case.


4.30.2 Occupation:

Sugar and Jaggary * Occupation Cross tabulation

Occupation TotalService Business Profession

alFarmer

Sugar and Jaggary

highly affected

39 19 8 18 84

affected 28 15 3 13 59average 17 12 2 10 41low affected

7 5 0 3 15

very low affected

1 0 0 0 1

Total 92 51 13 44 200


Ho: inflation affects the Sugar and Jaggary is independent to Occupation

H1: inflation affects the Sugar and Jaggary is dependent to Occupation



Findings:


same in this case.



Sugar and Jaggary * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Sugar and Jaggary

highly affected

18 57 9 84

affected 22 36 1 59average 30 11 0 41low affected 8 7 0 15very low affected

0 0 1 1

Total 78 111 11 200


Ho: inflation affects the Sugar and Jaggary is independent to Family income

H1: inflation affects the Sugar and Jaggary is dependent to Family income



Findings:

Reject the null hypothesis. Here people views are very different with each other.


4.31 How edible oil is affected by inflation?

4.31.1 Sex:


Sex Total

Male FemaleEdible oil highly affected 20 6 26

affected 99 11 110average 29 8 37low affected 19 7 26very low affected

1 0 1

Total 168 32 200


Ho: inflation affects the Edible oil is independent to sex

H1: inflation affects the Edible oil is dependent to sex



Findings:


same in this case.


4.31.2 Occupation:


Occupation Total


Farmer

Edible oil highly affected

16 3 3 4 26


9 9 0 8 26

very low affected

1 0 0 0 1

Total 92 51 13 44 200


Ho: inflation affects the Edible oil is independent to Occupation

H1: inflation affects the Edible oil is dependent to Occupation



Findings:


same in this case.




Income Total

71000-150000

151000-300000

more than 300000

Edible oil highly affected

15 11 0 26


0 0 1 1

Total 78 111 11 200


Ho: inflation affects the Edible oil is independent to Family income

H1: inflation affects the Edible oil is dependent to Family income



Findings:

Here all respondents have different view point regarding this case. So reject the null

hypothesis.


4.32 How vegetables and fruits are affected by inflation?

4.32.1 Sex:


Sex Total

Male FemaleVegetables and fruits

highly affected 41 2 43affected 73 7 80average 33 15 48low affected 21 8 29

Total 168 32 200


Ho: inflation affects the Vegetables and fruits are independent to Sex

H1: inflation affects the Vegetables and fruits are dependent to Sex


Pearson Chi-Square 18.452(a) 3 .000a. 1 cell (12.5%) has expected less than 5. The minimum expected is 4.64.

Findings:


hypothesis.


4.32.2 Occupation:


Occupation Total

Service Business

Professional

Farmer


highly affected

25 11 3 4 43


9 11 2 7 29

Total 92 51 13 44 200


Ho: inflation affects the Vegetables and fruits are independent to Occupation

H1: inflation affects the Vegetables and fruits are dependent to Family Occupation



a. 3 cells (18.8%) have expected less than 5. The minimum expected is 1.89.

Findings:


same in this case.




Income Total

71000-150000

151000-300000

more than 300000


highly affected

7 34 2 43

affected 22 50 8 80average 29 18 1 48low affected 20 9 0 29

Total 78 111 11 200


Ho: inflation affects the Vegetables and fruits are independent to Family income

H1: inflation affects the Vegetables and fruits are dependent to Family income


Pearson Chi-Square 37.283(a) 6 .000a. 4 cells (33.3%) have expected less than 5. The minimum expected is 1.60.

Findings:


hypothesis.


4.33 How milk and related products are affected by inflation?

4.33.1 Sex:

Milk and Related Products * Sex Cross tabulation

Sex Total

Male FemaleMilk and Related Products

highly affected 67 2 69affected 37 8 45average 43 15 58low affected 19 5 24very low affected 2 2 4

Total 168 32 200


Ho: inflation affects the Milk and Related Products are independent to Sex

H1: inflation affects the Milk and Related Products are dependent to Sex



Findings:


hypothesis.

4.33.2 Occupation:


Milk and Related Products * Occupation Cross tabulation

Occupation Total


Farmer

Milk and Related Products

highly affected

35 24 4 6 69


8 7 0 9 24

very low affected

2 2 0 0 4

Total 92 51 13 44 200


Ho: inflation affects the Milk and Related Products are independent to Occupation

H1: inflation affects the Milk and Related Products are dependent to Occupation



Findings:


hypothesis.



Milk and Related Products * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000


highly affected

12 54 3 69


2 2 0 4

Total 78 111 11 200


Ho: inflation affects the Milk and Related Products are independent to Family income

H1: inflation affects the Milk and Related Products are dependent to Family income



Findings:


hypothesis.

4.34 Monthly expenditure behind Cereals and pulses in rupees in 2008


4.34.1 Sex:

Serial and Pulses * Sex Cross tabulation

Sex Total

Male FemaleCereal and Pulses

0-500 17 5 22501-1000 142 26 1681001-1500 9 1 10

Total 168 32 200

Findings:

From total 200 respondents more that 80 % people spend between the range of 501-1000

rupee behind cereals and pulses while 5 % people spend between the ranges of 1001-

1500. In the range of 501-1000 142 are male while 26 are female respondents.

4.34.2 Occupation:

Cereal and Pulses * Occupation Cross tabulation


sProfession

alFarmer

Cereal and Pulses

0-500 14 4 1 3 22

501-1000 74 47 12 35 168 1001-

15004 0 0 6 10

Total 92 51 13 44 200

Findings:



1500. In the range of 501-1000 74 are doing service, 47 are doing business, 12 are

professionals and 35 are farmers.



Cereal and Pulses * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Cereal and Pulses

0-500 10 9 3 22501-1000 62 98 8 1681001-1500 6 4 0 10

Total 78 111 11 200

Findings:



1500. In the range of 501-1000, 62 has income between the ranges of 71000-150000

rupee, 98 has income between the ranges of 151000-300000 rupee and 3 has income

more than 300000 rupee.

4.35 Monthly expenditure behind Cereals and pulses in rupees in 2009


4.35.1 Sex:

Cereal and Pulses * Sex Cross tabulation

Sex Total

Male FemaleCereal and Pulses

0-500 20 4 24501-1000 128 25 1531001-1500 16 3 191501-2000 4 0 4

Total 168 32 200

Findings:


rupee behind cereals and pulses, 10 % people spend between the ranges of 1001-1500

and 2 % respondents spend between the ranges of 1501-2000 rupee. In the range of 501-

1000 128 are male while 25 are female respondents.

4.35.2 Occupation:


Occupation Total


Farmer

Cereal and Pulses

0-500 13 7 0 4 24501-1000 72 40 13 28 1531001-1500 4 3 0 12 191501-2000 3 1 0 0 4

Total 92 51 13 44 200

Findings:


rupee behind cereals and pulses, 10 % people spend between the ranges of 1001-1500

and 2 % respondents spend between the ranges of 1501-2000 rupee. In the range of 501-

1000 72 are doing service, 40 are doing business, 13 are professionals and 28 are

farmers.




Income Total

71000-150000

151000-300000

more than 300000

Cereal and Pulses

0-500 12 9 3 24501-1000 57 91 5 1531001-1500 7 9 3 191501-2000 2 2 0 4

Total 78 111 11 200

Findings:



1500. In the range of 501-1000, 57 have income between the ranges of 71000-150000

rupee, 91 have income between the ranges of 151000-300000 rupee and 5 have income

more than 300000 rupee.

4.36 Monthly expenditure behind Sugar and jaggary in rupees in 2008


4.36.1 Sex:


Sex

TotalMale FemaleSugar and Jaggary

0-500 166 32 198501-1000 2 0 2

Total 168 32 200

Findings:

In the above cross tabulation the between sex of respondent and their consumption of

the sugar and jaggary where in the majority of the male and female respondent is below

the Rs. 500. Only two respondents are having usage of more than Rs. 500. While all

female are having usage of below Rs. 500.

4.36.2 Occupation:


Occupation


Sugar and Jaggary

0-500 92 51 13 42 198501-1000

0 0 0 2 2

Total 92 51 13 44 200

Findings:

The above calculation shows that cross tabulation between occupation of respondent and

their usage of the sugar and jaggary. All service, professional and business person

respondent are having usage for below Rs. 500. The farmer of only two respondent

having the usage of the more than Rs. 500.




Income

Total71000-150000

151000-300000

more than 300000

Sugar and Jaggary

0-500 76 111 11 198501-1000 2 0 0 2

Total 78 111 11 200

Findings:

In the above cross tabulation between yearly income of respondent and their usage of

the sugar and jaggary. The people having income of 150000 and above having the usage

of the below Rs. 500. While respondent who are having income of the 71000-150000 are

only two having usage of the more than Rs. 500 for a month.


Sugar and Jaggary * No of person in family Cross tabulation

No of person in family

Total1-2 3-4 5-6more than 6

Sugar and Jaggary

0-500 8 67 97 26 198501-1000

0 0 2 0 2

Total 8 67 99 26 200

Findings:

In the above cross tabulation between No. of family member in family’s of respondent

and their usage of the sugar and jaggary. Majority of the family having the usage of the

sugar and jaggary is below Rs. 500. But two family with having the family size of the 5-

6 are using more than Rs. 500 after sugar and jaggary.

4.37 Monthly expenditure behind Sugar and jaggary in rupees in 2009

4.37.1 Sex:



Sex Total Male Female Sugar and Jaggary

0-500157 32 189

501-1000 11 0 11Total 168 32 200

Findings: In the above cross tabulation the between sex of respondent and their

consumption of the sugar and jaggary where in the majority of the male and female

respondent is below the Rs. 500. Only eleven male respondents are having usage of more

than Rs. 500. While all female are having usage of below Rs. 500.

4.37.2 Occupation:


Occupation


Sugar and Jaggary

0-500 89 47 13 40 189501-1000

3 4 0 4 11

Total 92 51 13 44 200

Findings:


their usage of the sugar and jaggary. Majority of service, professional and business

person respondent are having usage for below Rs. 500. The farmer of only four

respondents having the usage of the more than Rs. 500. In service person and business

person respectively three and four family are having usage of more than Rs. 500.




Income

Total71000-150000

151000-300000

more than 300000

Sugar and Jaggary

0-500 74 105 10 189501-1000 4 6 1 11

Total 78 111 11 200

Findings:

In the above cross tabulation between yearly income of respondent and their usage of the

sugar and jaggary. Majority people having income of 150000 and above having the

usage of the below Rs. 500 but only seven family having the usage of the Rs more than

500. While respondent who are having income of the 71000-150000 are only four having

usage of the more than Rs. 500 for a month





Sugar and Jaggary

0-500 8 61 95 25 189501-1000 0 6 4 1 11

Total 8 67 99 26 200

Findings:



sugar and jaggary is below Rs. 500. But eleven family with having the family size of the

3-4, 5-6, are using more than Rs. 500 after sugar and jaggary.

4.38 Monthly expenditure behind Edible oil in rupees in 2008

4.38.1 Sex:



Sex

TotalMale FemaleEdible oil 0-500 114 28 142

501-1000 54 4 58Total 168 32 200

Findings:


edible oil where in the majority of the male and female respondent is below the Rs. 500.

Only fifty four male respondents are having usage of more than Rs. 500. While four

female respondent are having usage of more than Rs. 500.

4.38.2 Occupation:


Occupation

TotalService Business Professional FarmerEdible oil

0-500 60 30 13 39 142501-1000 32 21 0 5 58

Total 92 51 13 44 200

Findings:


their usage of the edible oil. Majority of service, professional and business person

respondent are having usage for below Rs. 500. The farmer of only five respondents

having the usage of the more than Rs. 500. In service person and business person

respectively thirty three and twenty one family are having usage of more than Rs. 500.




Income

Total71000-150000

151000-300000

more than 300000

Edible oil 0-500 69 69 4 142501-1000 9 42 7 58

Total 78 111 11 200

Findings:


edible oil. Majority people having income of 150000 and above having the usage of the

below Rs. 500 but forty nine family having the usage of the Rs more than 500. While

respondent who are having income of the 71000-150000 are only nine having usage of

the more than Rs. 500 for a month.


Edible oil * No of person in family Cross tabulation



Edible oil

0-500 8 51 72 11 142501-1000

0 16 27 15 58

Total 8 67 99 26 200

Findings:


and their usage of the edible oil. Majority of the family having the usage of the edible oil

is below Rs. 500. But sixteen and sixteen and twenty two family with having the family

size of the 3-4, 5-6, are using more than Rs. 500 after edible oil.

4.39 What is Monthly expenditure behind Edible oil in rupees in 2009?

4.39.1 Sex:



Sex


501-1000 58 5 63Total 168 32 200

Findings:


edible oil where in the thirty two percentage of the male and female respondent is below

the Rs. 500. Only fifty eight male respondents are having usage of more than Rs. 500.

While five female respondent are having usage of more than Rs. 500.

4.39.2 Occupation:


Occupation


0-500 62 32 12 31 137501-1000 30 19 1 13 63

Total 92 51 13 44 200

Findings:



respondent are having usage for below Rs. 500. The farmer of thirteen respondent having

the usage of the more than Rs. 500. In service person and business person respectively

thirty and nineteen family are having usage of more than Rs. 500.



Income Total


71000-150000

151000-300000

more than 300000

Edible oil 0-500 62 71 4 137501-1000 16 40 7 63

Total 78 111 11 200

Findings:



below Rs. 500 but forty seven family having the usage of the Rs more than 500. While

respondent who are having income of the 71000-150000 are only sixteen having usage of

the more than Rs. 500 for a month.




Total1-2 3-4 5-6 more than 6Edible oil

0-500 8 48 69 12 137501-1000 0 19 30 14 63

Total 8 67 99 26 200

Findings:



is below Rs. 500. But nineteen and thirty family with having the family size of the 3-4,

5-6, are using more than Rs. 500 after edible oil. Fourteen Family having more than 6

member are having usage of the more than Rs. 500.

4.40 Monthly expenditure behind Vegetables in rupees in 2008

4.40.1 Sex:



Sex Total Male Female Vegetables and fruits

0-500158 30 188

501-1000 10 0 10 1001-1500 0 2 2Total 168 32 200

Findings:


vegetable and fruits where in the majority the male and female respondent is below the

Rs. 500. Only ten male respondents are having usage of more than Rs. 500. While two

female respondent are having usage of more than Rs. 1000.

4.40.2 Occupation:


Occupation



0-500 87 46 13 42 188501-1000 5 3 0 2 101001-1500 0 2 0 0 2

Total 92 51 13 44 200

Findings:


their usage of the vegetable and fruits. Majority of service, professional and business

person respondent are having usage for below Rs. 500. The farmer of two respondents

having the usage of the more than Rs. 500. In service person and business person

respectively five and three family are having usage of more than Rs. 500. In business two

person having the usage of more than 1000.




Income

Total71000-150000

151000-300000

more than 300000


0-500 72 108 8 188501-1000 4 3 3 101001-1500 2 0 0 2

Total 78 111 11 200

Findings:


vegetable and fruits. Majority people having income of 150000 and above having the

usage of the below Rs. 500 but six family having the usage of the Rs more than 500 to

1000. While respondent who are having income of the 71000-150000 are only four

having usage of the more than Rs. 500-1000 for a month and two family having usage of

1000.


Vegetables and fruits * No of person in family Cross tabulation




0-500 8 65 92 23 188501-1000 0 2 5 3 101001-1500 0 0 2 0 2

Total 8 67 99 26 200

Findings:


and their usage of the vegetable and fruits. Majority of the family having the usage of the

vegetable and fruits is below Rs. 500. But ten family with having the family size of the

3-4, 5-6, are using more than Rs. 500 after vegetable and fruits. Two Family having 5- 6

members are having usage of the more than Rs. 1000.


4.41 Monthly expenditure behind Vegetables in rupees in 2009

4.41.1 Sex:



Sex

TotalMale FemaleVegetables and fruits

0-500 87 19 106501-1000 80 11 911001-1500 0 2 21501-2000 1 0 1

Total 168 32 200

Findings:



Rs. 500. Only eighty male and eleven female respondents are having usage of more than

Rs. 500. While two female respondent are having usage of more than Rs. 1000.

4.41.2 Occupation:


Occupation



0-500 46 19 8 33 106501-1000 46 29 5 11 911001-1500 0 2 0 0 21501-2000 0 1 0 0 1

Total 92 51 13 44 200

Findings:



person respondent are having usage for below Rs. 500. The business person of two

respondents having the usage of the more than Rs. 1000. In service person and business

person respectively forty six and twenty nine family are having usage of more than Rs.

500. In business one person having the usage of more than Rs. 1500.




Income

Total71000-150000

151000-300000

more than 300000


0-500 47 56 3 106501-1000 29 55 7 911001-1500 2 0 0 21501-2000 0 0 1 1

Total 78 111 11 200

Findings:



usage of the below Rs. 500 but sixty two family having the usage of the Rs more than

500 to 1000. While respondent who are having income of the 71000-150000 are only

twenty nine having usage of the more than Rs. 500-1000 for a month and two family

having usage of 1000.



No of person in family Total


1-2 3-4 5-6more than 6


0-500 7 38 51 10 106501-1000 1 29 46 15 911001-1500 0 0 2 0 21501-2000 0 0 0 1 1

Total 8 67 99 26 200

Findings:



vegetable and fruits is below Rs. 500. But twenty nine, forty six, fifteen family with

having the family size of the 3-4, 5-6, are using more than Rs. 500 after vegetable and

fruits respectively. Two Family having 5- 6 members are having usage of the more than

Rs. 1000.

4.42 Monthly expenditure behind Milk and related items in rupees in 2008

4.42.1 Sex:



Sex

TotalMale FemaleMilk and Related Products

0-500 7 1 8501-1000 61 16 771001-1500 51 13 641501-2000 48 2 50more than 2000 1 0 1

Total 168 32 200

Findings:


milk and related product where in the majority the male and female respondent is

spending Rs. 500-1000. Only fifteen male and thirteen female respondents are having

usage of Rs. 1000-1500. While forty eight male respondent are having usage of more

than Rs. 1500.

4.42.2 Occupation:


Occupation



0-500 3 1 2 2 8501-1000 29 15 7 26 771001-1500 30 16 2 16 641501-2000 29 19 2 0 50more than 2000

1 0 0 0 1

Total 92 51 13 44 200

Findings:


their usage of the milk and related product. Majority of service, professional and


business person respondent are having usage for below Rs. 500-1000. The business

people of sixteen respondents are having the usage of the more than Rs. 1000-1500. In

service person and business person respectively twenty nine and nineteen families are

having usage of more than Rs. 1500. In service person having the usage of more than Rs.

2000.



Income

Total71000-150000

151000-300000

more than 300000


0-500 4 2 2 8501-1000 32 42 3 771001-1500 40 22 2 641501-2000 2 44 4 50more than 2000

0 1 0 1

Total 78 111 11 200

Findings:


milk and related product. Majority people having income of 150000 and above having

the usage of the below Rs. 1500 but forty two family having the usage of the Rs more

than 500 to 1000. While respondent who are having income of the 71000-150000 are

only forty having usage of the more than Rs. 1000-1500 for a month and two family

having usage of more than1500.


Milk and Related Products * No of person in family Cross tabulation





0-500 2 2 2 2 8501-1000 6 30 34 7 771001-1500 0 15 43 6 641501-2000 0 20 20 10 50more than 2000

0 0 0 1 1

Total 8 67 99 26 200

Findings:


and their usage of the milk and related product. Majority of the family having the usage

of the milk and related product is Rs. 500-1000. But fifty eight family with having the

family size of the 3-4, 5-6, are using Rs. 1000- 1500 after milk and related product. One

Family having 5- 6 members are having usage of the more than Rs. 2000.

4.43 Monthly expenditure behind Milk and related items in rupees in 2009

4.43.1 Sex:



SexTotalMale Female


0-500 10 1 11501-1000 52 14 661001-1500 28 4 321501-2000 59 13 72more than 2000 19 0 19

Total 168 32 200

Findings:



spending Rs. 500-1000. Only twenty eight male and four female respondents are having

usage of Rs. 1000-1500. While fifty nine male respondent are having usage of more than

Rs. 1500.

4.43.2 Occupation:


Occupation



0-500 7 2 0 2 11501-1000 26 16 6 18 661001-1500 11 4 3 14 321501-2000 37 22 3 10 72more than 2000

11 7 1 0 19

Total 92 51 13 44 200

Findings:




business person respondent are having usage for below Rs. 1500-2000. The business

people of sixteen respondents are having the usage of the more than Rs. 500-1000. In

service person and business person respectively thirty seven and twenty two families are

having usage of more than Rs. 1500. Eleven service persons having the usage of more

than Rs. 2000.



Income

Total71000-150000

151000-300000

more than 300000


0-500 7 2 2 11501-1000 27 38 1 661001-1500 14 16 2 321501-2000 29 39 4 72more than 2000

1 16 2 19

Total 78 111 11 200

Findings:



the usage of the below Rs. 1500 but thirty two family having the usage of the Rs 500 to

1000. While respondent who are having income of the 71000-150000 are only forteen

having usage of the more than Rs. 1000-1500 for a month and two family having usage

of more than1500.







0-500 0 3 6 2 11501-1000 8 23 29 6 661001-1500 0 14 14 4 321501-2000 0 23 43 6 72more than 2000

0 4 7 8 19

Total 8 67 99 26 200

Findings:



of the milk and related product is Rs. 1500-2000. But thirty two families with having the

family size of the 3-4, 5-6, are using Rs. 1000- 1500 after milk and related product.

Seven Family having 5- 6 members are having usage of the more than Rs. 2000.

4.44 ANOVA Table: monthly expenditure of food products and family income 2008 (Sig. Level 5 %)


Sum of Squares

df Mean Square

F Sig.

Cerial and Pulses

Between Groups .529 2 .264 1.693 .187Within Groups 30.751 197 .156Total 31.280 199

Sugar and Jaggary







Findings:

The above table shows the results of expenditure behind food products like cereals and pulses and sugar & jaggary accept the null hypothesis. So, there is no significant relationship between Income of family and expenditure of food products. But the factors like Edible oil, Vegetables and fruits and Milk & related products rejects the null hypothesis, and hence, there is a significant relation among them.

4.45 ANOVA Table: monthly expenditure of food products and family income 2009 (Sig. Level 5 %)


Sum of Squares

df Mean Square

F Sig.

Cerial and Pulses

Between Groups .112 2 .056 .187 .829Within Groups 58.843 197 .299Total 58.955 199

Sugar and Jaggary






Between Groups 7.257 2 3.628 2.878 .059Within Groups 248.323 197 1.261Total 255.580 199

Findings:

The above table shows the results of expenditure behind food products like cereals and pulses, sugar & jaggary and Milk & related products accept the null hypothesis. So, there is no significant relationship between Income of family and expenditure of food products. But the factors like Edible oil and Vegetables and fruits reject the null hypothesis, and hence, there is a significant relation among them.

4.46 ANOVA Table: monthly expenditure of food products and sex 2008 (Sig. Level 5 %)


Sum of Squares

df Mean Square

F Sig.

Cereal and Pulses


Sugar and Jaggary







Findings:

The above table shows the results of expenditure behind food products like cereals and pulses, sugar & jaggary and Vegetables & fruits accept the null hypothesis. So, there is no significant relationship between Income of family and expenditure of food products. But the factors like Edible oil and Milk & related products reject the null hypothesis, and hence, there is a significant relation among them.

4.47 ANOVA Table: monthly expenditure of food products and sex 2009


(Sig. Level 5 %)

Sum of Squares

df Mean Square

F Sig.

Cerial and Pulses


Sugar and Jaggary


Edible oil Between Groups .960 1 .960 4.505 .035Within Groups 42.195 198 .213Total 43.155 199





Findings:

The above table shows the results of expenditure behind food products like cereals and pulses, sugar & jaggary, Vegetables & fruits and Milk & related products accept the null hypothesis. So, there is no significant relationship between Income of family and expenditure of food products. But the factor like Edible oil rejects the null hypothesis, and hence, there is a significant relation between them.

4.48 What is monthly consumption behind Cereals and pulses in 2008 (in K.G.)?


4.48.1 Sex:


Sex

TotalMale FemaleCerial and Pulses

0-20 146 31 17721-40 18 1 1941-60 2 0 261-80 2 0 2

Total 168 32 200

Findings:


cereal and pulses where in the majority the male and female respondent is below the

20kg. Only eighteen male and one female respondent are having usage of more than Rs.

20kg. While two female respondent are having usage of more than Rs. 40kg.

4.48.2 Occupation:


Occupation

TotalService Business Professional FarmerCerial and Pulses

0-20 88 44 13 32 17721-40 3 6 0 10 1941-60 0 0 0 2 261-80 1 1 0 0 2

Total 92 51 13 44 200

Findings:


their usage of the cereal and pulses. Majority of service, professional and business person

respondent are having usage for below 20kg. The business person of forty four

respondents having the usage of the less than 20kg. In service person and business

person respectively three and six family are having usage of 20- 40kg. In business one

person having the usage of more than 60 kg.




Income

Total71000-150000

151000-300000

more than 300000

Cereal and Pulses

0-20 69 100 8 17721-40 9 7 3 1941-60 0 2 0 261-80 0 2 0 2

Total 78 111 11 200

Findings:


cereal and pulses. Majority people having income of 150000 and above having the usage

of the below 20kg but seven family having the usage of the 21-40kg. While respondent

who are having income of the 71000-150000 are only nine having usage of the 21-40kg

for a month.


Cereal and Pulses * No of person in family Cross tabulation



Cereal and Pulses

0-20 8 64 86 19 17721-40 0 1 11 7 1941-60 0 0 2 0 261-80 0 2 0 0 2

Total 8 67 99 26 200

Findings:



and their usage of the cereal and pulses. Majority of the family having the usage of the

cereal and pulses is below 20kg. But one, eleven with having the family size of the 3-4,

5-6, are using more than 20kg after cereal and pulses respectively. Two Family having 5-

6 members are having usage of 41-60kg.

4.49 What is monthly consumption behind Cereals and pulses in 2009 (in K.G.)?


4.49.1 Sex:


Sex

TotalMale FemaleCereal and Pulses

0-20 149 29 17821-40 16 3 1961-80 2 0 2more than 80 1 0 1

Total 168 32 200

Findings:


cereal and pulses where in the majority the male and female respondent is below the

20kg. Only sixteen male and three female respondent are having usage of more than Rs.

20kg. While two male respondent are having usage of more than Rs. 40kg.

4.49.2 Occupation:


Occupation


Cereal and Pulses

0-20 86 45 13 34 17821-40 4 5 0 10 1961-80 1 1 0 0 2more than 80

1 0 0 0 1

Total 92 51 13 44 200

Findings:



their usage of the cereal and pulses. Majority of service, professional and business person

respondent are having usage for below 20kg. The business person of forty five

respondents having the usage of the less than 20kg. In service person and business

person respectively four and five family are having usage of 20- 40kg. In business one

person having the usage of more than 60 kg.



Income

Total71000-150000

151000-300000

more than 300000

Cerial and Pulses

0-20 69 101 8 17821-40 9 7 3 1961-80 0 2 0 2more than 80 0 1 0 1

Total 78 111 11 200

Findings:


cereal and pulses. Majority people having income of 150000 and above having the usage

of the below 20kg but seven family having the usage of the 21-40kg. While respondent

who are having income of the 71000-150000 are only nine having usage of the 21-40kg

for a month.


Cereal and Pulses * No of person in family Cross tabulation




Cereal and Pulses

0-20 8 65 85 20 17821-40 0 0 13 6 1961-80 0 2 0 0 2more than 80

0 0 1 0 1

Total 8 67 99 26 200

Findings:


and their usage of the cereal and pulses. Majority of the family having the usage of the

cereal and pulses is below 20kg. But eleven family with having the family size of the 5-

6, are using more than 20kg after cereal and pulses respectively. Six Family having 5- 6

members are having usage of 21-40kg.

4.50 Monthly consumption behind Sugar & jaggary in 2008 (in K.G.)

4.50.1 Sex:



Sex

TotalMale FemaleSugar and Jaggary

0-20 165 32 19721-40 3 0 3

Total 168 32 200

Findings:


sugar and jaggary where in the majority the male and female respondent is below the

20kg. Only three male respondent are having usage of more than Rs. 20kg. While 32

female respondent are having usage of below than Rs. 20kg.

4.50.2 Occupation:


Occupation

TotalService Business Professional FarmerSugar and Jaggary

0-20 91 51 13 42 19721-40

1 0 0 2 3

Total 92 51 13 44 200

Findings:



person respondent are having usage for below 20kg. The business person of fifty one

respondents having the usage of the less than 20kg. In service person and farmer

respectively four and five family are having usage of 20- 40kg.




Income

Total71000-150000

151000-300000

more than 300000

Sugar and Jaggary

0-20 78 108 11 19721-40 0 3 0 3

Total 78 111 11 200

Findings:



usage of the below 20kg but three family having the usage of the 21-40kg. While

respondent who are having income of the 71000-150000 none family having usage of the

21-40kg for a month.




1-2 3-4 5-6 more than 6

Sugar and Jaggary

0-20 8 67 96 26 19721-40 0 0 3 0 3

Total 8 67 99 26 200

Findings:



sugar and jaggary is below 20kg. But three families with having the family size of the 5-

6, are using more than 20kg after sugar and jaggary respectively. 96 Family having 5- 6

members are having usage of below 20kg.

4.51 What is monthly consumption behind Sugar & jaggary in 2009 (in K.G.)?


4.51.1 Sex:



Sugar and Jaggary

0-20 167 32 19921-40 1 0 1

Total 168 32 200

Findings:


sugar and jaggary where in the majority the male and female respondent is below the

20kg. Only one male respondent are having usage of more than Rs. 20kg. While 32

female respondent are having usage of below than Rs. 20kg.

4.51.2 Occupation:


Occupation

TotalService Business Professional FarmerSugar and Jaggary

0-20 91 51 13 44 19921-40 1 0 0 0 1

Total 92 51 13 44 200

Findings:



person respondent are having usage for below 20kg. The business person of fifty one

respondents having the usage of the less than 20kg. In service person only one family are

having usage of 20- 40kg.




Income

Total71000-150000

151000-300000

more than 300000

Sugar and Jaggary

0-20 78 110 11 19921-40 0 1 0 1

Total 78 111 11 200

Findings:



usage of the below 20kg but one family having the usage of the 21-40kg. While

respondent who are having income of the 71000-150000 none family having usage of the

21-40kg for a month.





Sugar and Jaggary

0-20 8 67 98 26 19921-40

0 0 1 0 1

Total 8 67 99 26 200

Findings:



sugar and jaggary is below 20kg. But one families with having the family size of the 5-6,

are using more than 20kg after sugar and jaggary respectively. 98 Family having 5- 6

members are having usage of below 20kg.

4.52 What is monthly consumption behind Edible oil in 2008 (in K.G.)?

4.52.1 Sex:



Sex


21-40 2 0 241-60 2 0 2

Total 168 32 200

Findings:


edible oil where in the majority of the male and female respondent is below the 20kg.

one hundred sixty four male respondents are having usage of less than 20kg. While all

thirty two female respondent are having usage of less than 20kg. only four male

respondent are having usage of more than 20kg.

4.52.2 Occupation:


Occupation


0-20 91 50 13 42 19621-40 1 1 0 0 241-60 0 0 0 2 2

Total 92 51 13 44 200

Findings:




respondent are having usage for below 20 kg. The farmer of only two respondents having

the usage of the more than 40 kg. In service person and business person respectively

ninety one and fifty families are having usage of less than 20kg.



Income

Total71000-150000

151000-300000

more than 300000

Edible oil

0-20 78 108 10 19621-40 0 1 1 241-60 0 2 0 2

Total 78 111 11 200

Findings:



below 20kg but only three family having the usage of the Rs more than 20kg. While

respondent who are having income of the 71000-150000 are only nine having usage of

the less than 20kg for a month.






0-20 8 67 97 24 19621-40 0 0 0 2 241-60 0 0 2 0 2

Total 8 67 99 26 200

Findings:



is below 20kg. But sixty seven and ninety seven families with having the family size of

the 3-4, 5-6, are using more than 20kg after edible oil. Two family having six member

using edible oil of 40kg a month.

4.53 What is monthly consumption behind Edible oil in 2009 (in K.G.)?

4.53.1 Sex:



Sex


21-40 1 0 1Total 168 32 200

Findings:


edible oil where in the one hundred ninety nine of the male and female respondent is

below the 20kg. Only one male respondents are having usage of more than 20kg. While

none female respondent are having usage of more than 20kg.

4.53.2 Occupation:


Occupation


0-20 92 50 13 44 19921-40 0 1 0 0 1

Total 92 51 13 44 200

Findings:



respondent are having usage for below 20kg. The farmer none respondents having the

usage of the more than Rs. 20kg. In service person and business person respectively only

one and none family are having usage of more than 20 kg.




Income

Total71000-150000

151000-300000

more than 300000

Edible oil

0-20 78 111 10 19921-40 0 0 1 1

Total 78 111 11 200

Findings:



below 20kg but one family having the usage of the Rs more than 500. While respondent

who are having income of the 71000-150000 are seventy eight having usage of the less

than 20kg for a month.





0-20 8 67 99 25 19921-40 0 0 0 1 1

Total 8 67 99 26 200

Findings:



is below Rs. 20kg. But sixty seven and ninety nine families with having the family size

of the 3-4, 5-6, are using more than 20kg after edible oil. One Family having more than 6

member are having usage of the more than 20kg.

4.54 Monthly consumption behind Vegetables and fruits in 2008 (in K.G.)


4.54.1 Sex:


Sex


0-20 99 22 12121-40 66 10 7641-60 1 0 161-80 1 0 1more than 80 1 0 1

Total 168 32 200

Findings:



20kg. Only sixty six male respondents are having usage of more than 20-40kg. While 3

male respondent are having usage of more than 40 kg.

4.54.2 Occupation:


Occupation



0-20 53 28 9 31 12121-40 37 22 4 15 7641-60 0 0 0 0 0

Total 90 51 13 46 200

Findings:



person respondent are having usage for below 20kg. The farmer of thirteen respondents

having the usage of the more than 40kg. In service person and business person


respectively thirty seven and twenty seven families are having usage of more than 40kg.

In business twenty two person having the usage of more than 20kg.



Income

Total71000-150000

151000-300000

more than 300000


0-20 51 68 2 12121-40 27 42 7 7641-60 0 0 1 161-80 0 0 1 1more than 80 0 1 0 1

Total 78 111 11 200

Findings:



usage of the below 20kg but seventy six family having the usage of the Rs more than 21-

40 kg. While respondent who are having income of the 71000-150000 are twenty seven

families having usage of the more than 20-40kg. for a month.






0-20 8 57 46 10 12121-40 0 10 52 14 7641-60 0 0 0 1 161-80 0 0 0 1 1more than 80

0 0 1 0 1

Total 8 67 99 26 200

Findings:




vegetable and fruits is below 20kg. But seventy six family with having the family size of

the 3-4, 5-6, are using more than 20-40kg. after vegetable and fruits. Two Family having

5- 6 members are having usage of the more than 40kg.


4.55 What is monthly consumption behind Vegetables and fruits in 2009 (in K.G.)?

4.55.1 Sex:


Sex


0-20 84 22 10621-40 81 10 9141-60 2 0 2more than 80 1 0 1

Total 168 32 200

Findings:


vegetable and fruits where in the majority the male and female respondent is below 20kg.

Only eighty one male and ten female respondents are having usage of 20-40kg. While

two male respondents are having usage of more than 40 kg.

4.55.2 Occupation:


Occupation



0-20 47 23 8 28 10621-40 44 28 5 14 9141-60 0 0 0 2 2more than 80

1 0 0 0 1

Total 92 51 13 44 200

Findings:



person respondent are having usage for below 20kg. The business person of twenty eight


respondents having the usage of the more than 20kg. In service person and farmer

respectively forty four and fourteen family are having usage of more than Rs. 500. In one

service person having the usage of more than 40kg.



Income

Total71000-150000

151000-300000

more than 300000


0-20 49 55 2 10621-40 29 53 9 9141-60 0 2 0 2more than 60 0 0 0 0

Total 78 111 11 200

Findings:



usage of the below 20kg but fifty three family having the usage of the 20-40kg. While

respondent who are having income of the 71000-150000 are only twenty nine having

usage of the more than 20kg for a month and two family having usage of 40kg in income

group of 150000-300000.






0-20 8 46 44 8 10621-40 0 21 52 18 9141-60 0 0 0 3 3more than 60

0 0 0 0 0

Total 8 67 99 26 200


Findings:



vegetable and fruits is below 20kg. But twenty one, fifty two, eighteen families with

having the family size of the 3-4, 5-6, more than 6 are using more than 20kgs after

vegetable and fruits respectively. Three family having more than 6 members are having

usage of the more than 40kg.


4.56 What is Monthly consumption behind Milk and related products in 2008 (in

ltrs.)?

4.56.1 Sex:


Sex


0-20 6 0 621-40 73 19 9241-60 24 4 2861-80 60 9 69more than 80 5 0 5

Total 168 32 200

Findings:



spending Rs. 20-40kg. Seventy male and nineteen female respondents are having usage

of 20-40ltr. While sixty male and nine respondents are having usage of more than sixty

liters.

4.56.2 Occupation:


Occupation



0-20 2 0 0 4 621-40 37 20 8 27 9241-60 12 8 3 5 2861-80 37 23 1 8 69more than 80

4 0 1 0 5

Total 92 51 13 44 200


Findings:



business person respondent are having usage of 21-40 liters. The business people of

twenty respondents are having the usage of the 21-40 liters. In service person and

business person respectively thirty seven and twenty three families are having usage of

more than Rs. 1500. In twelve service person having the usage of more than 40 liters.



Income Total

71000-150000

151000-300000

more than 300000


0-20 2 2 2 621-40 43 46 3 9241-60 16 12 0 2861-80 16 48 5 69more than 80

1 3 1 5

Total 78 111 11 200

Findings:



the usage of the between 20-60 liters but forty six families having the usage of the 21-40

liters. While respondent who are having income of the 71000-150000 are only forty three

having usage of the 21-40 liters for a month and two family having usage of less than 20

liters.







0-20 0 0 4 2 621-40 8 35 40 9 9241-60 0 9 19 0 2861-80 0 22 36 11 69more than 80

0 1 0 4 5

Total 8 67 99 26 200

Findings:



of the milk and related product is 20-40 kg. But thirty five, forty families with having

the family size of the 3-4, 5-6, are using 20-40 liters after milk and related product

respectively.


4.57 What is monthly consumption behind Milk and related products in 2009 (in

ltrs.)?

4.57.1 Sex:


Sex


0-20 4 0 421-40 68 19 8741-60 33 8 4161-80 59 5 64more than 80 4 0 4

Total 168 32 200

Findings:



spending 21-40 kg. Only sixty eight male and nineteen female respondents are having

usage of 21-40 liters. While fifty nine male respondent are having usage of more than

60liters.

4.57.2 Occupation:


Occupation



0-20 2 0 0 2 421-40 37 17 9 24 8741-60 20 10 2 9 4161-80 29 24 2 9 64more than 80

4 0 0 0 4

Total 92 51 13 44 200


Findings:



business person respondent are having usage for between 20-40 liters. The business

people of seventeen respondents are having the usage of the more than 20-40 liters. In

service person and business person respectively twenty nine and twenty four families are

having usage of 60 liters. Two service persons having the usage of below 20 liters.



Income

Total71000-150000

151000-300000

more than 300000


0-20 2 0 2 421-40 41 45 1 8741-60 24 16 1 4161-80 11 46 7 64more than 80

0 4 0 4

Total 78 111 11 200

Findings:



the usage of the between 21-40 kg but forty six family having the usage of the more than

sixty liters. While respondent who are having income of the 71000-150000 are only forty

one families are having usage of the more than 21-40 for a month and two family having

usage of less than 20 liters.







0-20 4 0 0 0 421-40 8 34 39 6 8741-60 0 13 26 2 4161-80 0 20 31 13 64more than 80

0 0 1 3 4

Total 12 67 99 26 200

Findings:



of the milk and related product is Rs. 21-40 liters. Thirty four, thirty nine families with

having the family size of the 3-4, 5-6, are using 21-40 after milk and related product.

Thirteen Family having 5- 6 members are having usage of the 60 liters a month.


4.58 ANOVA Table: monthly consumption of food products and sex 2008 (Sig. Level 5 %)

Sum of Squares

df Mean Square

F Sig.

Cereal and Pulses


Sugar and Jaggary


Edible oil Between Groups .034 1 .034 .694 .406Within Groups 9.786 198 .049Total 9.820 199





Findings:

The above table shows the results of Consumption of food products like cereals and pulses, sugar & jaggary, Edible oil, Vegetables & fruits and Milk & related products accept the null hypothesis. So, there is no significant relationship between Sex and Consumption of food.


4.59 ANOVA Table: monthly consumption of food products and sex 2008 (Sig. Level 5 %)

Sum of Squares

df Mean Square

F Sig.

Cereal and Pulses


Sugar and Jaggary

Between Groups .001 1 .001 .190 .664Within Groups .994 198 .005Total .995 199

Edible oil Between Groups .001 1 .001 .190 .664Within Groups .994 198 .005Total .995 199





Findings:

The above table shows the results of Consumption of food products like cereals and

pulses, sugar & jaggary, Edible oil and Vegetables & fruits accept the null hypothesis.

So, there is no significant relationship between Sex and Consumption of food. But the

factor like Milk & related Products rejects the null hypothesis, and hence, there is a

significant relation between them.


4.60 How inflation affected to hotels and restaurants expenses?

4.60.1 Sex:

Hotel and Restaurants * Sex Cross tabulation

Sex Total

Male FemaleHotel and Restaurants

highly affected 29 5 34Affected 69 19 88Average 60 8 68low affected 9 0 9very low affected 1 0 1

Total 168 32 200


Ho: inflation affects the Hotel and Restaurants are independent to Sex

H1: inflation affects the Hotel and Restaurants are dependent to Sex



Findings:


same in this case.


4.60.2 Occupation:

Hotel and Restaurants * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Hotel and Restaurants

highly affected

20 4 0 10 34

affected 32 22 10 24 88average 36 22 3 7 68low affected 4 3 0 2 9very low affected

0 0 0 1 1

Total 92 51 13 44 200


Ho: inflation affects the Hotel and Restaurants are independent to Occupation

H1: inflation affects the Hotel and Restaurants are dependent to Occupation



Findings:


hypothesis.



Hotel and Restaurants * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Hotel and Restaurants

highly affected 15 17 2 34affected 40 40 8 88average 22 45 1 68low affected 1 8 0 9very low affected

0 1 0 1

Total 78 111 11 200


Ho: inflation affects the Hotel and Restaurants are independent to Family income

H1: inflation affects the Hotel and Restaurants are dependent to Family



Findings:


same in this case.


4.61 How inflation affected to Theatres?

4.61.1 Sex:

Theatres * Sex Cross tabulation

Sex Total

Male FemaleTheatres highly affected 16 2 18

affected 54 16 70average 88 11 99low affected 8 3 11very low affected 2 0 2

Total 168 32 200


Ho: inflation affects the Theatres are independent to Sex

H1: inflation affects the Theatres are dependent to Sex



Findings:


hypothesis.


4.61.2 Occupation:

Theatres * Occupation Cross tabulation

Occupation Total


Farmer

Theatres highly affected

13 3 0 2 18


5 2 0 4 11

very low affected

1 0 0 1 2

Total 92 51 13 44 200


Ho: inflation affects the Theatres are independent to Occupation

H1: inflation affects the Theatres are dependent to Occupation



Findings:


same in this case.



Theatres * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Theatres highly affected

5 11 2 18


0 2 0 2

Total 78 111 11 200


Ho: inflation affects the Theatres are independent to Family income

H1: inflation affects the Theatres are dependent to Family income



Findings:


same in this case.


4.62 How inflation affected to Tours and travels?

4.62.1 Sex:

Tour and Travels * Sex Cross tabulation

Sex Total

Male FemaleTour and Travels

highly affected 26 7 33affected 51 11 62average 68 9 77low affected 20 5 25very low affected

3 0 3

Total 168 32 200


Ho: inflation affects the Tour and Travels are independent to Sex

H1: inflation affects the Tour and Travels are dependent to Sex



Findings:


same in this case.


4.62.2 Occupation:

Tour and Travels * Occupation Cross tabulation

Occupation Total


Farmer

Tour and Travels

highly affected

15 7 2 9 33


17 6 0 2 25

very low affected

0 0 0 3 3

Total 92 51 13 44 200


Ho: inflation affects the Tour and Travels are independent to Tour and travels

H1: inflation affects the Tour and Travels are dependent to Tour and travels



Findings:


hypothesis.



Tour and Travels * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Tour and Travels

highly affected

12 20 1 33


2 1 0 3

Total 78 111 11 200


Ho: inflation affects the tours and travel is independent to income

H1: inflation affects the tours and travel is dependent to income



Findings:


hypothesis.


4.63 What was your monthly expenditure behind hotels and restaurants in 2008?

4.63.1 Sex:

Hotel and restaurants * Sex Cross tabulation

Sex Total

Male FemaleHotel and restaurants

0-200 31 10 41201-400 37 4 41401-600 43 5 48601-800 15 3 18more than 800 42 10 52

Total 168 32 200

Findings:

From the total 200 respondents 21 % people are spending between 0-200 rupee behind

hotel and restaurants while 21 % people are also spending between 201-400 rupee. 24 %

people are spending 401-600 rupee behind hotels and restaurants and 26 % people are

spending more than 800 rupee in a month behind hotels and restaurants.

4.63.2 Occupation:

Hotel and restaurants * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Hotel and restaurants

0-200 13 13 4 11 41201-400 26 9 1 5 41401-600 21 7 3 17 48601-800 10 6 0 2 18more than 800

22 16 5 9 52

Total 92 51 13 44 200

Findings:

From the 26 % respondents who spends more than 800 rupee in a month behind hotels

and restaurants, 22 are doing service, 16 people are doing business, 5 people are

professionals while 9 people are farmers.



Hotel and restaurants * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000


0-200 25 16 0 41201-400 10 29 2 41401-600 21 24 3 48601-800 4 14 0 18more than 800 18 28 6 52

Total 78 111 11 200

Findings:


and restaurants, 18 people have family income between 71000-150000 while 28 people

have family income between 151000-300000 rupee and 6 people have family income

above 300000 rupee.


4.64 What was your monthly expenditure behind hotels and restaurants in 2009?

4.64.1 Sex:

Hotel and restaurants * Sex Cross tabulation

Sex Total

Male FemaleHotel and restaurants

0-200 34 13 47201-400 51 6 57401-600 30 5 35601-800 36 4 40more than 800 17 4 21

Total 168 32 200

Findings:

Here because of inflation the prices gone up in hotels and restaurants because of that

people transfers from higher level spending to lower spending behind hotels and

restaurants. Now 23 % people are spending between the range of 0-200 rupee monthly

while 28 % people spending 201-400 rupee and 20 % people are spending between the

ranges of 601-800 rupee per month. In the segment of more than 800 rupee per month

very few people are belonging.

4.64.2 Occupation:

Hotel and restaurants * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer


0-200 18 16 0 13 47201-400 28 10 2 17 57401-600 16 9 6 4 35601-800 21 6 3 10 40more than 800

9 10 2 0 21

Total 92 51 13 44 200


Findings:

From the 28 % respondents who spends 201-400 rupee per month behind hotel and

restaurants, 28 people are doing service, 10 people are doing business, and 2 people are

professionals while 17 people are farmers.


Hotel and restaurants * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000


0-200 25 21 1 47201-400 21 36 0 57401-600 14 20 1 35601-800 13 20 7 40more than 800 5 14 2 21

Total 78 111 11 200

Findings:


and restaurants, 21 people have family income between 71000-150000 while 36 people

have family income between 151000-300000 rupee and 0 people have family income

above 300000 rupee.


4.65 What was your monthly expenditure behind Theatres in 2008?

4.65.1 Sex:


Sex Total

Male FemaleTheatres 0-200 118 27 145

201-400 25 4 29401-600 24 1 25more than 800 1 0 1

Total 168 32 200

Findings:

Above 70 % people are spending between the ranges of 0-200 rupee per moth behind

theatres. From that 73 % people 118 are male respondents while 27 are female.

4.65.2 Occupation:


Occupation Total


Farmer

Theatres 0-200 69 35 7 34 145201-400 8 9 4 8 29401-600 15 6 2 2 25more than 800

0 1 0 0 1

Total 92 51 13 44 200

Findings:

From above 70 % people who spend between 0-200 rupee per moth behind theatres, 69

respondents are doing service, 35 people are doing business, 7 people are professionals

and 34 people are farmers.




Income Total

71000-150000

151000-300000

more than 300000

Theatres 0-200 62 77 6 145201-400 12 13 4 29401-600 4 21 0 25more than 800

0 0 1 1

Total 78 111 11 200

Findings:

From the 73 % respondents who spend between 0-200 rupee in a month behind theatres,

62 people have family income between 71000-150000 while 77 people have family

income between 151000-300000 rupee and 6 people have family income above 300000

rupee.


4.66 What was your monthly expenditure behind Theatres in 2009?

4.66.1 Sex:


Sex Total

Male FemaleTheatres 0-200 107 31 138

201-400 51 1 52401-600 7 0 7601-800 2 0 2more than 800 1 0 1

Total 168 32 200

Findings:

69 % people are spending between the ranges of 0-200 rupee per moth behind theatres.

From that 69 % people 107 are male respondents while 31 are female. 26 % respondents

spend between 201-400 rupee. From that 26 % 51 are male and 1 is female respondent.

4.66.2 Occupation:


Occupation Total

Service Business

Professional

Farmer

Theatres 0-200 57 32 8 41 138201-400 31 15 5 1 52401-600 2 3 0 2 7601-800 1 1 0 0 2more than 800

1 0 0 0 1

Total 92 51 13 44 200

Findings:

From above 69 % people who spend between 0-200 rupee per moth behind theatres, 57

respondents are doing service, 32 people are doing business, 8 people are professionals

and 41 people are farmers.




Income Total

71000-150000

151000-300000

more than 300000

Theatres 0-200 69 64 5 138201-400 7 41 4 52401-600 2 5 0 7601-800 0 0 2 2more than 800

0 1 0 1

Total 78 111 11 200

Findings:

From the 69 % respondents who spend between 0-200 rupee in a month behind theatres,

69 people have family income between 71000-150000 while 64 people have family

income between 151000-300000 rupee and 5 people have family income above 300000

rupee.


4.67 Has your transportation expenditure got affected by inflation?

4.67.1 Sex:

Transportation Exp. affected by inflation * Sex Cross tabulation

Sex Total

Male FemaleTransportation Exp. affected by inflation

Yes 161 32 193No 7 0 7

Total 168 32 200

Findings:

From the total 200 respondents 193 has got affected by inflation in the case of

transportation. From that 193 respondents 161 are male and 32 are female respondents.

4.67.2 Occupation:

Transportation Exp. affected by inflation * Occupation Cross tabulation

Occupation Total


Farmer

Transportation Exp. affected by inflation

Yes 90 50 10 43 193No 2 1 3 1 7

Total 92 51 13 44 200

Findings:

From the 193 respondents who got affected by inflation in the case of transportation, 90

are doing service, 50 are doing business, 10 are professionals and 43 are farmers.



Transportation Exp. affected by inflation * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000

Transportation Exp. affected by inflation

Yes 76 107 10 193No 2 4 1 7

Total 78 111 11 200

Findings:

From the total 193 respondents 76 people have family income between 71000-150000

while 107 people have family income between 151000-300000 rupee and 10 people have

family income above 300000 rupee.


4.68 What is your monthly expenditure behind transportation in 2008?

4.68.1 Sex:

Expenditure behind transportation * Sex Cross tabulation

Sex Total

Male FemaleExpenditure behind transportation

0-300 13 3 16301-600 70 11 81601-900 36 9 45901-1200 28 6 34more than 1200 21 3 24

Total 168 32 200

Findings:

40 % people are spending between the ranges of 301-600 rupee per moth behind

transportation. From that 40 % people 70 are male respondents while 11 are female. 22

% respondents spend between 601-900 rupee. From that 26 % 36 are male and 9 are

female respondent.

4.68.2 Occupation:

Expenditure behind transportation * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Expenditure behind transportation

0-300 5 2 4 5 16301-600 36 23 2 20 81601-900 19 13 2 11 45901-1200 20 5 1 8 34more than 1200

12 8 4 0 24

Total 92 51 13 44 200

Findings:

From the 40 % respondents who spends 301-600 rupee behind transportation monthly,

36 are doing service, 23 are doing business, 2 are professionals and 20 are farmers.


4.69 What is your monthly expenditure behind transportation in 2009?

4.69.1 Sex:

Expenditure behind transportation * Sex Cross tabulation

Sex Total

Male FemaleExpenditure behind transportation

0-300 13 3 16301-600 42 6 48601-900 81 18 99901-1200 18 0 18more than 1200 14 5 19

Total 168 32 200

Findings:

From the total 200 respondents 50 % are spending between 601-900 rupee behind

transportation monthly. From that 50 % people 81 are male and 18 are female.

4.69.2 Occupation:

Expenditure behind transportation * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Expenditure behind transportation

0-300 5 2 4 5 16301-600 19 11 2 16 48601-900 50 28 1 20 99901-1200 10 6 2 0 18more than 1200

8 4 4 3 19

Total 92 51 13 44 200

Findings:

From the 50 % people who spend 601-900 rupee behind transportation, 50 people are

doing service, 28 are doing business, 1 is professional and 16 are farmers.


4.70 Have you started use of electronic equipments which lower your bills?

4.70.1 Sex:

Use of electronic equipments * Sex Cross tabulation

Sex Total

Male FemaleUse of electronic equipments

yes 149 29 178no 19 3 22

Total 168 32 200

Findings:

From the total 200 respondents 178 people have started use of electronic equipments

which lower your bills.

4.70.2 Occupation:

Use of electronic equipments * Occupation Cross tabulation

Occupation Total


Farmer

Use of electronic equipments

yes 84 49 9 36 178no 8 2 4 8 22

Total 92 51 13 44 200

Findings:

From the 178 respondents 84 people are doing service, 49 people are doing business, 9

are professionals and 36 are farmers.


4.71 Have you disconnected your landline connection because of fixed cost?

4.71.1 Sex:

Disconnected Land line connections * Sex Cross tabulation

Sex Total

Male FemaleDisconnected Land line connections

yes 123 28 151no 45 4 49

Total 168 32 200

Findings:

From the total 200 respondents 151 people have disconnected their landline connection

because of fixed cost.

4.71.2 Occupation:

Disconnected Land line connections * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Disconnected Land line connections

yes 66 39 9 37 151no 26 12 4 7 49

Total 92 51 13 44 200

Findings:

From the 151 people who have disconnected their landline connection 66 are doing

service, 39 are doing business, 9 are professionals and 37 are farmers.


4.72 How frequently do you shop in a month? (In 2008)

4.72.1 Sex:

Frequency of Shopping in 2008 * Sex Cross tabulation

Sex Total

Male FemaleFrequency of Shopping in 2008

Once 32 14 46Twice 74 5 79Thrice 27 2 29More than thrice 35 11 46

Total 168 32 200

Findings:

In 2008 40 % people were shopping twice in a month while 23 % people were shopping

once and more than thrice in a month.


4.73 How frequently do you shop in a month? (In 2009)

4.73.1 Sex:

Frequency of Shopping in 2009 * Sex Cross tabulation

Sex Total

Male FemaleFrequency of Shopping in 2009

once 67 14 81twice 57 7 64thrice 30 8 38more than thrice 14 3 17

Total 168 32 200

Findings:

In 2009 people have transferred from thrice and more than thrice segment to once. 41 %

people are going for shopping once in a month while 32 % people are going for shopping

twice in a month.


4.74 What is your yearly expenditure behind branded wear? (In 2008)

4.74.1 Sex:

Branded Wear * Sex Cross tabulation

Sex Total

Male FemaleBranded Wear 0-1000 47 12 59

1001-2000 42 3 452001-3000 42 7 493001-4000 16 8 24more than 4000 21 2 23

Total 168 32 200

Findings:

30 % people are spending 0-1000 rupee behind branded wears while 22 % & 24 %

people are spending 1001-2000 & 2001-3000 respectively behind branded wear.

4.7.42 Occupation:

Branded Wear * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Branded Wear

0-1000 25 13 4 17 591001-2000 26 13 1 5 452001-3000 27 9 2 11 493001-4000 4 10 4 6 24more than 4000

10 6 2 5 23

Total 92 51 13 44 200

Findings:

From the 30 % respondents who are spending 0-1000 rupee behind branded wear, 25 are

doing service, 13 are doing business, 4 are professionals and 17 are farmers.


4.75 What is your yearly expenditure behind branded wear? (In 2009)

4.75.1 Sex:

Branded Wear * Sex Cross tabulation

Sex Total

Male FemaleBranded Wear 0-1000 35 14 49

1001-2000 48 4 522001-3000 53 12 653001-4000 21 2 23more than 4000 11 0 11

Total 168 32 200

Findings:

In 2009 33 % respondents are spending 2001-3000 rupee behind branded wears while 25

% & 26 % people are spending 0-1000 & 1001-2000 rupee respectively behind branded

wears.

4.75.2 Occupation:

Branded Wear * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Branded Wear

0-1000 19 15 2 13 491001-2000 30 6 3 13 522001-3000 26 21 4 14 653001-4000 11 7 3 2 23more than 4000

6 2 1 2 11

Total 92 51 13 44 200Findings:

From 33 % who are spending 2001-3000 behind branded wears, 19 are doing service, 15

are doing business, 2 are professionals and 13 are farmers.


4.76 Have you applied any remedial measure to cope up with inflation?

25%

20%25%

16%

12%3%

Remidies to cope up with inflationbuy in bulk buy in small quinty DiscountBrand switching Minimize Consumption Add. Source of Income

Findings:

Majority of the people are started buying in bulk quantity and started buying in diss.

Many people has started buying in small quantity too in opposition of buying in bulk

quantity. 12% of the people are lower the consumption of different commodities.


4.77 Have you put any effort to increase your family income?

4.77.1 Sex:

Efforts to increase family income * Sex Cross tabulation

Sex Total

Male FemaleEfforts to increase family income

yes 147 31 178no 21 1 22

Total 168 32 200

Findings:

From the total 200 respondents 178 people have put efforts to increase their family

income.

4.77.2 Occupation:

Efforts to increase family income * Occupation Cross tabulation

Occupation Total

Service Business

Professional

Farmer

Efforts to increase family income

yes 84 40 10 44 178no 8 11 3 0 22

Total 92 51 13 44 200

Findings:

From 178 respondents 84 are doing service, 40 are doing business, 10 are professionals

and 44 are farmers.



Efforts to increase family income * Income Cross tabulation

Income Total

71000-150000

151000-300000

more than 300000


yes 76 92 10 178no 2 19 1 22

Total 78 111 11 200

Findings:

From 178 respondents 76 are belonging to 71000-150000 rupee family income, 92 are

belonging to 15000-300000 rupee family income and 10 are belonging to more than

300000 rupee family income who are putting efforts to increase their income.


Efforts to increase family income * No of person in family Cross tabulation


1-2 3-4 5-6 more than 6


yes 6 55 95 22 178no 2 12 4 4 22

Total 8 67 99 26 200

Findings:

From the total 178 respondents 6 people have 1-2 family members, 55 have 3-4

members, 95 people have 5-6 members in family and 22 people have more than 6

members in family.

4.78 How you have increased your income?


27%

15%

23%

30%

5%

source of additional incomeinvestment of saving Job started by other pearson part time jobovertime other

Findings:

As the inflation result in the increase in price people need more money to satisfied the

necessity. For that many people used different option to raise their income like part time

job, overtime, investment of saving etc. majority of the people are started overtime that is

thirty percent. While 27% has started investing in the different investment alternatives

too. Twenty three percent people have started part-time jobs.

4.79 What is your monthly saving? (In 2008)


4.79.1 Sex:

Savings in 2008 * Sex Cross tabulation

Sex Total

Male FemaleSavings in 2008 2501-5000 21 5 26

5001-7500 57 15 727501-10000 59 8 67more than 10000

31 4 35

Total 168 32 200

Findings:

36 % respondents have monthly savings between 5001-7500 rupee monthly while 34 %

respondents have saving between the range of 7501-10000 rupee per month.


4.80 What is your monthly saving? (In 2008)

4.80.1 Sex:

Savings in 2009 * Sex Cross tabulation

Sex Total

Male FemaleSavings in 2009 0-2500 4 2 6

2501-5000 48 4 525001-7500 62 21 837501-10000 30 1 31more than 10000

24 4 28

Total 168 32 200

Findings:

42 % people have saving between the range of 5001-7500 while 26 % people have

saving of 2501-5000 rupee per month.


4.81 How you are investing saving in different alternatives?

27%

33%

17%

12%

10%

1%

prefered investment optionInsurance share and stock postal Invst FD Govt Sec. Gold and Silver

Findings:

People who are investing their savings in a different investment alternative majority

people are prefer to invest In the security market by investing in the share and stocks.

Thirty three percentage people are investing in the security market to generate return on

their saving. While twenty seven percent people are investing in the insurance and

seventeen percentages are investing in a postal schemes. While people who are prefer

fixed return are investing government instrument and fixed deposits too. Only one

percentage are investing in precious metal because they need larger amount.


4.82 Are you satisfied with actions taken by government to control the inflation?

4.82.1 Sex:

Action taken by government * Sex Cross tabulation

Sex Total

Male Femaleaction taken by government

Strongly satisfied 10 5 15satisfied 36 16 52Moderate 51 5 56Dissatisfied 66 5 71Strongly Dissatisfied

5 1 6

Total 168 32 200

Findings:

35 % people are dissatisfied with the actions taken by government while 28 % & 26 %

people are moderate & satisfied respectively.


Ho: action taken by government is independent to sex

H1: action taken by government is dependent to sex



Reject the null hypothesis because the value of significance level is lower than the

defined significance level.


CHAPTER 5

CO-RRELATION AND

REGRESSION

ANALYSIS OF

SECONDARY DATA


5.1 Relationship between Food grains (Serials and pulses) and Inflation:

COMM_NAME Food Grains(Cereals+Pulses) InflationINDX012001 171.0 5.1INDX022001 169.2 5INDX032001 169.8 5.5INDX042001 171.1 0.5INDX052001 173.0 0.9INDX062001 175.7 1.1INDX072001 175.6 1.3INDX082001 174.1 1.5INDX092001 173.3 1.6INDX102001 172.9 2INDX112001 172.4 1.8INDX122001 171.2 1.4INDX012002 168.9 0.9INDX022002 169.7 1.1INDX032002 170.7 1.6INDX042002 170.1 0.6INDX052002 169.9 0.7INDX062002 170.7 2.2INDX072002 172.6 2.7INDX082002 175.8 3.5INDX092002 177.1 3.3INDX102002 175.1 3.5INDX112002 175.9 3.5INDX122002 175.6 3.3INDX012003 175.2 4INDX022003 176.9 5INDX032003 177.3 6.5INDX042003 176.1 0.6INDX102002 177.0 3.6INDX062003 177.3 1INDX072003 177.5 0.5INDX082003 176.4 1INDX092003 175.9 2.2INDX102003 176.6 2.2INDX112003 176.0 2.6INDX122003 174.2 2.7INDX012004 176.4 3.9INDX022004 177.7 4.4INDX032004 175.4 4.6INDX042004 172.7 0.5INDX052004 173.2 1.3


INDX062004 174.1 3.3INDX072004 175.4 3.9INDX082004 178.7 4.9INDX092004 178.9 4.8INDX102004 179.0 5INDX112004 178.9 5.2INDX122004 179.3 4.5INDX012005 179.3 4.4INDX022005 180.2 4.8INDX032005 179.9 5.1INDX042005 179.1 1.4INDX052005 179.2 1.5INDX062005 182.1 2.5INDX072005 184.9 3INDX082005 185.6 3.2INDX092005 186.1 4.1INDX102005 187.0 4.6INDX112005 188.4 4.5INDX122005 189.3 4.1INDX012006 192.7 3.4INDX022006 194.4 3.9INDX032006 194.8 4.1INDX042006 194.5 1.2INDX052006 196.7 2.4INDX062006 198.4 3.2INDX072006 198.8 3.6INDX082006 201.0 4.4INDX092006 206.5 5.6INDX102006 210.6 5.9INDX112006 212.4 6INDX122006 214.1 5.8INDX012007 213.5 6INDX022007 213.8 6INDX032007 211.1 6.7INDX042007 210.9 0.6INDX052007 210.9 0.9INDX062007 211.2 1.1INDX072007 214.1 1.7INDX082007 215.6 1.7INDX092007 215.5 2.3INDX102007 216.3 2.4INDX112007 216.9 2.5INDX122007 216.3 3INDX012008 217.7 4.11


INDX022008 219.1 5.02INDX032008 222.3 7.41INDX042008 223.9 7.61INDX052008 222.8 7.61INDX062008 223.8 8.75INDX072008 228.1 11.91INDX082008 229.7 12.1INDX092008 229.8 11.98INDX102008 235.3 10.72INDX112008 237.5 8INDX122008 239.6 5.91INDX012009 242.2 4.39INDX022009 247.9 2.43INDX032009 248.1 0.26INDX042009 250.6 0.75INDX052009 254.3 0.13INDX062009 256.0 -1.55INDX072009 259.8 -1.58INDX082009 262.3 -0.12INDX092009 266.8 0.7INDX102009 270.0 1.34INDX112009 282.6 4.78INDX122009 287.9 7.31

0 20 40 60 80 100 120-50.0

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

correlation

a. Food Grains(Cereals+Pulses)inflation

from jan 2001 to dec 2009

infla

tion

5.1.1 Karl Pearson Coefficient of correlation:


Correlation between inflation and food grains(cereals pulses)

0.17

Findings:

There is no relationship between inflation and food grains because both are not in the

same direction. The prices of food grains are very fast increasing as compare to inflation.

In India inflation is calculated on the bases of wholesale price index while whole world

calculate the inflation on the bases of consumer price index.\

5.1.2 Linear Regression Method:


SUMMARY OUTPUT

Regression Statistics

Multiple R 0.179506

R Square 0.032222Adjusted R Square 0.023092

Standard Error 29.25428

Observations 108

ANOVA

df SS MS FSignificance

F

Regression 1 3020.402 3020.402 3.529279 0.063041

Residual 106 90716.16 855.8128

Total 107 93736.56

CoefficientsStandard

Error t Stat P-value Lower 95%Upper 95%

Lower 95.0%

Upper 95.0%

Intercept 191.2874 4.68049 40.8691 1.04E-66 182.0079 200.5669 182.0079 200.5669

X Variable 1 1.994458 1.061651 1.878637 0.063041 -0.11037 4.099284 -0.11037 4.099284

Findings:

The Regression line Y= 191.28 + 1.99X.

R2= 0.023 which means the independent variable X explains 2% of the total variation

depends variable Y.

Standard error of intercept and slope co-efficient are 4.68 and 1.06 respectively. It shows

both co-efficient are statistically highly significant.

The confidence interval for Y intercept term at 5 % significance level is 182 and -0.11

5.2 Relationship between Fruits & vegetables and Inflation:

COMM_NAME b. Fruits & Vegetables


INDX012001INDX022001INDX032001INDX042001INDX052001INDX062001INDX072001INDX082001INDX092001INDX102001INDX112001INDX122001INDX012002INDX022002INDX032002INDX042002INDX052002INDX062002INDX072002INDX082002INDX092002INDX102002INDX112002INDX122002INDX012003INDX022003INDX032003INDX042003INDX052003INDX062003INDX072003INDX082003INDX092003INDX102003INDX112003INDX122003INDX012004INDX022004INDX032004INDX042004INDX052004INDX062004INDX072004INDX082004


INDX092004INDX102004INDX112004INDX122004INDX012005INDX022005INDX032005INDX042005INDX052005INDX062005INDX072005INDX082005INDX092005INDX102005INDX112005INDX122005INDX012006INDX022006INDX032006INDX042006INDX052006INDX062006INDX072006INDX082006INDX092006INDX102006INDX112006INDX122006INDX012007INDX022007INDX032007INDX042007INDX052007INDX062007INDX072007INDX082007INDX092007INDX102007INDX112007INDX122007INDX012008INDX022008INDX032008INDX042008


INDX052008INDX062008INDX072008INDX082008INDX092008INDX102008INDX112008INDX122008INDX012009INDX022009INDX032009INDX042009INDX052009INDX062009INDX072009INDX082009INDX092009INDX102009INDX112009INDX122009

140.0 160.0 180.0 200.0 220.0 240.0 260.0 280.0 300.0 320.0 340.0-4-202468

101214

Fruits and vegetables

inflation


Correlation between inflation and Fruits & vegetables

0.18


Findings:

There is no relationship between inflation and Fruits & vegetables because both are not

in the same direction. The prices of Fruits & vegetables are very fast increasing as

compare to inflation. In India inflation is calculated on the bases of wholesale price index

while whole world calculate the inflation on the bases of consumer price index.

SUMMARY OUTPUT


Multiple R 0.181082

R Square 0.032791

Adjusted R 0.023666


SquareStandard Error 33.92056

Observations 108

ANOVA


F

Regression 1 4134.886 4134.8863.59366

4 0.060724

Residual 106 121964.1 1150.605

Total 107 126099



Lower 95.0%

Upper 95.0%

Intercept 211.4322 5.376203 39.32741 4.79E-65 200.7733 222.091 200.7733 222.091

X Variable 1 2.318914 1.223252 1.8956960.06072

4 -0.1063 4.74413 -0.1063 4.74413

5.2.2 Liner Regression Method:

Findings:



depends variable Y.



The confidence interval for Y intercept term at 5 % significance level is 200 and -0.1

5.3 Relationship between Milk and Inflation:

COMM_NAME Milk inflationINDX012001 158.3 5.1INDX022001 159.8 5INDX032001 162.7 5.5


INDX042001 167.7 0.5INDX052001 166.1 0.9INDX062001 164.1 1.1INDX072001 163.5 1.3INDX082001 165.8 1.5INDX092001 165.3 1.6INDX102001 166.5 2INDX112001 165.8 1.8INDX122001 166.5 1.4INDX012002 166.9 0.9INDX022002 167.3 1.1INDX032002 168.7 1.6INDX042002 171.2 0.6INDX052002 170.7 0.7INDX062002 169.2 2.2INDX072002 171.5 2.7INDX082002 172.3 3.5INDX092002 172.3 3.3INDX102002 172.3 3.5INDX112002 172.3 3.5INDX122002 172.3 3.3INDX012003 172.3 4INDX022003 172.3 5INDX032003 172.3 6.5INDX042003 172.3 0.6INDX052003 172.3 0.4INDX062003 172.3 1INDX072003 172.3 0.5INDX082003 176.5 1INDX092003 176.5 2.2INDX102003 176.5 2.2INDX112003 175.9 2.6INDX122003 177.1 2.7INDX012004 177.1 3.9INDX022004 179.2 4.4INDX032004 184.4 4.6INDX042004 182.4 0.5INDX052004 181.8 1.3INDX062004 183.9 3.3INDX072004 185.0 3.9INDX082004 183.6 4.9INDX092004 183.6 4.8INDX102004 183.6 5INDX112004 183.6 5.2


INDX122004 184.0 4.5INDX012005 184.4 4.4INDX022005 184.3 4.8INDX032005 183.4 5.1INDX042005 183.6 1.4INDX052005 183.3 1.5INDX062005 184.4 2.5INDX072005 184.4 3INDX082005 184.4 3.2INDX092005 184.4 4.1INDX102005 184.4 4.6INDX112005 184.4 4.5INDX122005 182.7 4.1INDX012006 182.3 3.4INDX022006 185.8 3.9INDX032006 187.0 4.1INDX042006 187.0 1.2INDX052006 192.0 2.4INDX062006 198.3 3.2INDX072006 192.5 3.6INDX082006 191.6 4.4INDX092006 196.4 5.6INDX102006 199.8 5.9INDX112006 198.3 6INDX122006 196.1 5.8INDX012007 197.9 6INDX022007 200.5 6INDX032007 201.2 6.7INDX042007 203.0 0.6INDX052007 205.6 0.9INDX062007 207.3 1.1INDX072007 209.2 1.7INDX082007 212.2 1.7INDX092007 212.6 2.3INDX102007 213.9 2.4INDX112007 216.1 2.5INDX122007 216.1 3INDX012008 216.1 4.11INDX022008 218.2 5.02INDX032008 219.5 7.41INDX042008 221.3 7.61INDX052008 221.9 7.61INDX062008 224.5 8.75INDX072008 225.0 11.91


INDX082008 226.0 12.1INDX092008 227.4 11.98INDX102008 229.4 10.72INDX112008 230.7 8INDX122008 232.1 5.91INDX012009 233.7 4.39INDX022009 234.2 2.43INDX032009 235.8 0.26INDX042009 234.2 0.75INDX052009 235.8 0.13INDX062009 241.1 -1.55INDX072009 246.4 -1.58INDX082009 247.7 -0.12INDX092009 249.4 0.7INDX102009 252.4 1.34INDX112009 262.4 4.78INDX122009 263.1 7.31

140.0 160.0 180.0 200.0 220.0 240.0 260.0 280.0-4-202468

101214


inflation


Correlation between inflation and Milk 0.22

Findings:


There is no relationship between inflation and Milk because both are not in the same

direction. The prices of Milk are very fast increasing as compare to inflation. In India

inflation is calculated on the bases of wholesale price index while whole world calculate

the inflation on the bases of consumer price index.


SUMMARY OUTPUT


Multiple R 0.225149




Observations 108

ANOVA


F

Regression 1 3623.8293623.82

9 5.660306 0.019142

Residual 106 67863.11 640.218

Total 107 71486.94



Lower 95.0%

Upper 95.0%

Intercept 186.2982 4.01029746.4549

6 2.7E-72 178.3474 194.249 178.3474 194.249

X Variable 1 2.170884 0.912466 2.37914 0.019142 0.361832 3.979937 0.361832 3.979937

Findings:



depends variable Y.



The confidence interval for Y intercept term at 5 % significance level is 178 and 0.36.

5.4 Relationship between Sugar and Inflation:

COMM_NAME Sugar inflationINDX012001 141.1 5.1INDX022001 137.0 5INDX032001 137.9 5.5INDX042001 138.5 0.5INDX052001 137.2 0.9INDX062001 136.6 1.1INDX072001 135.9 1.3


INDX082001 135.2 1.5INDX092001 135.5 1.6INDX102001 136.0 2INDX112001 135.9 1.8INDX122001 134.1 1.4INDX012002 133.2 0.9INDX022002 133.1 1.1INDX032002 133.9 1.6INDX042002 132.1 0.6INDX052002 131.6 0.7INDX062002 129.9 2.2INDX072002 127.6 2.7INDX082002 126.8 3.5INDX092002 125.7 3.3INDX102002 124.3 3.5INDX112002 121.2 3.5INDX122002 117.3 3.3INDX012003 116.2 4INDX022003 115.2 5INDX032003 114.2 6.5INDX042003 115.0 0.6INDX052003 115.2 0.4INDX062003 116.0 1INDX072003 120.5 0.5INDX082003 126.3 1INDX092003 126.6 2.2INDX102003 127.6 2.2INDX112003 127.8 2.6INDX122003 126.0 2.7INDX012004 124.3 3.9INDX022004 134.4 4.4INDX032004 133.6 4.6INDX042004 133.9 0.5INDX052004 140.0 1.3INDX062004 141.3 3.3INDX072004 141.1 3.9INDX082004 144.3 4.9INDX092004 148.3 4.8INDX102004 147.5 5INDX112004 147.6 5.2INDX122004 149.8 4.5INDX012005 162.6 4.4INDX022005 160.4 4.8INDX032005 161.0 5.1


INDX042005 160.6 1.4INDX052005 159.4 1.5INDX062005 158.3 2.5INDX072005 161.4 3INDX082005 163.4 3.2INDX092005 162.3 4.1INDX102005 163.0 4.6INDX112005 164.9 4.5INDX122005 162.9 4.1INDX012006 166.3 3.4INDX022006 173.4 3.9INDX032006 171.9 4.1INDX042006 171.9 1.2INDX052006 173.3 2.4INDX062006 173.2 3.2INDX072006 171.6 3.6INDX082006 170.6 4.4INDX092006 169.0 5.6INDX102006 166.6 5.9INDX112006 164.8 6INDX122006 161.5 5.8INDX012007 155.2 6INDX022007 152.3 6INDX032007 149.3 6.7INDX042007 148.2 0.6INDX052007 143.8 0.9INDX062007 141.1 1.1INDX072007 140.9 1.7INDX082007 140.2 1.7INDX092007 141.2 2.3INDX102007 141.5 2.4INDX112007 140.9 2.5INDX122007 140.6 3INDX012008 143.2 4.11INDX022008 144.4 5.02INDX032008 146.9 7.41INDX042008 149.6 7.61INDX052008 149.1 7.61INDX062008 148.1 8.75INDX072008 149.8 11.91INDX082008 158.3 12.1INDX092008 160.6 11.98INDX102008 160.6 10.72INDX112008 160.9 8


INDX122008 161.0 5.91INDX012009 167.4 4.39INDX022009 179.2 2.43INDX032009 180.3 0.26INDX042009 191.1 0.75INDX052009 195.8 0.13INDX062009 201.8 -1.55INDX072009 202.5 -1.58INDX082009 217.3 -0.12INDX092009 233.0 0.7INDX102009 234.9 1.34INDX112009 248.4 4.78INDX122009 250.0 7.31

100.0 120.0 140.0 160.0 180.0 200.0 220.0 240.0 260.0-4-202468

101214

Sugar

inflation


Correlation between inflation and Sugar 0.04

Findings:

There is no relationship between inflation and Sugar because both are not in the same

direction. The prices of Sugar are very fast increasing as compare to inflation. In India





SUMMARY OUTPUT


Multiple R 0.041582

R Square 0.001729Adjusted R Square -0.00769


Observations 108


ANOVA


F

Regression 1 134.5412134.541

2 0.183594 0.669172

Residual 106 77678.71 732.818

Total 107 77813.25



Lower 95.0%

Upper 95.0%

Intercept 149.9651 4.290528 34.9526 5.29E-60 141.4587 158.4715 141.4587 158.4715

X Variable 1 0.418293 0.9762270.42847

9 0.669172 -1.51717 2.353758 -1.51717 2.353758

Findings:


R2= 0.001 which means the independent variable X explains less than 1 % of the total

variation depends variable Y.



The confidence interval for Y intercept term at 5 % significance level is 141 and -1.51.

5.5 Relationship between Jaggary and Inflation:

COMM_NAME Gur inflationINDX012001 117.7 5.1INDX022001 113.3 5INDX032001 118.3 5.5INDX042001 129.4 0.5INDX052001 138.8 0.9INDX062001 146.2 1.1INDX072001 148.4 1.3INDX082001 150.6 1.5INDX092001 156.5 1.6


INDX102001 147.3 2INDX112001 141.4 1.8INDX122001 125.5 1.4INDX012002 123.8 0.9INDX022002 121.4 1.1INDX032002 123.7 1.6INDX042002 127.0 0.6INDX052002 128.7 0.7INDX062002 134.0 2.2INDX072002 137.9 2.7INDX082002 139.1 3.5INDX092002 142.6 3.3INDX102002 142.2 3.5INDX112002 133.4 3.5INDX122002 111.7 3.3INDX012003 113.7 4INDX022003 114.5 5INDX032003 113.4 6.5INDX042003 115.1 0.6INDX052003 115.2 0.4INDX062003 116.5 1INDX072003 120.8 0.5INDX082003 122.1 1INDX092003 123.1 2.2INDX102003 131.7 2.2INDX112003 122.2 2.6INDX122003 115.3 2.7INDX012004 123.2 3.9INDX022004 127.3 4.4INDX032004 131.6 4.6INDX042004 134.9 0.5INDX052004 153.3 1.3INDX062004 167.3 3.3INDX072004 177.2 3.9INDX082004 190.7 4.9INDX092004 196.4 4.8INDX102004 192.9 5INDX112004 175.4 5.2INDX122004 167.4 4.5INDX012005 171.6 4.4INDX022005 174.3 4.8INDX032005 173.6 5.1INDX042005 179.3 1.4INDX052005 189.3 1.5


INDX062005 196.1 2.5INDX072005 195.8 3INDX082005 202.3 3.2INDX092005 208.6 4.1INDX102005 213.5 4.6INDX112005 201.2 4.5INDX122005 184.7 4.1INDX012006 182.1 3.4INDX022006 179.2 3.9INDX032006 178.3 4.1INDX042006 178.0 1.2INDX052006 182.8 2.4INDX062006 185.8 3.2INDX072006 185.8 3.6INDX082006 192.0 4.4INDX092006 199.5 5.6INDX102006 197.6 5.9INDX112006 191.8 6INDX122006 185.9 5.8INDX012007 178.7 6INDX022007 173.9 6INDX032007 171.8 6.7INDX042007 169.1 0.6INDX052007 166.7 0.9INDX062007 163.7 1.1INDX072007 165.7 1.7INDX082007 169.3 1.7INDX092007 172.2 2.3INDX102007 171.6 2.4INDX112007 171.1 2.5INDX122007 170.1 3INDX012008 172.2 4.11INDX022008 175.4 5.02INDX032008 176.2 7.41INDX042008 181.1 7.61INDX052008 189.4 7.61INDX062008 189.4 8.75INDX072008 190.1 11.91INDX082008 192.3 12.1INDX092008 196.4 11.98INDX102008 204.4 10.72INDX112008 212.9 8INDX122008 208.7 5.91INDX012009 221.8 4.39


INDX022009 232.5 2.43INDX032009 241.7 0.26INDX042009 248.0 0.75INDX052009 268.4 0.13INDX062009 270.0 -1.55INDX072009 268.3 -1.58INDX082009 274.8 -0.12INDX092009 275.0 0.7INDX102009 286.2 1.34INDX112009 283.0 4.78INDX122009 304.2 7.31

100.0 150.0 200.0 250.0 300.0 350.0-4-202468

101214

Jaggary

inflation


Correlation between inflation and Jaggary 0.10

Findings:

There is no relationship between inflation and Jaggary because both are not in the same

direction. The prices of Jaggary are very fast increasing as compare to inflation. In India





SUMMARY OUTPUT


Multiple R 0.10534



Observations 108

ANOVA


F

Regression 1 2309.488 2309.48 1.189437 0.277916


8

Residual 106 205816.41941.66

4

Total 107 208125.8



Lower 95.0%

Upper 95.0%

Intercept 166.1282 6.98392723.7872

2 2.64E-44 152.2819 179.9745 152.2819 179.9745

X Variable 1 1.733048 1.5890581.09061

3 0.277916 -1.41741 4.883511 -1.41741 4.883511

Findings:


R2= 0.011 which means the independent variable X explains 1 % of the total variation

depends variable Y.



The confidence interval for Y intercept term at 5 % significance level is 152 and -1.41.

5.6 Weekly Inflation Data of year 2008 and 2009:

Period 2008 2009 IR(y)1/5/2008 3.79 1/3/2009 5.24

1/12/2008 3.83 1/10/2009 5.61/19/2008 3.93 1/17/2009 5.641/26/2008 4.11 1/24/2009 5.072/2/2008 4.07 1/31/2009 4.392/9/2008 4.35 2/7/2009 3.92

2/16/2008 4.89 2/14/2009 3.362/23/2008 5.02 2/21/2009 3.033/1/2008 5.11 2/28/2009 2.43


3/8/2008 5.92 3/7/2009 0.443/15/2008 6.68 3/14/2009 0.273/22/2008 7 3/21/2009 0.313/29/2008 7.41 3/28/2009 0.264/5/2008 7.14 4/4/2009 0.18

4/12/2008 7.33 4/11/2009 0.264/19/2008 7.57 4/18/2009 0.574/26/2008 7.61 4/25/2009 0.755/3/2008 7.83 5/2/2009 0.48

5/10/2008 7.82 5/9/2009 0.615/17/2008 8.1 5/16/2009 0.615/24/2008 8.24 5/23/2009 0.485/31/2008 8.75 5/30/2009 0.136/7/2008 11.05 6/6/2009 -1.61

6/14/2008 11.42 6/13/2009 -1.146/21/2008 11.63 6/20/2009 -1.36/28/2008 11.89 6/27/2009 -1.557/5/2008 11.91 7/4/2009 -1.21

7/12/2008 11.89 7/11/2009 -1.177/19/2008 11.98 7/18/2009 -1.547/26/2008 12.01 7/25/2009 -1.588/2/2008 12.44 8/1/2009 -1.748/9/2008 12.63 8/8/2009 -1.53

8/16/2008 12.4 8/15/2009 -0.958/23/2008 12.34 8/22/2009 -0.218/30/2008 12.1 8/29/2009 -0.129/6/2008 12.09 9/5/2009 0.12

9/13/2008 12.23 9/12/2009 0.279/20/2008 11.99 9/19/2009 0.839/27/2008 11.98 9/26/2009 0.710/4/2008 11.44 10/3/2009 0.92

10/11/2008 11.35 10/10/2009 1.2110/18/2008 10.68 10/17/2009 1.5110/25/2008 10.72 10/24/2009 1.34


Correlation between weekly inflation data of two years

-0.89

Findings:

There is negative relationship between two years inflation.



SUMMARY OUTPUT


Multiple R 0.816799



Observations 43

ANOVA


F

Regression 1 270.5155 270.515 82.18265 2.41E-11


5

Residual 41 134.95713.29163

8

Total 42 405.4726



Lower 95.0%

Upper 95.0%

Intercept 9.949665 0.298013 33.3867 2.37E-31 9.347816 10.55151 9.347816 10.55151

X Variable 1 -1.22351 0.134964 -9.06546 2.41E-11 -1.49608 -0.95095 -1.49608 -0.95095

Findings:

The Regression line Y= 9.94 + -1.22X.

R2= 0.66 which means the independent variable X explains less than 66 % of the total

variation depends variable Y.



The confidence interval for Y intercept term at 5 % significance level is 9.34 and -0.95.

CONCLUSION

Conclusion of the primary data research:

We have gone through 200 respondents and from them 168 are male and 32 are

female respondents.

From the analysis we have found that 48 % respondents are strongly agree that

they have affected by inflation while 45 % are agree regarding the same case.

From the total respondents service people and farmers mostly affected by

inflation.


As per income criteria, between the ranges of 151000-300000 rupee family

income people mostly affected by inflation.

As per Family members, who has 5-6 members in family, affected most by

inflation.

As per service person in family, who has 0-2 service person in family, affected

most by inflation.

In the case of allocation of budget, in cereals and pulses 62 % people allocate 11-

15 % budget behind that while 23 % people allocate 5-10 % budget behind

cereals and pulses, and 15 % respondents allocate more than 16 % behind that in

the year 2008.

In the case of allocation of budget, in cereals and pulses 53 % people allocate 11-

15 % budget behind that while 42 % people allocate more than 16 % budget

behind cereals and pulses in the year 2009. Because of inflation respondents have

change the allocation of cereals and pulses.

In the case of allocation of budget, in Grocery 72 % people allocate 11-15 %

budget behind that while 21 % people allocate more than 16 % behind Grocery in

the year 2008.

In the case of allocation of budget, in Grocery 45 % people allocate 11-15 %

budget behind that while 21 % people allocate more than 52 % behind Grocery in

the year 2009. Because of inflation respondents have change the allocation of

Grocery.

In the case of allocation of budget, in Edible oil 68 % people allocate 6-10 %

budget behind that while 30 % people allocate 0-5 % budget behind Edible oil in

the year 2008.

In the case of allocation of budget, in Edible oil 63 % people allocate 6-10 %

budget behind that while 33 % people allocate 0-5 % budget behind Edible oil in

the year 2009.

In the case of allocation of budget, in Vegetables and fruits 63 % people allocate

6-10 % budget behind that while 36 % people allocate 0-5 % budget behind

Vegetables and fruits in the year 2008.


In the case of allocation of budget, in Vegetables and fruits 65 % people allocate

6-10 % budget behind that while 34 % people allocate 0-5 % budget behind

Vegetables and fruits in the year 2009.

In the case of allocation of budget, in Milk & related products 90 % people

allocate 6-10 % budget behind that while 9 % people allocate 0-5 % budget

behind Milk & related products in the year 2008 and year 2009.

. In the case of allocation of budget, in lpg 142 people allocate 0% to 5% and 58

people allocate 6% to 10% in 2008 where as in 2009 it is 157 and 43 people

respectively.

In the case of allocation of budget, in phone and electricity bill 148 people

allocate 0% to 5% and 52 people allocate 6% to 10% in 2008 where as in 2009 it

is 158 and 41people respectively.

In the case of allocation of budget, in Transportation 148 people allocate 0% to

5% , 52 people allocate 6% to 10% and 6 people allocate 11% to 15% in 2008

where as in 2009 it is 158, 41 & 11people respectively.

In the case of allocation of budget, in education 27 people allocate 0% to 5% , 44

people allocate 6% to 10% and 97 people allocate 16% to 20% in 2008 where as

in 2009 it is 30, 34 & 92 people respectively.

In the case of allocation of budget, in entertainment 141 people allocate 0% to

5% , 51 people allocate 6% to 10% and 6 people allocate 16% to 20% in 2008

where as in 2009 it is 169, 28 & 0 people respectively.

In the case of allocation of budget, in other items 94 people allocate 0% to 5% ,

83 people allocate 6% to 10% and 6 people allocate 16% to 20% in 2008 where

as in 2009 it is 167, 24 & 2 people respectively.

Conclusion of the secondary data analysis:

In this part the secondary data regarding of the rate of the inflation and the price of the

various commodity we reached the conclusion that though the inflation got negative no

difference is in the level of the price rise in the economy. There is a strong negative

relationship between weekly inflation rate of the two year 2008-2009. The inflation of

the both the year went in the opposite direction.


India, the 12th largest and the second fastest growing major economy in the world, has

been experiencing significant price instability in the recent past. Even though, the

sources of the phenomenon can be attributed to both internal as well as external factors,

correction of the problem will have to take place mainly though effective domestic

economic policies for both the demand management and supply adjustment. But the

domestic policy measures initiated in India have not seen bringing any significant effects

in controlling price volatility in the country.

It is also an appropriate time to critically think about the quality of the official inflation

statistics published in India. No single price index will be able to provide a measure

inflation that can be used for all the purposes. Five official price indices are published in

India, of which one is WPI and the other four are CPIs. All the five indices suffer from

some inherent deficiencies. The most common deficiencies include importantly the fact

that our compilation procedures neither systematically incorporate new goods and

services as they enter the market nor adjust for changes in the quality of goods and

services over time. Consequently, our price indices could not be used to gauge inflation

in the economy.

Our headline inflation measure, WPI, is extremely inadequate to track the inflationary

pressure in the economy for it excludes services, and it is more susceptible to the

problem of base effect. Moreover, it does not adequately reflect the expansion and

quality improvement of commodities. Therefore, the reported inflationary situation in

India, determined using the WPI, is unreliable to a great extent. In the absence of a

reliable measurement of inflation it is difficult to analyze the exact impact of the

inflation/deflation and announce appropriate policies to ensure price stability. It is high

time for India to revise the method of calculating price index and inflation measurement

so as to enable a proper and periodic assessment and control of inflation in the economy.

It would be desirable to take into consideration the following points while preparing a

price index and measuring inflation in India9.

Firstly, the current headline inflation measure, WPI, should be replaced with a newly

constructed comprehensive and aggregate broad based CPI or a cost of living index, and

which should be made available fortnightly or monthly. Inclusion of more services in the

index will give a true picture of inflation in India as the service sector accounts for more


than half of the GDP in India. More over, the new CPI should be made transparent in

terms of its content.

There seems to have a trade-off between the frequency and reliability of the inflation

figures. More frequent data are said to be less reliable data. Therefore, it is desirable to

changeover to a less frequent (fortnightly or monthly) and more reliable index in line

with the standard practice in other countries.

Secondly, the method of index calculation should accommodate quantitative and

qualitative changes in the commodity basket; the method should systematically

incorporate the entry of new commodities and services and also the exit of some old

commodities and services in the calculation of the index.

Thirdly, the current measure WPI should be modified or replaced (not for measuring

headline inflation, but to provide a better the producer price index) to incorporate

services and also more commodities in it.

Fourthly, a de-seasonalised price index should be used for measuring month-over-month

but annualized inflation rate, which is free from the base effect.

Finally, a better method of index construction, such as Fisher’s Ideal Index should be

used replacing the Laspeyres Index for the construction of all price indices. The indices

have to be revised periodically to capture the more dynamic segments of the economy.

However, the long run solution to the real inflation/deflation problem does not lie in the

revision of the method of its measurement; it rather depends on the appropriate supply

adjustment and demand management measures. Therefore, the government should

formulate appropriate economic policies to provide incentives to ensure adequate

domestic production and stabilize domestic demand for commodities and services in the

country.


Date post:	18-Nov-2014
Category:	Documents
Upload:	punitatvsn
View:	104 times
Download:	0 times

How Inflation Affect the Consumer in india

Documents