CHAPTER IV

DETERMINANTS OF DEMAND FOR DIFFERENT TELEPHONE

CALLS FOR RESIDENTIAL AND NON-RESIDENTIAL

SUBSCRIBERS - A CROSS SECTION ANALYSIS

4.0 Introduction

In the previous chapter, we have reviewed the extensive theoretical and

empirical literature on the demand for telephones. Lack of interest in sound

economic analysis, partly because of the statutory public monopoly

environment and supply-oriented approach to public utilities, as well as

absence of the data base have been responsible for the absence of any

econometric analysis of demand for telephones in India.

In our research we use the data obtained from a specially designed cross

section study of residential and non-residential telephone subscribers demand

for basic telephone service, a) to analyse the determinants of demand, by call

type, for the two categories of subscribers and b) to estimate the own price

elasticity of demand exploiting the temporal and spatial variations in the STD

demand pattern along the lines suggested by Lang and Lundgren (1991). This

chapter deals with the determinants of telephone demand and the estimation

of price elasticity in reported in chapter V.

The plan of the chapter is as follows : Section 4.1 specifies the demand

models for residential and non-residential subscribers. Section 4.2 describes the

design and features of the special survey and definitions of the variables used

in the regression analysis. Section 4.3 contains a descriptive analysis of the

data. Section 4.4 deals with the determinants of the demand for residential

and non-residential telephone subscribers. The last section summarises the

regression results.

4.1 Specification of the Demand Functions

For both residential and non-residential telephone subscribers, we

consider three types of calls : local, STD and ISD. Since all the three calls are

measured in pulses, we can also consider the total calls.

Engel specification is appropriate for a cross section analysis. In this

specification, a researcheis interest centres on the estimation of the income

elasticity of demand for households and output elasticity for business. We must

account for the possibility that the elasticities are functions of the income

(output) variables and not simply constants.

In a cross section data, in addition to income (output2household-specific

(firm-specific) variables also do influence the demand for different type of calls.

Keeping these factors into consideration we specify the following demand

functions :

For residential demand

In N, = & + aIi in Y, + 4, (In Y,)' + 4, Eh

where i = 1 refers to local calls, i = 2 refers to STD calls, i = 3 refers to

ISD calls and i = 4 refers to total calls; 'j' refers to jth household, Y is

household income (bimonthly), E, is educational dummy for ha category, 0, is

occupational dummy for ha category, A,, is age dummy for hh category and F,

is family size dummy for h& category. The educational, occupational and age

dummy variables relate to the heads of the households. For each call type, the

U,'s are assumed to be uncorrelated random normal variables with zero mean

and constant variance. The parameters of the equations will be estimated

using the ordinary least squares method.

For non-residential demand

where, as in equation (11, i = 1,2,3,4 refer to local, STD, ISD and total calls

respectively; j refers to j& business subscriber, S is a measure of firm size, A

is age of the phone connection and Th is a dummy variable for hth business

category. For each call type, the &,'s are assumed to be uncorrelated random

normal variables with zero mean and constant variance. The parameters in

equation (2) will be estimated using the ordinary least squares method.

4.2 The Database

The empirical implementation of the model disucssed in the previous

section requires socio-economic background of the residential subscribers and

their calling pattern during a particular period. Similar information on

business characteristics for the non-residential subscribers and their calling

p a t k m are required. Due to non-availability of micro level (Subscriber's data)

data with all required particulars fiom published sources, an experiment was

conducted to generate data needed for the study a t the micro level for a

bimonthly period. For generation of the relevant data, we have chosen

Haddows Road I1 EIOB digital exchange a t Nungambakkam in the City of

Madras. I t is centrally located and its geographical area covers main business

activity places as well as posh residential areas such as Thyagaraya N a p ,

Valluvarkottam, Nungambakkam and Royapettah.

As on December 1992, the total number of subscribers connected to the

working lines of the exchange was 8230. Excluding the service connections,

Government and PC0 subscribers, there were 5998 subscribers of whom 2558

were residential and 3440 were non-residential subscribers. On the basis of

bimonthly bills, all subscribers in each category, are divided into two groups.

i) those who made 1000 local calldpulses or below

ii) those who made 1000 local calla/pulses or more

From each strata, 5 percent sample is selected. In total, 300 subscribers

are selected using a simple random sampling technique. Among the sample

subscribers, residential subscribers are 128; of whom 69 have STD facility;

non-residential subscribers are 172; of whom93 have STD facility. The

generated calling pattern details for the sample subscribers pertain to the type

of call, timesf-day, distance duration and pulses charged for each type of call

during the bimonthly period from 26th February 1993 to 25th April 1993. The

researcher could gather the information on sample subscribers only for a

particular bimonthly period due to memory constraint in the exchange

computer. However, subscriber's individual calling data are recorded in

magnetic tapes for every bimonthly period but we could not process this data

due to memory and resource constraints.

A questionnaire is also framed to collect some vital information from the

subscribers through interview method. The researcher personally went to all

the sample subscribers' premises and collected the required data during the

period from May 1993 to October 1993. Since the calling particulars for the

sample subscribers are gathered from the exchange during the period February

1993 to April 1993, the socio-economic features of residential subscribers and

business characteristics for the non-residential subscribers have been collected

for the same period to match with each other. The researcher took maximum

efforts to obtain accurate and unbiased data from the sample subscribers and

cross questions were asked whenever necessary. The data collected for the

residential subscribers are : bimonthly household income, household size, age,

education and occupation levels of the subscribers. For non-residential

subscribers, information pertaining to type of business activity, number of

employees in the non production units, bimonthly sales turnover and age of

phone connection were collected.

Definitions of the Variables

The definitions of the explanatory variables used in the residential

demand models are given below :

(a) Household income : Household income includes the total money

income received by all household members. The logarithm of household

income and its square are included in the regressions. The inclusion of

the logarithm of the square of income will enable us to test whether the

income elasticity of demand is constant or a function of the income.

(b) Educational dummies : Completed years of education of the subscriber

is measured in terms of number of years from primary level of

education. This variable is classified into four dummies namely EDU1,

EDU2, EDU3 and EDU4. For exact definitions of the dummies, see the

variable definitions Table4.I.The dummy EDUl is taken as reference

!FOUP.

(c) Occupational dummies : Occupational status of the subscribers are

classified into self-employed, privately employed, government employed

and others. The categories are introduced as dummies such as OCC1,

OCC2,OCC3 and OCC4. For exact definitions of the dummies, see the

variable definitions Table 4S.The occupational dummy OCC3 which

refers to government employed is used as a reference group.

(d) Family size dummies : The total number of persons in the household

is referred to as household size or family size. Family size is divided and

termed as FS1, FS2 and FS3 dummies. FS3 is used as a reference

The following business characteristics are used as explanatory variables

in the non-residential demand models.

(i) Type of business activity : Business activities are divided into four

categories such as manufacturing, trade, finance and others. These

categories are used as dummies such as MANUF, TRADE and OTHERS

where the FINANCE dummy is taken as a reference group.

(ii) Number of employees in non-production units : The total number

of employees in non-production units (only if the production unit exists,

otherwise total number of employees in that particular branch where

the telephone is located) is considered as a measure of size of the firm

or business. The number of employees and its square are expressed in

natural logarithms in the models. These variables are used as

alternatives to sales turnover variables in a separate specifications for

non-residential subscribers.

(iii) Sales turnover (bimonthly) : Since the telephone bills are charged

and the calling particulars also collected bimonthly, we have used

logarithms of bimonthly sales turnover and its square as size variables

or output variables.

(iv) Age of phone connection : Age of telephone connection is measured

for each sample subscriber from the month of instalment of phone

c o ~ e c t i o n to the present time of study. It is measured interms of

number of months. This variable appears in logarithmic form in the

model.

The definitions of explanatory variables for residential and non-

residential subscribers are given in Tables 4.1 and 4.2 .

TABLE 4.1

DEFINITIONS OF EXPLANATORY VARIABLES FOR RESIDENTIAL SUBSCRIBERS

Education level dummy variables

EDUl - Subscriber's education level is upto 10th standard EDU2 - Subecriber's education level is S.S.L.C/P.U.C./H.Sc. EDU3 - Subscriber's education level is any degree or diploma other

than professional EDU4 - Subscriber's education level is any professional degree or

post graduates and above

Age dummies

AGE1 - Subscriber's age is upto 35 years old AGE2 - Subscriber's age is in between 36 to 50 years old AGE3 - Subscriber's age is above 50 years old

Family size dummies

FS1- The total number of persons in the household is upto 4 members

FS2 - The total number of persons in the household is between 5 and 7 members

FS3 - The total number of persons in the household is above 7 members

Occupational dummies

OCCl - Subscriber's occupational status is selfemployed OCC2 - Subscriber's occupational status is privately employed OCC3 - Subscriber's occupational status is government employed OCC4 - Subscriber'e occupational status is others such as brokers,

dealers etc.

LBHmC - Logarithm of bimonthly household income in rupees SLBHINC - Square of logarithm of bimonthly household income in

rupees BHmC - Bimonthly howhold income in rupees

Note : A dummy variable takes the value 1 if the attribute is present and zero otherwise.

TABLE 4.2

DEFINITIONS OF EXPLANATORY VARIABLES FOR NON-RESIDENTIAL SUBSCRIBERS

Business category dummies

MANLJF' - The type of business activity is manufacturing unit TRADE - Subscriber's type of business activity is trade (retail as well

as wholesale) FINANCE - Subscriber's type of business activity is an indigenous bank

or finance company OTHERS - Subscriber's type of business activity is other than the above

- --

Size variables

LNE - Logarithm of number of employees (if the type of business activity is manufacturing, then LNE refers to the number of employee in the non-production unit)

SLNE - Square of the logarithm of number of employees NE - Number of employees in the firm.

Sales turnover variables

LBST - Logarithm of bimonthly sales turnover of the firmhusiness. SLBST - Square of logarithm of bimonthly sales turnover BST - Bimonthly sales turnover

Age variable

LAPC - Logarithm of age orphone connection

STD dummy

STD - Subscriber's phone connection with STD facility

Note : A dummy variable takes the value 1 if the attribute is present and zero otherwise.

4.3 A descriptive analysis of the sample data

In the section, the purpose is to give the descriptive statistics for the

variables used in the analysis. It presents the mean and standard deviations

of variable included in both residential and non-residential disaggregated

demand models.

4.3a Mean and standard deviations of the variables for residential

and non-residential subscribers

Table 4.3 presents the means and standard deviations of the variables

included in the residential disaggregated demand models. This table shows

that the average bimonthly household income of the residential subscribers is

Rs.18015 with respect to local and total call demand equations. For STD and

ISD call models, the mean value is Rs.19587. Table 4.4 gives the means and

standard deviations of the variables in the non-residential demand models. The

average number of employees worlung in the firm or buslness 1s 21 for local

and total call demand models where as it is 31 for STD and ISD call demand

models. The mean value of the bimonthly salesturnover varlable is Rs.162148

for local and total calls where as it is Rs.257311 for STD and ISD calls.

TABLE 4.3

MIUNS AND STANDARD DEVIATIONS OF THE VARIABLES USED IN THE SAMPLE FOR RESIDENTIAL SUBSCRIBERS BY TYPE OF CALLWISE

* Figures in paranthesis are etandard deviat~ons.

Variablm I b d d b 18TD&I ISDcdo I (=%& Educational dummies

EDU2

EDU3

EDU4

0.22 (0.42)

0.31 (0.47)

0.28 (0.45)

Age dummies

0.20 (0.41)

0.35 (0.48)

0.33 (0.47)

AGE2

AGE3

0 20 (0 41)

0.35 (0.48)

0.33 (0.47)

0.50 (0.50)

0.38 (0.49)

0.22 (0.42)

0.31 (0.47)

0.28 (0 45)

Occupational dummiee

0.49 (0.50)

0.42 (0.50)

OCCl

OCC2

OCC4

0.49 (0.50)

0.42 (0 50)

0.53 (0.50)

0.22 (0.42)

0.06 (0.24)

0.50 (0.50)

0.38 (0.49)

Family Size dummies

0.51 (0.50)

0.19 (0.39)

0.03 (0.17)

FS 1

FS2

0 51 (0.50)

0 19 (0 39)

0.03 (0 17)

0.41 (0.49)

0.51 (0.50)

0.53 (0 50)

0.22 (0.42)

006 (0.24)

Household Income Variables

0.38 (0.49)

0.51 (0.50)

LBHINC

SLBHINC

0.38 (0.49)

0.51 (0.50)

9.72 (0.40)

94.62 (7.84)

0.41 (0.49)

0.51 (0.50)

9.72 (0.40)

94.62 (7.84)

9.80 (0.41)

96.19 (8.11)

Dependent Variable

9.80 (0 4 1 )

96 19 (8 11)

2.42 (3.25)

19587 68 (8180.471

69

6.22 (1.63)

19587.68 (8180 47)

69

LDV

BHINC

Number of cases

6.84 '

(1.19)

18015.23 (7365.62)

128

6.24 (1.03)

18015.23 (7365.6)

128

TABLE 4.4

MEANS AND STANDARD DEVIATIONS OF THE VARIABLES USED IN THE SAMPLE FOR NON-RESIDENTIAL

SUBSCRIBERS BY TYPE OF CALL WISE

Figures in parantheses are standard deviations

Variables 1 Local I STD ISD gregate Business category dummies

MANUI?

TRADE

OTHERS

0.17 (0.38)

0.31 (0.46)

0.38 (0.49)

Size Variables

0.18 (0.39)

0.29 (0.46)

0.38 (0.49)

LNE

SLNE

NE

0.18 (0.39)

0.29 (0.46)

0.38 (0.49)

2.18 (1.32)

6.44 (6.50)

21.23

0.17 (0.39)

0.31 (0.46)

0.38 (0.49)

Age Variable

2.64 (1.30)

8.66 (.7.28)

31.28

LAPC

2.64 (1.30)

8.66 (7.28)

21.28

4.27 (0.77)

2.17 (1.32)

6.44 (6.50)

21.23

4.29 (0.79)

4.29 (0.79)

Turnover Variables

4.27 (0.77)

LBST

SLBST

11.76 (1.22)

139.71 (29.0)

11.22 (1.15)

127.30 (26.91)

Dependent Variable

11.76 (1.22)

139.71 (29.0)

11.22 (1.15)

127.30 (26.91)

7.81 ( 1.54)

0.54 (0.50)

162148.89 ,

172

4.29 (3.89)

2573 11.03

93

7.79 (1.87)

257311.03

93

LDV

STD dummy STD

BST Number of cases

7.00 (1.02)

162148.89

172

4.3b The residential subscribers

First let us describe the data structure of the residentlal category which

include the socio-demographic and occupational characteristlcs, income and the

calling distribution of the different type of calls etc.

TABLE 4.6

DISTRIBUTION OF OCCUPATIONAL CATEGORIES OF SUBSCRIBERS BY BIMONTHLY HOUSEHOLD INCOME

Note : The figures in parentheses are perrcentages to group totals.

Occupational Categories

Self-employed

Private employed

Government employed

Others

Column Total

Table 4.5 presents the distribution of subscribers by their occupational

categories and their bimonthly household income levels. Occupational

categories of the residential subscribers are classified into four categories such

a s self-employed, private employed, government employed and others. Self-

employed category includes subscribers who are engaged in technical and non-

technical related business etc. Private employed subscribers are the executives,

Low Income Group

38 (52.1)

18 (24.7)

12 (16.4)

5 (6.8)

73

High Income Group

30 (54.5)

10 (18.2)

12 (21.8)

3 (5.5)

5 5

Total

68 (53.1)

28 (21.9)

24 (18.8)

8 (6.3)

128

officers and other cadres of employees working in private companies or firms.

Subscribers who are employed in central or state governments belong to

government employed category. Other category includes subscribers as

housewives or students etc.

Bimonthly household incomes of the residential subscribers are grouped

into two categories.

(i) Bimonthly household income upto Rs.18,000/- (Low Income Group)

(ii) Bimonthly household income above Rs.18,000/- (High Income Group)

I t is evident from the Table 4.5 that more than half of the residential

subscribers are self-employed and they account for 53.1 percent in total; of

whom 52.1 percent are in low income group and the rest are in high income

group. For both income groups, the number of subscribers in private employed

and government employed categories together account around 40 percent in

total.

TABLE 4.6

DISTRIBUTION OF RESIDENTIAL SUBSCRIBERS BY OCCUPATIONAL CATEGORIES AND BY AGE GROUPS

Note . The figures in parenthesee are percentages to total In respective groups,

Table 4.6 shows that among the subscribers, largest number of

subscribers are self-employed in both income groups. In the low income group

subscribers,38 percent, are in the age group above 50 years and only 15

percent in the age group below 35 years. Among the subscribers in the high

income group, the highest numbers of self-employed, private employed and

government employed are in the age group above 50 years old.

TABLE 4.7

DISTRIBUTION OF OCCUPATIONAL CATEGORIES OF RESIDENTIAL SUBSCRIBERS BY THEIR FAMILY SIZE

Note . The figures in parentheses are percentages to total in respective groups.

Occupational Categories

Self-employed

Private employed

Government employed

Others

Table 4.7 gives the distribution of residential subscribers according to

family size. For each occupational categories in the low income group I,

relatively more number of sample units have a family size of four followed by

5 to 7 persons. Similarly, for each occupational category in the high income

group, the largest percentage of subscribers have 5 to 7 persons per family;

followed by a size of four.

Low Income Group

Upto 4 Persons

22 (30.1)

13 (17.8)

7 (9.6)

4 (5.5)

High Income Group

Upto 4 Persons

6 (10.9)

2 (3.6)

3 (5.5)

1 (1.8)

5-7 Persons

15 (20.5)

5 (6.8)

5 (6 8)

1 (1.4)

Above 7 persons

1 (1.4)

0

0

0

5-7 Persons

22 (40.0)

7 (12.7)

8 (14.5)

2 (3.6)

Above 7 persons

2 (3.6)

1 (1.8)

1 (1 8)

0

TABLE 4.8

DISTRIBUTION OF OCCUPATIONAL CATEGORIES OF LOW INCOME GROUP RESIDENTIAL SUBSCRIBERS BY

NUMBER OF PULSES CHARGED FOR DIFFERENT TYPE OF CALLS

Note : The figurw m parantheeee are percentage6 to total for each type of call.

b u p r t i o d c~~~~~~

Table 4.8 gives the distribution of low income group subscribers over

their occupational categories by the number of pulses charged for different type

of calls. In total, the number of subscribers who are charged 1200 pulses or

less for local calls made in the self-employed, privately employed, government

employed and others account for 47.9 percent, 23.3 percent, 15.1 percent and

Upto 600 Puloer Pulma PuL.er P u b PpLer gIWI8D.

(i) W . ~ m p l o y e d

801-1200

a. Local Calla

b STD Calle

c. ISD Calla

1301-1800

26 (35.6)

13 (17.8)

2 (2.7)

(ii) Private employed

1801-8100

9 (12.3)

1 ( 1 4)

1 (1.4)

a. Local Calla

b. STD Calla

c. ISD Calls

Above 2400

13 (17.8)

5 (6.8)

2 (2.7)

, ,

1 (1.4)

0

0

(iii) Government employed

2 (2.7)

0

0

0

1 (1.4)

0

4 (5.5)

2 (2.7)

1 (1.4)

23 (31.5)

35 (47 9)

1 (1 4)

10 (13 7)

0

0

0

a. Local Calls

b. STD Calls

c. ISD Calle

(iv) 0th-

1 (1.4)

0

0

0

0

0

10 (13.7)

7 (9 6)

2 (2.7)

1 (1 4)

0

0

1 ( 1 4)

4 (5.5)

0

0

0

0

3 (4 1)

4 (5 5 )

0

0

0

0

0

11 (15.1)

15 (20.5)

0

0

0 ' 0

1 (1 4)

0

Local Calb a.

b. STD Calls

c. ISD Calls

0

0

0

4 (5.5)

2 (2 7)

1 (1 4)

6.9 percent respectively. Hence, nearly 93 percent of the low income group

subscribers are charged 1200 pulses or less for the local calls made, together

in all occupational categories. Only 1.4 percent of the self employed and none

from the other occupational category had made 2400 calls or more. The

proportion of households making STDIISD calls was the highest in the self

employed group.

TABLE 4.9

DISTRIBUTION OF OCCUPATIONAL CATEGORIES OF HIGH INCOME GROUP RESIDENTIAL SUBSCRIBERS BY

NUMBER OF PULSES CHARGED FOR DIFFERENT TYPE OF CALLS

Note . The figures in paranthese8 are percentages to total for each type of call

Occupational Categories Upto 600 Pulaes

(i) Self-employed

601-1200 Puleee

a . Local Calls

b S T D Calls

c. ISD Calls

1201-1800 Puleea

10 (18.2)

4 (7.3)

6 (10 9)

(ii) Private employed

1801-2400 Pulses

7 (12.7)

2 (3.6)

0

a Local Calls

b S T D Calls

c. ISD Calls

Above 2400 Pulaes

9 (16.4)

3 (5.5)

1 (1 8)

0

1 (1 8)

1 (1 8)

- - STDlISD

4 (7 3)

8 (4 5 )

4 (7 3)

3 (5 5)

0

(iii) Government employed

2 (3.6)

1 ( 1 8)

1 (1 8)

4 (7 3)

1 (1 8)

0

2 (3.6)

10 (18 2)

2 (3.6)

1 (1 8)

1 (1 8)

1 ( 1 8)

2 (3 6)

1 (1 8)

0

10 (18 2)

20 (36 4 ) .

2 (3 6)

1 (1.8)

1 ( 1 8)

4 (7 3)

7 (12.7)

0

1 ( 1 8)

2 (3 6)

a Local Calls

b STD Calls

c. ISD Calls

(iv) Otherr

0

0

0

6 (10 9 )

3 (5.5)

1 ( 1 8)

3 (5 5)

3 ( 5 5)

3 (5 5)

2 (3 6)

1 ( 1 8)

0

0

0

2 (3.6)

0

0

1 (1.8)

0

0

0

0

0

a Local Calla

b S T D Calls

c. ISD Calle

0

0

0

In the high income group, 30.9 percent of the self-employed, 14.6

percent of private employed and 16.4 percent of the government employed have

metered 1200 pulses or less for the local calls made. These percentages are

relatively higher in each occupational category than those subscribers who

have metered above 1200 pulses. Among the STD subscribers in the high

income group, a large percentage (18.2%) of self employed subscribers have

made above 2400 local pulses for the STD calls made. More number of

subscribers in private employed and government employed categories are

charged 1200 pulses and less for STD calls made with respect to total number

of subscribers in the respective categories. Only 31 percent of subscribers have

made ISD calls; of them 18 percent are self-employed.

TABLE 4.10

DISTRIBUTION OF OCCUPATIONAL CATEGORIES OF RESIDENTIAL SUBSCRIBERS BY NUMBER OF

PULSES CHARGED FOR TOTAL CALLS

Note The figures in paranthese8 are percentages to total for the respective income groups

acupatiod Catellorier Up&LKl 1001-8000 P u l e s

(i) Self-employed

20015000 Pulner

3001-4000 Above4000 Pu ler Pulerr

1 (1.4)

5 (9 1)

6 (8.2)

8 (14.5)

a Low income group

b. High ~ncome group

30 (41.1)

5 (9 1)

(ii) Private employed

0

2 (3.6)

1 (1 4) 10

(18.2)

0

1 (1 8)

1 (1.4)

0

a Low lncome group

b. High income group

0

2 (3 6 )

(iii) Government employed

14 (19 2)

6 (10.9)

3 (4.1)

1 (1.8)

0

0

1 (1 4)

2 (3.6)

0

3 (5.5)

5 (6.8)

2 (3.6)

a Low income group

b. High income group

(iv) Othen

6 (8 2)

5 (9.1)

0

0

0

2 (3.6)

2 (2 7)

1 (1.8)

a. Low income group

b. High income group

0

0

3 (4.1)

0

Table 4.10 depicts the distribution of residential subscribers over the

occupational categories by income groups and number of pulses charged for

total calls made during the bimonthly period. The highest proportions of

subscribers in the low income group in each occupational category have

metered only 1000 local pulses or less; of whom the largest percentage, 41.1

percent, is in the self-employed group,

In total, 30.9 percent of self-employed subscribers in the high income

group, have metered more than 2000 local pulses during the study period; of

whom 18.2 percent have made above 4000 local pulses. More number of

subscribers in the other occupational categories have metered less than 2000

local pulses except the others category.

TABLE 4.1 1

DISTRIBUTION OF OCCUPATION CATEGORIES OF RESIDENTIAL SUBSCRIBERS BY THEIR TYPE OF PHONE CONNECTION

Note : The figures in parentheses are percentages to total

Occupational Categories

Self-employed

Private employed

Government employed

Others

High income group Low income group

Total

30 (54.5)

12 (18.2)

12 (21.8)

3 (5.5)

S-

10 (18.2)

4 (7.3)

4 (7.3)

3 (5.5)

STD '

20 (36.4)

6 (10.9)

8 (14.5)

0

Total

38 (52.0)

18 (24.7)

12 (16.5)

5 (6.8)

' - STD

23 (31.5)

11 (15.1)

1 (1.4)

3 (4.1)

STD

15 (20.5)

7 (9.6)

11 (15.1)

2 (2.7)

Table 4.11 presents the distributions of residential subscribers over

occupational categories by the type of phone connection. Among the low income

group subscribers, the self-employed, privately employed and others categories

of subscribers without STD facility account for 31.5 percent, 15.1 percent and

4.1 percent respectively. These percentages are higher for those who have STD

facility. An interesting point to note is that majority of the government

employed subscribers have STD facility in both income groups.

4 . 3 ~ The non-residential subscribers

Non-residential subscribers are divided into four types. (i) Subscribers

who are engaged in manufacturing some products or raw materials (ii)

subscribers who are doing wholesale or retail business (iii) subscribers who are

financiers or indigeneous bankers and (iv) others including some self employed

persons like share-brokers, agents and dealers etc.

TABLE 4.12

DISTRIBUTION OF SUBSCRIBERS IN BUSINESS CATEGORIES BY THEIR BIMONTHLY SALES TURNOVER

Note : The figure^ in parantheses are percentages to respective group totals

Row Total

29 (16 9) - 53

(30.8)

24 (14.0)

66 (38.3)

172 (100.0)

High sales turnover Group

9 (22.0)

13 (31.7)

8 (19.5)

11 (26.8)

4 1 (23.8)

Busineee Categories

~ a n u f a c ' t u r i n ~ units

Trade

Finance

Others

Column Total

Low sales turnover Group

20 (15.3)

40 (30.5)

16 (12.2)

55 (42.0)

131 (76.2)

Table 4.12 gives the distribution of subscribers in business categories by

their bimonthly sales turnover. For non-residential subscribers or business

subscribers, sales turnover is considered as an important variable that

determines the demand for telephone calls. Hence their bimonthly sales

turnover is taken for analysis, and it is grouped into two categories.

(i) bimonthly sales turnover upto (low sales turnover group) Rs.10 lakhs

(ii) bimonthly sales turnover above Rs.10 lakhs (high sales turnover group).

Low sales turnover group subscribers account for 76.2 percent of the total non-

residential subscribers and the rest are high sales turnover group subscribers.

The majority of the business subscribers (72.5%) in the low sales turnover

group belong to others and trade categories while in the high sales turnover

group, more number of subscribers are in trade category followed by others

category.

TABLE 4.13

DISTRIBUTION OF SUBSCRIBERS BUSINESS CATEGORIES BY THE NUMBER OF EMPLOYEES EMPLOYED

Note The figures m parantheses are percentages to respective group totals

Bunineu Cahg0ri68

Manufacturing un~ts

Trade

Rnance

*

Others

-

High ales turnover Group Low ralem turnover Group

Above ,, 2

(4 9)

2 (4.9)

1 (2.4)

0

11-100

2 (4 9)

6 (14.6)

2 (4 9)

2 (4.9)

No. of Emplyee.

0

0

0

0

Ahwe 100

0

1 (0 8)

0

0

sl-lm

0

0

0

0

'

No. of Emplyeer

1 (08)

1 (0.8)

0

3 (2.3)

U P ~ ' 10

(2 4)

2 (4.9)

0

0

1140

1 4 (9 8)

3 (7 3)

5 (12.2)

9 (22.0)

10

14 (10 7)

27 (20.6)

12 (9.2)

37 (28 2)

'ldO

5 (3 8)

11 (8 4)

4 (3 1)

15 (11 5 )

Table 4.13 shows that firms or business units in low sales turnover

group generally employ 10 workers or less. Only one firm in low sales turnover

group has more than 50 employees. For the high sales turnover group, the

concentration of units is distributed in 11-50 and 51-100 employees categories;

only a few firms have more than 100 employees.

TABLE 4.14

DISTRIBUTION OF BUSINESS CATEGORLES OF SUBSCRIBERS BY THE TYPE OF PHONE CONNECTION

Note : The figures in parentheses are percentages to respective group totals.

Business Categories

Manufacturing

Trade

Finance

Others

Colum Total

It is evident from the Table 4.14, that 40.5 percent subscribers in the

low sales turnover group and 97.6 percent in the high sales turnover group

have STD facility. In the low sales turnover group about three-fifth of the

Low sales turnover Group -

STD

12 (9.2)

26 (19.8)

10 (7.6)

30 (22.9)

7 8 (59.5)

High sales turnover Group

STD

8 (6.1)

14 (10.7)

6 (4.6)

25 (19.1)

53 (40.5)

- STD

0

0

0

1

1 (2.4)

STD

9 (22.0)

13 (31.7)

8 (19.5)

10 (24.4)

40 (97.6)

subscribers do not have STD facility, in the high sales turnover group except

one all have STD facility.

TABLE 4.15

DISTRIBUTION OF LOW SALES TURNOVER GROUP SUBSCRIBERS BY NUMBER OF PULSES CHARGED

FOR DIFFERENT TYPE OF CALLS

Note : The figures in parentheses are percentages to total for each type of call.

Budneu Categoriem Upto 800 P u k e

(i) Manufacturing unite

601.1800 P u .

a. h l Calls

b STD Calls

c. ISD Calls

1201-1800 Pulses

6 (4.6)

4 (3 1)

2 (1.5)

(ii) Trade

1801-8400 hrleee

4 (3.1)

2 (1.5)

0

a Local Calls

b. STD Calla

c. ISD Calle

Above 2400 PuLser

5 (3.8)

1 (0 8)

1 (0 8

- - STDIIE3D

9 (6.9)

6 (4 6)

3 (2.3)

(iii) Finance

2 (1.5)

0

1 (0 8)

5 (3.8)

1 (0.8)

1 (0 8)

9 (6.9)

2 (1.5)

0

10 (7 6 )

13 (9 9)

3 (2.3)

1 (0.8)

1 (0.8)

10 (7.6)

1 (0.8)

2 (1.5)

7 (5.3)

4 (3.1)

1 (0 8)

12 (9 2)

15 (11.5)

26 (19.8)

33 (25 2)

2 (1 5

0

1 (0.8)

a . Local Calls

b STD Calls

c ISD Calls

(iv) Othem

3 (2 3)

2 ( 1 5)

1 (0.8)

2 (1.5)

1 (0.8)

1 (0 8)

7 (53)

2 ( 1 5)

0

2 ( 1 5)

1 (0.8)

0

30 (22.9)

44 (33.6)

5 (3.8)

8 (5.3)

3 (2.3)

5 (3 8)

1 (0.8)

1 (0.8)

5 (3.8)

2 (1.5)

0

15 (11.5)

4 (3.1)

2 (1.5)

a Local Calls

b. STD Calla

c ISD Calls

25 (19.1)

11 (8 4)

5 (3.8)

It is evident from Table 4.15, more number of subscribers in all business

categories except trade have metered upto 600 pulses for the local calls. Only

40.5 percent of them have made STD calls; of whom greater number of

subscribers are charged 1200 local pulses or less in all business categories.

TABLE 4.16

DISTRIBUTION OF HIGH SALES TURNOVER GROUP SUBSCRIBERS BY NUMBER OF PULSES CHARGED

FOR DIFFERENT TYPE OF CALLS

Note : The figures in parentheem are percentages to total for each type of call

,

Upto 800 801-1200 1201-1800 1801-2400 Above UOO - - B*erCatolode' I F ' ~ w I ~ I Pvlu I P u h n 1 PuLa I Puleen I STDKSD

Manufacturing

a. Local Calla

b. STD Calls

c. ISD Calla

1 (2.4)

0

0

Trade

1 (2.4)

0

0

a. Local Calla

b. STD Calls

c ISD Calla

1 (2.4)

0

0

2 (4.9)

0

1 (2.4)

Mnance

0

0

1 (2.4)

2 (4.9)

1 (2 4)

2 (4.9)

3 (17.3)

6 (14.6)

9 (22.0)

3 (7.3)

2 (4 9)

0

1 (2 4)

3 (7.3)

5 (12.2)

2 (4.9)

5 (12.2)

a. Local Calla

b. STD Calls

c. ISD Calls

Othere

1 (2.4)

0

0

0

1 (2 4)

0

2 (4.9)

0

2 (4.9)

1 (2.4)

3 (7.3)

6 (14 6)

12 (29.3)

7 (17.1)

2 (4.9)

2 (4.9)

0

2 (4.9)

1 (2 4)

' 0

1 (2.4)

2 (4.9)

0

2 (4.9)

3 (7.3)

0

2 (4.9)

4 (9.8)

10 (24.4)

2 (4.9)

1 (2.4)

0

2 (4.9)

a. Local Calla

b. STD Calls

c. ISD Calls

1 (2.4)

0

0

Table 4.16 reveals the highest percentage of high sales turnover group

subscribers come under 2400 or more local pulses in each business category.

In total, 46.3 percent of subscribers in all business categories are charged

above 2400 local pulses for the local calls made. The number of subscribers

who have made STD calls in the high sales turnover group account for 97.6

percent; out of whom 87.9 percent of subscribers are charged above 2400 local

pulses for STD calls made. Nearly 68 percent of high sales turnover group

subscribers have made ISD calls; of whom the largest percentage of subscribers

are charged above 2400 local pulses.

TABLE 4.17

DISTRIBUTION OF SUBSCRIBERS IN BUSINESS CATEGORIES BY TOTAL PULSES CHARGED (AGGREGATE)

Oc~upatiollPl Categorier Upto 1000 -#

Manufacturing

1001-2000 Pulses

a Low sales turnover P U P

b. High sales turnover group

2001-3000 P u k e

6 (4.6)

0

Trade

3001-4000 Puleer

3 (2 3)

0

7 (5.3)

0

Above 4000 Pulses

a. Low sales turnover group

b. High sales turnover p u p

2 (1 5)

0

17 (13 0)

0

7 (5 3)

0

2 ( 1 5)

9 (22 0)

Finance

7 (5 3)

1 (2 4)

2 ( 1 5)

0

3 (2.3)

1 (2 4)

1 (0.8)

0

7 (5 3)

12 (29 3)

2 (1.5)

6 (14.6)

3 (2.3)

1 (2 4)

a Low sales turnover group

b. High sales turnover p u p

Othelr

7 (5.3)

0

9 (6 9)

9 (22 0)

4 (3.1)

0

11 (8.4)

0

a Low sales turnover 27 group , (20.6)

4 (3.1)

2 (4 9)

b High sales turnover group

0

Table 4.17 presents the distribution of non-residential subscribers over

the business categories by the total number of pulses charged for different type

of calls. The largest percentage of low sales turnover group subscribers who are

charged 2000 pulses or less for total calls made in the manufacturing, trade,

finance and others account for 9.9 percent, 18.3 percent, 7.6 percent and 29

percent respectively. In the high sales turnover group, all the subscribers

whose business activities in manufacturing category are charged above 400

local pulses for the total calls made. All the high sales turnover group

subscribers except in finance category are charged above 2000 pulses for

different type of calls made; of them 87.9 percent are charged above 4000 local

pulses for the number of total calls made.

4.4 Estimates of disaggregated demand models for residential and

non-residential subscribers

In this section, the OLS estimates of demand for different types of calls

for residential and non-residential subscribers are reported in Tables 4.18,4.19

and 4.20. We have already discussed the specification of the functional forms

in the section 4.1.

TABLE 4.18

LEAST SQUARE ESTIMATES OF DEMAND FOR CALLS BY TYPE FOR RESIDENTIAL SUBSCRIBERS

Dependent variable = logarithms of number of pulses metered for each type of call

Note : Figures in the parentheses indicate Y' values

~ x p l - ~ r g ~ ~ ~ l - I wa~ C d r I S T D C ~ ~ 1 I S D ~ ~ U ~ 1 TOW Eduoatiod Dummiar

EDU2

EDU3

EDU4

-0.0520 (-0.214)

0 2873 (1.128)

-0.1360 (-0.503)

Occupatoanl dummies

0.5488 (1.090)

0.4945 (0.923)

0 2844 (0 513)

OCCl

OCC2

OCC4

0.4213 (0.282)

-0 3350 (-0.211)

-1 1876 (-0.721)

0.4049 (1 748)

-0.0213 (-0 087)

0.5330 (1 377)

0.1733 (0.790)

0.4325 (1.876)

0.1358 (0.557)

0.4189 (1.223)

0.2661 (0.669)

0 9992 (1.089)

-0 0367 (-0 154)

0.0336 (0.132)

Age dummies

-0.7783 (-0 765)

0.3687 (0 312)

0 3361 (0 123)

0 335 (0 022)

-0 2238 (-0 134)

AGE2

AGE3

Family dm dummier

0 3218 (1.535)

-0.1359 (-0 612)

0 3722 (1 056)

-0 2110 (-1.695)

-0.3916 (-1 147)

-0.6640 (-1 998)

' -0.3716 (-1 212)

0.9712 (1.859)

0 4036 (0 719)

19794 (1 147)

18180 (1 209)

-0 5958 (-1.026)

0 0156 (0 031)

FS1

FS2

Economic variables

-0 6276 (-1 695)

-0.3916 (-1 147)

2.1063 (0 259)

-0 0263 (-0 062)

0 6314 (4 315)

-11.3934

0.63

0.5854

9.72

1.5950

128

-9 5916 (-0 215)

0 7236 (0 316)

25.9587

0.21

0.445

990

4.5910

69

7 9955 (0 533)

-0 2636 (-0 342)

-47.8765

0.65

0.5721

9.80

2.8284

69

LBHINC

SLBHINC

STD

Comtant

R'

3 Mean (LBHINC)

Elmticity

Number of subacribera

7 0256 (0 775)

-0 3031 (-0 647)

-33.0381

0.38

0.3143

9.72

1 .I333

128

The OLS estimates of demands for different types of telephone calls for

the residential category are reported in Table 4.16. The disaggregated demand

models for each type of call include the educational dummies, age dummies,

occupational dummies, family size dummies, logarithms of bimonthly

howehold income and i t square as explanatory variables. Educational (except

EDU3) and age dummies show negative effects on local calls but none of the

dummies is statistically significant at the 5% level. The coefficients of self-

employed and others are positive but none is statistically significant a t the 5%

level. The coefficienh of logarithms of bimonthly household income are positive

except in the case of ISD calls; the coefficients of its square are negative except

in the case of ISD calls.

Educational and occupation dummies have positive impact in the STD

call demand, where as in the case of age dummies AGE2 is not only positive

but also statistically significant. This result implies that more number of STD

calls are made by the subscribers whose age lie between 35 to 50 years. As in

the case of local calls, the coefficients of logarithms of bimonthly household

income and its square are positive and negative respectively. However, they

are not significant.

The fit for ISD equation is poor.

In the total calls demand model, the coefficients of educational,

occupational and age dummies are positive but they are not statistically

significant. The family size dummy FS1 is negatively associated with total call

demand and i t is significant a t the 5% level. This implies that smaller family

size leads to lesser number of total calls. As in the cases of local and STD call

equations, the logarithms of bimonthly household income and its square are

not statistically significant, though they have the correct signs.

The OLS estimates of the demand for various types of telephone calls by

non-residential subscribers are given in Table 4.18.

TABLE 4.19

LEAST SQUARE ESTIMATES OF DEMAND FOR CALLS BY TYPE FOR NON-RESIDENTIAL SUBSCRIBERS

Dependent variable = logarithms of number of pulses metered for each type of call

Note : Figures in parantheses are Y' statistics

Vnriabler I ~ o c a l 1 STD I ISD 1 ~ g ~ g a t e Budnew category dummier

MANUF

TRADE

OTHERS

0.1880 i 0 793)

0.2240 ( 1 055)

-0.0751 (-0 359)

, Output Variables

0.4854 (1.090)

0.3877 (.0954)

0.2807 (0.700)

2.4079 (2.266)

-0.0668 ' (-1.460)

0.1805 (0.136)

0.7692 (0.634)

0 4119 (0.344)

LBST

SLBST

0.2790 (1.185)

0.3736 (1.771)

0.0923 (0.445)

5.6726 (2.782)

-0.1914 (-2.219)

2.8016 (2 617)

-0.1006 (-2.183)

Age Variable

15.0808 (2.474)

-0.5951 (-2.309)

LAPC -0.5249 (-0 989)

-0.0649 (-0.757)

0 0265 (0 306)

STD dummy

-0.0649 (-0.365)

STD

Comtant

R2 i?

Mean (LNE) Elmticity

Number of rubscribem

87.9212

0.18

0.13

11.76

1.0740

93

0.8869 (5 967)

-11.1144

0.71

0.7

11.22

0.9089

172

-11.8245

0.33

0.30

11.22

0.6441

172

-32.1964

0.60

0.68

11.76

1.1709

93

For each type of call demand, the dummy variables included to capture

the impact of the type of business category are not statistically significant. As

expected, the logarithms of bimonthly sales turnover variable have shown

positive signs; they are also significant at the 5% level. This coefficient is

highly significant in local call and STD call demand equations. The coefficients

of square of logarithms of bimonthly sales turnover have negative signs in all

types of calls and the coefficients are statistically significant at the 5% level,

except in the total calls demand model. The age of phone connection, which is

iincluded to capture the influence of duration of telephone connection, has no

significant impact on all the demand models. The estimated income elasticities

for local calls, STD calls, ISD and total calls are 0.54, 1.17, 1.07 and 0.91

respectively. These elasticities imply that the local calls and total calls are

normal goods and STD and ISD calls are superior goods for non-residential

subscribers.

The OLS results for alternative specifications of demand for telephone

calls by type, for the non-residential subscribers are given in table 4.19.

TABLE 4.20

LJUST SQUARE ESTIMATES OF DEMAND FOR CALLS BY TYPE FOR NON-RESIDENTIAL SUBSCRIBERS :

ALTERNATIVE SPECIFICATIONS

Dependent variable = logarithms of number of pulses metered for each type of call

Note : Figures in parantheses are 't' statistics

Variables I Local STD ISD Aggregate

Business category dummies

MANUF

TRADE

OTHERS

0.2384 (1.020)

0.2273 (1.093)

0.0037 (0.018)

Size Variables

0.3411 (0.721)

0.2191 (0.511)

0.888 (0.211)

0.7717 (4.772)

-0.0193 (-0.591)

-0.1022 (-0.075)

0.8742 (0.708)

0.4160 (0.344)

2.5716 (2.317)

-0.3238 (-1.625)

LNE

SLNE

0.3784 (1.564)

0.3257 (1.512)

0.1272 (0.599)

Age Variable

0.6003 (3.880)

-0.0365 (-1.159)

1.4043 (3.640)

-0.0777 (-1.122)

-0.2381 (-2.709)

-0.8577 (-1.630)

-0.3785 (-2.070)

LAPC

STD dummy

-0.0665 (-0.783)

1.1612 (8.016)

6.4425

0.69

0.68

2.17

0.6879

172

3.5704

0.15

0.09

2.64

0.8619

93

6.2074

0.55

0.52

2.64

0.9940

93

STD

Constant

R2

R2 Mean (LNE)

Elasticity

Number of subscribers

6.1068

0.35

0.33

2.17

0.4419

172

The coefficients of dummy variables included to capture the effect of

each type of business category are positive, but they are not statistically

significant in all the types of telephone call demand models. The logarithms of

number of employees in the non-production unit is included in the demand

models as an alternative measure of size of the firm. It does play a positive

role in determining the demand for local calls, STD calls and total calls

demands of the non-residential subscribers. These coefficients are statistically

significant a t the 5% level except in ISD call demand. The coefficients of the

square of the logarithms of number of employees in the non-production units

show negative signs in all types of call as expected but they are not

statistically significant.

Surprisingly age of phone connection is negatively influencing the call

demand in STD and total call demand models; its coefficients is also

statistically significant a t 5% level. The coefficient of dummy variable to

capture the effect of STD connection in the total call demand equation has a

positive sign and is also statistically significant at the 5% level. This result

implies that subscribers with STD facility make more number of total calls

measured interms of local pulses. The output elasticities obtained from the

alternative functional form used for non-residential subscribers indicate that

all the type of calls are normal goods for the non-residential subscribers.

4.6 Conclusion 8

The OLS estimates of disaggregated demand models are estimated

separately for each type of call for residential and non-residential subscribers.

In the residential category the economic variables could not significantly

influence the demand for local, STD and total calls, though their coefficients

have correct signs. Educational and age dummies are negatively influencing

the local call demand, whereas the same dummies have positive impact on the

demand for STD calls. But none of these dummies are statistically significant

a t the 5% level except the age dummy AGE2 in the STD calls demand model.

The family size dummy FS1 is negatively and significantly influencing the

total call demand which implies that those subscribers who have family size

upto four member made lesser number of total calls.

In the case of non-residential subscribers, the output variables logarithm

of bimonthly sales turnover and its square significantly influence the call

demand for all types a t the 5% level with the exceptions of SLBST variable in

total call demand model. Business category dummies and age dummies do not

influence call demand significantly except the trade dummy in the total call

demand model.

The logarithm of number of employees and its square are included in the

demand models as an alternative measure of size of firms. The coefficients of

logarithm of number of employees play a positive and significant roles in

determining the local, STD and total call demand for the non-residential

subscribers. All these coefficients are statistcally significant at the 5% level

except in ISD call demand model. The coefficients of square of the logarithm

of number of employees show negative sign in all cases but they are not

statistically significant. The output elasticities obtained from the demand

equations show the local calls and total calls are normal goods