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
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