Impact of Housing on GDP Employment FULL REPORT

Study supported by DFID and Ministry of

Housing and Urban Poverty Alleviation

Impact of Investments in the Housing Sector on GDP and Employment in the Indian Economy Sponsored

April 2014

National Council of Applied Economic Research April, 2014

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ACKNOWLEDGEMENT

The Council would like to thank the officials of The Ministry of Housing

and Urban Poverty Alleviation (MoHUPA) for their valuable inputs during the

project review meetings and presentations. The study also benefited

immensely from the insights from comments by invitees from the Ministry of

Finance, Ministry of Labour, Planning Commission and the Central Statistical

Office to these presentations. The Council is particularly grateful to Support to

National Policies for Urban Poverty Reduction (SNPUPR) and DFID for their

support and funding, and to Mr. Kiran Avadhanula for facilitating the study

right from the start.


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PROJECT TEAM

Project Leaders

Poonam Munjal P.C. Parida (till Dec, 2013)

Project Advisors

D.B. Gupta Shashanka Bhide

Senior Consultant

Ramesh Kolli


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CONTENTS

Section No.

Description Page no.

Executive Summary vii

Abbreviations and Acronyms x

1. Introduction 1

Context of the study 1

Scope of Work and Study Objectives 3

Structure of the Report 4

2. Input-Output analysis 5

Introduction 5

Applications of IO Tables 6

Limitations of IO Tables 7

Input-Output Model for Impact Analysis 7

Static IO Model 7

Multipliers 9

Inter-industry Linkage Analysis 11

Methodology and Approaches to construct Housing Sector IO Table 12

Sectoral Aggregates 16

Estimates of Inter-Industry Linkages 21

Output Multiplier 22

Employment Multiplier 26

Income Multiplier 31

Tax Multiplier 33

3. Impact of Housing Demand on Economy 37

Simulation 1: 10% increase in final demand of residential construction

37

Simulation 2: An increase of Rs. 1 lakh crore in final demand of residential construction

41

Simulation 3: An increase of Rs. 1 lakh crore in final demand of other construction

45

4. Summary of Findings 51

5. Appendices 55

Appendix 1: Aggregating 130 sectors of IO Table to 21 sectors 57

Appendix 2: About Input-Output table 61

Appendix 3: Input-Output table, 2009-10 65

Appendix 4: Leontief Inverse Matrix 73

Appendix 5: Extended Leontief Inverse Matrix 76

Glossary 79


vi

Table No. Description of Tables Page no.

2.1 Aggregation Scheme 13

2.2 Mapping between 21 sectors and NIC codes 15

2.3 Identification of Formal/Informal workers 16

2.4 Sectoral share in key aggregates of IO Table (%) 17

2.5 Sectoral share in employment (%) 18

2.6 Sectors rank on share in respective aggregates 19

2.7 Capital and Labour to Output Ratios 21

2.8 Output Multiplier 23

2.9 Sectors ranking on Output multiplier 24

2.10 Output Multiplier of Residential Construction by sectors 25

2.11 Direct Employment Coefficient 27

2.12 Total (Direct + Indirect) Employment Linkage Coefficient 28

2.13 Type I Employment Multiplier 29

2.14 Total (Direct + Indirect + Induced) Employment Linkage Coefficient

30

2.15 Type II Employment Multiplier 31

2.16 Type I Income Linkages 32

2.17 Type II Income Linkages 33

2.18 Type I Tax Linkages 34

2.19 Type II Tax Linkages 35

3.1 Type I impact of a 10% increase in Final Demand in residential construction on the economy

38

3.2 Sectoral increase (Type I) in various parameters following Simulation 1

39

3.3 Type II impact of a 10% increase in Final Demand in residential construction on the economy

40

3.4 Sectoral increase (Type II) in various parameters following Simulation 1

41

3.5 Type I impact of an increase of Rs. 1 lakh crore in Final Demand in residential construction on the economy

42


43

3.7 Type II impact of an increase of Rs. 1 lakh crore in Final Demand in residential construction on the economy

44


45

3.9 Type I impact of an increase of Rs. 1 lakh crore in Final Demand in other construction on the economy

46


47

3.11 Type II impact of an increase of Rs. 1 lakh crore in Final Demand in other construction on the economy

48


49

4.1 Salient Features of previous and present studies 51


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EXECUTIVE SUMMARY

The final report of the Study on Impact of investments in the housing sector on GDP

and Employment of Indian Economy is organised in four chapters.

Chapter 1 presents the overview of the housing sector, the objectives of the

present study and the key takeaways

Chapter 2 is devoted to the methodology adopted and the description of the

data sources used for the present study. The IO model, multipliers and

multiplier analysis to carry out policy simulations are also described and

presented in this chapter.

Chapter 3 outlines the policy interventions based on several simulations.

Chapter 4 presents the key findings of the study. This is followed by

annexures.

Overview

The study is based on Input Output Model (IO). An IO model describes the

interdependence between sectors in an economy. In other words, it simply shows the

transactions between the production sectors. The scope of transaction mainly covers

three purposes namely

(i) sell or buy inputs

(ii) sell or buy goods for final consumption, and

(iii) sell or buy goods for future use.

Here, input implies raw material being used for producing another goods or services,

known as intermediate consumption while final goods and goods for future use refer

to final consumption and capital formation (i.e. investment), respectively. An output

may be transacted for all three purposes. In other words, output of sector may be

demanded for intermediate uses by itself and the other sectors.

Direct, indirect and induced effects

If the final demand of a particular product increases, there will be an increase in the

output of that product, as production increases to meet the increase in demand. This

is known as direct effect.

As producers need to increase their output, they would also need more inputs,

therefore, there will also be an increase in demand for inputs from their suppliers.

This process goes on over the entire supply chain. This is known as indirect effect. In


viii

In response to the direct and indirect effects, the level of household income increases

due to increased employment and a proportion of this increased income are re-spent

on consumption of final goods and services. This is called the induced effect.

Multipliers

When an industry increases its production, there is increased demand for inputs from

industries. In the IO model, this demand is referred to as backward linkage.

Backward linkage is also known as output multiplier. This analyses how a change in

final demand of a sector affects the final demand of the economy.

The ratio of direct and indirect changes to the direct change due to a unit increase in

final demand is termed as type I multiplier.

The ratio of total output changes (direct + indirect + induced) to the direct output

change due to a unit increase in final demand is termed as type II multiplier

Key findings

The construction sector is disaggregated into residential construction, non-

residential construction and other construction sector and the residential

construction sector is treated as housing sector. The key findings of the report are

as follows:

1. The residential construction (housing sector) accounts for

a. 1.24% of the total output of the economy (total construction sector is

11.39%)

b. 1.00% of GDP (total construction sector is 8.2%)

c. 6.86% of the employment (total construction sector is 11.52%)

2. Housing sector is fourth largest employment generating sector.

3. 99.41 per cent of the jobs in housing sector are informal jobs.

4. Its labour to output ratio i.e. number of persons employed to produce a lakh

units of output, is 2.34 and is the highest among all the sectors.

5. The type I output multiplier for housing sector is 2.33 and type II is 5.11 i.e.

the increase of 1 unit in the final demand of housing translates into induced

cumulative revenues of 5.11 units in the economy.

6. For every lakh invested in the housing sector, 2.69 new jobs (2.65 informal

and 0.4 formal) are created in the economy. With induced effect, the number

of jobs created would be 4.06 (3.95 informal and 0.11 formal).

7. For every investment in the housing sector, the household income increases

by Rs. 0.41. With induced effect, this is estimated to be Rs. 0.76.

8. For every unit of housing created the household income increases by 0.41

units. With induced effect, this is estimated to be 0.76 units.


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9. The type I income multiplier for housing sector is 1.54 and type II is 2.84. This

would mean that a unit of increase in the final expenditure in the housing

sector would generate additional income as high as 3 times the income

generated within the housing sector itself.

10. Every additional rupee invested in the housing sector will add Rs. 1.54 to the

GDP and with household expenditure considered, this is going to add Rs. 2.84.

11. For every rupee invested in creation of housing, Rs. 0.12 gets collected as

indirect taxes.


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ABBREVIATIONS AND ACRONYMS Units used in the Report 1 crore = 10 million 1 lakh = 100 thousand

Abbreviations

CFC Consumption of Fixed Capital

CIS Change in stocks/change in inventories

COE/CoE Compensation of Employees

CSO Central Statistical Office

EUS Employment and Unemployment Survey

EXP Exports of goods and services

FU/FD Final Use / Final Demand

GCE/GFCE Government Final Consumption Expenditure

GDP Gross Domestic Product

GFCF Gross Fixed Capital Formation

GVA Gross Value Added

IC Intermediate consumption

IIHS Indian Institute for Human Settlements

IMP Imports of goods and services

I-O Table Input-Output table

IOTT Input output transaction table

NAS National Accounts Statistics

NCAER National Council of Applied Economic Research

NCS Net capital stock

NIC National Industrial Classification

NIT Net Indirect tax

NSSO National Sample Survey Office

OS/MI Operating Surplus/Mixed Income

PFCE Private Final Consumption Expenditure

UA Urban Agglomeration

Val Valuables


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1. INTRODUCTION

Context of the study

1.1. India is currently experiencing rapid growth in population, both urban and

rural. Along with rapid, although somewhat haphazard, urbanization the Indian cities,

both large and medium, are also growing.1 For example in 2011 there were 53 million

plus UAs/cities compared to 35 in 2001. The urban population itself went up from

286.1 million in 2001 to 377.1 million in 2011. Similarly the number of towns in the

corresponding period increased from 5161 to 7935. This has led to steep increase in

demand for housing especially in urban areas. For example during the period 1961-

2001, the total housing stock increased from 13.3 million units to 50.95 million

units.2

1.2. The local urban governments are unable to meet this increase in demand for

housing, leading to growth of informal/unauthorized housing in the form of slums,

squatter settlements and jhuggi jhompri colonies The vast shortage of housing offers

a great opportunity to stimulate growth in the economy as housing sector is

recognized for its potential for generating income and employment3. In addition,

provision of housing, not only contributes to peoples well being and happiness,

reduced absenteeism, and higher productivity of workers, but also, as recent

researches have shown, in limiting the size of families and lower mortality and

morbidity.

1.3. According to the Report of the Technical Group for the 11th Five Year Plan

2007-12 on Estimation of Urban Housing Shortage (HUPA), at the beginning of 2007

there was an estimated shortage of 24.71 million housing units, and that the total

housing requirement during 2007-12 was estimated at 26.53 million units. The

housing shortage in the beginning of 12th Five Year Plan (2012) is estimated at 18.78

million units. According to the Report of the Technical Group for the 12th Five Year

Plan, the housing shortage during the period 2012-17 may not increase if the rate of

growth in housing stock continues to be higher than the growth in number of

1 One or two facts about Indias pace of urbanization. One there are several other developing countries, including

China and Brazil, which have experienced higher rate of urbanization; two Indias urbanization compared to its income growth has not been as rapid as of some other countries at similar stage of development. 2 The housing stock includes pucca, semi pucca and kutcha housing. It is interesting to point out that during the decade 1991-2001, the growth in housing stock was lower compared to the two previous periods. Also over the period, there was a decline in the kutcha housing units, perhaps due to various housing schemes of both the Central government and the state governments. 3 New housing also involves development of raw land including construction of roads, laying of both civic and

physical infrastructure. These in turn have huge employment potential.


2

households in the 12th Five Year Plan as observed in the last decade. Apart from

housing sector, other critical sectors from the viewpoint of income and employment

are the construction and real estate.

1.4. As per the National Accounts prepared by the CSO for 2009-10, the

contribution to GDP by the construction sector was 8.2 per cent and that of real

estate, ownership of dwellings and business services was 11.4 per cent; thus

construction and real estate contributing nearly one-fifth of Indias GDP. In terms of

employment during 2009-10, a little over 616 lakh workers were engaged in the

construction sector, and another 7.6 lakh in real estate.4

1.5. Apart from rapid urbanization, India, in the recent period, has also

undergone through a significant structural transformation from a low skilled

economy to a relatively high skilled services oriented economy. For example the

share of agriculture in Indias GDP which was around 53 per cent in 1950-51 had

declined significantly to around 14 per cent in 2011-12. A consequence of this

structural change is reduced dependence on agriculture and increased migration

from agriculture to high value added sectors like services and industry, clearly in

search of employment.

1.6. Since these sectors are largely located in urban areas, critical relevance of

urban areas as a trigger in promoting economic growth of the country needs no

further emphasis. This is clear from the fact that top 10 cities in India are estimated

to produce about 15 per cent of the GDP with 8 per cent of the population and just 0.1

per cent of land area (Indian Institute for Human Settlements, IIHS). Also the 53

million plus cities in the country are estimated to produce 32 per cent of the GDP

with 13.3 per cent of the population and just around 0.2 per cent of the land area. The

corresponding percentages for 100 largest cities of the country are 43 per cent GDP,

16 per cent of the population and just 0.24 per cent of land area.

1.7. As far as the built up area is concerned, there is huge area outside the

purview of urban local bodies, although with far less population density. An

interesting feature of urban growth in the past two decades, especially in the case of

largest 10 cities, has been the pace of growth of built up area which is seen to be

faster than the growth of population in these cities.

1.8. Another feature of current urban scenario is the relatively higher

concentration of economic output around the major urban centres and urbanized

4 It may be noted that this employment does not mean that all the workers in these sectors had full time

employment.


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states. Real estate activity is also found to be concentrated largely in large cities and

metropolitan cities as well as in the more prosperous states too. Because of

employment opportunities in urban areas compared to the rural ones, there is

considerable inflow of migrants to larger cities leading to acute housing shortages.

1.9. In view of the importance of both housing and construction sectors as critical

sectors from the viewpoint of employment and income, the present study using the

input-output framework has attempted to study the impact of investment in housing

and construction on both employment and income. In doing this we have broadly

attempted to update an earlier study conducted by IIM-A faculty. The following is

broadly the scope of work for the study.

Scope of Work and Study Objectives

1.10. (a) The present study attempts to update and substantiate the findings of the

July 2000 Report on Impact of Investment in the Housing Sector on GDP and

Employment in the India Economy. In addition the study has attempted to:

Study and assess the model used in the July 200 report including the

relevance of its assumptions, and to refine them if required.

Assess, based on the validated model, the inter-industry linkages of

housing investment: A study of direct/indirect linkages with broad

sectors of Indian economy. The study also attempts updating the input-

output data of Indian economy to reflect the contemporary reality.

Assess impact of housing investment on income generation: A

comparative study of housing with other sectors on expenditure made,

and resulting growth and income generation. The study attempts to

reassess the income multiplier parameters and suggest the most

appropriate methodology to ascertain income multiplication through

housing.

Assess impact of housing investment on Employment Generation: A

comparative study of expenditure on sectors and resulting employment

generation. The study will attempt to reassess the change in labor

intensity and coefficients across sectors and sector-wise employment

multiplier assumptions to update the comparative employment

potential of the housing sector in terms of volumes and investments.

(b) The study attempts to assess on a broad basis the inter-linkages between

housing, construction and construction materials and to the extent practicable, the

real estate development sectors, drawing inferences on the drivers of growth and key

points on inter linkages.


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(c) The study attempts to draw possible inferences for short and long term

policy interventions.

Structure of the Report

1.11 The report is presented in four sections. The first section is introductory and

broadly outlines the importance of housing and construction sectors as generator of

income and employment provider. Inter alia, it also provides an idea of the scope of

study. The second section discusses in detail the methodology used to construct the I-

O table and the data used. The IO model, multipliers and multiplier analysis to carry

out policy simulations are also described and presented in this section. The following

section contains the results of policy simulations using output, employment, income

and tax multipliers. The concluding section summarizes the major findings of the

study. Inter alia, we indicate briefly the limitations of the study.


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2. INPUT-OUTPUT ANALYSIS

Introduction

2.1. Any economic activity of a region has both direct and indirect economic

benefits. Same is the case with construction sector, a vital component of housing

sector. It is evident that when the demand for this sector increases, its output

increases in order to meet this growing demand. This is clearly the sectors direct

impact on the economy. However, in order to meet this demand, the output of those

sectors also increases which provide inputs to construction sector and hence have

strong backward linkages with the sector. These input-providers produce the indirect

impact on the economys output and employment. While the value of output of the

construction sector may reflect the value of inputs, income generated by the

construction sector does not fully account for the income and employment that is

generated by the input suppliers. The multiplier effects of development of the

housing sector on income and employment need to be captured to understand the

impact of development of this sector on the economy.

2.2. There are a number of ancillary industries which support the growth of

construction sector, like steel, cement, glass, brick, wood and certain consumer

durables etc. Further, the industries that provide the inputs to these ancillary

industries also gain momentum. Hence, due to the inter-linkages among all the

sectors of economy, the overall economic impact of a particular sector far exceeds the

direct impact. The impact arising from such inter-linkages is called indirect impact or

the second-round impact or the spill-over impact.

2.3. The Input-Output (IO) model is a widely used and scientific method to

measure these inter-linkages and hence arrive at direct as well as indirect impact of

an economic sector. The need for input-output analysis arises from the fact that the

researchers, businesses and government policy makers may want to understand the

inter-industry linkages, linkages between final uses and output and impact of policy

decisions in the economy in terms of employment, income and taxes it generates and

also what capital and imports it needs to grow. The impact analysis can be in terms

of how other industries depend on the industry under study or how this industry

impacts on other industries. An IO model enables these impact analyses as this model

in its simplest form is a full articulation of inter-industry analysis and facilitates

impact analysis.


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2.4. With the quantification of these inter-linkages, it is possible to see how, an

additional demand in a particular sector affects other sectors of the economy through

its backward linkages and vice-versa through the forward linkages. Although some of

these questions can be answered intuitively, but the advantage of the IO model is that

it quantifies the impact through a value of the multiplier by which a particular sector

is expected to grow following a change in demand in the housing sector.

2.5. The impact estimates derived from the IO analysis is based on the economic

activity during one specific year, for which IO table is constructed. However, the IO

multipliers can be assumed to remain stable during a certain period, typically up to 5

years, unless the economys structure changes significantly.

Applications of IO Tables

2.6. Input-Output tables, now prepared by most of the economies, are powerful

tools and are applied for various purposes. The primary advantage of input-output

tables is the generation of multipliers output, income and employment multipliers.

Unlike economic base multipliers5, which calculate only one multiplier, input-output

multipliers are calculated for all the industries. It is able to reveal the impact of

growth or decline in one industry on all the other industries of the economy.

Similarly, it generates employment multipliers for all the sectors.

2.7. Further, with the multiplier analysis, input-output tables can be used for

impact assessment. It brings out the impact of change in final demand of one sector

on the output of that sector as well as the output of all other sectors of the economy.

Another use of these tables is in projections of sectoral level output. By multiplying

the vector of projected or forecasted value of final demand of each industry by the

input coefficient matrix, one arrives at the projected value of output of each industry.

5 The economic base multiplier corresponds to the economic base theory, which assumes that any local economy

can be divided into two economic activities basic and non-basic. Basic activities are those that produce goods (services) for export and non-basic activities are those that produce goods (activities) for local use. An increase (or decrease) in basic activities leads to an increase (decrease) in income flow in the local economy. This results in the increased (decreased) local demand for goods and services, which in turn increases (decreases) the non-basic activities. This is called the multiplier effect. The economic base multiplier is usually calculated in terms of employment and is expressed as the change in total employment in basic and non-basic activities with respect to change in employment in basic activities.


7

Limitations of IO Tables

2.8. The model derived from the table assumes that the present coefficients will

remain constant under the projected conditions. Therefore, it can be used for short-

term projections. In the longer range, coefficients are affected by changes in relative

prices, appearance of new industries or elimination of outdated industries, and

technological change in the production processes (Berke, Godschalk, and Kaiser,

2006). The prices of inputs change over time which may result in the industries

switching to alternative inputs or change the balance between labour and capital

inputs. The greater the rate of economic change in the system, the lesser reliable is

the fixed input-output coefficients. However, the price adjustments could be done

using the price ratios of base year to projected year. By specifying the changes in

technology input-output coefficients can be modified for applications in longer term

projections or analysis.

Input-Output Model for Impact Analysis

2.9. Input-output analysis starts with the calculation of input-output coefficients.

They are calculated by dividing each entry of the IO table by the corresponding

column total. The input coefficients can be interpreted as the corresponding shares of

costs for goods, services and primary inputs in total input (equals total output). As

the input coefficients cover all inputs including the residual variable operating

surplus, they add up to unity. The primary inputs consist of intermediate imports,

taxes less subsidies on products, compensation of employees, other net taxes on

production, and gross operating surplus.

2.10. The output coefficients describe the output structure of produced goods and

services. The output coefficients are calculated by dividing each entry of the input-

output table by the corresponding row total. They can be interpreted as the shares in

total output (revenue) or market shares for products and primary inputs. For value

added, they reflect the distribution of primary inputs. The final use here consists of

final consumption expenditures (by households, non-profit institutions serving

households (NPISH) and government), gross fixed capital formation, changes in

inventories and exports of goods and services.

Static IO Model

2.11. The input and output coefficients are used to prepare IO models which are

required for impact analysis and understanding inter-industry linkages. A well

known input-output model is the static input-output system of Wassily Leontief. It is

a linear model which is based on Leontief production functions and a given vector of


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final demand. The objective is to calculate the unknown activity (output) levels for

the individual sectors (endogenous variables) for the given final demand (exogenous

variables).

2.12. As we have seen earlier, the IO table depicts all the inter-industry

transactions of the economy. A row in an I-O table shows the sales made by one

economic sector to various sectors and final uses, whereas a column shows what the

sector purchased from different sectors for its intermediate consumption and

primary inputs, consisting of taxes less subsidies on production and imports, imports

of goods and services, compensation of employees, consumption of fixed capital and

net operating surplus/mixed income. The IO table with n sectors is shown below:

Intermediate uses Final uses Gross

output 123......j.....n Consumpti

on

expenditur

e

Capital

Formati

on

Net

Expor

ts

1 x 11 x 12 ....xi J....x1n c1 f1 e1 X1

2 x 21 x 22 ....x2j....x 2n c2 f2 e2 X2

. ............................... . . . .

. .............................. . . . .

I x i1 x i2.......x ij......x in ci f i ei Xi

. . ............................. . . . .

N x n1 x n2......xnj.....x nn cn fn en Xn

Primar

y

inputs

p1 p2 ........... pj............. pn C F E

The above matrix represents the following set of n balance equations:-

x i = x i1 + x i2 ..................+x in +y i, i =1,2......n, Yi is final use

Denoting aij for input output coefficient representing the output of sector i absorbed

by sector j per unit of output of sector j, we get,

xi=a i1 x1 + a i2 x 2...........a inx n +y i, i = 1,2........n, xij=aijxj

These equations can be written in matrix notations as

X = AX + Y or (I-A)X=Y

X = (I-A)-1Y


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2.13. A is the input-output coefficient matrix, (I-A) is known as Leontief matrix and

(I-A)-1 is the Leontief inverse matrix. This is the static open input-output model. It is

clear from above that the input-output system attains equilibrium in terms of supply

and demand: when there is a change in the final demand conditions, the application

of input-output system indicates the new set of output levels of sectors that establish

a new equilibrium to meet the changed final demand conditions. Thus, the input-

output analysis is an economic application of general equilibrium theory, when we

have the coefficient matrix A, and a given final demand vector y.

2.14. On the diagonal of Leontief matrix, net output is given for each sector with

positive coefficients (revenues) while the rest of the matrix covers the input

requirements with negative coefficients (costs). The Leontief inverse (I-A)-1 reflects

the direct and indirect requirements for domestic intermediates for one unit of final

demand. The difference between Inverse Matrix and A matrix corresponds to the

indirect input requirements of the economy for one unit of FD. The column sum of the

inverse can be interpreted as output multiplier which reflects the cumulative revenues

of the economy which are induced by one additional unit of final demand of a certain

product. For example, if the output multiplier of an industry is 2.12 then the increase

of 1 unit in the final demand for this industry translates into the induced cumulative

revenues of 2.12 units in the economy. Further description of multipliers is given in

the section below.

Multipliers

2.15. If the final demand of a particular product increases, there will be an increase

in the output of that product, as production increases to meet the increase in demand.

This is known as direct effect. However, as producers need to increase their output,

they would also need more inputs, therefore, there will also be an increase in demand

for inputs from their suppliers. This process goes on over the entire supply chain.

This is known as indirect effect. The most frequently used types of multipliers in

input-output analysis are those that estimate the effects of the exogenous changes of

final demand (consumption, investment, exports) on outputs of the sectors in the

economy and value added.

2.16. In addition to the indirect effects which arise as a result of inter-industry

linkages, there are induced effects on output, income and employment which are

triggered by the household consumption expenditure. In response to the direct and

indirect effects, the level of household income increases due to increased

employment and a proportion of this increased income are re-spent on consumption

of final goods and services. This is called the induced effect. Hence, these effects


10

reflect the changing pattern of households spending with the increase in income due

to additional production. To arrive at the induced effects, the household account is

endogenised into the input-output framework. The household account refers to the

household income (compensation of employees) and expenditure (private final

consumption expenditure).

2.17. As mentioned above, an output multiplier for a sector j is defined as the total

value of production in all sectors of the economy that is necessary at all stages of

production in order to produce one unit of product j for final demand. The inverse

coefficients indicate how many commodities i must be produced in order to satisfy

one unit of final demand for goods and services j. By including the interdependencies

between all activities it is therefore possible to determine the total outputs, i.e.

directly and indirectly required to satisfy a given final demand. The output multiplier

depicts the cumulative revenues of the economy which are induced by one additional

unit of final demand of a certain commodity. Due to this additional unit the output

(production) multipliers are equal to 1 or above 1. The higher the multipliers, the

larger are the effects on the input-output system of the economy.

2.18. The output multiplier is called Type I output multiplier when only direct and

indirect effects are taken into account. This is expressed as the ratio of direct and

indirect output changes to the direct output change due to a unit increase in final

demand. However, when induced effects are also added to direct and indirect effects

by endogenising household account, the multiplier so obtained is called Type II output

multiplier. This is, therefore, expressed as the ratio of total output changes (direct +

indirect + induced) to the direct output change due to a unit increase in final demand.

In other words, multiplying a change in final demand for an industrys output by that

industrys output multiplier (Type I and Type II) will generate an estimate of direct +

indirect effects (in case of Type I) and direct + indirect + induced effects (in case of

Type II).

2.19. The induced effects represent the response by all local industries caused by

increased expenditures of new household income and inter-institutional transfers

generated from the direct and indirect effects of the change in final demand for a

specific industry.

2.20. Similarly, the employment multiplier for jth sector is defined as the ratio of the

total (direct + indirect in case of Type I employment multiplier and direct + indirect +

induced in case of Type II employment multiplier) employment changes per rupees

change of final demand in sector j to the direct employment change per rupees

change of final demand in sector j. The direct employment effect of a rupee worth of

increase in final demand in sector j is obtained from jth sector's employment to output

ratio or employment coefficient. The total employment change per rupees change of


11

final demand in a sector j is estimated by multiplying the row vector of the

employment coefficient with the Leontief Inverse matrix (Mij).

2.21. Income multipliers measure the change in income (compensation of

employees) which occurs throughout the economy as a result of a unit change in

income in a sector. They show the ratio of direct plus indirect (plus induced if Type II

multipliers are used) income changes to the direct income change.

Inter-industry Linkage Analysis

2.22. In the framework of the input-output model, industry production has two

kinds of economic effects on other industries in the economy. These are the

absorption effects and the diffusion effects. When industry i increases its production,

there is increased demand for inputs from industries. In the input-output model, this

demand is referred to as backward linkage. This analyses how a change in final

demand of a sector affects the final demand of the economy. Backward linkage is also

known as output multiplier. An industry with higher backward linkages than other

industries means that expansion of its production is more beneficial to the economy

in terms of causing other induced productive activities. On the other hand, an

increase in production by other industries leads to additional output required from

industry i to supply inputs to meet the increased demand. This supply function is

referred to as forward linkage and helps in analysing how a change in the rest of the

sectors influences a particular one. An industry with higher forward linkages than

other industries means that its production is relatively more sensitive to changes in

other industries output.

2.23. The direct link between final demand and industrial output describes the

deliveries of finished goods and services to the various final demand categories. It

does not take into account the intermediate outputs, i.e. raw materials and semi-

finished goods which are required to produce finished goods. These intermediates

represent the indirect links between final demand and output levels. The direct and

indirect link can be identified by multiplying the Leontief Inverse with the matrix of

final demand categories ((I-A)-1 * Y). The resulting matrix shows the industrial

output levels directly and indirectly necessary to meet the final demand

requirements. In other words, it indicates the total importance of each category of

final demand for the production of different product groups. In this compilation, all

intermediate consumption part of the domestic output is transferred to the final

demand by using Leontief Inverse.


12

2.24. Further, the interrelation between primary inputs and one unit of production

induced by final demand can be disclosed by multiplying the primary input

coefficients with the Leontief Inverse. The resulting matrix depicts how many

primary inputs are directly and indirectly used within the whole production process

in order to satisfy one unit of final demand for goods and services j. Due to the fact

that the intermediate inputs are converted into primary inputs, the total input

coefficients for primary inputs per unit of production add up to one.

2.25. The multipliers for primary inputs [B (I-A)-1] (B is input coefficients for

primary inputs) are multiplied with a matrix of final demand by category to assess

the direct and indirect primary input requirements for the various categories of final

demand (consumption, investment, exports).

Methodology and Approaches to construct Housing Sector IO Table

2.26. In India, the input-output tables are compiled by CSO periodically, once in

every five years. These tables have complete coverage of the economy and are

consistent with the national accounts. The latest IO table is available for 2007-08.

However, for the present study, we have updated it for 2009-10.

2.27. The detailed IO table consists of 130 sectors, but for a meaningful input-

output analysis, it is desirable that the sectors are aggregated such that the

aggregation scheme is aligned to the purpose of the analysis. Evidently, the sectors of

interest and the ones which these sectors are closely related to are kept separately,

subject to the availability of their data.

2.28. The aim of the present study is to assess the impact of investment in the

housing sector on GDP and Employment of the Indian Economy. Further, the

objective is to assess the inter-linkages between housing, construction, construction

materials and the real estate development sectors, drawing inferences on the drivers

of growth and key points on inter-linkages.

2.29. In this regard, the CSOs 130 sectors of the 2009-10 IO table are aggregated

to 21 broad sectors6. The list of sectors and their aggregation scheme are given in the

table below:

6 It may be mentioned that sectors in the input-output tables are not additive, as the information contained in the

IO table is not observable. The observable information (which comes from surveys and administrative data) forms the basis for compiling supply and use tables, which in turn are converted to IO tables through transformation models and technology assumptions. The sectors in the supply and use tables are additive.


13

Table 2.1: Aggregation scheme

Sr No Proposed IO Sectors - Housing Study Concordance with 130 sectors

1 Agriculture incl. Livestock 1-24

2 Forestry and Logging 25

3 Fishing 26

4 Mining and Quarrying 27-37

5 Construction related Manufacturing 55, 56, 62, 64, 69, 74-77, 79-82, 89

6 Other Manufacturing 38-54, 57-61, 63, 65-68, 70-73, 78,

83-88, 90-105

7 Residential Construction

106 8 Non-Residential Construction

9 Other Construction

10 Electricity, Water Supply 107, 108

11 Trade 116

12 Hotel and Restaurants 117

13 Railways 109

14 Transport by Other Means 110-113

15 Storage 114

16 Communication 115

17 Real Estate Services 126

18 Ownership of Dwelling and Business

Services 120, 123-125, 127

19 Banking and Insurance 118, 119

20 Public administration and defence 130

21 Other Services 121, 122, 128, 129

Source: NCAER study team

2.30. Broadly, the sector classification is the same as followed by CSO in their

National Accounts Statements. However, keeping in view the objectives of the study,

some sectors are further disaggregated to capture the inter-linkages of housing

sector. This disaggregation of sectors is as follows:

Manufacturing sector is split into Construction related manufacturing and

Other Manufacturing. The sectors that include Construction related

manufacturing were Furniture and fixtures, wood & wood products, plastic

products, coal tar products, paints, varnishes & lacquers, non-metallic mineral

products, ferrous and non-ferrous metals & products, electrical cables & wires.

Therefore for a condensed IO table, one needs to recompile the supply and use tables at that condensed dimension and then the transformation models and technology assumptions are applied to get to an aggregated IO table.


14

Construction sector is divided into residential construction, non-residential

construction and other construction activities. Residential construction

refers to the general construction of residential buildings, carried out on own-

account or on a fee or contract basis. Non-residential construction is the

construction of non-residential buildings, like schools, offices, and hospitals

etc, carried out on own-account or on a fee or contract basis. All other

construction activities construction and maintenance of roads, rail-beds,

bridges, tunnels, pipelines, rope-ways, ports, harbours, runways, power,

telecommunication and transmission lines, waterways, hydro-electric projects

etc. come under Other Construction.

The NAS sector, Real Estate, Ownership of dwellings and business services is

disaggregated into Real Estate and Ownership of dwellings and business

services.

Hence we arrive at an IO table of 21 broad sectors.

2.31. As indicated in the aggregation scheme, barring the three components of

Construction sector, all other sectors are arrived by aggregated the existing 130

sectors of the detailed IO table. The values for these three components, that is,

residential construction, non-residential construction and other construction, are

obtained by splitting each cell of the row of the total Construction sector in the

proportion of the share of their value of output in total. The values of output are

taken from the NAS.

2.32. The CSOs IO tables do not provide employment information. However,

NCAER while updating the IO table to 2009-10 also included the employment in the

IO table. To arrive at the number of persons employed in each sector, the unit level

data of NSSO large scale survey on Employment and Unemployment for 2009-10

was analysed. The 21 sectors were mapped with the NIC 5-digit codes, the industrial

codes used to identify the sector of engagement of each employed person. The

mapping of 21 sectors with the NIC codes is given in the table below:


15

Table 2.2: Mapping between 21 sectors and NIC codes

Sr No Proposed IO Sectors - Housing Study Concordance with NIC-2004

1 Agriculture incl. Livestock 01111-01500

2 Forestry and Logging 02001-02006

3 Fishing 05011-05023

4 Mining and Quarrying 10101-14299

5 Construction related Manufacturing

19202(part), 20101-20299, 23101-23109,

24221-24229, 25201-27209, 27320, 28111-

28129, 28920-28932, 28939, 28991-28999,

31300, 36101-36103, 37100-37200

6 Other Manufacturing

15111-15127, 15131-15209, 15315-15429,

15424-15549, 16001-16009, 17111-17134,

17137-19209, 21011-22300, 23201-24219,

24231-25119, 27310, 28131-28910, 28933,

29111-29309, 30001-31200, 31401-35999,

36104-35999, 36104-36933, 36994-36999,

40200, 50404, 52601-52609

7 Residential Construction 45201

8 Non-Residential Construction 45202

9 Other Construction 45101-45102, 45203-45500

10 Electricity, Water Supply 40101-40109, 40300, 41000

11 Trade 50101-50103, 50300, 50401-50403, 50500,

51101-51909, 52110-52599

12 Hotel and Restaurants 55101-55109, 55201-55209

13 Railways 60101-60109

14 Transport by Other Means 60211-63090

15 Storage 63021-63023

16 Communication 64110-64204

17 Real Estate Services 70101-70200

18 Ownership of Dwelling and Business

Services 71110-74999

19 Banking and Insurance 65110-67200

20 Public administration and defence 75111-75302

21 Other Services 80101-80904, 85110-85320, 90001-99000


2.33. Construction, by its nature of activity, generates a large proportion of

informal employment which mostly comprises of casual labour. On the other hand,

construction companies or the factor owners fall into the formal employment

category. Hence, it is worthwhile disaggregating the total employment of all the 21

sectors into formal and informal categories. By doing this, we can not only generate

the total employment coefficients and employment multipliers but also formal and

informal employment coefficients and multipliers.


16

2.34. For identifying the formal and informal nature of job, the person employed is

classified accordingly using the information on his/her status of work and the

enterprise in which employed. On the basis of this information, a person is identified

as formal and informal using the mapping given in table below:

Table 2.3: Identification of Formal/Informal workers (EUS)

Enterprise Type Formal Informal

1. Proprietary male

None All 2. Proprietary female

3. Partnership with members of same household

4. Partnership with members of diff household

5. Public sector

Status=Regular wage

earner Status=Others

6. Public/Private limited company

Status= Regular wage

earner Status= Others

7. Co-operative societies/trust/other non profit

institutions

Status= Regular wage

earner and number of

workers > 5 and job

contract is written and is

for more than 1 year

Rest 8. Employer's households

9. Others


2.35. All the employees working in the proprietary and partnership types of

enterprises are considered as informal. Barring the regular wage earners, all others

are considered to be informal in public sector or public ltd. enterprises.

2.36. In rest of the enterprises, like cooperatives, household enterprises etc., those

regular wage earners are considered formal who work in enterprises that employ

more than 5 workers and who have written job contract and the duration of contract

is more than a year. Rest all are considered informal.

Sectoral Aggregates

2.37. Apart from the inter-industry transactions, the input-output table presents

various aggregates for all the sectors, like Gross Value of Output, Gross Fixed Capital

Formation (GFCE) and Indirect taxes. Besides, employment numbers are estimated

using the NSSO survey data. The tables below present the share of each sector in total

for these aggregates.


17

Table 2.4: Sectoral share in key aggregates of IO Table (%)

Gross output at factor cost

GFCF Net Capital Stock

Indirect Taxes on production

1 Agriculture incl. Livestock 10.83 8.71 9.98 5.00

2 Forestry and Logging 0.96 0.07 0.16 0.24

3 Fishing 0.48 0.58 0.32 0.18

4 Mining and Quarrying 1.65 3.91 2.99 0.87


8.59 8.05 7.72 13.81

6 Other Manufacturing 26.55 20.22 19.47 44.12

7 Residential Construction 1.24 0.54 0.49 1.36

8 Non-Residential Construction 6.71 2.63 2.41 7.83

9 Other Construction 3.44 1.27 1.16 4.15

10 Electricity, Water Supply 2.09 6.30 6.67 2.19

11 Trade 9.24 6.70 6.60 3.03

12 Hotel and Restaurants 2.10 1.48 1.10 1.45

13 Railways 0.76 1.54 1.66 0.62

14 Transport by Other Means 6.89 2.86 2.29 9.83

15 Storage 0.05 0.09 0.11 0.04

16 Communication 0.95 3.61 1.97 0.64

17 Real Estate Services 0.24 0.51 0.60 0.15

18 Ownership of Dwelling and Business Services

6.01 14.16 16.52 1.65

19 Banking and Insurance 3.11 0.47 0.71 0.70

20 Public administration and defence 3.19 10.08 11.79 0.00

21 Other Services 4.94 6.23 5.27 2.14

100.00 100.00 100.00 100.00

Source: NCAERs 21-sector IO Table


18

Table 2.5: Sectoral share in employment (%)

Formal employment

Informal Employment

Total employment

Share of Informal in Total employment (%)

1 Agriculture incl. Livestock 0.86 57.99 54.17 99.89

2 Forestry and Logging 0.18 0.23 0.23 94.87

3 Fishing 0.09 0.34 0.33 98.24

4 Mining and Quarrying 2.59 0.45 0.59 70.80


3.27 2.60 2.64 91.71

6 Other Manufacturing 12.54 7.68 8.01 89.53

7 Residential Construction 0.61 7.31 6.86 99.41

8 Non-Residential Construction 0.13 0.44 0.42 97.86

9 Other Construction 1.66 4.42 4.24 97.38

10 Electricity, Water Supply 2.72 0.06 0.24 23.38

11 Trade 2.70 8.37 7.99 97.74

12 Hotel and Restaurants 0.46 1.25 1.20 97.41

13 Railways 2.62 0.03 0.20 12.46

14 Transport by Other Means 3.18 3.47 3.45 93.83

15 Storage 0.22 0.02 0.03 57.11

16 Communication 2.77 0.17 0.35 46.44

17 Real Estate Services 0.12 0.14 0.14 94.22


4.76 0.71 0.98 67.55

19 Banking and Insurance 6.71 0.32 0.75 39.82

20 Public administration and defence

26.10 0.05 1.79 2.55

21 Other Services 25.71 3.94 5.40 68.17

100.00 100.00 100.00 93.31

Source: NSSO 66th Round survey, 2009-10


19

2.38. The relative importance of each of these sectors can be assessed by ranking

the sectors in decreasing order of their share in respective aggregates.

Table 2.6 : Sectors rank on share in respective aggregates

Gross output at factor cost

GFCF Net Capital Stock

Indirect Taxes on production

Formal employment

Informal Employment

Total employment

1 Agriculture incl. Livestock

2 4 4 5 14 1 1

2 Forestry and Logging 16 21 20 17 18 15 18

3 Fishing 19 16 19 18 21 13 16

4 Mining and Quarrying 14 9 9 13 12 11 13


4 5 5 2 6 8 8

6 Other Manufacturing 1 1 1 1 3 3 2

7 Residential Construction

15 17 18 12 15 4 4

8 Non-Residential Construction

6 12 10 4 19 12 14

9 Other Construction 9 15 14 6 13 5 6

10 Electricity, Water Supply 13 7 6 8 9 18 17

11 Trade 3 6 7 7 10 2 3

12 Hotel and Restaurants 12 14 15 11 16 9 10

13 Railways 18 13 13 16 11 20 19

14 Transport by Other Means

5 11 11 3 7 7 7

15 Storage 21 20 21 20 17 21 21

16 Communication 17 10 12 15 8 16 15

17 Real Estate Services 20 18 17 19 20 17 20


7 2 2 10 5 10 11

19 Banking and Insurance 11 19 16 14 4 14 12

20 Public administration and defence

10 3 3 21 1 19 9

21 Other Services 8 8 8 9 2 6 5

Source: NCAERs 21-sector IO Table

2.39. Other Manufacturing which refers to all manufacturing sectors excluding

construction related manufacturing ranks first in the share in total value of output,

fixed investment (GFCF), inventory (Net Capital Stock) and Indirect taxes. The rank of

residential construction is 15th among 21 sectors with regard to its share in total

value of output. Its rank in fixed investment and inventory is even lower at 17th and


20

18th respectively. However, the sectors share in both total employment and total

informal employment is fourth which means that residential construction sector is

highly labour intensive sector as compared to other sectors. While agriculture

accounts for 54 per cent in total employment, share of residential construction stands

at 6.9 per cent. Excluding agriculture, its share goes up to 15 per cent, next only to

other manufacturing and trade.

2.40. The capital to output ratio (Table 2.7) of residential construction, expressed

as a unit value of capital stock per 100 unit value of output, is 0.61. This means that

for residential construction, Rs. 0.61 lakh of capital stock produces Rs. 1 crore of

output. As compared to this, the capital to output ratio for all the sectors of economy,

put together, is higher at 1.53.

2.41. On the other hand, labour to output ratio of residential construction is the

highest, at 2.34, among all the 21 sectors. The overall labour to output ratio is 0.42.

This means that on an average 0.42 persons are required to produce a lakh unit of

output whereas for residential construction, 2.34 persons are required to produce a

lakh unit of output, accentuating the fact that residential construction is a highly

labour generating sector and is less capital intensive as compared to other sectors of

the economy.

2.42. Further, as given in Table 2.5, the share of informal employment in total

employment in residential construction is 99.41 per cent, second highest share

among all the sectors, next only to agriculture. This share in overall employment for

the economy is 93.31 per cent.


21

Table 2.7 : Capital and Labour to output ratios

Capital to Output Ratio (units of capital per 100 units of output)

Labour to Output Ratio (persons per lakh unit of output)

1 Agriculture incl. Livestock 1.41 2.11

2 Forestry and Logging 0.26 0.10

3 Fishing 1.01 0.29

4 Mining and Quarrying 2.78 0.15

5 Construction related Manufacturing 1.38 0.13

6 Other Manufacturing 1.12 0.13

7 Residential Construction 0.61 2.34

8 Non-Residential Construction 0.55 0.03

9 Other Construction 0.52 0.52

10 Electricity, Water Supply 4.89 0.05

11 Trade 1.09 0.36

12 Hotel and Restaurants 0.80 0.24

13 Railways 3.35 0.11

14 Transport by Other Means 0.51 0.21

15 Storage 3.36 0.29

16 Communication 3.19 0.15

17 Real Estate Services 3.84 0.25

18 Ownership of Dwelling and Business Services 4.21 0.07

19 Banking and Insurance 0.35 0.10

20 Public administration and defence 5.65 0.24

21 Other Services 1.63 0.46

Overall 1.53 0.42 Source: NCAERs 21-sector IO Table

Estimates of Inter-Industry Linkages

2.43. Using the Leontief Inverse matrix, various multipliers can be obtained like

output multiplier, employment multiplier and income multiplier, which gives an

estimate of direct and indirect effects resulting from change in final demand of a

sector, hence referred as Type I multipliers. Further, the extended Leontief Inverse

Matrix, where households are included in the analysis and considered a separate

sector, gives the measure of direct, indirect and induced effects resulting from change

in final demand of a sector, referred as Type II multipliers. In the extended Leontief


22

Inverse Matrix, a row and column are added for compensation of employees (CoE)

and private final consumption expenditure coefficients respectively.

2.44. The structure of the extended technical coefficients matrix is as follows:

A =

where,

AII is the i X j technical coefficient matrix A.

AIH is the column vector of household expenditure coefficients and refers to the

amount of industry i required per unit of total household income

AHI is the row vector of income coefficients and refer to the income paid to

households per unit of output of industry i (compensation of employees divided by

the total output of the industry)

AHH is the household expenditure per unit of household income (this cell is set to

zero)

2.45. The multipliers obtained using Leontief Inverse Matrix and extended

Leontief Inverse Matrix are described in the following sections.

Output Multiplier

2.46. As mentioned in the previous section, the column sum of the Leontief Inverse

Matrix, called Type I output multiplier, is the measure of inter-industry linkages and

gives an estimate of direct and indirect effects of an industry on the overall economy.

Similarly, the column sum of the extended Leontief Inverse Matrix (excluding the

element of row for compensation to employees), called Type II output multiplier, is

also the measure of inter-industry linkages where household is included as an added

industry. The following table presents the output multiplier of each of the 21

industries. Also given are sectors CoE to output ratio (CoE/Q). It should be noted that

sectors with high CoE/Q ratio have high values of Type II multipliers as the

proportion of household income in total output is high and therefore, the changes in

their final demand gets translated into increased household income faster than

sectors with low CoE/Q ratio.

AII AIH

AHI AHH


23

Table 2.8: Output Multiplier

CoE/Q Type I Output Multiplier

Type II Output Multiplier

1 Agriculture incl. Livestock 0.1160 1.6042 2.8481

2 Forestry and Logging 0.0512 1.3337 1.9270

3 Fishing 0.0838 1.3046 2.0593

4 Mining and Quarrying 0.2094 1.5257 3.3793


0.0398 2.5887 4.0237

6 Other Manufacturing 0.0479 2.6369 4.2071

7 Residential Construction 0.2689 2.3322 5.1148

8 Non-Residential Construction 0.2419 2.4174 5.0807

9 Other Construction 0.2271 2.4641 5.0621

10 Electricity, Water Supply 0.1829 2.2257 4.6008

11 Trade 0.1239 1.4037 2.5706

12 Hotel and Restaurants 0.0918 2.2477 3.7982

13 Railways 0.4334 1.8970 5.5860

14 Transport by Other Means 0.0932 2.3670 3.9168

15 Storage 0.2031 1.9180 4.0741

16 Communication 0.2886 1.5719 3.9428

17 Real Estate Services 0.0207 1.4207 1.8313


0.0610 1.3734 2.1414

19 Banking and Insurance 0.2566 1.3211 3.3497

20 Public administration and defence 0.8880 1.0000 6.9693

21 Other Services 0.4479 1.4728 4.9103

Source: NCAER computation

2.47. An output multiplier of 2.33 for residential construction means that a unit

increase in final demand for residential construction is expected to result in an

overall increase in the economys output by 2.33 units owing to its inter-industry

linkages with other sectors of the economy. With induced effects, the overall increase

in economys output is expected to be 5.11 units.

2.48. The table below gives the ranking of the 21 sectors with respect to both Type

I and Type II output multipliers.


24

Table 2.9: Sectors ranking on Output multiplier

Rank on Type I Output Multiplier

Rank on Type II Output Multiplier

1 Agriculture incl. Livestock 11 16

2 Forestry and Logging 18 20

3 Fishing 20 19

4 Mining and Quarrying 13 14

5 Construction related Manufacturing 2 10

6 Other Manufacturing 1 8

7 Residential Construction 6 3

8 Non-Residential Construction 4 4

9 Other Construction 3 5

10 Electricity, Water Supply 8 7

11 Trade 16 17

12 Hotel and Restaurants 7 13

13 Railways 10 2

14 Transport by Other Means 5 12

15 Storage 9 9

16 Communication 12 11

17 Real Estate Services 15 21


17 18

19 Banking and Insurance 19 15

20 Public administration and defence 21 1

21 Other Services 14 6

Source: NCAER computation

2.49. Residential construction occupies sixth and third positions respectively

when Type I and Type II output multipliers of all the 21 sectors are arranged in

decreasing order. The highest Type I output multiplier is that of Other

manufacturing followed by Construction related manufacturing and then Other

construction and Non-residential construction. Hence, construction, as a whole,

has strong backward linkages with other sectors of the economy. An increase in final

demand in these sectors triggers economic activity in other sectors much faster, due

to their stronger spill-over effects. On the other hand, Type II output multiplier is the

highest for Public Administration and Defence followed by Railways which have

high income (CoE) to output ratios.


25

2.50. The following table presents the increase in output in each sector with a unit

increase in final demand of residential construction. In other words, this table

presents the break-up of the output multiplier (2.33) of residential construction.

Table 2.10: Output multiplier of Residential Construction by sectors

Unit increase in sectoral output with one unit increase in

final demand of Residential Construction

Type I Output Multiplier Type II Output Multiplier



3 Fishing 0.0002 0.0223








11 Trade 0.1288 0.3802


13 Railways 0.0082 0.0327


15 Storage 0.0007 0.0020






21 Other Services 0.0093 0.1974

Overall 2.3322 5.1148 Source: NCAER computation

2.51. The table suggests that when the final demand of residential construction

increases by one unit, then the overall increase in total output of the economy is led

by additional economic activity spurred in other sectors due to inter-industry

linkages. For example, owing to direct and indirect effects, Construction related

manufacturing increases its output by 0.4378 units, other manufacturing by


26

0.2063, mining & quarrying by 0.1164, and so on, the aggregate Type I increase

being of 2.3322 units. The second column of the table presents the unit increase in

output on the back of direct, indirect and induced effects. The aggregate increase in

output of 5.1148 units is led by 0.9908 units increase in other manufacturing,

0.5960 units in construction related manufacturing and so on.

Employment Multiplier

2.52. As mentioned earlier, Type I employment multiplier for jth sector is the ratio

of the total (direct + indirect) employment changes per rupees change of final

demand in sector j to the direct employment change per rupees change of final

demand in sector j. Type II employment multiplier for jth sector is the ratio of the

total (direct + indirect + induced) employment changes per rupees change of final

demand in sector j to the direct employment change per rupees change of final

demand in sector j.

2.53. The direct employment change per rupees change in final demand in sector j

is obtained from jth sector's employment to output ratio or direct employment

coefficient. In case of Type I employment multiplier, the total employment change per

rupees change in final demand in a sector j (total linkage coefficient comprising direct

and indirect effects) is estimated by multiplying the row vector of the employment

coefficient with the Leontief Inverse matrix. For Type II employment multiplier, the

row vector of the employment coefficient is multiplied by the extended Leontief

Inverse matrix to arrive at total linkage coefficient comprising of direct, indirect and

induced effects.

2.54. The Type I and Type II employment multipliers are also obtained for formal

and informal types of employments. The employment coefficients and employment

multipliers for all the 21 sectors are given in the following tables:


27

Table 2.11 : Direct Employment Coefficient

S. No.

Sectors Direct Employment coefficient (persons employed per lakh unit of output)

Formal Informal Total



3 Fishing 0.0050 0.2805 0.2855


5 Construction related Manufacturing 0.0107 0.1189 0.1297






11 Trade 0.0082 0.3566 0.3649


13 Railways 0.0976 0.0139 0.1114


15 Storage 0.1229 0.1636 0.2865

16 Communication 0.0823 0.0714 0.1537


18 Ownership of Dwelling and Business Services 0.0223 0.0465 0.0689



21 Other Services 0.1468 0.3143 0.4611

Overall 0.0282 0.3936 0.4218 Source: NCAER computation


28

Table 2.12 : Total (Direct + Indirect) Employment Linkage Coefficient

S.

No. Sectors

Total (Direct + Indirect) employment linkage coefficient




3 Fishing 0.0101 0.3678 0.3779








11 Trade 0.0179 0.4779 0.4958


13 Railways 0.1178 0.2419 0.3597


15 Storage 0.1445 0.3738 0.5184

16 Communication 0.0951 0.2292 0.3243





21 Other Services 0.1600 0.4796 0.6396 Source: NCAER computation

2.55. The total employment linkage coefficient calculates the impact on

employment throughout the economy arising from a change in final demand for a

sector of 1 unit. According to Table 2.12, an increase of Rs. 1 lakh in final demand in

residential construction is expected to generate a total of 2.69 jobs in the economy

owing to the sectors direct and indirect linkages. Of these, 2.34 jobs are created as a

direct effect (Table 2.11). Hence, for every one job directly created in residential

construction, 1.15 additional jobs are created in the economy (Table 2.13).

2.56. As is evident, residential construction leads all other sectors, with the

highest value of direct and total employment linkage coefficient of 2.34 and 2.69

respectively. However, when it comes to Type I employment multiplier (ratio of total

employment linkage coefficient to direct employment coefficient), non-residential


29

construction notches the highest position, with the value of 15.25. This means that a

total of 15.25 jobs are created in the economy as a result of an increase in final

demand in non-residential construction which is enough to create one job in this

sector. In other words, for every one job directly created in non-residential

construction, 15.25 new jobs are created in the economy. Also, for every one formal

job directly created, 45.61 new formal jobs are created in the economy.

Table 2.13 : Type I Employment Multiplier

S.

No. Sectors

Type I employment multiplier




3 Fishing 2.0190 1.3113 1.3237








11 Trade 2.1731 1.3400 1.3589


13 Railways 1.2074 17.4237 3.2279


15 Storage 1.1763 2.2853 1.8096

16 Communication 1.1545 3.2109 2.1095






2.57. The following tables present the impact of induced effects besides direct and

indirect effects. Table 2.14 depicts the total (direct + indirect + induced) employment

linkage coefficient and Table 2.15 presents the Type II employment multiplier.


30

Table 2.14: Total (Direct + Indirect + Induced) Employment Linkage Coefficient

S. No.

Sectors Total (Direct + Indirect + Induced) employment linkage coefficient




3 Fishing 0.0294 0.7186 0.7480








11 Trade 0.0478 1.0203 1.0681


13 Railways 0.2122 1.9566 2.1687


15 Storage 0.1997 1.3760 1.5757

16 Communication 0.1557 1.3312 1.4870







31

Table 2.15 : Type II Employment Multiplier

S.

No. Sectors

Type II employment multiplier




3 Fishing 5.87 2.56 2.62








11 Trade 5.79 2.86 2.93


13 Railways 2.17 140.91 19.46


15 Storage 1.63 8.41 5.50

16 Communication 1.89 18.65 9.67






Income Multiplier

2.58. Like employment coefficient, income coefficient is the income change per

rupees change in final demand in sector j and is obtained from jth sector's income

(compensation to employees) to output ratio. In the case of Type I income effects, the

total income change per rupees change in final demand in a sector j (total income

effects comprising direct and indirect effects) is estimated by multiplying the row

vector of the income coefficient with the Leontief Inverse matrix. For Type II income

effects, the row vector of the income coefficient is multiplied by the extended Leontief


32

Inverse matrix to arrive at total linkage effects comprising of direct, indirect and

induced effects.

2.59. Type I income multiplier for jth sector is the ratio of the total (direct +

indirect) income change per rupees change of final demand in sector j to the direct

income change per rupees change of final demand in sector j. Type II income

multiplier for jth sector is the ratio of the total (direct + indirect + induced) income

changes per rupees change of final demand in sector j to the direct income change per

rupees change of final demand in sector j. The income linkages and multipliers are

given in the tables below:

Table 2.16: Type I Income linkages

Type I

Total Income (Direct +

Indirect) linkage Income Multiplier



3 Fishing 0.1123 1.3405








11 Trade 0.1736 1.4016


13 Railways 0.5488 1.2661


15 Storage 0.3207 1.5792






21 Other Services 0.5114 1.1416 Source: NCAER computation


33

Table 2.17: Type II Income linkages

Type II

Total Income (Direct +

Indirect + Induced) linkage

Income Multiplier



3 Fishing 0.2069 2.4705








11 Trade 0.3199 2.5832


13 Railways 1.0114 2.3334


15 Storage 0.5911 2.9105






21 Other Services 0.9425 2.1041 Source: NCAER computation

2.60. For residential construction, Type I income multiplier of 1.5395 indicates

the total (direct + indirect) increase in income that results from a unit change in

income in this sector. With induced effects included, this multiplier goes up to 2.8373.

Tax Multiplier

2.61. Tax multiplier gives the extra indirect tax (on production) collected on

account of increase in production led by increase in final demand. Indirect tax, paid

by industries, is a row in the IO table. Tax coefficient for jth sector is its tax to output

ratio. In the case of Type I tax effects, the total change in tax collection per rupees

change in final demand in a sector j (total effects comprising direct and indirect


34

effects) is estimated by multiplying the row vector of the tax coefficient with the

Leontief Inverse matrix. For Type II tax effects, the row vector of the tax coefficient is

multiplied by the extended Leontief Inverse matrix to arrive at total linkage effects

comprising of direct, indirect and induced effects.

2.62. Type I tax multiplier for jth sector is the ratio of the total (direct + indirect)

tax change per rupees change of final demand in sector j to the direct tax change per

rupees change of final demand in sector j. Type II tax multiplier for jth sector is the

ratio of the total (direct + indirect + induced) tax changes per rupees change of final

demand in sector j to the direct tax change per rupees change of final demand in

sector j. The tax linkages and multipliers are given in the tables below:

Table 2.18: Type I Tax linkages

Tax to Output ratio

Type I

Total Tax (Direct + Indirect) linkage

Tax Multiplier



3 Fishing 0.0084 0.0164 1.9436








11 Trade 0.0075 0.0167 2.2263


13 Railways 0.0188 0.0419 2.2273


15 Storage 0.0176 0.0403 2.2856

16 Communication 0.0155 0.0308 1.9859




20 Public administration and defence 0.0000 0.0000 -



35

Table 2.19: Type II Tax linkages

Type II

Total Tax (Direct +

Indirect) linkage Tax Multiplier



3 Fishing 0.0327 3.8805








11 Trade 0.0420 5.5938


13 Railways 0.1218 6.4699

14 Transport

Documents

Impact of Housing on GDP Employment FULL REPORT