The 2011-2016 Outlook for Fetal Monitors
in India
by
Professor Philip M. Parker, Ph.D.
Chaired Professor of Management Science
INSEAD (Singapore and Fontainebleau, France)
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About the Author
Dr. Philip M. Parker is the Chaired Professor of Management Science at INSEAD where he has taught courses on
global competitive strategy since 1988. He has also taught courses at MIT, Stanford University, Harvard University,
UCLA, UCSD, and the Hong Kong University of Science and Technology. Professor Parker is the author of six
books on the economic convergence of nations. These books introduce the notion of “physioeconomics” which
foresees a lack of global convergence in economic behaviors due to physiological and physiographic forces. His
latest book is "Physioeconomics: The Basis for Long-Run Economic Growth" (MIT Press 2000). He has also
published numerous articles in academic journals, including, the Rand Journal of Economics, Marketing Science, the
Journal of International Business Studies, Technological Forecasting and Social Change, the International Journal
of Forecasting, the European Management Journal, the European Journal of Operational Research, the Journal of
Marketing, the International Journal of Research in Marketing, and the Journal of Marketing Research. He is also
on the editorial boards of several academic journals.
Dr. Parker received his Ph.D. in Business Economics from the Wharton School of the University of Pennsylvania
and has Masters degrees in Finance and Banking (University of Aix-Marseille) and Managerial Economics
(Wharton). His undergraduate degrees are in mathematics, biology and economics (minor in aeronautical
engineering). He has consulted and/or taught courses in Africa, the Middle East, Asia, Latin America, North America
and Europe.
About this Series
The estimates given in this report were created using a methodology developed by and implemented under the direct
supervision of Professor Philip M. Parker, the Chaired Professor of Management Science, at INSEAD. The
methodology relies on historical figures across states or union territories. Reported figures should be seen as
estimates of past and future levels of latent demand.
Acknowledgements
Some of the methodologies and research approaches used in this report have benefited from the R&D Committee at
INSEAD, whose research support is gratefully acknowledged.
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Contents v
Table of Contents
1 INTRODUCTION 9
1.1 Overview 9
1.2 What is Latent Demand and the P.I.E.? 9
1.3 The Methodology 10
1.3.1 Step 1. Product Definition and Data Collection 11
1.3.2 Step 2. Filtering and Smoothing 12
1.3.3 Step 3. Filling in Missing Values 12
1.3.4 Step 4. Varying Parameter, Non-linear Estimation 13
1.3.5 Step 5. Fixed-Parameter Linear Estimation 13
1.3.6 Step 6. Aggregation and Benchmarking 13
2 SUMMARY OF FINDINGS 15
2.1 The Latent Demand in India 15
2.2 Top 100 Cities Sorted By Rank 16
2.3 Latent Demand by Year in India 19
3 ANDAMAN & NICOBAR ISLANDS 20
3.1 Latent Demand by Year - Andaman & Nicobar Islands 20
3.2 Cities Sorted by Rank - Andaman & Nicobar Islands 21
3.3 Cities Sorted By District - Andaman & Nicobar Islands 21
4 ANDHRA PRADESH 22
4.1 Latent Demand by Year - Andhra Pradesh 22
4.2 Cities Sorted by Rank - Andhra Pradesh 23
4.3 Cities Sorted By District - Andhra Pradesh 27
5 ARUNACHAL PRADESH 31
5.1 Latent Demand by Year - Arunachal Pradesh 31
5.2 Cities Sorted by Rank - Arunachal Pradesh 32
5.3 Cities Sorted By District - Arunachal Pradesh 32
6 ASSAM 33
6.1 Latent Demand by Year - Assam 33
6.2 Cities Sorted by Rank - Assam 34
6.3 Cities Sorted By District - Assam 35
7 BIHAR 37
7.1 Latent Demand by Year - Bihar 37
7.2 Cities Sorted by Rank - Bihar 38
7.3 Cities Sorted By District - Bihar 39
8 CHANDIGARH 41
8.1 Latent Demand by Year - Chandigarh 41
8.2 Cities Sorted by Rank - Chandigarh 42
8.3 Cities Sorted By District - Chandigarh 42
9 CHHATTISGARH 43
9.1 Latent Demand by Year - Chhattisgarh 43
9.2 Cities Sorted by Rank - Chhattisgarh 44
9.3 Cities Sorted By District - Chhattisgarh 45
10 DADRA & NAGAR HAVELI 47
10.1 Latent Demand by Year - Dadra & Nagar Haveli 47
10.2 Cities Sorted by Rank - Dadra & Nagar Haveli 48
10.3 Cities Sorted By District - Dadra & Nagar Haveli 48
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11 DAMAN & DIU 49
11.1 Latent Demand by Year - Daman & Diu 49
11.2 Cities Sorted by Rank - Daman & Diu 50
11.3 Cities Sorted By District - Daman & Diu 50
12 DELHI 51
12.1 Latent Demand by Year - Delhi 51
12.2 Cities Sorted by Rank - Delhi 52
12.3 Cities Sorted By District - Delhi 53
13 GOA 54
13.1 Latent Demand by Year - Goa 54
13.2 Cities Sorted by Rank - Goa 55
13.3 Cities Sorted By District - Goa 55
14 GUJARAT 56
14.1 Latent Demand by Year - Gujarat 56
14.2 Cities Sorted by Rank - Gujarat 57
14.3 Cities Sorted By District - Gujarat 61
15 HARYANA 65
15.1 Latent Demand by Year - Haryana 65
15.2 Cities Sorted by Rank - Haryana 66
15.3 Cities Sorted By District - Haryana 68
16 HIMACHAL PRADESH 70
16.1 Latent Demand by Year - Himachal Pradesh 70
16.2 Cities Sorted by Rank - Himachal Pradesh 71
16.3 Cities Sorted By District - Himachal Pradesh 72
17 JAMMU & KASHMIR 73
17.1 Latent Demand by Year - Jammu & Kashmir 73
17.2 Cities Sorted by Rank - Jammu & Kashmir 74
17.3 Cities Sorted By District - Jammu & Kashmir 74
18 JHARKHAND 75
18.1 Latent Demand by Year - Jharkhand 75
18.2 Cities Sorted by Rank - Jharkhand 76
18.3 Cities Sorted By District - Jharkhand 77
19 KARNATAKA 79
19.1 Latent Demand by Year - Karnataka 79
19.2 Cities Sorted by Rank - Karnataka 80
19.3 Cities Sorted By District - Karnataka 83
20 KERALA 86
20.1 Latent Demand by Year - Kerala 86
20.2 Cities Sorted by Rank - Kerala 87
20.3 Cities Sorted By District - Kerala 90
21 LAKSHADWEEP 93
21.1 Latent Demand by Year - Lakshadweep 93
21.2 Cities Sorted by Rank - Lakshadweep 94
21.3 Cities Sorted By District - Lakshadweep 94
22 MADHYA PRADESH 95
22.1 Latent Demand by Year - Madhya Pradesh 95
22.2 Cities Sorted by Rank - Madhya Pradesh 96
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22.3 Cities Sorted By District - Madhya Pradesh 99
23 MAHARASHTRA 103
23.1 Latent Demand by Year - Maharashtra 103
23.2 Cities Sorted by Rank - Maharashtra 104
23.3 Cities Sorted By District - Maharashtra 108
24 MANIPUR 113
24.1 Latent Demand by Year - Manipur 113
24.2 Cities Sorted by Rank - Manipur 114
24.3 Cities Sorted By District - Manipur 114
25 MEGHALAYA 115
25.1 Latent Demand by Year - Meghalaya 115
25.2 Cities Sorted by Rank - Meghalaya 116
25.3 Cities Sorted By District - Meghalaya 116
26 MIZORAM 117
26.1 Latent Demand by Year - Mizoram 117
26.2 Cities Sorted by Rank - Mizoram 118
26.3 Cities Sorted By District - Mizoram 118
27 NAGALAND 119
27.1 Latent Demand by Year - Nagaland 119
27.2 Cities Sorted by Rank - Nagaland 120
27.3 Cities Sorted By District - Nagaland 120
28 ORISSA 121
28.1 Latent Demand by Year - Orissa 121
28.2 Cities Sorted by Rank - Orissa 122
28.3 Cities Sorted By District - Orissa 124
29 PONDICHERRY 127
29.1 Latent Demand by Year - Pondicherry 127
29.2 Cities Sorted by Rank - Pondicherry 128
29.3 Cities Sorted By District - Pondicherry 128
30 PUNJAB 129
30.1 Latent Demand by Year - Punjab 129
30.2 Cities Sorted by Rank - Punjab 130
30.3 Cities Sorted By District - Punjab 131
31 RAJASTHAN 133
31.1 Latent Demand by Year - Rajasthan 133
31.2 Cities Sorted by Rank - Rajasthan 134
31.3 Cities Sorted By District - Rajasthan 137
32 SIKKIM 140
32.1 Latent Demand by Year - Sikkim 140
32.2 Cities Sorted by Rank - Sikkim 141
32.3 Cities Sorted By District - Sikkim 141
33 TAMIL NADU 142
33.1 Latent Demand by Year - Tamil Nadu 142
33.2 Cities Sorted by Rank - Tamil Nadu 143
33.3 Cities Sorted By District - Tamil Nadu 148
34 TRIPURA 154
34.1 Latent Demand by Year - Tripura 154
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34.2 Cities Sorted by Rank - Tripura 155
34.3 Cities Sorted By District - Tripura 155
35 UTTAR PRADESH 156
35.1 Latent Demand by Year - Uttar Pradesh 156
35.2 Cities Sorted by Rank - Uttar Pradesh 157
35.3 Cities Sorted By District - Uttar Pradesh 163
36 UTTARANCHAL 169
36.1 Latent Demand by Year - Uttaranchal 169
36.2 Cities Sorted by Rank - Uttaranchal 170
36.3 Cities Sorted By District - Uttaranchal 171
37 WEST BENGAL 172
37.1 Latent Demand by Year - West Bengal 172
37.2 Cities Sorted by Rank - West Bengal 173
37.3 Cities Sorted By District - West Bengal 176
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Introduction 9
1 INTRODUCTION
1.1 OVERVIEW
This study covers the latent demand outlook for fetal monitors across the states, union territories and cities of India.
Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given across over
2,100 cities in India. For each city in question, the percent share the city is of it’s state or union territory and of India
as a whole is reported. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others. This
statistical approach can prove very useful to distribution and/or sales force strategies. Using econometric models
which project fundamental economic dynamics within each state or union territory and city, latent demand estimates
are created for fetal monitors. This report does not discuss the specific players in the market serving the latent
demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might
affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective
of the players or products involved.
This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in
virtually all of the cities in India). This study gives, however, my estimates for the latent demand, or the P.I.E., for
fetal monitors in India. It also shows how the P.I.E. is divided and concentrated across the cities and regional markets
of India. For each state or union territory, I also show my estimates of how the P.I.E. grows over time. In order to
make these estimates, a multi-stage methodology was employed that is often taught in courses on strategic planning
at graduate schools of business.
Another reason why sales do not equate to latent demand is exchange rates. In this report, all figures assume the
long-run efficiency of currency markets. Figures, therefore, equate values based on purchasing power parities across
countries. Short-run distortions in the value of the dollar, therefore, do not figure into the estimates. Purchasing
power parity estimates of country income were collected from official sources, and extrapolated using standard
econometric models. The report uses the dollar as the currency of comparison, but not as a measure of transaction
volume. The units used in this report are: US$ Million.
1.2 WHAT IS LATENT DEMAND AND THE P.I.E.?
The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not
observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market
requires under different assumptions of price, quality, and distribution, among other factors. Latent demand,
therefore, is commonly defined by economists as the industry earnings of a market when that market becomes
accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.)
or total revenues (not profit) if India is served in an efficient manner. It is typically expressed as the total revenues
potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be latent
demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of
higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same value chain,
assuming all levels maintain minimum profitability).
The latent demand for fetal monitors in India is not actual or historic sales. Nor is latent demand future sales. In fact,
latent demand can be either lower or higher than actual sales if a market is inefficient (i.e., not representative of
relatively competitive levels). Inefficiencies arise from a number of factors, including the lack of international
openness, cultural barriers to consumption, regulations, and cartel-like behavior on the part of firms. In general,
however, latent demand is typically larger than actual sales in a market.
For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues
(i.e., a calculation of price times quantity is never made, thoug