The 2011-2016 Outlook for Softwood Dressed Lumber of Less Than 2 Inches in Nominal Thickness Not Edge Worked Made from Purchased Lumber in India

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The 2011-2016 Outlook for Softwood Dressed Lumber of Less Than 2 Inches in Nominal Thickness Not Edge Worked Made from Purchased Lumber in India Powered By Docstoc
					    The 2011-2016 Outlook for Softwood
  Dressed Lumber of Less Than 2 Inches in
   Nominal Thickness Not Edge Worked
   Made from Purchased Lumber 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                                           28
5       ARUNACHAL PRADESH                                                                       34
     5.1   Latent Demand by Year - Arunachal Pradesh                                            34
     5.2   Cities Sorted by Rank - Arunachal Pradesh                                            35
     5.3   Cities Sorted By District - Arunachal Pradesh                                        36
6       ASSAM                                                                                   37
     6.1    Latent Demand by Year - Assam                                                       37
     6.2    Cities Sorted by Rank - Assam                                                       38
     6.3    Cities Sorted By District - Assam                                                   41
7       BIHAR                                                                                   45
     7.1    Latent Demand by Year - Bihar                                                       45
     7.2    Cities Sorted by Rank - Bihar                                                       46
     7.3    Cities Sorted By District - Bihar                                                   49
8       CHANDIGARH                                                                              53
     8.1   Latent Demand by Year - Chandigarh                                                   53
     8.2   Cities Sorted by Rank - Chandigarh                                                   54
     8.3   Cities Sorted By District - Chandigarh                                               54
9       CHHATTISGARH                                                                            55
     9.1   Latent Demand by Year - Chhattisgarh                                                 55
     9.2   Cities Sorted by Rank - Chhattisgarh                                                 56
     9.3   Cities Sorted By District - Chhattisgarh                                             59
10      DADRA & NAGAR HAVELI                                                                    62
     10.1  Latent Demand by Year - Dadra & Nagar Haveli                                         62
     10.2  Cities Sorted by Rank - Dadra & Nagar Haveli                                         63
     10.3  Cities Sorted By District - Dadra & Nagar Haveli                                     63


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 Contents                                                                                   vi

11      DAMAN & DIU                                                                    64
     11.1  Latent Demand by Year - Daman & Diu                                         64
     11.2  Cities Sorted by Rank - Daman & Diu                                         65
     11.3  Cities Sorted By District - Daman & Diu                                     65
12      DELHI                                                                          66
     12.1  Latent Demand by Year - Delhi                                               66
     12.2  Cities Sorted by Rank - Delhi                                               67
     12.3  Cities Sorted By District - Delhi                                           69
13      GOA                                                                            71
     13.1   Latent Demand by Year - Goa                                                71
     13.2   Cities Sorted by Rank - Goa                                                72
     13.3   Cities Sorted By District - Goa                                            73
14      GUJARAT                                                                        75
     14.1   Latent Demand by Year - Gujarat                                            75
     14.2   Cities Sorted by Rank - Gujarat                                            76
     14.3   Cities Sorted By District - Gujarat                                        82
15      HARYANA                                                                        88
     15.1  Latent Demand by Year - Haryana                                             88
     15.2  Cities Sorted by Rank - Haryana                                             89
     15.3  Cities Sorted By District - Haryana                                         92
16      HIMACHAL PRADESH                                                               95
     16.1  Latent Demand by Year - Himachal Pradesh                                    95
     16.2  Cities Sorted by Rank - Himachal Pradesh                                    96
     16.3  Cities Sorted By District - Himachal Pradesh                                97
17      JAMMU & KASHMIR                                                                99
     17.1  Latent Demand by Year - Jammu & Kashmir                                     99
     17.2  Cities Sorted by Rank - Jammu & Kashmir                                    100
     17.3  Cities Sorted By District - Jammu & Kashmir                                101
18      JHARKHAND                                                                     103
     18.1   Latent Demand by Year - Jharkhand                                         103
     18.2   Cities Sorted by Rank - Jharkhand                                         104
     18.3   Cities Sorted By District - Jharkhand                                     107
19      KARNATAKA                                                                     111
     19.1  Latent Demand by Year - Karnataka                                          111
     19.2  Cities Sorted by Rank - Karnataka                                          112
     19.3  Cities Sorted By District - Karnataka                                      118
20      KERALA                                                                        125
     20.1  Latent Demand by Year - Kerala                                             125
     20.2  Cities Sorted by Rank - Kerala                                             126
     20.3  Cities Sorted By District - Kerala                                         130
21      LAKSHADWEEP                                                                   135
     21.1  Latent Demand by Year - Lakshadweep                                        135
     21.2  Cities Sorted by Rank - Lakshadweep                                        136
     21.3  Cities Sorted By District - Lakshadweep                                    136
22      MADHYA PRADESH                                                                137
     22.1  Latent Demand by Year - Madhya Pradesh                                     137
     22.2  Cities Sorted by Rank - Madhya Pradesh                                     138


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     22.3    Cities Sorted By District - Madhya Pradesh                               147
23      MAHARASHTRA                                                                   157
     23.1  Latent Demand by Year - Maharashtra                                        157
     23.2  Cities Sorted by Rank - Maharashtra                                        158
     23.3  Cities Sorted By District - Maharashtra                                    167
24      MANIPUR                                                                       176
     24.1  Latent Demand by Year - Manipur                                            176
     24.2  Cities Sorted by Rank - Manipur                                            177
     24.3  Cities Sorted By District - Manipur                                        178
25      MEGHALAYA                                                                     179
     25.1  Latent Demand by Year - Meghalaya                                          179
     25.2  Cities Sorted by Rank - Meghalaya                                          180
     25.3  Cities Sorted By District - Meghalaya                                      181
26      MIZORAM                                                                       182
     26.1   Latent Demand by Year - Mizoram                                           182
     26.2   Cities Sorted by Rank - Mizoram                                           183
     26.3   Cities Sorted By District - Mizoram                                       183
27      NAGALAND                                                                      184
     27.1  Latent Demand by Year - Nagaland                                           184
     27.2  Cities Sorted by Rank - Nagaland                                           185
     27.3  Cities Sorted By District - Nagaland                                       185
28      ORISSA                                                                        186
     28.1   Latent Demand by Year - Orissa                                            186
     28.2   Cities Sorted by Rank - Orissa                                            187
     28.3   Cities Sorted By District - Orissa                                        191
29      PONDICHERRY                                                                   195
     29.1  Latent Demand by Year - Pondicherry                                        195
     29.2  Cities Sorted by Rank - Pondicherry                                        196
     29.3  Cities Sorted By District - Pondicherry                                    196
30      PUNJAB                                                                        197
     30.1   Latent Demand by Year - Punjab                                            197
     30.2   Cities Sorted by Rank - Punjab                                            198
     30.3   Cities Sorted By District - Punjab                                        202
31      RAJASTHAN                                                                     206
     31.1   Latent Demand by Year - Rajasthan                                         206
     31.2   Cities Sorted by Rank - Rajasthan                                         207
     31.3   Cities Sorted By District - Rajasthan                                     212
32      SIKKIM                                                                        218
     32.1   Latent Demand by Year - Sikkim                                            218
     32.2   Cities Sorted by Rank - Sikkim                                            219
     32.3   Cities Sorted By District - Sikkim                                        219
33      TAMIL NADU                                                                    220
     33.1  Latent Demand by Year - Tamil Nadu                                         220
     33.2  Cities Sorted by Rank - Tamil Nadu                                         221
     33.3  Cities Sorted By District - Tamil Nadu                                     240
34      TRIPURA                                                                       260
     34.1   Latent Demand by Year - Tripura                                           260

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 Contents                                                                                   viii

     34.2    Cities Sorted by Rank - Tripura                                          261
     34.3    Cities Sorted By District - Tripura                                      262
35      UTTAR PRADESH                                                                 263
     35.1   Latent Demand by Year - Uttar Pradesh                                     263
     35.2   Cities Sorted by Rank - Uttar Pradesh                                     264
     35.3   Cities Sorted By District - Uttar Pradesh                                 280
36      UTTARANCHAL                                                                   296
     36.1   Latent Demand by Year - Uttaranchal                                       296
     36.2   Cities Sorted by Rank - Uttaranchal                                       297
     36.3   Cities Sorted By District - Uttaranchal                                   299
37      WEST BENGAL                                                                   301
     37.1  Latent Demand by Year - West Bengal                                        301
     37.2  Cities Sorted by Rank - West Bengal                                        302
     37.3  Cities Sorted By District - West Bengal                                    310
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 Introduction                                                                                                           9


1     INTRODUCTION
1.1    OVERVIEW

This study covers the latent demand outlook for softwood dressed lumber of less than 2 inches in nominal thickness
not edge worked made from purchased lumber 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 4,800 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
softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber.
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
softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber 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 $ mln.

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 softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made
from purchased lumber 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.


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    Introduction                                                                                                      10


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, though one is implied). The units used in this report are U.S.
dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends). If inflation rates vary in a
substantial way compared to recent experience, actually sales can also exceed latent demand (not adjusted for
inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution
inefficiencies that reduce actual sales below the level of latent demand.

As mentioned in the introduction, this study is strategic in nature, taking an aggregate and long-run view, irrespective
of the players or products involved. In fact, all the current products or services on the market can cease to exist in
their present form (i.e., at a brand-, R&D specification, or corporate-image level) and all the players can be replaced
by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be latent demand for softwood
dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber at the
aggregate level. Product and service offerings, and the actual identity of the players involved, while important for
certain issues, are relatively unimportant for estimates of latent demand.

1.3      THE METHODOLOGY

In order to estimate the latent demand for softwood dressed lumber of less than 2 inches in nominal thickness not
edge worked made from purchased lumber across the states or union territories and cites of India, I used a multi-
stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In
this case, I heavily rely on the use of certain basic economic assumptions. In particular, there is an assumption
governing the shape and type
				
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Description: This econometric study covers the latent demand outlook for softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber 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 4,800 cities in India. 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 softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber. 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 softwood dressed lumber of less than 2 inches in nominal thickness not edge worked made from purchased lumber in India. It also shows how the P.I.E. is divided and concentrated across the cities and regional markets of India.
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