How to Spot Bubbles in Markets for Homes

7/28/2019 How to Spot Bubbles in Markets for Homes

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The Long-Run Equilibrium Lens for Spotting Real Estate Bubbles

The equilibrium theory posits that markets tend toward equilibrium and that any

apparent fluctuations are merely random noise. It contends that prices in a market

reflect the underlying supply and demand fundamentals, which are in turn not affected

by the price. However, the theory struggles to explain business cycles; it is clear that

time and again some markets experience reflexive dynamics - phenomena where the

price not only reflects supply and demand, but also affects the demand in a self-

reinforcing pattern, where increases in prices lead to increase in demand, which further

increases prices and so on. George Soros, an investor and business magnate, in his

book The New Paradigm for Financial Markets, argues that different principles apply in

markets depending on whether they are in a near to equilibrium or a far from

equilibrium state, the latter being characterized by reflexive dynamics. Is it possible to

detect such a departure from equilibrium in its early stages? Can an equilibrium be

observed in the first place? This paper aims to address this challenge for real estate

markets with a focus on the United States and India. I will explore first whether there is

in fact an equilibrium that can be discerned, and if this is the case then can reflexive

episodes be identified. The ultimate objective is to develop a framework for spotting

bubbles in real estate markets before they burst by looking at them as departures from

an underlying equilibrium.

Is there an equilibrium in real estate markets?

If reflexivity is a characteristic of the market departing from its equilibrium state, we

must first establish what this equilibrium is. Equilibrium is a fundamental concept in

Financial Booms and Busts! Parmeet Shah

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economic theory, but can it be observed empirically in real estate markets? Karl Case

and Robert Shiller have devised the Case-Shiller index, which seems to be the longest

series of home prices for any country1. The following chart depicts Shillers data, which

is corrected for inflation, through 2012 (1890=100).

Analyzing the chart leads to some very interesting insights. Home prices in the US

have not significantly increased in real terms for the last 120 years. Also, real home

prices seem to have a strong tendency to return to their 1890 level.

Shiller released the second edition of Irrational Exuberance in 2005, at which

point the data depicts, in his words, a rocket taking off2. Shiller does express concern

over the long-run stability of home prices but refrains from explicitly stating that this

may be a bubble, after all the period after World War II had seen a substantial rise in

50

100

150

200

1890 1903 1916 1929 1942 1955 1968 1981 1994 2007 2020

Real Prices


2

1 Shiller, Robert J. Irrational exuberance. Crown Business, 2006: pp 13



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real prices without any subsequent drop. However, Standard and Poors continue to

collect data for the Case-Shiller index to this day. The chart depicted above reflects data

through till the second quarter of 2012. The picture is much more clear at this point - the

period since 1998 has seen the largest rise in real prices in the observable history of the

US Housing market, but the crash since 2007 has been as dramatic and ultimately

brought the real prices back to their 1998 level. The chart adds tremendous support to

Shillers hypothesis that real prices in the US Housing market are essentially trendless

in the long run and tend to toward their 1890 level.

Is such an observation limited to the US housing market? Perhaps some of key

aspects that are unique to the US context allow for such a long-run tendency - for

instance very good road and air connectivity across the nation, proactive regulatory

environment, free market fundamentals, size of the country, etc. This does not appear to

be the case however, because a similar pattern is seen in the housing prices of some

other countries as well. The real prices of homes in Norway, Netherlands and the US

are presented in the following chart3 (1890=100):


3

3 Shiller, Robert J. Understanding recent trends in house prices and home ownership. No. w13553. National Bureau

of Economic Research, 2007: pp 44


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0

50

100

150

200

250

300

350

400

1890 1910 1930 1950 1970 1990 2010

Year

RealHomePriceIndex,

1890=100

Netherlands

USA

Norway

Before 1990, the home prices in all three countries do not show any uptrend or

downtrend over a 100 year period. What happened after 1990 is clearly a reflexive

dynamic as discussed earlier. The paper was written in 2007 and does not show the

complete picture, and unfortunately data collection for the Norway and Netherlands

indices ceased in 2003 and 2004 respectively. The pattern for the most part has been

common for the three nations, and evidence supports the assumption that home prices

in Norway and Netherlands, along with those of many other nations in the world, went

through a similar trajectory as those of the US over the last decade 4. It may be safe to

conclude that an equilibrium does exist in housing markets around the world such that

the real price does not change substantially over the long run.


4

4 Cohen, Jeffrey P., Cletus C. Coughlin, and David A. Lopez. "The boom and bust of US housing prices from various

geographic perspectives." Federal Reserve Bank of St. Louis Review 94.5 (2012): 341-67.


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Why might this be? How do the market dynamics allow for the real prices to

behave in such a manner? Lets consider some fundamental factors that determine the

supply-demand dynamics in real estate markets.

Supply and Demand Fundamentals in Real Estate

Existence of a long run equilibrium implies that there are demand side and supply

side pressures on the real price such that an equilibrium is maintained at the macro

level, except when reflexive dynamics enter the picture. What are these pressures and

how do they manifests themselves in the market? Shiller alludes to a number of factors

that make the real estate market efficient, but many of his assumptions are

questionable.

Mobility: Shiller argues that people and business will, if home prices are high

enough, move far away, even leaving an area completely5. Land may be scarce locally,

but urban land area is only 2.6% of the total land area in the United States6. Because

there is abundant space at the macro level, if prices increase substantially people will

find cheaper locations to live. This argument, however, may be expecting too high a

degree of rationality and awareness when it comes to the home buyers. Consumption of

homes is different from consumption of other goods given that there is a lot of prestige

and emotional value that people attach to their homes and localities. The location of

your home determines to a large extent the kind of social circles you will engage with,

the neighborhood your children will grow in and the school they will attend. These


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aspects are intangible, but consumers must factor them in when it comes to their

willingness to pay. Thus, home buyers may be willing to pay much more than what

would seem rational and such anecdotes are not uncommon. Shiller contends that the

prestige one derives from simply living in a glamorous city is not very significant7 but

without evidence to support such an argument, it can be qualified only as an opinion

that is quite contentious. Intangibles are a big part of the equation when it comes to

home buying, and as incomes increase across the world, people may be willing to pay

an increasing amount for these intangibles and that might drive the price higher. Given

the intangibles that come along with buying a home, and also the fact that the common

man buys a home only a few times in his lifetime, the real estate markets may not be as

efficient as Shiller supposes.

Easing land restrictions: Increasing prices put pressure on the government to

ease restrictions on land in terms of how much can be built in a particular amount of

land and also the amount of land available for development. There is a lot of evidence

to this effect and it has even happened recently in New York8 and Mumbai9. However, it

is not that governments in democratic countries like US and India are directly

responsible when it comes to maintaining prices and keeping homes affordable.

Moreover, changes in regulations are not quick reactions to markets - they usually take

a lot of time and the actual development of real estate as a reaction to regulatory


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8http://therealdeal.com/blog/tag/floor-area-ratio/

9http://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-

regional
http://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-regionalhttp://therealdeal.com/blog/tag/floor-area-ratio/http://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-regionalhttp://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-regionalhttp://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-regionalhttp://articles.timesofindia.indiatimes.com/2012-07-02/mumbai/32508038_1_fsi-town-planning-act-maharashtra-regionalhttp://therealdeal.com/blog/tag/floor-area-ratio/http://therealdeal.com/blog/tag/floor-area-ratio/


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changes would take even more time. Some have argued that such delays in reaction

given the nature of the real estate industry may contribute to boom-bust dynamics 1011.

Technology Improvements: Construction technology, as is the case with any

technology, has improved considerably making home building cheaper and faster. This

puts downward pressure on home prices12. However, in the glamour cities that are

most susceptible to bubbles, the land prices comprise an overwhelming proportion of

the cost so the downward pressure of construction technology may be negligible.

The fundamental forces that would result in an efficient real estate market are

questionable. On the other hand, when real prices are aggregated across cities,

suburbs and states of the United States and evaluated over a very long term the

skewness that any inefficiencies may cause would diminish in significance. After all,

affordability is an overwhelming factor when it comes to the majority of the home-buying

decisions - prestige-buying may be limited to glamour cities and further to the very top

socio-economic strata. Land regulations may not ease the upward pressure on prices

quick enough in urban areas, but clearly, land is not a scarce resource at the national

level.

An understanding of the fundamentals of the market is critical to the discussion of

an equilibrium. However, any amount of post-hoc debate or justification does not

undermine the empirical fact that housing prices do seem to tend to a long-run

equilibrium. The argument remains that if at some point in the future real estate prices


7

10 Mankiw, N. Gregory, and David N. Weil. "The baby boom, the baby bust, and the housing market." Regional

Science and Urban Economics 19.2 (1989): 253-254.

11 Malpezzi, Stephen, and Susan M. Wachter. "The role of speculation in real estate cycles." Journal of Real Estate

Literature 13.2 (2005): 141-164.

12 Shiller, Robert J. Irrational exuberance. Crown Business, 2006: 22


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fail to exhibit the kind of pattern they have shown in the last 120 years, it will be

because of the inherent inefficiencies and intangibles that come with home buying. For

now it is safe to assume that any significant and consistent uptrend from this long run

equilibrium indicates a reflexive dynamic. Based on such a hypothesis, we could create

a framework to detect bubbles in their early stages. But where does one draw the line to

distinguish random fluctuations from reflexive bubbles? How can we actually deliver a

verdict? We will now analyze the graph that was initially presented and look at historical

cases to develop a framework for thinking about bubbles in the real estate market.

Historical Trends and Bubbles

If the long-run equilibrium is a reliable indicator of reflexive dynamics, that must

hold historically as well. While home prices fluctuated around the long term equilibrium

level between 1890 and 1912, the period from 1912 to 1946 saw the greatest drop in

real prices as seen below.

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150

200

1890 1903 1916 1929 1942 1955 1968 1981 1994 2007 2020


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During this period the real prices reached all time lows: a 34% drop from the 1890

level in 1921 and a 32% drop in 1942. The start of the decline roughly corresponds with

the start of World War I, which was followed by the Great Influenza Pandemic of 1918,

the Great Depression (1930) and finally World War II. By no measure can this era be

considered normal times - each of the events alluded to had tremendous socio-

economic impact for which there is no parallel. In any case, real prices were

consistently below par during this period. Could this have been anticipated? Probably

not. Can something similar happen in the future? The black swan theory implores us to

not discount such a possibility. However, they did end up more or less exactly at the

1890 level by 1948-49.

The period from 1953-1977 presents another mystery as prices remained higher

than the 1890 level though they gradually declined over the 25 year period. Shiller offers

a number of reasons why this was an optimistic time in American history: end of World

War II, beginning of the Baby Boom and the GI Bill or Rights (1944) that subsidized

home purchases13. He also claims that the scars of the Great Depression deflected any

speculative tendencies. Remarkably, at the end of this period the prices were again very

close to their 1890 level.

An interesting realization that comes from the analysis is that real estate booms

and busts at the national scale are a relatively modern phenomena as they do not seem

to have occurred before 197514. Might it be that the advent of communication


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14 Shiller, Robert J. Understanding recent trends in house prices and home ownership. No. w13553. National Bureau

of Economic Research, 2007: pp 23


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technology is what made the prices across the country highly interdependent?

Communication technology may indeed have a role to play - Shiller claims that reflexive

excitement can cross vast oceans15.

Reflexive dynamics of the boom-bust type seem to have started from the late 70s.

Three such episodes are clearly evident:

This is where the study of real estate booms and busts in the US really begins.

The approach from here on will be to examine the similarities between these bubbles.

The most contentious element of the analysis is to declare the start and end of a

bubble. With a bit of tinkering, I could find that if we arbitrarily make the following

assumptions in defining the start and end of the 3 bubbles, we get some interesting

properties:

An 8% consistent rise in real pricesover 2 years marks thestartof a bubble. A

consistent and significant rise in prices without any downward pressure implies a

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125

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175

200

1970 1974 1978 1983 1987 1991 1995 1999 2004 2008 2012


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reflexive dynamic in principle.Drawing the line in terms of hard numbers will inherently

be arbitrary in nature, but such a definition would predict all of the 3 bubbles in

discussion.

When prices decline to reach within 2% of the price at the start of the bubble, the

bubble hasended. Such an interpretation aims to delineate reflexive dynamics from

the equilibrium.

The average price in a period between two bubbles is where the equilibrium lies for

that period.

In the graph, the shaded regions depict bubbles, and the gaps between them

reflect the equilibrium. The following table summarizes some of the key characteristics

of the 3 bubbles:

Bubble Start Peak End Length (yrs)

1 1976.125 1979.125 1982.625 6.5

2 1985.125 1989.625 1994.125 9

3 1997.125 2006.125 ? ?

Bubble Peak Timi g Preceding Equilibrium

1 0.46 104.4

2 0.5 105.2

3 ? 108.3

The key conclusions one can make from this analysis are - first, the bubbles are

more or less symmetric. Second, the preceding equilibrium, which is the average price

within the gaps in the figure, has increased very slightly over the last 40 years. If one


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were to extrapolate both these characteristics and apply it to the current period, he

would conclude that the bubble has ended or is about to end:

Applying the peak timing of 0.46-0.5, the end of the bubble lies between 2011 and late

2014.

Assuming the equilibrium prices will increase at their historical rates, the equilibrium

price at the end of the bubble will be around 113. The Case-Shiller index prices

declined to 113.9 in the first quarter of 2012, but are back up to 120.

What does this say about the prices in the future? The direction, of course, is

impossible to predict. But what we can say is that the equilibrium seems to be around

the 110-115 price points. If it goes much lower than this, it is likely to bounce back

quickly and if it goes much higher than this, then we are seeing the first signs of another

reflexive dynamic.

Such an approach to evaluating and extrapolating from historical patterns is

inherently arbitrary and contentious. First, we have only 3 substantial cases within

merely one country. Will this be applicable to countries around the world and various

different indices? Moreover, will this be applicable to bubbles in the future? In defense

of the approach, home price data is surprisingly scarce and the Case-Shiller index

seems to be the most complete, holistic and updated index that is available. The

understanding and perspective that can be gained from it is unparalleled, without which

a long-run hypothesis would hardly be possible. As evident in a previous chart,

occurrence of bubbles across the globe seems to be a coordinated phenomenon. The

specific numbers and metrics developed in this section will need to be re-calibrated if

applied to a different country or index. The approach may still be highly relevant. And


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perhaps the approach is more of a lens or a way of looking for bubbles rather than a

strict indicator.

Inferences from the Analysis of Historical Bubbles

One interesting realization is that bubbles in the US Housing market are not a

short term phenomena and are even increasing in length. The bubbles we analyzed

lasted 6, 9 and (arguably) 13 years respectively.

A very intriguing characteristic of each of the three bubbles is that they are more or

less symmetric. Again the key reason for this may boil down to the nature of real estate

development. A relevant visualization of how this may occur is Mansharamanis

epidemic lens that utilizes a concept called infection rate when it comes to

understanding reflexive dynamics. Applying it to the real estate context, one can

imagine that the ascent of the bubble is when more and more buyers get infected by the

speculative atmosphere. The peak is when the market runs out of greater fools

implying a very high infection rate. The intriguing part is why the rate declines at a

similar and steady rate rather than dropping drastically. One possible explanation is on

the supply side - the most cash strapped and leveraged developers are forced to drop

rates to support their cash flow. This causes the prices to drop, which puts even more

developers in the same situation and the cycle continues till developers in the strongest

position also cannot sustain high prices. However, this theory requires consumer

demand to be consistently high - for if consumers decided to play the waiting game in

anticipation of prices to keep falling, then the crash would be much more swift as


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demand would suddenly evaporate and developers across the industry would face a

severe cash crunch due to a lack of transactions.

Yet another interesting realization is that real prices have shown a number of

uptrends but have not shown any downtrend that takes them significantly below the

equilibrium level, at least for the last 60 years. One can imagine that all the ambitious

forecasts of the peaks would result in significant ghost towns and vacant real estate,

creating a temporary over-supply situation that would crash the price below the long-run

equilibrium. High demand pressures may, again, be the key explanation to this

observed phenomena. Given rising incomes and rising aspirations regarding standards

of living, consumers are not willing to wait too long and are even willing to pay a

premium in order to move now. Perhaps the intangibles like more prestigious

communities and better schools that were discussed previously matter enough to keep

the demand consistently high. Waiting a few years for the prices to decline when your

childs schooling and career is being affected may not be rational after all.

For the majority of the last forty years, the US Housing market has been in a

boom-bust dynamic. The ability to spot reflexive dynamics in the market could not be

more relevant than it is in the modern era.

The Indian Context

The National Housing Bank, which is an institution owned by the Reserve Bank of

India has created an index of nominal home prices starting from 2000 called Residex. I

have compiled all the available data - for Mumbai, Kolkata, Bengaluru and Delhi up until


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2006 and the top 15 Indian cities from 2006 through to 2012 and corrected it for inflation

using the CPI16, borrowing from the methodology of the Case-Shiller index. When the

data from India is incorporated into Shillers graph (2001 = 130), this is the picture we

get:

0

75

150

225

300

2000 2001 2003 2004 2006 2007 2008 2010 2011 2013

The rise in real prices of homes in India since 2001 has been phenomenal and

towers the rise in prices in the US. This is not unprecedented - in a previous chart we

saw that real prices of homes in Norway and Netherlands also rose much more in

proportion to US prices. This may be due to the nature of the market, or even the way in

which the index is created.

The graph seems to reflect the reality - anecdotal evidence suggests that prices of

homes in Mumbai have risen 5-6 times in nominal terms since 200317

and CPI has only


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16 Appendix I

17 Appendix - II


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doubled over the same period18. Also real prices had more than doubled over the period

of 1990-200019 at least in Mumbai.

At the fundamental level, the economy in India is comparable to that of the US.

The growth rates in India have been much higher than those of the US for the last 20

years, but then so has inflation, which has been corrected for. The real estate market in

India is highly competitive and open, so one cant imagine any mechanism that would

distort the price. There are vast expanses of unused and unoccupied land, even close

to the big metros like Mumbai, Delhi, Kolkata, etc. So shouldnt rapidly increasing prices

be offset by a decrease in demand and an increase in supply? Well, not if reflexive

dynamics are at play.

If we have another look at the graph, the Indian market did go through a downward

blip when the US market tanked, but it soon recovered and since 2010 the prices have

soared above the peak of 2007. Again, anecdotal evidence suggests that this does

reflect the reality on ground20, and isnt a mere skew in the data. Might it be that the

Indian market entered yet another boom before it could complete its decline?

There are three possible explanations for why the Indian data does not look similar

to the US data. The first is that real prices of homes in India do not tend to a long term

equilibrium. One could argue that per capita income has risen almost three times in

India when it has risen only 22% in the US in real terms over the last two decades. But

over a 120 year period, the income per capita in the US rose eight times in real terms,

without any corresponding increase in real prices of home. Real home prices in the US


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18 Appendix - I

19 Appendix III - Ready Reckoner Data

20 Appendix - II


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have been resilient to many structural and technological changes and have had a strong

tendency to the long-run equilibrium. There is no significant reason why the same would

not be true of Indian home prices.

The second explanation is that there is something wrong with the data. This is

indeed plausible and in his paper Malcolm Athaide highlights a number of concerns

regarding the quality of Residex - the most critical ones being some of the historical

data is based on recall rather than actual transactions and that black money is involved

in many transactions21. However, none of the factors seem to indicate a consistent

inflation of the prices and given that it is the only home price index available for India

and is devised by premier institutions in India who set up a technical advisory group

for the development of the index22, Residex is the most reliable and best available data.

Moreover, the data seems to reflect anecdotal evidence and is in accordance with the

intuition of developers on the ground in Mumbai23.

The third explanation is in line with the hypothesis - the increase in real prices of

homes implies a reflexive dynamic is in effect. The price rise post 2010 depicts that yet

another bubble is developing or that the decline in prices has not corresponded to that

in the US and will come soon. If we were to extrapolate from the patterns seen in the

US we could say that when the price decline occurs, it will happen in a gradual manner

symmetrical to the pattern in which the price had risen. Also, the price will come back to

the preceding equilibrium level as defined earlier, which seems to be at most half of the

current level in real terms.


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21 Athaide, Malcolm (2008), The Robustness of Residex as a House Price Index, XLRI Jamshedhpur: 23-29

22 Athaide, Malcolm (2008), The Robustness of Residex as a House Price Index, XLRI Jamshedhpur: 31, 20

23 Appendix - II


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Concluding Thoughts

The approach developed in this paper can prove to be a reliable lens for spotting

bubbles in their early stages in real estate markets around the world. Such an

understanding could have a profound effect not only on how real estate professionals

and firms view price movements in the market but also on how the banking and financial

sector looks at real estate loans and collaterals. One hopes that such a macro level

perspective abates many of the misconceptions people across the globe seem to have

when it comes to real estate, and hopefully even prevent large scale bubbles from

occurring.


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Appendix - IResidex Data & CPI

Hyderabad

Faridabad

Patna

Ahme dabad

Chennai

Jaipur

Lucknow

Pune

Surat

Kochi

Bhopal

Kolkata

Mumbai

Bengaluru

Delhi

Average

CPI

200 200 2003 2004 2005 2006 2007 2008 2009 2009 2010 2010 2010 2011 2011 2011 2011 2012 2012 2012 2012 2013

100 96 92 65 81 81 82 87 87 83 9184 79 86 85 84

100 100 121 139 145 154 152 170 176 165 220206 218 217 217 216

100 103 100 107 119 127 124 148 146 146 146141 140 129 140 138

100 106 100 127 128 113 131 141 164 165 169163 167 164 174 180

100 104 95 120 143 164 183 210 214 218 248271 296 304 309 312

100 119 115 71 63 66 61 63 69 67 6465 64 80 78 85

100 103 102 104 119 112 133 148 152 157 160154 165 164 171 175

100 101 97 103 117 124 135 140 141 148 150169 184 181 200 201

100 101 98 111 123 109 136 128 133 128 149139 152 144 145 138

100 106 95 90 83 79 83 97 101 86 10797 82 72 73 80

100 139 151 139 162 158 153 166 173 167 224208 211 204 207 206

42 4 9 55.7 63.7 75.1 75.9 100 114 140 162 185 165 176 191 213 211 194191 190 191 196 191

37 4 3 49.3 55.6 66.4 83.6 100 112 117 124 126 134 160 167 173 175 181194 193 190 197 198

32 42 54.3 71.6 87.9 86.9 100 73 76 58 59 64 68 74 101 88 9293 100 92 100 98

34 3 6 43.3 50.3 67.4 90.3 100 124 130 121 113 106 110 115 123 126 147154 167 168 172 178

36 4 2 50.6 60.3 74.2 84.2 100 107 109 109 118 117 126 136 144 142 156 155 161 159 164 165

100 104 108 112 117 123 131 137 146 150 165 171 172 178 183 186 187195 198 199 206 214

Average Real Prices in India (corrected for inflation)Average

For US

100 112 129 148 175 189 211 215 205 202 197 189 202 211 218 211 230 220 224 220 220 213

130 146 168 193 227 245 273 279 266 262 256 246 262 274 283 274 299 286 290 286 285 277

Residex data was collected from NHBs official website: http://www.nhb.org.in/Press%20Release/

Quarterly_Update_April_June_2011.php

The information before 2007 is available on the websites but is hard to

navigate to, one can simply type .xls in the search function of the

website to retrieve city-wise file with the data.

All Residex data was rescaled to 2007 = 100; then to 2001 = 11 when

deflated by CPI (Average) and then 2001 = 130 (For US) for the chart

that compares US and India home prices.

CPI Data was collected from the Labour Bureau (http://labourbureau.nic.in/indtab.html) and rescaled to 2007 = 100.


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http://labourbureau.nic.in/indtab.htmlhttp://labourbureau.nic.in/indtab.htmlhttp://labourbureau.nic.in/indtab.htmlhttp://labourbureau.nic.in/indtab.htmlhttp://www.nhb.org.in/Residex/Data&Graphs.phphttp://www.nhb.org.in/Residex/Data&Graphs.phphttp://www.nhb.org.in/Residex/Data&Graphs.phphttp://www.nhb.org.in/Residex/Data&Graphs.php


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Appendix - IIAnecdotal evidence from the Mumbai Market

This annexure depicts the anecdotal evidence that has been used in this paper

under The Indian Context. They reflect the information I have collected through

conference calls with my father, uncle (MD and Vice-Chairman of Marathon Group,

respectively) and a few other developers from Mumbai. They also include some of my

first hand experiences when I was working at Marathon Group from 2009-2012. The

following is a list of projects in different parts of Mumbai, rates are approximate and in

Rs. / square foot.

Project Name Location 2003 2007 2009 2012

Marathon Era Lower Parel 6000 30000 22000 33000

Monte Vista Mulund - 9000 6000 13000


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Appendix - IIIData from Ready Reckoner, a government body under the Revenue ministry. The prices are innominal terms and are available for specific localities in Mumbai from 1990-2000. Presenting asample page from the publication:


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How to Spot Bubbles in Markets for Homes

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