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Topic 5 Empirical Research on Network Effects

Fall 2003 Gandal, N.,

"Hedonic Price Indices for Spreadsheets and an

Empirical Test for Network Externalities," Rand

Journal of Economics (25), 1994, 160-70. Gandal,

N., Kende, M., and R. Rob, The Dynamics of

Technological Adoption in Hardware/Software

Systems The Case of Compact Disc Players, Rand

Journal of Economics (31), 2000, 43-61.

Gandal, Rand Journal of Economics, 1994 Did

spreadsheet programs that were compatible with

Lotus command a premium? Idea is that

compatibility gives users of your product access

to other products network. Results not due to

switching costs because the spreadsheet market

was growing a lot b/w 1986 and 1991. Direct

effects because people want to share files and

indirect with compatible software e.g. database

programs.

- Paper uses product level data on spreadsheet

prices and characteristics between 1986 and 1991 - Estimate hedonic pricing equations of form
- ln(pit) Zit ? ?it
- Z are product attributes, one of which is a

compatibility dummy, others network variables

are dummies for linking capabilities between

spreadsheets (LINKING), (GRAPHS). There is a

variable that measures capacity of the

spreadsheet as well. - By 1991, nearly all high end spreadsheets were

compatible. That was not the case in 1986, when

many of the premium brands were not compatible

with Lotus format. - Article examines consumers valuation of

compatibility, yet formally doesnt address

firms decisions to become compatible. Would

need a structural model for this.

Data There is an unbalanced panel of 91

model-observations. In addition to the basic

editing functions common to all spreadsheets, the

DATAPRO report contains the following

characteristics and features. I briefly

summarize the available data. (1) The dummy

variable LOCOMP takes on the value one if the

program is compatible with the Lotus (WKS, WK1)

format. Otherwise the variable takes on the

value zero. If the program is compatible with

the Lotus format, it is capable of exchanging

files with Lotus and other spreadsheets that

support the Lotus format. (2) The dummy

variable RECALC takes on the value one (zero) if

the program can (can not) automatically

recalculate when new entries are made. (3)

The dummy variable SORTING takes on the value one

if the program can sort a group of data

observations on at least two levels.

(4) The variable GRAPHS is a dummy variable that

takes on the value one if the program is capable

of performing all of the following basic graphs

pie, bar, and line. If the program cannot

perform these basic functions, the variable

GRAPHS takes on the value zero. These basic

functions are bundled because the early DATAPRO

reports collected the data in this manner. (5)

The variable WINDOW takes on the value one if

the maximum number of windows on-screen

simultaneously is between two to fifteen and

takes on the value two if this maximum is sixteen

or more. If this feature is not available, the

variable WINDOW takes on the value zero. This

variable was defined in this manner because some

spreadsheets offer a maximum that is limited only

by hardware features. (6) The dummy variable

LINKING takes on the value one if values in

several worksheets can be updated at the same

time.

(7) The dummy variable EXTDAT takes on the value

one if the program provides links to external

data bases, and zero otherwise. This link can be

either proprietary or through SQL support. If

this feature is available, databases on

mainframes can be downloaded directly into the

spreadsheet. (8) Macros allow a user to

automate repetitive tasks. The dummy variable

PROGRAM takes on the value one if macros can be

written in this manner. (9) Macros can also be

written in learn mode. In learn mode, the

keystrokes that are to be replicated are typed

and the spreadsheet converts these keystrokes

into a Macro. The dummy variable LEARN takes on

the value one if the program enables the users

to automate repetitive tasks in this manner.

(10) The dummy variable LANCOM takes on the

value one if the program has the capability of

linking independent users through a LAN.

(11) The dummy variable PRINT takes on the value

one if three or more of the following five

advanced print functions are possible Sideways

printing, Background Printing, Preview Mode,

PostScript Support, and Printing of

non-contiguous worksheet portions. (12) The

variable PRESENT takes on the value one if

worksheets and graphs can be printed on the same

page OR if multiple printing fonts (and character

sizes) are available. If both features are

available, this variable takes on the value two,

while if neither feature is available, the

variable takes on the value zero. Although it

seemed natural to group the two presentation

features together, nothing in the analysis

changes if these features are entered as separate

variables. (13) The dummy variable LOTUS takes

on the value one if the program is produced by

Lotus Development Corporation and zero otherwise.

(14) The variable MINRC measures the power of

the spreadsheet and is defined to be the minimum

of the maximum number of rows and columns that

the spreadsheet can handle. (15) The variable

PRICE is the list price for a single copy of the

program. (16) The variable LPRICE is defined

to be the natural log of the price. (17) The

variable LMINRC is defined to be the natural log

of MINRC. Variables (1) through (6) are

considered to be basic spreadsheet features,

while variables (7) through (12) are more

advanced features. Some of these advanced

features (EXTDAT, PRESENT, and PRINT) were not

available until 1989.

In addition, to the above information, the year

in which the observation was taken and the date

of introduction are available. This allows the

construction of time, age and vintage dummy

variables, which are important for the analysis.

The time dummy variables are denoted TIME87,

TIME88, TIME89, TIME90, and TIME91. Similar to

the personal computer (hardware) market, most

products in this market were less than two years

old. In this sample, fully 54 percent of the

spreadsheets were new, 26 percent had been

available for one year, 9 percent were two years

old and 11 percent had been available for three

or more years. Lotus was the dominant firm

throughout the period. Other major spreadsheets

include Microsoft (first with Multiplan and then

with Excel), Computer Associates (various

versions of SuperCalc), Paperback Software

(VP-Planner), WordPerfect (PlanPerfect) and

Borland (Quattro and Quattro Pro) in the latter

part of the sample.

TABLE 2 REGRESSION RESULTS (DEPENDENT VARIABLE

IS LPRICE) Regression (1) Regression

(2) Regression (3) Regression (4) All

independent Variables Significant

Variables Preferred equation New Models

Only coeff. (t-stat) coeff.

(t-stat) coeff. (t-stat) coeff.

(t-stat) VARIABLES CONSTANT 3.73

(10.92) 3.76 (12.31) 3.12

(9.50) 2.61 (4.91) TIME87 -0.076

(-0.45) -0.062 (-0.38) -0.07

(-0.43) -0.57 (-1.73) TIME88 -0.42

(-2.37) -0.44 (-2.67) -0.45

(-3.03) -0.94 (-2.91) TIME89 -0.64

(-3.50) -0.70 (-4.20) 0.92 (1.71) 1.63

(1.65) TIME90 -0.74 (-4.13) -0.79

(-4.90) 0.90 (1.67) 1.47

(1.51) TIME91 -0.82 (-4.48) -0.85

(-5.30) 0.85 (1.59) 1.54

(1.56) LMINRC 0.11 (1.31) 0.11

(1.59) 0.26 (3.24) 0.41

(3.42) LOTUS 0.59 (3.46) 0.56

(4.36) 0.46 (3.62) 0.44

(1.97) GRAPHS 0.45 (2.94) 0.46

(3.51) 0.52 (4.18) 0.36

(2.03) WINDOW 0.17 (2.16) 0.17

(2.14) 0.14 (1.92) 0.18

(1.71) LOCOMP 0.76 (5.30) 0.72

(5.28) 0.66 (5.17) 0.70

(3.02) EXTDAT 0.52 (3.10) 0.55

(4.05) 0.57 (3.93) 0.67

(3.16) LANCOM 0.25 (1.62) 0.21

(1.65) LINKING 0.18 (1.51) 0.21

(1.91) 0.26 (2.00) 0.43

(2.22) LEARN 0.03 (0.18) PROGRAM 0.13

(0.70) PRESENT -0.08

(-0.54) PRINT 0.20 (0.86) SORTING -0

.21 (-1.27) TLANCOM 0.61

(3.28) 0.33 (1.20) TLMINRC -0.34

(-3.07) -0.52 (-2.76) TLINKING -0.31

(-1.49) -0.25 (-0.76) No.

Observations 91 91 91 49 S.E. of

Regression .391 .385 .356 .385

R2 . 862 .857 .881 .875 ADJ.

R2 . 827 .833 .857 .819

(No Transcript)

Price Indexes Table 3 shows the quality-adjusted

(hedonic) price indexes for regressions 2,3 and 4

from Table 2. The numbers in parentheses are

the percentage price declines from the previous

year. The average yearly decline in quality

adjusted prices was 15 percent for the full

sample and 22 percent for new products in the

sample. For the second regression, price indexes

are calculated by taking the exponentiated

estimated coefficients on the time dummy

variables, with the coefficient on T86 normalized

to zero. For regressions 3 and 4, the procedure

is slightly more complicated. See Berndt and

Griliches (1993) for details. Table 3. Price

Indexes for Spreadsheets (19861.00) Year 1986 1

987 1988 1989 1990 1991 Regression (2 1.00

.94 (6.0) .64 (31.7) .49 (22.6) .45 (8.6) .42

(5.5) Regression (3) 1.00 .93 (7.0) .64

(30.9) .50 (21.9) .48 (4.0) .46 (4.2) Regression

(4) 1.00 .57(43.0) .39 (31.6) .31 (20.5) .27

(12.9) .28 (-3.7) Percentage decline from

previous year in parentheses

Further Tests of the Significance of Lotus

Compatibility In the first subsample, 15 of the

40 model observations (38 percent) were not

compatible with the Lotus platform and some of

these "incompatible" spreadsheets were relatively

expensive. This is not the case with the second

subsample, in which 42 of the 51 model

observations (82 percent) were compatible with

the Lotus platform. Further, the spreadsheets

not compatible with the Lotus platform in the

second subsample ranged in price from 39.00 to

60.00, while the spreadsheets that were

compatible with the Lotus platform ranged in

price from 60.00 to 695.00. It is thus

encouraging that the variable TLOCOMP (which is

LOCOMP interacted with a dummy variable for the

second (1989-1991) sample period) is

insignificant in both regressions 3 and 4.

Adding the variable TLOCOMP to regression 3, one

obtains a coefficient (t-stat) of -0.12

(-0.53), while adding the same variable to

regression 4 yields a coefficient (t-stat) of

0.02 (0.055). Thus, the Lotus compatibility

parameter is essentially the same for both

subsamples. Despite the fact that some of the

incompatible spreadsheets were relatively

expensive in the (1986-1988) subsample, the

average price of a lotus compatible spreadsheet

in this subsample (365.00) is much higher than

the average price of an incompatible spreadsheet

(80.00). Thus this subsample was further

restricted to spreadsheets that cost less than

200.00. In this restricted sample of

non-premium spreadsheets, there were 24

observations, of which 9 were compatible with the

Lotus platform. The mean price of lotus

compatible spreadsheets in this subsample was

151.00 versus 80.00 for the 15 incompatible

spreadsheets. Gandal (1992) shows that although

the lotus compatibility effect declines slightly

in magnitude, it is still highly significant.

Thus, the effect of Lotus compatibility continues

to hold for non-premium spreadsheets.

- Comments
- Common critique of all hedonic price equations is

question of demand or supply effects (they are

very reduced form). Is this really a premium or

does it just cost more to make Lotus compatible

spreadsheets? - Finds 93 premium for Lotus compatibility. (e.66

-1) - At first glance, the premium seems quite large,

but once one thinks about the importance of

compatibility - Results are robust to all sectors of the market

(premium, generics, etc.) - Gandal (1995) extends the results to Database

Management Software and multiple standards. He

finds similar results, but the only important

standard is the Lotus (WK) standard.

Gandal, Kende, Rob (Rand Journal of Economics,

2000) The dynamics of technological adoption in

hardware/software systems the case of compact

disc players First Structural Model used in

Empirical Network Literature. See also Rysman

(2001). This paper examines the diffusion of a

hardware/software system. For such systems there

is interdependence between the hardware-adoption

decisions of consumers and the supply decisions

of software manufacturers. Paper considers the

CD-industry and estimates the (direct) elasticity

of adoption with respect to CD-player prices and

(the cross) elasticity with respect to the

variety of CD-titles. Results show that the

cross elasticity is significant. Model can be

used to quantify the effect of various policies

aimed at speeding up the diffusion of a system.

Methodology useful for public-policy analysis

regarding the benefits of backward compatibility

for other systems. (Example HDTV). Firm

strategy it is claimed that high-tech firms can

enhance their profits by subsidizing the adoption

of their technology. (Elasticities of hardware

sales with respect to hardware prices and with

respect to software availability.) Dynamic

model for estimating demand (technology

adoption) is applicable even when there is no

complementary software industry. Consumers

explicitly trade-off the lower prices which will

result from waiting one period with the loss of

one period's services from the durable product.

Step 1 Learn about the CD industry. (Helpful

for modeling purposes) Step 2 Informal reduced

form regressions -- get feel for data Step 3

Develop a structural model. Step 4 Econometric

Specification and Estimation of Structural

Model. Step 5 Discuss, Interpret, and Check

Robustness of the Results Step 6 Perform

counterfactuals

Step 1 Key institutional details (i) in the

case of CD-players, hardware prices are

essentially exogenous. Philips licensed the

technology to more than 30 firms. Hardware

market for compact disc players quite

competitive. (ii) There are cost instruments for

CD-variety. These cost instruments are the

fixed cost of installing capacity for pressing

compact discs. (iii) Record companies were

integrated into the production of compact discs.

The first CD (disc) pressing plant in the U.S was

opened by Sony/CBS Records (of Japan) in

1984. The second plant was opened by

Phillips/Polygram Records. CD production/recordin

g industry was an integrated software industry

2. Informal Regressions

Step 3 Structural Model Entry decision of

software firms If a software firm enters at time

t, lifetime profits are -Ft ??t1 ?2?t2

, where ?t1 are operating profits from sales of

software in period t1. If a software firm waits

and enters at time t, lifetime profits

(calculated at time t) are -?Ft1 ?2?t2

(Enters at time t1) Free entry equilibrium

condition requires that benefit of waiting (cost

savings) equal benefit from early entry Ft -?Ft1

??t1 ?Ytf(nt), where n of software

firms, Yinstalled base. (1) log f(nt) -log ?

- log Yt log (Ft -?Ft1)

Consumer Adoption Decision ? is an individual

characteristic measuring intensity of preference

for the system, 0 The total number of potential buyers is

MF(?) If consumer ? purchases in period t, net

benefit is -Pt ??CS(pt1 ) ?2CS(pt2 ) ,

where Phardware price, psoftware price,

CSConsumer Surplus. If consumer purchases in

period T1, net benefit (evaluated at t)

is -Pt1 ??2CS(pt2 ) ?3CS(pt3 ) . Pt

- ?Pt1 ?t?CS(pt1 ) ?t?g(nt). (Indifferent

consumer) (2) log(?t)log(Pt - ?Pt1) - log ? -

log g(nt).

_

_

4. Econometric Specification Estimation F(?)???

1 g(n)anr f(n)bn? Comment First assumption is

somewhat different from what is usually done.

People typically assume a bell-shaped

distribution over ?. However, the assumptions

give us tractable functional forms to estimate

and the insight of the model -- that one should

use cumulative variables -- is not dependent on

these functional forms. (1) log f(Nt) ?0 ?1

log Yt ?2 log (Ft -?Ft1) ?t , (2) log

(M-Yt) b0 b1 log (Pt -?Pt1) b2 log Nt nt

, where Nmn (m number of titles per firm) model

implies ?1 -?2 From the theoretical model, ?1

0, ?2 0, and b2

OLS Results with AR(1) terms are in Table

3 Instrumental Variables Estimation Table

4 Cost Shifters (for Nt ) log (Ft -?Ft1) , (Ft

-?Ft1)2 Cost Shifters (for Yt ) log (Pt

-?Pt1) , (Pt -?Pt1)2 Theoretical direction of

OLS bias Estimates of cross coefficients biased

away from zero estimates of own coefficients

biased towards zero. Results in Tables (3) and

(4) consistent with theoretical direction of OLS

bias.

5. Discussion/Interpretation of

Results Elasticity of hardware sales with respect

to variety of software - b2(M-Yt)/Yt Elasticity

of hardware demand with respect to a permanent

percentage price cut - b1(M-Yt)/Yt Ratio -

b2/b1 is independent of time. From table (4),

estimate of the ratio is 0.54. A 10 percent

increase in CD titles would have had as large an

effect on sales as a 5 percent price cut.

Robustness of the Results Potential Market

(Index) M300,000 (rather than 500,000). Both the

price and variety effects nearly double in

absolute value. But the estimate of the ratio (-

b2/b1) remains essentially unchanged at 0.52. We

also examined an alternative set of instruments.

In the alternative case, we just employed log (Ft

-?Ft1), as an instrument. In this case, the

consumer adoption equation is exactly identified.

The ratio (- b2/b1) remains essentially

unchanged at 0.56. We also estimated the consumer

adoption equation using first differences and

estimated the consumer adoption equation using an

alternative specification. See the paper for

discussion.

6. Counterfactual The Effect of

Compatibility Assume that it had been possible

to make CD-players compatible with LPs, and that

the IV parameter estimates of table (4) describe

the true diffusion process. Using simulations,

we examine how compatibility could have

accelerated the adoption process. We find that

if the amount of variety had grown by 100 percent

between the first and the second quarter of 1985

the diffusion process would have been shortened

by 1.5 years. While this counterfactual is

purely a thought experiment'' for

the CD-system, it is of great relevance for other

systems such as high-definition television (HDTV).

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