information technology and productivity in services: … · jorgenson, ho and stiroh(jep 2008) “a...

INFORMATION TECHNOLOGY AND PRODUCTIVITY IN SERVICES: SOME EMPIRICAL OBSERVATIONSEMPIRICAL OBSERVATIONS

Ali Hortaçsu – University of ChicagoChaehee Shin – University of ChicagoC ae ee S U e s ty o C cago

O iOverview• Briefly review macro evidence on contribution of IT to

productivity growth

• Survey of firm-level evidence on:h th IT i d ti it• whether IT increases productivity

• how IT contributes to productivity

M idMacro evidenced• Fact 1: IT investment appears to account for about 1/3rd of

labor productivity growth in the US

IT’s contribution to productivity growth

Jorgenson, Ho and Stiroh(JEP 2008) “A Retrospective Look at the U.S. Productivity Growth Resurgence”(Table 1)

3

Sources of U.S. Average Labor Productivity Growth 1959-2006

L b lit h

2

2.5Labor quality change

Total factor productivity: Non-IT-Producing Industries

1

1.5

Producing Industries

Captial deepening: Non-IT

Total factor productivity: IT-Producing

0

0.5

1 Total factor productivity: IT Producing Industries

Captial deepening: IT11 %

43%

59%38%

01959-1973 1973-1995 1995-2000 2000-2006

• IT includes computer hardware, software and communications equipment.IT includes computer hardware, software and communications equipment.• Although IT investment accounts for less than 5% of GDP, it takes up 1/3 of average

labor productivity growth since 2000.

US IT spending as % of GDP

M idMacro evidenced• Fact 1: IT investment appears to account for about 1/3rd of

labor productivity growth in the US

• Fact 2: IT is also associated with growth in inequality in productivity across firmsproductivity across firms

IT and dispersion of productivity

Brynjolfsson, McAfee and Zhu (2009) “Leaders and Laggards: IT and the Growth of Performance Differences Between Firms”

• High IT industries characterized by a small chance of a very high payoff.• Cross-sectional variance of gross profit margin of IT vs. non-IT intensive firms begins to

diverge from the mid-nineties.

IT and dispersion of productivity

Faggio, Salvanes and Van Reenen(2007) “The Evolution of Inequality in Productivity and Wages: Panel Data Evidence”

• Sample: 11,000 UK firms during 1984-2001• 10% rise in the relative share of ICT capital is related to 2.3-3.1% rise in dispersion of

labor productivity.

Micro mechanisms of productivity growth

• “Within” firm productivity growth:• Process innovation: make products/services cheaper

Product innovation: make products/services better• Product innovation: make products/services better

Micro mechanisms of productivity growth• “Across” firm productivity growth

• Absent frictions, demand will reallocate to firms making cheaper and/or better products/services raising productivity of the industryand/or better products/services, raising productivity of the industry

• In many industries, it is difficult for consumers to find the best/cheapest service provider

• IT reduces these “search” costs, and makes reallocation easier

Th ll i f f ITThe reallocative force of IT• Depending on the nature of demand, reallocation can lead

to:1 “Winner take all” markets1. Winner take all markets

• The most efficient service providers dominate the market, leading to more concentrated markets

2. “Long-tail” markets• Niche players are matched with consumers for their product,

leading to less concentrated marketsg

Caution: Establishing causality is difficult!

• Suppose we see that firms that adopt IT are also more productiveD thi th t IT hi h d ti it ?• Does this mean that IT causes higher productivity?

• What if higher productivity firms were just more likely to adopt IT?adopt IT?

• Ideal study would seek to find “natural experiments” regarding IT adoptionregarding IT adoption• Firm A is randomly selected to get IT subsidy vs. Firm B who does

not get the subsidy

• Since such natural experiments are rare, most studies I will review look at within firm changes in productivity, i.e.:• look at the difference in productivity before IT is adopted vs. after

IT and “within firm” productivityIT and within firm productivity improvements• 4 case studies of “within firm” productivity effects of IT

1. Retail2 Transportation2. Transportation3. Public services4. Healthcare

IT and Productivity Improvements Retail

First supermarket barcode scanner installed at a Marsh store in Troy, Ohio, in June 197(Basker 2011)( )

IT and “Within Firm” Productivity Improvements in Retail

Basker(2011) “Raising the Barcode Scanner: Technology and Productivity in the Retail Sector”

• Barcode scanner installation increased stores’ labor productivity by 4.5% during 1972-1982.

IT and “Within Firm” Productivity Improvements inIT and Within Firm Productivity Improvements in Retail

• Mortimer (ReStud, 2008) finds that introduction of barcode scanning systems in video rental stores allowed for the widespread adoption of “revenue sharing” contracts between movie distributors and rental stores

• This alleviated the double marginalization problem, and helped both consumer and producer surplus

• I.e. IT can increase productivity by helping solve contractual problemscontractual problems

IT and Productivity Improvements in Transportation

IT and “Within Firm” Productivity Improvements in Transportation

Hubbard(AER 2003) “Information, Decisions, and Productivity: On-Board Computers and Capacity Utilization in Trucking”

Trucks with EVMS have 10.4% higher loaded miles compared to those with trip drecorder.

IT and Productivity Improvements in Public Services

IT and “Within Firm” Productivity Improvements in Public Services

Garicano, Heaton(JLE 2010) “Information Technology, Organization, and Productivity in the Public Sector: Evidence from Police Departments”

• Sample: U.S. police department data during 1987–2003• Investment in IT relates to improved productivity when complemented with particular

organizational/ management practices, the Compstat program in particular.

IT and Productivity Improvements in Healthcare

• Large investments into Clinical decision support systems (CDS) and electronic medical records (EMR)

IT and Productivity Improvements in Healthcare

IT and “Within Firm” Productivity Improvements in Healthcare?

Agha(2010), “The Effects of Health Information Technology on Costs and Quality of Medical Care”

• Medicare claims data during 1998-2005during 1998-2005

• HIT(Health Information Technology) includes contracts of a CDS(clinical decision support)or an EMR(electronic medical records)medical records) system.

• HIT is not associated with improvements in either the efficiency or quality of hospital care for Medicare patients, through five years after adoption.

IT and “within firm” productivity improvements

• Significant productivity improvements in 3 out of 4 case studiesA l t IT i it i f l• A common element: IT improves monitoring of employees, enhancing “pay for performance” type incentive mechanismsmechanisms

IT and “across firm” productivityIT and across firm productivity improvements• We noted in the macro evidence that IT is also associated

with increases in productivity dispersion across firmsIT h th d fi t h ith h• IT changes the way consumers and firms match with each other

• This can lead to:• This can lead to:• More intense price competition• Reallocation of demand to most efficient producersReallocation of demand to most efficient producers• OR reallocation of demand to the best “match” for the consumer

IT b d ll iIT based reallocation• 4 case studies of the reallocative effects of IT

1. Life insurance2 Fisheries in India!2. Fisheries in India!3. Travel agencies and bookstores4. Apparelpp

IT and Price Competition in Life Insurance

Brown and Goolsbee (JPE 2002) "Does the Internet Make Markets More Competitive? Evidence from the Life Insurance Industry.“

3 5

4Change in Term Insurance Prices 1992-1997

State Calif., Wash., Va.

1992=2.5

3

3.5State Ala., La., Ky., Ark.Occupation High Skill

3

1992=21

1.5

2Occupation Low Skill

Age <302

1992=10

0.5

1

1992 1993 1994 1995 1996 1997

Age <30

Age >45

• During 1992-1997, term life prices fell by 32% in high-Internet-penetration states vs. 13% in low-penetration states, 33% among high-skilled workers vs. 23% among low-kill d 35% f d 30 14% f b 45

1992 1993 1994 1995 1996 1997

skilled, 35% for under age 30 vs. 14% for above age 45.

IT and the fishing industry in Kerala India (“The DigitalIT and the fishing industry in Kerala, India ( The Digital Provide,” Robert Jensen, QJE 2007)

Figure 1. Region of Study

Source: Reproduced from SIFFS (1999).

Large Changes in Fish MarketingLarge Changes in Fish Marketing1996 20011996

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IT and the market structure of serviceIT and the market structure of service industries• The previous 2 case studies showed that IT leads to

closing of price differentials/stiffer price competitionWh t d thi l d t i t f k t t t ?• What does this lead to in terms of market structure?

• I.e. who wins and who loses due to IT? If d diff i th i d ti it t th• If producers differ in their productivity, we may expect the more productive ones to benefit from IT, and the less productive ones to exitproductive ones to exit

• This leads to more concentrated markets with (sometimes) fewer producers and fewer workers(sometimes) fewer producers and fewer workers

IT and market structure of service industries

No. of travel agencies vs. e-commerce adoptionGoldmanis, Hortacsu, Syverson, Emre, (Economic Journal, 2010.)


Size distribution of travel agencies (Lieber and Syverson (2011))


Size distribution of bookstores (Lieber and Syverson (2011))


Size distribution of firms in the overall economy (Lieber and Syverson (2011))

• However, IT improvements in matching consumers with products need not always lead to more concentrated marketsmarkets

• “Long tail” hypothesis (Anderson 2004):• IT allows easier matching of idiosyncratic tastes• IT allows easier matching of idiosyncratic tastes• Thus small firms producing niche products may find it easier to sell

their products

Th “L T il”The “Long Tail”

• Unfortunately, we do not have firm level evidence for the long tail hypothesisTh i d t l l id• There is some product level evidence:• The concentration of sales of “hit” songs and movies has declined• Brynjolfsson Hu Simester (2011) find that better search tools lead• Brynjolfsson, Hu, Simester (2011) find that better search tools lead

to less concentrated sales among a given retailer’s products

R “L T il” M k ?Restaurants – a “Long Tail” Market?

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stopping at the bean bag every morning on my way to work. The bean bag coffee is NOT like that.They sell coffee that tastes like roasted fiery burning charred blackness the way coffee is supposed

1. Bean Bag Coffee HouseCategory: Coffee & TeaNeighborhood: Western Addition/NOPA

601 Divisadero StSan Francisco, CA 94117

« Mo' Map462 reviews

(415) 563-3634

Map, stay put! Redo search in map

They sell coffee that tastes like roasted, fiery, burning charred blackness, the way coffee is supposed

Would it be too much to ask for the baristas here to know a thing or two about coffee? I have hadthe same experience twice when trying to buy beans. It goes something like this. I pick up a bag

2. Mojo Bicycle CaféCategories: Coffee & Tea, BikesNeighborhood: Western Addition/NOPA


295 reviews

(415) 440-2338

Been coming here regularly for a couple of years. Not too much to say except the beers are fantastic.My fave is the 21st Amendment IPA which is their house beer. The drawback is that they

3. 21st Amendment BreweryCategories: Breweries, Pubs, American (Traditional)Neighborhood: SOMA

563 2nd StSan Francisco, CA 94107

1081 reviews

(415) 369-0900Map data ©2011 Google -

Salt House is the kind of restaurant you're only going to find in Manhattan, SF or maybe Chicago. The focus is on the cuisine where it should be. Even though the decor and staff are West Coast laid

4. Salt HouseCategory: American (New)Neighborhood: SOMA

545 Mission StSan Francisco, CA 94104

1085 reviews

(415) 543-8900

5. NOPACategory: American (New)Neighborhood: Western Addition/NOPA


2218 reviews

(415) 864-8643

C l di h hConcluding thoughts• Despite massive spending in IT, systematic “micro”

evidence on how IT impacts “within” firm productivity is still scarcestill scarce• Evidence is still being sought in important sectors like healthcare

• More evidence on reallocative effect of ITMore evidence on reallocative effect of IT• Most evidence points to IT stiffening competition• And leading to more concentrated market structures• The “long tail” hypothesis is very compelling, but its impact on

market structure and productivity has not been studied

IT and Korean Service Sector – some initial thoughts

80Internet Penetration Trend: Individuals, 2001-2010

657075

%

505560

2001.5 2002.5 2003.5 2004.5 2005.5 2006.5 2007.5 2008.5 2009.5 2010.5

Internet Penetration Trend: Businesses*, 2002-2009

85.090.0 95.0

70 075.0 80.0 85.0

%

*With over 5 employees. Source: IT Statistics of Korea

70.0 2002 2003 2004 2005 2006 2007 2008 2009


Productivity Trend of Korean Service Sector 2000-2010 (2005=100)

150

160

Overall

130

140Wholesale and retail trade

Accommodation and food

100

110

120 Accommodation and food service activitiesInformation and communications

80

90

100 Financial and insurance activitiesReal estate activities and renting and leasing

60

70

80 renting and leasingHuman health and social work activities

Source: Korean Statistical Information Service

602000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010


Size Distribution of Business in Korean Service Sector

0.960.98

1

0 90.920.94

Density

0 840.860.880.9

0.80.820.84

1 4 5 9 10 49 Ab 501~4 5~9 10~49 Above 50Number of Employees

1988 2009

Source: Korean Statistical Information Service


Number of Bookstores in Korea 1997-2009

5407

45954595

26462247 2103 2042

1825

1997 1999 2001 2003 2005 2007 2009Source: Korea Foundation of Bookstore AssociationSource: Korea Foundation of Bookstore Association

"Macro" evidence of IT on productivity growth

Jorgenson, Ho and Stiroh(JEP 2008) “A Retrospective Look at the U.S. Productivity Growth Resurgence”


Van Ark, O’Mahony and Timmer(JEP 2008) “The Productivity Gap between Europe and the United States: Trends and Causes”


Van Ark, O’Mahony and Timmer(JEP 2008) “The Productivity Gap between Europe and the United States: Trends and Causes” (Table 3)

3.5%

Sources of Average Labor Productivity Growth, EU vs. US 1980-2006

2.5

3

3.5

Non-ICT capital service per hour

1

1.5

2p p

Labor composition

Multifactor productivity

0

0.5

1

0- 5 5- 4 0- 5 5- 4

p y

ICT capital service per hour

• EU’s contribution of investment in ICT(information and communication technology),

1980

1995

1995

2004

1980

1995

1995

2004

EU U S

substitution towards high-skill workers, and multifactor productivity growth to labor productivity has lagged behind that of U.S. by 1.5% since 1995.

information technology and productivity in services: … · jorgenson, ho and stiroh(jep 2008) “a...

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