SEVENTY-NINTH INTERNATIONAL
ATLANTIC ECONOMIC CONFERENCE
INVITED ADDRESS
LUIGI ZINGALES
CHICAGO BOOTH SCHOOL OF BUSINESS
“Diagnosing the Italian Disease”
MILAN 11-14 MARCH 2015
Diagnosing the Italian Disease
December 2014
Bruno Pellegrino
Luigi Zingales
University of California
University of Chicago
GDP per Hour Worked (2005 PPP$)
52.5
50
47.5
2005 $ per hour
45
42.5
40
37.5
35
32.5
30
27.5
EU
Italy
US
25
1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
Motivation
• Twenty years ago Italy’s labor productivity
stopped growing.
• Understanding why is important for several
reasons:
1. Italy is the sick country of Europe. Difficult for
the euro to survive without Italy improving
2. The Italian disease is a more acute form of a
European disease-> understand better link
between institutions and growth
Sector Level Data
EU-KLEMS structural database,
– value added, output, inputs, total factor productivity,
and input compensation shares
•
•
•
•
•
at the 3-digit ISIC level for 25 European countries,
Australia, South Korea, Japan, and the United
States for the period 1970-2012.
We stop at 2007 to cut out the crisis
Lose 11 countries for lack of capital formation
series
3 for inconsistent data
Down to 15 countries
Growth in GDP / Capita (1994–2006)
80%
70%
60%
Hour Worked/Employee
Employment/Population
GDP/Hour
50%
40%
30%
20%
10%
0%
-10%
-20%
GDP p.Capita
Sectors
• We aggregate sectors 50 to 52 (wholesale and
retail trade) to merge some explanatory variables
in the dataset that are available at industry-level.
• We use the aggregate sector 70t74 instead of 70
(real estate) and 71t74 (other business services)
for problems in the attribution of real estate assets
• We drop, as customary, public sector and social
services (sectors 75-99)
• Left with 23 sectors
Total Factor Productivity
Sector Name
Value Added/Hour
Code
Italy
Average
Italy
Average
Agriculture, Hunting, Forestry And Fishing
01t05
1.0%
1.8%
2.3%
3.2%
Mining And Quarrying
10t14
-2.6%
-1.4%
0.1%
-0.2%
Food Products, Beverages And Tobacco
15t16
-0.4%
-0.7%
0.7%
0.6%
Textiles, Leather And Footwear
17t19
-0.8%
0.7%
0.5%
2.3%
20
1.8%
0.6%
2.5%
1.6%
21t22
-0.8%
0.0%
0.9%
1.7%
Coke, petroleum products and nuclear fuel
23
-12.8%
-0.3%
-11.0%
2.5%
Chemicals
24
0.3%
1.8%
0.8%
4.2%
Rubber and Plastic Products
25
0.1%
1.3%
1.0%
2.7%
Other Non-Metallic Mineral Products
26
0.1%
1.0%
1.7%
2.8%
27t28
0.1%
0.8%
0.6%
1.7%
29
-0.9%
1.7%
-0.4%
3.4%
Electrical And Optical Equipment
30t33
-0.8%
8.8%
0.4%
11.2%
Transport Equipment
34t35
0.1%
2.2%
0.5%
3.6%
Manufacturing N.E.C. And Recycling
36t37
0.0%
1.1%
0.7%
2.5%
Electricity Gas And, Water Supply
40t41
0.2%
1.1%
2.7%
3.8%
45
-1.3%
-1.3%
-0.5%
-0.6%
50t52
-1.0%
1.8%
0.7%
3.1%
Hotels And Restaurants
55
-1.5%
-0.2%
-0.8%
0.4%
Transport And Storage
60t63
-0.6%
0.5%
0.1%
1.5%
64
5.9%
3.1%
8.9%
6.3%
Financial Intermediation
65t67
1.4%
1.0%
2.3%
3.0%
Other Business Service Activities
70t74
-0.6%
-0.6%
-3.1%
0.1%
Wood And Products Of Wood And Cork
Paper, Printing And Publishing
Basic Metals And Fabricated Metal Products
Machinery And Equipment, N.E.C.
Construction
Wholesale and Retail Trade
Post And Telecommunications
Firm Level Data
• EFIGE (European Firms in a Global
Environment), developed by Altomonte and
Aquilante (2012) for the think-tank Bruegel.
• It contains balance sheet data for over 14,000
firms from 6 European countries (Austria,
France, Germany, Hungary, Italy, Spain, UK).
• EFIGE has a short time span and does not allow
us to study the dynamics of productivity growth.
• Yet, it allows us to observe key features of the
businesses’ organizational model more directly.
Italy’s productivity growth gap
Explanations Based on Traditional
Italian Characteristics
1. “Bad” firm demographic
– “Wrong” sectors and too small a size
2. Lack of labor flexibility
3. Government inefficiency
4. Quality of human capital
Size and Sectors
Actual
Predicted
(Sector)
Predicted
(Size)
Predicted
(Sector & Size)
Australia
30.0%
18.0%
21.8%
22.6%
Austria
22.8%
20.7%
20.0%
23.1%
Belgium
13.8%
18.3%
20.3%
21.0%
Denmark
11.4%
20.6%
19.0%
21.6%
Finland
32.0%
23.4%
20.2%
25.1%
France
20.5%
18.9%
20.0%
19.5%
Germany
19.9%
20.3%
18.3%
21.5%
Ireland
36.2%
23.5%
19.5%
24.4%
Italy
1.8%
20.9%
27.0%
30.0%
Japan
24.8%
19.9%
23.0%
25.9%
Netherlands
22.8%
17.4%
18.8%
16.4%
Spain
2.1%
18.6%
24.4%
24.2%
Sweden
37.6%
21.0%
20.2%
23.9%
United Kingdom
28.0%
16.6%
18.2%
16.3%
United States
16.9%
18.0%
14.4%
11.7%
Country
Lack of Labor Flexibility
Need for Labor Flexibility
Table 5. TFP growth and Labor Market Regulation
Government Inefficiency
Impact of PA on a Sector
• For the period 2000-2007 we count all news
regarding a sector in Reuters, Thomson,
Bloomberg, FT, WSJ, and Dow Jones (Factiva
tag).
• We re-compute from the same sources the
news regarding the sector having government
as topic.
• We take the ratio of the two
Public Sector Dependence Scores (Factiva)
Agriculture, Hunting, Forestry And Fishing
Chemicals (inc. Pharma)
Electricity, Gas AndWater Supply
Construction
Automotive
Other Manufacturing & Recycling
Financial Intermediation
Electrical, Optical & Medical Equipment
Post And Telecommunications
Transport And Storage
Other Business Service Activities
Coke, petroleum products and nuclear fuel
Food Products, Beverages And Tobacco
Machinery And Equipment, N.E.C.
Mining And Quarrying
Paper, Printing And Publishing
Wholesale and Retail Trade
Hotels And Restaurants
Rubber and Plastic Products
Textiles, Leather And Footwear
Wood And Products Of Wood And Cork
Basic Metals And Fabricated Metal Products
0.0%
2.5%
5.0%
7.5%
10.0%
Table 6. TFP growth and public sector performance
TFP Growth and Human Capital
Growth
(1)
Δlog PIAAC
2.80***
(.870)
-5.67
(4.05)
Δlog PIAAC × Labor Compensation Share
Country-Clustered Standard Errors
(2)


Country-Fixed Effects


Observations
345
345
R-squared
.256
.365
Sector-Fixed Effects
*significant at 10% confidence, **significant at 5% confidence, ***significant at 1% confidence
Trade-Based Explanations
• In the short term, a decrease in external demand for Italian
products can adversely affect productivity through several
channels
1.
2.
3.
4.
Scale effect
Embedded technological progress
Impact on profitability
Labor adjustment costs
• In the long term, if there is a permanent drop in demand
for Italian products, firms will eventually adjust or close.
– If they adjust, they will be forced to increase productivity.
– If they close, the least productive firms will close first,
increasing the average productivity simply through a
compositional effect.
Table 8. Capital Accumulation, Firm Size
Growth and the Trade Balance
Table 9. Productivity growth, Employment
Protection, Firm Size and China
Table 10. Innovation and Foreign Competition
Figure 5. The ICT Revolution
Table 11. Productivity growth and
ICT capital growth
Ability to Exploit IT Revolution
• Bloom et al. (2012) productivity gap between
US and EU due to a combination of IT and
management.
• Bresnahan et al (2002): complementarities
between IT and workplace reorganization.
• Institutional factors (size, organization, low
labor flexibility, large black market economy)
may have prevented Italy from taking full
advantage of the ICT revolution.
Networked Readiness Index
• World Economic Forum measures “Networked
Readiness”:
• Networked Readiness Index =
1/4 Environment subindex
+ 1/4 Readiness subindex
+ 1/4 Usage subindex
+ 1/4 Impact subindex
Networked Readiness
ICT Contribution to Growth, by Sector
Table 12. Productivity growth, ICT capital
and Networked Readiness
Table 13. Productivity growth, ICT
capital, and Networked Readiness
What is Network Readiness?
• Quality of managers?
– Quality of management schools
– Number of GMAT takes /population
• Meritocratic selection:
i) perceived favoritism in officials’ decision
making.
ii) the degree of meritocracy in the selection of
private sector managers.
We average these two variables to form a proxy for
meritocracy
Meritocracy
Table 14. Productivity growth, ICT capital
accumulation and Management
ICT and productivity
• The impact of ICT on productivity is crucially
mediated by management
• As Garicano and Heaton (2010) show enjoying
the benefits of technology requires
1)
2)
3)
4)
Measurable goals
Internal accountability
Middle management empowerment
Rewards
=> performance-based, meritocratic management
Compstat
Introduced by the New York Police
Department in 1994 by Commissioner
William Bratton.
•the real time mapping of crime by
time and place
•(notorious) early morning meetings
Weisburd:
(1) statement of the measurable
goals of the department;
(2) internal accountability,
particulary through Compstat
meetings
(3) geographic organization of
command-- district commanders
have authority and resources to
accomplish their goals over their
areas;
(4) empowerment of middle
managers;
(5) data driven problem
identification and assessment;
(6) innovative problem solving
tactics.
Firm-Level IT usage
To quantify a firm’s level of IT usage, we count the
number of “yes” answers to the following questions:
– Does the firm have access to a broadband connection
(high-speed transmission of digital content)?
– Does the firm use IT systems/solutions for internal
information management (e.g. SAP / CMS)?
– Does the firm use IT systems/solutions for Ecommerce (e.g. SAP / CMS)?
– Does the firm use IT systems/solutions for
management of the sales/purchase network?
Firm-Level Performance Manag.
• Mimicking Bandiera et al (2008) we extract the
first principal component from the following six
dummy variables:
1.
2.
3.
4.
5.
6.
the firm’s CEO belongs to the controlling family (-)
the firm is family-managed
(-)
management is de-centralized
(+)
the firm uses bonuses to incentivize managers (+)
the firm has sought a third-party quality certif. (+)
at least one of the firm’s executives has worked more
than one year abroad
(+)
Table 15. IT usage and Management Models
Institutions and Incentives
Public Funds
Credit Information
Firm Size
Firm Size
Perf-Oriented Mgmt
Ordered Logit
Ordered Logit
Ordered Logit
Ordered Logit
OLS
(1)
(2)
(3)
(4)
(5)
Performance Oriented Management
.074***
(.018)
-.050***
(.017)
.799***
(.016)
.801***
(.039)
Performance-Oriented Mgmt. × Italy Dummy
-.121***
(.037)
.117***
(.031)
-.144***
(.031)
-.230 ***
(.115)
Bank Offers Efficient On-line Services
.117***
(.035)
Bank has Long-lasting Relationship with Firm
-.060**
(.030)
Country-Fixed Effects
P
P
P
P
P
Firm Age Fixed Effects
P
P
P
P
P
Firm Size Fixed Effects
P
P
P
P
P
Sector-Fixed Effects
P
P
Pavitt Classification Fixed Effects
P
P
P
P
Sample Restricted to Firms that do business
with Public Administration
Observations
(Pseudo) R-squared
P
P
P
10365
13451
13451
2118
8267
.095
.025
.106
.115
.305
Conclusions
• The Italian disease appears to be an extreme
form of a European disease:
– inability to take full advantage of the ICT
revolution
• This disease appears to be linked to the lack of
meritocracy and professional performancebased management.
• We still need to explain why these practices
are so rare in Italy and Southern Europe.
Conclusions - 2
• Suppose that there is some institutional factor
in Southern Europe that makes difficult to keep
up with technological change.
• Difficult to keep up with a fixed exchange rate.
• How could have Japan and the United States
kept a fixed exchange rate from 1950 to 1990?
• Organizational issues are crucial for the
survival of the euro.