Kennedy School (Harvard 2008)

SOUTHERN ITALY
A DEVELOPING COUNTRY
A DEVELOPMENT STRATEGY
MASSIMILIANO SANTINI
ADVISOR: RICARDO HAUSMANN
SEMINAR LEADER: MATTHEW ANDREWS
Second Year Policy Analysis submitted on March 24th, 2008
In fulfillment of the requirements for the degree of
Master in Public Administration in International Development
John F. Kennedy School of Government, Harvard University

2
Dedicated to Amos Santini
Who taught me that having a job
Is the essence of freedom
At the end of the day

Executive Summary1
Southern Italy has a GDP per capita half of Northern Italy. The South seems to be a
different country to the Northerner or the foreigner: it is less productive, less
industrialized, less urbanized, and fares worse in all statistics capturing the standards of
living of the twenty Italian regions. About 80% of the Italians who immigrated to the
United States were from Southern Italy.
Every year, the Italian government allocates part of its budget to help the South catch up
with the North. Nevertheless, convergence has not happened. This Policy Analysis
attempts to give the Italian government a fresh approach towards Southern Italy, by
moving past the historical reasons behind the economic divide, and concentrating instead
on the current shape of the productive landscape: Southern Italy will be framed as if it
were a developing country, and this prism will filter accordingly the best suggested
economic strategy.
If we take two pictures of Southern and Northern Italy, we would see a dry desert in the
South studded by flourishing oases of productivity, and a fairly homogeneous fertile
valley in the North. The product space analysis confirms this intuition, and highlights the
goods that Southern Italy successfully produces, which are mainly labor intensive,
tropical agriculture and forestry. These goods have a low level of sophistication.
The process of structural transformation does not look promising: Southern Italy
struggles to produce higher value goods. However, production in firms in the South
evolves similarly to firms in the North, in the same way as people in the South behave
similarly to people in the North when they work in the same environment.
1
This Policy Analysis received support from the Sustainable Development Fund, a gift of the Italian
Ministry for Environment, Land and Sea to the Sustainability Science Program of the Center for
International Development, Harvard University. The data used in the quantitative analysis were obtained
from ISTAT with the support of the Center of International Development, Harvard University. I thank
Sandro Parodi Sifuentes, Shafique Jamal, Bailey Klinger and Marc Shotland for the help with the data
analysis. All errors are my own.

4
The problem seems to belong to the realm of path-dependency: due to historical reasons,
lack of social capital, geography and accidental occurrences, Southern Italy (1)
specialized in low technology and labor intensive products (2) much later then the North.
As a consequence, the South is stuck with what it currently produces.
Far from being inescapable, there are high hopes to bridge the current divide. Local and
central governments ought to initiate public policies that would collect information to
understand what the markets really need, while at the same time deliver specific services.
The government could (1) foster the creation of institutions for collaboration in which the
public sector learns about the needs of the private sector, (2) start public venture capital
funds, (3) provide incentives to universities to collaborate with the private sector, and (4)
systematically fight institutionalized crime.
Southern Italy must look at its own intrinsic productive nature and bet on it, while the
government can help by responding to market signals. Eventually, the government shall
act to remove ever-changing obstacles to competitiveness within the region, consequently
advancing its position in world markets, the ultimate test of success. Northern Italy shall
be the lighthouse in the midst of a sea of discoveries, where the South will ride its own
personal waves of risk and success, and Italy as a whole will benefit from a more uniform
landscape.

5
Northern, Central and Southern Italy2
2
http://www.sitesled.com/members/racialreality/italy_regions.gif

6
Table of Content
Executive Summary ........................................................................................................3
1. Introduction: The Great Divide...................................................................................7
2. Product Space Analysis, Not History........................................................................11
3. Structural Transformation Reflects the Economic Divide..........................................13
4. The Potential Export Basket Is Not Attractive...........................................................20
5. The Product Space Evolves In The Wrong Direction................................................24
6. What Does The South Export Successfully? .............................................................27
7. Northerners And Southerners Are Alike ...................................................................31
8. Southern Dynamism (Or Lack Thereof)....................................................................34
9. Social Capital and Lack of Competitiveness .............................................................36
10. The Efficiency Syndrome.......................................................................................38
11. What’s Next?..........................................................................................................40
Bibliography .................................................................................................................43
Appendix 1: Methodological Notes ..............................................................................46
Appendix 2: Additional Graphs and Tables ..................................................................48

7
Christ never came this far, nor did time, nor the individual soul, nor hope,
nor the relation of cause to effect, nor reason nor history.
Primo Levi3
1. Introduction: The Great Divide
Italy can be divided into three macro-areas, Northern, Central and Southern Italy.
With a population of 19.4 million people, Southern Italy includes seven Regions and is
comparable to Northern Italy, which includes eight Regions and has a population of 26.1
million.4
Southern Italy has an average GDP per capita of $16,700 per year, compared to
almost $32,000 in the North, the latter of which is well above the levels of Italy’s
European competitors. Since 1861, when the Italian peninsula unified in a centralized and
independent State, politicians, sociologists and economists have scrambled to find out the
reasons behind the economic divide between Northern and Southern Italy.5
Table 1. The Two Italies and their neighbors, 2004.
Southern Italy Northern Italy Italy United Kingdom France Germany
Population 19,377,736 26,100,554 57,888,245 59,694,353 62,251,817 82,531,671
GDP per capita, PPP $16,728 $31,941 $25,905 $26,476 $27,244 $25,789
Source: OECD, Eurostat.
3
Levi, P., Christ Stopped at Eboli - The Story of a Year, Read Books, 2007, p. 4.
4
Italy has a centralized State, politically and administratively divided into twenty Regions. Citizens within
each Region elect the Regional Assembly and the President. Regions can be considered as the equivalent of
States in a federal republic like the United States or Germany.
5
For selected literature on the issue, see Eckaus, R. “The North-South Differential In Italian Economic
Development,” The Journal of Economic History, Vol. 21, No. 3. (September 1961), pp. 285-317;
Zamagni, V., The Economic History of Italy, 1860-1990, Oxford University Press, 1993; Leonardi, R.
“Regional Development In Italy: Social Capital And The Mezzogiorno,” Oxford Review Of Economic
Policy, Vol. 11, No. 2, 2002.

8
If we compare the GDP per capita trend of the past ten years in the European
Union countries,6
Northern Italy has the highest GDP per capita (excluding Luxemburg),
while the South has one of the lowest. GDP per capita in the North declined slightly after
2002 when Ireland, with the second-highest GDP per capita, surpassed Northern Italy. As
an alternative measure of wealth differential, which includes financial holdings, money
transfers and real GDP allocation, households in Southern Italy have an average income
32% lower then households in the North.7
Graph 1. GDP per capita in European Union.
Source: ISTAT, Eurostat.
6
We graph the fifteen European Union countries before the 2004 enlargement, when ten more countries
joined the Union. In 2007, Bulgaria and Romania also joined, bringing the total to twenty-seven member
States.
7
In 2007, households in Northern Italy had an average total income of $44,682, while households in
Southern Italy had an average of $30,350. Data is from the Survey of Household Income and Wealth
(2006) by the Italian Central Bank and Global Financial Data.

9
After World War II, many governments tried different policy strategies to tackle
the economic divide. Development policies ranged from upfront transfers of capital from
the central government in Rome to regional and provincial governments; subsidized loans
to the same territorial entities, conditional to specific goals; incentives for successful
businesses in the North to expand their productive capacity in the South; increased fight
to the notorious criminal organizations, believed to be the root of regional
underdevelopment.
Alesina, Danninger and Rostagno (1999) have shown how the “allocation of
public employment in Italy is an important source of geographical redistribution between
regions, in particular between the North and the South. About half of the wage bill can be
thought of as redistributive.”8
As an unintended consequence, this money transfer ignited
a vicious cycle whereby a “heavy reliance on public jobs leads to a series of educational
choice and attitude towards risk which may self-reinforce a tendency to escape from
private markets.”9
After this and the many other interventions, the net gain for the South
was possibly negative.
As we see in the following graphs, GDP per capita in Northern and Southern Italy
has not shown signs of convergence in the last twenty-five years. GDP per capita in
Southern Italy grew at an annual rate of 1.45%, while in Northern Italy at 1.69%;10
Southern Italy’s GDP per capita as a percentage of Northern Italy declined from a peak of
62% in the mid-eighties to approximately 57% in 2004.
8
Alesina, A., Danninger, S. and Rostagno, M. “Redistribution Through Public Employment: The Case of
Italy,” IMF Staff Paper, Vol. 48, 2001, p. 472
9
Ibid.
10
CAGR based on GDP per capita EUR 1995 prices. Source: ISTAT, OECD.

10
Graph 2. GDP per capita in Italy, 1980-2004.
Values are logs of Euro (1995). Source: ISTAT.
Graph 3. GDP per capita of Southern Italy as a percentage of Northern Italy.
Source: ISTAT.

11
Cannari and D’Alessio (2003) show that the economic divide becomes wider if
we use the Sen welfare index, a measure of welfare that combines the average measure of
income with its distribution in the society. While specific historical characteristics of the
Italian society, like the lack of social capital in the South and its abundance in the
North,11
and the presence of criminal organizations, like the Mafia in Sicily, may have
contributed to the actual economic divide, academic research and policy design have
failed to envision a winning approach to tackle it.
2. Product Space Analysis, Not History
This SYPA will move beyond the historical reasons that have produced the
divide. It will instead attempt to photograph successful Italian enterprises as they exist
now in the territory and map out what they produce. I will show that the “product space”
of Southern Italy looks like a typical developing country, while the product space of the
North is almost a photocopy of the richest countries in the world.12
The snapshots of the
successful exports from the South to the rest of the world, and its striking comparison to
the North, will give us insights to envision a public policy that could foster growth.
We frame the product space analysis within the literature started by Hausmann,
Rodrik and Velasco (2005), where they propose an empirical approach to the analysis of
the impediments to economic growth within country. The analysis aims at finding the
existence of a “binding constraint” to growth, i.e. the flawed element in the country that,
11
See the research sparked by the seminal work on social capital in Italy by Robert Putnam, Making
Democracy Work. Civic Traditions in Modern Italy, Princeton University Press, 1993.
12
See Chapter 3 for a formal definition and explanation of the product space.

12
once unlocked, will allow the economy to grow. In other words, the framework helps to
find the best bang for the buck: since government resources are limited, and governments
will annually spend their revenues in any case, a “growth diagnostics” helps formulating
policies that will give the best results for economic growth.
The analysis of the evolution of the product space in Southern Italy in the last
fifteen years, and its comparison with the North, will focus our attention on one potential
binding constraint to growth, the lack of entrepreneurship. I leave the overall growth
diagnostic for Southern Italy, and the exploration of other potential binding constraints to
growth, to future research.
Southern Italy successfully exports fewer products then Northern Italy, and these
products are not very sophisticated in the level of technology that they need to be
produced. Since the product space in the South is extremely sparse, the capabilities
required by firms to produce the goods exported cannot easily be reused to produce
different products.
These symptoms exemplify a potential situation of market failure, where not
enough companies produce relevant goods, because they don’t find convenient to invest
in these missing industries. As a consequence, we observe a lower level of
entrepreneurship in Southern Italy, compared to Northern Italy.
The Italian government should not simply redistribute wealth as it has been doing
since the beginning of the fifties, but it should participate in the economy by improving
the conditions in which businesses operate, and by fostering the development of new
sectors. The government will have to devise mechanism to collect information from the

13
markets in Southern Italy, their failures and inefficiencies.13
Then, it could help profitable
products to be even more successful, but more importantly it ought to push the product
space to evolve beyond the current frontier of production. Northern Italy could also signal
specific hints for the development of the South.
In the second part of the SYPA, I will integrate the results of the interviews that I
conducted with two firms, one from the North and the other from the South Italy, that
helped to shed light to the way that firms operate and in particular their needs.
3. Structural Transformation Reflects the Economic Divide
Structural transformation is the process whereby poor countries change the mix of
goods that they produce from simple, labor-intensive, low-technology products into more
complex, sophisticated one (Hausmann and Klinger, 2006). The level of sophistication of
a product refers to the assets required to produce it, i.e. the set of “knowledge, physical
assets, intermediate inputs, labor training, requirements, infrastructure needs, property
rights, regulatory requirements or other public goods.”14
The sophistication of the goods
exported by a country is associated to its economic growth: the more sophisticated the
products are, the higher is the country’s GDP per capita.15
Innovation is the engine that propel firms to adapt, transform and upgrade their
capabilities into new products, and it is nurtured within “cluster of firms” (or industrial
13
The idea of public policy as a “window” through which the market signals its need comes from
Hausmann, Rodrik and Sabel (2007), p. 14.
14
Hausmann and Kinger (2006), p.1.
15
Hausmann, Hwang and Rodrik (2006).

14
districts) at a local level. Accordingly, it is imperative that countries open their economy
to world competition to strengthen their local clusters, where firms innovate and generate
higher levels of productivity.16
The product space (or “network of relatedness between products”)17
maps the
goods exported by a country according to their distance, measured by the probability that
a country has to export any pair of products. The distance implies that goods will be
closer or farther apart according to the “amount” of similar assets they need to be
produced. As Hausmann and Klinger (2006) argue, “the speed of structural
transformation will depend on the density of the product space near the area where each
country has developed its productive capabilities.”18
By mapping the existing product
space, we learn more about the real level of entrepreneurship on the ground and we can
think thoroughly about policies that may foster innovation, the creation of more
sophisticated products, and economic growth.
Using the metaphor introduced by Hausmann, the product space can be thought as
a forest, and the products are its trees: monkeys that populate the forest can jump to
nearby trees, like firms can redeploy their assets to produce goods similar to those that
they are currently producing.19
We start our analysis by visualizing the unoccupied trees
in the forest of Southern Italy.
The x-axis on Graphs 4 and 5 measures the density corresponding to each product
that is not exported with revealed comparative advantage. “Density” gives a sense of the
position of the product in the space: the lower the number, the likelier the product
16
Michael Porter, On Competition. Harvard Business Review Books, 1998, Ch. 7.
17
Hidalgo, Klinger, Barabási, Hausmann, “The Product Space Conditions the Development of Nations,”
Science, Vol. 317, 27 July 2007, p. 482.
18
Hausmann and Klinger (2006), p.2
19
Hausmann and Rodrik (2006).

15
occupies a “dense” part of the product space, i.e. it is surrounded by many other similar
products, and therefore it would be easier for firms to switch their production to that
specific product because it has similar assets. The higher the number, the likelier the good
occupies a “sparse” part of the space. The y-axis measures the level of attractiveness of
each product: the higher the value of PRODY-EXPY, the more sophisticated is the
product.20
The products are color-coded according to the classification introduced by
Leamer, that distinguishes products into 10 commodity clusters: Petroleum, Raw
Materials, Forest Products, Tropical Agriculture, Animal Products, Cereals, Labor
Intensive, Capital Intensive, Machinery, Chemicals.21
Southern Italy shows a picture very similar to a developing country like
Colombia.22
The more attractive products, situated in “dense” parts of the product space
(on the x-axis, those products around 1.5), are mainly labor intensive, tropical agriculture
and forestry. These goods have a low level of sophistication. The structural
transformation that Southern Italy could more easily and will more likely embark upon
does not look promising, because it will include goods that will not necessarily guarantee
high economic growth in the future.
20
Hausmann, Hwang and Rodrik (2006) develop the measures of PRODY and EXPY. The level of
sophistication of a product, or PRODY, is the level of income implicit in each product exported, calculated
by weighing the GDP per capita of the countries exporting the product (the weights relates to the revealed
comparative advantage, RCA, of the countries for that product); the level of sophistication of the export
basket, or EXPY, is calculated by weighing the average of the PRODY for each product exported by the
country (Hausmann and Klinger, 2006).
21
The classification and its link to the product space are introduced in Hidalgo, Klinger, Barabási,
Hausmann, “The Product Space Conditions the Development of Nations,” Science, Vol. 317, 27 July 2007.
22
See Hausmann, R., Kinger, B., “Advancing Export-Led Growth in Colombia,” Quantum Advisory
Group, May 2007, p. 24

16
Graphs 4 and 5. Unoccupied parts of the “forest” for Southern and Northern Italy, 2005.
-3-2-1012
PRODY-EXPY(PPP,2005)
1.5 2 2.5
Density (inverse)
Petroleum Raw Materials
Forest Tropical Ag
Animal Prods Cereals
L Intensive K Intensive
Machinery Chemicals
Southern Italy, 2005
-3-2-101
.5 1 1.5 2
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
Northern Italy, 2005
Variables on both axis are expressed in logs. Source: ISTAT, UN COMTRADE, additional database
courtesy of Hausmann and Klinger (2006).
Sophistication
Sophistication
Distance from
Export basket
Distance from
Export basket

17
On the contrary, Northern Italy in 2005 presents a situation diametrically
opposite, and looks more similar to a developed country like Canada.23
There are many
close “unoccupied trees,” and they represent sophisticated products like machinery,
chemicals and capital intensive goods. Northern Italy finds itself in the “healthy part” of
the product space and it will likely continue its structural transformation towards more
sophisticated goods.
If we compare the evolution over time of the product space, Northern Italy seems
to have missed opportunities to move to higher level of export sophistication. The North
had an enviable position in 1991, where many of its machinery, chemical and capital
intensive goods where in a dense part of the product space and thus had many attractive
opportunities. Along the years, the opportunities seemed to shift towards less dense part
of the forest. It seems that Northern Italy failed to seize opportunities that were easy to
catch (see Appendix 2 for the Graphs depicting the historic evolution of structural
transformation in Northern and Southern Italy in 1991, 1995 and 2000).
As for Southern Italy, the texture of its product space remained similar along the
years, showing that the South has not found yet a way to change its productive system: its
firms keep producing the same unsophisticated products, and it is difficult for them to
change their production to different kind of goods.
23
See Hausmann, R., Klinger, B., “Structural Transformation in Chile,” Quantum Advisory Group, June
2007, p. 30

18
Graph 6. The Product Space in Southern Italy, 2005.
Source: ISTAT.

19
Graph 7. The Product Space in Northern Italy, 2005.
Source: ISTAT.

20
The previous Graphs 6 and 7 represent a visual representation of the product
space in Southern and Northern Italy in 2005 (see Appendix 2 for the visual
representation of the product space in Northern and Southern Italy in 2000). The
difference between the two “countries” is puzzling, and it shows two productive systems
that reached stages of development dramatically different. What happened to Southern
Italy? How is it possible that two parts of the same country, that share the same legal and
political system, populated by the same people, show an entrepreneurial environment so
different?
4. The Potential Export Basket Is Not Attractive
In 2006, Italy exported a total of $263 billion worth of products.24
High-value
goods were over 41% of exports: mechanical and electrical machineries, transport
equipment, rubber, plastic and chemicals. If we consider the overall level of
sophistication of the export basket, the variable “open forest”25
captures the aggregate
value of the products not currently exported, but relatively “close” to the current export
basket. The higher the value of open forest, the greater is the value of the potential export
basket which would include new potential exports based on their proximity to actual
exports.
24
ISTAT FOB data, as reported in Euro by EIU; exchange rate from Global Financial Indicators.
25
The concept of “open forest” was first introduced in Hausmann and Klinger (2006), p.6

21
Graph 8. Composition of Italian Exports in 2006.
Export values are FOB. Source: ISTAT, as reported by EIU.
In Graph 9, we observe a strong cross-country correlation between the level of
GDP per capita and the value of the potential export basket: open forest is a good
predictor of the current level of wealth.26
While Northern Italy (ITN) displays a excellent
potential export basket, Southern Italy (ITS) does not presents a sophisticated one.
Nevertheless, the gamut of possibilities that firms in the South face is very similar both to
some developing countries like Mexico and Uruguay, and to developed countries like
New Zealand and Israel. It seems that Southern Italy does not have the opportunities to
move to highly sophisticated parts of the product space like Northern Italy, but it is not
badly positioned if compared to other developing (and developed) countries. Southern
Italy is disadvantaged compared to Northern Italy.
26
See Hausmann and Rodrik (2006) for a full proof.

22
Graph 9. “Open Forest” and GDP per capita in 2000.
Variables on both axis are expressed in logs; GDP per capita is expressed in USD PPP 2000. Source:
ISTAT, OECD Stat, UN COMTRADE, additional database courtesy of Hausmann and Klinger (2006).
Looking at the following two graphs, while the level of sophistication of the
export basket has increased in the South in the past decade, the value of the option to
move to a more sophisticated level of the export value has actually decreased, indicating
a potential slowing in the future evolution of the product space, and accordingly,
economic growth. If we compare both the level of sophistication and the option value to
move to a higher sophisticated part of the product space with Germany and the United
Kingdom, the results are in line with the GDP per capita differentials, positioning
Northern Italy ahead of the two European competitors and the South.

23
Graph 10 and 11. Evolution of “EXPY” and “Open Forest”
Source: ISTAT, OECD Stat, UN COMTRADE, additional database courtesy of Hausmann and Klinger
(2006).

24
5. The Product Space Evolves In The Wrong Direction
Each product that Southern Italy does not currently export with revealed
comparative advantage is a potential contributor to the future process of structural
adjustment. If Southern Italy started to export tiles, for example, how would this new
capability influence the overall product space? It would depend from the position that
tiles occupy in the current product space of the South. If tiles were surrounded by existing
firms producing glazing, coatings or art decorations, then the South would highly benefit
from specializing in the production of tiles. On the other hand, if there were no firms
related to the production of tiles, then the South would not benefit as much if it started to
specialize in the tile industry. Tiles would not have a high strategic value for the South.27
These graphs give us a vivid snapshot of the products with high strategic value in
Southern and Northern Italy. Like before, it seems that the two pictures visualize two
different countries. Firms in the South will more easily redeploy their capabilities onto
those products close to 0 on the x-axis.28
Unfortunately, these products do not have a high
strategic value, beside being relatively unsophisticated products, like labor intensive,
tropical agriculture products, forestry and raw materials.
On the other hand, we see a very different picture in the North, where chemicals,
machineries and capital intensive products display high strategic value. Even if the South
embarked upon a process of structural transformation, it would not reap the benefits from
its advancement. In other words, the South could evolve its product space into a dead
end, where it could easily move into the production of goods that do not help bridging the
27
The concept of Strategic Value comes from Hausmann and Klinger (2007).
28
Like before the x-axis measure the proximity to the current production space.

25
GDP per capita gap with the North.
Graph 12 and 13. Strategic Value of Each Products in Southern and Northern Italy, 2005.
56789
StrategicValue
1.5 2 2.5
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
678910
StrategicValue
.5 1 1.5 2
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
Strategic Value
of Each Product
Distance from
Export basket
Distance from
Export basket
Strategic Value
of Each Product

26
On Graph 14, we observe the quality of the specialization of Southern Italy
around specific products or sectors. The measure of “centrality”29
indicates the dense or
sparse area in the product space where a country specializes. In other words, it captures
the idea that Southern Italy specializes in a sparse (bad) part of the product space, as
opposed to Northern Italy that specializes in a much denser (good) part. Hausmann and
Klinger (2007) show a strong correlation of “centrality” with GDP per capita, indicating
that rich countries specialize in dense parts whereas poor countries specialize in sparse
part. Southern Italy’s level of centrality has also been worsening in the past decade. In
summary, when the products space evolves, it does so in the wrong direction.
Graph 14. Position of exports in the product space for Southern and Northern Italy.
29
As first introduced in Hausmann and Klinger (2007).

27
6. What Does The South Export Successfully?
The idea that a country should specialize in highly sophisticated products, because
they will be associated with higher income per capita, is the core of this analysis. If we
focus on what Southern Italy produces advantageously compared to Northern Italy and
other countries, then policy makers will have hints for devising the appropriate economic
strategy. This will necessarily balance interventions on products (and firms, or cluster of
firms) that Southern Italy already successfully produces and on sophisticated products
that firms in the South could potentially start producing with comparative advantage.
The concept of Revealed Comparative Advantage (RCA) captures well the idea of
successful products.30
In an open economy, countries that successfully produce specific
goods also export them with RCA>1. For example, in 2005 Southern Italy exported
canned tomatoes with RCA=94.3. This indicates that Southern Italy share of canned
tomatoes exports over the total exports of Southern Italy is well above the aggregated
world export of canned tomatoes over the total world export. Southern Italy has
developed an healthy industry of canned tomatoes: it has developed all the capabilities
and assets connected with producing, selling and exporting canned tomatoes. Southern
Italy is good at it.
30
I use the concept of RCA as mentioned in Hausmann and Klinger (2006).

28
Graph 15. Number of Products Exported with RCA>1 in Southern and Northern Italy.
Source: ISTAT, UN COMTRADE, additional database courtesy of Hausmann and Klinger (2006).
If we look at the past two decades, Southern Italy has slightly augmented the
number of products that it exports with RCA>1: they were 174 in 1991, they are 183 in
2005. On the other hand, in 2005 they are still less then half the number of products
exported by Northern Italy with RCA>1. In addition, Northern Italy has been going
through a more relevant process of product space evolution since 1991, and increased its
exports of products with RCA>1 by almost 6%.
Table 2 details the top 20 products (out of a total of 484) that Southern Italy
exports with RCA>1: agricultural products or related goods like tomatoes, oil, grapes,
fruit, vegetable and nuts preserves, lettuce and chicory; labor intensive products like skin
leather and carving material.

29
Table 2. Top 20 products exported with RCA>1 in Southern Italy, 2005.
RCA HS code Description
1 94.3 2002 Tomatoes prepared or preserved otherwise than by vinegar or acetic acid
2 61.7 4112
Sheep or lamb skin leather, without wool on, further prepared after tanning or
crusting, other than of heading 4114
3 45.8 1510 Olive-residue oil and blends of olive oil and oil-residue oil, not chemically
4 34.9 0806 Grapes, fresh or dried
5 34.5 0812
Fruit and nuts provisionally preserved (by sulfur dioxide gas, in brine etc.), but
unsuitable in that state for immediate consumption
6 28.6 9601
Worked ivory, bone, tortoise-shell, horn, coral and other animal carving
material and articles thereof (including articles obtained by molding)
7 26.5 1902
Pasta, whether or not cooked or stuffed or otherwise prepared, including
spaghetti, lasagna, noodles etc.; couscous, whether or not prepared
8 21.6 2209 Vinegar and substitutes for vinegar obtained from acetic acid
9 18.4 0814
Peel of citrus fruit or melons (including watermelons), fresh, frozen, dried or
provisionally preserved
10 18.4 4105
Tanned or crust skins of sheep or lamb, without wool on, whether or not split,
but not further prepared
11 14.2 1509 Olive oil and its fractions, whether or not refined, but not chemically modified
12 13.8 2105 Ice cream and other edible ice, whether or not containing cocoa
13 13.4 0501
Human hair, unworked, whether or not washed or scoured; waste of human
hair
14 12.6 2901 Acyclic hydrocarbons
15 11.9 0705 Lettuce (lactuca sativa) and chicory (cichorium spp.), fresh or chilled
16 10.2 9401
Seats (other than barber, dental and similar chairs), whether or not convertible
into beds, and parts thereof
17 10.1 2006
Vegetables, fruit, nuts, fruit-peel and other parts of plants preserved by sugar
(drained, glace or crystallized)
18 9.6 0813
Fruit, dried, nesoi (other than those of headings 0801 to 0806); mixtures of
nuts or dried fruits of this chapter
19 9.0 0702 Tomatoes, fresh or chilled
20 8.9 2515
Marble, travertine and other calcareous building etc. Stone of an apparent
specific gravity of 2.5 or more, and alabaster roughly shaped etc. Or cut
Source: ISTAT, UN COMTRADE, additional database courtesy of Hausmann and Klinger (2006); the
descriptions of products (Harmonized System 4-digit level, HS code) is from the United States
International Trade Commission, available at http://reportweb.usitc.gov/commodities/naicsicsitc.html.
The picture is dramatically different in Northern Italy, where capital intensive
goods like tiles, glasses, machineries like those to process leather, automatic good
vending machines, presses and crushes, appliances and guns and rifles, as well as
chemicals rubber and related articles are the top exports.

30
Table 3. Top 20 products exported with RCA>1 in Northern Italy, 2005.
RCA HS code Description
1 18.3 2205
Vermouth and other wine of fresh grapes flavored with plants or aromatic
substances
2 16.8 6907
Unglazed ceramic flags and paving, hearth or wall tiles; unglazed ceramic
mosaic cubes and similar products
3 14.0 2209 Vinegar and substitutes for vinegar obtained from acetic acid
4 11.6 9004 Spectacles, goggles and the like, corrective, protective or other
5 10.4 6215 Ties, bow ties and cravats, not knitted or crocheted
6 10.3 8453
Machinery for preparing or working hides, skins or leather or for making or
repairing footwear or other articles of leather etc. Nesoi; parts thereof
7 10.2 6908
Glazed ceramic flags and paving, hearth or wall tiles; glazed ceramic mosaic
cubes and similar products
8 10.0 8476
Automatic goods vending machines, including cigarette, food or beverage and
money-changing machines; parts thereof
9 9.3 5109 Yarn of wool or fine animal hair, put up for retail sale
10 9.0 8435
Presses, crushers and similar machinery used in the manufacture of wine,
cider, fruit juices or similar beverages; parts thereof
11 8.9 5112 Woven fabrics of combed wool or combed fine animal hair
12 8.7 4114
Chamois leather; patent leather and patent laminated leather; metallized
leather
13 8.7 1902
Pasta, whether or not cooked or stuffed or otherwise prepared, including
spaghetti, lasagna, noodles etc.; couscous, whether or not prepared
14 8.1 9003 Frames and mountings for spectacles, goggles or the like, and parts thereof
15 7.8 0210
Meat and edible meat offal, salted, in brine, dried or smoked; edible flours and
meals of meat or meat offal
16 7.4 5107 Yarn of combed wool, not put up for retail sale
17 7.4 4017
Hard rubber (for example, ebonite) in all forms, including waste and scrap;
articles of hard rubber
18 7.1 8422
Machines, for dishwashing, for cleaning, drying, filling, closing etc. Containers,
for other packing etc., and for aerating beverages; parts thereof
19 6.9 4806
Vegetable parchment, greaseproof papers, tracing papers, glassine and other
glazed transparent or translucent papers, in rolls or sheets
20 6.8 9303
Sporting shotguns and rifles, muzzle loading firearms, very pistols and similar
devices, pistols and revolvers firing blank ammunition, etc.
Source: ISTAT, UN COMTRADE, additional database courtesy of Hausmann and Klinger (2006); the
descriptions of products (Harmonized System 4-digit level, HS code) is from the United States
International Trade Commission, available at http://reportweb.usitc.gov/commodities/naicsicsitc.html.
Entrepreneurship arises in the wrong part of the product space of Southern Italy.
How is it possible that people in the South do not seize upon opportunities to create high
sophisticated products? Are Southerners too much risk-averse? Is there something else
that characterizes inherently their behavior and entrepreneurial actions?

31
7. Northerners And Southerners Are Alike
In 2006, wages in Southern Italy were on average approximately 6% lower than in
the North (See Appendix 2 for descriptive statistics). Their distribution according to the
level of education highlights that people with no education and people with very high
level of education earn more in the South that in the North (See Graph 16). The latter
could be explained with the scarceness of highly educated people, who tend to migrate to
the North. The South tends to be more unequal, with a Gini Coefficient of 0.31 versus
0.25 in the North.31
Almost 38% of the residents in the South has less then 5 years of
education while in the North the percentage is 30%; 55% of the residents in the South
have between 5 and 13 years of schooling, while this ratio increases to 62% in the North.
Graph 16. Wages in Southern and Northern Italy, by education level, 2006.
05101520
HourlyWages
None Elementary Middle High Bachelor Post
Wages in SOUTH Wages in NORTH
Source: Survey of Household Income and Wealth (2006), Italian Central Bank.
31
I used the Household Survey for 2006 to calculate the GINI coefficient.

32
Brunello, Comi and Lucifora (2000) show that returns to education in Italy are
stable over time: they have not significantly changed in the period 1977-1995, with the
exception of 1993 and 1995 when the increase was due mainly to higher return to
education in the public sector. A simple analysis of individual behavior through the
Household Surveys published by the Italian Central Bank sheds some light on
hypothetical differences between people in the South and in the North. In 2006, workers
in Southern Italy earn on average almost 13% less then workers in Northern Italy, after
controlling for the effect on wages of their education, work experience and place of birth
(see regressions 4-6 on Table 4).
Southern Italians earn less than Northerners because they work in the South. Is
this due to some intrinsic characteristic of being a Southerner? We delve into this
question with a thought experiment, based on data from the Household Surveys of the
past twenty years. If we consider the Italians who worked in Northern Italy, and compare
those who were born in the South with those who were born in the North, we do not find
any unexplained difference in their “economic performance.”
In 1989 (2000), Southerners working in the North outperformed their fellow
Northerners by almost 8% (5.6%), and over 50% of this small difference is explained by
the difference in their respective endowments, i.e. education and experience (see Table
5); these results are consistent with the findings of Brunello, Comi and Lucifora (2000)
for the period 1977-1995. Using the Blinder-Oaxaca decomposition we can describe the
wage gap into an “explained” portion due to differences in endowments and an
“unexplained” portion due to differences in coefficients.

33
Table 4. Estimation Results: Returns to Education in Italy, 2006.
Dependant Variable: Log of Hourly Wage
(1) (2) (3) (4) (5) (6)
Education (years) 0.065 ** 0.068 ** 0.013 0.064 ** 0.006 0.061 **
(0.002) (0.002) (0.014) (0.002) (0.014) (0.003)
Education Squared 0.002 ** 0.003 **
(0.001) (0.001)
Education by Born in South 0.007
(0.004)
Experience (years) 0.049 ** 0.050 ** 0.052 ** 0.048 ** 0.050 ** 0.048 **
(0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Experience Squared -0.001 ** -0.001 ** -0.001 ** -0.001 ** -0.001 ** -0.001 **
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
Female (dummy) -0.154 ** -0.156 **
(0.014) (0.014)
Born in South (dummy) 0.035 0.032 -0.039
(0.024) (0.024) (0.054)
Works in South (dummy) -0.126 ** -0.129 ** -0.127 **
(0.026) (0.026) (0.026)
Born in Centre (dummy) 0.029 0.031 0.033
(0.032) (0.032) (0.032)
Works in Centre (dummy) -0.041 -0.043 -0.044
(0.031) (0.031) (0.031)
Born in North (dummy)
Works in North (dummy)
Constant 0.535 ** 0.551 ** 0.831 ** 0.572 ** 0.867 ** 0.604 **
(0.044) (0.043) (0.078) (0.044) (0.080) (0.047)
R-square 0.208 0.224 0.226 0.213 0.216 0.213
Observations 5957 5957 5957 5957 5957 5957
Notes:
OLS with Heteroskedasticity-robust Standard Errors
Heteroskedasticity-robust standard errors are shown in parenthesis
* Statistical significance at the 10-percent level
** Statistical significance at the 5-percent level
There is no significant “unexplained gap” between Southerners and Northerners
working in the North: accordingly, we did not find any hints of either discrimination
towards Southerners, nor “intrinsic difference” of the Southerners.

34
Table 5. Southern-Northern Italy Wage Gap Decomposition Results, 1989-2006
Year Hourly Wage Gap Explained Unexplained
1989 0.078 ** 0.039 ** 0.028
1995 0.005 0.024 0.012
2000 0.056 ** 0.046 ** 0.008
2006 0.016 0.025 0.040
Notes:
Blinder-Oaxaca decomposition of the mean outcome differential
Wage Gap is in percentage
Decomposition results based on the regression results in Table 8
Source: Survey of Household Income and Wealth (1989-2006), Italian Central Bank.
8. Southern Dynamism (Or Lack Thereof)
There are no intrinsic differences between Southern and Northern Italians. Still,
the product space of the South looks like a desert dotted by oases of productivity. If we
look at the existing firms and analyze the way that they evolved during a brief period of
time, from 2000 to 2005, the process of structural transformation took place indeed.
Firms in the South developed on average RCA in five years 4 percentage points
less than firms in the North (see regression 8). The difference is very small, and when we
control for the position of the firm in the product space (“Density”), and the relative
sophistication of the product (“ProdY”), the difference between North and South almost
vanishes (see regressions 7). Different specifications of the model return similar results
(regressions 1-6). The low density of the product space in the South is the main factor
explaining the poor performance of Southern Italy as a whole.

35
Table 6. Estimation Results: The Process of Structural Adjustment
Dependant Variable: RCA_dummy in 2005
(1) (2) (3) (4) (5) (6) (7) (8)
RCA_dummy in 2000 0.3780 ** 0.3778 **
(0.0100) (0.0098)
Density 0.1678 ** 0.1533 ** 0.3081 ** 0.4251 **
(0.0240) (0.0187) (0.0252) (0.0609)
ProdY 0.0054 ** 0.0044 ** 0.0050 ** 0.0137 **
(0.0009) (0.0007) (0.0001) (0.0024)
SOUTH_dummy -0.0057 -0.0160 ** 0.0146 ** -0.0334 ** 0.0212 * -0.0031 -0.0144 ** -0.0403 **
(0.0057) (0.0045) (0.0052) (0.0045) (0.0114) (0.0109) (0.0142) (0.0112)
Constant 0.4041 ** 0.5496 ** 0.4280 ** 0.5598 ** 0.6199 ** 0.8289 ** -0.2438 ** 0.1246 **
(0.0220) (0.0043) (0.0164) (0.0046) (0.0251) (0.0076) (0.0560) (0.0107)
R-square 0.0056 0.0002 0.1411 0.1372 0.0302 0.0000
Observations 3308 3310 4637 4648 3334 3345 3308 3310
Notes:
(1-6) OLS with clustering over product
(1-2) are with RCA_dummy in 2000 = 0
(5-6) are with RCA in 2005 > then RCA in 2000
(7-8) Probit with clustering over product
ProdY values were multiplied by 1,000
Source: ISTAT, UN COMTRADE, additional database courtesy of Hausmann and Klinger (2006).
Firms in the South evolve their capabilities and move to nearby products, like
firms in the North, but fail to develop new capabilities of producing different, more
sophisticated product, due to their current position in the product space. Southern Italy
seem stuck in what it produces now. It is easier for the North to transform since its firms
can redeploy the productive characteristics to different, strategic products nearby.
These results can be framed within the broader literature of path-dependency.32
Firms will deploy their capabilities based on the existing assets: since Southern Italy
32
Many authors have linked entrepreneurships with path-dependency. As relevant examples, see De Blasio
and Nuzzo (2003) p.6, Greener (2002) p. 614, Porter (2001) p.28.

36
presents a sparse picture of products and related capabilities, firms struggle to redeploy
capabilities into new opportunities, or embarking upon the process of “self-discovery.”33
9. Social Capital and Lack of Competitiveness
Since (1) there is no intrinsic difference between Southerners and Northerners,
and (2) firms in the South struggle to produce new, different goods, it may be interesting
to explore the relevance of specific sociological elements that could affect the current
structure of the product space.
Endowments of social capital in Southern and Northern Italy have been incredibly
consistent across centuries (Putnam, 1993). Social capital influenced the two different
economic growth paths through its effects on financial development, level of investments,
work behavior, labor productivity, public spending and corruption, among other channels.
More specifically, it seems that “differences in trust, reciprocity, and habits of co-
operation lead to large differences in economic outcomes across areas characterized by
identical formal institutions” (De Blasio and Nuzzo, 2004). Southern and Northern Italy
exist within the same legal framework, but have developed different formal and informal
institutions. Gambetta (2000) hints at the presence of Mafia in Sicily as the main
impediment to development of healthy relationships of trust in the South, factor that
negatively influences the entrepreneurial decisions to invest. In 2006, the Mafia had an
33
As described in Hausmann and Rodrik (2003).

37
estimated turnover of $120 billion, which correspond approximately to 6% of the Italian
GDP for that year.34
The southern regions of Campania and Calabria are dominated by region-wide
criminal organizations like Mafia, called respectively Camorra and ‘Ndrangheta. In these
regions the criminal organizations have penetrated the vacuum left by the lack of trust
between people by guaranteeing business transaction through coercive intimidation and
overt violence. Negative consequences are rent-seeking, blocked innovations, dwarfed
competitiveness and monopolistic tendencies (Gambetta and Reuter, 1995) that
deteriorated the business environment.
Southern Italy displays higher levels of corruption than Northern Italy (Del Monte
and Papagni, 2006), due to two main reasons: the lower social capital in the South and the
associated lower levels of civic-ness, or care for the public good; and the higher relative
presence of public jobs provided by the State. Guiso, Sapienza and Zingales (2004) prove
the positive correlation between high levels of social capital and lack of financial
development, more so in places like Southern Italy where the rule of law is weak. Ichino
and Maggi (2000) show that misconduct and absenteeism in large Italian banks is
“considerably more frequent in the Southern branches of the bank.”
Low level of social capital in Southern Italy can be associated to low level of
entrepreneurship and the low number of products successfully exported: “the success of
small and medium-sized enterprises operating inside industrial districts seemed to be
somehow more connected with social and institutional elements than with merely
economic ones” (Cainelli and Rizzitiello, 2004). Institutions like the public
administration, the judicial system but also large private corporations, “can function very
34
Confesercenti (2007).

38
differently in different cultural environments,” and it seems that “the south of Italy is an
area where the prevailing “culture” discourages private activity and entrepreneurship”
(De Blasio and Nuzzo, 2004).35
10. The Efficiency Syndrome
Ellis and Pecotich (2001) suggest that the decision to export a product, as well as
the destination of the export, is strongly associated with the “cosmopolitanism” of the
decision makers. In December 2007, I traveled to Sicily and interviewed with the CEO of
a successful firm that manufactures pharmaceutical products, to shed some light into the
business environment where it operates.
“Local firms are affected by ‘acquired immune efficiency syndrome.’ We must
build our own destiny,” Interviewee A recounts, moving into a tirade about the lack of
infrastructures (like internet and a modern natural gas grid) and the inefficiency of the
local public administration. “We based our success on technological innovation and new
foreign markets: our standard is not based on the local prevailing culture or market needs,
but the international markets.” Since the firm has a small branch in Northern Italy, the
CEO highlights the difference between the business environments in Southern and
Northern Italy: the latter has (1) a more efficient public administration (2) a more
dynamic labor market.
35
They paraphrase a concept from Alesina et al. (2001).

39
The choice to operate in the specific territory is connected with the history of the
family who started the business three generations ago. The firm does not operate within
an industrial district, nor there is any element of the local environment that would make it
more successful than operating somewhere else: there is no link between the goods
produced and the territory. Actually, the cost of operating in a business environment
where special care and time is required to build and maintain vertical social relationships
adds to the total production cost. The geographic isolation negatively impact the
competitiveness of the firm: since there are no “institution of collaboration”36
nor local
public or private research centers, the firm must internalize all R&D. This factor is
negatively combined with an abundance of unskilled workforce.37
The negative elements of operating in the South were in great part confirmed by
Interviewee B, a middle-level manager of an important car maker in Northern Italy, in
charge of the institutional relations of the company. Interviewee B mentions the lack of
infrastructure (railways and reliable electricity) and the organized crime as the main
constraints for the firm to operate in the South, despite the incentives that the government
and the European Union provide to operate a business there.
In the end business decisions are political. The firm does not invest for the
specific advantage of operating in the South, but to maintain a long term cozy political
relationship with the government: “Market research showed that we would have had the
same monetary incentives to operate in Portugal, England or Southern Italy. Even if in
36
Porter, M., Emmons, W., “Institution for Collaboration: Overview,” HBS Case 9-703-436, January 29,
2003.
37
In 2006, over 31% of the residents in Southern Italy held a high school diploma or higher level of
education, while in the North the level is over 41%.

40
the South there were infrastructure deficiencies, we choose it following strong political
pressures.”
11. What’s Next?
The product space is sparse, the productive capabilities are deployed in low
sophisticated goods, the cultural problem has historical motivations dating back a
thousand years ago. If we deem important that “new activities […] need to exploit
existing capabilities, [like] markets, physical and human assets, norms and institutions
that were developed and accumulated for other pre-existing activities,”38
then Southern
Italy is in a discouraging position. What can the government do to help?
Following the line of reasoning highlighted by Hausmann, Rodrik and Sabel
(2007), the government should encourage new firms to emerge and assist existing one to
evolve. While the market has faltered due to self-discovery externalities, coordination
failures and lack of public inputs, the government does not have ex-ante the relevant
information to intervene and foster entrepreneurship in future highly productive activities.
In addition, Guiso and Schivardi (2006) have exposed the vicious cycle of the
relationship between low level of entrepreneurship and externalities.
The approach that we describe here starts from the analysis of what happens now
on the ground and pairs this information with “setting up self-organizing, open
38
Hausmann and Rodrik (2006) p.12

41
architecture, transparent entities […] to create windows […] that receive requests;”39
it
aims at creating institutions for collaboration where the public sector can establish an
ongoing dialogue with private companies to understand what is needed in the business
environment that would help to produce a specific good. For example, each main city in
the South already has a Chamber of Commerce widely believed to know well the local
private sector. The government should establish a permanent link with these entities to
open a window into the existing private sector and be alert to the possibilities of new
goods being produced.
Lobbying the government is not enough. Hausmann, Rodrik and Sabel (2007)
suggest the creation of public venture funds that would help in the collection of valuable
information on the ground. These venture funds would operate similarly to private
venture capital: for example, a firm in Messina or Trapani that want to establish a new
business in the production of an innovative machine for the processing of olive oil would
knock the door. The public fund would screen all requests of funding in the same way as
a private fund would do, but it would be financed by the government (local?) and collect
information about the business environment and its needs.
Universities in Italy are infamously detached from the business environment,
more so in Southern Italy. The government could promote institution for collaboration
between universities and the existing firms, in ways to ignite virtuous cycles of reciprocal
influence.
Crime should be fought at a local level by the police, but at the same time the
government could spark a culture of civic-ness and show that healthy, entrepreneurial
39
Hausmann and Rodrik (2006) p.33

42
ideas are rewarded and encouraged. New businesses in particular should be protected
from the potential infiltration of criminal organizations.
These interventions would address the lack of product innovation by helping the
existing businesses to improve their capabilities and make the leap of faith of venturing
into unknown parts of the production space. For example, the government should look at
the canned tomatoes industry as a productive sector that works, and try to see if there is
any way to improve the business environment to foster and sustain growth and encourage
firms to innovate in similar activities but with higher value.
Can we learn something from what Northern Italy currently produces? While
Campania and Puglia, Basilicata and Sardinia, Molise and Calabria, and Sicily should
focus on what they currently produce to infer elements that could guide their own vision
for the future, it seems extreme to exclude the North from this analysis. The overall
economic strategy for the South should include synergies with the successes obtained by
Northern entrepreneurs and firms, transfer of product innovation, business best practices
and human capital. After all the trouble that Giuseppe Garibaldi went thorough when he
led the unification of Italy almost one hundred and fifty years ago, the Italian
entrepreneurial spirit from the South and the North integrate and converge into a new
renaissance of Italian development.

43
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Appendix 1: Methodological Notes
Qualitative Analysis
• I submitted the Preliminary Questionnaire on the Use of Human Subjects or Human
Subjects Data in Research for the interviews to RAO (HKS Research Administration
Office) on 11/15/2007; RAO granted the research exemption from IRB committee
review on 12/03/2007.
• I conducted two interviews, and kept the name of the interviewees confidential, as per
original request to RAO :
o Interviewee “A” on 12/17/2007 (from Sicily, Southern Italy)
o Interviewee “B” on 12/19/2007 (from Piedmont, Northern Italy)
Quantitative Analysis
• Export data by region (for years 1991, 1995, 2000 and 2005) were obtained from
ISTAT (Italian National Institute of Statistics). The total of the export data of each
year is lower then the official figure published by ISTAT, because some data could not
be released due to privacy laws (less then 10% in value);
• Eurostat is the Statistical Office of the European Union. Data at regional level were
obtained either through their website (http://epp.eurostat.ec.europa.eu) or through
Eurostat databases published in CD-Rom; other data at regional level were obtained
from the statistical portal of OECD (http://www.oecd.org/statsportal);

47
• The Surveys of Household Income and Wealth for the years 1977-2006 are published
bi-annually by the Italian Central Bank, and are available for download from its
website (http://www.bancaditalia.it/statistiche/indcamp). The Bank also publishes a
Survey of Industrial and Service Firms for the years 1984-2006
(http://www.bancaditalia.it/statistiche/indcamp/indimpser).

48
Appendix 2: Additional Graphs and Tables
Graph 17. GDP of Southern Italy as a share of GDP of Italy.
Source: ISTAT.
Graph 18. Long run GDP per capita in Italy (and United States).
Values on y-axis are natural logs of GDP per capita in 1990 International Geary-Khamis dollars. Source:
Maddison’s website (file: Historical Statistics for the World Economy: 1-2003 AD).

49
Graphs 19, 20. Unoccupied parts of the “forest” for Southern and Northern Italy, 1991.
-4-202
PRODY-EXPY(1991)
1 1.5 2 2.5
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
-4-3-2-101
PRODY-EXPY(1991)
.5 1 1.5 2
Density (inverse)
Forest Tropical Ag
Machinery Chemicals

50
Graphs 21, 22. Unoccupied parts of the “forest” for Southern and Northern Italy, 1995
-3-2-1012
PRODY-EXPY(1995)
1.6 1.8 2 2.2 2.4
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
-3-2-1012
PRODY-EXPY(1995)
1.2 1.4 1.6 1.8 2
Density (inverse)
Forest Tropical Ag
Machinery Chemicals

51
Graphs 23, 24. Unoccupied parts of the “forest” for Southern and Northern Italy, 2000.
-3-2-101
1.5 2 2.5
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
-3-2-101
.6 .8 1 1.2 1.4
Density (inverse)
Forest Tropical Ag
Machinery Chemicals

52
Graph 25. The Product Space for Southern Italy, 2000
Source: ISTAT.

53
Graph 26. The Product Space for Northern Italy, 2000
Source: ISTAT.

54
Graph 27. “ Legend” for the Product Space for Northern Italy, 2000-2005
Graphic elaboration courtesy of Bailey Klinger.

55
Graphs 28, 29. Strategic Value of Each Products in Southern and Northern Italy, 2000.
56789
StrategicValue
1.5 2 2.5
Density (inverse)
Forest Tropical Ag
Machinery Chemicals
678910
StrategicValue
.6 .8 1 1.2 1.4
Density (inverse)
Forest Tropical Ag
Machinery Chemicals

56
050010001500
Frequency
mean
wage_NORTH
Tables 7. Wages and Educational Attainment in Southern and Northern Italy, 2006
Wages in Southern Italy Wages in Northern Italy
Percentile Smallest Percentile Smallest
1% 0.89 0.20 1% 0.77 0.29
5% 2.20 0.29 5% 2.99 0.29
10% 3.13 0.29 Obs 1557 10% 4.81 0.29 Obs 3038
25% 5.00 0.30 Sum of Wgt. 1557 25% 6.25 0.30 Sum of Wgt. 3038
50% 7.21 Mean 8.08 50% 7.69 Mean 8.57
Largest Std. Dev. 5.86 Largest Std. Dev. 5.06
75% 9.62 52.20 75% 9.62 53.13
90% 12.99 61.97 Variance 34.33 90% 12.82 57.69 Variance 25.61
95% 17.09 64.10 Skewness 4.08 95% 16.15 57.69 Skewness 3.92
99% 32.05 76.92 Kurtosis 32.60 99% 28.13 67.31 Kurtosis 29.94
0100200300400500
Frequency
mean
wage_SOUTH
Educational Attainment in Southern Italy Educational Attainment in Northern Italy
Years Number Percentage Cum. Per. Years Number Percentage Cum. Per.
0 928 14.49 14.49 0 866 9.88 9.88
5 1,490 23.27 37.76 5 1,739 19.84 29.71
8 1,965 30.68 68.44 8 2,557 29.17 58.88
13 1,576 24.61 93.05 13 2,845 32.45 91.33
17 433 6.76 99.81 17 738 8.42 99.75
19 12 0.19 100 19 22 0.25 100
Total 6,404 100 Total 8,767 100

57
Table 8. Estimation Results: Return to Education in Italy, 1989-2006.
Dependant Variable: Log of Hourly Wage
(1989) (1989) (1995) (1995) (2000) (2000) (2006) (2006)
Born in South Born in North Born in South Born in North Born in South Born in North Born in South Born in North
Works in North Works in North Works in North Works in North Works in North Works in North Works in North Works in North
Education (years) 0.057 ** 0.053 ** 0.048 ** 0.066 ** 0.055 ** 0.059 ** 0.059 ** 0.062 **
(0.005) (0.002) (0.007) (0.003) (0.006) (0.003) (0.0010) (0.003)
Experience (years) 0.037 ** 0.040 ** 0.040 ** 0.063 ** 0.059 ** 0.065 ** 0.024 ** 0.051 **
(0.006) (0.003) (0.013) (0.004) (0.011) (0.004) (0.009) (0.004)
Experience Squared 0.000 ** -0.001 ** -0.001 -0.001 ** -0.001 -0.001 ** 0.000 -0.001 **
(-0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
R-square 0.369 0.296 0.146 0.319 0.324 0.298 0.154 0.218
Observations 426 2547 381 2549 369 2553 326 2324
Notes:
OLS with Heteroskedasticity-robust Standard Errors

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