xxii conferenza italiana di scienze regionali

XXIX CONFERENZA ITALIANA DI SCIENZE REGIONALI
TRANSFRONTIER COMMERCIAL COOPERATION IN ‘METROPOLI TERRA DI
BARI’: FOREIGN DIRECT INVESTMENT AND ENVIRONMENTAL
SUSTAINABILITY
Elena PALMA1, Caterina DE LUCIA2 e Pasquale PAZIENZA3
1 Office for Strategic Metropolitan Planning - Bari
2 University of York, University of Foggia and Technical University of Bari
3 University of Foggia and University of Durham
ABSTRACT
The present work constitutes a starting point in the process of strategic planning of
‘Metropolitan Area of Bari’ with particular reference to the openness of the area to
transfrontier commercial cooperation.
The last Italian Economic Census showed a clear improvement in the economic performance
(in terms of workers and sectoral added value) of the Adriatic Regions with respect to the rest
of Italy over the last ten years.
The improved economic performance of the Adriatic Regions compared to the Tyrrhenian
ones seems to be mostly related to the growing ‘openness to trade of Eastern Europe’ towards
the Adriatic Regions of Italy. The analysis of import-export, of the place of origin and
destination of goods and of the sectors involved, is preliminary for the investigation of the
impact of foreign direct investments (FDI) in the province of Bari and Apulia.
To analyse the linkages between FDI, economic growth and sustainability issues, the dataset
is extended to include environmental variables. The methodology used in this study is a panel
data analysis which is able to show not only the relationships between FDI, economic and
environmental variables but also if these relationships are of the same nature across different
provinces and across time (fixed effect model) or if they vary (random effects model). To
study this difference is crucial for policy makers. In the case of a fixed effect model, the
provinces involved in the strategic planning process should try to harmonize their economic,
environmental and trade policies; in the case of a random effect model the adoption of
diversification of policies would be more effective.
1
METROPOLI TERRA DI BARI: AN ECONOMIC OVERVIEW
The added value generated in the Metropolitan Area of Bari1 in 2004 is about 16 Billion Euro
derived mostly from the services (77,5%), and industry (19,7%). Agriculture contribute to the
creation of added value only in a small percentage (2,8)2.
As shown in Figure 1, most of the municipalities whose the service sector performs at its
highest form most of the part of their value added (60-80%).
The 135.000 enterprises registered to the local Chamber of Commerce (CCIA) in the
Metropolitan Area of Bari employ almost 90.000 workers. This very small average size of the
economic actors in the territory could be interpreted as a threat with respect to firms’ capacity
of innovating and internationalizing. The number of enterprises is related to the population
and the relevant sectors are commerce and agriculture (52%) followed by manufacturing,
building and ICT.
Looking at the workers, the most relevant sectors to highlight are industry and commerce
(48%) followed by building, agriculture and ICT. Tradition and Innovation or Tradition
within Innovation would be the expression of the local economy.
Figure 1 Sectoral Added Value
Source: elaboration on CCIA data, 2007.
1
The Metropolitan Area of Bari represents an area formed by the 31 Municipalities of the Province of Bari
(Acquaviva delle Fonti, Adelfia, Bari, Binetto, Bitetto, Bitonto, Bitritto, Capurso, Casamassima, Cassano
delle Murge, Cellamare, Conversano, Corato, Goia del Colle, Giovinazzo, Grumo Appula, Modugno, Mola
di Bari, Molfetta, Noicattaro, Palo del Colle, Polignano a Mare, Rutigliano, Ruvo di Puglia, Sammichele di
Bari, Sannicandro di Bari, Terlizzi, Toritto, Triggiano, Turi, Valenzano) which in October 2006 gathered
together to sign a formal Pact of Intentions while formally committing themselves to the idea of strategically
planning the future of the Bari’s regional socio-economic and socio-environmental system.
2
This is higher than the national average.
Figure 2 and 3 show the composition of firms and labour force across the municipalities of the
Metropolitan area of Bari
Figure 2 Sectoral Number of Firms across the Municipalities in the Metropolitan Area of Bari
Source: elaboration on CCIA data, 2007.
Figure 3 Sectoral Workers across the Municipalities in the Metropolitan Area of Bari
Source: elaboration on CCIA data, 2007.
As shown in Figures 2 and 3 the territory is characterised by:
o The rural activity of the surrounding area. The municipalities of Rutigliano (47%),
Turi (32,3%) and Toritto (23,8%) show the highest rates of workers in agriculture;
o The highest number of workers and local units in the Municipalities of Bari,
Modugno and Bitonto where is located one of the most important industrial parks of
the Adriatic Region (the ASI Consortium);
o The presence of medium-sized enterprises in the Municipalities of Bari, Molfetta and
Valenzano specialised in the ICT sector;
o The small presence of hotels, restaurants and cafes in the territory, except for Bari,
Polignano a Mare and Giovinazzo in which these are present due to tourism activities;
o The importance of the service sector (e.g., commerce, marketing and distribution)
mostly related to wholesale businesses.
In the Metropoli Terra di Bari could be recognised some traditional and emerging local
economic systems (ICE, 2007):
1. Mechanics. This is located in the urban ring of the capital city, showing good export
performance and capacity of innovation;
2. Agro-industry. The food and the flower industries are the most prominent sub-sectors
with good export performance and medium capacity of innovation;
3. Building. This is one of the strongest sector in terms of workers and number of firms,
although its performances are strongly related to the market trends;
4. Tourism. A growing sector with great opportunities to attract capitals;
5. Information and Communication Technologies. It has been particularly vital over the
last decade, with particular reference to creative industries;
6. Energy. This is an interesting growing sector. Its expansion is mainly due to regional
investments, especially in the eco-building sector.
These view do not lack however of some weaknesses. The first is related to the loss of the
entire value chain within the territory. The second is the lack of local and/or international
collaboration, innovation and internationalization, mainly due to the presence of few large
firms and a multitude of small-sized firms. To overcome these problems the Apulia Region
has promoted - by means of the Regional Law 23/2007 - the creation of regional industrial
districts whose process is still in progress.
The rest of the paper is structured as follows: in section 2 the analysis will focus on the
‘openness’ of the local economic system to the trans-border commercial cooperation in order
to investigate the impact of foreign direct investments (FDI) in the province of Bari and an
overview of main environmental quality issues; section 3 illustrates the empirical analysis
across provinces and sectors to test the existence of relationships between environmental
quality, FDI and economic growth; finally, section 4 shows some policy discussion and
concludes.
2
TRANSBORDER COMMERCIAL COOPERATION IN THE METROPOLITAN
AREA OF BARI
The last Italian Economic Census showed a clear improvement of the economic performance
(in terms of workers and added value) of the Adriatic Regions with respect to the other one in
the last ten years.
With respect to the analysis of import-export data the Metropolitan Area of Bari showed in
the last three years a positive balance of payment mainly due to exports of Food, Mechanic
and ‘Other Industries’. For this reason the province of Bari is ranked 29th across Italian
provinces for the value of its exports (3 Billion Euros in 2007). Furthermore, its performance
is better than that of the entire Mezzogiorno’s aras. The balance is positive with respect to EU
15 and Unites States (North America). Albania, Greece and Montenegro represent the most
important commercial partners of the Province in the Adriatic Area even though the main area
of export in the Eastern Europe is Albania.
Central Eastern Europe, Asia and Latina America are potential markets (Report ICE 20062007). Import-Export with Central Eastern Europe and Russia is growing and the linkages
between the Metropolitan Area and the trans-frontier Regions are also supported by the
number of decentralized firms mainly in the leather sector (Osservatorio Banche-Imprese,
2002). This improvement seems to be linked to the better performance of the Adriatic side of
Italy with respect to the Tyrrhenian one and also to the growing ‘commercial openness to the
East Europe’ from the Adriatic regions of Italy (Botta and Capriati, 2003).
The Province of Bari is leader in the Apulia Region for the attraction of net FDI. The
quantitative analysis of FDI in the Apulia Region with an eye to the Metropolitan Area of
Bari in the next sections, involves the study of the relationships between FDI and GDP. The
‘empowerment’ of the Metropolitan Area towards sustainability issues, which are compulsory
for the strategic planning process, would suggest environmental quality also to be affected by
these FDI-GDP relationships.
2.1 Overview of FDI, economic growth and environment linkages
The debate over FDI, economic growth and environment issues is relatively new. Many
studies focus their attention on the cause-effect nexus of stringent environmental policies on
firm’s competitiveness as migration from / attraction to a given location. “Theoretically, a
process of arbitrage (factor price equalisation) drives up emissions in countries with more
abundant environmental resources and lower pollution regulation, to the point where
industries migrate, and drive down emissions in those countries that lose their industries.
Comparative advantages may therefore be seen as pollution haven and industry flight
hypothesis. In the first case, some less developed regions “may attract more high technology
industries by performing a low wages scheme, for example. By offering lax environmental
regulations, less developed countries may provide for industries' cost saving incentives. On
the other hand, the industrial flight hypothesis is mainly concerned with two main aspects:
pollution control costs, new plant expansion and hazard production. As with every other
factor of production, environmental endowments enter in to the firms' production function as
a cost. Firms need to find the optimal allocation of environmental assimilative services for
their capital spending and production costs; therefore, the problem is to what extent
production costs increase when environmental endowment enters in to the production
function to meet with the environmental regulatory system. As a consequence, due to
incremental costs driven by environmental requirements, industries that are able to move their
capital abroad will migrate across national boundaries to countries with low environmental
costs. Empirically, the impact of industry migration due to environmental regulation has been
relatively small: firstly, because environmental costs form a small part of total costs of
production; and secondly, some studies (Low and Yates, 1992; Lucas et al., 1992) show that
industry migration (over the last three decades) has been due to changes in other source of
comparative advantages, whereas the environmental component plays a secondary role.” (De
Lucia, 2007).
The Porter hypothesis on the other hand asserts that over a long-time view of the economic
system environmental protection would eventually encourage firms’ efficiency, innovation
and technological process to become more environmentally friendly. (Porter and van del
Linde, 1995; Xepapadeas and de Zeeuw, 1999; Eskeland and Harrison, 2003). Two main
reasons can be adducted to support this hypothesis. First, heavy pollution can be seen as a
signal to investors that FDI enterprises’ production is inefficient and therefore reduce the
expectations on the multinational liabilities. Second, a replacement of these FDI firms’
production to less efficient domestic technologies, can only lead to a substantial emission
reduction in total pollution in the host area.
A further aspect to be considered is the link between FDI and pollution. Most of the literature
concerned with this topic was born in connection with Environmental Kuznets Curve (EKC)
“because of its similarity to the inverted U-shaped relationship between inequality and income
levels advanced by Simon Kuznets (Kuznets, 1955). The EKC hypothesis purposes an
inverted U-shaped between various indicators of environmental degradation and per capita
income. This implies that one country’s economic growth will redress the environmental
impacts of the early stages of economic development and that growth and technological
progress will lead to improve environmental performances in the developed countries” (De
Lucia, 2002). EKC studies have captured the international community’s attention given the
increasing interest in the economic growth, trade and environmental quality. The debate is
still on-going. “The essence of the EKC is to consider the determinants of environmental
quality in three components: the scale of economic activity, the composition of economic
activity and the income effect on the demand and supply to abate pollution. All else equal, the
scale effect is represented by GDP. So, the higher is the output produced, the higher is the
level of pollution and the higher is the level of resource use and waste generation. The
composition effect of economic activity is related to environmental variable because of
different pollution levels by different sectors of economy. The agriculture sector tends to be
more resource-intensive than the industry, where, on the other hand, this last tends to be more
pollution-intensive. The income effect is explained by the existence of positive pollution
emissions elasticities […] at low level of incomes, which gradually invert to negative
emission elasticities as income rise” (De Lucia, 2002).
FDIs are seen here as depending on in the income effect (one country’s preferences for the
environment) and the scale effect of the host region. However, once foreign capitals enters the
host region, they can certainly have effects on all the EKC’s characteristics. They can
accelerate economic growth (Li et al., 2001; Chen and Demurger, 2002; Liu and Wang, 2003)
or provide technology improvements and therefore to accelerate income effects (Thompson,
2002; Lemoine and Ünal-Kesenci, 2004) that would in turn affect and reinforce decision
making process towards sustainability issues.
2.2 FDI: some descriptive statistics issues for Apulia and the Metropolitan Area of Bari
Figure 4 illustrates the inflow and outflow of firms in the Apulia region over the years 19882000. Although a positive trend can be drawn from both inflow and outflow of firms, a
massive increase of firms outflow rates is observed. While at the end of 1980s until mid
1990s a net inflow of firms prevails, from 1996 to 2000 a net outflow of just about 3 firms
occurs in Apulia region. It can be argued that this trend follow the economic business cycle
during those years. In fact, at the beginning of the 1980s the development of new services in
the informatics or banking sector worldwide for example, provided a rapid increase of new
industries in which the Apulia region benefitted until mid 1990s. As the international business
cycle reached its peak during the 1990s, the negative expectations, and the presence of
structural problems favoured the increase of foreign firms outflow from the Apulian territory.
Figure 4 Inflow and Outflow of Foreign Firms in Apulia
Source: ISTAT
Figure 5 Inflow and Outflow of Foreign Turnover in Apulia
Source: ISTAT
Figure 6 Inflow and Outflow of Workers Employed in Foreign Firms in Apulia
Source: ISTAT
In figure 5, the turnover of foreign firms is showed. It is noticeable how the turnover inflow
remains almost below a Thousand billion Lira until mid 1990s, to jump at a peak of more than
10 Thousand billion Lira (5 billion Euros) in 1998-1999. During those years, in fact, massive
investments of just about 90 Thousand billion Lira (45 billion Euros) in the industrial sectors
took place (ICE, 1999). The turnover outflow on the other hand was of just about 100 billion
Lira (50 million Euros) over the same time span.
Finally, in Figure 6 the inflow and outflow of workers employed in foreign firms in Apulia
region is showed. It is remarkable how the number of people employed has its peak of just
about 18,000 workers during the same years when the turnover inflow is at its highest. From
mid 1990s a conspicuous increase of workers outflow is also present. This will remain stable
of just below 10,000 units, on average, until the year 2000.
The description now turns to briefly analyse the trend in FDI at Apulian and the Metropolitan
Area of Bari. Figure 7 illustrates FDI in Apulia region during a time period 1999-2005.
Figure 7 FDI in Apulia
Source: ICE, Statistics, 1999-2005
It is interesting to notice the increasing trend in foreign inflow and outflow of investments in
the Apulia region. Both reach peak values in 2005, where foreign capital inflow is about
120,000 million Euros against just about 10,000 million Euros of capital outflow. Many
reasons can be adopted to explain such phenomenon. One of the most apparent is the effect of
the European Union Structural Funds system of which Apulia region benefits. This would
favour higher business climate expectation in foreign firms. The same argument can be
claimed for Apulian firms which are well willing to invest their capital in their native Region
rather than in foreign markets. The Apulian capital inflow shows increasing investments
growth from 2002 onwards. Capital inflow reaches its highest value in 2005 of just about
180,000 million Euros.
Figure 8 illustrates capital inflow and outflow in the Metropolitan area of Bari.
Figure 8 FDI in the Metropolitan Area of Bari
Source: ICE, Statistics, 1999-2005
In Figure 8, it can be argued that foreign and Metropolitan capital inflow follow the same
pattern during the time period considered. The Metropolitan capital inflow however presents
higher values in 2001 and 2005, than those in other years. These are around 50,000 and just
about 65,000 million Euros. Foreign capital outflow on the other hand remains almost
constant, reaching a peak of just about 1,000 million Euros in 2002.
Finally, Metropolitan capital outflows are massive at the beginning of the time considered. Its
value is around 64,000 million Euros. From 2000 to 2003 Metropolitan capital outflow is
maintained below 10,000 million Euros of investments; it then increases up to around 2,000
million Euros in 2004 to stabilize again at the values of the previous years in 2005.
2.3 Environmental quality: issues for Apulia and the Metropolitan Area of Bari
In this section a description of air quality issues for Apulia and the Metropolitan region of
Bari are presented. Over the last years western lifestyles have negatively affected the
environment. The global warming or biodiversity threats are few examples of the irrational
and inefficient resource use of anthropogenic activities. Though environmental regulation to
protect the environment is active throughout the globe and at different institutional levels,
much is still needed to do. Italy, as other European countries, has recently adopted various
international regulations to combat global problems such as acid-rain, ozone layer, or global
warming problems. These can be named as the Kyoto Protocol, the Montreal Protocol, the Air
Quality Directives to regulate on long range transboundary flux emissions, or the latest
renewable energy policy adopted by the European Council in March 2007 (the so-called 2020-20 CO2 policy target) to cite a few.
This picture allows urban centres to treat environmental pollution as an emergency problem to
face under various aspects, i.e, health, sanitary etc. In fact, atmospheric pollution is one of
those factors that most affect human health for increasing respiratory diseases over the last
years. Increasing and efficient monitoring at both national and regional level has therefore
taken place. Figure 6 shows air quality monitoring in Apulia. The Apulian Environmental
Protection Agency (ARPA) is monitoring daily emissions of various pollutants, such as SO2,
PM10, NO2, CO, O3 and Benzene. In the latest report on air quality (ARPA, 2008) for the
Metropolitan area of Bari is argued that PM10 concentrations have exceeded the daily limits,
whereas all other pollutants have kept their concentrations below their limit values.
Figure 9 Air Quality Monitoring in Apulia
As it can be shown from Figure 9, monitoring of main air pollutants mainly occurs nearby
urban centres. This is particularly true for all provinces but Foggia, where monitoring stations
are instead situated around the area of Manfredonia. Furthermore, a massive monitoring is
carried out, compared to other provinces, in the Taranto and Brindisi areas. It is in fact
reasonable to believe that in these industrial districts, where pollution levels are at their
highest levels, a ponderous monitoring should be carried out.
The need for increasing monitoring would also favour the adoption of environmental
inventories for which Apulia still lacks. With the project SPIN-ECO, the province of Siena
jointly with the University and its municipality (Provincia di Siena, 2001; Pulselli et. al,
2008), provided the first dynamic analysis on sustainability to evaluate emergy balances, the
absorption capacity of the natural environment, the regional economics and environmental
vulnerability and mitigation strategies through adaptation plans.
The first attempt to construct an Italian emission inventory disaggregated at NUTS 33
(provinces) and sectoral levels has been published in 1995 by the APAT (De Laurentis et al,
1995) for 1990 data. Since then, no study whatsoever updated the CORINAIR emission
inventory4. Figure 7, 8 and 9 below illustrate SO2, NOX and PM10 emissions across economic
activities in the Metropolitan area of Bari in 1990.
These pollutants have generally a both local and long range nature. Although their effects on
human health, for example, can be mostly the same, they can be generated from various
economic sectors. Therefore, the amount of these pollutants differs across sectors.
In Figure 10, it can be argued that more than a quarter of SO2 emissions come from road
traffic whereas almost less than a quarter has its source in the cement industry. Major
contributors for SO2 emissions are also power generators in the agriculture, industry and
tertiary sectors. In Figure 11, the major source for NOX emissions is the road traffic, followed
by pollution emitted in the cement industry. Power generators in the industry and tertiary
sectors are instead considered minor polluting sources for NOX. In Figure 12, the cement
industry is the major polluting source for PM10. Relevance also assumes PM10 emissions
from road traffic. Finally, it can be argued that in the Metropolitan area of Bari, common
sources across these pollutants are road traffic and the cement industry.
3
Nomenclature of Territorial Units for Statistics (EUROSTAT, 1988)
The Apulian Agency for Environmental Protection, University of Lecce and National Council of Research have
signed the adoption of an Environmental Programme Action for Apulia (2005). The Programme cover six main
strategies, namely: the extension of the regional environment monitoring network, the emission inventory, the air
quality plan, the air quality modelling, the data mining for industrial emission sources and the personnel training
for environmental management
4
Figure 10 Sectoral SO2 Emissions in the Metropolitan Area of Bari in 1990
Figure 11 Sectoral NOX Emissions in the Metropolitan Area of Bari in 1990
Figure 12 Sectoral PM10 Emissions in the Metropolitan Area of Bari
3
EMPIRICAL ANALYSIS: FDI AND ENVIROMENTAL QUALITY
INTERACTIONS
In this section an empirical analysis is carried out to study the relationships occurring between
FDI and environmental quality. In particular, the section’s aim is to focus on the effects of
FDI on environment. The methodology carried out is a panel data analysis across the five
provinces of the Apulia region, and across sectors types such as: Agriculture, Energy
Intensive and Bricks Industry, Other Industry, Services and Transports. The time period
considered is a seven year period from 1999 to 2005. SO2 and NOX are the main pollutants
considered in the case study.
3.1 Data sources
The main dataset employed for this study consists of net fluxes of FDI in the five provinces at
sectoral level taken from the Istituto per il Commercio Estero. Sectoral GDP5 for each
province has been downloaded from ISTAT available from website6. Given the lack of an
emission inventory for the Apulia region disaggregated by sectors, estimates of sectoral
emissions have been obtained by projections of the De Laurentis et al (1995) inventory based
on 1990 data. Emissions projections have been obtained considering the relationship existing
between diffuse pollution and GDP, as follows7:
Et  et Yt
(1)
where E t is pollution, et indicates an emission factor for the pollutant under examination and
Yt is the GDP level; t is the time subscript. In other words, a direct relationship occurs
between GDP and the level of pollution. The higher the GDP, the higher pollution levels,
given the state of the technology. Given that emission factors were not available, a
computation of GDP growth rates has been carried out. Emission projections for the years
1999-2005 have therefore been achieved by multiplying GDP growth rates to the original
sectoral emission dataset of the year 1990.
5
Sectoral Value Added has been considered for this study.
www.istat.it. The dataset at province level is available for the years 1999-2003. For the years 2004 and 2005 an
average (computed for the period 1999-2003) value added across relevant sectors has been considered.
7
Perman et al (2006)
6
3.2 Panel Data methodology
“Panel data analysis endows regression analysis with both a spatial and temporal dimension.
The spatial dimension pertains to a set of cross-sectional units of observation” (Yaffe, 2003),
whereas the temporal dimension is characterised by various temporal sources such a as years,
months or daily observations. The bi-dimensionality therefore is characterised by a cross
sections of observations of sectors and provinces and the temporal reference which is the year
time period 1999-2005. The presence of this bi-dimensionality causes unobserved effects that
can affect the dependent variable. These are of various types: time invariant, which are those
that can vary across provinces and sectors and are constant across time; individual variant,
those that can vary across time but are constant across provinces and sectors; and individual
and time invariant, which are those that can vary across provinces, sectors and time.
Panel data models take into account the effects (omitted variables) of these unobserved effects
that remain constant over time. The general model to be estimated is the following:
k
yit   i    ij xijt   it
(2)
j 1
with i  1...N , t  1...T . Furthermore:  i is the individual term that capture the effects of
those variables that are specific for each ith individual and are time invariant; the  j s are the
coefficients to be estimated, the xijt are the regressors and the y ijt is the dependent variable of
interest. The error term is assumed to be independently and identically distributed with zero
mean and  2 .
There are two main approaches in which models like those in equation (2) can be estimated.
Fixed effects (FE) and Random effects (RE) models. With the FE model the  j s (the effect of
the explanatory variables) are the same across provinces, sectors and in each time period. This
restriction implies that similarities in environment-FDI relationship exist across provinces and
sectors over a period of time. This restriction is instead relaxed in the case of the RE model.
3.3 Panel Data results
Table 1 illustrates a descriptive statistics for the dataset considered in this case study. Mean,
Standard Deviation, Minimum and Maximum values are showed for the within (FE), between
groups and for overall. SO2 presents an overall minimum and maximum value of almost 15
thousand tonnes to almost 59,500 thousand tonnes. Whereas NOX emissions have an overall
range of 1-450,000 tonnes. These values’ ranges are reasonable given that emissions are
distributed differently across sectors. Mean values are 2,242 and 12,054 tonnes for SO2 and
NOX, respectively. FDI values are given in the range of -5,883 and 52098 million Euros
across sectors and provinces. Negative values indicate disinvestments. Finally, value added
ranges from almost 273 to just about 53,000 million Euros across sectors and provinces.
Table 1 Descriptive Statistics
Variable
SO2
overall
between
within
Mean
Std. Dev
Min
Max
Observations
2442.42
4896.97
14.99
59485.52
N = 175
794.39
1908.65
4212.734
4841.10
-1751.92
57715.21
NOX
overall
between
within
12054
38371.81
5944.61
37972.77
1.40
8677.70
-13361.31
447543.2
25417.03
434180.2
N = 175
FDI
overall
between
within
1423.58
5732.66
1569.47
5544.35
-5883.8
25.98
-6580.08
52098.98
4276.23
49246.33
N=175
VA
overall
between
within
3219.45
5080.38
719.05
5036.33
272.85
2647.27
-1279.13
52789
4797.48
51210.97
N=175
The relationships to be estimated can be expressed with the following equations:
SO2 it   i  1 FDI1it   2VA2it   it
(3)
NOX it   i  1 FDI1it   2VA2it   it
(4)
Where SO2 and NOX are the pollutants (dependent variables of interest), FDI is the net flux
of foreign direct investment and VA represents the sectoral value added. The predictions for
the models expressed in equations (3) and (4) can be summarised as follows:
SO2it
NOXit
SO2it
NOXit
 0;
 0;
 0;
 0; In other words, the presence of FDI on the
FDI it
FDI it
VAit
VAit
Apulian region across sectors and provinces would favour investments in greener technology.
This would provide to decrease emissions levels; on the other hand, increasing emission
effects is instead captured by the value added, as described in equation (1). Furthermore, to
consider the nature of local pollutants, all variables to be estimated have been transformed in
per-capita terms. Tables 2 and 3 show estimates results for SO2 and NOX.
Table 2 Panel Data Estimates for SO2
Variables name
FDI
VA
Constant
R2
Wald chi2(2)
Number of obs.
Hausman
Coefficient Std.Err.
Z
P>¦z¦
-.057
.045
-1.24
.46
.056
8.22
4.11
1.41
2.92
0.29
0.00
175
Prob>chi2
0.7807
[95% CI]
0.213 -.146
.033
0.000 .353
.574
0.004 1.35
6.88
Table 3 Panel Data Estimates for NOX
Variables name
FDI
VA
Constant
R2
Wald chi2(2)
Number of obs.
Hausman
Coefficient Std.Err.
Z
P>¦z¦
-.069
.399
-1.73
3.50
.494
7.08
6.75
12.34
0.55
0.24
0.00
175
Prob>chi2
0.8451
[95% CI]
0.083 -.147
.03
0.000 2.53
4.46
0.585 -17.45 30.95
Estimates results for both SO2 and NOX panel data regressions indicate that a negative
relationship exists between FDI and emissions level. In particular, a million Euro increase of
net FDI flux in the five sectors across Apulian provinces lead to a decrease of 0.05 thousand
tonnes of SO2 and 0.7 thousand tonnes of NOX. While this result is statistically consistent for
the latter at 95% Confidence Interval, this is not the case for the former. Predictions for the
value added in both cases are assumed to be true given the positive signs of the value added
coefficients. In the case of SO2 panel data analysis a million Euro increase in the value added
would increase SO2 emissions by 0.4 thousand tonnes; whereas NOX emissions would be
instead subject to an increase of 3.5 thousand tonnes. Both value added coefficients are
statistically significant at the 95% Confidence Interval. R2 in both cases is relatively low. In
other words, the independent variables considered in the equations are able to explain 28%
and 23% of the SO2 and NOX panels estimates, respectively. It can be argued that given the
uncertainties linked to the study of environmental quality itself this can be explained by a
number of factors. This is surely beyond the scope of this paper.
A Hausman diagnostic test has been also carried out to test the validity of a RE model against
the FE model. For both panels, the Housman test’s null hypothesis – that the RE model is
consistent – cannot be rejected at 95% Confidence Intervals. Therefore, the sectoral and
provincial individual effects do not appear to be correlated with the regressors (Baum, 2006).
4
A POLICY DISCUSSION ON FDI AND ENVIROMENTAL QUALITY
INTERACTIONS AND CONCLUDING REMARKS
The results obtained in the previous section can be used to formulate optimal policies in term
of planning strategies.
The relationship between FDI and environment is plain: the presence of FDI on the Apulian
region across sectors and provinces would favour investments in greener technology. This
would provide to decrease emissions levels; on the other hand, increasing emission effects is
instead captured by the value added.
To provide increasing of net FDI inflow on the Apulian region, policy makers should
organize a better system for monitoring. This would especially be realistic for urban areas and
industrial settlements. As described in paragraph 2.3, in fact, the increasing monitoring would
also favour the adoption of environmental emission inventories for which Apulia still lacks.
Furthermore, given that the main source of pollution vary across provinces (for example in
the Metropolitan Area of Bari the main polluting source is road traffic, whereas in Taranto or
Manfredonia this is industrial activities), it is advisable that these adopt different planning
methods and strategies which would better adapt to their territorial context. Differences also
exist across economic sectors within the same area. It would be more efficient for the policy
maker to address policies that would take into account FDI effects and sustainability issues
across economic sectors.
For the Metropolitan Area of Bari the strategic planning process play a great role in context of
trade, FDI and environment relationships. Policy decisions should be addressed to consider
their impact on the environment of the strategy planning as a whole (i.e. different actions to
be taken within the economic, transport, and environmental systems). The actual strategic
planning process is already directed towards this direction. The promotion of the railway and
the public transport systems, as well as the support to ‘green’ firms (i.e. firms which adopted
‘green’ systems of productions and new firms in the ‘green’ sectors) are examples of policies
converging to the reduction of pollution and attraction and /or creation of new investments8.
8
See www.ba2015.org
5
Bibliography
Botta F., Capriati M. (a cura di) (2003) Transizione nei Balcani e reti transadriatiche. Il
valore della prossimità, Cacucci, Bari.
Baum C. F., (2006) An introduction to modern econometrics using STATA, STATA Press.
Chen, Y., Demurger, S. (2002) Croissance de la productivité dans l'industrie manufacturière
chinoise: Le rôle de l'investissement direct étranger. Economie Internationale 92, 131–164
De Laurentis R., Gaudioso, D., Liburdi., R. (1995) CORINAIR PROJECT, Air Pollutant
Emission Inventory in Italy for the Year 1990, Final Report, doc. ENEA.
De Lucia C., Leonida L. (2002) The Evidence of the Environmental-Economic Transition
Hypothesis: a Semi-Parametric Approach, Planum European Journal of Planning –
Urbanistica, n.117.
De Lucia, C., (2007) Integrating trade and transboundary pollution in an enlarged Europe: A
computable general equilibrium model, PhD Thesis, University of York, UK
EUROSTAT, (1988), Nomenclature of Territorial Units for Statistics
Eskeland, G.S., Harrison, A.E. (2003) Moving to greener pasture? Multinationals and the
pollution haven hypothesis. Journal of Development Economics 70 (1), 1–23.
Istituto per il Commercio Estero, L’Italia nell’economia internazionale, Rapporto 20062007.
Istituto per il Commercio Estero (1999) Statistiche.
ISTAT, Statistiche, 1988-2000.
Lemoine, F., Ünal-Kesenci, D. (2004) Assembly trade and technology transfer: the case of
China. World Development 32 (5), 829–850.
Li, X., Liu, X., Parker, D., (2001) Foreign direct investment and productivity spillover in the
Chinese manufacturing sector. Economic Systems 25, 305–321.
Liu, X., Wang, C. (2003) Does foreign direct investment facilitate technological progress?
Evidence from Chinese industries. Research Policy 32, 945–953.
Low, P. and Yates, A. (1992) Do dirty industry migrate? in Low, P., editor, International
Trade and the Environment. World Bank, Washington, D.C.
Lucas, R., Wheeler, D., and Hettige, H. (1992) Economic development, environmental
regulation and the international migration of toxic industrial pollution: 1960-1988, in Low,
P., editor, International Trade and the Environment. World Bank, Washington, D.C.
Osservatorio Banche Imprese (2002) Il sistema produttivo in Puglia. Il prodotto Lordo,
l’Occupazione e Settori. Rapporto Annuale 2002.
Provincia di Siena, (2001) Progetto SPIN-ECO.
Perman R., Ma Y., McGilvray J., Common M. (2003) Natural resources and environmental
economics, Longman, Pearson Education.
Porter, M.E., van der Linde, C. (1995) Toward a new conception of the environment–
competitiveness relationship. Journal of Economic Perspective 9, 97–118.
Pulselli F.M., Ciampalini F., Leipert C., Tiezzi, E. (2008) Integrating Methods for the
Environmental Sustainability: The SPIn-Eco Project in the Province of Siena (Italy),
Journal of Environmental Management, 86(2), 332-341.
Thompson, E.R. (2002) Clustering the foreign direct investment and enhanced technology
transfer: evidence from Hong Kong garment firms in China. World Development 30 (5),
873–889.
Viesti G., (2001) I distretti nell’economia meridionale, Rassegna Economica, N. 1, gennaiogiugno.
Xepapadeas, A., de Zeeuw, A. (1999) Environmental policy and competitiveness: the porter
hypothesis and the composition of capital”. Journal of Environmental Economics and
Management 37, 165–182.
Yaffe R. (2003) A primer for panel data analysis, New York University.

Download Report