Journal of Policy Modeling
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Economic Convergence of Italian Regions: The Role of Organized Crime and of Public Expenditures, 1960-1993[1]

Giuseppe Tullio*,[2] and Stefano Quarella[3]

University of Brescia (June 1998)

*Current address: Università degli Studi di Brescia, Facoltà di Economia, Via San Faustino 74/B, 25122 Brescia, Italy.


Introduction

From 1960, the first year accurate data are available, to 1996 the differences in real GDP per capita between the regions of the South md of the Center-North have been reduced considerably. Real GDP per capita of the South increased as a ratio of North-Central GDP from 47% in 1960 to 58% in 1996. However, the differences still persisting Lre large, despite 'massive public investments and current transfers iom the Center-North and a very deliberate policy of all Italian Governments of the period to reduce these differences. Worst still, since 1984 the convergence has come to an end: GDP per capita of the South fell from 62% of Central-Northem GDP in 1984 to 58% in 1996. Unemployment in the South remains above 20%, while the Center-North is very close to full employment.

It should therefore not be a surprise that the debate on what during the last century was labelled "the Southern question" has revived again in the last years both from a political and an economic point of view. After the decision of May 2nd 1998 to accept Italy into the European Monetary Union the focus of the Prodi government has shifted from policies aimed at achieving entry into the Monetary Union to policies aimed at increasing public investment in the South to fight unemployment.

Increasing public investment in order to fight unemployment is very sensible policy in a "normal" socio-political environment. It may achieve nothing and even be counterproductive in an environment in which public investments are decided on the basis of political-electoral motivations rather than on the basis of objective economic criteria, in which local administrators are corrupt, in which the informal connections between organized crime and local authorities and sometimes even the central authorities are strong, and in which the property rights are not guaranteed because of the activities of organized crime in the presence of a judicial system which is always extremely slow and sometimes not sufficiently "distant" from organized crime and corrupt officials.

We do not mean to say that all of Southern Italy presents these features, although the reluctance of Northern Italian and foreign capital to move there despite high subsidies, lower labour costs and fiscal incentives seems to suggest that there are significant problems of the type mentioned above[4]. The Sicilian judge Giovanni Falcone killed by Mafia in 1992 wrote in his book 'Cose di Cosa Nostra" that he thought Mafia was getting about 20% of his total income from public investment. In addition there may well be a link, so at least some newspapers suggest, between the large number of killings among different criminal organizations in Naples in the first half of 1998 and the fact that public money is about to arrive to the city.

If the South of Italy is a sick socio-political environment, as we are firmly convinced[5], the right economic policies to get again the convergence process of the South in motion consist mainly in fighting corruption more seriously than has been done so far, increasing enormously the resources of the judiciary and the police, give more power to the judges and police officials who are known to be honest and remove all the others, make sure that all pending civil and criminal lawsuits are resolved rapidly, make careers of judges and policemen dependent on honesty and professional abilities rather than on political affiliations or other dubious affiliations, pass special laws as requested by honest judges in the South[6], take measures to increase the confidence of honest citizens in the police and in the judicial system so that they will report crimes with less fear. Public investments should wait until the environment has been sufficiently "cleansed". On the other hand if our judgement is wrong, then increasing immediately public investment in the South is the right policy.

The answer to the question concerning the right policy to fight unemployment in the South and to reverse the economic divergence of the South recorded since 1984 ultimately hinges on how important organized crime and corruption really are and on what has been their role in stopping the process of convergence of the South. This paper intends to analyze by means of regression analysis the factors which influenced the convergence/divergence of Italian regions since 1960 with a particular emphasis on the role of regional crime rates and regional public expenditures. As to the latter we shall consider both total expenditures and their split into investment and current consumption.

The above mentioned variables show a significant difference in behaviour both across regions (in particular between the South and the Center-North) and through time. For instance Figure 1 shows the number of voluntary homicides as a fraction of the resident population in the Center-North and in the South. The systematic difference in the crime rates between the two main areas of the country is impressive. Even more so is the sharp increase in the Southern crime rates since the mid 1970s and then again in the second half of the 1980s and early 1990s.

Several empirical studies already exist on convergence of Italian regions[7]. Many do not consider crime as an explanatory variable and among the few which do no one finds it to be significant. However, existing studies use the number of crimes against property and the economy or of crimes in general instead of voluntary homicides. We feel that in the South there is a large underreporting of crimes against property and of crimes in general because of the obvious dangers involved in reporting them to the authorities. The number of voluntary homicides, although it is certainly still not a good measure of the strength of organized crime, is instead less subject to underreporting except when bodies are dissolved in acid or hidden in cement walls, both of which have occurred.

Fig. 1: Italy: voluntary homicides in the South and in the Center-North for every 100,000 inhabitants, 1960-1995.
Figure 1

It is important to mention that in Italy there is virtually no killing going on in connection with small robberies in the streets of big cities of the type which is common in US cities or in Rio de Janeiro, so that it is safe to assume that regional voluntary homicides are truly exogenous with respect to regional GDP growth. They are probably much less exogenous with respect to public spending for the reason mentioned above.

Concerning public expenditures the hypothesis has been advanced that they may have had a beneficial effect on growth and Convergence of Southern regions in the 1960s, when the marginal productivity of public investments was very high, current expenditures, till moderate and corruption much lower, while in the 1980S the effect may have become negative as a result of a much lower productivity of public investment, high corruption, a deeper link between politics and "business", systematic use of public money for personal enrichment or to finance lavish expenditures by political parties in power and increasing distortions in the labour market caused by current expenditures (Micossi and Tullio, 1992a, 1992b). In the 1980s a widespread system of false invalidity pensions and a generous pension system (not linked to actual contributions), coupled with strong intergenerational solidarity within the Italian family caused a halt in he emigration from the South despite increasing unemployment especially among the young.

It cannot be excluded that in the last two decades or so many public investment projects were decided with the main objective of maximizing bribes and votes for politicians and profits for contracting firms without any regard to economic rationality[8] and as a result an increasing fraction of what in the government and in the accounts of state industries and agencies is recorded as "investment" is really something else, namely bribes[9] and sheer waste of money. In this study we intend to test explicitly the hypothesis that the effect of public expenditures on convergence changed through time and across regions. Only one of the existing studies on convergence has tried to do so. Piras (1992) finds a positive and significant relationship between GDP growth and the variable "public works" for the period 196'D-75. The variable becomes insignificant for the period 1963-84. Finally with respect to previous studies on convergence of Italian regions we extend the sample period to the last year for which all the data were available at the time the study was started.

Our proxy for organized crime turns out to be of utmost significance and goes a long way in explaining why divergence set in after 1984. We show that the very high significance of our proxy for organized crime in our regressions for the whole sample period is explained mainly by the effect it exerted in the South after 1980. The change in sign of public expenditures through time is also confirmed by the data as the non-significant effect in the regressions for the whole sample period hides a very positive and significant effect on growth until the mid 1970s, a much weaker positive effect in the second half on the 1970s and a neutral or negative effect in the 1980s and 1990s with significant differences among the major areas of the country. We conclude that in the South organized crime and the waste of public money have interfered so heavily in the mechanism of allocation of resources and on the factors affecting growth that after 1980 their negative influence has even become visible on (macro-economic) growth rates of regional GDP per capita.

The paper is structured as follows. Section I presents a brief historical overview since 1960 of the various phases of the convergence process of Southern GDP per capita towards the level of the Center-North. We shall distinguish two periods of rapid convergence (1960-71 and 1978-84) and two periods during which the two areas of the country diverged (1971-78 and 1984-96). According to preliminary data the phase of divergence continued in 1997. Section 2 presents the regression results. We have divided the period 1960-93 into 7 5-year periods, except for the last one which has only four, and we use 5-year averages of annual data. Since Italy has 20 regions we have 140 observations for each regression (7 times 20) and usually well over 120 degrees of freedom. The use of 5-year averages allows us to study better how the impact of the explanatory variables (in particular organized crime and public expenditures) on convergence changed through time and across the three main groups of regions (South, Center, North). None of these three groups is perfectly homogeneous and thus by comparing the aggregate for the South with he aggregate for the Center-North as we do in Section 1 and Figure 1 for convenience of exposition we hide important information. In Section 3 we analyse the effect of the crime rate and of public expenditures on the ratio of employment to the resident population. Section 4 summarises the main results and draws conclusions for economic policy.

1. A brief historical overview of convergence of the South towards he Center-North, 1960-1996.

Figure 2 shows the behaviour of Southern GDP per capita in relation to the one in the Center-North from 1960 to 1996. For the whole of the sample period there was a significant degree of convergence as GDP per capita in the South increased from 47.3% of Central-Northern GDP tin 1960 to 58.2% in 1996.

Fig. 2: Real GDP per capita in the South in percentage of GDP per capita in the Center-North (1980 prices).
Figure 2

However, the convergence process did not proceed smoothly. A period of very rapid convergence between 1960 and 1971 was followed by a period of divergence in the period 1971-78. Convergence resumed at a more moderate pace in the period 1978-84 which was followed again by divergence in the period 1984-96 during which Southern GDP fell from 62 to 58.2% of Central-Northern GDP.

The 1960-71 period: rapid convergence

Most of the convergence recorded in the period 1960-96 occurred from 1960 to 197 1. During this brief 12 year period Southern GDP per capita increased from 47.3% to 61.1% of Central-Northern GDP (a reduction of 13.8 percentage points in the gap; more than 1% per year). The reasons of this strong convergence are first the very favourable behaviour of the whole Italian economy which grew in the period at a rate close to 5% per year[10] helped by increased integration with the European economy, a stable financial environment and falling real prices of raw materials. Second the high migration from the South strongly contributed to the increase in productivity and GDP per capita in the area. Third public expenditures were mostly limited at least in the first half of the 1960s to productive investment in infrastructures the main objective of which was to create the conditions for growth rather than to intervene directly in the production process. On the other hand the investments of state owned industries made in the area during the period were still mostly motivated by economic rationality rather than other objectives and must therefore have exerted a positive impact on Southern GDP per capita.

The 1971-78 period: sharp interruption of convergence

From 1971 to 1978 Southern GDP per capita fell from 61.1% of Central-Northern GDP to 57.4% or 3.7 percentage points. The Italian economy was weakened during this period by the world recession and the aftermath of the Bretton Woods crisis of 1971, leading to the August devaluation of the US dollar, the more militant attitude of labour unions since 1969, the convergence of wages nationwide, the oil crisis of 1973-74 and increased uncertainty. The lira was repeatedly devalued in 1973 and then again in 1976. Inflation accelerated and became very variable. Government expenditures accelerated in a disorderly fashion in an attempt to fight unemployment originating in the excessive increase in real wages and in the increase in the real price of oil. The level of remittances of wage income on the part of Southern Italian workers abroad was held back by expectations of devaluation of the lira and by negative real interest in Italy for most of the period.

In sum, when things turned for the worse, the weakest Italian regions were affected more heavily than the rest of the country and the economic policy of the government which started to be characterized by disorderly deficit spending certainly did not contribute to the long run solution of the economic problems of the South. Public industries which in the previous period had started to direct a large share of their Investments to the South suffered severely from the increase in labour costs and the first oil crisis. In addition Italian medium and small enterprises were the fastest to adapt to the new environment and the Fact that they were predominantly located in the Center-North left the South in a weak position. Rather than stimulating the development of private small and medium sized enterprises in the South and creating the legal and social environment needed to attract foreign direct Investment, the government preferred to fight unemployment by sharply increasing public employment and by making huge Investments in very capital intensive cement, steel and chemical mega-factories in the hope, so at least the story goes, that these huge factories would stimulate the birth of a sufficient number of small enterprises around them. Our preferred explanation for the choice of mega-industrial projects is instead that bribes and electoral considerations were already becoming important in the period. Far from creating the environment necessary to stimulate direct investment from abroad and from the Center-North in small and medium enterprises these policies of building cathedrals in the desert reduced the role of the market in the South, increased the corruption and arrogance of the local political class and made organised crime stronger, an outcome which may have been quite welcome in the eyes of the then ruling political class given that at the time of elections hundreds of thousands of votes could be mobilised by organized crime[11].

The 1978-84 period: resumption of convergence

After the foreign exchange crisis of 1976 the lira was stabilized, the monetary financing of budget deficits was highly reduced, the Trasury bill market was developed and Italy recorded large current account surpluses in 1978-81. In March 1979 the lira joined the European Monetary System (EMS), albeit with a larger band (+/-6%) than other members (+/-2.25%). In July 1981 the bank of Italy was relieved from the obligation to buy trasury bills and bonds at primary auctions. Despite the second oil shock of 1979-80 the above institutional changes and especially the joining of the EMS significantly reduced uncertainty.

During this period Southern GDP increased from 57.4% of the level in the Center-North to 62.3 % (a postwar peak) or 4.8 percentage points. When in Section 2 we use regional 5-year averages rather than annual data aggregated for macro-regions (like in Figs. I and 2) we find that in the first half of the 1980s government expenditures and especially the crime rate in the South were already affecting convergence negatively. Thus the continuation of convergence in the first half of the 1980s may be the result of a sharp fall in the crime rate in the South during the period (see Fig. 1) coupled with a more favourable national macroeconomic environment characterized by reduced uncertainty with respect to the 1971-77 period.

The 1984-96 period: the South looses ground again

Between 1984 and 1996 Southern GDP per capita fell from 62.3% to 58.2% of Central-Northern GDP per capita or 4.1 percentage points. Most of the deterioration in the South occured between 1991 and 1996 when the gap increases by 3.7 percentage points in the presence of a virtual stop of growth in the South and very moderate growth in the Center-North. In 1996 the gap falls back to the level of sixteen years earlier (1979) or 58.2%.

The causes of the 1991-96 developments are two. In the South organized crime reached a strength never seen before and after the large September 1992 devaluation of the lira and its exit from the EMS the Center-North compensated the fall in domestic demand with a strong increase in exports. The very significant increase in voluntary homicide in the South in the period 1990-93 (see Fig. 1) went hand in hand with a remarkable increase in government consumption expenditures there (see the comments to Fig. 4).

In many ways the South of Italy can be considered as one of the Few remaining truly centralized economies of the world (together with Cuba and North Korea) as the public sector dominates the economy to in incredible extent. Micossi and Tullio (1992a, 1992b) calculate that in 1988 the share of government expenditures to GDP in the South amounted to 76%. In addition public enterprises still play an important role and their outlays are not fully included in the above figures. If one considers that agriculture, which is still very important in the South, is heavily subsidized by Brussels (but the money is actually distributed by Italian agencies) and that virtually no economic activity can be started without official authorizations[12], it becomes clear that local political or criminal groups (or both together) fully direct the allocation of economic resources in the South. Even the large investment of Fiat in Melfi decided in the early 1990s cannot be labelled as truly "private" as out of an investment of 5000 billion Italian lire (about 4 billion dollars) Fiat received a generous grant (not a loan!) of 3000 billion lire. In addition not enough has been done yet to re-establish law and order at least to the level of the early 1960s and speed up the solution of pending legal cases.

2. Effects of Organized Crime and Public Expenditure on Convergence of Italian regions: empirical evidence from 1960 to 1993

2.1. Absolute or unconditional convergence

According to the neoclassical theory of economic growth if two countries or regions are characterized by the same structural parameters (production functions) but different initial levels of income per capita they will tend in the very long run towards the same level of income per capita (the same steady state)[13]. The region with a lower initial income per capita will grow faster than the richer region and its income per capita will converge towards that of the richer region owing to the neoclassical hypothesis of declining marginal productivity of capital (along the same production function for the two regions). In this case one talks of absolute or unconditional convergence. The absolute convergence is measured in the empirical literature by the b-indicator or by the s-indicator. An estimate of the b-indicator is obtained by running the following regression:

(1/T) . ln (yi,t/yi,t-T) = a + b . ln yi,t-T + ui,t    (1)

where y is GDP per capita, In stands for the natural logarithm, a reflects its equilibrium (steady state) level, b measures the effect of the initial level of GDP per capita on its average growth rate from time t-T to time t, u is a stochastic variable, i represents the i-th region, t the time index and T the time interval considered (in our case 1960 to 1994). Thus the dependent variable is the average geometric growth rate of real GDP per capita of each region from period t-T to period t and b is an approximation of the b-indicator with the sign reversed. It measures absolute convergence or the speed of adjustment of actual GDP per capita to its steady state level[14].

In particular there is absolute convergence when b is negative (b positive). In such a case the regions which are poorer in the initial period tend to grow faster in the succeeding periods. The larger is b in absolute value the shorter is the period needed for the poorer regions to "catch-up" with richer ones.

Table 1 presents OLS estimates of equation (1). It includes estimates of the equation for the whole sample periods 1960-1993 and 1960-1994 and for all the subperiods analysed in the historical overview of Section 1.

The estimate of b for the period 1960-93 indicates a statistically significant (at the 1% level) but rather slow convergence of 1.4 per cent per year. If we add 1994 to the sample period the convergence falls to 1.3 per cent per year. The first number implies that the gap between the poor and the rich regions tended to be closed at the rate of about 1.4 percentage points per year. Remembering that in 1960 the initial gap of the Southern GDP per capita with respect to Central- Northern GDP was 52.7% this estimate implies that it would take 54 years for the gap to be closed[15].

However, as we have already seen in Section 1 the convergence process was not stable through time. A period of strong absolute convergence from 1960 to 1971 at a rate of 3.2% per year (statistically significant at the 1% level) was followed during the 1971-78 subperiod by a trivial and statistically insignificant convergence of 0.5% per year. Then from 1978 to 1984 convergence becomes again high and statistically significant at the 1% confidence level (2.9%). Finally in the subperiod 1984-94 we observe divergence at a rate of 0.73% per year.

Comparing the last two rows of Table 1, it is interesting to observe how the addition of only one year (1994) changes the degree of divergence of the last subperiod from 0.46% to 0.73% per year and makes the coefficient significantly different from zero.

The finding of a small albeit non significant convergence in the period 1971-78 is in apparent contradiction with the divergence observed in Fig. 2. However, the contradiction is only apparent as Fig. 2 shows average GDP per capita of the South compared with average CIDP per capita of the Center-North, while the regressions are based on 20 regional observations. The continuation of convergence of poorer Central and Northern regions towards their richer neighbours has outweighed in the regressions the divergence which set in between the Southern regions and the rest of the country. In effect several regions of the Center-North like the North Eastern regions (Veneto, Friuli, Trentino), Emilia-Romanga, Marche and Abruzzi, characterized by medium-small industrial firms were much more able than the traditional industrial regions like Piemonte, Liguria and Lombardy to adapt the wage shocks, militant unions and the two oil shocks. The same considerations could explain the fact that in Table 1 the divergence observed from 1984 to 1993 is not statistically significant, while it seems substantial in Fig. 2.

Table 2 shows for each year the s-convergence which is the dispersion of the natural logarithms of real GDP per capita of the regions. It is measured by the standard deviation of the natural logarithms of real GDP per capita of each region. If the s-indicator falls there is absolute convergence.

The s-indicator falls significantly and without interruption from 1960 to 1971. It oscillates until 1978 at a higher level than in 1971, then it starts to fall again from 1978 to 1984 when it reaches the minimum of the whole sample period. Thus the behaviour of the s-indicator fully confirms the conclusions based on the P-indicator.

2.2. Conditional convergence: the role of organized crime, government expenditures and education

If we add to the initial level of GDP per capita, the only independent variable contained in equation (1), additional explanatory variables like the regional crime rate, regional government expenditures, and a proxy for education, the estimate of the coefficient b is called conditional b-convergence. The inclusion of additional explanatory variables takes into account the fact that the various regions may be structurally different (i.e. have different steady states) and that regional economic policy, organized crime, education and micro or macroeconomic uncertainty may speed up or interfere with the natural convergence process determined by the declining marginal productivity of capital.

The additional explanatory variables we shall consider are:

  1. crim = the regional crime rate, defined as the number of voluntary homicides per 100,000 inhabitants, as a proxy for the strength of organized crime.
  2. ip = regional public investment in construction and public works, in constant 1980 lire and in proportion to the population resident in the region. This variable excludes subsidies to private investment and investment by public enterprises; it is thus an imperfect measure of the investment activities of the government in each region.
  3. cp = regional public consumption in constant 1980 lire and in proportion to the resident population. The data used for public consumption and investment are national accounts data and not data from the budget. Hence transfers to households, the most dynamic part of Italian government expenditures in the last decades are excluded. Had we been in possession of more comprehensive data, our econometric results may have been better.
  4. sp = ip+cp = the sum of public investment and consumption as defined above.
  5. e = number of students enrolled in secondary schools in percent of resident population.

For a more detailed description of the data used and their sources see Appendix 1. The coefficient of the education variable never turned out to be significantly different from zero, thus confirming what had been found by other studies on Italian convergence, and as a result we dropped it in the initial stages of our research. Another variable which was never significant in other studies was "net migration". After some initial attempts on our part which confirmed that it is not significant, we decided to drop also this variable.

National accounts data for the Southern regions are Systematically biased by the fact that government services are estimated at factor costs and that the government has sharply increased public employment after 1970 as unemployment was going up there. For instance Paci (1997) shows that in the 1980s virtually all the growth recorded in Sardinia (a Southern region) was due to the growth of the "non-salable services" sector which virtually coincides with the government sector. We therefore performed all the tests presented below also with the GDP per capita redefined to exclude "non-salable services" as we were expecting to find stronger results than with official GDP per capita growth. However, the results did not differ significantly and we present therefore in this paper only the regressions with the official definition of GDP growth[16].

A few comments concerning our proxy for organized crime are in order. First in Italy there is virtually no killing going on in connection with small robberies in the inner cities of the type which is common in US cities or in Rio de Janeiro, so that it is safe to assume that the excess of regional voluntary homicides per capita of the South with respect to Center-North is closely related to the interests and activities of organized crime. The latter systematically kills all people who greatly disturb its activities: judges, entrepreneurs, policemen, members of rival bands, former affiliates who know too much or collaborate with judges. Concerning the latter, if organized crime does not succeed in killing them they sometimes systematically kill close relatives, including children. Also politicians who were no longer able to guarantee to criminals protection from condemnation in courts have been killed[17].

Second, as the voluntary homicides of organized crime are well pondered joint decisions based on economic-political considerations, they can safely be assumed to be truly exogenous with respect to economic growth unlike homicides in inner cities in the US which must be very sensitive to the business cycle. Third contrary to other proxies for crime used in other studies on Italy which have been found not to be significant (crimes against property or crimes in general), our proxy is much less subject to the risk-of underreporting for reasons which hardly need an explanation. Basically as the government is not capable of reacting in real time (court cases take decades to be solved[18]) and as organized crime has the virtual monopoly of the use of violence, people are afraid of reporting illegal acts to the police. Worse than that, when it comes to gathering information from public offices about potentially illegal activities by criminals in order to formulate clearly the accusations against them to the police, some officials in some regional branches in the South seem to know very well which information they have to conceal and from whom[19].

At a more theorectical level it is worth spending a few words on why organized crime and corruption should affect economic growth negatively. They do not create wealth, they only redistribute it and by doing so they discourage productive economic activities much like taxation[20]. They reduce the efficiency of each lira spent on public investment because of the percentage cashed by organized crime and corrupt officials and/or entrepreneurs and because they distort choices towards bribe-maximizing at the expense of truly productive investments[21]. In addition they distort occupational choices in favour of activities of redistribution and rent-seeking rather than of true creation of wealth. Organized crime is a threat to property rights and it discourages therefore the accumulation of capital. True entrepreneurs existing in the territory controlled by organized crime have the tendency to leave; worst still, potential investors from other areas of the country or of the world have no incentive to invest in the area[22]. If in addition the presence of organized crime is linked, like in many parts of Southern Italy, with an inefficient and slow judicial system and a non-transparent public administration the officials of which are also often colluded with organized crime and corrupt, it is easy to understand why the conditions for convergence are not present. Also the efficiency and equity of the tax system is influenced negatively by corruption[23].

Table 3 shows the estimates of equation (1) in which the explanatory variables mentioned above are added to the natural logarithm of the initial GDP per capita (lnyin). The sample period is 1960-93; 1993 is the last year for which all explanatory variables are available. In order to obtain statistically more robust results and to be able to study better the changes through time of the coefficients of the crime rate and of government expenditures we divided the sample period into 7 subperiods of 5 years each[24] and calculated 5-year averages of all the additional explanatory variables. Exceptions are the initial level of income, which refers to the initial year of the 5-year period, and the dependent variable which is a 5-year average geometric growth rate. We thus run regressions with 140 observations (7 periods times 20 regions) which guarantee robust results. The procedure used also has the advantage that excessive yearly volatility especially in the crime rate is not allowed to bias the estimates.

We observe first that the coefficient of initial real GDP per capita is negative and significantly different from zero at the 1% level. Comparing with the estimate of absolute b-convergence of Table I the coefficient almost doubles in absolute value from 1.4% to 2.1-2.5%. This implies that the influence on convergence of the additional explanatory variables included in Table 3 has been significantly negative i.e. that organized crime and government expenditures have significantly reduced convergence for the average of the sample period below what it would have been otherwise. Second the crime rate has a coefficient which is significantly different from zero at the 1% level. Its effect on convergence has been negative. This finding is in sharp contrast with what found by other studies on Italy. Third total government expenditures and investment are not significant and government consumption has a negative influence on convergence but only at a confidence level of 10%. We shall see below that the crime rate and government expenditures are not independent from each other: in the period 1980-93 the crime rate in the South seems to be particularly influenced in a positive way by public consumption, slightly less by public investment.

In the regressions of Table 3 all coefficients are constrained to be the same through time and across regions. This is a very heroic assumption. In the remaining of this section we shall remove this assumption and by doing so learn a lot about where and when the crime rate and government expenditures had a negative effect on convergence. First we test whether the coefficients of the additional exogenous variables changed through time. The periods eventually chosen are three: 1960-74, 1975-79 and 1980-9.). They were decided following Micossi and Tullio (1992a, 1992b) on the basis of their that regional economic policies were characterized by some efficacy in the 1960s, by a neutral transition period in the 1970s and by distictly negative effects since the early 1980s associated with the degeneration of the Italian political system.

The main doubt was where to place the first half of the 1970s and we let the data tell us by placing this period first with the second half of the 1970s and later with the 1960s. Three dummy variables were constructed dl which assumes the value of I in the first three periods (1960-74) and zero otherwise, the dummy d2 which assumes the value of I only in the period 1975-79 and the dummy d3 which is equal to one for the last three periods (1980-93) and zero otherwise. Then we constructed the variables spdl, spd2 and spd3 as the the product of sp and the temporal dummies. The variables ip, cp and crim were split in the same way. The results are presented in Table 4.

As before the initial level of income is statistically significant with the right sip at the 1% confidence level, suggesting the presence of conditional convergence. The crime rate is statistically significant at the 1% confidence level only in the third period during which the Italian political system had degenerated (1980-93). Without the variable government expenditures the statistical significance of the coefficient of the crime rate in the period 1980-93 increases sharply and it is noteworthy that the Adjusted R2 is hardly influenced by the suppression of the former (cfr. regr. 4 with regr. 1-3). This may be an indication that these two variables were closely linked to each other in this period. If our views about the Italian political system and about the Southern society since 1980 is correct, the crime rate was influenced positively by government expenditures. The coefficient of government expenditures is positive and statistically significant at the I% confidence level in the first period (1960-74), it is still positive but less significant in the second period (at the 2.5% confidence level) and becomes insignificantly different from zero in the third. The same holds for its components ip and cp. This fully confirms the views expressed by Micossi and Tullio (1992a, 1992b) and others about the enormous waste of public resources in the South after 1980. Of the two components the variable cp seems to maintain a slightly more significant and positive role than ip.

From a temporal decomposition of the explanatory variables we move to a geographical decomposition by the three major areas of the country: the North, the Center and the South. In order to verify whether the coefficients of the crime wave and government expenditures are significantly different across macro-regions, we define three dummy variables: dn, dc and dm. The first assumes the value of one for each region of the North and the value of zero otherwise[25], dc assumes the value of one for each region of the Center[26] and dm for each region of the South[27]. Then for each exogenous variable we define three new variables; for instance crim is split into crimdn, crimdc, crimdm where crimdn is simply the product of crim and dn. A similar procedure is used for sp, ip and cp. The results are reported in Table 5.

The conditional b-convergence ranges from 2.6 to 2.9% per year and is significantly higher in absolute value than the unconditional b-convergence estimated in Table 1. The coefficient of the crime rate is not significantly different from zero in the North and in the Center. It is instead different from zero at the 1% percent confidence level and with the expected coefficient in the South. Government expenditures are nowhere significant.

The evidence from Tables 4 and 5 seems to suggest that organized crime and corruption became a drag on growth mainly in the period 1980-93 and mainly in the South and that government expenditures may have stimulated growth only in the first period (1960-74) and somewhat less in the second (1975-79).

In order to find out more we decided to decompose the exogenous variables jointly by major period and by macro-regions. We define the appropriate dummies and then split each exogenous variable into 9 variables. The results are reported in Table 6. For instance. the variable crimdldn is the product of crim and the dummies dl and dn and represents the crime rate in the North during the first period (1960-74). Since we have 140 observations and since the exogenous variables are maximum two in each regression we are still left with at least 120 degrees of freedom.

There is again strong multicollinearity between the government expenditures variables and the crime rate, especially between total government expenditures and crim, so we present regressions also without the crime rate. If we introduce government spending and the crime rate simultaneously no variable is significant. The crime rate is a factor significantly retarding economic growth in the South in the period 1980-93 (see the coefficient of crimd3dm). Government expenditures has significantly contributed to the convergence in the first and second period in the North and in the Center with both consumption and investment expenditures contributing to this outcome. In the South instead only government consumption expenditures contributed in the first period to convergence, investment never did. Thus in the South public investment expenditures have never significantly contributed to convergence, despite the enormous and increasing sums spent there. In the third period government expenditures, and investment in particular, stop contributing positively to convergence in the whole country.

One criticism to the regressions presented above could be that sp, cp and ip may be partly endogenous as a weak business cycle may stimulate the government to act anticyclically. However, first the potential bias resulting from this endogeneity would be negative, i.e. it would fond to reduce the absolute value of the coefficients in Tables 4-5. Thus as we generally find positive or zero coefficients, if we were to remove the alleged bias, our results would only be reinforced. Second, assuming the intention of the government to act anticyclically, the lags between an economic downturn and the actual increase in public investment are extremely long especially in Southern Italy where public administrations are more inefficient. Third public investment tends to be distributed across the country more on he basis of the location of the electoral constituency of the most powerful political figures in Rome and of the occurrence of natural events like earthquakes than on the basis of economic criteria anticyclical policy, economic return on the investment). Fourth, the geographical distribution of public consumption must be rather independent of the cycle, especially in the South, as unemployment benefits are not very developed in Italy: they favour only employees of large firms which are mainly concentrated in the North. Fifth, the use of 5-year averages strongly reduces this possible bias as business cycles are usually not longer than 5 years.

Be that as it may, we have looked at the relationship between 5-year average growth rates and five year averages of ip and cp in all macroregions (the same data used for the regressions). For the whole period there is a significant and negative correlation between 5-year regional growth, ip and cp. This negative correlation is more significant with cp than with ip. However, in the South in the 1980-93 period the correlation between regional growth and ip disappears.

This is shown in Fig. 3. The correlation between Southern growth and public consumption (cp) is shown in Fig. 4. It is significantly negative, but only because of the presence of 8 "outliers" (see the lower right hand side). Without the 8 "outliers" the correlation is positive. All of these outliers refer to the 1990-93 period of very slow Southern growth and major fiscal adjustment at the national level. Strangely enough, cp in the South increased dramatically during this period. Since anticyclical unemployment compensations are virtually non- existent in Southern Italy for the reasons explained above, the huge increase in cp observed in these regions in the 1990-93 period must be the consequence of public employment policies and other expenditure programs probably decided mostly in the previous 5-year period(s). Thus the observed behaviour of cp in 1990-93 is most likely the consequence of the same corrupt political-business interests the activities of which explain also the spreading of organized crime, the increase of voluntary homicides and the halt of economic growth in these regions.

Fig. 3: Correlation between regional growth and public investment (ip), 5-year averages, South, 1980-93[28]
Figure 3

Fig. 4: Correlation between regional growth and public consumption (cp), 5-year averages, South, 1980-93[29]
Figure 4

We conclude that in the South cp and ip at least in the period 1980-93 do not behave anticyclically. This lack of reverse causation between regional growth on the one side and ip and cp on the other has also important implications for the confidence one can put in the results of the next section (where employment is the dependent variable).

If one considers plausible the hypothesis that public spending in the South has stimulated since about 1980 corruption and organized crime, the obvious conclusion follows that the money spent by the Italian government in the South since about 1980 has had a very negative effect on convergence and that it is therefore better not to spend public money in the South until the environment is completely cleaned. A sharp reduction in taxation in the whole country would have much more positive effects on long run growth of the whole country and most likely also of the South. The clear perception on the part of the taxpayers in the Center-North that money in the South is wasted and only contributes to corruption and organized crime Stimulates tax evasion (which under the circumstances has at least a partial moral justification) and has led in the early 1990s to the growth of a separatist party in the North, the Lega Nord.

A rough estimate of the joint effect of crime and government expenditures on Southern convergence can be obtained from the difference between the absolute b-convergence estimated in Table 1 (1.4%) and the conditional b-convergence estimated from Tables 3-6, which in the best regressions is as high as 3%. Taking more prudently

an estimate of 2.7%, the "wrong" economic policies for the South and the incapability or unwillingness on the part of Italian governments to keep law and order there at least at the level of the 1960s has cost the South on average 1.3% per year in terms of lower growth rates of GDP per capita for the 34 year period. Only in the 1960-71 period economic policies followed by the government were correct as the absolute b-convergence for this period (3.2%, see second regression of Table 1) which measures actual convergence is above the conditional b-convergence for the whole sample period taken as the basis of our computations (2.7%). Thus in this period the right economic policies and the fact that organized crime and corruption were still held in check contributed positively by 0.5% annually to convergence. In the period 1971-93 they contributed instead to subtract 2.2% annually from Southern growth and to reduce it from the underlying 2.7% to the actually recorded 0.5%. These calculations do not take into account the fact that the higher taxation to finance these damaging expenditures has slowed down growth nationwide, as suggested by Daveri and Tabellini (1997).

3. An alternative dependent variable: regional employment as percent of the resident population.

Using exactly the same methodology and the same explanatory variables as in Section 2 we analyse in this section the effect of the crime rate and of government expenditures on the employment rate defined as the ratio of regional employment to the population resident in the region. Table 7 corresponds to Table 3 of Section 2, where only the dependent variable has changed.

The coefficient of initial income is positive, suggesting that richer regions also have higher employment ratios. The coefficient of the crime rate is negative and in general much more significantly different from zero than in the regressions explaining real GDP growth. The variable government consumption expenditures has a coefficient which is negative and significantly different from zero at the 1% level of significance, confirming the hypothesis that invalidity pensions, a generous pension system, subsidies to households and an increase in public employees lead to lower employment ratios. The coefficient of public investment is not significantly different from zero, but we shall see below that this insignificance only hides huge differences between the Center-North and the South.

The regressions with the temporal breakdown of the explanatory variables are shown in Table 8. In the first place we observe that the coefficient of the crime rate is always very significantly by different from zero and exerts a negative impact on the employment rate. Second its significance strongly increases through time, as expected. Third total government spending is always insignificant. Fourth, this results from a persistently negative effect of public consumption on employment, a negative effect the significance of which increases steadily as time goes by, and an effect of public investment which is positive in the first period and in this period only. Fifth in the regressions without the crime rate the Adjusted R2 falls significantly, while this was not happening to the same extent in the regressions with real GDP growth as a dependent variable (cfr. Tables 3-6), suggesting that the crime rate is more important to explain employment than growth and convergence.

From the geographical breakdown of the exogenous variables one draws additional important information. The results are shown in Table 9. First the initial level of income looses its significance as we proceed with the breakdown of the explanatory variables, but this poses no serious problem since we are explaining here the employment rate and not convergence. Second the crime rate is never significantly correlated with employment in the North, while it is very significant in the Center and even more so in the South. In the Center-South its impact on employment is negative. Third public investment has a positive and very significant effect on employment in the North and in the Center, as one would expect in a healthy country, but its effect is negative and significant in the South, confirming our hypothesis that something is very wrong there. Fourth equally bad is -he finding that in the South government spending and consumption have a negative and significant effect on employment. In the Center-North the effect of public consumption varies from neutral to positive depending on the regression.

The regressions with the joint temporal/geographical breakdown if the erogenous variables are shown in Table 10. We present also regressions without the crime rate because in the third period in the South it is too highly correlated with government spending and this leads to imprecise estimates of the spending variables. The main results are first that in all three periods the crime rate does not significantly influence employment in the North, while it always does influence it negatively and very significantly in the South. This result for the South contrasts with what we found in Table 6 where in the first period the crime rate in the South did not influence convergence negatively.

Second a rough idea of how much government spending and the crime rate are correlated in the South can be obtained by comparing the significance of crimd3dm in the first 2 regressions of Table 10: when we remove spending in the second regression, the t-statistics of the coefficient of the crime rate increases from 5.4 to 8.6. It is also noteworthy that if we remove the variable spending the Adjusted R2 falls relatively little (cfr. regr. 1 and 2 of Table 10). Third the crime rate in the Center has mixed effects on employment, the effect depending on the period. It was significantly negative in the first, had no significant effect in the second and there is a renewed negative effect in the third, but it is not very significant. Fourth government consumption in the South always exerted a negative and very significant effect on employment by creating distortions in the labour market. In all three periods the significance of the coefficient of government consumption increases sharply if we remove the crime rate from the regression, a sign that the correlation between them is high. In the Center-North government consumption has no clear-cut effects on employment. Fifth public investment tends to have a positive and significant effect on employment in all three periods in the Center-North, particularly in the Center, while it always has a negative and significant coefficient in the South.

Overall the regressions with the employment rate as dependent variable show even more significant and clear-cut effects of the crime rate and of government spending than the regressions with the growth rates of GDP per capita. They tend to confirm the results of Section 2 and give a clearer picture of the role of government spending in the three groups of regions and in the three periods considered, highlighting the marked differences between the North and the South.

4. Summary and conclusions

In line with other studies on the subject this paper finds a strong convergence of Italian regions from 1960 to 1971. The estimated absolute b-indicator of convergence is a remarkable 3.2% for this period. After 1971 the paper finds periods of divergence followed by slower convergence than in the 1960s (see Table 1). After 1984 the average real GDP per capita of the Southern regions falls back with respect to the Center-North and the process accelerated after 1991. As a result the absolute b-convergence for the whole period 1960-93 is a much more modest 1.4% per year.

Section 1 presents a brief historical overview of the factors which may have influenced these phases of convergence and divergence of Italian regions and in particular of the South with respect to the Center-North and advances two mutually reinforcing explanations of why the process of convergence first slowed down Considerably in the 1970s and then came to a virtual halt in the 1980s. The wrong economic policies unrepentantly pursued by successive Italian governments in the South and the growth of organized crime

and corruption slowly blocked the underlying forces of growth present in the area. Concerning the changes through time of the effect of Government expenditures our starting hypothesis was that government intervention in the South was largely beneficial in the 1960s, turned neutral in the 1970s and became negative in the 1980s and 1990s. This subdivision of the period is also in suggested by Costabile and Giannola (1996).

We offer at the beginning of Section 2 theoretical explanations of why one should expect lower growth where organized crime and corruption are widespread. We also offer in the text and in several footnotes some first-hand evidence of episodes experienced personally by one of us. They are intended to give to the reader, especially to the Northern Italian and to the foreign one, an indication of the lack of transparency of the public administrations in the Center-South and of the virtual absence of the rule of law (court trials last for decades) and to show how difficult it must be to conduct business in many areas of the South. These episodes could contribute to explain why there is Virtually no foreign direct investment going to the provinces of Italy, where organized crime is strong and why private Northern Italian capital moves to the South only when attracted by very high government subsidies and social security and tax exemptions[30].

In the empirical parts of the paper (Sections 2 and 3) we divide he sample period (1960-93) into 7 subperiods of 5 years each[31] and construct 5-year averages of annual data. We have thus 7 observations for 20 regions, a total of 140 observations for each regression. The regressions presented in the paper have thus at least 120 degrees of freedom, a fact which greatly enhances the confidence which can put in the results. Contrary to a few previous studies on convergence of Italian regions which do not find significant effects of crime on convergence, we use a new variable to proxy organized crime: the number of voluntary homicides. This variable is certainly less subject to underreporting than crimes against property and crimes in general (the two variables used in previous studies) and is not biased by homicides committed for robbery like in US inner cities because these types of homicides are not common in Italy.

Our hypotheses are fully confirmed by the econometric analysis of Section 2 which shows that our proxy for organised crime turns out to be the most significant variable in explaining the lack of convergence of Southern Italian regions after 1980, that government consumption expenditures tended to be beneficial in the three main areas of the country in the 1960s, maintained a weak positive effect in the 1970s and became insignificant after 1980, while public investment had an insignificant effect in the South in all three periods. One study on convergence of Italian regions finds that corruption, measured by crimes against the public administration, did influence convergence negatively (Del Monte and Papagni, 1997) and this certainly does not contradict the main conclusions of this paper as corruption and organized crime go hand in hand.

In Section 3 we replicate the tests of Section 2 using as dependent variable the ratio of regional employment to the resident population and we show that already in the 1960s the crime rate influenced employment in the South negatively, that its negative effect becomes more significant with the passage of time, that government consumption in the South always exerted a negative and very significant effect on employment and that public investment tended to have a positive and significant effect on employment in all three periods in the Center-North while it had a negative and significant coefficient in the South already in the 1960s. Overall the explanatory power of our exogenous variables is stronger in the regressions explaining employment than in the ones explaining convergence. By adding Section 3 to the paper we also analyse one of the main channels through which the crime rate and government expenditures influence convergence: the labour market[32].

At the end of Section 2 we present a rough estimate of the joint effect of crime and government expenditures on Southern convergence by comparing the absolute b-convergence estimated in Table 1 with the conditional b-convergence estimated from Tables 3-6. Taking a prudent estimate of the latter of 2.7%, the "wrong" economic policies pursued by the government in the South and the incapability or unwillingness on its part to keep sufficient law and order there has cost the South on average 2.2% per year in terms of lower growth of GDP per capita during the 23 years from 1971 to 1993. On the contrary during the period 1960-71 economic policies followed by the government were "correct" and contributed positively by 0.5% annually to convergence. These calculations do not take into account the fact that the higher taxation to finance these damaging expenditures has slowed down nationwide growth[33].

One hypothesis which we advance but do not test directly in this paper is that government expenditures particularly for investment enhance the financial strength of organized crime and its control over the territory. The judge Giovanni Falcone killed by Mafia in 1992 was well aware of these links. Unfortunately we cannot report direct evidence about the validity of this hypothesis, also because our proxy for organized crime is certainly not ideal to capture the millions of underground connections and economic transactions which interfere negatively with the process of optimal allocation of resources in the South. Yet the fact that during the last period considered (1984-93) in the first regressions of Table 10 the crime rate in the South (crimd3dm) gains so much significance when we remove spending may be an indication that the two variables almost perform the same function in explaining regional employment.

An interesting study on the determinants of voluntary homicides in the 20 Italian regions by Marselli and Vannini (1997) shows that they are significantly influenced by social spending, by the share of employment in services and by public works, all positively. Furthermore also the number of policemen in the region as a percent Df the resident population influence homicides negatively. Marselli and Vannini also show that law enforcement officials are not at all concentrated in the high crime regions as one would expect. Similarly Del Monte (1996) shows that in the South public spending affects corruption. The results of these authors are perfectly in line with ours.

Turning to the implications for economic policy the message of this paper should be clear enough. First the government in Rome should concentrate on speeding up the cases pending in front of the courts in the South, increase the resources of the judicial system and the police there, fight more convincingly corruption and organized crime in the area and pass special laws limited to the most infiltrated areas. A criminal code written for "normal" crimes is not suited to fight the criminal organizations operating in the South. These special laws should aim at breaking the mortal embrace of organized crime with local public administrations and even with the political system. Second until the job above is not done the government should refrain from increasing investment in the South because at present it is largely incapable of controlling the ultimate use of funds in the region. It would be much better for the whole country to lower taxation drastically.

Third since government consumption expenditures have been shown to exert negative effects on employment in the South, the government should reduce them as fast as possible. Also reducing public employment would help long run growth in the South and in the whole of Italy and it is well known that there is a huge excess of public employment in the South. A policy of retrenchment of the government would also help to reduce tax rates and lower labour costs nationwide and contribute to economic growth through this channel. It would also create more room for the market in the South. But it goes without saying that no market can really develop if the job of re-establishing law and order is not done. Measures to increase flexibility in labour markets (like allowing tax deductions for migrating workers) would also help. Above all clear signals should be sent to households to convince them that the music has changed, while the government is doing at the moment exactly the opposite by employing for one or two years hundreds of thousand of young workers for "useful social works" thereby creating the expectation that the job will become permanent. In addition since it is always the local authorities which decide whom to employ we are confronted again with a case in which public money is likely to stimulate corruption and the influence of organized crime. Imagine the risks incurred by a mayor if he refuses to hire the young people recommended by local mobsters!

Several very recent studies on Italy about the role of organized crime, corruption, taxation, the size of the government, the quality of institutions and the lack of economic freedom arrive at policy conclusions which are as strong as ours. Quintieri (1998) and Quintieri (1998) suggest that the lack of economic freedom and excessive regulations are negative for growth, Del Monte and Papagni (1997) show that corruption has been very negative for Italian growth, Costabile and Giannola (1996) and Marselli and Vannini (1996) emphasize the role of the probability of punishment and proper law enforcement. Daveri and Tabellini (1997) show that high taxation increases unemployment and slows down economic growth.

Since we have very little hope that the present or for that matter future Italian governments will adopt the necessary measures we hope that the Governments of the European Union and the European Commission will convince the Italian government to sign a binding pact which forces it to take the necessary measures. This pact is not only in the interest of Italy and of the South, it is also in the interest of the European Union. Billions of ECU in agricultural subsidies and public Investment money go to people in the South who should be in jail. Above all, with the Monetary Union, increased financial integration and greater mobility of Italians within Europe, it is in the interest of all EU member governments to at least try to eliminate this cancer.

Italian governments are too weak to do the job alone and they will always be. Without wanting to downplay the merits of the Prodi government for bringing Italy into the Monetary Union, it is safe to say that without strong pressure from Europe and binding laws and treaties Italy would never have abolished controls on capital flows in 1990, made the Banca d'Italia independent from the government in 1994, introduced more competition in some industrial sectors, reduced inflation below 2% in 1998 and reduced the budget deficit below 3%. Similarly it will not be able to tackle seriously without due pressure from abroad the problem of organized crime, which in our modest opinion is much more severe than the problem of inflation or high budget deficits. We think so because the vested interests in Italy for maintaining the status quo are too strong and because too many Intellectuals have gathered behind the banner of defending at all cost personal freedoms and the existing excessive guarantees of the citizen in front of the judicial system, probably also because of reminiscences from fascist times and because they may not trust the police and judges enough (and they may be partly right). The fact that there are a number of corrupt judges and policeman is of course one of the problems in this difficult war. At present the political debate about the reform of the judicial system is purely driven by personal interests of the politicians in power. In particualr Mr. Berlusconi, the Head of the opposition and leader of Forza Italia, faces many criminal charges and listening to the political debate on Italian justice is just depressing.

Should European governments decide to look into the matter seriously and constrain the future behaviour of this and successive Italian governments there is no lack of honest judges in Sicily and elsewhere in Italy who can help in drafting the list of the measures needed[34]. Also the sovereignty of Italy in the fight against Mafia and corruption should be reduced by introducing foreign personnel and close foreign monitoring in the units/commissions in charge of directing the fight.

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Appendix 1: Definition and sources of the data used

y=regional GDP per capita at constant 1980 prices, obtained by dividing regional GDP at current prices by the consumer price index of each region and then by the resident population. The dependent variable in the regressions of Table I is the average geometric growth rate of real GDP per capita for each period calculated as indicated in equation (1). In the regressions of Tables 3-6 it is the average ,geometric growth rate of real GDP per capita for each 5-year period. Sources: for regional GDP at current prices: Istat (Noterapide, December 1997), Istat (Conoscere l'Italia 1996), Istat (I Conti Economici Regionali, 1995), Fondazione ENI Enrico Mattei (Banca dati regionals ad opera di C. Tirloni-G. Veronese). For the regional consumer price index: Istat (Annuario Statistico, Italiano, various issues), Fondazione ENI Enrico Mattei (Banca dati regionals ad opera di C. Tirloni-G. Veronese). For the population resident in each recion: Istat (Annuario Statistico Itatiano, various issues), Fondazione ENI Enrico Mattei (Banca dati regionals ad opera di C. Tirloni-G. Veronese).

lnyin=natural logarithm of real GDP per capita in the first year of the sample period (in Table 1) or in the first year of each quinquennium (in Tables 3-10). Source: see "y".

crim=the crime rate, defined as the number of voluntary homicides committed in each region for 100.000 inhabitants; 5-year aritmethic averages of annual data. Source: Istat (Annuario delle Statistiche Giudiziarie, various issues).

ip=regional public investment in construction and public works, in constant 1980 lire and in proportion to the population resident in the region; 5-year aritmethic averages of annual data. Source: Istat (I Conti Economici Regionali, 1995), Fondazione ENI Enrico Mattei (Banca dati regionals ad opera di C. Tirloni-G. Veronese).

cp=regional public consumption in constant 1980 lire and in proportion to the resident population; 5-year aritmethic averages of annual data. Source: see "y".

sp=ip+cp--the sum of public investment and consumption as defined above.

ot=the ratio of regional employment to the population resident in the region; 5- year aritmethic averages of annual data. Source: Istat (Annuario Statistico Italiano, various issues).

e=number of students enrolled in secondary schools in percent of resident population. Source: Istat (Annuario Statistico Italiano, various issues).

Dummy variables

D1 = 1 in the 5-year periods 1960-64, 1965-69, 1970-74; D1 = 0 otherwise;

D2 = 1 in the 5-year period 1975-79 and 0 otherwise;

D3 = 1 on the 5-year periods 1980-84, 1985-89, 1990-93 and 0 otherwise;

DN = 1 for each region of the North and 0 otherwise;

DC = 1 for each region of the Center and 0 otherwise;

DM = 1 for each region of the South and 0 otherwise;

Hence it follows that:

crimdl= crime rate in the period 1960-74;

crimd2= crime rate in the period 1975-79;

crimd3= crime rate in the period 1980-93;

crimdn= crime rate in the North;

crimdc= crime rate in the Center;

crimdm= crime rate in the South;

crimd1dn= crime rate in the period 1960-74 in the North;

crimd1dc= crime rate in the period 1960-74 in the Center;

crimdldm= crime rate in the period 1960-74 in the South;

crimd2dn= crime rate in the period 1975-79 in the North;

… … …

The same procedure has been applied to the variables sp, ep, ip.


Tables

Table 1: Absolute -convergence, number of observations: 20
Table 1

Table 2: Absolute sigma-convergence (Standard Deviation of the natural logarithm of real GPD per capita of the 20 Italian regions, number of observations: 20)
Table 2

Table 3: Relative -convergence; 5-year averages of annual data, 1960-93, number of observations: 140
Table 3

Table 4: Relative -convergence; 5-year averages of annual data, 1960-93, number of observations: 140
Table 4

Table 5: Relative -convergence; 5-year averages of annual data, 1960-93, number of observations: 140
Table 5

Table 6: Relative -convergence; 5-year averages of annual data, 1960-93, number of observations: 140
Table 6

Table 7: Dep. var.: Employment rate, 5-year averages of annual data, 1960-93, number of observations: 140
Table 7

Table 8: Dep. var.: Employment rate, 5-year averages of annual data, 1960-93, number of observations: 140
Table 8

Table 9: Dep. var.: Employment rate, 5-year averages of annual data, 1960-93, number of observations: 140
Table 9

Table 10: Dep. var.: Employment rate, 5-year averages of annual data, 1960-93, number of observations: 140
Table 10


Footnotes

[1]This paper is based on a chapter of the laurea dissertation of Stefano Quarella presented at the University of Brescia on February 4th 1997 and entitled "Diseguaglianze economiche fra Nord e Sud e sviluppi del mercato del lavoro". We would like to thank Prof. Francesco Daveri for useful suggestions on earlier drafts.

[2]Professor of Economics, University of Brescia, Via San Faustino 74/B, 25122 Brescia.

[3]Banca San Paolo di Brescia, Corso Martiri della Libertá 13, 25121 Brescia.

[4]For very large Italian firms like Fiat these problems are less serious because they have a strong bargaining power with the Central government, local admistrations and anyone else who comes along.

[5]It may be worth mentioning that one of the writers of this paper has inherited property in the Center-South of Italy and he has incurred in the following three interesting episodes. They are quite revealing of the lack of the rule of law in the South. First in 1981 and 1982 his farm incurred into a VAT credit with the government. When his father died in 1984 the inheritance tax was promptly paid on the VAT credits. By 1988 he still had not received the VAT credits. The Ministry of Finance in Rome said that the case of the 1981 reimbursement was "closed" because "this is our standard practice for reimbusements of less than half a million lire". Therefore they would not pay neither the capital nor the interest despite the fact that inheritance taxes were paid on the 1981 VAT credit. As to the 1982 reimbusement, they would pay the capital, but if he wanted also the interest he would have to go to court. He went to court for the 1981 credit (capital and interest) and for the interest on the 1982 credit. The case was closed with full reimbursement in 1998, after 17 years! This episode makes you wonder how people can trust such a government and may even provide a full moral justification for tax evasion. Second he owns a strip of land by sea in a Central-Southern beach resort. According to the regulations of the town one can build on it and it is already built all around. He asked for a building permit for the first time in 1983. The request has been rejected two times in the course of the succeeding years on the ground that the town has not yet built a sewage system in the area, although he had planned to construct at his own expenses a link to the closest point of the existing sewage system. In the course of time he was repeatedly told by city officials first that a recommendation to the mayor from Mr. Andreotti would greatly help and secondly that money was still lacking for the next town celebrations. In March 1994 after the second application for a building permit had been turned down with a two year delay, he went to court against the decision of the town administration to turn the project down and to this day he is still waiting (15 years after the first application and almost 5 years after the appeal to the courts!). The third episode is even more disturbinc,: in March 1994 he sold the farm in Southern Italy (the same on which VAT credits were due) and he agreed with the buyers that the European Union subsidy on hard wheat for the acrarian year 1993/94 would go to him and the receipts from the sale of the product to the buyers. There was no objection and the tranfer of the property took place regularly on March 30 1994. He was accused by the buyers in July 1994 of extorting from them with threats the clause that the EU subsidy would go to him. I'he buyers have false witnesses to whom they have probably promised a part of the subsidies, should the courts find him guilty of extorsion. He has not heard from the judges in four years. Meanwhile his name is on the police records as a potential criminal. We could tell of a fourth episode of injustice caused by the virtual absence of a legal system, but we do not want to bore the reader further. The point is either that one of is is extremely unlucky or that something must be dead wrong in Southern-Central Italy. We should add that the family of the one of us who incurred into the above three legal Droblems lives in Rome while its property is/was scattered in several towns of Southern/Central Italy; as a result in the eyes of local criminal elements its social standing is small. In addition we are not members of a party, we do not have close contacts with the higher hierarchy of the Catholic Church and we are not freemasons; these organizations are known to frequently solve problems of the type mentioned above through connections in the right administrations and by speeding up processes bringing them to the "right" conclusion. He won the battle concerning VAT reimbursement and hes confident he shall win the other two. The question is when and at what cost. We have ost all confidence in the Italian government and theltatian legal system and the one of us nvolved in these matters is at the moment packing all his belonging to leave Italy for good and in digust.

[6]See the clear and strong appeal by judge Morvillo of Palermo, brother-in-law of Giovanni Falcone, on the Maurizio Costano show (Channel 5 of Italian Television) in May 1998. He appealed for special laws on the ground that there is a war in the South and that laws designed for normal criminal offences cannot be sufficient to fight the types of crimes committed there by organized crime.

[7]See Piras M.G. (1992), Di Liberto A. (1994), Paci R.-Pigliaru F. (1995), Cosci S.-Mattesini F. (1995), Fabiani S.-Pellegrini G. (1997), Bianchi C.-Menegatti M. (1997), Ferri G.-Mattesini F. (1997), Del Monte A.-Papagni E. (1997).

[8]In the early 1980s a unit was created at the Ministry of the Budget in order to evaluate public investment projects on the basis of the rigorous techniques used by the World Bank. Experienced staff from the World bank was hired. Initiailly politicians were favourable. When they understood that they would loose their discretionality in deciding which investments to make the Unit was "sacked" by inventing criminal offenses against the best and most honest officials and forcing them to leave. Later the personnel of the unit was replaced with "safe" officials.

[9]In the late 1980s in the Southern region where the Earthquake of 1980 caused over 1000 casulaties a small piece of land of one of us was expropriated to build a road linking a town of 3000 inhabitants to a village of about 300 souls. The road was built with bridges and tunnels at about midway between the bottom of the valley and top of the mountain. Planned cost: 32 billion lire. Although we are not civil engeneers we noticed that the road could have been built much further down the valley without so many bridges and Galleries. We found out that an alternative project existed. Planned cost: 4 billion. However, local authorites must have made sure that the alternative project disappeared so that it could not even be considered. The presumed reason is that the margins for bribes and unjust profits are in absolute value much higher on a 32 than on a 4 billion project. This reflects a very high esteem for the taxpayer on the part of public administration in some areas of the country. If the courts had been functioning well and fast we may have asked them to investigate the matter more deeply than we could with our limited means and only for the sake of satisfying our intellectual curiosity.

[10]4.6% to be precise.

[11]Mr. Andreotti, amny times prime minister and virtually always in the government or a leading figures of the Christain Democratic Party since 1947 has been charged of committing such a crime in Sicily. It would be a big mistake to think that these practises have ended after the fall of the Christian Democratic-Socialist regime in 1992. Leading Sicilian figures of Forza Italia, the party created by the TV tycoon Berlusconi in 1993, have been charged and at least one is under arrest at present for maintaining very close connections with Mafia at the time surrounding the 1994 elections. In addition Mr. Dell'Utri, head for decades as one of the most important firms of Berlusconi (Publitalia) has been charged of associated with the Sicilian Mafia.

[12]See footnote 5, the second episode.

[13]See Ramsey (1928), Solow (1956), Cass (1965), Koopmans (1965).

[14]See Barro and Sala-i-Martin (1991).

[15]The calculation is done as follows: (1-0.527) * (1+0.014)t = 1. Hence, solving for t one obtains t = ln (1/0.473) : ln (1.014) = 53.849 = 54.

[16]The interested reader can consult Quarella (1997), Chapter III.

[17]I am thinking of the Sicilian member of Parliament Salvatore Lima, killed in March 1992.

[18]See footnote 5.

[19]Recently one of us managed to get for the moment only tentiative and preliminary information from AIMA, the state agency in charge of paying out agricultural subsidies of the European Union, on traces of illegal demands for subsidies presented in 1993 by third parties on his farm (see episode no. 3, footnote 5), only after writing to the European Commision in Brussels. The Commission put AIMA under pressure. Before writing to the Commission we cannot answer to his request of information was: "there is now a law on privacy and we cannot answer".

[20]See Bardhan (1997).

[21]See footnote 9.

[22]Not suprisingly foreign direct investment in Italy as a percent of GDP is among the lowest in Europe and most of it goes to the North. For instance on January 1st 1996 the percentage of factories with foreign participation was 73% in the North, 16% in the Center and 11% in the South (Quintieri, 1998).

[23]For a comprehensive analysis of the channels through which corruption affects negatively the efficiency and equity of the tax system and the power of the state to enact economic policy see V. Tanzi (1995).

[24]The 5-year periods considered are: 1960-64, 1965-69, 1970-74, 1975-79, 1980-84, 1985-89, 1990-93. The last period is an exception as the data are averaged over 4 years instead of 5.

[25]The regions of the North are 7: Lombardia, Piemonte, Valle d'Aosta, Liguria, Trentino-Alto Adige, Veneto, Friuli-Venezia Giulia.

[26]The regions of the Center are 5: Emilia-Romagna, Toscana, Marche, Umbria and Lazio.

[27]The regions of the South are 8: Abruzzo, Molise, Campania, Puglia, Calabria, Basilicata, Sicilia and Sardegna.

[28]The linear interpolation shown in Fig. 3 is based on the following regression, where numbers in paranthesis are t-statistics: y = 0.013 (1.06) - 0.003 (0.29) ipd3dm; Adj.R2 = 0.04.

[29]The linear interpolation shown in Fig. 4 is based on the following regressions, where numbers in paranthesis are t-statistics: y = 0.05 (3.59) - 0.023 (-2.39) cpd3dm; Adj.R2 = 0.17.

[30]And when they go they tend to go to those provinces where organized crime is absent or not very strong.

[31]Only the last period is a four year-period.

[32]For a model of economic growth which explains also how increased unemployment can reduce economic growth in the long run see Daveri and Tabellini (1997).

[33]See again Daveri and Tabellini (1997) for empirical evidence on the strength of this effect.

[34]One of them is Mr. Morvillo, judge in Palermo and brother-in-law of Mr. Falcone.



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