Why do north south disparities persist

Only in the period — are growth rates higher in the South than in the rest of the country: a weak phase of convergence occurs. We lack reliable figures on North—South inequality before On the eve of World War 1, the South—North ratio in product per capita was 80 percent; in it was 50 percent Fig. At that time, all of the Southern regions shared a level of per capita GDP lower than the national average.

The two and a half decades after the war was the only period when GDP rose faster in the South than in the North. However, after 25 years of modest progress, per capita GDP in the South began to fall again relative to that in the North and then stabilised around 60 percent.

Since both data on regional disparity and North—South inequality seem to be reliable, the only explanation for the diverse evolution of disparities among regions and between North and South is that inequality, once widespread across the national territory, depended ultimately on the divergence between two parts of the same country which were internally relatively homogeneous. We could thus hypothesise a rising convergence within both the North and South together with a rising divergence between these two sections.

We present two different and complementary statistical methods aimed at specifying this reshaping of the Italian economic geography. A first method in order to distinguish dualism and disparities is that of exploiting a property of the deviance: having a set divided into two subsets, total deviance DevT is equal to the sum of the deviances within the subsets DevW plus the deviance between the averages of the subsets DevB.

Deviance within the subsets North and South DevW is represented by:. The deviance between the two groups of regions, North and South DevB , is equal to:. The share of North—South disparity Dns of total regional disparity is then computed as:. Table 6 reports the ratio between the North—South deviance and total deviance among regions according to Eq.

We see how the North—South disparity only accounted for 21 percent of total regional disparity in At that time, the North and South were hardly distinguishable. However, it can be seen that, in the following century, the North and South gradually became two different economies.

From the s onwards, DevB accounted for 80 percent of the total deviance DevT. While convergence occurred both within the North and the South and DevW declined , divergence widened between the North on the one hand and the South on the other and then DevB. The conclusion is that convergence occurred over the period both within the North and the South, but North—South divergence rose.

A graphic presentation of the North—South disparity within the Italian regional disparity can be reached by computing the Theil index of the North—South divide and by comparing it to the national Theil index. In Fig. We see that, at the beginning, the North—South disparity was negligible, but increasing.

The analysis of the deviance is confirmed. The decline in the level of regional inequality from cancelled the disparities among the regions in both the North and South, but hardly interested the inequality between North and South. Gradually Italian regional inequality intensified between North and South, with the formation of two convergence clubs: a rich one including most of the Centre and North, and a poor one consisting of a small group of Southern regions Paci and Pigliaru, Theil indices between the regions and between North and South — In order to explain regional disparity, and especially the North—South divide, several scholars recall remote causes: the different history of the North and South in the distant past Guiso et al.

A traditional approach in Italy is to see the North—South divide as the consequence of political errors and then to attribute it to faults by governments and mistaken economic policies. In this contribution we have investigated the proximate causes and focused on measurable facts. These alleged social and political causes, both distant and recent, are often impossible to plausibly measure. They are frequently object for conjecture and political debates and are out of our perspective.

In our view, to be properly understood, regional inequality must be set within the general process of modern growth and can be realistically linked to the structural change which has taken place in Italy over the last years. We have examined this process, focusing on the relationship between the geographical distribution of industry and the evolution of regional inequality. The evolution of regional inequalities in Italy in part confirms Williamson's hypothesis: a long phase of divergence started with the process of industrialisation, when industrial concentration increased; later, however, the spreading of industry engendered a relative convergence.

In this case, we do not find any bell-shaped curve: per capita income levels diverged in a first long-phase of about years — , slightly converged in a second short period of about years — , and remained roughly stable in the subsequent period as they are today. This interpolation method permits the obtaining of yearly data for the periods comprised between the benchmarks e.

It is easy to see how this method gives regional GDP per capita estimates whose trends, between the benchmark years, replicate exactly the national business cycle. A serious limitation does not emerge in absence of severe and regional specific supply-side shocks such as natural catastrophes or profound deindustrialisation. In order to test our procedure, we applied the same method to Istat regional data for the period — more or less the same number of years as our reconstruction between the benchmarks for the years — ; we predicted, that is, regional per capita GDP in — with the same method we utilised for the earlier periods.

The partial correlations between predicted and actual GDP per capita for the cross-sections were, for the years —, in the order of 0. The result of this test supports our previous reconstructions of annual regional data from benchmark years.

For — we utilised data on gross product from Svimez For the years —69, we took data from Unioncamere For — Svimez For the three decades — Istat, Conti economici regionali. The differentials of our previous Table 2 have been obtained by dividing per capita regional output by the national per capita output. We did the same in Table 2 , for the North and the South. Regional per capita GDP — euros Labour force in the secondary sector — Saito Hitotsubashi University and L.

Many more details on labour force are presented in Daniele and Malanima forthcoming. See also the important article by Zamagni Data between and are from Vitali Data from are from Istat series of population censuses and data on labour force.. Map of the Italian regions. Note : actually, in , the Italian Regions are This Map and our Maps 1—8 refer to 16 homogeneous regions. Some of them are sets of regions existing nowadays and then it is easy to aggregate figures referring to them into bigger sets.

Felice reached results similar to ours. Since his reconstruction is not based on present, but on past regional borders, his results are hard to exploit and relate to other regional indicators.. With the exception of , when the population census was not held. For , our data in Table 1 are based on the interpolation through the censuses held in and We refer here to the share of labour force in industry out of the total population and not to the participation rate.

Data in Table 1 refer to the participation rate the ratio of workers in industry to the total labour force.. The interactions between potential market size, transport costs and economies of scale in determining the location of industry are at the centre of the new economic geography; see, for example, Krugman a, b..

As will be shown in Section In this same App. The correlation between our series and those by Baffigi is 0. Using the series by Baffigi, our following analysis would be totally unaffected.. Looking at the disparities between the East and West of the Apennines, Sicily and Sardinia are not included..

Here we refer to regional disparity and not North-South disparity, still significant and stable at a high level.. Some changes did in fact occur in the relative demographic weight of specific regions, although these changes were on the whole modest. In the Southern regions the high rate of emigration was, in fact, counterbalanced by a high birth rate.

In this case, we computed the industrial participation rate as the industrial labour force in each region divided by the population of the same region, in order to capture the abandonment of the labour market by a share of the industrial labour force. This abandonment is captured if the denominator of our ratio is population whereas it is not if the denominator is labour force..

The year has been chosen since from the early Seventies onwards the North-South divide is more or less stable.. Brunetti et al. There is no reference at all to the sources, and especially to the kind of wages used in their estimation: agricultural or industrial?

How much data? To what regions do these data refer? The lack of clarity on the procedure does not allow us to exploit their calculations. Felice and Vasta estimated for a North-South disparity of 8. ISSN: Falling disparities and persisting dualism: Regional development and industrialisation in Italy, — Descargar PDF.

Vittorio Daniele a ,. Autor para correspondencia. Venuta, Catanzaro, Italy. Castellino, , Napoli, Italy. Table 1. Table 2. Table 5. Table 6. Table A. After presenting series of both labour force in industry and regional GDP, we analyse the relationship between industrialisation and inequalities and, finally, quantify the importance of the North—South dualism within the context of the Italian regional disparities.

JEL classification:. Palabras clave:. Texto completo. Source : Appendix and Daniele and Malanima forthcoming. Sources : Table 1 and Appendix. Source : See Appendix. Source : Daniele and Malanima Sources : Table 2 and Appendix. Table 3. Intercept Labour force industry R 2 Source : See Text. Table 4. Source : see Appendix. Source : calculations from data in Appendix. Source : Daniele and Malanima , forthcoming.. Regional disparities: internal geography and external trade: regional disparities in Italy — Presidential address: five bell-shapes in development.

Papers of the Regional Science Association, 45 , pp. Amos Jr.. Unbalanced regional growth and regional income inequality in the latter stages of development. Regional Science and Urban Economics, 18 , pp. Guilera, P. Regional incomes in Portugal: industrialisation, integration and inequality, — Italian National Accounts, — Barrios, E. Regional Science and Urban Economics. Donzelli, ,. Naegle and Benjamin H. Pike, and Brigitta Spaeth-Rublee. By Alexis Kuerbis and Silke Behrendt.

Nguyen and Timothy C. Tong, Elisabeth U. Kato, Mary P. Nix, and Arlene S. Greenstein, Haley V. Solomon, and Margo C. By Jordan P. Gonyea and Amanda Grienier. Garcia, Adriana M. Reyes, and Catherine Garcia. Suggested citation for articles in this issue: [Last Name s , First Name s ].

In the United States it is well-documented that there are huge gaps in healthcare access, treatment and outcomes for minority populations IOM, ; Riley, Feeding into health disparities are the dearth of studies, inadequate studies and limited or incorrect data on AIAN health. The problem grows when specifically looking at older AIAN.

When looking at national numbers, AIAN life expectancy at birth appears to be only approximately five years less than U. However, when drilling down to tribe-specific or even region-specific data, huge disparities appear. This is a stunning disparity when compared to life expectancy for White women in the United States at 81 years , and reflects life expectancies of the White population from more than years ago.

AIAN older than age 65 reporting one race make up 4. Compare this to U. Health inequities are affected by social, economic, and environmental conditions.

This points to few national studies, and scattered regional or tribal studies. All about population in Figures: tables on the French and world population and access to several online databases. The latest data on the population of metropolitan France structure and trends are given in a series of tables.

More complete datasets dating back to earlier years can also be downloaded in CSV format. INSEE includes the DOMs in its annual demographic overview and in most of the tables in its detailed annual study of the demographic situation in France. A provisional estimate is first issued and final figures are published at a later date. Censuses are conducted in certain years to enumerate the population.

The population changes from one year to the next. Natural change is the difference between births and deaths, and can be determined precisely from vital records. Net migration is the difference between the number of immigrants and the number of emigrants. It is estimated on the basis of available statistics. Adjustments are sometimes made to establish overall consistency between census population figures and inter-census estimates of population change.

To estimate its relative scale, population change is often expressed in relation to the mean population of a given year. Rates of birth, death, natural increase and total variation are obtained in this way. Registered births are recorded in statistical bulletins which provide a rich source of information. Completed cohort fertility is also calculated every year. For example, women born in were 34 years old in We know how many children they have had before age 34 and we can estimate how many children they will have during their reproductive life.

Fertility can be controlled by means of contraception and induced abortion. Information on contraceptive practice in France is obtained through surveys conducted regularly by INED since among the entire female population. The number of induced abortions is estimated on the basis of abortion notifications and hospital statistics.

INED is responsible for publication of abortion statistics. Marriage registers provide a rich source of information on marriage practices: number of marriages, previous marital status and nationality of spouses, etc. The first task in a population census is to enumerate dwellings. Persons living in the same dwelling form a household, so each household comprises all the persons living in a single dwelling. According to the census definitions, a household may comprise one or more families. Death registers provide a means to measure variations in mortality.

Deaths by sex and age are used to construct life tables which give life expectancy at birth, i. The mortality of children under the age of one year is also specifically calculated. When a person dies, a doctor records the cause of death on a death certificate which is sent to INSERM where all causes of death are coded.

Two statistical series drawing on different sources are presented. INSEE uses annual census surveys that provide an overview of net migration and entries and departures of non-immigrants and immigrants including undocumented foreigners. Population censuses provide an opportunity to count the number of inhabitants who were born outside France. Among foreign-born inhabitants, a distinction is generally made between persons born with French nationality and immigrants, who are born with a different nationality.

Inhabitants are distinguished by their nationality, i. French or foreign and, among French citizens, those who were born French and those who have been naturalized. The census provides information on current nationality and nationality at birth. Foreigners and immigrants form two different categories. Immigrants "born abroad as a foreign national" may still be foreigners at the time of the census or may have become French. Foreigners, for their part, may have been born abroad in which case they are immigrants or in France in which case they are not immigrants.

This section provides data tables on populations, births and deaths in Europe and in developed countries. It also includes indicators of population change birth and death rates and the two main demographic indicators: the total fertility rate and life expectancy at birth. The World Population Prospects publication provides United Nations population estimates for all countries in the world for each year between and and projections under different scenarios low, medium and high for each year between and The figures presented here correspond to the projections for the current year in the medium scenario.

An atlas, interactive maps, an animated film on migrations and annotated graphs that will enable you to visualize and understand world demographic trends and the issues they involve. So you think you know everything about population? Check how well you do on our quizzes. Demographic fact sheets offer a brief, clear overview of current knowledge about populations.

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