II Wax into the ears? Migration, equality and growth strategies
Navigating between Scylla and Charybdis. Tentative generalizations on the global scale and a case-study for the Polish case
After meeting so many Gods and monsters on our way, the difficult homecoming of Eastern Europe back to the center stage of the continent is, like Ulysses’ homecoming, confronted with yet another difficult trial. For Greek mythology, Scylla is a female sea monster, with the heads of dogs growing from her waist, who stood opposite Charybdis, a whirlpool in the straits between Italy and Sicily, that Ulysses had to cross. The sirens lured mariners to one of these two monsters by their singing. To be between Scylla and Charybdis is to be between two equally hazardous alternatives. The sirens lure the mariners in either one of the two dangerous directions: confronted with the siren calls of ‘fortress Europe’ and ‘Schengen means the re-erection of an Iron Curtain’, we should look anew at the process of mass migration and its relationship with the development marathon. Ulysses survived the straits of Messina - by putting wax into his ears not to listen the sirens and thus to be able to follow his long-term strategy. Scylla today means: fortress Europe, while Charybdis is unlimited mass migration.
We are not dealing here with trafficking human beings, the growth industry of the transnational criminal corporations in the 21st Century, not only in the straits of Messina at the crossroads of the Mafia, the ‘Ndrangheta, the Camorra, the Sacra Corona Unita, the Stidda, the Turkish Bozkurtcu and babas, the Yakuzas and Triads, and cartels (see also the excellent insight articles provided by the Web-Site of the Committe for a Safe Society at the Internet address http://www.alternatives.com/crime/). Our research question deals only with the long-run effects of migration on socio-economic development. The message of the present Chapter, that expands the presentation in Tausch, 1998, is fairly simple: building up and maintaining a viable social safety net is an option for both the recipient and the sending countries of international migration, an option which - in the long run and completely in agreement with a Myrdalian world view - is conducive to long-run economic growth. It is the long-term strategy to be followed, and neither of the siren calls, coming from two directions, should be heeded.
Above, we analyzed the trade-off between the ‘unlimited supplies of labor’ and long-term economic growth. Mass migration, as Amin (1997) reminded us, is part and parcel of this process of transnational capitalism. Starting in the 1970s, Amin and the dependency research tradition developed a viewpoint on migration, which focuses on the effects of migration on the world periphery. There is a considerable brain drain and human capital export from the periphery, which blocs long-term development; worker remittances are being used mainly for luxury consumption and imports, and migration has a long-term devastating effect on the gender equilibrium in peripheral and semi-peripheral societies (Braun and Topan, 1998, for a survey of the literature). 3% of the scientists and 10% of the doctors in the United States are, in fact, imported from the pool of cheap, mostly free University education in the world periphery. If there are free riders in the world economy, certainly the customers, Universities, hospitals and communes in the United States, which employ the free human capital from Third and Second World countries. The world periphery lost between 1960 and 1980 human capital to the tune of 16 billion $ to the center (Braun and Topan, 1998: 35 - 37). Critical, skilled and opposition elements leave the periphery, with the benefits of such a human capital import reaped by the center in the long run.
The market economies of western Europe first imported labor; now, with the transfer of production away from the European central zones, second generation foreigners become increasingly marginalized. In the inner cities of countries like France, Germany, and Britain, real ‘ghettos’ develop, a process that began in the United States of America three or two decades ago. Women also have to suffer from these tendencies, as their jobs are being exported away to the still much-lower paid labor power of the periphery and the semi-periphery (Stiftung Entwicklung und Frieden, 1993). Migration, we recall, is even part of the five pillars of international inequality (Amin, 1997):
Following research contributions which linked the patterns of international migration to the overall patterns of the center-periphery relationship, we try to develop here some hypotheses. The impact of migration on the sending countries under such conditions will be increasing the patterns of unequal exchange and the peripheral role in the world economy. It might be, that income distribution will become perhaps less unequal under the impact of the absence of millions of unskilled laborers from their home countries, but many other phenomena of peripheral development will be intensified; such as the deficient structures of agriculture, the environmental crisis (due to the intensification of traffic), and - in the end - the dependent character of accumulation, leading to slower economic growth and increased capital imports. World system oriented empirical research on migration confirmed, by and large, such a somber perspective (Amankwaa, 1995; Arrighi/Silver, 1984; Boehning and Schloeter-Paredes, 1994; Elsenhans, 1978; Parnreiter, 1994; Stalker, 1994; Stark and Taylor, 1991; Tausch, 1997, and Tausch 1998).
Semi-peripheral and peripheral decision makers, largely representing the import-dependent, urban elites, - and here there is no basic difference between the Philippines and Poland - demand semi-peripheral or peripheral access to the labor markets of the centers, but they overlook the dire sociological implications of mass migration on their own sending peripheries (Tausch, 1997, with a detailed debate about mainly ILO research). Recent econometric models, reviewed by Breuss (1997), could show that, in the case of EU-recipient countries with relatively high rigidities, immigration leads to higher unemployment, lower wage growth, but also a slightly lower inflation rate. Wage ‘dumping’ indeed is a problem on a European scale, made all the worse by present-day and future dispositions to migrate (see also the empirical survey in Poland, the Czech Republic, Hungary, Slovakia, and Slovenia by the Gallup Institute and the Austrian Academy of Science, reported in Fassmann/Hintermann, 1997; IOM, 1999; UN ECE and UN Population Council, 1998). These tendencies could even increase after EU-accession, basically because the problem of millions of small-scale peasants in East-Central Europe is unresolved. Unimpeded competition by high-tech and high-subvention Western agriculture will ruin millions of jobs in the peripheral rural structures of the East (Tausch, 1997, 1998). The recent surveys (Fassmann/Hintermann; IOM; RECESS quoted in Business Central Europe, April 1999, page 63) yielded the following pretty similar final results for the migration propensities from EU accession countries:
Table 2.1a: migration propensity from East Central Europe in 1996 - number of persons, willing to migrate
general migration potential |
probable migration potential |
immediate migration potential |
|
to Austria |
|||
from CS |
378138 |
209488 |
54830 |
from PL |
876337 |
285686 |
61344 |
from H |
523697 |
216810 |
16235 |
to Austria total |
1778172 |
711984 |
132409 |
to Germany |
|||
from CS |
712773 |
421249 |
75554 |
from PL |
1841293 |
614992 |
147303 |
from H |
539144 |
226440 |
18870 |
to Germany total |
3093210 |
1262681 |
241727 |
to UK |
|||
from CS |
153932 |
90974 |
16317 |
from PL |
221546 |
73996 |
17724 |
from H |
65247 |
27404 |
2284 |
to UK total |
440725 |
192374 |
36325 |
to France |
|||
from CS |
48522 |
28677 |
5143 |
from PL |
265855 |
88796 |
21268 |
from H |
73832 |
31009 |
2584 |
to France total |
388209 |
148482 |
28995 |
to Italy |
|||
from CS |
97044 |
57353 |
10287 |
from PL |
251085 |
83863 |
20087 |
from H |
39491 |
16586 |
1382 |
to Italy total |
387620 |
157802 |
31756 |
to Scandinavia |
|||
from CS |
45176 |
26699 |
4789 |
from PL |
152621 |
50975 |
12210 |
from H |
84134 |
35336 |
2945 |
to Scandinavia total |
281931 |
113010 |
19944 |
to NL |
|||
from CS |
56888 |
33621 |
6030 |
from PL |
172314 |
57553 |
13785 |
from H |
37774 |
15865 |
1322 |
to NL total |
266976 |
107039 |
21137 |
to the above 9 EU countries |
|||
from CS |
1492473 |
868061 |
172950 |
from PL |
3781051 |
1255861 |
293721 |
from H |
1363319 |
569450 |
45622 |
to the above 9 EU countries total |
6636843 |
2693372 |
512293 |
to rest of the world |
|||
from CS |
180703 |
120787 |
4406 |
from PL |
1142193 |
388502 |
100138 |
from H |
353699 |
151697 |
14473 |
to rest of the world total |
1676595 |
660986 |
119017 |
Legend: our own compilations from Fassmann/Hintermann, 1997
Table 2.1b) IOM study on migration propensity from East Central Europe in 1997 - number of persons, willing to migrate
total temporary migration potential |
to Austria |
total permanent migration potential |
to Austria |
Austrian share in total temporary migration flow from the region |
Austrian share in total permanent migration flow from the region |
|
Slovenia |
258310 |
10332 |
69545 |
0 |
4 |
0 |
Bulgaria |
724465 |
14489 |
298309 |
2983 |
2 |
1 |
Slovakia |
1280717 |
102457 |
272493 |
2725 |
8 |
1 |
Hungary |
1434534 |
186489 |
382542 |
22953 |
13 |
6 |
Croatia |
1622140 |
145993 |
42939 |
2576 |
9 |
6 |
Belarus |
1874236 |
18742 |
749694 |
7497 |
1 |
1 |
Czech Republic |
2494778 |
648642 |
623701 |
37422 |
26 |
6 |
FR Yugoslavia |
3172200 |
63444 |
1374620 |
0 |
2 |
0 |
Romania |
4887850 |
48878 |
2183933 |
21839 |
1 |
1 |
Poland |
7148215 |
285929 |
2704751 |
81143 |
4 |
3 |
Ukraine |
9890010 |
1879102 |
3296670 |
131867 |
19 |
4 |
Total 4 accession countries |
17703043 |
1046893 |
6887005 |
140404 |
5,91 |
2,04 |
Total 11 Countries |
34529145 |
3394165 |
11929652 |
311005 |
9,83 |
2,61 |
Recipient Country |
a few months |
a few years |
forever |
Austria |
|||
from CS |
648642 |
353808 |
37422 |
from PL |
285929 |
139101 |
81143 |
from H |
186489 |
124326 |
22953 |
Austria total |
1121060 |
617235 |
141518 |
Germany |
|||
from CS |
948016 |
517104 |
31185 |
from PL |
2573357 |
1251913 |
405713 |
from H |
358633 |
239089 |
38254 |
Germany total |
3880006 |
2008106 |
475152 |
UK |
|||
from CS |
598747 |
326592 |
31185 |
from PL |
428893 |
208652 |
189333 |
from H |
43036 |
28691 |
7651 |
UK total |
1070676 |
563935 |
228169 |
France |
|||
from CS |
424112 |
231336 |
37422 |
from PL |
357411 |
173877 |
135238 |
from H |
28691 |
19127 |
7651 |
France total |
810214 |
424340 |
180311 |
Scandinavia |
|||
from CS |
424112 |
231336 |
62370 |
from PL |
357411 |
173877 |
135238 |
from H |
28691 |
19127 |
7651 |
Scandinavia total |
810214 |
424340 |
205259 |
other EU countries |
a few months |
a few years |
forever |
from CS |
14345 |
54432 |
31185 |
from PL |
285929 |
139101 |
135238 |
from H |
99791 |
9564 |
3825 |
other EU countries |
400065 |
203097 |
170248 |
Source: our own compilations from IOM, 1999
Table 2.1c): RECESS Research Center, Warsaw simulations by comparison with the above results
Future Polish migration to |
Fassmann/Hintermann |
IOM |
RECESS Scenario B 4% Polish growth |
RECESS, based on current differentials |
RECESS, based on 7% Polish growth |
Austria |
61344 |
81143 |
61000 |
123000 |
23000 |
Germany |
147303 |
405713 |
276000 |
410000 |
195000 |
UK |
17724 |
189333 |
50000 |
91000 |
25000 |
France |
21268 |
135238 |
77000 |
134000 |
43000 |
Italy |
20087 |
52000 |
93000 |
27000 |
|
Scandinavia |
12210 |
135238 |
126000 |
277000 |
34000 |
NL |
13785 |
48000 |
104000 |
15000 |
|
other countries |
100138 |
1758086 |
81000 |
240000 |
18000 |
Polish world-wide migration |
393859 |
2704751 |
771000 |
1472000 |
380000 |
Source: our own compilation from the above materials and Business Central Europe, April 1999. The RECESS simulations are based on a 2% growth rate in the EU countries and on an analysis of the Southern European experience after EU accession. Modest or rapid growth changes the picture in favor of Poland, but still, some EU countries face considerable future Polish migration. The RECESS study, quoted in Business Central Europe, mentions the concrete figures for the Scandinavian countries only for the present European Union Scandinavian member states SW, DK and SF. In the case of the IOM study, Italy and the Netherlands are included among ‘other countries’.
In the centers, inequality will increase under the impact of mass migration, while at the same time, mass demand and technical progress, the ‘twin engines’ of auto-centered development, will suffer under the impact of the evolution of a ‘2/3-society’ in the center countries.
Our dire prediction, based on the systematic study of ‘hard’ data about world development in the 1990s, is - as we have shown above - that there is hardly any ‘mobility’ in the international system; and that in particular, mass migration is not a strategy of ascent for the semi-periphery and periphery.
Western Europe could be tempted, in order not to fall behind China, to overexploit Latin America and Africa, and to try to shift the present favorable East European and former Soviet balance in its favor, while North America’s negative balance with Asia is also an expression of the dramatic shifts in the production of multination US corporations.
Outward foreign direct investment stock of western European countries increased dramatically its share in West European gross domestic product, as one of the most visible signs of the process of globalization.
It is to be expected, that world capitalism is on its way towards an anti-egalitarian, and de-regulatory phase which will do away with many of the social advances that characterized the corporatist economic cycle of the post-World-War-II period. South Asia’s and Latin America’s inequality will decline, while in Sub-Saharan Africa, in the industrialized countries, and in Eastern Europe inequalities will increase considerably, and in the Middle East and North Africa there will be only a slight reduction of inequality rates. The growth of inequality in Eastern Europe, in Sub-Saharan Africa and in the industrial countries might herald the advent of a ‘Latin-American’-style capitalism of the 1960s and 1970s, that goes hand in hand with mass migration, the growth of transnational corporations penetration, short-term spurts of growth and long-term stagnation, and protected markets and economic distortions. The imperative of ‘balanced budgets’, ‘financial markets’ and ‘de-regulation’ might, in the end, undermine the very logic of economic growth that the anti-Keynesianism of the 1990s maintains to uphold. Comparative data for the 1980s and 1990s show, that inequality - as in the past - has no positive relationship to economic growth, and that, rather, the opposite is true (Tausch, 1993, 1997).
Our analysis in Tausch (1998) showed the effects, that transnational migration has on the sending and on the receiving countries in the context of overall dependency mechanisms across long cycles. The hope of many semi-periphery and periphery nations to change their weak position in the world-wide structure of the division of labor by mass migration to the developed countries is also not realistic. These findings could have an implication not only for the social scientific, but also for the political debate in Europe. At present, ‘green’, ‘alternative’ and socialist-left-wing groups claim, more often than not, that Western Europe should allow more immigration from the South and the East. But migration greatly increases inequality in the migration recipient countries, without really solving the long-run weak position of the sending countries in the international economy. If the ‘migration industry’ were right, then Jordan, Mexico, Jamaica, ex-Yugoslavia, Greece, Portugal and other highly migration-dependent countries would be ‘economic miracles’. And Ireland could have foregone its heavy investments in human capital, and just ‘let them go’.
In the migration recipient countries, environmental decay, as measured by the UNDP greenhouse index, increases as one of the main consequences of the process of international migration, due to mass traffic and the consumption model that mass migration induces. For us, migration is - above all - an expression of a peripheral position in the world economy. At first sight, migration has practically no positive or negative effect on economic growth, as is to be shown in the following graph:
Graph 2.1: migration, economic growth, inequality, the greenhouse-index and human development
Legend: balance of worker remittances per GDP (x-axis) and economic growth (y-axis)
Legend: balance of worker remittances per GDP (x-axis) and economic inequality (ratio of the income of the top 20% to the income of the bottom 20%)(y-axis)
Legend: balance of worker remittances per GDP (x-axis) and the human development index (y-axis). Sources: our own compilations from UNDP data
The dominant countries, like Japan or the United States, send their managers abroad, but never their workforce. It is a sign of world economic weakness to be a net exporter of labor force. Poor and peripheral countries, like Jordan, Pakistan, Portugal, or Poland, always send their workers abroad, and import their managers, and never the other way around. In the old colonial days, priests and soldiers were imported, timber, ivory, wheat, copper, slaves and bananas were exported. Still, the structure exists, but at a much higher level, with a lot of ‘soft body’ components as well. Interestingly enough, the effect of government size on growth becomes significantly and highly negative, once we consider the effect of migration on development. Introducing the variable: ‘worker remittances per total GNP’ into the above equations, we achieve for the countries with complete data on worker remittances the following results:
Table 2.2: The Pearson-Bravais-correlations of worker remittances per GDP with variables of economic growth
correlation with migration remittances |
|
Govex (government expenditures) |
0,26 |
war/internal war |
0,24 |
government consumption |
0,19 |
aid per capita |
0,18 |
public investment |
0,17 |
refugees per population |
0,15 |
violation of political Rights |
0,14 |
MPR (military personnel ratio) |
0,14 |
violation of civil rights |
0,09 |
deforestation |
0,05 |
LEX 1990 (life expectancy) |
-0,03 |
SIPE-Index (Social Insurance Programme Experience Index) |
-0,07 |
HDI (Human Development Index) |
-0,07 |
GNP growth 80-92 |
-0,07 |
mean years of schooling |
-0,09 |
gender empowerment |
-0,11 |
reserves per GDP |
-0,13 |
social security expenditures |
-0,14 |
years of female voting |
-0,17 |
Source: our own calculations from worker remittances and other UNDP structural data for n = 123 countries of the world system, bivariate correlations according to EXCEL 5.0
Migration indeed is connected with state capitalism, with aid dependency; and world political instability, war, and refugee crises enhance the migration potential. But economic dependence from migration is also characterized typically by the absence of what characterizes the leading social welfare states in Europe: feminism (gender empowerment, years of female voting), high social security expenditures et cetera. The multivariate results now show the interaction of the migration process with long-run development:
Table 2.3: International dependency and its effects on growth and adjustment, allowing for the influence of the migration process (n=64 countries with complete data on worker remittances)
MNC PEN73 |
Govex |
Trade Dep |
social sec |
UN-membery |
Women Parl |
Women %LF |
ln PCI |
ln PCI^2 |
ln(MPR+1) |
Fertility Rate |
migration |
constant |
|
adjustment |
-0,143 |
-1,13 |
0,525 |
0,589 |
-11,5 |
-0,018 |
-0,033 |
-0,05 |
0,115 |
-0,02 |
-0,02 |
-0,004 |
60,89 |
0,049 |
0,207 |
1,195 |
0,404 |
6,05 |
0,026 |
0,05 |
0,027 |
0,081 |
0,017 |
0,036 |
0,003 |
22,69 |
|
0,56 |
|||||||||||||
5,402 |
51 |
||||||||||||
t-Test |
-2,897 |
-5,452 |
0,439 |
1,456 |
-1,901 |
-0,671 |
-0,667 |
-1,852 |
1,426 |
-1,191 |
-0,552 |
-1,278 |
|
MNC PEN73 |
Govex |
Trade Dep |
social sec |
UN-membery |
Women Parl |
Women %LF |
ln PCI |
ln PCI^2 |
ln(MPR+1) |
Fertility Rate |
migration |
constant |
|
growth |
-0,119 |
-1,42 |
1,832 |
0,42 |
-9,152 |
-0,01 |
-0,008 |
-0,041 |
0,063 |
-0,019 |
-0,017 |
-3E-04 |
53,4 |
0,046 |
0,194 |
1,12 |
0,379 |
5,671 |
0,025 |
0,047 |
0,025 |
0,076 |
0,016 |
0,034 |
0,003 |
21,27 |
|
0,614 |
|||||||||||||
6,767 |
51 |
||||||||||||
t-Test |
-2,569 |
-7,307 |
1,636 |
1,108 |
-1,614 |
-0,407 |
-0,179 |
-1,637 |
0,827 |
-1,166 |
-0,51 |
-0,113 |
Legend: As in all EXCEL 5.0 outprints in this work, first row: unstandardized regression coefficients, second row: standard errors, last row: t-Test. The values immediately below the standard errors are R^2 (third row, left side entry), F, and degrees of freedom (fourth row). The above results were achieved by inserting international migration remittances data (remittances per GDP) into our cross-national growth and development equations. Only countries with complete data from the original n=123 sample of OECD and underdeveloped countries were used.
Migration does not positively bring about growth or adjustment; but is part and parcel of the state-class dominated structures that rely on state expenditures, militarization, and the influx of foreign capital. The greatest proponents of mass migration from the semi-periphery and periphery are in reality those very social strata, that represent the powerful urban power monopolies at home: instead of bringing their monopolies under the discipline of the market and allowing their agricultural regions to prosper under a system of export-led growth and mass-demand at home, they are inclined to send a considerable part of their talented work-force abroad so that it does not constitute any threat to the elites’ privileged social position at home. State sector expenditures and a reliance on foreign aid will be part and parcel of a such a migration-driven development model. The migration-state sector effect described above is significant at the 12.5% level and narrowly misses the 10% mark. 61.4% of economic growth are explained by our migration-centered equation. Although small and open economies - especially in Europe (like Austria) - tend towards higher economic growth rates and a less painful structural adjustment towards the realities of the evolving post-1982/89 world economic and social order, it stands out very clearly, that under due consideration for the effects of migration on growth, the critique of the state sector under conditions of present day EU spending patterns in agricultural subsidies et cetera become all the more relevant.
Our point for transition phases could be also dramatically underlined by a comparison of countries like Austria today with the future EU member country Poland tomorrow. According to IOM 1998, 36% of adults in the Ukraine would like to work for a few months abroad, 19% of them in Poland. With a labor force participation ratio of 50%, this makes 50718000 inhabitants times 0.50 labor force participation rate times 0.19 Ukrainian migration target figure for Poland times 0.36 Ukrainian temporary migration potential, i.e. in all 3.42% percent 50718000 inhabitants, i.e. 1.7 million seasonal laborers from the Ukraine, if Poland abolishes all border controls and permits the free flow of labor upon Ukrainian EU-accession.
Up to now, our predictions were mainly directed against the migration optimists. Where we distinguish ourselves from a generalized migration pessimism is in the hypothesis about the possibility of a long-run interrelation between human development and migration propensity. But this hypothesis would presuppose a very thorough human capital effort on the part of the accession countries, similar to the one to be observed in Spain under Felipe Gonzales. As already predicted by Rostow and others, migration is also closely connected to the tendencies of the Kondratieff cycle, as is to be seen from the following Graph:
Graph 2.2: migration balances and the Kondratieff cycle
Legend: economic growth (left hand scale) and migration balances from Eastern Europe (right hand scale) during the Kondratieff cycle from 1950 onwards.
Under such a Gonzales scenario, slowly, Eastern Europe’s outward migration potential could recede, as the countries could become immigration regions themselves, like Southern Europe before:
Graph 2.3: Eastern and Southern European migration
Legend: This graph compares the results from the above graph (economic growth, left-hand scale) with the migration balances in Eastern and Southern Europe (right hand scale).
Southern Europe became an immigration region long ago, and tightened its borders, as East Central Europe should most probably tighten its own borders:
Graph 2.4: human development migration thresholds
Legend: human development index (left hand scale) and outward migration balance (right hand scale). The darker non-linear trend line (‘polynomial, south-migration’) indicates migration balances for Europe’s South, while lighter trend line (‘polynomial, Spain) indicates the human development experience of Spain since 1960 (left-hand scale). The straight trend line is the probable course of Polish human development. It reaches the 0.900-human-development-threshold for migration certainly by the end of the century (last UNDP HDR Poland 1998 published measurement 0.883); the European South became a net importer of labor after reaching these human development levels. The graph, as before, combines data from this study and data about the globalization of migration from IFRI (1998). The economic cycle in Eastern Europe is time-lagged in comparison to the world economic cycle. Southern Europe becomes a major immigration region; whose importance grows with the downswing of the world economic cycle. During an upswing, immigration to Europe’s South will decline. The data series again starts with 1950. The last graph compares the migration balance in the European South with the evolution of Spain’s UNDP Human Development Index since 1960. The graph shows the two migration policy thresholds of HDI = 0.500 and HDI = 0.800 and compares the Spanish HDI performance over time with the UNDP figures for Poland. Not before long, Poland could become - according to a Gonzales scenario - a net immigration country, reaching a human development index of 0.900. It should be emphasized that, due to regional inequalities, 12 regions (former voivodships) in Poland are still below the 0.8 threshold. They will still provide a reservoir of considerable migration potential for years to come.
It can also be shown, that the propensity to migrate is a function of the Human Development Index of a society, and that migration is connected to the redistribution struggles in world society, described in this book. Two data series are used here to test this hypothesis. In the following, we will deal with the issues of Polish migration as a case study for the effects of migration on a periphery country. Together with Italy and Greece, Poland is one of the main sources of international migration from Europe over centuries. Between 1950 and 1990, more than 1.1 million Poles were registered officially as emigrants (UN ECE, 1999). In Graph 2.5 we show the trade-off between the Human Development Index and migration propensity in 49 Polish voivodships (provinces). For many reasons, Poland can be regarded here as the key to the understanding of the problems of the entire region of East Central Europe. For one, Poland’s population size of 38.7 million inhabitants accounts for a large part of the entire region. In addition, Poland’s case can be regarded as the most well-documented case of the region. By following a ‘Gonzales’ strategy, indeed it could, like Spain, overcome the outward-migration pressures, still prevalent in society:
Graph 2.5: the trade-off between migration and human development in 49 Polish voivodships
Legend: Polish voivodship migration propensity (y-axis) is being explained by the human development index of a voivodship (x-axis). Migration propensity of a province is measured by the migration balance of a province * 100 divided by the number of inhabitants of the province (thousands). Migration balance data: Polish Central Statistical Office; Human Development Index: UNDP Poland (1996). As a note of caution, it should be emphasized, though, that at present only Warsaw surpasses the 0.9 threshold (UNDP, HDR Poland, 1998 figures).
By neglecting the poor and backward regions, Polish and East European post-1989 elites up to now did more often than not really address the issues, leading towards mass migration. A recent UN study on Polish migration says:
‘Assuming no significant or dramatic departure from the present course of political and economic reforms in Poland, three important trends in international migration might be predicted for the near future: 1) continuing strong pressure to emigrate to overseas countries, 2) rising numbers of workers seeking short-term employment in Germany and other countries of Western Europe, and 3) increasing pressure to immigrate to Poland from the states of the former USSR’ (UN ECE, 1998)
But with a possible the rise of the Polish Human Development Index, dependent upon a thorough human development policy, migration propensity would decrease, and the country would become a net importer of labor. But as it is to be seen from the above graph, a number of regions (indeed the majority) will be first faced by a rising tendency towards outward migration - the experience of Warsaw, Krakow, or Poznan cannot be generalized. In other words: successful regional development will be the key one day to perhaps shortening the EU-transition phases for Poland.
Our following analysis now shows the relationship between the three-layer-structure of the world system in the sense of Arrighi’s theory and the structure of transnational migration. Far from being a strategy of world economic ascent, mass migration is a phenomenon at the periphery, and the poorer and richer semi-periphery level. Graph 2.6 shows the trade off between migration dependence of a society (as measured by the balance of worker remittances per GDP) and the development level (PPP GDP per capita in % of the European Union average) (a) and the Human Development Index (b), again supporting our above hypotheses:
Graph 2.6: migration propensity and development on a world scale:
a) PPP GDP per capita in % of the European Union average (x-axis) and balance of worker remittances (y-axis)
Legend: real purchasing power of a country in percent of the European Union average real purchasing power (each measured in PPP $) (x-axis) and the balance of worker remittances per GDP in % (y-axis). Source: our own compilations and calculations from UNDP Human Development Report. Note the three-layer structure with three summits.
Legend: x-axis: the Human Development Index of a country of the world system. Else: see above. Note again the three-layer structure that is similar to the three-layer structure of world society.
The application of GDP or GDP PPP data alone could be very misleading in determining ‘migration policy thresholds’, viz. the negotiations between the (East) Central European accession countries and the European Union. The Human Development Index by far better reflects the overall social situation of a country than the mere application of real purchasing power parity rate GDP data. We look therefore at the historic trajectory of human development in the world’s main sending countries:
Graph 2.7: human development in migration societies
Legend: data analysis and projections about the human development trajectory of migration societies in the world system since 1990. Y-axis: the Human Development Index. Source: our own compilations from UNDP HDR, 1997 and IFRI, 1998. The number of people who emigrated from these countries were (millions of people)
Mexico |
7.1 |
Bangladesh |
5.0 |
Philippines |
4.5 |
Afghanistan |
4.2 |
Pakistan |
2.9 |
Vietnam |
2.2 |
Algeria |
1.8 |
Egypt |
1.5 |
Poland |
1.4 |
Poland already achieved a development level (measured by the human development index) that corresponds to the levels of Austria in the late 1960s, Spain in the mid 1970s, and Portugal in the late 1980s.
Without doubt, migration propensity is highest at a human development level that corresponds to the value 0.6 to 0.5 of the HDI (Human Development Index); i.e. countries like the Ukraine, the Philippines, Indonesia, Mongolia, Albania, Armenia, China, Egypt, El Salvador, Morocco, Vietnam. This hypothesis would also correspond to the every-day experience of any migration official around the world. Countries in the vicinity of HDI = 0.900 or more, like Portugal, Chile, Singapore, Italy, or Greece, cease to be the source of mass migration. The three-layer structure corresponds also to careful interpretation of different migration ‘waves’: the migration of rural laborers, the migration of industrial workers, the migration of service-personnel, and the migration of intellectuals at all three phases.
Instead of leveling-off international hierarchies, migration is indeed, as Samir Amin foresees it, one of the 5 pillars of international inequality, cementing the unequal positions in the world system instead of leveling them off. It can be shown, that a large number of today’s accession candidates already fulfill the conditions of the West European countries by 1980, while today’s Croatia, Latvia, Lithuania, Moldova, Romania and Ukraine are at the level of Portugal 1980, Bulgaria, Poland, and Turkey reach the level of Greek and Spanish human development in 1980, while Hungary and Slovakia are already at the level of Austria, Belgium, Finland, Ireland and Italy in 1980. Slovenia and the Czech Republic reach already a level of human development that is equal to that of Denmark, Germany, and the Netherlands in 1980. (Source: our own compilations from UNDP Human Development Report, 1997. The contemporary human development differences in Europe range from France = 0.946 to Albania = 0.655. Thus, they are as large as those between, say, USA (0.942) and Peru (0.717)).
At any rate, it would be naive to assume that aid can be a substitute for structural policy to overcome the migration propensity of a society, which, in the end, is nothing but the reaction of a semi-periphery or a periphery to the ups and downs of three-layer structure of the international system in the Arrighian sense. In fact, aid recipients tend to be migratory labor exporters; and aid seems to be unable to reduce long-term migration propensity; on the contrary. The weak trade-off (R^2 = only 4.4%) between aid and migration propensity is the following:
Graph 2.8: aid per capita received and migration propensity
Legend: aid per capita (x-axis) and balance of worker remittances per GDP (y-axis) in the countries of the world system. A negative figure for aid per capita means, that a country is a net donor country. Source: our own compilations from UNDP HDR, various years. The graphical presentation excludes the out-layer Lesotho. Aid does not prevent migration.
There are two important, further caveats in this context, going much beyond the year 2010, when East Central Europe long ago will have become an integral part of the European Union. One is the fundamental question - do we really talk about the most probable places of future outward migration, when concentrating on the European East, and not so much on the Balkans, the Middle East and North Africa? And the other is fairly strong evidence about the cyclical character of the migration process. Both in demographic as well as in sociological terms, much of West European fears about Central East European migration at least would tend to conceal the real, still bigger issues of the future migration processes. An analysis of world population growth trends shows that Africa, West Asia and Southeast-Asia become the real future sending countries, while the demographic structure of East Central Europe more and more resembles the countries of Western Europe. Schengen, in a way, is likely to control these migration flows for some years. But after? It is entirely possible, that outward migration pressure from Sub-Saharan Africa and West, Central and Southeast Asia in turn will have long-lasting effects on the countries of Eastern Europe, Turkey, and the Arab countries. For that reason, East Central Europe already by now should be integrated in a pan-European system of migration reception from third countries, that could be modeled for all practical purposes and all what we have said above notwithstanding, around the present-day Canadian immigration system. The East Central European accession countries must be early on brought into this system of selective immigration and border management. We also think that mass migration, especially illegal migration, is closely inter-linked with the changing structure of the elites in the capitalist world system away from ‘legal’ to ‘semi-legal’ and ‘illegal’ business undertakings. Extraction and protection money, forced prostitution, all belong nowadays to a structure, which will increasingly affect the reform countries of East and Central Europe, when they themselves will become targets of mass migration.
However, the above mentioned tendencies of a possible positive human development in the region of East Central Europe must not be misunderstood as an argument against transition phases for European Union accession of these countries. On the contrary: our evidence shows, that the more long-term positive developments, mainly caused by a rise in the Human Development Index, are compounded by the short-and medium term fluctuations of the business cycle and the restructuring problem of heavy industry.
Some further generalizations can be risked, at least tentatively, from the Polish case. Our evidence at least suggests, that the neo-liberal growth strategy, prevalent in Poland and elsewhere in the region after 1989, was not really able to push human development upwards, so the tendency for outward migration shows only a very slow linear down-ward trend. Recent data series from the Polish Central Statistical Office also show, that mass dismissals in industry might be on the rise again, due to industrial restructuring:
Graph 2.9: industrial restructuring in Poland
Source: our own compilations from Polish Central Statistical Office, Registered Unemployment in Poland
Polish migration data seem to confirm the hypothesis, that migration is a cyclical as well as a structural phenomenon, as the following data series from Central Statistical Office data clearly shows:
Table 2.4: Polish official migration data
Polish migration in 000 |
|
1980 |
22,7 |
1981 |
23,8 |
1982 |
32,1 |
1983 |
26,2 |
1984 |
17,4 |
1985 |
20,5 |
1986 |
29 |
1987 |
36,4 |
1988 |
36,3 |
1989 |
26,6 |
1990 |
18,4 |
1991 |
21 |
1992 |
18,1 |
1993 |
21,3 |
1994 |
25,9 |
1995 |
26,3 |
1996 |
21,3 |
Source: IBnGR Gdansk, Regionalne rynki pracy w procesie integracji Unia Europejska, 16/1998
Graph 2.10 now confirms the cyclical hypothesis:
Graph 2.10: Polish migration cycles
Source: our own compilations from IBGR, above. Id est: Optimists must assume, that Polish migration has a downward trend, compared to the 1980s. One optimistic interpretation (implicit linear downward trend) has only 3% explanatory potential; another one - the most favorable possible interpretation for the Polish government - a 2nd order polynomial expression, yields only 7%, while a cyclical hypothesis, proposed by the present author, yields up to 60% in terms of R^2
One might be tempted to project earlier Polish Ministry of the Interior estimates, quoted in the Gdansk Study, onto these more recent official data, since unofficial migration exceeds by far official Polish migration, because illegal migration by far exceeds legal migration:
Graph 2.11: official migration data and the SERP-data-base of the MSW in the 1980s
Source: our own compilation from the IBGR study, quoted above
This yields the following hypothetical data series:
Table 2.5: Polish migration data under the assumption of the SERP-data of the Polish Ministry of the Interior for the 1980s, projected onto the 1990s
Polish migration. Legal and illegal migration, applying the multiplication factor, arising from the difference between the SERP-data-of the Polish MSW and official data for the 1980s, to the official data series of the 1990s in 000 people |
|
1980 |
88,53 |
1981 |
92,82 |
1982 |
125,19 |
1983 |
102,18 |
1984 |
67,86 |
1985 |
79,95 |
1986 |
113,1 |
1987 |
141,96 |
1988 |
141,57 |
1989 |
103,74 |
1990 |
71,76 |
1991 |
81,9 |
1992 |
70,59 |
1993 |
83,07 |
1994 |
101,01 |
1995 |
102,57 |
1996 |
83,07 |
This yields the following graphical results:
Graph 2.12: Polish migration data
The very long term tendencies of Polish migration in world capitalism are however the following: war and world political as well as Polish internal crises (1956, 1968, 1970, 1980/81) pushed migration upwards, while in the long run - after the 1960s - migration is a pro-cyclical function of world capitalist growth:
Graph 2.13: world capitalism, global wars and Polish migration
Legend: Our own compilations from IFRI (1998); Goldstein (1989) and UN ECE and UN Population Fund, 1998
Polish official and unofficial migration, then, is closely connected to the fluctuations of world capitalism. It does not matter here, whether we use data for the official migration or estimates for the legal plus the illegal migration:
Graph 2.14: Polish migration and world growth
Legend: legal migration per year (left hand scale) and growth rate of the capitalist world economy (right hand scale). Data from IBGR (migration) and below (growth rate of the capitalist world economy)
Only very rapid growth that dries up labor reserves in Poland itself will prevent Polish migration from rising again. Graph 2.15 now shows some of the projections, which are to be derived from the official and the SERP-factor-corrected data series. At any rate, after 2008 there also would be support for the hypothesis, that Polish migration would really and seriously begin to fall under the assumption of a non-linear, 2nd order time-series polynomial trade-off for Polish migration:
Graph 2.15: Polish migration projections and possible transition paths for EU accession
Legend: yearly outward migration in thousands, under the assumption of a 2nd order polynomial expression, applied to the original data provided by the IBGR study
Migration will fluctuate on and on in the course of development, until finally, the negative trends in the age-structure in Western Europe will provide the answer to the question. The most optimistic assumption, a polynomial trend, will lead towards a significant decrease in Polish migration.
There are two important, further caveats in this context, going much beyond the year 2010, when East Central Europe long ago will have become an integral part of the European Union. One is the fundamental question - do we really talk about the most probable places of future outward migration, when concentrating on the European East, and not so much on the Balkans, the Middle East and North Africa? And the other is fairly strong evidence about the cyclical character of the migration process. Both in demographic as well as in sociological terms, much of West European fears about Central East European migration at least would tend to conceal the real, still bigger issues of the future migration processes. An analysis of world population growth trends shows that Africa, West Asia and Southeast-Asia become the real future sending countries, while the demographic structure of East Central Europe more and more resembles the countries of Western Europe. Schengen, in a way, is likely to control these migration flows for some years. But after? It is entirely possible, that outward migration pressure from Sub-Saharan Africa and West, Central and Southeast Asia in turn will have long-lasting effects on the countries of Eastern Europe, Turkey, and the Arab countries. For that reason, East Central Europe already by now should be integrated in a pan-European system of migration reception from third countries, that could be modeled for all practical purposes and all what we have said above notwithstanding, around the present-day Canadian immigration system. The East Central European accession countries must be early on brought into this system of selective immigration and border management. We also think that mass migration, especially illegal migration, is closely inter-linked with the changing structure of the elites in the capitalist world system away from ‘legal’ to ‘semi-legal’ and ‘illegal’ business undertakings. Extraction and protection money, forced prostitution, all belong nowadays to a structure, which will increasingly affect the reform countries of East and Central Europe, when they themselves will become targets of mass migration.
Then, however, politics are faced with the stark realities of the old-age crisis in mature societies in full swing. Europe in roughly the borders of the future European Union will grow by only 1.7 million people, 1.1 million of which will be Poles, much of the rest the children of the former migration generations in the European center countries. The South and the Southeast as well as the East of the continent will be faced by a dramatic population decline, combined with a vast population pressure from the Southern rim of the Mediterranean. Turkey alone will add another 17.8 million people and will number by then 78.6 million people. Egypt will increase its population to 85.4 million people:
1995 |
2015 |
change in millions |
change in % of EU15 pop increase |
|
EU 15 |
371,6 |
373,8 |
2,2 |
100 |
Czech R |
10,3 |
9,9 |
-0,4 |
-18,2 |
Hungary |
10,1 |
9,1 |
-1 |
-45,5 |
Poland |
38,6 |
39,7 |
1,1 |
50 |
Slovenia |
1,9 |
1,8 |
-0,1 |
-4,5 |
Estonia |
1,5 |
1,3 |
-0,2 |
-9,1 |
former USSR, former Yugoslavia, former communist countries in the Balkans, Slovakia |
333,1 |
336,1 |
3 |
136,4 |
Turkey |
60,8 |
78,6 |
17,8 |
809,1 |
Algeria |
28,1 |
41,6 |
13,5 |
613,6 |
Tunesia |
9 |
12,1 |
3,1 |
140,9 |
Egypt |
62,1 |
85,4 |
23,3 |
1059,1 |
Morocco |
26,5 |
35,6 |
9,1 |
413,6 |
Libyan Jam. |
5,4 |
10,1 |
4,7 |
213,6 |
Eastern 5-enlargement |
62,4 |
61,8 |
-0,6 |
-27,3 |
Islamic southern Mediterranean rim |
191,9 |
263,4 |
71,5 |
3250 |
Legend: our own compilation from UNDP, 1998
Poland’s population increase in the period until 2015 will be more than 1.1 million people who will correspond to a theoretical 50% of the entire population increase of the whole of the present European Union. There will be a dramatic population crisis in most of the former USSR, and in Southern and Southeastern Europe. Russia’s demographic depression will be as dramatic as the present economic depression, with a decline of more than 10.4 million people projected until 2015 from the present 148.5 million people. But all this will be nothing compared to the huge demographic pressure that builds up on the southern rim of the Mediterranean, where more than 260 million people will by then await the cross-cultural enlargement of the European Union.
The geography of unequal development in Poland, 1992 - 95
The Human Development Report Poland, 1998, published by the Warsaw UNDP office in late winter 1999, provides a wealth of information on the logic of regional development in Poland. Unfortunately, social science date are calculated and published with a great time-lag, but the now available data again confirm the picture of regional inequality in the 1990s, already established above. A successful regional development, as we have shown, will be also the cornerstone of any successful reduction of the tendency towards migration in the early 21st Century; and - even more important - it could bring a final turnaround in the way from Poland to overcome its semi-peripheral status. What, then, is the brief empirical verdict that can be tentatively established on the basis of the recently made-available data?
First of all, the UNDP Polish report again mentions the regional HDIs for the 49 regions of the country that existed until 31st of December, 1998. Only a fraction of them, Warsaw, Krakow, Poznan, and Wroclaw, were in 1995 already above the average for Portugal in 1994, then and now the poorest country in the European Union. It will be a decisive task for the next few years to raise Poland’s development level to the 0.900 HDI threshold, beyond which the tendency for outward migration will in all probability tend to decline:
Table 2.6 regional Human Development Indices in Poland, 1995
Voivodship |
Human Development Index, 1995 |
percentage difference to the average value for Portugal, 1994 (HDI = 0.890) |
percentage difference to the average value for Italy, 1994 (HDI = 0.921) |
war |
0,909 |
+2,13 |
-1,3 |
bialpodlas |
0,77 |
-13,48 |
-16,4 |
bistock |
0,84 |
-5,62 |
-8,79 |
bielski |
0,878 |
-1,35 |
-4,67 |
bydg |
0,878 |
-1,35 |
-4,67 |
chelm |
0,761 |
-14,49 |
-17,37 |
ciech |
0,777 |
-12,7 |
-15,64 |
czesto |
0,835 |
-6,18 |
-9,34 |
elblas |
0,864 |
-2,92 |
-6,19 |
gdan |
0,885 |
-0,56 |
-3,91 |
gorzo |
0,837 |
-5,96 |
-9,12 |
jelen |
0,827 |
-7,08 |
-10,21 |
kalis |
0,833 |
-6,4 |
-9,55 |
kato |
0,875 |
-1,69 |
-4,99 |
kiele |
0,816 |
-8,31 |
-11,4 |
konin |
0,848 |
-4,72 |
-7,93 |
kosza |
0,83 |
-6,74 |
-9,88 |
krak |
0,905 |
+1,69 |
-1,74 |
krosn |
0,804 |
-9,66 |
-12,7 |
legni |
0,868 |
-2,47 |
-5,75 |
leszcz |
0,877 |
-1,46 |
-4,78 |
lubel |
0,877 |
-1,46 |
-4,78 |
lomzy |
0,761 |
-14,49 |
-17,37 |
lodz |
0,883 |
-0,79 |
-4,13 |
nowosad |
0,774 |
-13,03 |
-15,96 |
olszt |
0,821 |
-7,75 |
-10,86 |
opol |
0,864 |
-2,92 |
-6,19 |
ostrol |
0,795 |
-10,67 |
-13,68 |
pilsk |
0,84 |
-5,62 |
-8,79 |
piotrk |
0,861 |
-3,26 |
-6,51 |
plock |
0,88 |
-1,12 |
-4,45 |
pozn |
0,895 |
+0,56 |
-2,82 |
przem |
0,775 |
-12,92 |
-15,85 |
radom |
0,858 |
-3,6 |
-6,84 |
rzesz |
0,858 |
-3,6 |
-6,84 |
siedle |
0,778 |
-12,58 |
-15,53 |
sierad |
0,805 |
-9,55 |
-12,6 |
skiernie |
0,805 |
-9,55 |
-12,6 |
slupsk |
0,779 |
-12,47 |
-15,42 |
suwal |
0,808 |
-9,21 |
-12,27 |
szczec |
0,88 |
-1,12 |
-4,45 |
tarnbrzes |
0,836 |
-6,07 |
-9,23 |
tarnow |
0,804 |
-9,66 |
-12,7 |
torun |
0,845 |
-5,06 |
-8,25 |
walbrz |
0,794 |
-10,79 |
-13,79 |
wlocl |
0,781 |
-12,25 |
-15,2 |
wroc |
0,897 |
+0,79 |
-2,61 |
zamoj |
0,76 |
-14,61 |
-17,48 |
zielono |
0,877 |
-1,46 |
-4,78 |
Voivodship |
Human Development Index, 1995 |
percentage difference to the average value for Portugal, 1994 (HDI = 0.890) |
percentage difference to the average value for Italy, 1994 (HDI = 0.921) |
Source: our own compilations from UNDP Warsaw Office, HDR Poland 1998
Rapid development in Poland increased the per capita income of the different regions, but in a very unequal fashion. Although growth positively affected, say, both Zamosc and Warsaw, the real income increase for Warsaw was more than 2000 $ above the expected trend, while Zamosc and the other poor, mainly Eastern provinces were largely much slower in their income increases. In the short run, such a development might be viewed by some as positive; but development theory suggests that in the long run such instabilities are quite destabilizing. The relative differences between the richest and the poorest parts of Poland widened, contributing towards a feeling of ‘exclusion’ from the fruits of development. If there already was a ‘Polska A’ and a ‘Polska B’ in 1992, there was even more so such a division of the country in 1995 (and most probably, still further on in 1999):
Table 2.7: regional per capita incomes in Poland, 1992 - 1995
voivodship |
per capita income 95 in PPS$ |
per capita income 92 |
trend value: 92->95 (EXCEL Trend) |
regression residual (growth privilege) |
warsaw |
11558 |
6418 |
9511,4 |
2046,6 |
bialpodlas |
4046 |
3105 |
4625,8 |
-579,8 |
bistock |
5097 |
3698 |
5500,3 |
-403,3 |
bielski |
6269 |
3950 |
5871,9 |
397,09 |
bydg |
6727 |
4635 |
6882,1 |
-155,1 |
chelm |
3877 |
3458 |
5146,4 |
-1269 |
ciech |
4154 |
3074 |
4580,1 |
-426,1 |
czesto |
5128 |
3479 |
5177,3 |
-49,34 |
elblas |
5835 |
3682 |
5476,7 |
358,3 |
gdan |
7384 |
4578 |
6798 |
586 |
gorzo |
5310 |
3381 |
5032,8 |
277,18 |
jelen |
5220 |
3948 |
5869 |
-649 |
kalis |
5161 |
3237 |
4820,5 |
340,53 |
katowice |
7995 |
4532 |
6730,2 |
1264,8 |
kiele |
4621 |
3002 |
4473,9 |
147,08 |
konin |
5535 |
3180 |
4736,4 |
798,59 |
kosza |
4996 |
3417 |
5085,9 |
-89,91 |
krak |
6927 |
5199 |
7713,8 |
-786,8 |
krosn |
4473 |
2927 |
4363,3 |
109,68 |
legni |
6578 |
4903 |
7277,3 |
-699,3 |
leszczno |
6833 |
3485 |
5186,2 |
1646,8 |
lubel |
5546 |
3634 |
5405,9 |
140,09 |
lomzy |
3914 |
2877 |
4289,6 |
-375,6 |
lodz |
6603 |
4405 |
6542,9 |
60,117 |
nowosad |
3966 |
2729 |
4071,3 |
-105,3 |
olszt |
4872 |
3632 |
5403 |
-531 |
opol |
5717 |
3961 |
5888,1 |
-171,1 |
ostrol |
4429 |
2775 |
4139,2 |
289,83 |
pilsk |
5337 |
3180 |
4736,4 |
600,59 |
piotrkow tribunalski |
5788 |
4731 |
7023,6 |
-1236 |
plock |
13275 |
9091 |
13453 |
-178,2 |
pozn |
8165 |
5843 |
8663,5 |
-498,5 |
przem |
4035 |
2730 |
4072,8 |
-37,81 |
radom |
5560 |
3417 |
5085,9 |
474,09 |
rzesz |
5257 |
3833 |
5699,4 |
-442,4 |
siedle |
4125 |
2996 |
4465,1 |
-340,1 |
sierad |
4713 |
3059 |
4558 |
155,03 |
skiernie |
4650 |
2947 |
4392,8 |
257,19 |
slupsk |
4213 |
3047 |
4540,3 |
-327,3 |
suwal |
4689 |
2704 |
4034,5 |
654,53 |
szczec |
7220 |
5086 |
7547,1 |
-327,1 |
tarnbrzes |
5164 |
3159 |
4705,4 |
458,56 |
tarnow |
4494 |
3553 |
5286,5 |
-792,5 |
torun |
5189 |
3543 |
5271,7 |
-82,72 |
walbrz |
4613 |
3042 |
4532,9 |
80,095 |
wlocl |
4346 |
3021 |
4501,9 |
-155,9 |
wroclaw |
7644 |
4417 |
6560,6 |
1083,4 |
zamoj |
3807 |
2840 |
4235 |
-428 |
zielona gora |
6011 |
4783 |
7100,3 |
-1089 |
voivodship |
per capita income 95 in PPS$ |
per capita income 92 |
trend value: 92->95 (EXCEL Trend) |
regression residual (growth privilege) |
Source: see Table 2.6, above
Disturbing pictures emerge from this Table, indeed, when we give these data a second thought. Regional centers grow in power, but their hinterland stagnates. The axis Poznan - Wroclaw had a very remarkable growth, but Zielona Gora, on its western backdoor, was exceptionally slow in catching the benefits of growth. The same thing happens with Piotrkow Tribunalski, half way between Katowice/Opole/Czestochowa and Warsaw. And a similar picture emerges from Chelm, the hinterland of the growth center Lublin. Tourism (and perhaps also cross-border trade and smuggling) explain the relative success of Suwalki, which managed to get away from its very poor position in 1992. Suwalki - with its Mazurian lakes and its ‘East Prussian’ past will most probably make it - but Biala Podlaska, Chelm and Zamosc will become the new focus of stagnation in a changing Poland. Other regions, like Walbrzych and Jelenia Gora, will have to struggle hard to create a regional profile. The problem of the recently introduced regional reform is of course, that it still increases the power of mighty ‘regional centers’, thus creating a structure, where - in the end - Poland will have the following growth poles and such a stagnating ‘hinterland’:
Szczecin - Western Pommerania
Gdansk - Central Pommerania and Warmia/Mazuria (with the exception of the touristic ‘enclaves’)
Poznan/Wroclaw - the outer western, southern and eastern ring of this growth pole
Upper Silesia - Krakow - the northern and eastern outer ring
Lublin - the eastern hinterland
Warsaw - the eastern and northern perimeter
These developments can be highlighted by further statistical analyses of the development distances between the richest and the poorest provinces. While Warsaw, for example, was 2.37 times richer than the poorest region in 1992, the difference widened in just two years to 3.04, and will certainly have gone up further in the last 4 years:
Table 2.8: regional development distances in Poland, 1995
voivodship |
development distance to the poorest province, 1995 (poorest voivodship = 1.0) |
development distance to the poorest province, 1992 (poorest voivodship = 1.0) |
growth or decline of the development distance ((1)-(2)) from 1992 to 1995 |
war |
3,04 |
2,37 |
0,67 |
bialpodlas |
1,06 |
1,15 |
-0,09 |
bistock |
1,34 |
1,37 |
-0,03 |
bielski |
1,65 |
1,46 |
0,19 |
bydg |
1,77 |
1,71 |
0,06 |
chelm |
1,02 |
1,28 |
-0,26 |
ciech |
1,09 |
1,14 |
-0,05 |
czesto |
1,35 |
1,29 |
0,06 |
elblas |
1,53 |
1,36 |
0,17 |
gdan |
1,94 |
1,69 |
0,25 |
gorzo |
1,39 |
1,25 |
0,14 |
jelen |
1,37 |
1,46 |
-0,09 |
kalis |
1,36 |
1,2 |
0,16 |
kato |
2,1 |
1,68 |
0,42 |
kiele |
1,21 |
1,11 |
0,1 |
konin |
1,45 |
1,18 |
0,27 |
kosza |
1,31 |
1,26 |
0,05 |
krak |
1,82 |
1,92 |
-0,1 |
krosn |
1,17 |
1,08 |
0,09 |
legni |
1,73 |
1,81 |
-0,08 |
leszcz |
1,79 |
1,29 |
0,5 |
lubel |
1,46 |
1,34 |
0,12 |
lomzy |
1,03 |
1,06 |
-0,03 |
lodz |
1,73 |
1,63 |
0,1 |
nowosad |
1,04 |
1,01 |
0,03 |
olszt |
1,28 |
1,34 |
-0,06 |
opol |
1,5 |
1,46 |
0,04 |
ostrol |
1,16 |
1,03 |
0,13 |
pilsk |
1,4 |
1,18 |
0,22 |
piotrk |
1,52 |
1,75 |
-0,23 |
plock |
3,49 |
3,36 |
0,13 |
pozn |
2,14 |
2,16 |
-0,02 |
przem |
1,06 |
1,01 |
0,05 |
radom |
1,46 |
1,26 |
0,2 |
rzesz |
1,38 |
1,42 |
-0,04 |
siedle |
1,08 |
1,11 |
-0,03 |
sierad |
1,24 |
1,13 |
0,11 |
skiernie |
1,22 |
1,09 |
0,13 |
slupsk |
1,11 |
1,13 |
-0,02 |
suwal |
1,23 |
1 |
0,23 |
szczec |
1,9 |
1,88 |
0,02 |
tarnbrzes |
1,36 |
1,17 |
0,19 |
tarnow |
1,18 |
1,31 |
-0,13 |
torun |
1,36 |
1,31 |
0,05 |
walbrz |
1,21 |
1,13 |
0,08 |
wlocl |
1,14 |
1,12 |
0,02 |
wroc |
2,01 |
1,63 |
0,38 |
zamoj |
1 |
1,05 |
-0,05 |
zielono |
1,58 |
1,77 |
-0,19 |
voivodship |
development distance to the poorest province, 1995 |
development distance to the poorest province, 1992 |
growth or decline of the development distance ((1)-(2)) from 1992 to 1995 |
Source: see Table 2.6, above
Increases in life expectancy and decreases in infant mortality however, were concentrated in the ‘Catholic’ Southeast of the country, while in terms of life expectancy, the West and North rather did badly:
Table 2.9: life expectancy increases over time, 1992 - 1995
voivodship |
life expectancy 95 |
life expectancy 92 |
trend value: 92->95 (EXCEL Trend) |
regression residual (efficiency of social and health policy |
warsaw |
72 |
71,43 |
71,666 |
0,3341 |
bialpodlas |
71,4 |
71,98 |
72,168 |
-0,768 |
bistock |
72,5 |
72,81 |
72,926 |
-0,426 |
bielski |
72,2 |
71,7 |
71,912 |
0,2876 |
bydg |
71,1 |
70,76 |
71,054 |
0,0457 |
chelm |
71,2 |
71,58 |
71,803 |
-0,603 |
ciech |
71,1 |
70,88 |
71,164 |
-0,064 |
czesto |
71,3 |
70,94 |
71,219 |
0,0814 |
elblas |
70,5 |
70,08 |
70,434 |
0,0665 |
gdan |
71,8 |
70,87 |
71,155 |
0,6453 |
gorzo |
71 |
70,72 |
71,018 |
-0,018 |
jelen |
70,3 |
70,32 |
70,653 |
-0,353 |
kalis |
71,3 |
71,23 |
71,483 |
-0,183 |
kato |
70,6 |
69,72 |
70,105 |
0,4951 |
kiele |
72,1 |
71,81 |
72,013 |
0,0872 |
konin |
71,2 |
71,1 |
71,365 |
-0,165 |
kosza |
71 |
70,66 |
70,963 |
0,037 |
krak |
72,5 |
71,85 |
72,049 |
0,4507 |
krosn |
72,6 |
72,25 |
72,414 |
0,1856 |
legni |
71 |
70,73 |
71,027 |
-0,027 |
leszcz |
71,6 |
71,36 |
71,602 |
-0,002 |
lubel |
72 |
71,8 |
72,004 |
-0,004 |
lomzy |
72,3 |
72,35 |
72,506 |
-0,206 |
lodz |
69,9 |
69,67 |
70,059 |
-0,159 |
nowosad |
72,7 |
72,12 |
72,296 |
0,4043 |
olszt |
71,4 |
71,16 |
71,419 |
-0,019 |
opol |
71,5 |
70,81 |
71,1 |
0,4001 |
ostrol |
71,6 |
71,85 |
72,049 |
-0,449 |
pilsk |
70,8 |
70,54 |
70,853 |
-0,053 |
piotrk |
71,1 |
70,98 |
71,255 |
-0,155 |
plock |
70,8 |
71 |
71,273 |
-0,473 |
pozn |
71,3 |
70,76 |
71,054 |
0,2457 |
przem |
72 |
71,54 |
71,766 |
0,2337 |
radom |
71,6 |
71,29 |
71,538 |
0,0619 |
rzesz |
73,4 |
72,5 |
72,643 |
0,7574 |
siedle |
71,9 |
72,08 |
72,259 |
-0,359 |
sierad |
71,9 |
71,57 |
71,794 |
0,1063 |
skiernie |
71,1 |
71,16 |
71,419 |
-0,319 |
slupsk |
70,9 |
70,53 |
70,844 |
0,0557 |
suwal |
71,5 |
71,7 |
71,912 |
-0,412 |
szczec |
70,6 |
70,22 |
70,561 |
0,0387 |
tarnbrzes |
72,6 |
72,17 |
72,341 |
0,2586 |
tarnow |
73 |
72,28 |
72,442 |
0,5582 |
torun |
71,1 |
70,59 |
70,899 |
0,2009 |
walbrz |
70,1 |
70,81 |
71,1 |
-1 |
wlocl |
70,6 |
70,07 |
70,424 |
0,1756 |
wroc |
71,7 |
71,13 |
71,392 |
0,308 |
zamoj |
72,2 |
72,12 |
72,296 |
-0,096 |
zielono |
70,6 |
70,49 |
70,808 |
-0,208 |
voivodship |
life expectancy 95 |
life expectancy 92 |
trend value: 92->95 (EXCEL Trend) |
regression residual (efficiency of social and health policy |
Source: see Table 2.6, above
The scatterplots show how the residuals from the above Tables are being determined by variables which are central to our approach of explaining migration and development. Both foreign capital penetration (in terms of the employment structure) as well as external migration contribute in the shape of an ‘U’ to ‘growth privileges’, showing that only beyond reaching certain levels of development there is a positive trade-off between foreign capital oriented strategies and growth and migration oriented development strategies and growth, while at lower levels even negative trade-offs between foreign capital domination, migration and development occur:
Graph 2.16: the key to Polish regional development success: foreign capital penetration, outward migration? A critical survey
Without Warsaw, the trade-off for foreign capital penetration becomes all the more questionable:
Graph 2.17 now shows the performance of Poland’s regions over time as measured by their Human Development Index, 1992 and 1995:
Graph 2.17: Polish regional development over time
Again, there is a tendency for ‘concentric’ development that clearly emerges from the statistical data. In Table 2.10, we further analyze these trends. In which year a Human Development Index of 0.95 would be reached, provided, that the rhythm of development 1992 does not diminish? Our statistical materials, based on the UNDP Human Development Report, at least permit us a tentative answer to this question:
Table 2.10: projections of regional development in Poland, based on the continuation of the rapid growth scenario of the mid 1990s
Voivodship |
HDI 1992 |
HDI 1995 |
HDI 1992 |
HDI 1992^2 |
non-linear trend |
Voivodship |
Residual |
yearly growth of HDI |
number of years to reach HDI 0,95 |
Voivodship |
Year, by which HDI = 0,95 could be reached, assuming rapid growth like in the 1990s |
war |
0,877 |
0,909 |
0,877 |
0,7691 |
0,8916 |
war |
0,0174 |
0,0107 |
4 |
war |
1999 |
bialpodlas |
0,733 |
0,77 |
0,733 |
0,5373 |
0,8082 |
bialpodlas |
-0,038 |
0,0123 |
15 |
bialpodlas |
2010 |
bistock |
0,778 |
0,84 |
0,778 |
0,6053 |
0,8514 |
bistock |
-0,011 |
0,0207 |
5 |
bistock |
2000 |
bielski |
0,791 |
0,878 |
0,791 |
0,6257 |
0,861 |
bielski |
0,017 |
0,029 |
2 |
bielski |
1997 |
bydg |
0,831 |
0,878 |
0,831 |
0,6906 |
0,8823 |
bydg |
-0,004 |
0,0157 |
5 |
bydg |
2000 |
chelm |
0,754 |
0,761 |
0,754 |
0,5685 |
0,8303 |
chelm |
-0,069 |
0,0023 |
81 |
chelm |
2076 |
ciech |
0,725 |
0,777 |
0,725 |
0,5256 |
0,7989 |
ciech |
-0,022 |
0,0173 |
10 |
ciech |
2005 |
czesto |
0,754 |
0,835 |
0,754 |
0,5685 |
0,8303 |
czesto |
0,0047 |
0,027 |
4 |
czesto |
1999 |
elblas |
0,763 |
0,864 |
0,763 |
0,5822 |
0,8387 |
elblas |
0,0253 |
0,0337 |
3 |
elblas |
1998 |
gdan |
0,831 |
0,885 |
0,831 |
0,6906 |
0,8823 |
gdan |
0,0027 |
0,018 |
4 |
gdan |
1999 |
gorzo |
0,747 |
0,837 |
0,747 |
0,558 |
0,8233 |
gorzo |
0,0137 |
0,03 |
4 |
gorzo |
1999 |
jelen |
0,782 |
0,827 |
0,782 |
0,6115 |
0,8545 |
jelen |
-0,027 |
0,015 |
8 |
jelen |
2003 |
kalis |
0,741 |
0,833 |
0,741 |
0,5491 |
0,817 |
kalis |
0,016 |
0,0307 |
4 |
kalis |
1999 |
kato |
0,819 |
0,875 |
0,819 |
0,6708 |
0,8772 |
kato |
-0,002 |
0,0187 |
4 |
kato |
1999 |
kiele |
0,728 |
0,816 |
0,728 |
0,53 |
0,8024 |
kiele |
0,0136 |
0,0293 |
5 |
kiele |
2000 |
konin |
0,734 |
0,848 |
0,734 |
0,5388 |
0,8093 |
konin |
0,0387 |
0,038 |
3 |
konin |
1998 |
kosza |
0,75 |
0,83 |
0,75 |
0,5625 |
0,8264 |
kosza |
0,0036 |
0,0267 |
5 |
kosza |
2000 |
krak |
0,876 |
0,905 |
0,876 |
0,7674 |
0,8916 |
krak |
0,0134 |
0,0097 |
5 |
krak |
2000 |
krosn |
0,727 |
0,804 |
0,727 |
0,5285 |
0,8013 |
krosn |
0,0027 |
0,0257 |
6 |
krosn |
2001 |
legni |
0,846 |
0,868 |
0,846 |
0,7157 |
0,8871 |
legni |
-0,019 |
0,0073 |
11 |
legni |
2006 |
leszcz |
0,758 |
0,877 |
0,758 |
0,5746 |
0,8341 |
leszcz |
0,0429 |
0,0397 |
2 |
leszcz |
1997 |
lubel |
0,771 |
0,877 |
0,771 |
0,5944 |
0,8457 |
lubel |
0,0313 |
0,0353 |
2 |
lubel |
1997 |
lomzy |
0,719 |
0,761 |
0,719 |
0,517 |
0,7916 |
lomzy |
-0,031 |
0,014 |
14 |
lomzy |
2009 |
lodz |
0,812 |
0,883 |
0,812 |
0,6593 |
0,8737 |
lodz |
0,0093 |
0,0237 |
3 |
lodz |
1998 |
nowosad |
0,713 |
0,774 |
0,713 |
0,5084 |
0,784 |
nowosad |
-0,01 |
0,0203 |
9 |
nowosad |
2004 |
olszt |
0,767 |
0,821 |
0,767 |
0,5883 |
0,8423 |
olszt |
-0,021 |
0,018 |
7 |
olszt |
2002 |
opol |
0,787 |
0,864 |
0,787 |
0,6194 |
0,8582 |
opol |
0,0058 |
0,0257 |
3 |
opol |
1998 |
ostrol |
0,71 |
0,795 |
0,71 |
0,5041 |
0,7801 |
ostrol |
0,0149 |
0,0283 |
5 |
ostrol |
2000 |
pilsk |
0,734 |
0,84 |
0,734 |
0,5388 |
0,8093 |
pilsk |
0,0307 |
0,0353 |
3 |
pilsk |
1998 |
piotrk |
0,833 |
0,861 |
0,833 |
0,6939 |
0,883 |
piotrk |
-0,022 |
0,0093 |
10 |
piotrk |
2005 |
plock |
0,866 |
0,88 |
0,866 |
0,75 |
0,8909 |
plock |
-0,011 |
0,0047 |
15 |
plock |
2010 |
pozn |
0,868 |
0,895 |
0,868 |
0,7534 |
0,8911 |
pozn |
0,0039 |
0,009 |
6 |
pozn |
2001 |
przem |
0,709 |
0,775 |
0,709 |
0,5027 |
0,7788 |
przem |
-0,004 |
0,022 |
8 |
przem |
2003 |
radom |
0,751 |
0,858 |
0,751 |
0,564 |
0,8274 |
radom |
0,0306 |
0,0357 |
3 |
radom |
1998 |
rzesz |
0,788 |
0,858 |
0,788 |
0,6209 |
0,8589 |
rzesz |
-9E-04 |
0,0233 |
4 |
rzesz |
1999 |
siedle |
0,726 |
0,778 |
0,726 |
0,5271 |
0,8001 |
siedle |
-0,022 |
0,0173 |
10 |
siedle |
2005 |
sierad |
0,727 |
0,805 |
0,727 |
0,5285 |
0,8013 |
sierad |
0,0037 |
0,026 |
6 |
sierad |
2001 |
skiernie |
0,72 |
0,805 |
0,72 |
0,5184 |
0,7928 |
skiernie |
0,0122 |
0,0283 |
5 |
skiernie |
2000 |
slupsk |
0,726 |
0,779 |
0,726 |
0,5271 |
0,8001 |
slupsk |
-0,021 |
0,0177 |
10 |
slupsk |
2005 |
suwal |
0,707 |
0,808 |
0,707 |
0,4998 |
0,7761 |
suwal |
0,0319 |
0,0337 |
4 |
suwal |
1999 |
szczec |
0,857 |
0,88 |
0,857 |
0,7344 |
0,8896 |
szczec |
-0,01 |
0,0077 |
9 |
szczec |
2004 |
tarnbrzes |
0,739 |
0,836 |
0,739 |
0,5461 |
0,8149 |
tarnbrzes |
0,0211 |
0,0323 |
4 |
tarnbrzes |
1999 |
tarnow |
0,768 |
0,804 |
0,768 |
0,5898 |
0,8432 |
tarnow |
-0,039 |
0,012 |
12 |
tarnow |
2007 |
torun |
0,759 |
0,845 |
0,759 |
0,5761 |
0,8351 |
torun |
0,0099 |
0,0287 |
4 |
torun |
1999 |
walbrz |
0,726 |
0,794 |
0,726 |
0,5271 |
0,8001 |
walbrz |
-0,006 |
0,0227 |
7 |
walbrz |
2002 |
wlocl |
0,718 |
0,781 |
0,718 |
0,5155 |
0,7903 |
wlocl |
-0,009 |
0,021 |
8 |
wlocl |
2003 |
wroc |
0,821 |
0,897 |
0,821 |
0,674 |
0,8781 |
wroc |
0,0189 |
0,0253 |
2 |
wroc |
1997 |
zamoj |
0,716 |
0,76 |
0,716 |
0,5127 |
0,7878 |
zamoj |
-0,028 |
0,0147 |
13 |
zamoj |
2008 |
zielono |
0,837 |
0,877 |
0,837 |
0,7006 |
0,8844 |
zielono |
-0,007 |
0,0133 |
5 |
zielono |
2000 |
Voivodship |
HDI 1992 |
HDI 1995 |
HDI 1992 |
HDI 1992^2 |
non-linear trend |
Voivodship |
Residual |
yearly growth of HDI |
number of years to reach HDI 0,95 |
Voivodship |
Year, by which HDI = 0,95 could be reached, assuming rapid growth like in the 1990s |
Voivodship |
Year, by which HDI = 0,900 could (have been/) be reached, assuming rapid growth like in the 1990s |
war |
1994 |
bialpodlas |
2006 |
bistock |
1998 |
bielski |
1996 |
bydg |
1996 |
chelm |
2055 |
ciech |
2002 |
czesto |
1997 |
elblas |
1996 |
gdan |
1996 |
gorzo |
1997 |
jelen |
2000 |
kalis |
1997 |
kato |
1996 |
kiele |
1998 |
konin |
1996 |
kosza |
1998 |
krak |
1994 |
krosn |
1999 |
legni |
1999 |
leszcz |
1996 |
lubel |
1996 |
lomzy |
2005 |
lodz |
1996 |
nowosad |
2001 |
olszt |
1999 |
opol |
1996 |
ostrol |
1999 |
pilsk |
1997 |
piotrk |
1999 |
plock |
1999 |
pozn |
1996 |
przem |
2001 |
radom |
1996 |
rzesz |
1997 |
siedle |
2002 |
sierad |
1999 |
skiernie |
1998 |
slupsk |
2002 |
suwal |
1998 |
szczec |
1998 |
tarnbrzes |
1997 |
tarnow |
2003 |
torun |
1997 |
walbrz |
2000 |
wlocl |
2001 |
wroc |
1995 |
zamoj |
2005 |
zielono |
1997 |
Voivodship |
Year, by which HDI = 0,900 could (have been/) be reached, assuming rapid growth like in the 1990s |
Source: our own compilations from the Polish HDR, 1995 and 1998, published by the UNDP Warsaw Office
Assuming the continuation of the growth trends of the mid 1990s, there could be just 4 regions, which by the most probable date of entry into the European Union, January the 1st 2004, will not have reached the migration political ‘safe’ level of HDI = 0.900. But this hyper-optimistic scenario depends on a great deal of good luck and a wise policy of human development in the Polish regions, and, above all, on the continuation of rapid economic growth. The multivariate analysis again shows the relevance of the ‘concentric’ rings of development that have developed in post-transformation Poland. The typical characteristics of a region as a periphery, high external migration, and the legacy of post-feudal landholding before 1939, along with environmental strains, explain why regions were lagging behind in life expectancy increases, while the urbanized and capital-penetrated regions more than reaped away the benefits of social and health development in the country. Our equation explains 48.7% of life expectancy growth over time. Our determination of the growth privilege indicator (see Table 2.8 above) shows again the concentric character of the 1992 - 1995 growth process, and in addition also - again - hints at the question of identity of a region in world society: paradoxically, perhaps, only at first sight, is thus the positive trade-off between religious practice and above than standard regional growth. Under the particular Polish circumstances, the functioning of a relatively well-defined civil society (in Poland a Catholic civil society, modeled after the Vatican teachings) is an important precondition for economic growth, while the regions with only a traditionalist and decaying identification with the Catholic Church (as more often than not, in the East of the country), suffered the severest identity crises in the transformation process. And finally, the residuals from the non-linear function of the increase/decrease of the Human Development Index over time (Graph 2.17) can be well explained by the
Table 2.10: the efficiency of social and health policy (above or below average life expectancy increase over time)
0,1347 |
0,1936 |
-0,027 |
-0,013 |
2E-07 |
-0,007 |
-0,034 |
0,0034 |
1E-06 |
0,0034 |
0,013 |
-3E-06 |
2,4388 |
0,1415 |
0,2784 |
0,0099 |
0,009 |
0,0002 |
0,0084 |
0,0135 |
0,0045 |
3E-06 |
0,0016 |
0,0079 |
5E-05 |
1,0733 |
0,4865 |
||||||||||||
2,8424 |
36 |
|||||||||||
real gdp pc |
religious pra |
ext migr/pop |
industr waste |
private land |
peasants |
big estates |
fem exc inf m |
ind.employm |
urbanisation |
for cap pen |
mixed cap pen |
|
0,9523 |
0,6953 |
-2,751 |
-1,458 |
0,0009 |
-0,86 |
-2,504 |
0,7418 |
0,4958 |
2,1478 |
1,6377 |
-0,058 |
Constant |
the concentric character of regional development in Poland (over time growth or decline of the development differential of the voivodship in comparison to Poland’s poorest voivodship, 1992-95)
0,1328 |
0,202 |
0,0035 |
-1E-03 |
3E-05 |
-0,001 |
0,0039 |
0,0015 |
1E-06 |
0,0001 |
-0,006 |
-3E-05 |
-0,255 |
0,0846 |
0,1665 |
0,0059 |
0,0054 |
0,0001 |
0,005 |
0,0081 |
0,0027 |
2E-06 |
0,0009 |
0,0047 |
3E-05 |
0,6418 |
0,2608 |
||||||||||||
1,0583 |
36 |
|||||||||||
real gdp pc |
religious practice |
ext migr/pop |
industr ial waste |
private land |
peasants |
big estates |
fem exc inf m |
ind.employm |
urbanisation |
for cap pen |
mixed cap pen |
|
1,5691 |
1,213 |
0,5907 |
-0,18 |
0,2297 |
-0,209 |
0,4826 |
0,5673 |
0,684 |
0,1506 |
-1,165 |
-1,097 |
the concentric character of the increase in the Human Development Index over time, 1992-1995
0,0188 |
0,0023 |
0,0005 |
0,0006 |
3E-06 |
6E-05 |
0,0003 |
0,0001 |
-2E-07 |
-7E-05 |
-8E-04 |
-5E-06 |
-0,04 |
0,0109 |
0,0214 |
0,0008 |
0,0007 |
2E-05 |
0,0006 |
0,001 |
0,0003 |
2E-07 |
0,0001 |
0,0006 |
4E-06 |
0,0826 |
0,2526 |
0,0225 |
|||||||||||
1,0138 |
36 |
|||||||||||
0,0062 |
0,0182 |
|||||||||||
real gdp pc |
religious pra |
ext migr/pop |
industr waste |
private land |
peasants |
big estates |
fem exc inf m |
ind.employm |
urbanisation |
for cap pen |
mixed cap pen |
constant |
1,7314 |
0,1051 |
0,6727 |
0,8671 |
0,204 |
0,0935 |
0,2532 |
0,3736 |
-0,852 |
-0,577 |
-1,289 |
-1,527 |
Legend: As in all EXCEL 5.0 outprints in this work, first row: unstandardized regression coefficients, second row: standard errors, last row: t-Test. The values immediately below the standard errors are R^2 (third row, left side entry), F, and degrees of freedom (fourth row).
Time will tell, whether or not Poland will be able to transform the more backward regions according the ‘Terza Italia’ model of Tuscany and Venice, so aptly described by Piore and Sabel. If Poland achieves to regionalize its positive development performance, than, indeed, no one would have to fear in 8 to 10 years from now the influx of Polish labor to the fellow countries of the European Union. But this condition should not be underestimated, and it should also be made the starting point of a really serious reconsideration of the policies of the urban elites of Poland vis-à-vis the countryside, which they failed to comprehend in the last 500 years of capitalist development. One of the keys to such a process will be the success of Poland’s regional reform. Up to now, the trade-off between regional development and the political structure of the country has been clearly dominated by the fact, that only the PSL party, the Polish Peasant Party, had a clear constituency among the poorest provinces, while the left-wing of former Solidarity, the Labor Union, is clearly centered in the rich, well-to-do regions. The two main political camps in Poland, the AWS, Solidarity, and the post-communist SLD, have no clear linear tendencies regarding their regional constituencies. The AWS is strong in very poor and very rich regions, while the SLD is anchored in the medium development regions of Poland. And here, there is a real dilemma for the presently governing coalition: the opposition PSL and the opposition SLD much stronger represent the poorest and middle income regions of Poland, while the AWS will have to chose whether to be at the service of regional concentration or regional redistribution:
Graph 2.18: regional development and voter preference. The Human Development Index and the 1997 general election
Thus, the conditions would be at least principally in place for a successful ‘Gonzales’ strategy of Polish integration into the European structures, but these would presuppose a strong political will to overcome the center-periphery heritage in Poland.