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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):

  1. unequal exchange: the gaps in wages are much greater than the gaps in productivities
  2. capital flight from the peripheries to the centers
  3. selective migration from the peripheries into the centers
  4. the monopoly position of the centers in the international division of labor
  5. the control of the centers over the earth’s natural resources

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.

  1. human development and migration

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.

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