Zoltán Lippényi What are the determinants of intergenerational mobility in Hungary? What are the...

Zoltán LippényiWhat are the determinants of intergenerational mobility in

Hungary?

What are the determinants of intergenerational mobility in

Hungary?

Comparing municipalities and periods before and during

modernization Social Stratification Research Seminar 2010

Utrecht, the Netherlands10 – 09 – 2010

Zoltán LippényiICS/Utrecht University


Hungary?

Comparative intergenerational mobility

– back to the past

• Towards open societies project (Marco van Leeuwen, Ineke Maas, ICS/UU/IISH)– Long-term intergenerational mobility in

several historical contexts

• Is there a trend towards increasing intergenerational occupational mobility?

• Could changes in occupational mobility be explained by industrialization, urbanization, and institutional development?


Hungary?

Intergenerational mobility in Hungary, 19th-20th Century

• Previous research: communism, transition 1989 (Szelényi, 1998; Bukodi & Róbert, 2004)

• “modernization”: increases from second half of the 19th Century (Berend & Ránki, 1982)

• Austro-Hungarian Monarchy (1867-1918)

• agricultural society with large farming underclass• immobility of agricultural classes decline

• regional and municipal differences in “modernization” (Beluszky & Győri, 2005)

• growing distances on the urban ladder


Hungary?

• Data collection: 60 Hungarian municipalities• Marriage records (1850-1950)

• Sampling: town and village typologies based on data from the 1930 Hungarian census

• Two-stage selection: – 1. towns from different macro-regions– 2. two-three villages from the town’s micro-region

Collecting mobility data from the past


Hungary?

Municipal centers industrial centers agrarian centers


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Preliminary results

• Kalocsa (Mid-Hungary) and its rural outskirts

• 15-20.000 residents, primarily agrarian

• Marriages: 1895-1950

• men, aged 18 -40

• N= 2,247


Hungary?

050

100

150

200

250

num

ber of

mar

riage

s

1890 1900 1910 1920 1930 1940 1950

year of marriage

Total number of marriagesNumber of marriages

Number of marriages per year, Kalocsa 1895-1950


Hungary?

Data quality - coverage• Population: Kalocsa residents who lived in the town at the

time of their marriage

• “Unit non-response”:

– Never got married• Hajnal-line: marriage almost universal in most

Hungary (Hajnal, 1965)

– Married outside church• Secularization began in the 1950’s

– Married in another city• Hungary: joint household formation system (Hajnal,

1982)

• “Item non-response”:

– occupation of the father missing:• Father’s early death: Van Poppel and Van Gaalen

(2008) found no social status effect


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Data quality – reliability• Comparability of father’s occupation with that of the

son:

– different life stage at time of measurement: overestimating downward mobility/immobility

• Class differences in marital age: could confound with change over time in mobility

• E.g. sons of farmers marry at older age increasingly over time relative to other classes greater mobility from agricultural origin

• Additional analyses: famers and farm workers marry earlier, but no time effect and no origin-destination class*time effect on age at marriage

• Quality of occupational measurement: more detailed titles more mobility observed


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Occupations

• Occupational origin and destination:– HISCO (Van Leeuwen, Maas, Miles, 2002):

historically comparable occupational coding scheme– HISCLASS: 6 categories

• Higher managers and professionals• Lower managers and professionals• Foremen and skilled workers• Farmers• Lower/unskilled workers• Lower/unskilled farm workers


Hungary?

020

4060

8010

0

1890 1900 1910 1920 1930 1940 1950

year of marriage

% of grooms in agricultural classes% of grooms in industrial classes% of grooms in professional classes

Changes in the occupational structure, Kalocsa 1895-1950


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020

4060

80%

of m

obile

gro

oms

1890 1900 1910 1920 1930 1940 1950

year of marriage

Intergenerational class mobility per year %, Kalocsa 1895-1950


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Methods and model specification

• Multinomial conditional logit model (Breen, 1994; Hendrickx & Ganzeboom, 1998; Wu & Treiman, 2007)

• Quasi-equal row and column effects 2 model

– Equal scaled metric for origins and destinations

Origin-destination association:– Scaled association parameter

Immobility:– Overall immobility parameter (diagonal)– Immobility parameter for agricultural classes

Control covariates:– Immigrants– Rural outskirts


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Model selection

Model LR chi2(diff)

Df (diff)

P BIC (diff)

Baseline: class-specific intercepts + association + immobility + covariates

3366 11 4790

M1: Baseline + time-varying intercepts

-199.5

5 .000

-152

M2: M1 + time-varying association and immobility parameters

-33.35

3 .000

-5

M3: M2 + time-varying association and immobility, separate for outskirts

-7.36 3 0.06

+21

M4: M1 + time-varying immobility parameters

-33.24

2 .000

-15

M5: M1 +time-varying overall immobility

-32.28

1 .000

-23


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Higher managers and professionals

-0.63

Lower managers/ professionals

-0.29

Foremen/skilled workers -0.07

Lower skilled/unskilled workers

-0.02

Farmers 0.50

Farm workers 0.51

Parameter estimates M5Scaled metric


Hungary?

Origin-destination association 4.56 ***

Immobility 1.55 ***

Agricultural immobility .86 ***

Time * Higher managers and professionals

-.001

Time * Lower managers/ professionals

-.004

Time * Foremen/skilled workers -.027***

Time * Lower skilled/unskilled workers

REF

Time * Farmers -.048***

Time * Farm workers -.062***

Immobility*time -.02***

Parameter estimates M5


Hungary?

– Indicators: collected from gazetteers and census sources

– Population size (per 100 inhabitants)• 7 censuses: 1890, 1900, 1910, 1921, 1930, 1940, 1948• Other years: linear interpolation

– Yearly modernization-index (per 1000 inhabitants) • number of institutions in a given year

(bank, hospital, tax office)• number of schools• number of larger industrial establishments

– High correlations: separate models (time excluded)

Modernization and mobility


Hungary?

MODERNIZATION

Modernization* immobility -.30 ***

LR2 (17) = 3510, p<.000, BIC=4703

POPULATION

Population*immobility -.03 ***

LR2 (17) = 3517.17, p<.000, BIC=4697

Results

• Model 5: Baseline + main effects + immobility interaction


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Conclusion

• Evidence of changing mobility regime before communism: declining immobility (1.3% per year)

• Similar decline in immobility for agricultural and non-agricultural classes

• No change in overall association and difference between city and its rural outskirts

• Modernization and population size: decreasing inheritance


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Future plans

• More contexts: municipal level variation in modernity

• Multilevel modeling: combine MCL-estimates from several municipalities in meta analysis

• Comparability of vital records with representative survey data for the same period

• Urban centers and villages in their micro-regions: residential and intergenerational mobility

• Hungary, a multiconfessional land: intergenerational mobility and religion


Hungary?

Thank you for your attention!


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Controls and additional model specifications

Immigrant (Stereotyped ordered effect)

+

Outskirt resident*agricultural occupation

+

Outskirt resident*industrial occupation

_

Father dead at time of marriage

n.s.

Aged 14 between 1914 and 1924 (1st World War)

n.s.

Quadratic time-specification n.s.

Leave out post 1945 marriages

identical results


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The statistical model

logit(πj/πk) = αj – αk + (φj – φk)(μ0 + ∑ μtXt) φv + (βjt – βkt)Xt

∑ φj=0, ∑ φj2 = 1

Stereotyped ordered effect:

(φj – φk) ∑ βmXm

Estimation: Iteratively: φj scaling metric β parameters

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