The New Economic _ Climatic Context and Changing Migration Pattern

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					The New Economic & Climatic
Context and Changing Migration
Pattern in India
SANEI: 10th Annual Conference: 30th – 31st March, 2010

Presented by
Dr. Renu Khosla
Centre for Urban and Regional Excellence (CURE)
Centre for Economic Policy and Studies (ISEC)
This study is about new internal migration triggers and
 trends in India; economic growth - in particular urban
economic growth; inflation - rising oil and food prices;
    changing climate condition - impact on farming
                 patterns; and disasters.
Inevitability of being Urban

 “People move to urban areas for work and/or for higher
  income…… Urban work is more productive than rural,
  urban wages are higher.”
    Sustained economic growth and higher urban wages provide new
     impetus to India‟s urbanization.
    Climate change and linked disasters are making farming practice
     uncertain, diminishing outputs, stoking up rural to urban
    Inflationary pressures from macro economic changes (spike in oil
     prices, global financial crisis), hike up cost of farming, making it
     less sustaining and appealing.
  Features of India’s Urban Growth

  285 million (28%) projected to be 600 million (40%) by 2030.
  Medium urbanized with medium to high urban growth rate (2-4%)
  Urban growth faster than rural in past 2 decades
  Most will live in metros; nodes of employment and/or wage growth
  1/5th growth in cities is from migration
  Low supply of land/affordable housing means poorer migrants live in
 slums, neighbouring cities, peri-urban settlements with implications for
 urban planning, development and mobility.
  Slums are overcrowded, congested, unhygienic environmental
 conditions, poor housing

Slums are “evidence of cities that are working….but….also problematic,
because …… these …. are „fragile‟ organizationally, and often suffer acute
poverty…..” Nabeel Hamdi and Goethert (1997)
Migration: Distress or Brain Drain?
“Migration is a permanent moving away of a collectivity, called migrants
from one geographical location to another preceded by decision making
on part of migrants based on …… set of values and valued ends and
resulting in changes in the interactional system of migrants.”
       Permanent, Temporary (regular/irregular/seasonal), or Circular
        (sleeping away from home without changing usual residence or
       Conventionally attributed to economic distress/shocks
       Accumulative option for poor/ and non-poor

   Distress migration: Uneven development of regions/states,
    interlocked markets for credit, output, labour; lack of market for
    traditional skills, availability of surplus labour within the household,
    cultural norms regarding sexual division of labour, children‟s
    education etc.
   Aspirational migration or Brain-drain: education, better health care
 Migration: Complexities and Contradictions

Migration can both reduce and perpetuate poverty
Response to poverty – yet there is slum growth
Rural investment bias – unevenness in rural-urban
development – fuelling migration
No amount of urban growth can cope with migration pressures.
Urban development strategy does not address complexities of migration;
except for „planned‟ infrastructure investment, that too in the larger cities.
                     Table 1 Growth of migrants by migration streams, India 1991-2001 (in Million)
Migration affects
                                             Lifetime Migrants                     Inter-censal Migrants
origin and
destination          Migration Streams       Persons      Males         Females    Persons   Males   Females
economies            All Internal Migrants

                     Rural To Rural          18.40        -1.41         22.82      15.37     7.78    17.71
                     Rural To Urban          29.51        34.37         25.41      22.84     27.68   18.35
                     Urban To Rural          -3.56        0.00          -5.37      3.00      6.48    0.70
                     Urban To Urban          38.39        43.12         34.73      24.27     26.85   22.17
                     Source: Lusome and Bhagat (2006)
    Growing Economy
• 8.5% (av.) past 5 years, current fiscal expected: 6-7%
     Largely in non-farm sector - manufacturing industry and services
     Farm sector growth down to 2.5% per annum

• Threats from Global Crisis
     • Slower growth rates in developed countries shrinking local markets
     • Food price volatility, oil and gas price rise, asset price collapse, unemployment,
     underemployment and working poverty, fall in remittances

• Food price increases from weather unpredictability/global warming - reduction in farm
acreage, low productivity, etc.
    “higher food prices … more immediate concern than higher fuel prices….for...
    impact, implications on income, distribution, inflation and poverty” Ghauri-2009.

• Climate Change: reduces availability of local natural resources on which rural
populations depend
     Predicted to deepen poverty from loss of life, livelihoods, assets, infrastructure, etc.
     from climatic linked disasters/events.
     Climatic migrants expected to become major driving force in migration exceeding
     economic migrants.

  Study the changes in internal migration trends
   in India, from distress to aspiration and
   metropolitan to small town migration from
   recent changes in India‟s economic paradigm.
  Identify the complex factors that contribute to
   migrant families capabilities of moving out of
  Make recommendations to existing urban
   planning - policy and practice to address
   migration with sustainable poverty reduction
  Cities and Migrants in the Study
 4; 2 metros – Delhi, Bangalore, 2 peripheral towns; Faridabad, Dodballapur
 Why Metros? Fast growing-diverse economy-employment, attractive to
   migrants, high migration rate, large numbers of/in slums
 Neighbouring Towns: Relieve metro population pressure – absorb
   spillover, decentralized location for industries, part of Capital Regions with
   strong linkages/dependence, growing migration

 2000 migrants; 500 per city selected in a two-stage, disproportionate,
  stratified, random sampling method to observe two types of migration
    Distress migration; pushed out from villages/small towns due to lack of
      income opportunities/ livelihoods, mostly illiterate or semi literate,
      absorbed in labour intensive jobs or small enterprises, mostly squatting
      near employment sites
    Aspiration migration: Migrants from villages/small towns searching for
      better income opportunities, mostly literate, absorbed in skilled jobs and
      accommodate themselves in rented/shared arrangements
                          Chart No. 2.1: Sampling Design of the Study Area

             KARNATAKA                                                    DELHI
              (Sample size 1000)                                    (Sample size 1000)

 BENGALURU                   DODBALLAPUR                        DELHI                FARIDABAD
 (Sample size 500)          (Sample size 500)             (Sample size 500)         (Sample size 500)

                                           Sample size 250

Slum         Company/        Slum      Company/          Slum      Company/         Slum       Company/
             BPO/Bank/                 BPO/Bank/                   BPO/Bank/                   BPO/Bank/
             Hospitals.                Hospitals.                  Hospitals.                  Hospitals.
             etc                       etc                         etc                         etc
Slums-Respondent selection

    Variability in employment patterns
    Geographical dispersion
    Slum size: 2000-3000 HHs

   250 per city spread over 6-7 slums using snowballing method
   Distress Migrants (DMs): In job, recently migrated - 2-5 years, at
    least one intermediate town
   Aspiration Migrants (AMs): occupation groups (guards/service
    providers, call centres/BPO, contractors in metro construction,
    institutional area offices, ward boys and nurses, drivers)
 Data Collection and Analysis
 Primary survey through questionnaires
 Statistical Analysis
    Comparisons between Distress and Aspiration Migrants, metro and
     small cities
    Testing of Hypotheses
    Significance of different factors that contribute to migration; t test, at
     1% - 10% level of significance
    Level of association between contributing variables; Chi-square

    Logistic Regression Analysis
    Non linear regression model to understand probability of a
     particular factor being instrumental in influencing migration.
Key Findings

                                • Lower castes dominate;
                                • SC-Minority communities
                                prefer metros/ are more

• Young and male
• Aspirants younger than
distressed migrants

                                                   DMs more than AMs were illiterate;
Direct- negative correlation with
                                                   Metros received double the number
state GDP - Bottom or lower
                                                   of illiterates than smaller/industrial
GDP States with higher
inequalities push more migrants.
                                                               Av. monthly pre
                                Mostly                         migration family income
                                unskilled                      was Rs.2434; Rs274
                                labour;                        per capita, is skewed
                                1 in10                         due to some high
                                were                           earners.
                                            Modulus value
                                farmer                         AMs earned marginally
                                            of calculated t
                                owners      statistic (tcal)   more than DMs -
                                                               difference being
                                            1.36               statistically insignificant
                              1 in 4 owned land;
                              Fewer AMs were from farming families
Low asset ownership:          More DMs owned arable land – indicative of
Less than half owned          experiencing low agriculture productivity.
livelihood/economic assets    More DMs had mortgaged land - to manage
contributing to low earning   financial shocks
                                                         1/5 DMs were in debt,
                                                         twice the AMs
                                                         Av. debt per family
                                                         (DMs: Rs.31417; AMs:
                                                         Rs.62489). DMs low
                                                         debt was due to lower
                                                         creditworthiness/ felt
                                    FOOTPRINTING MIGRATION

Migration is Pacing Up
• High incidence of first time
migration (3 of 4)
• Aspiration-based migration
increasing to metros
                                       Why Migrate?
                                       AMs move because of lack of opportunities
                                       that match their skills in rural areas

                                                        Urban to Urban
                                                        More DMs go to metros,
                                                        migrate to smaller towns
                                                        in search of opportunities
• Migration jumped with disasters
                                   WHAT’S CHANGING?
                                   Table 40 Changing Pattern of Agriculture
                                   Indicators                  Increased Remained Decreased
                                   Cost of Farming                    69%     31%            0%
                                   Cost of Fertilizers                67%     33%            0%
Timing & amount of rainfall
                                   Access to agricultural             5%      94%            1%
was no longer predictable,         Water Supply
affected outputs/earnings,
this weather inclemency           Farming was more costly/less affordable – fertiliser
was getting worse                 costs had soared reducing profitability - practice of
                                  preparing indigenous fertilisers has decreased adding
 Is it Disaster?                  to costs, rainfall pattern/quantity change is not
 1/3 DMs were disaster            mitigated by additional irrigation facilities these have
 affected; mostly from            mostly remained constant/ need added expenses.

The Upside                                         Is it inflation?
Better access to infrastructure facilities;        2 of 5 DMs
1/3 report better road connectivity,               attributed
significant rise in mobile access – 7/10,          migration to
only some improvement in drinking                  inflation.
water facilities or schooling.

Migrants have
DMs: 13% to 86%
AMs: 41% to 100%
Acquire new skills: 13% shift
from unskilled to semi-
Employment is remunerative
                                Gender differences
but less secure - mostly in
                                More women DMs in informal work –
informal sector
                                More women AMs in formal work
Satellite cities have higher
formal employment (38%)
                                    POST MIGRATION INCOMES
                                                       Incomes are significantly
                                                       higher, rise immediately on
                                                       migration and increase with
                                                       duration of stay as migrants
                                                       get to know their self-worth

                                                               New employment is private –
                                                               contractual, as government
                                                               employment backslides /is
 Table 46 Income Earned by Migrants in the City                less remunerative
                          Delhi          Faridabad
 Average Income                   5009               5540      Self-employment is
                                                               uncommon mostly among
 Modal Income                     3000               4000
                                                               DMs (14%) and for vending
 maximum Income                45000              50000        vegetables
 Minimum Income                    900                800
 Range of Income               44100              49200

Gender differences
Women DMs and male AMs earn more.
Gender difference in earnings not statistically significant,
Men in smaller towns see more income increases than in
                                                  POST MIGRATION

                                                Ownership of
                                                economic and
                                                social/luxury assets

                    Nearly 90% migrants do not have city ID
                    even after 5 years of stay, continue to be
                    deemed of „foreign‟ origin.
                    10% with ID accessed these fairly quickly
                    through patronage

Half continued to live in rental housing due to low
affordability (Metros 60%, small cities 40%); More
owned housing in small cities suggests affordable
land values
Human-Social Capital: Impact of Migration

     Table 61 Human and Social Capital Creation: Perceptions of Migrants
                                        DMs (%)                AMs (%)
                                Delhi        Faridabad Delhi      Faridabad
     More Incomes                   33%           27%     55%            43%
     More educated                  10%           15%      8%            17%
     More assets                    10%           16%     10%            14%
     Better housing                     6%        17%     12%            9%
     Better Dressed                 29%           11%     15%            7%
     Children are better                7%         9%      5%            10%
     Others                             5%         5%      1%            0%
 Migration: The New Paradigm
Pre-meditated Migration: When people choose to move
From climate change that is slow and occurs over time, the full impact of which is
often delayed and realised by families after several years of poor production or
inflation that deepens poverty or aspiration-linked.

    Decision to migrate is pre-meditated, fully thought out, could be permanent,
    involves the entire family.

  Table 66 Climate Change: Pre meditated – Permanent
                             Chi-square Value                Significance
  Choice of City            26.507 at 1 degrees of freedom   1% level of significance
  Income earned in home     12.076 at 3 degrees of freedom   1% level of significance
  Asset Ownership at Home   1.215 at 2 degrees of freedom    statistically non-significant
  Home State                0.583 at 3 degrees of freedom    statistically non-significant
  Impact of Migration
  Asset Ownership at City   0.833 at 1 degrees of freedom    statistically non-significant
  Income earned in city     5.802 at 4 degrees of freedom    statistically non-significant
 Gradual Economic Shock and Pre-meditated Migration
 Chose and move (to larger cities for better incomes)
 Unaffected by incomes earned or asset owned.
 Affects both higher income and low income families equally.

Table 67 Rise in Prices: Sudden but Temporary Impact
                                Chi-square Value                  Significance

                 Choice of City 192.511 at 2 degrees of freedom   1% level of significance
  Income earned in home state 4.855 at 3 degrees of freedom       statistically non-significant
Asset Ownership at Home state 1.233 at 4 degrees of freedom       statistically non-significant
                   Home State 18.903 at 6 degrees of freedom      1% level of significance
Impact of Migration Decision
         Income earned in city 15.013 at 8 degrees of freedom     10% level of significance
       Asset Ownership at City 0.524 at 2 degrees of freedom      statistically non-significant
Sudden Migration from Economic Shocks
Disasters are unexpected, families are unprepared for the devastation, effects
/asset loss is enormous, both rich and poor affected.

    Decision to migrate is rushed, survivalistic, may be temporary/reversible as
    situation improves.

Disaster affects choice of city, but is not influenced by pre-disaster asset ownership
or level of income and has very little impact on post migration income.
  Table 68 Disaster: Unexpected Crisis
                                 Chi-square Value              Significance

               Choice of City 18.205 at 1 degrees of freedom   1% level of significance
                 Home State 5.035 at 3 degrees of freedom      statistically non-significant
     Income earned in home 6.019 at 3 degrees of freedom       statistically non-significant
   Asset Ownership at Home 5.997 at 2 degrees of freedom       10% level of significance
  Impact of Migration Decision
       Income earned in city 7.22 at 4 degrees of freedom      statistically non-significant
     Asset Ownership at City 5.243 at 1 degrees of freedom     significant at 5% level of significance

Better educated, better skilled and richer migrants choose larger cities;
whether distressed or aspirational.

  Table 69 Factors Influencing Choice of City
                             Chi-square Value                  Significance

  Age                        2.954 at 4 degrees of freedom     statistically non-significant
  Education                  17.849 at 1 degrees of freedom    1% level of significance
  Income at Village          5.379 at 4 degrees of freedom     statistically non-significant
  Land Ownership             6.242 at 1 degrees of freedom     5% level of significance
  Skills                     9.755 at 1 degrees of freedom     1% level of significance
  Home State                 6.758 at 1 degrees of freedom     1% level of significance
  Cause of Migration         82.471 at 15 degrees of freedom   1% level of significance
  Impact of Migration Decision
  Income in City             27.713 at 4 degrees of freedom    1% level of significance
Recipient City Benefits-A Logit Analysis

An Aspirant Migrant is neither too young nor too old, has acquired a certain
level of education and professional skill prior to moving, has a better safety
net - reasonable income and land in home village. A Distressed Migrant has
lower education, skills and slender safety nets.

Cities getting more AMs will do better than cities getting more DMs.
     Probability of earning higher income for DMs is low.
     Probability of illiterate migrants earning high incomes is low.
     Probability of skilled migrants earning high incomes is more.
                                              M skill
Old Theories                                  i Low
Early demographers
concluded that low-                           g incom
                                              r    e
skilled, low-income and
low-caste people                              a High
migrated, albeit not       Expected           n skill
                           difference in
those at the bottom of                        t Low
the pyramid who could
                           Prospect for       s incom
not afford the expense                              e               Larger
                           occupational/                            towns,
of migration.              social mobility         Low               cities

                           for lower class,   N    skill
There was also a           castes,            o    High
phenomenon called          distressed             incom
absorption: those living   households                e
closer to a growing
urban centre were                             i    High
                                                           Small urban
more likely to migrate                        g    skill     centres
to it.                                        r    High
                                              a   incom
                                              n      e
                                              t    areas
Migration Now
New factors catalysing migration, including among high income/skilled; modernisation,
transport/communication links, high urban growth, better infrastructure; weaker traditional controls,
local democratic governance, achievement orientation
Technological advancement in villages/cities has generated labour surplus - demand for urban
workforce and urban growth has potential to absorb skills/knowledge among AMs.
Weakening social safety nets/increasing uncertainty limits coping strategies in disasters, forcing
Growing small/satellite towns provide comfortable /affordable haven.

   Climate change
   Rapid urbanisation and               Low skill
                                       Low income
   development of small towns
   Modernisation and
   economic development
   High skill employment         Mig High skill
   opportunities                  rant Low income
   Breakdown of traditional        s
   Expected difference in               Low skill
                                       High income       Small urban centres
   Reduced distance between                                                      Larger towns, Cities

   rural and urban centres due
                                        High skill
   to improvements in transport
                                       High income
   and communication
                                        Rural areas
    Policy Implications
    Catch 22? High rate of migration has implications for urban
     development planning. Unprepared cities are feeling the challenges
     of services for all even as they wish to absorb the work force
     required to move the economy.
    Choose to Move: As more stay back in destination cities, efforts
     are needed to integrate them into city systems including with
    Future Planning: Cities need futuristic planning based on profile
     and nature of migrants expected with affordable housing and
    Mission Focus: India‟s urban development Mission; Jawaharlal
     Nehru National Urban Renewal Mission (JNNURM), even as it
     unpicks the urban mess from unplanned growth, it must restructure
     planning frameworks for the development of spaces and livelihoods
     for new migrants.
    Appropriate Information: Any meaningful corrective action is
     possible only with a proper statistical database regarding the size
     and growth of population at lesser time intervals than provided by
     the decennial census
Thank You