Determinants of Household Saving in China

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Determinants of Household Saving in China

• Marcos Chamon
• Eswar Prasad

Disclaimer The views expressed are those of the
authors and do not necessarily represent those of
the IMF or IMF policy.
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Motivation

• Chinese households save a lot!
• About 25 of disposable income
• Historically, households main contributor to
  national savings
• Recently, enterprises have become largest savers
• But household savings are still large about 16
  of GDP

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Savings as a percentage of GDP
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High household saving rate somewhat puzzling

• High enterprise savings can be justified by
  attractive returns on retained earnings
• But households typically face small real returns
  on their savings (sometimes negative!)
• Moreover, rapid income growth suggests households
  should be anticipating future consumption/delaying
  their life-cycle savings

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Overview of presentation

• Paper uses household-level data from a subset of
  the Urban Household Survey
• Focuses on three determinants of savings
• 1) Life-cycle effects
• 2) Transition effects from reform process
• 3) Credit constraints (durable good
  purchases)

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Life-cycle effects

• In a fast growing economy people should
• Borrow against future income
• If credit constrained, at least delay
  retirement savings
• Paper presents a very simple OLG model showing
  that interplay of credit constraints and high
  income growth can actually increase savings

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Model set-up

• Agents live for 3 periods, earn wages in first
  two periods
• All wages in the economy grow at a geometric rate
  ggt1 every period
• Cohort born at t0 w01, w1g, w20
• Cohort born at t1 w1g, w2g2, w30
• Cohort born at t2 w2g2,
  w3g3, w40
• Agents can only borrow up to share b of their
  second period income in the first period

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Simple example with no borrowing (e.g. b0)

• Household born at t0 has
• wt1, wt1g, wt20
• If g2, household can perfectly smooth its
  consumption by consuming
• ct(1g)/3, ct1(1g)/3, ct2(1g)/3
• If ggt2, household would like to borrow against
  future income in first period. Since it cannot,
  the best it can do is not to save at t0.
  Resulting consumption path is
• ct1, ct1g/2, ct2g/2

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With borrowing constraints, income growth
increases savings

• Aggregating across overlapping cohorts yields

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Aggregate savings rate in an OLG economy as a
function of growth rate of wages
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Relaxing borrowing constraints (bgt0 but still
small) yields (for ggt2)

• Aggregating across overlapping cohorts yields

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Aggregate savings rate in an OLG economy as a
function of growth rate of wages and borrowing
constraints
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Empirical Evidence on life-cycle effects

• Use data from urban household survey. Entire
  sample for 1986-1992, subset of 10
  provinces/municipalities for 1993-2001.
• Limit analysis to households whose head between
  25 and 70 years old

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Summary of Urban Household Survey
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Age and cohort effects

• Following Deaton and Paxson (1994), we compute
  average log(income) and log(consumption) for each
  ageyear combination and regress on age, cohort
  (age in 1986) and year dummies
• There is a linear relationship between age,
  cohort and year. Year effects are constrained to
• Add to zero
• Be orthogonal to a time trend

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Age effects on income and consumption
Effects shown for household that was 10 years old
in 1986
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Cohort effects on income and consumption
Effects shown for 25 year old household
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Age and cohort effects on savings
Effects shown for 25 year old household in 2001
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Time trend on income overwhelms all other effects

• Alternative approach
• Give up trying to identify cohort effects, and
  regress log (income) and log(consumption) on age
  dummies and unrestricted time trend

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Age effects on income and consumption
Effects shown for 2001
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Age profile of savings
Effects shown for 2001
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Qualitative results match our priors

• Young households save substantially (possibly to
  self-finance purchases of durables)
• Savings increase sharply around mid 40s
  (suggesting retirement savings begin around
  that age)

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Implications for future aggregate saving
patterns Demographics

• In the long run, population aging should lead to
  a contraction in aggregate savings
• Share of population in prime saving age group
  will increase vis-à-vis prime dissaving group
  in the short- and medium-term

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Share of Chinese population by age group
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Precautionary Saving motives

• Many observers emphasize role of precautionary
  motives and uncertainty related to reforms
• Several benefits traditionally provided by State
  Owned Enterprises to their employees
• Health Education Pensions Housing...
• Provision of these benefits either lost or became
  uncertain

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Precautionary saving motives

• Households may be saving a lot not only because
  of higher uncertainty, but also to make-up for
  past savings that were not made
• Different groups affected differently by this
  uncertainty
• SOE workers have potentially a lot to lose vs
  collective enterprise workers that didnt have
  many benefits to begin with
• Private sector workers face uncertainty but may
  also face better income growth prospects

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Percentage of households by type of employer of
head of household

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Estimated effect of employer type on saving rates
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Implications for future aggregate saving
patterns Transition effects

• Shift to a market economy and SOE reforms likely
  contributed to the increase in household savings
• The effect may weaken over time
• As households continue to accumulate savings, at
  some point they will have enough assets to
  protect them from most adverse shocks
• Eventual development of social safety net and
  pension system should also lower savings

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Durable goods and borrowing constraints

• Consumer finance very limited in China
• Development of consumer credit should lower
  savings
• But magnitude of the effect may be small
• If household saves 20 of income and wants to buy
  a new TV, it can do so just by saving less.
• No need to rely on credit or even deplete past
  savings!

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Durable good consumption

• Survey has detailed data on income and
  consumption expenditures. We focus on 1993-2001
  subsample
• Exclude households with home purchasing/constructi
  on expenditures (about 8 of households)
• Durable good purchases correspond on average to
  6.5 of income (but distribution is very skewed
  due to their lumpiness)
• Durable good purchases exceed income minus other
  expenditures for 33 of households (thus cannot
  finance purchase just by saving less)

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Financing sources for durable good purchases

• We break down the source of funds for durable
  good purchases between
• (i) Income nondurable consumption
  nonconsumption expenditures
• (ii) Net financial dissavings (e.g. net saving
  withdrawals)
• (iii) Credit

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Financing sources for durable good purchases in
2001
Note Variables expressed as share of income
unless otherwise noted. Negative net financial
dissavings indicates households net financial
savers
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Are net financial dissavings related to large
durable purchases?

• We run probit regressions of a dummy equal to one
  if household is net financial dissaver (about 30
  of households) on
• Log (Durable good purchases/Y)
• Log Y
• Dummy for household head below 35

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Probit regression results
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Marginal effects on probability of being a net
financial dissaver in 2001
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Large durable purchases increase likelihood of
net financial dissavings

• Magnitude of the effect non-negligible, but
  relatively small
• Households likely to remain net financial savers
  even when making very large durable purchases

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Ownership of most durable goods common except cars
Source CEIC based on NBS data covering whole
sample
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Home ownership rates also very high
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Implications for future aggregate saving patterns

• Development of consumer financing migth only have
  limited impact on saving behavior (with possible
  exception of auto financing)
• Developments in housing market should also have
  limited impact given very high rates of home
  ownership

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Conclusion

• Precautionary saving motives seem to play an
  important role
• Demographic changes have contributed to aggregate
  savings (high income growth leverages that
  effect).
• Demographics should continue to contribute to
  aggregate savings over the next two decades
• Developments in consumer credit may not have a
  substantial effect on savings