Determinants of Household Saving in China

1. 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.

2. 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

3. Savings as a percentage of GDP

4. 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

6. 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)

7. 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

8. Model set-up • Agents live for 3 periods, earn wages in first two periods • All wages in the economy grow at a geometric rate g>1 every period: • Cohort born at t=0: w0=1, w1=g, w2=0 • Cohort born at t=1: w1=g, w2=g2, w3=0 • Cohort born at t=2: w2=g2, w3=g3, w4=0 • Agents can only borrow up to share b of their second period income in the first period

9. Simple example with no borrowing (e.g. b=0) • Household born at t=0 has: • wt=1, wt+1=g, wt+2=0 • If g≤2, household can perfectly smooth its consumption by consuming: • ct=(1+g)/3, ct+1=(1+g)/3, ct+2=(1+g)/3 • If g>2, household would like to borrow against future income in first period. Since it cannot, the best it can do is not to save at t=0. Resulting consumption path is: • ct=1, ct+1=g/2, ct+2=g/2

10. With borrowing constraints, income growth increases savings Aggregating across overlapping cohorts yields:

11. Aggregate savings rate in an OLG economy as a function of growth rate of wages

12. Relaxing borrowing constraints (b>0 but still small) yields (for g>2) Aggregating across overlapping cohorts yields:

13. Aggregate savings rate in an OLG economy as a function of growth rate of wages and borrowing constraints

14. 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

15. Summary of Urban Household Survey

16. Age and cohort effects • Following Deaton and Paxson (1994), we compute average log(income) and log(consumption) for each age*year 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

17. Age effects on income and consumption Effects shown for household that was 10 years old in 1986

18. Cohort effects on income and consumption Effects shown for 25 year old household

19. Age and cohort effects on savings Effects shown for 25 year old household in 2001

20. 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

21. Age effects on income and consumption Effects shown for 2001

22. Age profile of savings Effects shown for 2001

23. 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)

24. 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

25. Share of Chinese population by age group

26. 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

27. 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 didn’t have many benefits to begin with • Private sector workers face uncertainty but may also face better income growth prospects

28. Percentage of households by type of employer of head of household

29. Estimated effect of employer type on saving rates

30. 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

31. 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!

32. Durable good consumption • Survey has detailed data on income and consumption expenditures. We focus on 1993-2001 subsample • Exclude households with home purchasing/construction 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)

33. 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

34. 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

35. 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

36. Probit regression results

37. Marginal effects on probability of being a net financial dissaver in 2001

38. 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

39. Ownership of most durable goods common except cars Source: CEIC based on NBS data covering whole sample

40. Home ownership rates also very high

41. 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

42. 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