Transcript Achieving Food Security in China: Policy Reform

Risk Coping Strategies for Farmers in
Transition: Labor Supply Flexibility
versus Precautionary Saving
Kevin Z. Chen and Ling Jin
International Food Policy Research Institute and
Zhejiang University, respectively
April 26, 2012
1
Typical Risks Farmers Face in
Developing Countries
Events
Harvest failure (drought, flooding, frost, pests)
Percentage of Rural
Households Who
Reported
78
Policy shock (forced labor, ban on migration, new levies
42
or taxes)
Labor problems (illness or deaths)
40
Oxen problems (diseases, deaths)
39
Other livestock (disease, deaths)
35
Land problems (villagization, land reform)
17
Assets losses (fire, loss)
16
War
7
Source: Quoted from Dercon (2005): Risk Insurance and Poverty: A Review.
And
Crime/banditry
(theft, violence)
3
the author’s calculation
is based on Ethiopian Rural Panel Data Survey (1994-1997).
2
Impact of Risk
• In the short run, risk induces income and consumption
fluctuations
 Heathcote, Storesletten and Violante (2012): 40% of permanent wage
shocks pass through to consumption
• In the long run, risk has adverse effects on farmers’
investment in nutrition, health and human capital, and
probably traps them in poverty
 Jacoby and Skoufias (1997): negative rainfall shocks are associated with
higher child mortality rates in landless households but not in households
with significant landholdings in India
3
Risk Coping Strategies
• Ex ante: income diversification, income skewing
 Morduch (1995): Indian households of subsistence devote a larger share
of land to safer, traditional varieties of rice and castor.
 Dercon and Christiaensen (2011): the possibly low consumption
outcomes when harvest fail discourage the application of fertilizer in
Ethiopia.
• Ex post: precautionary saving, labor supply, access to formal
credit and insurance markets, informal risk-sharing
mechanisms, and safety nets
 Udry (1994): informal credit play a role in pooling risk between
households in Nigeria, because repayments depend on realization of random
shocks by both borrowers and lenders.
 De Weerdt and Fafchamps (2011): inter-household transfers respond to
reported illness, and net transfers to households with disabled members
depends crucially on a kinship link.
4
Effectiveness of the Risk Strategies
• The characteristics of these strategies
 Self-insurance: income diversification, precautionary saving, and labor
supply flexibility
 Insurance supplied by institutional arrangements: access to formal
credit and insurance markets, informal risk-sharing mechanisms, and
safety nets



access to formal credit and insurance markets: moral hazard and
adverse selection due to information asymmetry, contract
enforcement
informal risk-sharing mechanisms: self-enforcement constraints,
genetic limits to altruism, and the bounded reach of social networks
safety nets: fiscal budget constraints, targeting
• The institutional environments
5
Why Labor Supply Flexibility and
Precautionary Saving?
• Relying less on external institutions
• Incurring less costs
• The underlying institutions of these strategies have
experienced transition in China in the past 30 years
 easy access to saving service supported by extensive financial branch networks
 pervasive credit constraints in rural areas
 majority of smallholders are discouraged from participating in agricultural
insurance schemes
 rural health reform does not significantly reduce the out-of-pocket payments
 rural minimum living security system can only achieve meeting the food
demands of the poor
 high mobility and penetration of marketization undermine the informal risksharing mechanisms
 gradual integration of the labor market facilitates consumption smoothing
6
Research Questions
• Do farmers in China apply precautionary
saving and labor supply flexibility to insulate
against risk?
• If they do, what is the relationship between
the two self-insurance strategies?
7
Theoretical Framework (1)
• The buffer-stock model (Deaton, 1991; Carroll, 1997; Caroll,
2009)
max Et [ t  0  - t u (ct )]
T
wt 1  1  r  wt  ct   yt 1
yt  pt  t
pt 1  pt gt 1
R E[(g ) ]  1

• Theoretical implications
 Prudent and impatient consumers have a target ratio as the balance
between consumption and saving
 A positive correlation between uncertainty and saving rate or the
target ratio
8
Theoretical Framework (2)
• A stylized fact on intertemporal substitution of
labor supply
– labor supply tends to be high early in life when wages are
low, but low later in life when wages are high
• Explanations from uncertainty
 Approximation results: increased variability in leisure, wage and
consumption lead to leisure being deferred (Low, 2005)
 Simulation results: 1) Flexibility over labor supply allows the age
profile of hours-of-work tracks coincident with the stylized fact (Low,
2005) and 2) Uncertainty about future wages raises current labor supply
and reduces future labour supply (Floden, 2006)
 Estimation results: the self-employed perform self-insurance in
response to greater uncertainty by working longer hours (Parker, Belghitar
and Barmby, 2005)
9
Labor Supply Flexibility and Consumption Path
• Algan et al. (2003): both unemployment duration and job quits rise with
holdings of short-term liquid assets
• Low (2005): labor supply flexibility means individuals can accumulate
assets through working longer hours rather than just through lower
consumption
• Pijoan-Mas (2006): households use their working effort as a self-insurance
mechanism at least as much as they do with precautionary saving
• Marcet, Obiols-Homs and Weil (2006): due to the ex post wealth effect on
labor supply that runs counter the precautionary savings motive,
equilibrium savings and output may be lower under incomplete markets
• Floden (2006): labor supply flexibility facilitates intertemporal
substitution, and raises precautionary saving
• Kimball and Weil (2009): both aversion to risk and aversion to
intertemporal substitution determine the strength of the precautionary
saving motive
10
Data
• Data source
 An annual national rural household survey by the Ministry of Agriculture’s
Research Center for Rural Economy (RCRE)
 A balanced panel from Zhejiang, composing of 427 rural households from 10
villages and 7,686 observations altogether over 1986-1991 and 1995-2006
• Farmers’ saving rate and wealth accumulations
 Trend of farmers’ saving rate
 Wealth accumulations
• Farmers’ participation in labor market





Transformation of income structure
Riskiness of income sources
Number of rural households who earn wage income
Number of rural households who take wage income as the first income source
Time allocation across economic activities
11
Trend of Saving Rate
Rural Households' Saving Rate
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
19781980198219841986198819901992199419961998200020022004200620082010
China
Zhejiang
RCRE Zhejiang
12
Wealth Accumulations
1986
2006
3,933
24,636
(4,899 )
(53,644 )
1) Savings
8.6
53.2
2) Productive capital assets
6.4
0.0
3) Consumer durables
9.6
3.6
4) Housing
76.3
34.6
Total net wealth (yuan at the price in 1978)
Structure of wealth accumulations (%)
13
Transformation of Income Structure
Total net income (yuan)
Income Structure (%)
On-farm business
Agriculture
Cultivation
Forestry
Husbandry
Fishery
Non-agriculture
Manufacturing
Construction
Transportation
Commerce, Catering and Service
Off-farm investment
Labour work
Income from the collective
Salary
Property income
Mean
2,633
1986
Median
2,294
Std
1,713
55.1
40.8
26.6
5.9
4.3
4
14.3
4.5
0.4
4.2
2.6
1.6
8.6
32.6
2
0
57.2
36.2
19.2
0
1.5
0
1
0
0
0
0
0
0
16.8
0
0
34.5
31.9
24.9
18.2
9.3
12.8
26.1
17.2
5.2
15.8
11.9
9.1
17.5
35.2
10.2
0
Mean
14,330
2006
Median
7,283
Std
32,035
37.6
16.5
7.8
3
1
4.8
21.1
9.7
0.4
2.7
3.8
13.7
33.1
3
1.2
11.3
26.1
0
0
0
0
0
0
0
0
0
0
0
12.9
0
0
0
65.5
30.1
19.8
12.4
10.9
17.8
62.4
37.2
4.7
15.7
47.7
29.7
44.9
14.2
7.5
52.2
14
Riskiness of Income Sources
Total net income
On-farm business
Agriculture
Cultivation
Forestry
Husbandry
Fishery
Non-agriculture
Manufacturing
Construction
Transportation
Commerce, Catering and Service
Off-farm investment
Labour work
Income from the collective
Salary
Property income
Observations
427
427
424
423
160
397
181
406
220
52
164
301
305
417
407
92
348
Mean
0.51
0.86
0.86
0.8
1.81
3.62
1.58
1.69
1.85
3.12
3.43
2.34
2.64
1.48
1.88
13.3
2.21
Median
0.47
0.73
0.76
0.69
1.73
1.45
2.5
1.34
2.28
4.01
2.45
2.36
2.52
1.29
1.72
1.3
2.05
Std
0.23
0.77
1.3
0.46
2.49
63.22
7.93
1.45
3.76
1.94
16.03
7.14
1.06
0.8
0.79
28.39
1.12
15
Percentage of Rural Households
Who Earn Wage Income (%)
Income Sources
1986
2006
Agricultural on-farm business
94.8
49.9
Non-agricultural on-farm business
57.8
43.3
Wage
40.0
55.5
Income from the collective
73.1
33.0
Off-farm investment
4.4
21.1
Property income
0.0
46.6
Salary
4.9
3.3
16
Percentage Who Take Wage Income as the
First Income Source (%)
Income Sources
1986
2006
Agricultural on-farm business
40.5
15.2
Non-agricultural on-farm business
13.3
23.0
Wage
5.2
36.5
Income from the collective
36.5
2.3
Off-farm investment
2.1
15.2
Property income
0.0
7.0
Salary
2.3
0.7
17
Time Allocation across Economic Activities
(days per laborer)
Total
On-farm business
Agriculture
Cultivation
Forestry
Husbandry
Fishery
Non-agriculture
Manufacturing
Construction
Transportation
Trade and service
Off-farm investment
Wage
Within village
Agriculture
Non-agriculture
Out of village
Within township
Within county
Income from the collective
Salary
Property income
1986
167.8
123.9
93.1
55
3.4
25.5
9.2
30.8
9.7
2.6
7.4
4.7
6.4
43.8
21.7
—
—
22.1
—
—
—
—
—
2006
261.0
98.3
36.2
15.3
1.9
5.7
13.3
62.2
20.8
0.8
5.7
23.5
11.4
127.9
64.6
24.9
39.6
64.4
24.5
47.6
15.7
2.5
16.5
18
Time Allocation across Economic Activities
All Economic Activities
300
280
260
240
220
200
180
160
140
120
100
80
60
40
20
0
1986
1988
1990
Total
Non-agri On-farm Business
Working as Civil Servant
1995
1997
1999
On-farm Business
Off-farm Labor Supply
Others
2001
2003
2005
Agri On-Farm Business
Off-farm Investment
19
Time Allocation on Agricultural On-farm
Business
Agricultural On-farm Business
60
50
40
30
20
10
0
1986
1988
1990
Cultivation
1995
1997
Forestry
1999
Husbandry
2001
2003
2005
Fishery
20
Time Allocation on Non-Agri On-farm Business
Non-agricultural On-farm Business
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
1986
1988
Manufacture
Transportation
Other Industries
1990
1995
1997
1999
2001
2003
2005
Construction
Commerce,Catering and Service
21
Time Allocation on Off-farm Labor Supply
Off-farm Labor Supply
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
1986
1988
Within Village
1990
1995
1997
Within Township
1999
2001
Within County
2003
2005
Out of County
22
Empirical Strategies
• Constructing Measures of Various Sources of
Risk
• Testing the Functioning of Labor Supply
Flexibility as a Self-insurance
• Testing the Functioning of Precautionary
Saving as a Self-insurance
• Investing the Interaction of Labor Supply
Flexibility and Precautionary Saving
23
Measuring Production Risk (1)
• Just and Pope (1978)
yit  f  xit   h 

  0 


yit

xit  it   0   j x j ,it

j




 jk x j ,it xk ,it  t Dt  uit 

j k

 

 jk x j ,it xk ,it  t Dt it   it


j  j x j,it  
j k
rural household i’s income in one of eight on-farm industries in year t
f (.) the function indicating the effect of input on the mean of output
h(.) the function indicating the effect of input on the variance of output
x j ,it xk ,it the jth or kth input in production in one of eight on-farm industries
Dt dummy variable for survey year t
uit it error term for mean and variance function, respectively
 it stochastic shock in production
24
Measuring Production Risk (2)
• Production specification: a quadratic function
• Estimation strategy: Feasible Generalized Least Square (FGLS)
• Constructing a weighted measure of production risk: taking
time of work on each on-farm industry as weight
• Downside production risk:

s
it
 E[ it  E ( it )]2 if it  E(it )

if it  E(it )
0
 its semivariance of estimated production risk after weighting
 it estimated production risk after weighting
25
Measuring Price Risk (1)
• Chavas and Holt (1990), Coyle (1992), Coyle (2007)
 Step 1. calculating covariance matrix of the adapted price of agricultural
Products
Et 1 p j ,it  p j ,it 1
covt 1  p j ,it , pk ,it   0.50  p j ,it 1  Et  2 p j ,it 1   pk ,it 1  Et  2 pk ,it 1 
0.33  p j ,it  2  Et 3 p j ,it  2   pk ,it  2  Et 3 pk ,it  2 
0.17  p j ,it 3  Et  4 p j ,it 3   pk ,it 3  Et  4 pk ,it 3 
p j ,it pk ,it
price of agricultural product j and k in village i in year t
Et
expectation operator based on information in year t
covt 1  p j ,it , pk ,it  covariance matrix of price of agricultural product j and k
26
Measuring Price Risk (2)
 Step 2. calculating revenue risk of agricultural products
VRt  ytTVpt yt
VRt revenue risk
Vpt covariance matrix of adapted price of agricultural products
yt
vector of each agricultural product’s output
 Step 3. calculating aggregate Tornqvist output index
Torn
 Yt 
log 

 Yt 1 
  i 1 (
m
it  it 1
2
) log(
yit
)
yit 1
Torn
 Yt 

 aggregate Tornqvist output index
Y
 t 1 
it
m
number of agricultural products
share of agricultural product i’s revenue
27
Measuring Price Risk (3)
 Step 4. calculating aggregate Tornqvist price index
Torn
 Pt 


P
 t 1 
Torn
 Yt 
VRt
(
) / (

VRt 1  Yt 1 
)2
 Step 5. calculating the variance of adapted aggregate Tornqvist price
index to measure price risk
vart 1
 P Torn 
  P Torn  P Torn
 t 
  0.50   t 
  t 1 
 P
P


 Pt  2 
 t 1 

  t 1 




2
2
  P Torn  P Torn 

0.33   t 1 
  t 2 
  Pt  2 

 Pt 3 


Torn
Torn
P 
P 
0.17( t  2 
  t 3 
)2
 Pt 3 
 Pt  4 
28
Measuring Health Risk
• Chamon and Prasad (2010)
1
hrikt  
0
hrikt
ifmediikt / consumptionikt  0.2
ifmediikt / consumptionikt  0.2
health risk
mediikt medical expenses
consumptionikt consumption expenditure, expenditure on consumer
durables and housing are calculated as their consumption
flows after depreciation
29
Modeling Labor Supply Flexibility (1)
• Heckman Two-step Estimation Strategy
 The first-stage estimation: participation decision
*
'
pikt
 0  1ikt  Zikt
2  3 t  4 k   ikt
*
1 ifpikt  0
pikt  
*
 0 ifpikt  0
*
the latent variable indicating whether rural household i in village k
pikt
participated in labor market or not in year t
pikt whether rural household i in village k participated in labor market or not
in year t
ikt per capita income of other sources
Z ikt' a vector of variables indicating household characteristics, including age of
the head and its square, household size, dependency ratio, ratio of female
members, number of labors, area of arable lands and forest lands
 t  k dummy variable for survey year and village, respectively
30
Modeling Labor Supply Flexibility (2)
 The second-stage estimation: wage equation (constructing instrumental
wage rate)
wikt  0  1ikt  2ikt  Mikt' 3  4 t  5 k   ikt
wikt real wage rate
Mikt' a vector of variables indicating household characteristics, including age
of the head, its square and cubic, education of the head, highest
education of non-headed laborers, number of laborers with expertise,
number of laborers with trainings, number of years members have
participated in labor market before and its square, percentage of rural
households with members participating in labor market in the village
ikt
inverse Mill’s ratio
 ikt
disturbance term
31
Modeling Labor Supply Flexibility (3)
 The second-stage estimation: time of work decision
'
dikt  0  1wikt  2 ikt  3ikt  Nikt
4
5orikt  6 prkt   7 hrikt  8 t  9 k   ikt
dikt per laborer days of work in labor market
wikt instrumented wage rate
N ikt' a vector of variables indicating household characteristics, including age
of the head and its square, household size and its square, dependency
ratio, ratio of female members, area of arable lands, number of years
members have participated in labor market before and its square,
percentage of rural households with members participating in labor
market in the village
orikt prikt hrikt measures of production risk, price risk and health risk
32
Results: Labor Supply Flexibility
The Sub-sample with Labor Supply
Full Sample
(1)
(2)
(3)
**
Production risk
6.68
(×10-11)
(2.77)
(4)
(5)
**
*
Lagged production risk
4.800
(×10-11)
(2.83)
**
(1)
(2)
***
6.51
10.2
6.83
(2.93)
(3.13)
(1.64)
(2.96)
(4)
***
***
5.11
(3)
(5)
***
7.04
6.83
(1.58)
(1.64)
***
5.57
5.99
(5.96)
(0.52)
Lead production risk
-1.49
-1.36
11.1
(×10-11)
0.00
(10.90)
1.166
2.418
-0.166
1.166
(1.61)
(1.64)
-14.05
(1.57)
(1.61)
2.601
(20.67)
(1.44)
Price risk
-2.25
-1.908
(1.17)
*
-2.179
(1.52)
(1.36)
(1.23)
Lagged price risk
-1.778
-0.256
(1.57)
(1.24)
*
Lead prce risk
Health risk
Lagged health risk
Lead health risk
*
-2.195
-0.608
0.951
(1.33)
(1.45)
-28.4
-25.32
-28.4
(18.63)
(16.90)
(18.63)
-24.05
-19.7
(0.95)
-15.65
(17.17)
(16.17)
(15.94)
6.383
10.37
-9.58
(18.67)
(17.13)
(19.19)
-6.191
-7.983
-23.91
(17.37)
(15.27)
(17.98)
33
Modeling Precautionary Saving
• The wealth accumulation equation
P
'
ln wealthikt  0  1 yikt
 Nikt
2  3orikt  4 prkt
5hrikt  6 t  7 k  ikt
wealthikt total net wealth
yiktP
N ikt'
permanent income constructed by calibrating a dynamic income
process
a vector of variables including demographics (age of the head and
its square, household size and its square, and number of laborers),
social connections as proxies for risk preference (whether a rural
household is a five-guarantee one, with members being martyrs,
civil servants, cadres and party members), income structure
(number of income sources, the first and second important income
source, the principal on-farm business and the industry with most
labor allocation)
34
Interaction of Labor Supply Flexibility and
Precautionary Saving
• The wealth accumulation equation with the interaction terms
of risks and time of work
P
'
ln wealthikt  0  1 yikt
 Nikt
2  3orikt  4 prkt  5hrikt
(6orikt  7 prkt  8hrikt )  dikt  9dikt
10 t  11 k  ikt
(orikt  prkt  hrikt )  dikt the interaction terms of production risk, price risk and
health risk and time of work
35
Estimation Results
Full Sample
(1)
Production risk
-13
(×10 )
Price risk
Health risk
(2)
***
1.65
(0.30)
-0.002
(0.00)
***
-0.196
(0.05)
Production risk*days of work
-16
(×10 )
Price risk*days of work
-5
(×10 )
Health risk*days of work
-4
(×10 )
Days of work
-4
(×10 )
Constant
Observations
Adjusted R2
A Sub-sample with Labor Supply
*
1.056
(0.55)
7256
0.6147
***
2.41
(0.33)
0.001
(0.00)
***
-0.220
(0.06)
***
-1.02
(1)
(2)
***
1.44
(0.17)
-0.005
(0.00)
**
-0.197
(0.06)
***
29.9
(10.20)
-0.005
(0.01)
**
-0.255
(0.11)
***
-26.4
(0.30)
-0.807
(9.42)
-0.036
(0.68)
0.919
(0.79)
1.462
(1.49)
0.92
(0.65)
*
1.055
(0.55)
7256
0.6151
(2.11)
1.036
(0.69)
**
1.243
(0.58)
5091
0.6221
**
1.190
(0.58)
5091
0.6212
36
Empirical Findings
• Farmers adjust instantaneous and ex post labor supply in response to risk
• Farmers increase days of work to mitigate production risk, but reduce days
of work as a consequence of health risk
• Farmers hold precautionary saving to insulate against risk
• Farmers increase wealth in anticipation of production risk, but deplete
assets to react to health shocks
• Given the level of risk, adjustment in days of work functions as a
substitute to precautionary saving
• Dynamic relationship between the two strategies: when the severity of
shocks exceeds the extent to which precautionary saving can insulate
against, farmers increase days of work and deplete assets first. After
accumulated precautionary saving due to increased days of work can
perfectly insulate against shocks, farmers reduce days of work.
37
Policy Implications
• Promoting the development of labor market improves the
opportunities which poor rural households with low assets can
exploit in response to risks
• Promoting the development of labor market can also be an
effective way to lessen rural households’ strength of precautionary
saving
• With precautionary saving and labor supply flexibility to insulate
against idiosyncratic risk, policies should focus on severe shocks like
catastrophes and major diseases
• The functioning of precautionary saving and labor supply flexibility
as self-insurance partly explains farmers’ low demand for
agricultural insurance
• Improving the effective coverage of social safety nets will be more
helpful for the majority of smallholders
38
Limitations and Future Work
• Estimating days of work and wealth accumulation equations
simultaneously to avoid the endogeneity of labor supply and
wealth holdings
• Conducting a simulation to gauge the substitution between
labor supply flexibility and precautionary saving
• Introducing measures of the risk of return to capital and wage
risk
• Improving estimation strategy to exploit the advantage of
panel data
• Investigating the importance of labor supply flexibility by
using individual information
39