Risk Coping Strategies for Farmers in Transition: Labor Supply Flexibility

versus Precautionary Saving

Kevin Z. Chen and Ling JinInternational Food Policy Research Institute and

Zhejiang University, respectivelyApril 26, 2012

1

Typical Risks Farmers Face in Developing Countries

Source: Quoted from Dercon (2005): Risk Insurance and Poverty: A Review. And the author’s calculation is based on Ethiopian Rural Panel Data Survey (1994-1997).

EventsPercentage of Rural

Households Who Reported

Harvest failure (drought, flooding, frost, pests) 78

Policy shock (forced labor, ban on migration, new levies or taxes)

42

Labor problems (illness or deaths) 40Oxen problems (diseases, deaths) 39Other livestock (disease, deaths) 35Land problems (villagization, land reform) 17

Assets losses (fire, loss) 16

War 7Crime/banditry (theft, violence) 3

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 yearseasy access to saving service supported by extensive financial branch

networkspervasive credit constraints in rural areasmajority of smallholders are discouraged from participating in agricultural

insurance schemesrural health reform does not significantly reduce the out-of-pocket paymentsrural minimum living security system can only achieve meeting the food

demands of the poorhigh mobility and penetration of marketization undermine the informal risk-

sharing mechanismsgradual 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)

• Theoretical implicationsPrudent and impatient consumers have a target ratio as the balance

between consumption and savingA positive correlation between uncertainty and saving rate or the

target ratio

8

-

0max [ ( )]

T t

t ttE u c

1 11t t t tr w cw y

t t ty p

1 t 1gt tp p

[(g ) ] 1R E

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 uncertaintyApproximation 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 accumulationsTrend of farmers’ saving rateWealth accumulations

• Farmers’ participation in labor marketTransformation of income structureRiskiness of income sourcesNumber of rural households who earn wage incomeNumber of rural households who take wage income as the first income

sourceTime allocation across economic activities

11

Trend of Saving Rate

12

19781980

19821984

19861988

19901992

19941996

19982000

20022004

20062008

20100.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

Rural Households' Saving Rate

China Zhejiang RCRE Zhejiang

Wealth Accumulations

13

1986 2006

Total net wealth (yuan at the price in 1978) 3,933 24,636

(4,899 ) (53,644 )

Structure of wealth accumulations (%)

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

Transformation of Income Structure

14

1986 2006Mean Median Std Mean Median Std

Total net income (yuan) 2,633 2,294 1,713 14,330 7,283 32,035Income Structure (%) On-farm business 55.1 57.2 34.5 37.6 26.1 65.5 Agriculture 40.8 36.2 31.9 16.5 0 30.1 Cultivation 26.6 19.2 24.9 7.8 0 19.8 Forestry 5.9 0 18.2 3 0 12.4 Husbandry 4.3 1.5 9.3 1 0 10.9 Fishery 4 0 12.8 4.8 0 17.8 Non-agriculture 14.3 1 26.1 21.1 0 62.4 Manufacturing 4.5 0 17.2 9.7 0 37.2 Construction 0.4 0 5.2 0.4 0 4.7 Transportation 4.2 0 15.8 2.7 0 15.7 Commerce, Catering and Service 2.6 0 11.9 3.8 0 47.7 Off-farm investment 1.6 0 9.1 13.7 0 29.7 Labour work 8.6 0 17.5 33.1 12.9 44.9 Income from the collective 32.6 16.8 35.2 3 0 14.2 Salary 2 0 10.2 1.2 0 7.5 Property income 0 0 0 11.3 0 52.2

Riskiness of Income Sources

15

Observations Mean Median StdTotal net income 427 0.51 0.47 0.23 On-farm business 427 0.86 0.73 0.77 Agriculture 424 0.86 0.76 1.3 Cultivation 423 0.8 0.69 0.46 Forestry 160 1.81 1.73 2.49 Husbandry 397 3.62 1.45 63.22 Fishery 181 1.58 2.5 7.93 Non-agriculture 406 1.69 1.34 1.45 Manufacturing 220 1.85 2.28 3.76 Construction 52 3.12 4.01 1.94 Transportation 164 3.43 2.45 16.03 Commerce, Catering and Service 301 2.34 2.36 7.14 Off-farm investment 305 2.64 2.52 1.06 Labour work 417 1.48 1.29 0.8 Income from the collective 407 1.88 1.72 0.79 Salary 92 13.3 1.3 28.39 Property income 348 2.21 2.05 1.12

Percentage of Rural HouseholdsWho Earn Wage Income (%)

16

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

Percentage Who Take Wage Income as the First Income Source (%)

17

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

Time Allocation across Economic Activities (days per laborer)

18

1986 2006Total 167.8 261.0On-farm business 123.9 98.3Agriculture 93.1 36.2 Cultivation 55 15.3 Forestry 3.4 1.9 Husbandry 25.5 5.7 Fishery 9.2 13.3Non-agriculture 30.8 62.2 Manufacturing 9.7 20.8 Construction 2.6 0.8 Transportation 7.4 5.7 Trade and service 4.7 23.5Off-farm investment 6.4 11.4Wage 43.8 127.9 Within village 21.7 64.6 Agriculture — 24.9 Non-agriculture — 39.6 Out of village 22.1 64.4 Within township — 24.5 Within county — 47.6Income from the collective — 15.7Salary — 2.5Property income — 16.5

Time Allocation across Economic Activities

19

19861987

19881989

19901991

19951996

19971998

19992000

20012002

20032004

20052006

0 20 40 60 80

100 120 140 160 180 200 220 240 260 280 300

All Economic Activities

Total On-farm Business Agri On-Farm BusinessNon-agri On-farm Business Off-farm Labor Supply Off-farm InvestmentWorking as Civil Servant Others

Time Allocation on Agricultural On-farm Business

20

1986198719881989199019911995199619971998199920002001200220032004200520060

10

20

30

40

50

60

Agricultural On-farm Business

Cultivation Forestry Husbandry Fishery

Time Allocation on Non-Agri On-farm Business

21

19861987

19881989

19901991

19951996

19971998

19992000

20012002

20032004

20052006

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0 Non-agricultural On-farm Business

Manufacture Construction Transportation Commerce,Catering and ServiceOther Industries

Time Allocation on Off-farm Labor Supply

22

19861987

19881989

19901991

19951996

19971998

19992000

20012002

20032004

20052006

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Off-farm Labor Supply

Within Village Within Township Within County Out of County

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)

24

, ,0 , t tit it it it j j it j it itjk k itj j k

y f x h x x x x D u

, ,0 , t tj j it j it it itjk k itj j kx x x D

ity 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

,j itx the jth or kth input in production in one of eight on-farm industries,k itx

tD dummy variable for survey year t

itu it error term for mean and variance function, respectively

it stochastic shock in production

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:

25

2[ ( )]

0s it itit

E E

( )it itif E

( )it itif E

sit semivariance of estimated production risk after weighting

it estimated production risk after weighting

Measuring Price Risk (1)•Chavas and Holt (1990), Coyle (1992), Coyle (2007)

Step 1. calculating covariance matrix of the adapted price of agricultural Products

26

1 , , 1t j it j itpE p

1 , , , 1 2 , 1 , 1 2 , 1cov , 0.50t j it k it j it t j it k it t k itp p p E p p E p

, 2 3 , 2 , 2 3 , 20.33 j it t j it k it t k itp E p p E p

, 3 4 , 3 , 3 4 , 30.17 j it t j it k it t k itp E p p E p

,j itp ,k itp price of agricultural product j and k in village i in year t

tE expectation operator based on information in year t

1 , ,cov ,t j it k itp p covariance matrix of price of agricultural product j and k

Measuring Price Risk (2)

Step 2. calculating revenue risk of agricultural products

Step 3. calculating aggregate Tornqvist output index

27

Tt t t tVR y Vp y

tVR revenue risk

tVp

vector of each agricultural product’s output ty

covariance matrix of adapted price of agricultural products

11

1 1

log ( ) log( )2

Torn

t it itm

iit

t it

Y y

Y y

1

Torn

t

t

Y

Y

aggregate Tornqvist output index m number of agricultural products

it share of agricultural product i’s revenue

Measuring Price Risk (3)

Step 4. calculating aggregate Tornqvist price index

Step 5. calculating the variance of adapted aggregate Tornqvist price index to measure price risk

28

2

1 1 1

( ) / ( )

Torn Torn

t t t

t t t

P VR Y

P VR Y

2

11

1 1 2

var 0.50

Torn Torn Torn

t t tt

t t t

P P P

P P P

2

1 2

2 3

0.33

Torn Torn

t t

t t

P P

P P

22 3

3 4

)0.17(Torn Torn

t t

t t

P P

P P

Measuring Health Risk

• Chamon and Prasad (2010)

29

1

0ikthr

/ 0.2ikt iktifmedi consumption

/ 0.2ikt iktifmedi consumption

ikthr

iktmedi

health risk

medical expenses

iktconsumption consumption expenditure, expenditure on consumer durables and housing are calculated as their consumption flows after depreciation

Modeling Labor Supply Flexibility (1)

• Heckman Two-step Estimation StrategyThe first-stage estimation: participation decision

30

* '0 1 2 3 4ikt ikt ikt t k iktp Z

1

0iktp

* 0iktifp * 0iktifp

*iktp the latent variable indicating whether rural household i in village k

participated in labor market or not in year t

ikt per capita income of other sources

iktpwhether rural household i in village k participated in labor market or not in year t

'iktZ 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

Modeling Labor Supply Flexibility (2)

The second-stage estimation: wage equation (constructing instrumental wage rate)

31

'0 1 2 3 4 5ikt ikt ikt ikt t k iktw M

iktw real wage rate

'iktM 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

Modeling Labor Supply Flexibility (3)

The second-stage estimation: time of work decision

32

'0 1 2 3 4ikt ikt ikt ikt iktd w N

5 6 7 8 9ikt kt ikt t k iktor pr hr

iktd per laborer days of work in labor market

iktw instrumented wage rate

'iktN 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

iktor iktpr ikthr measures of production risk, price risk and health risk

Results: Labor Supply Flexibility

33

Full Sample The Sub-sample with Labor Supply

(1) (2) (3) (4) (5) (1) (2) (3) (4) (5)

Production risk 6.68** 6.51** 10.2** 6.83*** 7.04*** 6.83***

(×10-11) (2.77) (2.93) (3.13) (1.64) (1.58) (1.64)

Lagged production risk 4.800* 5.11 5.57*** 5.99***

(×10-11) (2.83) (2.96) (5.96) (0.52)

Lead production risk -1.49 -1.36 11.1

(×10-11) 0.00 (1.17) (10.90)

Price risk -2.25 -1.908 -2.179* 1.166 2.418 -0.166 1.166

(1.52) (1.36) (1.23) (1.61) (1.64) (1.57) (1.61)

Lagged price risk -1.778 -0.256 -14.05 2.601*

(1.57) (1.24) (20.67) (1.44)

Lead prce risk -2.195* -0.608 0.951

(1.33) (0.95) (1.45)

Health risk -24.05 -19.7 -15.65 -28.4 -25.32 -28.4

(17.17) (16.17) (15.94) (18.63) (16.90) (18.63)

Lagged health risk 6.383 10.37 -9.58

(18.67) (17.13) (19.19)

Lead health risk -6.191 -7.983 -23.91

　 　 (17.37) (15.27) (17.98)

Modeling Precautionary Saving • The wealth accumulation equation

34

'0 1 2 3 4ln P

ikt ikt ikt ikt ktwealth y N or pr

5 6 7ikt t k ikthr

iktwealth total net wealthPikty

permanent income constructed by calibrating a dynamic income process

'iktN 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)

Interaction of Labor Supply Flexibility and Precautionary Saving

• The wealth accumulation equation with the interaction terms of risks and time of work

35

'0 1 2 3 4 5ln P

ikt ikt ikt ikt kt iktwealth y N or pr hr

6 7 8 9( )ikt kt ikt ikt iktor pr hr d d

10 11t k ikt

( )ikt kt ikt iktor pr hr d the interaction terms of production risk, price risk and health risk and time of work

Estimation Results

36

Full Sample A Sub-sample with Labor Supply

(1) (2) (1) (2)

Production risk 1.65*** 2.41*** 1.44*** 29.9***

(×10-13) (0.30) (0.33) (0.17) (10.20)

Price risk -0.002 0.001 -0.005 -0.005

(0.00) (0.00) (0.00) (0.01)

Health risk -0.196*** -0.220*** -0.197** -0.255**

(0.05) (0.06) (0.06) (0.11)

Production risk*days of work -1.02*** -26.4***

(×10-16) (0.30) (9.42)

Price risk*days of work -0.807 -0.036

(×10-5) (0.68) (0.79)

Health risk*days of work 0.919 1.462

(×10-4) (1.49) (2.11)

Days of work 0.92 1.036

(×10-4) (0.65) (0.69)

Constant 1.056* 1.055* 1.190** 1.243**

(0.55) (0.55) (0.58) (0.58)

Observations 7256 7256 5091 5091

Adjusted R2 0.6147 0.6151 0.6212 0.6221

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

39

• 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