Promoting sustainable agrifood production under climate change: adaptation, returns, and food security implications

Figures & data

Table 1. Variable definition and summary statistics.

Variables	Measurements	Mean (S.D.)
Dependent variables
Land productivity	Rice output per unit of land (Yuan/mu)^a	670.63 (722.36)
Labor productivity	Rice output per unit of labor (Yuan/labor-day)	59.53 (186.04)
Climate change adaptation	1 if household has adopted improved varieties (e.g. Insect/disease-resistant or stress-tolerant varieties) and/or soil and water conservation practices (e.g. minimum tillage), 0 otherwise	0.54 (0.50)
Independent variables
Age	Age of household head (years)	53.90 (12.55)
Gender	1 if household head is male; 0 otherwise	0.65 (0.48)
Education	Educational years of household head (years)	6.95 (3.95)
Life satisfaction	Self-reported life satisfaction level of household head: 1=very unsatisfied; 2=unsatisfied; 3=fair; 4=satisfied; 5=very satisfied	4.06 (0.88)
Family size	Number of family members (persons)	4.50 (1.54)
Farm size	Total land size for rice cultivation (mu)^a	8.18 (27.69)
Asset ownership	1 if household owns electronic bicycle(s), 0 otherwise	0.58 (0.49)
Access to extension	1 if agricultural information extension agents exist in the local village, 0 otherwise	0.20 (0.40)
Pest experience	1 if household experienced pest attack during rice production, 0 otherwise	0.12 (0.32)
Temperature perception	Self-reported perception of temperature change in the last five years: 1=Extremely severe; 2=Severe; 3=Moderate; 4=Minor; 5=Very minor	3.35 (1.10)
Precipitation perception	Self-reported perception of precipitation changes in the last five years: 1=Extremely severe; 2=Severe; 3=Moderate; 4=Minor; 5=Very minor	3.43 (1.03)
Drought experience	1 if household experienced drought during rice production, 0 otherwise	0.10 (0.30)
Irrigation frequency	Frequency of irrigation during rice cultivation	2.84 (2.83)
Transportation	Distance to the nearest train station (km)	40.39 (41.22)
Distance to credit source	Distance to the nearest formal (e.g. bank or financial agents) and informal (e.g. relatives or friends) credit sources (km)	2.61 (2.44)
Jiangsu	1 if household locates in Jiangsu province, 0 otherwise	0.13 (0.34)
Henan	1 if household locates in Henan province, 0 otherwise	0.15 (0.36)
Hubei	1 if household locates in Hubei province, 0 otherwise	0.19 (0.39)
Hunan	1 if household locates in Hunan province, 0 otherwise	0.27 (0.45)
Sichuan	1 if household locates in Sichuan province, 0 otherwise	0.26 (0.44)
Sample size		415

S.D. refers to the standard deviation.

^aYuan is Chinese currency (1 USD = 6.45 Yuan in 2021); 1 mu = 1/15 hectare.

Table 2. Mean differences of the selected variables between adapters and non-adapters.

Variables	Adapters	Non-adapters	Mean differences
Land productivity	743.07 (719.58)	584.45 (718.04)	158.62**
Labor productivity	73.04 (217.48)	43.47 (138.61)	29.57
Age	54.17 (12.70)	53.59 (12.39)	0.58
Gender	0.68 (0.47)	0.61 (0.49)	0.07
Education	7.08 (3.82)	6.80 (4.11)	0.28
Life satisfaction	3.96 (0.91)	4.18 (0.84)	−0.23***
Family size	4.31 (1.50)	4.73 (1.57)	−0.43***
Farm size	8.97 (26.23)	7.25 (29.38)	1.72
Asset ownership	0.55 (0.50)	0.61 (0.49)	−0.06
Access to extension	0.16 (0.37)	0.26 (0.44)	−0.10**
Pest experience	0.14 (0.35)	0.09 (0.29)	0.05
Temperature perception	3.57 (0.99)	3.08 (1.17)	0.49***
Precipitation perception	3.62 (0.91)	3.19 (1.12)	0.43***
Drought experience	0.11 (0.31)	0.08 (0.27)	0.03
Irrigation frequency	2.66 (2.69)	3.06 (2.97)	−0.41
Transportation	44.76 (49.10)	35.20 (28.49)	9.56**
Distance to credit source	2.90 (2.66)	2.25 (2.11)	0.65***
Jiangsu	0.09 (0.28)	0.18 (0.38)	−0.09***
Henan	0.19 (0.39)	0.10 (0.30)	0.09***
Hubei	0.18 (0.38)	0.19 (0.40)	−0.02
Hunan	0.28 (0.45)	0.26 (0.44)	0.03
Sichuan	0.26 (0.44)	0.27 (0.44)	−0.01
Sample size	225	190

***p < 0.01 and **p < 0.05. Standard deviation is presented in parentheses.

Table 3. Determinants of climate change adaptation: probit model estimates.

Variables	Coefficients	Marginal effects
Age	0.015 (0.007)**	0.005 (0.002)**
Gender	0.225 (0.145)	0.078 (0.049)
Education	0.038 (0.021)*	0.013 (0.007)*
Life satisfaction	−0.260 (0.079)***	−0.090 (0.026)***
Family size	−0.072 (0.045)	−0.025 (0.015)
Farm size	0.003 (0.002)	0.001 (0.001)
Asset ownership	−0.074 (0.148)	−0.026 (0.051)
Access to extension	−0.204 (0.166)	−0.070 (0.057)
Pest experience	0.139 (0.261)	0.048 (0.090)
Temperature perception	0.213 (0.087)**	0.074 (0.030)**
Precipitation perception	0.110 (0.097)	0.038 (0.033)
Drought experience	0.069 (0.285)	0.024 (0.098)
Irrigation frequency	−0.028 (0.025)	−0.010 (0.008)
Transportation	0.005 (0.002)***	0.002 (0.001)***
Distance to credit source	0.035 (0.030)	0.012 (0.010)
Jiangsu	0.034 (0.248)	0.012 (0.085)
Henan	0.521 (0.234)**	0.180 (0.079)**
Hubei	−0.222 (0.206)	−0.076 (0.071)
Hunan	0.155 (0.185)	0.053 (0.064)
Constant	−1.098 (0.676)
Summary statistics
Pseudo R^2	0.121
Model χ^2	70.83***, p-value = 0.000
Log-likelihood	−251.477
Sample size	415

***p < 0.01, **p < 0.05, and *p < 0.10. The reference province is Sichuan. Robust standard errors are presented in parentheses.

Figure 1. Density distribution of propensity scores for adapters and non-adapters before and after matching.

Table 4. Matching quality test: balancing property.

	Before matching	After matching
		KBM	NNM (1–5)
Pseudo R^2	0.121	0.006	0.009
Mean bias	19.0	3.5	4.0
LR χ^2	69.40***	3.72	5.07
p-value	0.000	1.000	0.999

***p < 0.01.

Table 5. Average treatment effects of climate change adaptation on returns to land and labor: PSM estimation.

	Mean outcomes			Change (%)
	Actual	Counterfactual	ATT
KBM
Land productivity	740.820	513.419	227.401 (72.122)***	44.29
Labor productivity	71.978	46.419	25.559 (14.964)*	55.06
NNM (1–5)
Land productivity	740.820	524.520	216.300 (84.827)**	41.24
Labor productivity	71.978	43.966	28.013 (16.910)*	63.72

***p < 0.01, **p < 0.05, and *p < 0.10. ATT refers to average treatment effects on the treated. Bootstrap standard errors based on 100 replications are presented in parentheses for ATT.

Table A1. Rosenbaum bounds for treatments effects of climate change adaptation on returns to land and labor.

Outcome variables	Gamma	Sig+upper bound significance level	Sig- lower bound significance level	t-hat+upper bound Hodges- Lehman point estimate	t-hat+upper bound Hodges- Lehman point estimate
Land productivity	1.00	0	0	674.844	674.844
	1.20	0	0	633.333	720.000
	1.40	0	0	583.333	783.333
	1.60	0	0	550.000	836.667
	1.80	0	0	525.000	872.500
	2.00	0	0	500.000	900.000
Labor productivity	1.00	0	0	28.571	28.571
	1.20	0	0	21.875	34.722
	1.40	0	0	18.056	39.818
	1.60	0	0	14.444	46.875
	1.80	0	0	12.578	52.000
	2.00	0	0	11.638	56.250

N = 225 matched pairs. Gamma is the log odds differential assignment due to unobserved factors.

Table A2. Average treatment effects of climate change adaptation on returns to land and labor: IPWRA estimation.

	Mean outcomes			Change (%)
	Actual	Counterfactual	ATT
IPWRA
Land productivity	743.921	535.323	208.598 (69.138)***	38.97
Labor productivity	73.098	48.105	24.993 (16.022)	51.96

***p < 0.01. ATT refers to average treatment effects on the treated. Robust standard errors are presented in parentheses for ATT.

Table A3. Average treatment effects of climate change adaptation on net returns: PSM estimation.

	ATT
	KBM	NNM (1–5)
Net returns	318.552 (72.137)***	311.245 (94.038)***

***p < 0.01. ATT refers to average treatment effects on the treated. Bootstrap standard errors based on 100 replications are presented in parentheses for ATT.

Data availability statement

The data that support the findings of this study are available from Hongyun Zheng upon request.