The impact of adaptation practices on crop productivity in northwest Ethiopia: an endogenous switching estimation

Figures & data

Figure 1. Location map of Rib watershed. The map shows the location of the study area with indication of woredas and the stream flow.

Table 1. Proportional sample size distribution.

Agro-climatic zone	Number of Kebeles	Number of household by 2014	Sampled Kebeles	Proportional sample size
Dega	11	15,278	Ata Sahrna	73
WoinaDega	40	65,435	Woji; Tiwha; Kokit; Agela; Tara; Bura; Angot; Yifag; Hiruy; Tsegur	310

Source: (Computed from Central Statistical Agency, 2013).

Note: The table shows the proportional sample distribution within the agro-climate zone of the study area.

Table 2. Description of variables and hypothesis for the outcome variable.

Dependent variable for the outcome equation: (yield)
No.	Explanatory variables with codes		Definition and measurement	Expected. sign
1	Demographic characteristics
	EDUC	Education in years	Continuous	+
	HHSIZE	Household size	Head count	+
	SEX	Gender of the head of the household	1 if male and 0 otherwise	+/−
	AGE	Age of the household head	Continuous	+/−
	EXP	Farm experience in years	Continuous	+/−
2	Assets/wealth
	FRMSZE	Farm size in hectare	Continuous	+/−
	FRMY	Farm income in a year	Continuous	+
	NFRMY	Nonfarm income in a year	Continuous	+/−
	RADO	Radio ownership	1 if yes; and 0 otherwise	+
	MOBLE	Mobile ownership	1 if yes; and 0 otherwise	+
	TLU	Tropical Livestock Unit	TLU	+
3	Institutional factors
	CREDT	Credit access	1 if there is and 0 otherwise	+
	EXTN	Extension access frequency with DA (experts)	1 if None; 2 if weekly; 3 if per two-three weeks; 4 if monthly and above	+
	DEMO	Demonstration site availability	1 if available 0 otherwise	+
4	Social capital
	F_F_EXTN	Farmer to farmer extension	1 yes; and 0 otherwise	+
	NEIGBOR	Number of neighbors	Headcount	+
	COOP	Membership in cooperative	1 member and 0 otherwise	+
5	Infrastructure
	HOME_FARMDSTCE	Average distance between home and farm in minutes	Continuous	−
6	Land characteristics
	FRMSLP	Farmers perceived slope of the farm	1 if gentle, 2 if moderate, 3 if steep	+
	SOIL	Farmers’ reported soil fertility	1 if Fertile, 2 if moderate, 3 if degraded	+
7	Environmental factors
	AGRO_ClIMATE	Traditional climate zone	1 if Dega, and 0 WoinaDega	+/−
	RF	Average rainfall of 1980–2015		+/−
	Temp	Average temperature of 1980–2015		+/−
	Drought	If experienced drought in 2016	1 if experienced and 0 otherwise	−
	Flood	Flood severity on cropland	1 if severely affected and 0 otherwise
8	Instruments for adaptation
	DSTCE_Mkt	Distance markets in minutes	Continuous	−
	CLI_INFO	Have information on climate change	1 if there is and 0 otherwise	+

Notes: The table shows the definition and measurement of the variables. The variables are the determinants of adaptation and crop yield. The instrumental variables are hypothesized as determinants of adaptation only.

Table 3. Parameters estimates of adaptation and crop productivity equations (Maize in ln of yield).

1	2	3	4	5
Explanatory variables	Adaptation (1/0)	OLS	ESR adapters	ESR non-adapters
Marital status (married)	0.1156*(0.236)	0.0134(0.026)	0.0052(0.031)*	0.0059(0.043)
AGE	−0.005(0.008)	0.0004(0.001)	−0.002**(0.001)	0.0021*(0.002)
Education	0.059(0.198)	0.0029(0.023)	−0.0076(0.026)	−0.0038(0.040)
Household size	0.0503(0.055)	−0.0011(0.006)	0.0002(0.007)	−0.0011(0.01)
Credit	0.1118(0.199)	0.0078(0.023)	0.0089(0.027)	−0.0026*(0.04)
TLU	0.195***(0.05)	0.0028(0.006)	0.0085*(0.006)	0.0163(0.01)
Urea/ha		0.0008(0.001)	0.0001(0.001)	0.0038*(0.002)
Soil erosion (high)		−0.0086(0.018)	−0.0309(0.020)	0.0632(0.032)
Seed type (improved)		0.0050(0.022)	0.0507**(0.025)	0.0731*(0.04)
Soil fertility degraded		−0.063**(0.025)	−0.0402(0.028)	−0.0649(0.05)
Farm size		0.0004(0.020)	−0.0222(0.023)	0.0335(0.033)
Soil type		0.0318**(0.014)	0.0134(0.016)	0.0636**(0.023)
Contact DA		−0.074**(0.035)	−0.078**(0.043)	−0.0945(0.05)
Working days		−0.0011(0.001)	−0.0006(0.002)	−0.003(0.002)
Agro-climate zone	−1.716**(0.53)	0.0106(0.050)	0.2042(0.164)	0.0547(0.065)
Compost	−0.51**(0.31)	0.0230(0.025)	0.0364(0.031)	0.0495**(0.035)
Insecticide use		−0.0110(0.029)	0.0051(0.032)	0.0014(0.048)
Temperature	0.219**(0.051)	−0.0004(0.006)	0.0068(0.007)	−0.026**(0.010)
Rainfall (rainy season)	0.0009*(0.001)	0.002**(0.0001)	0.002**(0.0001)	0.002**(0.0001)
Drought	0.596(0.231)*	−0.0062(0.025)	−0.0248(0.030)*	−0.0218(0.047)
Flood	0.761(0.211)	−0.0062(0.025)	−0.0120(0.032)*	−0.0211(0.038)
Demonstration site	0.8405(0.191)
Constant	−5.68**(1.209)	0.587***(0.169)	0.598***(0.224)	0.925(0.303)***
Distance to market	0.0120*(0.007)
Climate information	0.616***(0.23)
Adaptation		0.04(0.027)
	/lns0 −1.734***(.096)	/lns1-1.89***(.059)	/r0 -.82***(.256)	/r1 .328(.248)
Number of obs	282	282	282	282
Wald chi2(21) = 818.49; Log likelihood = 16.759549; Prob > chi2 = 0.0000
	F(22, 259) = 104.62; Prob > F = 0.0000; Adj R^2 = −.89
LR test of indep. eqns.:chi2(2) = 9.34 Prob > chi2 = 0.0094

Notes: The table shows adaptation is statistically insignificant in the OLS estimation. However, the ESR estimation, that accounts the potential endogeneity, shows the heterogeneity of the factors that affect the yield of adapters and non-adapters.

***p < .01, **p < .05, *p < .1. Standard errors in parentheses.

Table 4. Average expected yield (kg/hectare) and net crop income; treatment and heterogeneity effects.

Crop	Farm households (r1)	Decision		Adaptation effects (c3)
		Adapt (c1)	Not to adapt (c2)
Maize	That adapted (r2)	21.29(.798)	18.5(.755)	ATT = 2.79(1.1)**
	That did not adapt (r3)	21(.901)	17.9(.10)	ATU = 3.1(1.3)**
	Heterogeneity (r4)	0.29(.05)***	0.6(1.2)	−.31(2.5)
Teff	That adapted (r5)	14.2 (.32)	9.5(.11)	ATT = 4.7(.34)***
	That did not adapt (r6)	19.4 (1.04)	14.6(.52)	ATU = 4.8(1.2)***
	Heterogeneity (r7)	−5.2(.95)***	−5.1***(.45)	−.1 (.53)**
Net Crop income/ha in Birr	That adapted (r8)	5205 (39)	3312(15)	ATT = 1893(42)***
	That did not adapt (r9)	6294(175)	2642(16)	ATU = 3652(176)**
	Heterogeneity (r10)	−1089*	670	−1759***

Notes: The row (r2) and (r5) of Table 4, respectively report the adapters’ actual yields of Maize and Teff and the yields that would have been produced if the farm households had not adapted. The row (r3) presents the non-adapters yield of Maize and the yield that would have been produced if the farm households had adapted.

***p < .01, **p < .05, *p < .1. Standard errors in parentheses.

Table 5. T-test on soil attributes of adapters and non-adapters for teff.

Averaged soil characteristics	Adapters	Non-adapters	Difference
Rated average soil fertility	1.86(0.049)	1.99(0.045)	.13**(0.071)
Soil erosion	2.31(0.057)	2.1(0.053)	.21**(0.081)

Source: Researchers survey (2016).

Notes: Soil fertility (1 refers degraded, 3 very fertile); soil erosion (1 low; 3 severe). The table shows the statistically significant difference in degree of soil erosion and fertility between adapters and non-adapters.

***p < .01, **p < .05, *p < .1. Standard errors are in brackets.

Central Statistical Agency. 2013. Population Projection of Ethiopia for All Regions at Wereda Level from 2014–2017. Addis Ababa, Ethiopia: Central Statistical Agency.

 Google Scholar