Experimental evidence from a fodder shrub promotional effort among dairy farmers in Uganda

Figures & data

Figure 1. Treatment Groups.

Table 1. Baseline respondent and household characteristics and outcome variable comparison.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
	T	C	TS	TS+CS	T vs. C	TS = TS+CS	T vs. C	TS vs. C	TS+CS vs. C
	Mean	Mean	Mean	Mean	Dif.	Chi2/F	Std. dif.	Std. dif.	Std. dif.
Head is 60 years of over	0.19	0.21	0.20	0.17	−0.0083	0.0603	0.070	0.039	0.100
					(0.026)
Respondent is female	0.53	0.55	0.51	0.55	−0.018	0.891	0.037	0.070	0.005
					(0.027)
Male headed household	0.94	0.90	0.95	0.93	0.038*	2.37	−0.144	−0.168	−0.120
					(0.021)
Res. member of dairy group	0.05	0.06	0.02	0.09	−0.014	3.018*	0.004	0.179	−0.123
					(0.030)
Fodder shrub last 12 months	0.18	0.25	0.22	0.15	−0.043	0.352	0.154	0.066	0.246
					(0.039)
Respondent’s age	42.93	44.65	44.19	41.68	−1.02	2.514	0.127	0.034	0.217
					(0.87)
Years of education of respondent	6.41	6.34	6.05	6.76	−0.095	1.131	−0.017	0.077	−0.108
					(0.34)
Household size	6.83	6.65	6.96	6.71	0.30	0.179	−0.064	−0.109	−0.019
					(0.25)
Baseline wealth index	1.61	1.74	1.48	1.74	−0.092	8.034***	0.149	0.323	−0.003
					(0.11)
Baseline # of dairy cows	2.39	2.18	2.34	2.44	0.10	0.519	−0.159	−0.126	−0.190
					(0.11)
Baseline FTT knowledge score	1.32	1.33	1.50	1.14	0.077	1.213	0.010	−0.121	0.145
					(0.17)
Log # of baseline fodder shrubs	1.14	1.21	1.22	1.06	0.0029	0.0127	0.031	−0.006	0.068
					(0.25)
Chi-2 test of joint orthogonality (all variables; p-value)							0.365	0.258	0.690
Observations	480	272	238	242	752	752	752	510	514

Standard errors in parentheses and clustered at the village cluster level; * p < 0.1 ** p < 0.05*** p < 0.01;

Probit and OLS regression used to test differences between groups for binary and continuous measures, respectively, with reporting of marginal effects for the latter; Sub-county fixed effects used (strata used in random assignment);

T = pooled treatment group; C = control group; TS = trees and seedling treatment group; TS+CS = TS base treatment plus Citizen Science add-on treatment group

Table 2. Comparison of attrition rates across treatment groups.

	(1)	(2)	(3)	(4)	(5)	(6)
	T	C	TS	TS+CS	T vs. C	TS vs. TS+CS
	$\hat{p}$	$\hat{p}$	$\hat{p}$	$\hat{p}$	Dif.	chi2 (p-value)
Attrition proportion	0.29	0.26	0.29	0.28	0.033	0.983
					(0.034)
Observations	673	367	335	338	1,040	1,040

Standard errors in parentheses and clustered at the village cluster level; * p < 0.1 ** p < 0.05 *** p < 0.01;

Probit used to test differences between groups, with reporting of marginal effects;

Sub-county fixed effects used (strata used in randomisation);

T = pooled treatment group; C = control group; TS = trees and seedling treatment group; TS+CS = TS base treatment plus Citizen Science add-on treatment group

Table 3. Tests of internal validity for covariates and baseline outcome indicators.

	Test of IV-R (p-values)			Test of IV-P (p-values)
Covariate/baseline outcome	Pooled	TS	TS+CS	Pooled	TS	TS+CS
Head is 60 years of over	0.712	0.533	0.837	0.101	0.289	0.0895
Respondent’s age	0.221	0.0676	0.070	0.008	0.0181	0.004
Years of education of respondent	0.947	0.729	0.800	0.172	0.287	0.112
Baseline wealth index	0.561	0.0840	0.907	0.0932	0.0928	0.0255
Total number of dairy cows at baseline	0.627	0.404	0.875	0.0133	0.0227	0.0505
Baseline FTT knowledge score	0.826	0.604	0.529	0.747	0.768	0.406
Shrubs planted at baseline last 12 months	0.545	0.284	0.242	0.002	0.000	0.009
Log # of baseline fodder shrubs	0.956	0.897	0.734	0.704	0.441	0.701
Observations	1,040	702	705	1,040	702	705

IV-R = Internal validity for responders (non-attritors; local average treatment effect); IV-P = Internal validity for entire study population (both attritors and non-attritors; average treatment effect).

Table 4. Difference in changes in FTT knowledge score.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Pooled	TS	TS+CS	Control	Pooled vs. C	TS vs. C	TS+CS vs. C	TS vs. TS+CS
	mean	mean	mean	mean	dif.	dif.	dif.	F (p-value)
Overall	1.15	0.97	1.33	0.48	0.56**	0.47	0.71**	0.483
					(0.27)	(0.31)	(0.32)
Observations	480	238	242	272	752	510	514	752
By district
Manafwa	0.43	0.27	0.65	0.31	0.083	−0.089	0.31	0.133
					(0.17)	(0.19)	(0.24)
Observations	227	131	96	161	388	292	257	388
Kapchorwa	1.79	1.82	1.77	0.72	1.09**	1.28**	1.03*	0.643
					(0.44)	(0.47)	(0.51)
Observations	253	107	146	111	364	218	257	364
By gender
Female	0.89	0.60	1.15	0.03	0.76**	0.55	1.02***	0.274
					(0.31)	(0.37)	(0.33)
Observations	254	122	132	149	403	271	281	403
Male	1.44	1.35	1.54	1.02	0.32	0.36	0.36	0.915
					(0.27)	(0.28)	(0.38)
Observations	226	116	110	123	349	239	233	349

Standard errors in parentheses clustered at village cluster level; OLS regression used to test differences between groups;

Baseline wealth index controlled for in all models;

Subcounty fixed effects used in all models (unit of stratified randomisation); * p < 0.1 ** p < 0.05*** p < 0.01

Table 5. Proportions of HHs with newly planted shrubs with logistic regression output.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Pooled	TS	TS+CS	Control	Pooled vs. C	TS vs. C	TS+CS vs. C	CS vs. TS+CS
	Mean	Mean	Mean	Mean	Dif.	Dif.	Dif.	chi2 (p-value)
Overall	0.39	0.37	0.40	0.20	0.19***	0.17***	0.21***	0.465
					(0.047)	(0.045)	(0.056)
Observations	480	238	242	272	752	510	514	752
By district
Manafwa	0.36	0.34	0.40	0.27	0.078*	0.058	0.10	0.425
					(0.044)	(0.037)	(0.073)
Observations	227	131	96	161	388	292	257	388
Kapchowa	0.41	0.40	0.41	0.10	0.34***	0.31***	0.31***	0.982
					(0.070)	(0.055)	(0.066)
Observations	253	107	146	111	364	218	257	364

Standard errors in parentheses with standard errors clustered at the village level; probit regression used to test differences between groups with reporting marginal effects (Stata dprobit command); subcounty fixed effects used in all models (strata used in stratified randomisation); * p < 0.1 ** p < 0.05*** p < 0.01

Table 6. Approximate % change in number of tree fodder shrubs reported on farm.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Pooled	TS	TS+CS	Control	Pooled vs. C	TS vs. C	TS+CS vs. C	TS+CS vs. TS
	mean	mean	mean	mean	dif.	dif.	dif.	F (p-value)
Overall	177.53	182.69	172.45	56.97	108.0***	113.0**	106.6**	0.840
					(34.4)	(41.8)	(39.2)
Observations	480	238	242	272	752	510	514
By district
Manafwa	133.13	122.81	147.22	51.79	69.2	59.6	84.7	0.714
					(44.8)	(56.2)	(53.1)
Observations	227	131	96	161	388	292	257
Kapchorwa	217.36	256.00	189.04	64.49	151.9***	187.9***	123.1*	0.278
					(49.0)	(47.6)	(56.3)
Observations	253	107	146	111	364	218	257

Standard errors in parentheses, with standard errors clustered at village cluster level; OLS regression used to test differences between groups; subcounty fixed effects used in all models (strata for stratified randomisation); % change computed by placing baseline and endline on-farm fodder shrub estimates on logarithmic scale and differencing the two; * p < 0.1 ** p < 0.05*** p < 0.01

Table 7. Results of mediation analysis – FTT uptake through FTT knowledge.

	(1)	(2)	(3)	(4)
	Total Effect (equivalent to OLS estimates)	Direct Effect (independent effect of T)	Indirect Effect (combined effect of T + K)	% of T’s effect mediated by K
Overall (n = 752)
Fodder shrub plant dummy	0.184***	0.159***	0.027*	13.9
	(0.045)	(0.041)	(0.014)
Differenced % change # shrubs	107.97***	89.90***	18.07	16.7
	(34.31)	(34.46)	(9.53)
Manafwa (n = 388)
Fodder shrub plant dummy	0.077*	0.073	0.004	4.8
	(0.035)	(0.045)	(0.01)
Differenced % change # shrubs	69.18372	66.07	3.110249	4.5
	(44.66)	(44.47)	(6.60)
Kapchorwa (n = 364)
Fodder shrub plant dummy	0.309***	0.265***	0.044*	14.2
	(0.062)	(0.061)	(0.024)
Approx. % change in # shrubs	151.89***	125.65**	26.24**	17.3

* p < 0.1, ** p < 0.05, *** p < 0.01; standard errors in parentheses and clustered at village clusters;

Models are all saturated, i.e. they were constructed to perfectly reproduce all variances, co-variances, and means.

T = pooled treatment dummy; K = differenced knowledge score

Column 1 – Total Effect – corresponds to the overall treatment effect estimated by the mediation models. These estimates are like those of the OLS models presented above, with minor differences given the differing nature of the modelling approaches. Each total effect estimate is then subdivided into the Direct Effect and Indirect Effect. The direct effect estimates (column 2) correspond to the extent to which our pooled treatment dummy independently accounts for the total effect estimates. The indirect effect estimates (column 3), on the other hand, correspond to the extent to which the variation shared by both the pooled treatment dummy and the differenced knowledge score accounts for these estimates. The percentage of the total effect mediated (column 4), then, corresponds to the percentage of the total effect that is accounted for by the variation our pooled treatment dummy shares with our differenced knowledge score measure (as a measure of the hypothesised mediator variable).