Effect of public subsidies on farm technical efficiency: a meta-analysis of empirical results

Figures & data

Table 1. Share of observations depending on the sign of the estimated effect.

	Share (%) of the 195 observations reporting
	Significantly negative estimated effect	Null (non-significant) estimated effect	Significantly positive estimated effect
All 195 observations	54	22	24
Observations depending on
The type of subsidies used
Total subsidies	29	6	7
Input subsidies	2	1	1
Environmental subsidies	6	3	4
LFA subsidies	4	2	1
Investment subsidies	1	2	4
Coupled subsidies	8	2	4
Decoupled subsidies (including direct payments and Single Farm Payment)	46	20	20
The subsidy proxy used
Value of subsidies per farm	10	8	11
Subsidy rate	35	4	2
Subsidies per hectare	5	2	5
Subsidy dummy	4	8	6
The type of farms considered
Crop farms	21	9	7
Dairy farms	18	7	12
Other livestock farms	7	6	6

The estimated effect refers to the effect of subsidies on technical efficiency found in the primary studies.

Table 2. Meta-analysis moderator variables and descriptive statistics.

		Full sample		Subsample
Variables	Description	Mean	SD	Mean	SD
Dependent variable	Effect of subsidies on technical efficiency in primary studies
Significantly negative	=1 for significantly negative effect, 0 otherwise	0.54	0.49	0.62	0.49
Null (non-significant)	=1 for null effect, 0 otherwise	0.22	0.41	0.18	0.39
Significantly positive	=1 for significantly positive effect, 0 otherwise	0.24	0.43	0.2	0.40
Significantly positive or null	=1 for significantly positive or null effect, 0 otherwise	0.46	0.49	0.38	0.49
Moderator variables
Subsidies as output	=1 if subsidies are modelled as output, 0 otherwise	0.23	0.42	0
Total subsidies	=1 if the type of subsidies is total subsidies, 0 otherwise	0.44	0.49	0.46	0.50
Input subsidies	=1 if the type of subsidies is input subsidies, 0 otherwise	0.04	0.18	0.05	0.21
Environmental subsidies	=1 if the type of subsidies is environmental subsidies, 0 otherwise	0.12	0.33	0.09	0.29
LFA subsidies	=1 if the type of subsidies is LFA subsidies, 0 otherwise	0.05	0.22	0.03	0.18
Investment subsidies	=1 if the type of subsidies is investment subsidies, 0 otherwise	0.06	0.24	0.07	0.26
Coupled subsidies	=1 if the type of subsidies is coupled subsidies, 0 otherwise	0.13	0.34	0.14	0.35
Direct payments	=1 if the type of subsidies is direct payments, 0 otherwise	0.8	0.40	0.83	0.38
Single Farm Payment	=1 if the type of subsidies is Single Farm Payment, 0 otherwise	0.11	0.32	0.12	0.33
Subsidies per revenue	=1 if the subsidy proxy is the amount of subsidies per revenue, 0 otherwise	0.41	0.49	0.41	0.49
Subsidies per hectare	=1 if the subsidy proxy is the amount of subsidies per hectare of land, 0 otherwise	0.11	0.32	0.13	0.33
Parametric estimation	=1 for parametric estimation in the case of SFA, 0 otherwise	0.76	0.43	0.75	0.43
Bayesian estimator	=1 for Bayesian estimation in the case of SFA, 0 otherwise	0.05	0.21	0.06	0.24
Quantile regression	=1 for quantile estimation in the second stage following DEA, 0 otherwise	0.03	0.16	0.03	0.18
Tobit regression	=1 for Tobit estimation in the second stage following DEA, 0 otherwise	0.06	0.24	0.08	0.27
DEA output-orientation	=1 for DEA output-oriented model, 0 otherwise	0.11	0.31	0.13	0.33
Panel data	=1 for panel data, 0 otherwise	0.87	0.33	0.92	0.29
EU area	=1 for EU member states, 0 otherwise	0.82	0.38	0.78	0.41
North America	=1 for North American countries, 0 otherwise	0.03	0.17	0.04	0.19
Publication date	=1 for papers published in 2003 or before, 0 otherwise	0.11	0.31	0.13	0.34
Publication status	=1 for articles published in journals, 0 otherwise	0.51	0.50	0.48	0.50
Number of observations		195		150

The subsample is the full sample without the observations where subsidies are treated as an additional output.

LFA: Less favoured areas; DEA: data envelopment analysis; SFA: stochastic frontier analysis.

Table 3. Ordered probit and binary probit estimates for the meta-regression on the full sample.

		Ordered probit			Binary probit	Binary probit
	Estimates	Marginal effects
		For significantly negative effect (j = 1)	For non-significant effect (j = 2)	For significantly positive effect (j = 3)	Significantly positive or null effect versus. negative effect	Significantly positive effect versus. significantly negative effect
Intercept					1.18 (0.77)	0.39 (1.38)
Subsidies as output	0.94 (0.29)***	−0.36 (0.10)***	0.09 (0.03)***	0.26 (0.10)**	1.09 (0.31)***	1.98 (0.64)***
Total subsidies	0.25 (0.32)	−0.10 (0.13)	0.04 (0.05)	0.06 (0.07)	0.21 (0.40)	0.61 (0.55)
Input subsidies	0.52 (0.69)	−0.20 (0.26)	0.05 (0.05)	0.14 (0.23)	0.73 (0.73)	−1.43 (1.08)
Environmental subsidies	−0.43 (0.45)	0.16 (0.16)	−0.06 (0.04)	−0.08 (0.07)	−0.61 (0.43)	−0.36 (0.71)
LFA subsidies	−0.45 (0.51)	0.17 (0.17)	−0.08 (0.11)	−0.08 (0.06)	−0.28 (0.67)	0.43 (1.00)
Investment subsidies	1.10 (0.63)*	−0.39 (0.18)**	0.04 (0.08)	0.35 (0.25)	1.14 (0.80)	1.95 (0.96)**
Coupled subsidies	0.95 (0.42)**	−0.36 (0.14)**	0.07 (0.03)**	0.28 (0.15)*	0.67 (0.45)	1.24 (0.48)**
Direct payments	−0.58 (0.42)	0.23 (0.16)	−0.07 (0.04)*	−0.15 (0.12)	−0.24 (0.41)	−0.11 (0.56)
Single Farm Payment	−0.25 (0.52)	0.09 (0.19)	−0.05 (0.10)	−0.05 (0.09)	−0.16 (0.53)	0.11 (0.77)
Subsidies per revenue	−2.03 (0.42)***	0.66 (0.09)***	−0.27 (0.06)***	−0.39 (0.06)***	−2.31 (0.47)***	−2.86 (0.73)***
Subsidies per hectare	0.08 (0.44)	−0.03 (0.17)	0.01 (0.07)	0.02 (0.11)	0.05 (0.46)	0.66 (0.67)
Parametric estimation	0.35 (0.36)	−0.13 (0.14)	0.06 (0.07)	0.07 (0.07)	0.71 (0.41)	1.88 (1.11)*
Bayesian estimator	0.56 (0.84)	−0.22 (0.31)	0.06 (0.03)**	0.16 (0.29)	−0.03 (0.64)	0.27 (0.90)
Quantile regression	−0.86 (0.68)	0.26 (0.17)*	−0.17 (0.12)	−0.12 (0.05)**	−1.22 (0.61)	−0.78 (0.59)
Tobit regression	−0.46 (0.55)	0.17 (0.18)	−0.08 (0.11)	−0.08 (0.07)	−0.20 (0.59)	0.89 (1.03)
DEA output-orientation	−0.27 (0.53)	0. 10 (0.19)	−0.05 (0.10)	−0.05 (0.10)	−0.08 (0.53)	0.26 (0.77)
Panel data	−0.74 (0.35)**	0.28 (0.13)**	0.07 (0.03)**	−0.21 (0.12)*	−0.49 (0.40)	−1.75 (0.77)**
EU area	−0.50 (0.35)	0.19 (0.13)	−0.06 (0.04)*	−0.13 (0.10)	−0.55 (0.33)	−1.18 (0.53)**
North America	−0.03 (0.67)	0.02 (0.26)	0.007 (0.12)	0.01 (0.14)	−0.39 (0.71)	−0.48 (0.73)
Publication date	−1.26 (0.36)***	0.39 (0.07)***	−0.23 (0.07)***	−0.16 (0.03)***	−1.53 (0.45)***	−1.72 (0.62)***
Publication status	−0.15 (0.24)	0.02 (0.09)	−0.02 (0.04)	−0.03 (0.05)	−0.06 (0.29)	0.06 (0.43)
Number of observations	1.1E − 05 (2E − 05)	−4E − 06 (10E − 05)	−1.2E − 06 (1.1E − 05)	−2E − 06 (1.1 − -05)	4.2E − 06 (1.5E − 05)	2.9E − 05 (2.6E − 05)
Cut1	−1.69 (0.70)**
Cut2	−0.78 (0.63)
Likelihood ratio	186.18***				111.42***	175.12***
Pseudo R-squared	0.28				0.39	0.51
Percentage of correctly predicted observations					80.00	87.58
Number of observations	195				195	153

Robust SEs are in brackets. The asterisks ***, ** and * indicate significance at the 1, 5 and 10% levels, respectively.