Efficiency and its determinants in the public irrigation projects of Brazil

Fragoso, Rui Manuel de Sousa; Pizaia, Marcia Gonçalves

doi:10.1590/1806-9479.2023.276113

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Revista de Economia e Sociologia Rural

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Article • Rev. Econ. Sociol. Rural 61 (spe) • 2023 • https://doi.org/10.1590/1806-9479.2023.276113 copy

Efficiency and its determinants in the public irrigation projects of Brazil

Eficiência dos regadios públicos no Brasil e os seus determinantes

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This paper aims to assess efficiency in the public irrigation projects of Brazil. A Data Envelopment Analysis (DEA) model using a limited set of significant variables and adapted to the specific characteristics of existing public irrigation projects in the country was used. Then a Multiple Regression Analysis was performed to efficient irrigation projects to estimate other inputs that did not have been considered in the DEA model. The results indicate that 15 public projects out of the 34 studied, reached the technical efficiency score, as well as pure efficiency and scale efficiency. The work brings several new contributions to the literature on irrigation management and practical implications for decision makers. It is noteworthy that the results of the study can be useful for a better understanding of the general efficiency of public irrigation and what are its most determining factors.

Keywords:
irrigated agriculture; data envelopment analysis; multiple regression

Irrigation Project	State	Age of the project (years)	Management entity	Total area (ha)	Equipped area (ha)	Irrigated area (ha)	Revenue (million $R)	Water use (m3/s)
1. Boacica	Alagoas	37	Codevasf	5484	2762	2299	14	4.9
2. Itiúba	Alagoas	43	Codevasf	1296	900	1198	7	1.1
3. S.Nilo Coelho	Bahia	37	Codevasf	55525	23486	21797	2	70.4
4. Tourão	Bahia	42	Codevas	14567	14677	14677	134	65.0
5. Formoso	Bahia	32	Codevasf	15505	11772	8337	246	106.0
6. Curaçá	Bahia	41	Codevasf	15234	4708	4708	160	65.0
7. Maniçoba	Bahia	41	Codevasf	11786	4847	3913	156	65.0
8. Salitre	Bahia	23	Codevasf	67400	5009	3601	79	65.0
9. São Desidério/ Barreiras Sul	Bahia	43	Codevasf	4322	1934	1934	12	102.0
10. Mirorós	Bahia	25	Codevasf	4870	1772	1701	20	106.0
11. Vaza Barris	Bahia	48	DNOCS	11677	1487	1487	23	106.0
12. Brumado	Bahia	35	DNOCS	8302	4313	1509	19	106.0
13. Jaguaribe Apodi	Ceará	32	DNOCS	9606	5658	5658	31	3.9
14. Baixo Acaraú	Ceará	20	DNOCS	13909	8439	5277	65	3.9
15. Curu-Paraipaba	Ceará	47	DNOCS	6913	3357	2733	16	3.9
16. Tabuleiros de Russas	Ceará	17	DNOCS	18915	10766	2055	42	3.9
17. Morada Nova	Ceará	51	DNOCS	11166	4474	1268	1	3.5
18. Luiz Alves do Araguaia	Goiás	21	Goiás State	8148	2742	2742	24	7.4
19. Jaiba - Etapa I	M. Gerais	46	Codevasf	32754	21889	13348	248	77.2
20. Gorutuba	M.Gerais	43	Codevasf	8487	4800	1583	34	92.5
21. Varzeas de Sousa	Paraíba	15	Paraíba Stat.	6336	4404	1600	5	1.8
22. Caraíbas/Fulgêncio	Pernambuco	23	Codevasf	33437	4728	4728	55*	34.8
23. Icó-Mandantes	Pernambuco	27	Codevasf	26097	2187	2187	25*	34.8
24. Bebedouro	Pernambuco	53	Codevasf	7484	2418	1892	49	34.8
25. Brígida	Pernambuco	27	Codevasf	8685	1436	1436	17*	34.8
26. Platôs de Guadalupe	Piauí	28	DNOCS	3196.2	3106	2080	36	6.4
27. Baixo Açu	R.G. Norte	27	DNOCS	6000	5168	2099	24*	1.1
28. Arroio Duro	R. G do Sul	54	MDR	58623	20406	20406	181	272.2
29. Chasqueiro	R. G. do Sul	36	MDR	25738	19619	7314	14	275.2
30. Platô de Neópolis	Sergipe	26	Sergipe Stat.	10432	7230	6860	80*	2.5
31. Betume	Sergipe	43	Codevasf	8481	4671	4671	9	2.4
32. Cotinguiba/Pindoba	Sergipe	39	Codevasf	3085	2232	1798	6	2.5
33. Rio Formoso	Tocantins	41	Tocant. Stat.	27787	23000	20000	250	20.7
34. São João	Tocantins	11	Tocant. Stat.	5139	3027	1048	7	3.0

% of irrigated area					Water use per crop (m3/s)
Irrigation Project	Rice	Sugar cane	Other crops with pivot	Other crops	Rice	Sugar cane	Other crops with Pivot	Other crops
1. Boacica	44.7	55.3	0.0	0.0	1.000	8.100	0.500	0.500
2. Itiúba	97.1	1.1	0.0	1.8	1.000	8.000	1.000	1.000
3. Sen. Nilo Coelho	0.0	0.0	1.2	98.8	0.100	5.600	70.400	70.400
4. Tourão	0.0	42.6	1.0	56.4	0.000	9.900	106.000	106.000
5. Formoso	0.0	0.0	6.4	93.6	0.000	9.900	106.000	106.000
6. Curaçá	0.0	42.6	1.0	56.4	0.000	9.900	106.000	106.000
7. Maniçoba	0.0	42-6	1.0	56.4	0.000	9.900	106.000	106.000
8. Salitre	0.0	42.6	1.0	56.4	0.000	9.900	106.000	106.000
9. São Desidério/ Barreiras Sul	0.0	0.0	8.63	9.4	0.000	9.900	106.000	106.000
10. Mirorós	0.0	0.0	0.3	99.7	0.000	9.900	106.000	106.000
11. Vaza Barris	0.0	0.0	0.0	100.0	0.000	9.900	106.000	106.000
12. Brumado	0.0	0.0	0.0	100.0	0.000	9.900	106.000	106.000
13. Jaguaribe Apodi	1.0	0.0	3.2	67.0	2.300	1.300	3.900	3.900
14. Baixo Acaraú	0.0	0.0	1.2	98.8	2.300	1.300	3.900	3.900
15. Curu-Paraipaba	0.0	0.0	2.3	97.7	2.300	1.300	3.900	3.900
16. Tabuleiros de Russas	2.6	0.0	27.9	69.5	2.300	1.300	3.900	3.900
17. Morada Nova	25.9	0.0	20.6	53.5	2.300	1.300	3.900	3.900
18. Luiz Alves do Araguaia	92.3	0.0	1.3	6.4	5.100	5.900	34.400	34.400
19. Jaiba - Etapa I	0.0	19.2	12.2	68.6	0.300	12.700	92.500	92.500
20. Gorutuba	0.0	0.0	0.00	100.0	0.300	12.700	92.500	92.500
21. Varzeas de Sousa	0.0	0.0	53.0	47-0	0.000	0.000	1.800	1.800
22. Caraíbas/Fulgêncio	0.0	0.0	0-8	99.2	0.200	1.300	34.800	34.800
23. Icó-Mandantes	0.0	0.0	0.5	99.5	0.200	1.300	34.800	34.800
24. Bebedouro	0.0	0.0	1.2	98.8	0.200	1.300	34.800	34.800
25. Brígida	0.0	0.0	4.1	95.9	0.200	1.300	34.800	34.800
26. Platôs de Guadalupe	0.0	0.0	26.7	73.3	1.700	2.100	6.400	6.400
27. Baixo Açu	91.7	0.0	0.7	0.076	0.300	0.600	10.000	10.000
28. Arroio Duro	97.9	0.0	0.0	2.1	277.700	0.000	16.400	16.400
29. Chasqueiro	99.0	0.0	0.0	1.0	277.700	0.000	16.400	16.400
30. Platô de Neópolis	17.3	44.1	2.0	36.6	2.300	1.300	3.900	3.900
31. Betume	94.6	0.0	0.0	5.4	2.300	1.300	3.900	3.900
32. Cotinguiba/Pindoba	72.2	9.9	3.1	14.8	2.300	1.300	3.900	3.900
33. Rio Formoso	99.6	0.0	0.0	0.4	20.800	0.700	3.000	3.000
34. São João	0.0	0.0	26.9	73.1	20.800	0.700	3.000	3.000

	Mean	STD	Coefficient of variation	Max	Min
Age of the project (years)	34.5	11.2	0.324	54.0	11.0
Total area (ha)	16364.3	16047.7	0.981	67400.0	1296.0
Equipped area (ha)	7159.5	6728.2	0.940	23486.0	900.0
Irrigated area (ha)^* * Output parameters	5292.5	5751.0	1.087	21797.0	1048.0
Revenue (million $R)*	107.2	262.6	2.450	1555.0	1.0
Percentage of irrigated area:
Rice	24.6%	39.2%	1.595	99.6%	0.0%
Sugar cane	8.8%	17.2%	1.952	55.3%	0.0%
Other crops with pivot	9.3%	18.2%	1.965	86.3%	0.0%
Other crops	57.2%	38.2%	0.667	100.0%	0.0%
Water use per crop (m3/s):
Rice	18.4	65.0	3.530	277.7	0.0
Sugar cane	4.8	4.4	0.923	12.7	0.0
Other crops with Pivot	43.3	44.1	1.019	106.0	0.5
Other crops	43.3	44.1	1.019	106.0	0.5
Water use (m3/s)	52.5	67.1	1.279	275.2	1.1

Parameters / performance indicators	Public Irrigation Projects (DMU)
Output	1. Boacica	18. Luiz Alves do Araguaia
1. Irrigated area (ha);	2. Itiúba	19. Jaiba - Etapa I
2. Revenue (million $R)	3. Sen. Nilo Coelho	20. Gorutuba
Input	4. Tourão	21. Varzeas de Sousa
1. Age of the project (years)	5. Formoso	22. Caraíbas/Fulgêncio
2. Total area (ha) - DMU	6. Curaçá	23. Icó-Mandantes
3. Equipped area (ha)	7. Maniçoba	24. Bebedouro
4. Water use (m3/s)	8. Salitre	25. Brígida
Percentage of irrigated area:	9. São Desidério/ Barreiras Sul	26. Platôs de Guadalupe
1. Rice	10. Mirorós	27. Baixo Açu
2. Sugar cane	11. Vaza Barris	28. Arroio Duro
3. Other crops with pivot	12. Brumado	29. Chasqueiro
4. Other crops	13. Jaguaribe Apodi	30. Platô de Neópolis
Water use per crop (m3/s):	14. Baixo Acaraú	31. Betume
5. Rice	15. Curu-Paraipaba	32. Cotinguiba/Pindoba
6. Sugar cane	16. Tabuleiros de Russas	33. Rio Formoso
7. Other crops with Pivot	17. Morada Nova	34. São João
8. Other crops

	Age of the project (years)	Total area (ha)	Equipped area (ha)	Irrigated area (ha)	Revenue (million $R)	% of irrigated area				Water use (m3/)
	Age of the project (years)	Total area (ha)	Equipped area (ha)	Irrigated area (ha)	Revenue (million $R)	Rice	Sugar cane	Other crops with pivot	Other crops	Rice	Sugar cane	Other crops with Pivot	Other crops	Total (m3/s)
Age of the project	1.000
Total area	0.065	1.000
Equipped area	0.214	0.619	1.000
Irrigated area	0.300	0.645	0.909	1.000
Revenue	0.252	0.356	0.584	0.604	1.000
Percentage of irrigated area:
Rice	0.202	0.039	0.243	0.230	0.022	1.000
Sugar cane	0.051	0.204	0.065	0.137	0.405	-0.212	1.000
Other crops with pivot	-0.178	-0.246	-0.169	-0.220	-0.209	-0.269	-0.194	1.000
Other crops	-0.150	-0.002	-0.198	-0.191	-0.086	-0.838	-0.091	-0.142	1.000
Water use:
Rice	0.220	0.397	0.491	0.385	0.129	0.497	-0.134	-0.128	-0.407	1.000
Sugar cane	0.250	0.037	-0.024	-0.003	0.302	-0.339	0.387	-0.051	0.221	-0.292	1.000
Other crops with Pivot	0.215	0.180	0.021	0.065	0.319	-0.463	0.406	-0.059	0.347	-0.190	0.898	1.000
Other crops	0.215	0.180	0.021	0.065	0.319	-0.463	0.406	-0.059	0.347	-0.190	0.898	1.000	1.000
Total water use	0.352	0.442	0.461	0.380	0.258	0.166	-0.015	-0.128	-0.110	0.809	0.237	0.394	0.394	1.000

Irrigation Project	Technical Efficiency	Pure Efficiency	Scale Efficiency	Irrigation Project	Technical Efficiency	Pure Efficiency	Scale Efficiency
1. Boacica	0.66	0.80	0.83	18. Luiz Alves do Araguaia	0.95	1.00	0.95
2. Itiúba	1.00	1.00	1.00	19. Jaiba - Etapa I	0.78	0.80	0.98
3. Senador Nilo Coelho	1.00	1.00	1.00	20. Gorutuba	0.28	0.46	0.61
4. Tourão	1.00	1.00	1.00	21. Varzeas de Sousa	0.32	1.00	0.32
5. Formoso	1.00	1.00	1.00	22. Caraíbas/Fulgêncio	0.98	1.00	0.98
6. Curaçá	1.00	1.00	1.00	23. Icó-Mandantes	0.87	0.98	0.89
7. Maniçoba	1.00	1.00	1.00	24. Bebedouro	0.70	0.71	0.98
8. Salitre	0.81	0.96	0.84	25. Brígida	0.68	1.00	0.68
9. São Desidério/ Barreiras Sul	0.77	0.81	0.95	26. Platôs de Guadalupe	1.00	1.00	1.00
10. Mirorós	0.72	1.00	0.72	27. Baixo Açu	1.00	1.00	1.00
11. Vaza Barris	0.72	0.78	0.93	28. Arroio Duro	1.00	1.00	1.00
12. Brumado	0.17	0.45	0.38	29. Chasqueiro	0.39	0.44	0.88
13. Jaguaribe Apodi	1.00	1.00	1.00	30. Platô de Neópolis	1.00	1.00	1.00
14. Baixo Acaraú	1.00	1.00	1.00	31. Betume	1.00	1.00	1.00
15. Curu-Paraipaba	0.67	0.69	0.98	32. Cotinguiba/Pindoba	0.55	0.87	0.64
16. Tabuleiros de Russas	0.90	0.90	1.00	33. Rio Formoso	1.00	1.00	1.00
17. Morada Nova	0.06	0.38	0.17	34. São João	1.00	1.00	1.00

	Mean	STD	Max.	Min.
Total DMU
Overall Technical Efficiency	0.79	0.27	1.00	0.06
Pure Efficiency	0.88	0.19	1.00	0.38
Scale Efficiency	0.87	0.21	1.00	0.17
Inefficient DMU
Overall Technical Efficiency	0.63	0.28	0.98	0.06
Pure Efficiency	0.72	0.19	0.98	0.38
Scale Efficiency	0.76	0.24	0.98	0.17

	Efficient	inefficient	%Δ
Mean age of the project (years)	34.5	34.53	0.0
Equipped area/total area (ha/ha)	0.549	0.342	38%
Irrigated area/equipped area (ha/ha)	0.870	0.559	36%
Water use (m3/s)	45.91	57.74	-26%
Revenue/equipped area($R/ha)	9834.8	6870.2	30%
Revenue/water used(Million $R/m3/s)	2.015	0.6409	68%

Independent variables:	Dependent Variables
	Irrigated area
	Rice	Sugarcane	Other crops with pivot	Other crops
Age of the project	66.48	-25.45	-6.90	-36.63
Equipped area	0.17	-0.61*	-0.01	0.83
Irrigated area	0.08	0.71*	-0.01	-0.15
Revenue	24.67*	6.15	-0.03	-40.14***
Total water use	-64.17***	-12.39*	-0.66	-18.60
Water use in rice	96.53***	-	-	-
Water use in sugar cane	-	131.68**	-	-
Water use in crops with pivot	-	-	-1.104	-
-Water use in other crops	-	-	-	19.11***
Constant	2069.56	1007.91	505.60	-240.26
Explanatory capacity	70.1%	48.5%	6.8%	78.1%

	Irrigated area (ha)
	Rice	Sugarcane	Other crops with pivot	Other crops
Mean non-efficient values	675	291	279	1779
Mean efficient values	73	0	178	3823
	Water use (m3/s)
	Rice	Sugarcane	Other crops with pivot	Other crops
Mean non-efficient values	15.49	5.23	48.57	48.57
Mean efficient values	1.70	0.00	30.90	104.40

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[1] Note: *Estimated values

[2] Source: Prepared by the author, based on Agência Nacional ds Águas e Saneamento Básico, 2021.