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Price elasticity of the demand for water in the Brazilian states: a panel data analysis, 2011–2017

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Abstract

This study estimates the price elasticity of the demand for water using a panel data model for 5570 Brazilian municipalities in the period 2011–2017. Given the country’s environmental and socioeconomic heterogeneity, regional demand elasticities are also estimated for each unit of the Federation. The results suggest demand for water is inelastic to the price. Since water is essential to life, it is reasonable to assume that the demand for water is relatively inelastic to the price level. However, for Brazil as a whole, the parameter associated to real tariff variations was significant at the 1%. The estimates effects also suggest that users tend, to some extent, to change water consumption levels. This may occur mainly, where consumption levels are relatively higher compared to the minimum required for survival. This relationship was significant in 25 of the 27 Brazilian states. It is concluded, therefore, that tariff policy could be an effective instrument in reducing water consumption.

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Fig. 1

Source: National Sanitation Information System (SNIS)

Fig. 2

Source: National Sanitation Information System (SNIS)

Fig. 3

Source: National Sanitation Information System (SNIS)

Fig. 4

Source: National Sanitation Information System (SNIS)

Fig. 5

Source: Research results

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Notes

  1. The IPCA is the index of water tariffs most used by the 30 largest providers of this service in Brazil.

  2. This variable was chosen because a significant proportion of water is consumed by the industrial sector.

  3. In several predominantly rural municipalities in Brazil, water consumption is mainly determined by the pace of expansion of agricultural activities.

  4. In this functional specification, the variance of the data is minimized and the coefficients can be interpreted as relations of percentage variations (that is, elasticities).

  5. Due to the crisis in the state of São Paulo in 2015, SABESP adopted an emergency measure to increase rates by 15.24%. This measure was supported by the regulator, ARSESP. Considering the period under study, in the 2 years prior to the increase, the average per capita consumption for the capital of São Paulo stood at 13.34 l/inhabitant/day, while, with the rationing policies, together with the real increase in tariffs, consumption dropped to 11.29 l/inhabitant/day in 2017, corresponding to a decrease of 13.9% (SNIS 2010–2017).

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Authors and Affiliations

  1. DMAE/PMPA, Porto Alegre, Brazil

    Cristiano Ponzoni Ghinis

  2. PUCRS.CNPq, Porto Alegre, Brazil

    Adelar Fochezatto

  3. Fadergs, Porto Alegre, Brazil

    Christian Velloso Kuhn

  4. Uniritter, Porto Alegre, Brazil

    Christian Velloso Kuhn

  5. CEEE-D, Porto Alegre, Brazil

    Christian Velloso Kuhn

Authors
  1. Cristiano Ponzoni Ghinis
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  2. Adelar Fochezatto
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  3. Christian Velloso Kuhn
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Correspondence to Cristiano Ponzoni Ghinis.

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Appendices

Appendix 1: Indicators selected from the SNIS by Federal Unit-2017

State

IN005: average water tariff (R$/m3)

IN026: expenditure on exploration per m3 billed (R$/m3)

IN009: hydrometricIndex (%)

IN010: micro-measured index for the volume made available (%)

IN014: micro-measured consumption by economy (m3/month/eco)

IN022: average per capita consumption (l/inhab/day)

IN025: volume of water made available by economy (m3/month/eco)

IN049: loss rate in distribution (%)

IN053: average water consumption by economy (m3/month/eco)

Volume of water consumed/volume of water made available (%)

Acre

2.35

2.27

63.13

29.26

19.56

156.72

56.51

61.06

16.62

29.40

Alagoas

2.88

3.91

88.51

28.78

9.21

96.66

28.94

45.90

11.96

41.32

Amazonas

4.06

3.25

67.40

19.11

9.87

165.87

36.41

44.76

17.56

48.24

Amapá

2.34

2.49

20.86

4.11

12.17

172.20

69.60

70.49

19.73

28.35

Bahia

3.09

2.45

95.16

50.91

8.91

110.72

25.07

38.36

9.89

39.43

Ceará

2.60

2.02

97.53

56.12

9.37

124.67

25.48

40.55

9.70

38.07

Distrito Federal

4.71

3.90

99.51

59.83

12.09

148.87

32.22

35.21

13.02

40.39

Espírito Santo

2.98

1.94

95.59

60.74

12.80

164.35

32.94

36.28

12.96

39.33

Goiás

5.06

3.72

98.69

67.21

9.92

135.63

23.78

30.23

10.03

42.16

Maranhão

2.50

2.68

27.65

9.35

11.39

136.96

40.34

62.85

13.94

34.56

Minas Gerais

3.44

2.17

96.23

59.69

10.40

154.85

27.19

35.13

10.98

40.37

Mato Grosso do Sul

4.80

2.47

98.21

66.81

12.41

152.54

31.99

31.93

12.38

38.71

Mato Grosso

2.31

1.59

87.84

42.68

12.77

166.35

35.88

43.47

13.98

38.98

Pará

2.14

2.76

35.48

17.42

12.78

146.81

33.32

42.78

16.23

48.69

Paraíba

3.61

3.07

85.70

50.95

9.54

115.49

25.85

36.46

10.44

40.38

Pernambuco

3.50

2.99

87.34

42.69

8.86

91.11

28.19

52.64

8.70

30.88

Piauí

3.10

3.68

90.85

39.65

8.98

124.48

30.93

43.69

11.61

37.53

Paraná

3.81

2.34

99.85

64.82

10.84

136.98

27.41

34.33

10.90

39.75

Rio de Janeiro

3.44

1.93

68.40

38.68

16.21

247.28

42.82

31.39

20.53

47.93

Rio Grande do Norte

3.60

2.81

84.73

41.89

10.54

115.34

30.29

49.87

10.74

35.45

Rondônia

3.55

3.90

77.53

33.87

13.78

170.34

42.77

50.83

15.71

36.73

Roraima

2.55

2.79

62.82

19.11

15.43

150.52

60.99

66.61

16.84

27.62

Rio Grande do Sul

4.16

3.91

97.39

55.17

10.09

148.30

27.12

36.97

10.67

39.35

Santa Catarina

2.52

2.45

98.76

55.74

10.77

147.90

25.72

32.23

11.53

44.84

Sergipe

3.96

3.92

98.00

50.03

10.76

116.08

31.66

47.69

11.04

34.86

São Paulo

2.96

1.97

99.44

59.62

11.94

164.91

23.77

37.66

12.43

52.31

Tocantins

3.73

3.39

96.61

58.61

10.48

142.74

27.72

29.47

11.84

42.72

Brazil

3.30

2.37

92.14

50.91

11.23

153.50

28.45

38.24

12.38

43.51

  1. Source: NationalSanitationInformation System (Sistema Nacional de Informações sobre Saneamento—SNIS)
  2. Bold values indicate the totals for Brazil and national averages

Appendix 2: Indicators selected from the SNIS for Brazilian State Capitals—2017

Capital

IN005: average water tariff (R$/m3)

IN026: expenditure on exploration per m3 billed (R$/m3)

IN009: hydrometric Index (%)

IN010: micro-measured index for the volume made available (%)

IN014: micro-measured consumption by economy (m3/month/eco)

IN022: average per capita consumption (l/inhab/day)

IN025: volume of water made available by economy (m3/month/eco)

IN049: loss rate in distribution (%)

IN053: average water consumption by economy (m3/month/eco)

Volume of water consumed/volume of water made available (%)

Rio Branco

2.42

2.02

63.31

29.73

19.07

170.61

42.81

58.19

17.31

40.43

Manaus

5.28

3.80

84.09

23.56

9.81

171.46

42.22

44.15

19.39

45.93

Macapá

2.49

2.56

29.17

6.46

12.62

187.69

60.14

66.25

20.30

33.75

Belém

2.73

2.53

47.78

27.71

13.47

118.99

28.40

46.77

14.79

52.08

Porto Velho

5.02

8.23

82.67

24.02

15.98

153.13

56.40

70.88

16.43

29.13

Boa Vista

4.69

4.19

91.52

71.93

7.94

91.94

10.44

15.37

8.56

81.99

Palmas

5.07

1.69

100.00

61.50

12.08

214.01

20.50

13.05

17.08

83.32

Maceió

5.79

5.17

86.05

25.61

8.91

80.35

31.08

59.93

12.45

40.06

Salvador

4.33

2.25

94.61

42.22

10.51

121.62

25.27

53.07

10.77

42.62

Fortaleza

2.95

1.75

99.99

57.36

9.96

128.41

17.37

42.64

9.96

57.34

São Luiz

2.17

5.12

15.59

3.92

12.04

120.35

49.52

64.10

17.78

35.90

João Pessoa

3.91

2.85

92.86

51.93

11.97

148.90

23.51

40.28

13.34

56.74

Recife

4.26

4.82

85.24

36.24

10.41

109.16

28.67

61.16

9.93

34.64

Teresina

3.28

4.10

95.15

37.85

9.48

144.43

28.51

47.54

12.55

44.02

Natal

3.96

2.42

87.78

42.03

12.06

128.95

25.45

54.22

11.65

45.78

Aracaju

5.01

4.36

99.63

66.19

13.08

154.63

19.69

33.45

13.10

66.53

Goiânia

7.20

2.90

96.33

73.92

11.34

155.14

14.81

22.53

10.89

73.53

Campo Grande

5.41

1.90

99.91

77.72

13.23

163.93

21.47

19.42

13.71

63.86

Cuiabá

3.86

1.91

93.80

34.62

12.65

178.44

34.48

59.22

13.17

38.20

Vitória

4.00

1.79

90.19

63.99

14.90

206.92

22.19

33.21

14.80

66.70

Belo Horizonte

4.51

2.16

100.00

62.64

11.31

160.61

18.14

37.36

11.31

62.35

Rio de Janeiro

3.63

1.45

69.12

41.76

20.38

328.94

37.61

25.36

26.57

70.65

São Paulo

3.60

1.89

99.96

63.28

11.48

151.80

19.72

36.69

11.48

58.22

Curitiba

4.06

2.04

100.00

60.54

11.58

156.15

19.17

39.46

11.58

60.41

Porto Alegre

4.03

2.54

95.17

67.06

13.21

220.30

23.61

24.98

14.42

61.08

Florianópolis

4.91

2.51

97.21

39.89

9.41

181.36

23.26

39.35

11.97

51.46

Brazil

3.30

2.37

92.14

50.91

11.23

153.50

28.45

38.24

12.38

43.51

  1. Source: NationalSanitationInformation System (Sistema Nacional de Informações sobre Saneamento—SNIS)
  2. Bold values indicate the totals for Brazil and national averages

Appendix 3: Hausman test

Estimated model with random effects (GLS)

Dependent variable: D

 

Coefficient

Standard error

z

P value

const

− 1.8113

0.0363

− 49.8927

0.0000

P

− 0.2811

0.0049

− 57.0335

0.0000

DOM

0.7643

0.0012

618.9459

0.0000

POP

0.0058

0.0042

1.3938

0.1634

T

0.0077

0.0010

8.0555

0.0000

IND

0.0467

0.0034

13.7624

0.0000

AGRO

0.0361

0.0049

7.3951

0.0000

ESC1

0.0384

0.0050

7.6588

0.0000

ESC2

− 0.0147

0.0039

− 3.7554

0.0002

ESC3

− 0.0053

0.0039

− 1.3474

0.1779

REM

0.0662

0.0031

21.0792

0.0000

Hausman test

 

Null hypothesis: GLS estimates are consistent

  

Asymptotic test statistics: Chi square (10) = 156.927 with P value = 0.0000

Test statistic

156.9273

   

P value

0.0000

   
  1. The null hypothesis is rejected at a level of 1% significance. Therefore, the fixed effects model should be chosen

Appendix 4: Unit root tests

Increased Dickey–Fuller test

Akaike criterion lags selection

Null unit root hypothesis: a = 1

Variables

Order

Lags

Test without constant

Test with constant

Test with constant and trend

Test statistic: tau

Asymptotic P value

Test statistic: tau

Asymptotic P value

Test statistic: tau

Asymptotic P value

D

In level

1

− 5.2268

0.0000

− 13.6762

0.0000

− 13.8802

0.0000

P

In level

1

− 4.3557

0.0000

− 10.8893

0.0000

− 12.0424

0.0000

DOM

In level

1

− 5.7495

0.0000

− 13.6978

0.0000

− 13.9209

0.0000

POP

In level

1

− 5.2268

0.0000

− 12.4525

0.0000

− 12.6554

0.0000

T

In level

1

− 16.2294

0.0000

− 25.6129

0.0000

− 26.4698

0.0000

IND

In level

0

− 4.7913

0.0000

− 12.3289

0.0000

− 12.4429

0.0000

AGRO

In level

0

− 5.0308

0.0000

− 13.6653

0.0000

− 13.6791

0.0000

ESC1

In level

0

− 4.8843

0.0000

− 13.3496

0.0000

− 13.3513

0.0000

ESC2

In level

0

− 4.9331

0.0000

− 12.4323

0.0000

− 12.4327

0.0000

ESC3

In level

0

− 4.7434

0.0000

− 11.8376

0.0000

− 11.8421

0.0000

REM

In level

1

− 4.9779

0.0000

− 13.7978

0.0000

− 13.9209

0.0000

  1. The null hypothesis is rejected at a level of 1% significance. Therefore, there is no evidence of a unit root process in the variables

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Ghinis, C.P., Fochezatto, A. & Kuhn, C.V. Price elasticity of the demand for water in the Brazilian states: a panel data analysis, 2011–2017. Sustain. Water Resour. Manag. 6, 72 (2020). https://doi.org/10.1007/s40899-020-00429-0

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