Effects on poverty and equity of the decline in collective tank irrigation management in Tamil Nadu, India

Transcription

1 Effects on poverty and equity of the decline in collective tank irrigation management in Tamil Nadu, India Kei Kajisa* International Rice Research Institute (IRRI) and Foundation for Advanced Studies on International Development (FASID) K. Palanisami Tamil Nadu Agricultural University Takeshi Sakurai Policy Research Institute, Ministry of Agriculture, Forestry and Fisheries of Japan November, 2006 Abstract This paper investigates the factors influencing the decline in collective management of local commons and the impact of this decline on agricultural production and household consumption. The analysis is based on a village and household data set collected in 1999 in Tamil Nadu, India, where tank irrigation systems are managed collectively for rice cultivation by informal water users organizations. Our statistical analyses find that one major reason for the decline in collective tank irrigation management is the dissemination of private well irrigation systems. Once the decline has occurred, our analyses predict that the gap in rice yields between farmers who have access to private wells and those who must rely solely on tanks will widen, with only the latter group suffering lower yields. Our analyses also find that the same pattern holds for levels of income and consumption because the affected farmers cannot sufficiently compensate for the loss of their rice income by diversifying their income sources to agricultural labor or non-agricultural work. In this way, the decline in collective management results in greater inequality and poverty. JEL classifications: D31, D71, O33, Q25 Key words: common property, irrigation, income distribution, poverty, India. * Corresponding author: Address: IRRI DAPO Box 7777, Metro Manila, Philippines; kajisa@grips.ac.jp 1

2 1. Introduction Tank irrigation management is at a crossroads. Tank irrigation systems collectively operated and managed by informal local bodies have been a dominant source of irrigation in southern India since time immemorial. However, the agricultural area under tank irrigation has been in retreat, especially since the 1990s, due to the decline in collective management. Concurrent with this is the rapid dissemination of private well irrigation systems. The percentage share of tank-irrigated agricultural area in southern India fell from 37 in the 1960s to 29 in the 1970s, 22 in the 1980s, and 18 in the 1990s. Meanwhile, the percentage share of private wells rose from 20 to 26 to 31 and to 40 in the corresponding periods (Fertilizer Association of India, various issues). The shift in relative share reflects not only a preference for private wells when new systems are installed but also the actual replacement of tank systems by well systems. This process has been associated with significant increases in the average yield of rice, a staple crop in the area, and in the average income level of farmers. Despite such positive effects on average, there is concern that the diffusion of private wells is also associated with increased poverty and inequality. Access to water for irrigation from tanks is available to all farmers in the system command area in principle. Access to irrigation water from private wells, however, is limited to the 2

3 owners and to those who can buy from the owners. Private wells provide freedom in irrigation water control, and thus those who have access can increase their yields and income. When farmers who can access private wells exit from the collective management of their tank system out of disinterest or loss of incentive the quality of tank management declines and the tanks deteriorate. When this happens, farmers who are dependent solely on tanks suffer a reduction in rice yields, while farmers who have recourse to private wells can still achieve high yields. Whether this leads to a significant increase in poverty and inequality is an empirical question. If farmers with greater water availability due to access to private wells increase their demand for agricultural labor and then hire farmers without access to wells, the income of the farmers without access to wells may not decline significantly. Besides, farmers without access to wells may be able to diversify their income source to non-agricultural occupations. In this way, farmers without access to wells may be able to compensate to some extent for their income loss caused by the yield reduction. On the other hand, if opportunities to participate in agricultural labor and non-agricultural work are limited, the decline in collective management results in a reduction in income of farmers without access to wells to the extent that it increases poverty and inequality significantly. Numerous attempts have been made to examine the determinants of the decline 3

4 in collective management (Wade, 1988; Ostrom, 1990; Ostrom et al., 1994; Singh, 1994; Baland and Platteau, 1996; Palanisami and Easter, 2000; Dayton-Johnson, 2000; Bardhan, 2000; Bardhan and Dayton-Johnson, 2001; Fujiie et al., 2005). However, few quantitative analyses have been made of the impact of the decline on the livelihoods of rural households. 1 This paper aims to both investigate the determinants of the decline and examine whether this decline results in lower yields and income among farmers without access to private wells. As this was found to be true, this paper seeks to answer the question of whether a revitalization of tank management would reduce poverty and inequality. The analysis is based on a set of data collected from sample surveys at both the village and household levels in Tamil Nadu, India. The organization of this paper is as follows: the next section, Section 2, explains the characteristics of tanks and wells in Tamil Nadu and advances the hypotheses. Section 3 describes the study site and data collection. Sections 4 and 5 present the regression analyses on the determinants of collective management and on yield and income effects. Finally, Section 6 summarizes the discussion and presents policy implications. 1 One exception is the benefit-cost analysis conducted by Kikuchi et al. (2001). Some significant descriptive studies are Jodha (1986), Singh (1994), Palanisami (2000), and Meinzen-Dick et al. (2002a). 4

5 2. Tanks and wells in Tamil Nadu The tank irrigation system The tank irrigation system consists of a water storage area, sluices, and water supply channels. The water storage area, or tank, is a small reservoir constructed across the slope of a valley to catch and store water. Water is controlled by sluices that are attached to the tank bank and is delivered to paddy fields through the channels. Traditionally, these tank systems are managed collectively by informal local bodies, called water users organizations (WUO), which mobilize community labor to perform the maintenance and management tasks. These tasks include (1) de-silting the water storage area, (2) cleaning the water supply channels, and (3) arranging water distribution among users. De-silting work for tanks with a minimum command area of 40 hectares is supposed to be arranged and implemented by the Public Works Department (PWD) using state government funds. However, due to the limitation of such funds, de-silting work is occasionally done at the village level based on WUO initiatives. For command areas of less than 40 hectares, this work must be done by the village-level administration and the WUO. Channel cleaning and water distribution are arranged and implemented through collective action by the WUO, regardless of system size. 5

6 The tank irrigation system has the attributes of a common pool resource (CPR) in that the exclusion of farmers within the command area is difficult, but, if use exceeds supply capacity, the resource will become exhausted. Hence, in arranging collective action, the system is doomed to face two types of CPR management problems: provision and appropriation (Ostrom et al., 1994). The former problem arises in arranging the maintenance of the resource stock, while the latter occurs in arranging the distribution of output flow from the resource. In the context of tank management, the former corresponds to de-silting and cleaning arrangements, while the latter corresponds to water distribution arrangements. The central issue in CPR management of tank irrigation is the resolution of the provision problem because two technological features specific to the tank irrigation system make resolution difficult. First, tank irrigation technology is indivisible to some extent in terms of its supply capacity; hence, it is difficult to reduce the supply capacity precisely in accordance with a decline in the number of users. Therefore, as long as the tank irrigation system is used, it must maintain a certain supply capacity level and, for that purpose, a certain amount of labor input must be mobilized. Second, the maintenance work must be completed within a short period of time at the outset of the monsoon season. This means that all the participants in maintenance work must be 6

7 mobilized at once. However, this period corresponds to the preparation period of rice nurseries for those who are able to start preparation earlier with water from wells. For them, the opportunity cost of participation is high. 2 Hence, when the number of private well users increases, it becomes difficult to mobilize a certain amount of labor input within a particularly short period of time. In this way, the cost of maintaining the tank system becomes too high to irrigate for the small number of remaining users. While Olson (1965) argues that a smaller group may facilitate the arrangement of collective management, due to the tank s technological features, once the number of formal users declines, it becomes difficult to provide a sufficient level of tank maintenance work. Replacement of tank irrigation by private well irrigation Even when tanks are properly maintained, having access to private well irrigation systems substantially increases rice yields because those systems serve as a supplementary source of irrigation and thus improve water control, especially during the critical stages of rice cultivation (Palanisami, 2000). Hence, as long as the costs of private wells are relatively low, farmers are willing to incur the costs of installing private wells even if they can still obtain water from tanks. 2 Non-participants are asked to contribute money for the maintenance. However, the collection of money is often incompletely implemented. 7

8 In the 1990s, the costs of installing and operating private wells declined dramatically because of changes in several exogenous conditions. First, the price of pumps declined significantly due to the development of the domestic pump industry. Figure 1 shows the decline in the relative price of electric motor pumps to paddy price throughout the 1990s in Tamil Nadu. Second, the introduction of the hydraulic drilling method in the 1980s reduced the cost of drilling by 30%. Because the nominal cost of drilling did not change much since then and the paddy price increased 135% in the 1990s, the relative price of drilling to paddy price declined. Third, starting in 1989, the government policy of free electricity supply to farmers made the adoption of electric pumps more attractive. Fourth, policies to facilitate groundwater development, such as the provision of credit by agricultural cooperatives for pump and well investment, accelerated the process. These exogenous changes in the 1990s promoted the dissemination of private wells. One could argue that there is another reason: the deterioration of tank systems induced farmers to install private wells. We encountered such opinions during our field interviews and thus do not deny this direction of causality. At the same time, however, it is important to note that the sharp decline in the investment and operation costs of private well systems is also a strong driving force for the dissemination of private wells. 8

9 This paper examines some of the consequences of this phenomenon; specifically, it attempts to determine whether the diffusion of private well irrigation leads to a deterioration in tank management and tank quality, and ultimately to greater poverty and inequality. To understand how this process proceeds, we advance our hypotheses in the following subsection. Hypotheses The literature on collective action argues that if farmers have ready access to earning activities that are not reliant on local commons, their incentive to devote themselves to the collective management of such local commons will be reduced (Agrawal, 2001; Kikuchi, et al., 2001). Because of the tanks technological features explained previously, once such farmers exit from collective management, it becomes difficult to provide a sufficient level of tank maintenance activities. Thus, we hypothesize the following: Hypothesis 1 As the number of farmers with access to private well irrigation systems grows, it becomes more difficult to provide a sufficient level of collective management of tank 9

10 irrigation systems. What will happen to farmers livelihoods if Hypothesis 1 holds? When tanks are well maintained, private wells are usually used for supplementary irrigation at the critical stages of rice cultivation. As explained before, by improving water control at these stages, the availability of well irrigation increases rice yields (Palanisami, 2000). Even if the tanks become less well maintained, yields for these farmers are protected because they have recourse to wells. The situation is quite different for farmers who cannot use private wells. While they do not suffer the complete loss of their rice harvest, they face lower yields because they are totally dependent on the insufficiently maintained tanks. This leads us to hypothesize the following: Hypothesis 2 The yields of farmers who use only tank irrigation because they cannot access private wells are lower than the yields of farmers who can access wells. The decline in tank management results in much lower rice yields only among farmers without access to private wells. 10

11 Whether this leads to greater poverty and inequality is an empirical question. One income compensation strategy usually adopted by farmers without access to wells is to work as agricultural laborers for more productive farmers, who are usually farmers using private wells. If the labor demand increases appreciably with the greater water availability from private wells, the farmers without access may be able to compensate partially for their income loss caused by the yield decline. Another possible strategy is to diversify their income sources into non-agricultural activities. If these strategies are available for the farmers without access to wells, their incomes may not decline drastically. On the other hand, if these strategies are not available and their income is generated predominantly from their own rice plots that receive less and less water from the silted tanks, the lower yields will translate into lower income. Thus, our third hypothesis follows: Hypothesis 3 Unless the farmers without access to private wells can sufficiently diversify their income sources to agricultural labor or non-agricultural work, the decline in tank irrigation management results in lower income for these farmers. 11

12 We test Hypothesis 1 in Section 4 and Hypotheses 2 and 3 in Section Study site and data collection This study is based on our survey of 79 tank-irrigated villages randomly selected from four contiguous districts (Madurai, Ramnad, Virudunagar, and Sivaganga) in southern Tamil Nadu State, India. In these districts, rice is the dominant crop, irrigated mainly by tanks supplemented by wells. Other crops such as sorghum, millet, groundnut, cotton, chili, and sugarcane are cultivated with or without irrigation. In each village, we conducted a group interview to collect information on the management of tank irrigation as well as on village characteristics. When a village uses several tanks, we identified the most important one through the group interview and collected information on that particular tank. We also interviewed 450 rice-farming households, randomly selected with a sample of 5 or 6 households from each village. Due to the focus of this study, we excluded non-farmers from the sample. The authors collected the data in Normal rainfall was recorded at the study sites in the survey year. We observed no case wherein collective tank management was not conducted due simply to insufficient rainfall. 12

13 4. Determinants of collective management We test the first hypothesis postulated in Section 2 by means of a cross-section regression analysis based on sample village observations. For this purpose, we must specify the variables to measure the changes in the quality of collective management as well as the factors underlying the changes. Measuring collective management In order to measure the decline in collective management, we must evaluate the overall status of the collective actions devoted to tank management in the survey year as compared with the past. There are two approaches: (1) physical performance indicators, which measure the outcomes of collective action; and (2) more direct measures of cooperation, which evaluate the degree of cooperation. 3 The former approach is not appropriate for our case due to difficulties in isolating the current status of irrigation from the influence of exogenous environmental conditions and from accumulated past successes or failures in collective management. Therefore, we use the latter approach, 3 Examples of the former approach include Bardhan (2000), who uses the index of the quality of the maintenance of distributaries and channels, and Dayton-Johnson (2000), who uses the conditions of canals as the proxy for the existence of collective action. Bardhan (2000) also uses the latter approach when he uses the number of conflicts and the frequency of rule violations among beneficiaries. Another example of the latter approach is Fujiie et al. (2005), who measure cooperation in terms of the success or failure in organizing several water management related activities. 13

14 although this approach also presents difficulties. Past studies generate a dichotomous variable because of the difficulty in objectively ranking the degree of cooperation. We were able to generate a dummy for each of the three tasks of collective management explained in Section 2. However, evaluating each separately will not necessarily provide useful information regarding the overall status because the activities may be mutually substitutable, that is, the lack of one activity does not necessarily indicate an overall decline (Fujiie et al., 2005). Moreover, the lack of de-silting and channel cleaning does not necessarily indicate that the management level declined in the survey year because such activities are carried out according to need. 4 In order for the second approach to produce appropriate measurements, we must be able to measure the overall status in the survey year. The variable that we chose to implement in the second approach to measuring collective management is the dichotomous response of key village informants to the question of whether the informal water users organization (WUO) is active or inactive in the survey year; the dummy takes the value one if inactive. We consider this dummy variable to be an appropriate proxy for measuring tank management activity because, 4 The need for channel cleaning varies across villages depending on the structure of the irrigation systems and their environment. Some villages require channel cleaning annually, while others may need it only biennially, or even less frequently. The need for de-silting work arises much less frequently, usually once or twice in ten years. 14

15 first, it evaluates the overall status of collective management, and, second, it evaluates the status in the survey year. Although this variable is somewhat arbitrary as it is based on subjective judgment, it is the best available proxy that we were able to identify, performing better in the regression analysis than other proxy variables. 5 Using this dummy as our measure, we classified the villages into those with and those without active collective management, and we found that the number of inactive villages (that is, without active collective management) is 31 (39%) and the number of active villages is 48 (61%). Determinants of collective management To test Hypothesis 1, the explanatory variable we use is the density of private wells in the tank command area. However, there may be reason for concern that the current number of private wells may be endogenously determined in the model in that 5 This inactive WUO dummy has a high correlation (correlation coefficient 0.75) with a dummy that becomes one when channel cleaning had not been conducted in the last three years, indicating the consistency of villagers cleaning behavior and the subjective evaluation of the overall status. However, the channel cleaning dummy was not used because it failed to produce reasonable econometric results in the following section. The inactive WUO dummy is consistent also with water supply conditions. Among the inactive villages according to the classification of our variable, 48% of these villages claimed that the availability of tank water had worsened, whereas the corresponding percentage goes down to 29% in the active villages. Moreover, in the active villages, even in those that claimed that the situation had worsened, the majority claimed that the reason was bad rainfall rather than the poor management of irrigation facilities, whereas this was reversed in the inactive villages. The regression analysis with the dependent dummy of water availability did not produce reasonable results either. The low performance of these two alternative dummies stems from the shortcomings explained in the first paragraph of this section. 15

16 inactive management may cause farmers to switch to private wells. To circumvent this problem, we apply the instrumental variable (IV) method, using the relative cost of pump sets and the relative cost of well digging to paddy price as the identifying instruments. 6 Note that if we obtain a significant coefficient of this well density variable, this simply indicates causality from private well dissemination to inactive management without denying a possible reverse causality. In other words, what we can confirm from our regression analyses is that although such a reverse causality possibly exists, the direction from private well dissemination to inactive management can also be a strong driving force behind failure in collective management. We also control the other determinants suggested by the literature on collective action. Relying on a synthesis by Agrawal (2001), and also on an empirical study of tank irrigation management in Tamil Nadu by Bardhan (2000), we divide the other factors into six categories: exit options, heterogeneity, group size, government interventions, destructive shocks, and weather. 7 The descriptive statistics of the variables are presented in Appendix Table A1. 6 The cost of pump set consists of the cost of pump with a particular horsepower and the cost of equipments typical in a survey village. The cost of digging is the cost required to dig a typical depth of well in a village. These costs vary across villages as the depth of well and the required pump set differ across villages, depending on geographical conditions and the locations of aquifer. 7 Agrawal s (2001) synthesis relies on three major contributors in this area, that is, Wade (1988), Ostrom (1990), and Baland and Platteau (1996), supplemented by other studies. 16

17 To capture the accessibility to exit options, four variables are employed in our regression analysis: (1) the percentage of high-school graduates in a village, (2) the percentage of college graduates in a village, (3) male wage rate, and (4) agricultural area physically non-feasible for tank irrigation per agricultural household. All these variables are expected to have positive coefficients as they increase the attractiveness of activities other than rice cultivation. Among the variables of the second category, heterogeneity variables, we include the two variables that measure wealth heterogeneity: (1) the Gini coefficient and its squared term of animal holdings and (2) of tank-irrigable plot size. The squared terms are included to capture the inverted U-shape relationship between heterogeneity and inactive management (Bardhan, 2000; Dayton-Johnson and Bardhan, 2002). The third category, group size, is measured by the number of households having agricultural land in the tank command area. Along the theme of Olson (1965), the positive relationship between group size and inactive collective actions is expected. However, in the context of the tank management, a large group is less likely to suffer labor scarcity that would arise when a certain amount of labor input is required to maintain the indivisible tank technology. Hence, the effect of this variable is an empirical question, as empirically observed by Bardhan (2000). 17

18 Regarding the fourth category, government interventions, one relevant policy variable is the percentage length of the water supply channel lined by blocks and cement. This construction work is done by the Public Works Department (PWD) with funds from the government or from international aid programs. According to a specialist at Tamil Nadu Agricultural University, the selection of villages by the PWD was more or less at random. Channel lining reduces water loss in delivery and also eases cleaning, making tank irrigation more profitable with less labor. Hence, even if private well users exit from collective management, the introduction of this labor-saving technology makes management feasible by the remaining formal users. Thus, we postulate that tank management is less likely to be inactive when the channels are lined (negative coefficient). Another variable is a PWD tank dummy, which occurs if the PWD is supposed to perform tank de-silting. Although if this happens villagers may come to rely on the government even for those activities that are supposed to be the responsibility of the local water users organization, this may also enhance collective management by reducing the burden on the local organization; the direction of the effect is an empirical question. The fifth category, destructive shocks, includes (1) a dummy of at least one ethnic or religious conflict within a village in the last ten years and (2) the number of 18

19 droughts. As the literature argues, after experiencing such destructive shocks, collective management tends to disappear (positive coefficients of these variables) (Baland and Platteau, 1996; Sethi and Somanthan, 1996). The last category is weather and it is measured by block-level annual rainfall in the survey year. Regression results The results of the regression analyses are presented in Table 1. In addition to the probit model results, we report the linear probability model results, first, because the probit model cannot include one policy variable, the percentage of channel lining, due to the perfect prediction problem, and, second, because the linear model can provide diagnostic statistics that confirm the validity of our IV specification. 8 The test statistics for the linear IV analysis presented in the lower part of Table 1 indicate that the current density is an endogenous variable (F test for endogeneity) but it is significantly predicted by the identifying instrumental variables (first-stage F test) that can be considered as exogenous to the model (χ 2 test for over identification), providing confidence in the validity of the model specification (Wooldridge, 2002). The first-stage regression of the well density function (not reported here) indicates that the coefficient 8 To circumvent the heteroskedasticity problem in the application of OLS to the dichotomous dependent variable, we report the robust standard errors in our OLS results. 19

20 of the relative price of pump sets is negative and highly significant, which is consistent with our observation of the dissemination of private wells with a reduction in pump costs. The qualitative results of our IV probit model are the same as those of our linear model. A key finding from these IV results is that the density of wells is statistically significant with a positive sign. Our supplementary analyses also find two supportive empirical results which are presented in Appendix. Hence, we conclude that the results support Hypothesis 1. This finding is consistent with Palanisami and Easter s (2000) study on tank irrigation in other regions in Tamil Nadu. Turning to the other explanatory variables, the exit options are not statistically significant except for the male wage rate in the probit model. The educational variables become insignificant presumably because these variables capture not only educated people s likelihood of exit (a positive coefficient) but also the effect of their leadership for collective management as local elites (a negative coefficient) (Meinzen-Dick et al., 2002b). Regarding wealth heterogeneity, the Gini of plot size and its squared term are strongly significant. Their signs are consistent with the inverted U-shape relationship in all four models, and thus are consistent with Bardhan s (2000) empirical study. 9 This result confirms the importance of socioeconomic factors for collective management. As 9 For example, turning point value of Gini is for linear IV or for Probit IV which is or standard deviation higher than the mean value (=0.275). 20

21 for the two kinds of destructive shocks, the number of droughts is significantly positive. This result suggests that even in villages where collective management provides positive economic returns to the participants, this collective management may disappear due to shocks. Turning to the policy variable, as we have postulated, the percentage of channel lining in the linear probability models is highly significant with a negative sign. Thus, this policy could be an effective intervention tool for the revitalization of collective management. 5. Impact on rice yields and income Binary comparison To develop an understanding of the impact of the decline in collective management, we compare rice yields, monthly income, monthly consumption value, and a subjective poverty assessment among 171 households in 31 inactive villages and 279 households in 48 active villages. These data appear in Table 2. The difference in rice yields is clear: row (1) shows that rice yield in kg per hectare is lower in the inactive villages than in the active villages, and the difference is statistically significant. Note, however, that the difference is merely 7.6%, which seems rather small. The lower yield due to inactive management is likely largely compensated for by the existence of a 21

22 larger number of private well users in the inactive villages than in the active villages. Inequality measured by the Gini coefficient is higher among households in the inactive villages than in the active villages, indicating that yield variation is larger in the former than in the latter. Likewise, although the levels are very small, the average of the village-level Gini coefficients for the inactive villages is higher than that for the active villages, and the difference is statistically significant. A similar structure is observed in row (2) in the adult equivalent per capita monthly income: that is, lower income and higher inequality in the inactive villages. 10 Comparison of the poverty indexes shows that both the incidence of poverty and the poverty gap are higher in the inactive villages. 11 Comparison of the consumption value shows a slightly different picture, though the conclusions are essentially the same. The mean is lower in the inactive villages but the difference is not statistically significant, presumably because of the existence of consumption smoothing mechanisms to some extent. The magnitudes of the Gini are moderately higher for the inactive villages and significantly different from those of the 10 The weights used for computation of adult equivalent household size are 0.5 for a child of age below 5 years, 0.73 for a child aged 6-10, 0.83 for a child aged 11-14, 0.83 for a female above age 14, and 1.0 for males above age 14 (Rao, 1983). Household members living outside of the household because of work are excluded but members living outside because of educational pursuit are included as members of the household, on the assumption that students receive financial support from the household. 11 Use of the national poverty line of Rs. 324 monthly per capita for , instead of US$ 1, does not change the qualitative results. The same applies to the comparison of the consumption value. 22

23 active villages. 12 Moreover, poverty is more severe in the inactive villages in terms of both the ratio and the gap. 13 These observations are consistent with the villagers subjective assessment of their poverty conditions presented in row (4): a larger percentage of villagers in the inactive villages judged that they were in serious poverty than villagers in the active villages. In summary, the binary comparison suggests that inactive collective management is associated with greater poverty and inequality presumably because of insufficient income compensation from agricultural labor and non-agricultural work among farmers without access to private wells in the inactive villages. The regression analyses in the following subsection examine whether and to what extent this consequence is explained by inactive collective management and access to private wells, controlling for other covariates. Variables for regression analyses We estimate the regression functions explaining rice yield, agricultural labor income, non-agricultural income, total income, and consumption value. To test 12 The national-level Gini coefficient based on expenditure data in was 32.5, which is very close to our Gini coefficients (all households in each category), indicating the appropriateness of our data (World Bank, 2004). 13 The national-level head count ratio of poverty and poverty gap are 34.7 and 8.2, respectively, in the data (World Bank, 2004). Our figures show higher magnitudes, reflecting the high incidence of poverty in rural areas. 23

24 Hypotheses 2 and 3, we include the village-level inactive management dummy as one of the explanatory variables. To confirm that the decline in village-level collective management is exogenous to each individual in the villages, we apply the F-test for endogeneity and confirm that it is not necessary for this variable to be instrumented. 14 Also important is the household-level variable that measures inaccessibility to private wells. This is a dichotomous variable: non-well-owners who did not buy water from well-owners are classified into the no-access group (dummy=1), whereas owners and non-owners with water transaction records are classified into the access group (dummy=0). The differential impacts of no access to wells with and without collective management are captured by considering four different cases. Using the case of farmers having access to wells at an active village as the base (Access&Active), we construct three irrigation status dummies: (1) no access at an active village (No Access&Active), (2) no access at an inactive village (No Access&Inactive), and (3) access at an inactive village (Access&Inactive). 14 The identifying instrumental variables used here are the village-level variable used in our analyses of the determinants of inactive collective management. These instruments are jointly significant in the first-stage F-test. The variable measuring inaccessibility to wells, which might be an endogenous variable, as we discuss later, is excluded from the model in order to keep all the variables other than the inactive collective management dummy exogenous. The F-values and the corresponding p-values on the residuals from the first-stage prediction of inactive collective management (F-test for endogeneity) are F=0.02 and p=0.88 for the rice yield regression, F=2.20 and p=0.14 for the consumption regression, and F=0.48 and p=0.50 for the income regression, indicating that the inactive management dummy is exogenous and use of the OLS model will not cause serious problems. 24

25 In Table 3, we summarize the expected signs on these irrigation status dummies. Note that the base (Access&Active) is the most irrigation-water-sufficient case. The coefficients of the dummies capture the differences from this base. Hence, in the rice yield function, if Hypothesis 2 holds, we observe negative coefficients on the first two dummies, No access&active and No access&inactive, at a larger magnitude for the second one. As long as private wells provide sufficient irrigation water, farmers achieve a high yield even in an inactive village; thus, the coefficient of the Access&Inactive dummy is expected to have no significant difference from the base. Turning to the agricultural labor income function, if income is supplemented by an increase in agricultural labor income, we should observe positive coefficients on the first two dummies at a larger magnitude for the second one. The same structure can be observed in the non-agricultural income function. However, since accessibility to non-agricultural occupations is largely determined by level of education rather than by irrigation status, we may not observe significant coefficients on the irrigation status dummies. Finally, if supplemental income is large enough, in the total income and consumption value functions, we should not observe any significant coefficients on the irrigation status dummies. On the other hand, if supplemental income is insufficient, we should observe negative coefficients again on the first two dummies at a larger magnitude for the 25

26 second one. To measure irrigation status, we must also control for the distance from the irrigation source to farmers fields because, in gravity irrigation systems like tank systems, this distance affects water availability. Moreover, the effect of distance may vary depending on the status of collective management and well access. In our explanatory variables, we include not only the distance from the tank but also the interaction of distance with our three irrigation status dummies. Consequently, our regression equations include six explanatory variables containing information on the status of accessibility to wells. Accessibility to wells, however, potentially entails endogeneity and measurement biases. 15 These potential biases are controlled by the instrumental variable method. 16 The other determinants included in the rice yield regression are a set of household human and physical asset variables, socioeconomic characteristics, and 15 There are two kinds of potential bias. First, under our definition of this dummy variable, the no-access group would include non-owner farmers who actually had access to well irrigation but chose not to use it because they had enough water from tanks or rainfall. These farmers presumably achieve yields and income as high as those of the farmers who use wells. The incorrect inclusion of them in the no-access group would result in an underestimation of the negative impact of non-access. Second, if high-income farmers selectively became well-owners, the impact of non-access would be overestimated. 16 The identifying instrumental variables that explain the six potentially endogenous variables include not only those that explain non-access to wells such as the number of water sellers in a village, the number of water buyers in a village, the cost of well digging and its squared term, and the value of house building but also the interactions of those variables with the inactive management dummy and with distance from the tank (Wooldridge, 2002). 26

27 village-level characteristics. The descriptive statistics are presented in Appendix Table A4. The household asset variables include (1) the proportion of working members with primary, secondary, and college-level schooling, respectively; (2) the average age of a working member and its squared term; (3) the size of the rice plot and its squared term; (4) the value of animal holdings per working member and its squared term; (5) the number of working members; and (6) a tractor owner dummy. The socioeconomic variable is the gender of the household head (male=1). Village-level differences are controlled by the male wage rate, block-level annual rainfall, the dummy measuring accessibility to the village by a vehicle, and the percentage of households wired for electricity. In the regressions other than the rice yield function, instead of rice plot size, we use (1) the size of tank-irrigable plots per working member and its squared term and (2) the size of tank-non-irrigable plots per working member and its squared term. Since the consumption value is affected by permanent household income instead of income for a particular year, average rainfall over the last ten years is used rather than annual rainfall. Regression results The regression results for yield, agricultural labor income, and non-agricultural 27

28 income are reported in Table 4, and the results for total income and consumption value in Table 5. In the functions in Table 4, endogeneity is not detected, thus we show the OLS results alone. Meanwhile, Table 5 shows both the OLS and IV results, since the F-tests indicate the possibility of endogeneity. In Table 5, the F-tests on the instruments in the first-stage regression are highly significant for all six endogenous variables, indicating high predictive power. The over-identification tests show the difficulty of rejection of the exogeneity of the instruments at the 5% significance level, adding confidence to the validity of our IV specifications. The results of the rice yield function in Table 4 show the expected signs and magnitudes for the No access&active and No access&inactive dummies. A key finding from this is that compared with the yields of farmers with access to wells in collective management active villages (base case), the yields of farmers without access to wells is 337 kg lower even in the same active villages, confirming the importance of private wells as a supplementary irrigation source. Another key finding, this one related to inactive villages, is that in those villages, the yield gap between farmers with access and those without is becoming wider (863 kg). 17 This is larger by far than the yield gap in 17 Note that, unexpectedly, the coefficient of the Access&Inactive dummy is positive and significant (773.2 kg). Note also that the distance has a negative effect only among Access&Inactive farmers; at the average distance from the tank (0.545 km), this variable has a negative effect of 664 kg. Hence, the yield gap in inactive villages between the farmers without access to wells and those with access to wells is computed as ( )=863 kg. 28

29 the active villages noted above. Based on this result, we conclude that Hypothesis 2 holds. The results also indicate that all village characteristics are not significant. This feature holds for all the following regression functions except for the agricultural labor income function. Presumably, our key village variable, collective management status, representatively captures the village-level differences in our tank-irrigated villages, and thus its inclusion reduces the importance of the other village-level variables. The results for the agricultural labor income function in Table 4 also show the expected signs and magnitudes for the irrigation status dummies, indicating that lower income is compensated for by agricultural labor. However, the amount of compensation is not large in either case: Rs or Rs per person per month. In the non-agricultural income function, the insignificant coefficients for the first two dummies indicate that this income source is not available to either No access&active farmers or No access&inactive farmers as a supplemental income source. Rather, non-agricultural income is determined by the proportion of college-level graduates to the number of working members in a household. These results imply that opportunities for income diversification are limited, and thus we expect lower income and consumption among farmers without access to private wells in Table 5. As expected, the coefficients of No access&active and No access&inactive are 29

30 negative at larger magnitude for the second one. The IV results on total income indicate that in the active villages, the gap of total income between the farmers with and those without access to wells is Rs , becoming wider (Rs ) in the inactive villages. 18 The same qualitative pattern holds for the consumption value function, except for the insignificant coefficient of the distance variable. Given an average distance for all farmers of 0.4 km, the impact of distance is not large, and thus it is probably not captured as significant in the consumption value function. Counter-factual analysis The regression analyses indicate that farmers without access to wells suffer not only lower yields but also a lower income and consumption value when collective management declines. Although the negative coefficients are statistically significant, the magnitudes of the impacts may be marginal. Hence, one may raise a question as to whether the lower income caused by the decline in collective management is large 18 Two remarks are necessary here. First, comparison of the OLS and IV results shows the OLS s overestimation of the negative effects, implying that the root of the bias is in the rich farmers self-selection of being well-owners. Since income level is important to well ownership but yield, agricultural labor income, and non-agricultural income alone may not be, the three functions in Table 4 do not suffer an endogeneity problem. Second, the coefficients of Access&Inactive are no longer significant. Although the farmers with access to wells in the inactive villages achieve high yields, they grow rice intensively, with the use of wells as the primary source of irrigation. Sakurai and Palanisami (2001) show that the intensive use of wells does not necessarily result in high profit as it requires greater operation and maintenance costs than does tank management. Hence, no significant difference in profitability and thus in income is observed. 30

31 enough to result in greater poverty and inequality in the inactive villages. In other words, will the revitalization of collective management help alleviate poverty and inequality? Using the regression results and assuming active collective management in all the villages, we predict yield, total income, and consumption value. These descriptive statistics, including the Gini and the poverty indexes computed from the predicted values, are added to Table 2 as column (A-2) and are shown as Table The last column in Table 6 shows the differences between the inactive villages under the counter-factual assumption and the actual active villages. The differences in the mean values are no longer significant for either variable. The Gini coefficients of income and consumption in the inactive villages have declined, resulting in insignificant differences in the comparison of village-level averages. Comparison of yields still indicates the existence of significant differences, yet the levels of the Gini coefficients themselves have become very small. The changes in the poverty indexes show that the poverty ratio and gap are reduced to the levels of the active villages. These results indicate that the negative impacts from the decline in collective management on farmers without access to wells are so large that the revitalization of collective management can contribute significantly to reductions in 19 For comparability with the figures in Table 2, the residuals from the actual data are added back to the counter-factual predicted value. Otherwise, the Gini, which measures a kind of variation, becomes incomparably small. 31

32 poverty and inequality. 6. Conclusion and policy implications Using village- and household-level data collected in Tamil Nadu, India, we examined the factors underlying the decline in collective management of tank irrigation systems and the impact of that decline on rural livelihoods, especially in terms of poverty and inequality. A key conclusion of our regression analyses and counter-factual analysis is that the diffusion of private wells is one of the factors accelerating the decline in collective management, and that this decline leads to lower yields only among farmers without access to private wells. Our analyses also find that since these without-access farmers cannot sufficiently compensate for their lower income by diversifying income sources to agricultural labor or to non-agricultural work, lower yields translate into lower income. Farmers with access to private wells, by contrast, can continue to obtain high yields and high levels of income. As a result of this situation, poverty and inequality increase; thus, through this process, the decline in collective management carries social costs. According to our field observations in inactive villages, this consequence has yet to reach the point where without-access farmers sell their land to with-access farmers. The former usually leave their land fallow, relying on a 32

33 subsidized rice quota from public ration shops for their living. One of the major contributing factors to the decline is the exit behavior by some farmers who have gained alternative irrigation sources such as private wells. It is difficult to deter their exodus from collective management because they do not suffer the consequences of the deterioration in tank performance, unlike the remaining farmers. The number of exiting farmers will inevitably tend to increase in response to the development of small or medium-size irrigation technologies that are used by individual farmers. Unless less labor-intensive systems are introduced or some kind of support is given, it will be difficult to maintain collective tank management. One promising possibility suggested by our analysis is the use of lined channels with tank systems. This technology significantly reduces the labor required for maintenance work and also increases water availability by minimizing seepage. Although thus far construction of lined channels has been undertaken by the PWD, if the return on investment is assured, WUOs may decide to take over the task as a local public goods initiative. It will be important to conduct detailed cost-benefit analyses on the impact of channel lining and, if warranted, design appropriate support programs. Charging an appropriate fee for electricity would also help prevent a decline in collective management. Under the present practice of free electricity for agricultural 33