An Empirical Analysis of Pricing Strategies for Water in Agricultural Punjab

Abstract

This paper examines how water pricing would affect water demand and the productivity of farmers in rural Punjab. The paper aims to answer the following questions: To what extent can water pricing mechanisms solve water insecurity in rural Punjab? Is the absence of price controls for water affecting the efficient supply of water to farmers? Does water pricing lead to equal and more efficient use of water? Are farmers willing to pay for such a water pricing mechanism? I surveyed farmers across Punjab, specifically with 47 respondents, to understand the issue through a regression analysis. The farmers surveyed are from key areas across Punjab, including Multan, Bahawalnagar, Gujrat, Sargodha, Rahim Yar Khan, Sahiwal, and Faisalabad. I estimate the elasticity of demand for water usage and revenue under different tax regime schedules. I find that water is a productive input for farmers across Punjab, with the finding that a 1% increase in water usage leads to a 0.83% decrease in farm revenue. I find that farmers report a decrease in water due to taxes, resulting in loss of revenue from the reduced water supply, as well as loss of revenue from taxes on water. The loss in revenue varies with the change in income bracket. Ultimately, my results suggest that the government of Punjab employs cautious, piloted, and progressive taxation on water reform in rural Punjab. The limitations of this paper include the absence of water metering data in Punjab, which necessitates the paper’s reliance on farmer responses

Introduction

Efficient water use in agriculture is a crucial topic for economic analysis. Crucially, overuse and water wastage are a worldwide phenomenon, but are dependent on local systems and policies. Punjab, a province in Pakistan, lacks holistic, manageable legislation in policy and regulation in the water sector. The proof of their obsolescence lies in their reliance on the Warabandi system, a water distribution system developed in the 1800s. This document remains the schedule for surface water distribution. With the onset of climate change and faulty infrastructure, Punjab’s water supply continues to fall dramatically. A water scarcity crisis arises from Punjab’s inability to meet the excessive demand, as farming across Pakistan accounts for 45% of the labour force, 20% of the GDP, and 60% of the country’s foreign exchange. Punjab and Pakistan, more than anywhere in the world, rely on their agricultural sector¹. Critically, Punjab lacks a tax or tariff-based system of legislation, relying instead on general government regulation, which has yielded no benefit. These conditions make it a good setting to study, and few studies have investigated this setting, for example²,³.

On the one hand, water is underpriced, which means agriculture can become a dominant industry in certain countries, thereby significantly increasing the country’s GDP and quality of life. On the other hand, underpricing could lead to inefficiencies that counteract this effect. Underpricing could lead to significant amounts of over-extraction for water-intensive crops (rice, etc.). Furthermore, it could create a spillover effect, with overextraction leading to a decrease in the overall water supply in less rainy seasons, thereby reducing the ability of poorer farmers to extract water for their crops. This process mirrors the tragedy of the commons, as the lack of regulation creates non-excludability for ground and surface water. Studies in the past have explored the use of tighter regulatory controls and property rights; however, none based in Pakistan have proposed a pricing/metering approach. Crucially, it is essential to determine whether farmers would be amenable to such a tax or if it would hinder their agricultural production.

In this study, I directly test the willingness of farmers in Punjab to participate in such a scheme by surveying them to understand better their perception of water wastage, as well as their responsiveness to the changes in prices for taxes per gallon of water. Crucially, I try to understand that the introduction of pricing mechanisms may lead to a reduction in farmers’ extraction of water from both the canal and groundwater, thereby reducing water wastage. Due to limited data on water usage and the absence of studies that survey farmers, an approach that interpolates the farmers’ willingness to pay is necessary.

My findings indicate that the overuse and wastage of water in Punjab farms have created a negative externality of consumption, thereby reducing the water supply for other farmers in similar regional areas. This is because of the overextraction of groundwater, which leads to a shortage for other farmers in Punjab. Punjab’s water crisis is fueled by the overexploitation of groundwater resources and inefficient techniques for using surface and canal water. Of the total 90 MAF of available water in Punjab, the total losses amount to 37 MAF⁴. As the years pass, Pakistan has been increasingly grappling with the water insecurity crisis. Being an Agri-based economy, with more than 80% water usage in the agricultural sector⁵, the shallow and outdated policy for the supply and usage of water has led to critical inefficiencies. It has come at a significant cost to Pakistan’s water supply. Finally, through the survey, I found that the effect of the tax varies with income level. In general, farmers report losing water from taxes, losing revenue from the loss of water, and losing revenue from a tax on water. The loss in revenue varies with the change in income bracket.

I contribute to two main strands of literature: (1) water use and scarcity in agriculture and (2) water policy for agriculture. Among the current literature, this paper is essential for understanding farmers’ perception of water wastage and their responsiveness to pricing mechanisms introduced to curb overuse. For groundwater, the current literature portrays a picture of an overused and exploited groundwater system in Punjab, characterized by a well-developed yet poorly managed policy infrastructure. My paper aims to examine government intervention, specifically in the form of taxes or tariffs, rather than previous market policies and regulations, to curb the excessive depletion of the resource. Finally, for surface water, current literature supports demand side policies as well as managing supply and inefficiencies by increasing storage capacity, increasing data inflows, and establishing water rights⁶,⁷,⁸,⁹. Though most issues pointed out by current literature make surface water less dependable, less replenishable, and an overall depleting resource in the future. This leads to the overuse of groundwater, which, through excessive extraction, contributes to water scarcity. This study aims to address this issue by implementing a pricing mechanism for both, as well as providing further recommendations for increasing data inflows through metering and establishing property rights.

Institutional Setting

Pakistan is an agriculturally based economy, with less than a quarter of its GDP derived directly from agricultural resources. For this usage, Pakistan has an estimated net withdrawal of 148 billion cubic meters of water per year on average; however, its water availability has declined, with⁵ suggesting a stress level of 80% on water usage. On average, Pakistan uses the most water for the four primary crops: wheat, cotton, rice, and sugarcane. Punjab dominates the agricultural sector, accounting for over half of the country’s agricultural output. Accordingly, the productivity per hectare of water used has increased in both Sindh and Punjab, with values ranging from US 0.04 to US 0.08 in Punjab and from US 0.03 to US 0.06 in Sindh⁵. Although this growth has shown a potentially double value, the potential for maximum yield is now low. Groundwater is over-extracted, and the absence of a price mechanism does not account for that. Furthermore, arable land is diminishing, and the Warabandi system² has made surface water unattractive for many farmers.

Groundwater

Groundwater (private tubewells) has experienced an overwhelming boom in the last few decades.
Following a significant increase from the 1960s Green Revolution, Pakistan had 1.2 million tubewells as of 2018. This is a substantial increase from just 30,000 in 1960¹,². which makes it the fourth-largest country in the world in terms of groundwater extraction. 85% of these tube wells are in Punjab, making the province the largest of the five. The extraction, on the other hand, is closer to 90% Furthermore, this has led to an increase in agricultural land in Punjab, moving from 8.6 to 16 million hectares of land. Groundwater has become crucial, as it provides 73% of the water used for irrigation in Punjab, making it the primary source of water².

With this overreliance on groundwater, the literature reveals that Punjab faces multiple issues and driving factors that have contributed to a crisis of insecurity today. The first issue is over-extraction and recurring depletion of aquifers. Additionally, Punjab’s favourable quality of groundwater massively favoured farmers, with only 23% of the resources classified as poor³. With an overall increase in demand for more water-intensive crops, the aquifer pumping has already hit the ceiling of 43 MAF, as groundwater today completely depletes natural aquifers (Pakistan Irrigation Department, 2018). The water in aquifers is not “new” water; it is recharging, seeping in from the unlined canals of the Indus Basin (IBIS). The implication of this is that there is a significant amount of over-extraction in groundwater resources. Corroborating this, current research indicates an aquifer recharge-to-discharge ratio of 0.8%, suggesting that groundwater is being extracted faster than aquifers can recharge⁶. This has resulted in a reduction of Punjab’s water tables. Key areas, such as Lahore (48 feet drop), Multan (32 feet), and Pakpattan, with a 44 feet drop. 27 out of the 30 districts have experienced a drop in water tables¹⁰. Although current literature outlines this threat, the lack of data management and reporting may imply a greater issue than currently understood.
The literature attributes this lack of policy and regulation to the government’s continued allowance of privately developed tubewells. Initially, the government was primarily focused on soil salinity and waterlogging as the most significant issues, which is why they allowed private tubewells to continue in use and maintain their popularity. The lasting impact of these results is a disappointing dearth of legislation. The earliest account of this legislation is found in the Provincial Irrigation and Drainage Act of 1987. Even this analysis, however, remained confined to the role of canal and surface water for farmers, while largely disregarding the regulation of groundwater¹¹.

Notwithstanding, progress has started to develop recently. The most significant policies include the Punjab Water Act of 2019, a revolutionary act that not only emphasizes the need for licensing, monitoring of aquifer conditions, and classifying groundwater as a public resource but also includes emergency restrictions. Furthermore, the complementary policy introduced in the Punjab Irrigation, Drainage and Rivers Act 2023 strengthens quotas, aquifer zones, and sanctions the use of illegal pumps and tubewells. Current literature tends to overlook regulatory steps that address the issue at its core. Though a metering and a tariff system are not included in the mentioned acts, regulations that this study aims to add to, additionally, current policy has not led to a slowdown in falling water tables, as the rate at which they fall has been consistent, even with the introduced policy¹⁰.

Surface Water

The surface water in Punjab is dominated by the Indus River, with large tributaries and canal networks spanning the province. The tributaries and canals were established during the British colonial era in the 19th century.

Annually, the tributaries carry 180-190 billion cubic meters (BCM) of water from India⁶. This is due to the Indus Water Treaty (1960), which allocates three eastern rivers (Beas, Ravi, and Sutlej) to India, with the three western rivers (Indus, Jhelum, and Chenab) allocated to Pakistan. Of the water the tributaries carry, 130 BCM goes into the Canals for irrigation. Punjab rests on the three western rivers; hence, it has the best access to canals. It accounts for 48% of the share of surface water diversions, as mandated by the 1991 Water Appointment Accord. This accord, although outdated, may serve as an inaccurate tally of how much Punjab uses. Of this amount, 95% of the withdrawals go to agriculture¹². The withdrawals cover 16 hectares of land on the IBIS (Indus Basin Irrigation System), which is often cited as the world’s most contiguous irrigation network². As described previously, the rising demand for crops was met with an increase in groundwater extraction, as little to no new canals were constructed from the 1980s onwards. This indicates that the deliveries of surface water are insufficient for the growing Agri-economy.

The first issue the literature mentions is that of the inefficiencies in infrastructure. The recurring problem here is the limited storage capacity of the canals and tributaries. This is due to Pakistan’s river water being seasonal, as it sees a sharp increase in the monsoon periods and a decrease in the winter months. Even then, they deliver only 30 of water, which only fulfills 15% of the crop water required, which falls greatly short of the mark. Furthermore, Pakistan’s reservoir capacity is around 30 days, which is an extremely low number compared to the 900 days of the Colorado River². Pakistan has only built a few large dams. The last major dam, Tarbela, was completed in 1970. The neglect of water beds has led to an increase in siltation, which is predicted to decrease storage capacity by 57% by 2025¹³. Moreover, the National Water Policy of 2019 states that more than 50% of the water does not reach fields due to inefficiencies in irrigation and canal supplies, a figure that groundwater has had to compensate for. For farmers, this can create a spatial imbalance, as head-to-end farmers have a greater advantage in accessing water than tail-to-end farmers.

Furthermore, literature focuses on productive output. According to the UNDP 2017 report on Pakistan’s water vulnerability, it is classified as the lowest globally in terms of crop yield per benchmark. Rice, sugarcane, and wheat all fall behind international benchmarks, as they are heavily reliant on canal and surface water for irrigation. This leaves the reduced storage and efficiency problem as not just a question of improving storage capacity, but rather working on improved techniques for farming, such as drip irrigation, which is argued to save 30-70% of water across crop types and depending on the season¹⁴.

Lastly, the everlasting effects of climate change are hard to ignore. Studies such as¹² project glacial melt, which can increase supply in the short term, but prove detrimental to long-term supply. Threats such as these, coupled with droughts in 2010 and 2014, suggest that climate change has a significant impact on Pakistan’s surface water supply.

Policy Litterature

Sheila M. Olmstead and Robert N. Stavins (2009)¹⁵ argue that economic signals, particularly price-based approaches, can often be more predictable and cost-effective in conserving water than purely regulatory or educational efforts. Their focus on urban environments still provides valuable insights for agricultural contexts, as effective policy in both cases hinges on accurately measuring water consumption to determine what, if anything, users should be charged for. The importance of measuring mechanisms becomes clear when considering Warford’s¹⁶ contention that the marginal opportunity cost of water should include not only production and user costs but also environmental impacts. If policymakers cannot track how much water is being consumed, they cannot incorporate these broader costs into fees, taxes, or any form of price-based policy.

Several types of measurement technologies have been proposed or deployed in various agricultural settings worldwide. Mechanical or accumulation meters record total usage over time, providing a cumulative figure that can be read periodically for billing or data gathering. Pulse-signal meters add a layer of detail: after a fixed volume of water passes (for example, every ten or one hundred liters), a pulse is sent to a data logger, which can be accessed via a drive-by system or a remote transmitter. Interval meters take this further by recording usage at defined time intervals (such as hourly), thereby offering a more granular view that could, for instance, flag unexpected surges in consumption that might indicate leaks. Advanced models, such as the one Thomas Boyle¹⁷ discusses, Automated Meter Reading (AMR) and Advanced Metering Infrastructure (AMI), enable either one-way or two-way digital communication between the meter and the utility, often providing near real-time data. This higher-frequency information can be paired with dynamic pricing, similar to peak and off-peak rates in electricity markets, and can enable faster detection of anomalies, such as leaks or unauthorized usage. However, the cost of equipping entire regions

Parameter	Measurement	Transfer	Processing/Analysis	Feedback
Mode	Water meter and data logger technology combinations used to capture information about water consumption. Residential intelligent metering typically uses displacement meters which generate a pulse signal after a set volume passes through the meter.	Means by which data is transferred from meters to utilities, customers and back. Data is transferred from the data logger via broadband, cable or wireless (e.g., radio, GSM, CDMA *). May be fully remote or require near range collection (e.g., drive-by download).	Means by which a utility/third party stores (e.g., data servers) and manipulates (e.g., end-use analysis software package) water use data. Implications for third party access.	Method by which data is provided to customers for interpretation, e.g., postal bill, email, web interface, smart phone application. Behaviour change may/may not ensue.
Frequency	The specified time intervals at which (i) water use is recorded by the meter/between number of pulses; and (ii) data from the meter is collected by the data logger, e.g., 15 min intervals.	How often data is sent or collected by the utility/third party, e.g., daily, half hourly, real-time. Will vary depending on the type of meter, e.g., pulse versus interval.	The frequency at which water use information is used to update utility operations (e.g., for pressure management).	The frequency at which water use information is communicated to the customer (e.g., quarterly, monthly, daily, real-time,etc.)
Resolution	The granularity of water flow detected by a water meter (e.g., L/pulse). Determined by the purpose, capabilities and settings of the water meter. Resolution of the recorded data by the data logger, e.g., L/15 min (i.e.,frequency of measurement, above).	Resolution of data remains unchanged, though quality of data (i.e., complete/partial) may suffer from disruptions to transmission process.	Data may be aggregated or manipulated to analyse trends (e.g., leak assessment; end-use analysis).	The level of detail of information provided to the customer, such as usage per unit of time and/or end use breakdown. Comparative framing and benchmarking may aid legibility and comprehension. Content and framing should be informed by behaviour change theory, information about target audience and tailored to the mode in question.

Within the context of Pakistan, colonial-era documents continue to define surface water allocations, leaving formal property rights incomplete or nonexistent¹⁸. Without legally recognized entitlements to water, it becomes difficult to implement metering programs that assign each user a specific allotment. Furthermore, the socio-political environment can allow powerful farmers or local bureaucrats to extract more water than they are entitled to, while smaller farmers are marginalized. Groundwater extraction poses another challenge: many farmers pay only for the energy (diesel, electricity) it takes to pump water from aquifers, rather than for the water itself. As Gisser and Sanchez¹⁹ have noted, if an aquifer is not yet on the brink of depletion, policymakers may underestimate the long-term consequences of unregulated extraction. This gap is especially concerning in arid or semi-arid regions of Pakistan, where the threat of serious depletion looms but has not always manifested into immediate crises. Zekri²⁰ and co-authors suggest that “smart water” solutions, including metering and integrated hydro-economic models, can help track groundwater usage and prevent catastrophic drawdown. Still, high installation and operational costs, coupled with limited local institutional capacity, hinder their large-scale rollout.

Despite these obstacles, global case studies illustrate the benefits of accurate metering for effective water management. A time-varying difference-in-differences analysis in China, conducted by Lin Fang and Fengping Wu²¹ , demonstrated that well-defined water rights, combined with a trading scheme that relied on robust consumption measurements, promoted conservation across regions. A similar outcome was observed in Northern Italy, where shifting from flat irrigation fees to volumetric charges (supported by meter readings) curtailed over-irrigation Pronti²². Robert Stavins’s²³ broader work on environmental pricing suggests that if water usage is verifiable, either a cap-and-trade system or a water tax can reduce consumption; indeed, both approaches depend on consistent data about how much water each user withdraws. Yet it is crucial to acknowledge that implementing such schemes in Pakistan might require not just technological tools but also social and institutional reforms—Elinor Ostrom’s (2000)²⁴ work on local-level governance, for instance, hints that community buy-in may be critical where trust in central authorities is weak. Meanwhile, Pigouvian taxes (Andres Chambouleyron, 2002)²⁵ , aimed at capturing the environmental externalities Warford (1994)¹⁶ described, will only be effective if they are tied to reliable measurements and if revenues are managed transparently.

Chambouleyron’s (2003)²⁵ perspective on optimal metering and pricing further underscores that installing the most advanced meter in every location is not always economically justified. If the cost of installing and maintaining meters outstrips the savings or revenue derived, a more targeted approach—universal in some areas, selective in others—might be the best compromise. Indeed, his work highlights the risk that private water utilities may place meters primarily where they expect to maximize profits, thereby excluding lower-income or less profitable regions. Addressing this in Pakistan will demand clear regulations and oversight to ensure that short-term economic gains do not eclipse the social objectives of equity and sustainability. Coase’s²⁶ insights into property rights and bargaining suggest that once water rights are properly delineated, communities or individuals might negotiate usage levels among themselves. Yet, corruption and bureaucratic myopia can derail such negotiations if there is no transparent system in place to enforce agreements.

Taken together, these studies imply that Pakistan’s path forward must include improving and expanding water metering technology while simultaneously overhauling legal, institutional, and governance structures. Accumulation and pulse-signal meters may be low-cost stepping stones for gathering baseline data, instilling a habit of measuring, and managing water. In high-stakes regions, interval metering or even partial AMI deployment might offer richer data for dynamic pricing or swift enforcement. If property rights are clarified, as Coase (1960)²⁶ would recommend, then trading schemes echoing Stavins’s carbon-market analogy could theoretically allocate water more efficiently, provided that metered data are reliable. Warford’s (1994) idea of incorporating environmental costs into the marginal opportunity cost of water highlights the broad scope of the vision for pricing. Although Pigouvian taxes or other charges may seem out of reach in places with weak governance, Elinor Ostrom’s (2000)²⁴ emphasis on local stakeholder involvement suggests that community-driven metering could still mitigate the unrestrained depletion of common resources, such as aquifers.
Ultimately, the solution may lie in a combination of advanced measurement technologies, targeted pilot programs, progressive legal reforms, and careful attention to the social context in which these tools are introduced. Whether universal metering is adopted or a more selective rollout is pursued, the experiences from China, Italy, and other regions demonstrate that accurate, verifiable data on water usage is indispensable for guiding policy—whether tax-based, trade-based, or otherwise. The cost of ignoring water measurement in Pakistan becomes increasingly clear each day, as escalating demand, looming climate pressures, and entrenched institutional inertia threaten the sustainability of this essential resource.

Methods

The primary question driving this study is to understand the extent to which farmers will respond to the addition and use of metering systems and subsequent water taxation for their farm-based water usage. The study hypothesizes that farmers will acknowledge significant water wastage, as seepage and crop overflows are common practices in Pakistani agriculture, as noted in the literature. Furthermore, it is expected that the introduction of a metering system, coupled with incremental increases in the price per gallon of water, will incentivize farmers to reduce their consumption, thereby decreasing the extent of over-extraction. I aim to demonstrate a trend among a subsample of farmers acknowledging high water wastage, which may be indicative of the rest of the farmers in the area. Secondly, with an increase in the price per gallon of water (accompanied by the addition of a metering system), farmers would use less water and eventually reduce their overextraction. Ideally, we would like to test whether a policy introducing these price variations causes changes in our outcome variables of interest. However, no such policy has ever existed in Pakistan, and data on water usage for farms is not readily available. Therefore, I use a survey to capture how farmers would respond to such a scheme. Although the reliability of human judgement of quantitative metrics (e.g., water wastage) may bring a threat of unreliability, the survey follows best practices for ensuring the most reliable answers for such an exercise.

Survey

The survey conducted was a comprehensive questionnaire to over 100 farmers. Out of those, 10 surveys were conducted in person at the farms, and the rest were completed over the phone. The farmers were chosen through a random sampling, which utilized FarmDar (an Agri-tech business in Pakistan’s farmer database. The timeframe for the sample set was five months, spanning from January to May. This covered the spring to early summer seasons for farmers. The average completion time of the survey was five minutes. No additional compensation or incentive was given to the respondents. Two versions of the survey were created, one in English for ease of data analysis and another in Urdu, the native language of Pakistan, for ease of interviewing. Each answer was taken consensually and asked in Urdu.

The questions, as listed in the appendix, follow three general themes. The first theme is general information on the farm, which would recover data on income, farm size, region, and crop type. The second theme is water usage, in which I recovered data on the amount of water farmers use, how much they pay, and what method they use to extract. The third area involves hypothetical pricing scenarios, in which I analyse data on changes in farms, including changes in revenue, size, growth, and types of crops.

This data was essential for finding the elasticities of water and tax, as well as the productivity of water, and for understanding how different income groups respond to pricing scenarios, which are later presented in the regression. The survey went through three iterations. All three were piloted with three farmers, who provided feedback on the length, ease of understanding, and general accuracy.
The sample pool was restricted to farm owners to focus on respondents with the greatest information about their own farms. In total, 47 surveys have been completed out of 150 respondents engaged. This response rate of 31.3% is good compared to the generally low response rates of short on-the-phone surveys, which average around 30% in other on-the-phone or email-based studies²⁷.

Data

The survey population consisted of farm owners, as they would be best disposed to knowledge about the demand for water, the size of land that requires water, the farm’s revenue, and their willingness to pay for each volume of water. Ultimately, the farm owners will be responsible for paying for water by volume; therefore, they are the most critical individuals to target through the survey. The data received will provide the most representative sample of the farm, hence it is the best population to use. The locations of the farmers interviewed are displayed in Figure 1

Although locations are spread across Punjab, each area has similar regional and climatic features, such as arid climates, low annual rainfall with precipitation between 200-500 mm annually, and an average summer temperature between 35.6-39 degrees, and a winter temperature between 18.5-26.6 degrees. With surveyed farmers facing similar regional and climate features, this mitigates unwanted bias from the findings.
The data required from the survey ultimately aims to identify trends in the willingness to install volumetric meters, as well as to gauge the willingness to pay of each farmer. This data will provide necessary insight and nuance into the prices per volume of water that people would be willing to pay. Not only would the willingness to pay make the distribution more equitable, but it also indicates the price at which all farmers can access water, thereby avoiding neglect of certain groups, which would create further market failure. Moreover, the survey elicits information on progressive tariffs per volume for water. As shown, progressive taxation not only increases equity but also reduces market failure and corrects for the myopic nature of farmers. This is studied in Menzein-Dick²⁸, as the paper employs behavioural economics to explain farmers’ short-term decision-making preferences in comparison to decisions made for long-term sustainability. The question elicits information on the perceived extra amount that higher-income farmers should pay. Relating the answer to this question to income, we can see the trends of which income levels wish for there to be more progressive taxation, and against which income levels do not. The expected trend is that larger farms and higher-income farmers may opt for higher tariffs, while lower-income farmers may prefer lower tariffs.
Finally, the survey determines the water wastage of farms. This is crucial for understanding the extent of market failure and addressing the need for marketing to reduce water overuse. I ran a regression analysis to break this down, and the result was that, on average, farmers reported a 46.5% water wastage.

Results

General Overview of Farms

Analyzing the survey results, the average water wastage reveals an alarming 50% of water being wasted. This suggests that nearly half of the water resources that farmers either procure from canals or groundwater bores, or both, are of no use to the farm and are barred from further use, as runoff water collection methods are scarce. On average, 46.5% of total water is wasted, creating market failure as the market never achieves allocative efficiency. This occurs because water that other farms may need is wasted through the water wastage of different farms, thereby decreasing the supply to a level below the socially optimal level. This also provides a further reason as to why metering water is essential, as measuring exactly the amount of wastage of water helps investment target where infrastructure may be improved to increase supply.

Further analyzing the water wastage trend, as shown in Figure 2, it is observable that there is a difference in average water wastage according to the size of the farm. A small farm was taken as less than 10 acres of land, a medium farm was taken as between 10 and 200 acres of land, and large farms were taken as greater than 200 acres of land. On average, waste in smaller farms is greater than that in medium and large farms. The difference between small farms and large farms is an average of 28 gallons, whereas the difference between smaller and medium-sized farms is 13 gallons.

As the size of the farm is often indicative of revenue, this may mean that smaller farms have less money to spend on water-conservation techniques. A lack of these techniques would result in an increase in water waste, as runoff water is not collected and reused. Excess waste may be a contributing factor to the poorer quality of the infrastructure used to supply water to the rest of the farm. In all scenarios, the wastage of water creates a negative externality; however, it is essential to note that this effect is particularly pronounced for smaller farms, as wastage leads to greater inefficiency. With this problem arising, all farmers surveyed expressed a desire to have a volumetric meter installed on both their canal and their bores to measure the intake of water. Every farmer reported that the sole purpose of this was to gauge their water wastage and implement conservation methods to correct for this inefficiency in supply. The methods of acquiring water is shown in Figure 3

To further understand the trends of farmers in Punjab, Figure 4 shows the types of crops cultivated across Punjab. Wheat, rice, and other crops, such as potatoes, bajra, and maize, are the most common, regardless of the growing season. The most water-intensive crops are rice and sugarcane, with rice accounting for 70.97% of all respondents. This indicates that the water requirement is relatively high across all farms. Moreover, Punjab’s agricultural economy is primarily driven by wheat production, earning it the nickname the “Breadbasket of Pakistan.” It accounts for 75% of the total output²⁹. Other than this, there is no discernible trend, as the cultivation of different crops is spread evenly across farmers.

The survey details that 100% of the farmers were willing to install meters on their farms, as their motives often included seeing their water usage in real-time, as well as making their water supply more efficient for each crop. Furthermore, regardless of income distribution, each farmer expressed concern about water wastage and argued that meters would help reduce the amount of water they waste. Figure 5 details the willingness to pay for the installation of water meters for canals and bores. The data show that most respondents favored a price of 1,000 PKR, with 2,500 PKR and 0 PKR following. The value that farmers are willing to pay is 4,500 PKR. The policy implications are that farmers are most willing to pay between 0 and 2,500 PKR for installation by either the government or local utility companies.
In our results, 51.612% of farmers are unwilling for the government to provide installations, whilst 48.38% of them are willing. The difference between the two is 3.23%, indicating that farmers are split between the decisions. Policy implications suggest that farmers should be given the option for their local third-party utility company or the government to be responsible for their meters, ensuring that meters are installed throughout Punjab.

The Effect of a Water Tax on Water Use

The specification in Column 1 examines how current monthly changes in water cost from a tax log tax affect reported water use log water, controlling for farm size and income. The coefficient on log tax is 2.020***, meaning that a 1% increase in water-related costs is associated with a 2.02% increase in water use. This counterintuitive result most likely reflects the behavior of borewell users, who bear higher pumping costs but extract water in large volumes. Since costs are not volumetrically regulated, usage is not constrained.

The positive and significant coefficient on Log_FarmSize (1.301***) indicates that larger farms consume more water. Several income group dummies are negative and significant, indicating that middle-income farmers may use less water relative to the lowest-income group, possibly due to different crop choices, access to better infrastructure, and more effective irrigation practices.

Column 2 has the same story as Column 1, but in this specification, I regress log_Water on dummy variables representing three hypothetical price points presented to farmers in the survey: Rs 0.01, Rs 0.05, and Rs 0.10 per unit in level terms. The coefficients are large and statistically significant: 16.84* for Rs 0.01, 19.62* for Rs 0.05, and 23.93* for Rs 0.10. The increasing pattern suggests that farmers who responded to higher price scenarios also report higher current water usage. This is not a causal effect of pricing, as all farmers responded to all scenarios. Instead, the pricing dummies proxy underlying farmer characteristics. Larger, wealthier farms are more confident about handling higher prices and also tend to use more water. Log FarmSize remains strongly positive and significant (1.145*), reinforcing the idea that water use scales with landholding size.

The Effect of a Water Use Tax on Revenue

The third column in Table 1.8 estimates the relationship between water use and farm revenue. The coefficient on is 0.834***, indicating that a 1% increase in water use is associated with a 0.83% increase in revenue. This strong, positive relationship confirms the central role of water as a productive input in agriculture. Notably, is not significant in this model, suggesting that water access is more closely tied to revenue generation than landholding size. Several income dummies are negative, indicating that some middle-income farms may generate lower revenue than the poorest group — possibly due to limited water access, less intensive cultivation, or different crop choices. Further, the fifth column provides insight into how revenue might change under hypothetical volumetric pricing. Moving from a scenario with no tax to Rs 0.01 per unit is associated with a significant revenue loss (13.33 units), while increasing the tax tenfold to Rs 0.10 results in a further loss of only 8.33 units. This diminishing marginal revenue loss from higher pricing suggests that the most significant adjustment in farmer behavior or revenue impact occurs at the initial imposition of pricing. Subsequent price increases appear to have a proportionally smaller impact, likely reflecting that only larger, high-revenue farms remain viable at higher rates. These results suggest that the revenue impact of volumetric pricing may disproportionately affect smaller or more marginal farms at low price thresholds. In contrast, larger farms exhibit resilience at higher price levels.

Columns 4 and 5 in Table 1.8 examine how increases in water cost—both actual () and hypothetical (TaxFactor) are associated with changes in farm revenue. In Column 4, the coefficient on is 1.862***, indicating that a 1% increase in current water cost is associated with a 1.86% increase in revenue. This positive relationship likely reflects reverse causality or structural features of the system: farmers who earn more are also those who use more water and spend more on it, particularly through borewell pumping costs.
However, in Column 5, where revenue is regressed on hypothetical pricing level dummies, a clear negative pattern emerges. Moving from no tax to Rs 0.01 per unit is associated with a 13.33-unit drop in log revenue. Increasing the price to Rs 0.05 results in an additional 4-unit drop (totaling 17.32), while a further increase to Rs 0.10 leads to a total decline of 21.66 units. This suggests that increasing the tax from Rs 0 to Rs 0.01 results in a disproportionately large revenue loss, while increasing the tax tenfold from Rs 0.01 to Rs 0.10 results in a smaller additional decline (only 8.33 units).

Expressed in terms of elasticity: the first 0.01 unit tax increase results in a ~13% drop in revenue, while increasing the tax by 100% from Rs 0.05 to Rs 0.10 causes only a ~25% increase in revenue loss (from -17.32 to -21.66). This diminishing elasticity suggests that the most acute burden of pricing is felt at the initial introduction of volumetric pricing, disproportionately affecting marginal or smallholder farms.

These patterns are consistent with the idea that higher revenue farms—typically larger and more capitalized—are more resilient to price increases. The dummy variables likely reflect differences in scale and financial capacity rather than behavioral responses. Larger farms that are comfortable with discussing or absorbing higher pricing scenarios are also those that report higher revenues. The results, therefore, reflect an evident heterogeneity of impact, reinforcing that volumetric pricing would need to be designed with equity safeguards to avoid regressive effects on smaller farms.

Discussion

The regression results provide mixed evidence on the viability and design of water pricing as a regulatory tool for farmers in Punjab. Higher water costs are positively correlated with both water use and revenue, suggesting that the most productive farmers are also the highest users. Volumetric constraints do not drive this relationship, but rather the cost structure of borewell and surface water extraction.
The results from the regression indicate that even modest water taxes, such as Rs 0.01/unit, are associated with a substantial decrease in the revenue of farmers, hurting their farms and businesses.

This is particularly true among the smaller farmers. The elasticity diminishes as price increases, implying that most behavioural shifts or revenue impacts occur at lower price points. This finding suggests that if implemented, water pricing needs to be introduced cautiously and progressively, with a focus on minimizing the harm to farm owners.
All the while, the regression results show that higher-revenue farmers are more price-elastic, as they can absorb the price increase resulting from the tax. These farmers have a more inelastic demand, as they currently consume the most significant amount of water in gallons and are most likely to continue their usage under a pricing scheme. The implication is the adoption of a tiered pricing structure. Under such a system, the initial block of usage would be heavily subsidized or provided free of charge, while subsequent consumption would be subject to progressively higher taxation. This could serve as a feasible policy reform. This would maintain equity among consumers while also discouraging the over-extraction done by larger farms.

Metering is also viewed positively across income levels, as indicated by the survey responses. This positive reaction enables the Government of Punjab to pilot metering infrastructure, as it has done in urban use cases. This could be done in high-use districts where groundwater is dominant and mostly unregulated. The benefit of metering for the government is to collect data that measures water overextraction/scarcity more effectively.

All this said, pricing regulation may not be enough to solve the efficiency problems, as Pakistan has a longstanding issue with implementation. These issues include tax evasion, bureaucratic lag, and a lack of resources and funding for adoption. The problem then calls for complementary reforms. Areas such as water-saving technology (drip irrigation), campaigns, and support for crop diversification to move away from rice should be piloted and run alongside any metering or pricing regulations.

Limitations

Like any paper, this one presents limitations. The first limitation is the hypothetical bias in pricing scenarios. The paper solicited farmers’ responses to hypothetical pricing, which may have the limitation of not reflecting real behavior under actual price conditions; thus, the results should not be interpreted as causal estimates of price elasticity but can serve as indicators of farmers’ willingness to pay. Secondly, since Punjab currently lacks metering infrastructure, data for real water usage had to be inferred or, again, self-reported. This limits the precision of the regression estimates and introduces bias to the results. Furthermore, within the regression analysis itself, column 4 presents limitations. Higher water costs are positively associated with revenue, but this likely reflects reverse causality. Large farms consume more and earn more; without panel data or an exogenous variation in pricing, it is difficult to establish a clean causal relationship with these results. The sample size is relatively small and may not be perfect for making inferences. A larger sample may be feasible with a larger research team or one with access to funding.

Conclusion

To conclude, this study highlights the complexities of introducing water pricing as a regulatory instrument in Punjab’s agriculture. Whilst the results suggest that water use is productive and positively correlated with revenue, the current cost structure fails to promote water conservation. The overuse of water is the primary reason for inefficient water management and severe water insecurity in Pakistan. Water insecurity is characterized in the literature as a complete lack of water resources, where water tables are depleted too quickly and overextraction is rampant.

Hypothetical price scenarios indicate that small taxes can result in significant revenue reductions, particularly for small stakeholders, raising concerns about the regressive impact of flat volumetric taxes on water. This implies that any pricing mechanism taken must be gradual, targeted, supported by investments in metering, and progressive to be successful.

Ultimately, this study provides empirical evidence to a critical yet underexplored policy question in Pakistan and lays the groundwork for future field experiments, pilot programs, and other tests that measure real-world responses to water pricing under more controlled conditions. These future experiments could look like monitoring fundamental changes in water by installing water meters, or piloting supplemental policy reforms, such as Agri-tech reforms in Punjab.

Acknowledgements

Thank you to Trevor Dean Arnold, mentor from Cornell University, in the development of this research paper.

Appendix

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