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Thursday, May 28, 2026

A Market Failure Framework for Evaluating Public Sector Undertakings

by Arjun Krishnan.

Commentators and investors often judge companies, including state-owned firms, by their profitability. While profit is a useful metric for private firms focused on generating returns for owners, applying the same standard to state-owned enterprises is problematic. Many lament that India's Public Sector Undertakings (PSUs) incur losses, assuming that losses signal failure and profits signal success. However, this assumption misjudges the real purpose of PSUs. Although some evaluation frameworks expand beyond profit, few explicitly align performance criteria with the specific market failure that the enterprise was established to address. This article argues that assessing PSUs solely on profitability is misguided, and their success should be measured by how well they address the public purpose for which they were created.

This article proposes a two-part framework for evaluating PSUs. The first part poses an ex-ante question about purpose. A PSU is justified only when it aims to correct a market failure that less intrusive instruments cannot correct. The second part poses an ex-post question about performance. Evaluators should then judge a justified PSU on two dimensions: efficiency and effectiveness. Efficiency measures how productively an enterprise converts resources into outputs. Effectiveness captures whether the PSU actually corrects the failure it was created to address. Balance sheets cannot serve as a reliable proxy for either dimension on their own.

Ex-ante: when is a PSU justified?

The justification for any PSU must begin with market failure. When markets function well, they allocate resources efficiently, and the state has no grounds to intervene. Economists identify four situations where markets fail to do so. First, externalities arise when a cost or benefit of an economic activity falls on an unrelated third party. Positive externalities lead to underprovision, and negative externalities to overproduction. Second, public goods are non-excludable and non-rivalrous. Firms cannot easily charge users, and private markets typically underprovide them. Third, information asymmetry occurs when one party to a transaction knows more than the other, distorting decisions and reducing market efficiency. Fourth, market power arises when limited competition allows firms to raise prices or restrict output below socially optimal levels.

A market failure on its own does not justify a PSU. There are three additional tests. First, scale: how many people are affected, and by how much? A localised information asymmetry in a niche market is different from one that excludes millions from credit. Second, persistence: is the failure temporary and self-correcting, or structurally durable? Markets sometimes endogenously mitigate their own failures through competition, reputation, or contracting. Exogenous forces such as technological innovation or institutional adaptation can have the same effect. Non-state mechanisms such as industry associations, cooperatives, or third-party certifiers may emerge to address coordination problems or information asymmetries without government ownership. Even classical public-good cases have been addressed without state ownership. Coase's (1974) account of English lighthouses is a canonical illustration: what was treated in classical economics as a pure public good requiring state provision was, in fact, supplied for centuries by Trinity House, a private body that collected dues from ships at port. The presence of such adaptive mechanisms weakens the case for a PSU. By contrast, failures that persist despite opportunities for institutional adaptation present a stronger case for public intervention.

Even when a market failure is large-scale and persistent, the state has many ways to respond. The third test, then, is instrument choice: Is ownership the right way to address this failure? The state can regulate, tax, subsidise, or contract with private providers. Ownership is one of the most costly options. Ownership exposes the exchequer to operating losses, creates a vehicle vulnerable to political capture, and softens the budget constraint in ways regulation and subsidy do not. The case for ownership has weakened with experience. Publicly owned natural monopolies in many sectors turned out to deliver less output for a given level of inputs than the textbook treatment had suggested. Regulatory practice has grown more sophisticated, with sector-specific knowledge and administrative law tools that did not exist when many PSUs were created. Public-private partnerships have further narrowed the cases for state ownership, with private firms providing goods and services under contracts that set market structure, pricing, and quality. For every PSU, the central question is why the problem could not be addressed through one of these alternatives.

India operates 291 Central Public Sector Enterprises across sectors as varied as petroleum refining, power transmission, hotel management, and defence manufacturing. The policy debate about this universe has been conducted in terms of profitability. How many are loss-making? What do aggregate losses cost the exchequer? These questions are downstream of a prior one: which market failure, if any, justifies each enterprise. Those that address no market failure have no business existing and should be sold off to buyers or wound down, with assets liquidated. Those that aim to correct a market failure face a harder question: how well do they perform in addressing the failure they are expected to correct?

Ex-post: efficiency and effectiveness

Two questions emerge for judging how well a PSU is performing. The first is efficiency. Efficiency is the ability to derive the greatest possible output from a given quantity of financial, physical, and human resources. The second is effectiveness. Since a PSU is justified only for market failures, we need to evaluate whether it, in fact, corrects the failure it was created to address. A PSU can be efficient at producing what a competitive market would produce anyway, or effective at reaching its target population at three times the cost a regulated private operator would charge. Both outcomes are undesirable. In the first case, the PSU adds little social value. In the second, it imposes unnecessary costs to achieve a legitimate public objective.

Experience with direct public provision over the last half-century has weakened the case for PSUs on efficiency grounds. Publicly owned natural monopolies in many sectors exhibited poor x-efficiency, producing less output for a unit of input than private firms. The Ministry of Road Transport and Highways reports that the revenue-to-cost ratio for the 58 reporting undertakings fell to 63.6% in 2021-22, that state cabinets blocked fare revisions, and that the resulting losses reached Rs 30,192 crore in aggregate. The mobility problem the SRTUs were created to address is real, but the case for state ownership of the operator is much weaker than the case for state involvement in the sector through options like subsidies.

The regulatory and contracting alternatives to ownership have grown more capable over the same decades. The regulatory state now possesses sector-specific tariff and quality regulation, administrative law procedures for rule-making, and incentive-compatible contracting techniques (Laffont and Tirole, 1993). Public-Private Partnership (PPP) models have spread across sectors once considered the natural home of direct provision. Iossa and Martimort (2015) show that bundling construction and operation into a PPP can be efficient when build quality materially lowers operating costs. This structure is common in roads, water systems, and many public utilities. Even classical public goods, including urban streets and water supply, are now routinely constructed and operated through PPP agreements that specify quality and pricing. The Government of India's disinvestment policy lists market imperfections and public purpose as criteria for retaining a PSU in public hands. The government excludes profitability as a criterion.

For certain types of goods, state ownership may be the preferable option. When contract terms cannot specify aspects such as quality, the case for ownership over contracting strengthens (Hart, Shleifer, and Vishny, 1997). A private operator paid to deliver an output will cut costs along whatever margins the contract leaves unspecified. Where quality is one of those margins, the cost saving comes at the consumer's expense. A private prison contractor's contract may specify calorie counts and dietary variety, but regulating food quality or taste may prove impossible. These savings flow to the contractor while the welfare loss falls on inmates. Direct public ownership is preferable in such settings precisely because the public manager's weaker incentive to cut costs leaves the unspecified quality dimensions intact.

In addition to efficiency, effectiveness needs to be judged. Effectiveness measures whether the PSU is correcting the market failure it was created to address. To illustrate the difference, consider a state-owned bus operator tasked with providing transport connectivity to remote rural areas. An efficient operator minimises the resources needed to run the service. An effective operator ensures that the targeted rural communities are actually connected. A PSU may succeed on one dimension while failing on the other.

The effectiveness criteria take different forms across failure types because the welfare yardstick differs. The market power row needs some additional explanation. A monopolist with declining average costs cannot price at marginal cost without losses. Ramsey-Boiteux pricing sets the loss-minimising alternative: markups above marginal cost should rise as demand elasticity falls, placing the heaviest charges on users whose consumption is least price-sensitive. A markup on inelastic demand reduces output the least and destroys the least surplus per rupee of revenue. A political cross-subsidy structure follows a different logic, allocating markups across user groups by political weight rather than by elasticity. The effectiveness test for a PSU that disciplines market power, therefore, asks whether its markup structure approximates Ramsey-Boiteux rather than political cross-subsidy.

Table 1 sets out the effectiveness criterion for each market failure, with the less intrusive instrument serving as the comparator.

Table 1: Effectiveness criteria for PSUs by type of market failure

Market failure Market problem Role of PSU Effectiveness criterion Less intrusive instrument
Externalities (positive) Producers cannot capture the full social benefit, so the private market undersupplies relative to the social optimum. Produce at a level that accounts for spillovers private producers ignore, or finance investments whose social returns exceed appropriable private returns. Is the targeted output being delivered, and is the additional supply above the private optimum sufficient to close the externality gap? Production subsidies, tax credits, intellectual property protection, advance market commitments.
Externalities (negative) Private producers impose costs on third parties they do not bear, so the market overproduces relative to the social optimum. Produce at a level that internalises external costs private producers would otherwise externalise. Has the targeted reduction in harm been achieved, and are emissions per unit of output below the unregulated counterfactual? Pigouvian tax, tradable permits, command regulation.
Public goods Private producers cannot exclude users from a non-rivalrous good, so the market undersupplies or fails to supply. Provide the good where private cost recovery is impossible or inefficient. Is the service reaching the target population, and is coverage approaching the welfare-maximising level? Contracting with private providers under a public service obligation.
Information asymmetry (seller knows more) Private sellers hold information about quality that buyers cannot observe, so low-quality goods crowd out high-quality ones. Enter the market and disclose costs, quality, and pricing as a benchmark that private sellers would otherwise suppress. Has the PSU's presence made quality observable to buyers and sustained transactions that would otherwise have unravelled? Mandatory disclosure regulation, third-party certification, independent benchmarking authority.
Information asymmetry (buyer knows more) Buyers hold private information about themselves that sellers cannot verify. Sellers respond by raising prices, rationing, or withdrawing supply. Offer service to groups private firms avoid because they cannot distinguish high-risk from low-risk customers. Is the PSU enrolling the high-risk groups private markets exclude, and is the share of high-risk individuals covered higher than under the private counterfactual? Risk-pooling mandates, mandatory insurance schemes.
Market power Private firms price above competitive levels or restrict output below the social optimum. Compete to discipline private pricing. In a natural-monopoly case, price at the welfare-optimal level. Is the PSU pricing closer to marginal cost than an unregulated monopolist would, and does the markup structure approximate Ramsey-Boiteux rather than political cross-subsidy? Competition law and antitrust enforcement, sectoral price regulation, separation of monopoly network from competitive services.

A PSU can fail on either dimension or both, and each case calls for a different response. A state-owned bus operator that abandons remote routes for crowded urban corridors is efficiently delivering something the market can deliver. Efficient delivery of a service that the market would have provided is no justification for state ownership. A PSU that effectively corrects a market failure but does so at an unjustified cost may generate more welfare loss through waste than welfare gain from correcting the failure. Reform or contracting out may be the appropriate response.

Soft budget constraints

PSUs operate under what Kornai (1998) called a soft budget constraint. A private firm that runs at a persistent loss is likely to go bankrupt. A PSU does not, because the PSU expects the state to cover the shortfall. The expectation of rescue weakens the discipline that revenues and costs would otherwise impose on managers.

A PSU pursuing a legitimate mandate should not show sustained accounting losses on its own books. Where pricing reflects deliberate policy, including selling output below cost for welfare reasons, the resulting deficit is a transfer from the treasury to the consumer. The right place for that transfer is the government's expenditure account, recorded as an explicit subsidy and matched by income on the PSU's accounts. Accounting separation keeps the cost of social policy visible in the budget, where parliamentarians can scrutinise it, rather than in an enterprise's operating accounts.

The Food Corporation of India illustrates what happens when this discipline breaks down. The Corporation procures grain at minimum support prices set by the Cabinet, stores it, and supplies it to ration shops at prices well below procurement cost. The shortfall is intended to be transferred to FCI as a food subsidy from the union budget. However, for long stretches, the government did not transfer the full subsidy in time, and FCI raised debt, much of it from the National Small Savings Fund, to bridge the gap. This practice was especially prevalent between 2016 and 2021. The losses that appeared on FCI's books reflected the failure to transfer the subsidy on time. The government used FCI's balance sheet to delay recognition of expenditure that should have appeared in the budget.

The existence of PSUs can then soften budget constraints in two ways. First, if a PSU knows it can rely on transfers from the treasury to cover any shortfall, its managers have less incentive to contain costs than managers of a private firm would. As a result, the PSU's budget constraint is softened. Second, PSUs like FCI soften the budget constraint of the government that created them. Since the enterprise absorbs costs that should have appeared in the budget, the state's social spending is understated. Once this practice exists, the headline profit or loss of a PSU carries less information. A loss-making PSU may be one that delivered the mandate but did not receive the subsidy. A loss-making PSU may also be wasteful. Which case applies cannot be understood based on the profit and loss account. Persistent losses on a PSU's books are therefore a useful diagnostic. They suggest either operational inefficiency or off-budget accounting through the PSU's balance sheet.

The framework, so far, treats PSUs as faithfully pursuing their mandates. They often do not. Even an enterprise with a legitimate market failure justification is run by people with their own interests. Governments are themselves made up of self-interested actors, and political objectives can capture an enterprise created to address a market failure. These government failures show up in the performance criteria above: prices far from welfare-optimal levels, investments that do not deliver the promised social benefits, or operations that consume more inputs than the next-best instrument would have required.

Government failure also shapes how the state manages exit from enterprises that have outlived their justification. A framework that identifies when a PSU has no reason to exist is useful only if exit decisions follow honestly from that assessment. Chakrabarty (2023, page 9) finds that around 43% of India's disinvestment proceeds between 1991 and 2022 involved no actual transfer to private hands. Shares were transferred between public entities, and the proceeds were counted towards the disinvestment target without any change in underlying ownership. Even where the case for a PSU has lapsed, political incentives corrupt the exit process and sustain enterprises that should not exist.

Applying the framework

Consider three applications of the framework. First, the electricity transmission network exhibits natural-monopoly characteristics, with high fixed costs and declining average costs over the relevant output range. State intervention to address market power is justified ex-ante, whether through regulated private ownership or direct public ownership of the grid operator. Power Grid Corporation of India is a PSU that runs the inter-state grid. From the standpoint of allocative efficiency, tariffs should be set close to marginal cost. Because the marginal cost of transmission is below the long-run average cost, such pricing would generate a structural revenue deficit. A deficit of this kind would not necessarily signal operational inefficiency. It can reflect a deliberate tariff policy that expands access and maximises network use, and it would be justified where it represents the least-cost route to the social objective when compared with direct transfers or alternative subsidy mechanisms. India does not price transmission at marginal cost. Tariffs are set under the CERC Tariff Regulations, 2024, which use a cost-plus framework. For new transmission projects, Regulation 30(3) provides a base return on equity of 15%, along with recovery of interest costs, depreciation, interest on working capital, and operating and maintenance expenses. The PSU's operational record is strong: the transmission system was available 99.85% of the time in FY24 across 1,77,699 circuit kilometres carrying around half of India's inter-state electricity. Whether the cross-subsidy implicit in cost-plus regulation is the least-cost route to network expansion, or whether a direct transfer would deliver the same access at lower fiscal cost, is a question worth asking. Power Grid no longer builds new lines by default. The regulator auctions each new project to the lowest bidder, and Power Grid competes for these contracts alongside Adani, Sterlite and Tata Power. Private bidders win a growing share. Whether the legacy network would also be cheaper in private hands is a separate question. The framework's verdict on Power Grid therefore turns on an empirical question: whether the cost-plus regulation of the legacy network delivers cheaper transmission than competitive procurement would.

Second, the India Tourism Development Corporation (ITDC) runs the Ashok Group of Hotels. ITDC was established in 1966 to develop tourist infrastructure, including hotels. The Taj, Oberoi, ITC, Lemon Tree and Marriott chains, among others, operate across the segments and price points ITDC serves. Hotels are not a public good. Private operators can charge customers, competition is adequate, and there are no externalities, information failure, or market power problems that require the state to own a hotel chain. The market failure test fails at the first step, so no ex-post analysis is needed.

A third example concerns the post-independence wave of public investment in heavy industry and infrastructure. The standard defence of state ownership in this period rested on the absence of capital markets: long-term finance was scarce, and only the state could mobilise it. Bhagwati and Desai (1970) contested this claim, arguing that private capital existed and that the licensing regime was producing the shortages it purported to remedy. Whatever the merits of the original argument, India's capital markets have since deepened. A second defence rests on positive externalities through learning effects and supply-chain spillovers, where social returns exceed what a private investor can appropriate. Underinvestment results from this appropriability gap, even when capital is available. The defence still has limits. Where production subsidies, intellectual property protection, or advance market commitments can close the gap, ownership is the costlier instrument. A surviving PSU founded on these grounds must show that such alternatives remain inadequate.

India's early integrated steel plants at Rourkela, Bhilai, Durgapur, and Bokaro are concrete cases. The plants were justified on grounds that private firms could not raise the long-term capital required, and that they would generate large downstream spillovers through skilled labour, supplier networks, and engineering capabilities whose full social value private investors could not capture. The appropriability gap was real, and thin capital markets compounded the problem by raising the cost of private investment. Both conditions have since changed. India's capital markets have deepened, project finance has matured, and Tata Steel and JSW Steel have built modern integrated capacity at scale. The spillovers that public investment was meant to generate now flow through the private steel industry instead. SAIL, the operator of the original plants, produces around 15% of Indian steel and is profitable. Profitability does not save it from the framework's test. Where private operators produce the same steels at a comparable scale, the market failure has been resolved, and continued public ownership no longer has a justification.

The way forward

Profit is the wrong measure for judging a PSU. It speaks neither to whether the enterprise should exist nor to whether it is doing what it exists to do. For each of India's 291 central PSUs and more than a thousand at the state level, the question is whether a market failure persists, whether ownership is the cheapest way to address it, and whether the enterprise actually does so. Some profitable PSUs would fail this test. Some loss-making ones would pass.

References

India: Planning for Industrialization: Industrialization and Trade Policies Since 1951 by Bhagwati J and Desai P, 1970, Oxford University Press for OECD Development Centre.

On the Management of Public Monopolies Subject to Budgetary Constraints by Boiteux M, 1971, Journal of Economic Theory, 3(3), 219 to 240.

The Lighthouse in Economics by Coase R H, 1974, Journal of Law and Economics, 17(2), 357 to 376.

The Proper Scope of Government: Theory and an Application to Prisons by Hart O, Shleifer A and Vishny R W, 1997, Quarterly Journal of Economics, 112(4), 1127 to 1161.

The Simple Microeconomics of Public-Private Partnerships by Iossa E and Martimort D, 2015, Journal of Public Economic Theory, 17(1), 4 to 48.

In Service of the Republic: The Art and Science of Economic Policy by Kelkar V and Shah A, 2019, Penguin Allen Lane.

The Place of the Soft Budget Constraint Syndrome in Economic Theory by Kornai J, 1998, Journal of Comparative Economics, 26(1), 11 to 17.

A Theory of Incentives in Procurement and Regulation by Laffont J-J and Tirole J, 1993, MIT Press.

Allocative Efficiency vs. "X-Efficiency" by Leibenstein H, 1966, American Economic Review, 56(3), 392 to 415.

State versus Private Ownership by Shleifer A, 1998, Journal of Economic Perspectives, 12(4), 133 to 150.


Arjun Krishnan is a consultant at the Centre for Civil Society, a Delhi-based think tank. He thanks Sourya Banerjee for the early conversations that inspired this article, Jayana Bedi for her thoughtful feedback during its drafting, and an anonymous referee whose comments considerably sharpened the argument.

Tuesday, May 19, 2026

Words and deeds in the Indian exchange rate

by Rajeswari Sengupta and Ajay Shah.

The most important price in any economy is the exchange rate. In India's case, this is the price of the Indian rupee against the US dollar. By default, the exchange rate is controlled by market forces. The policy stance of the government, towards the exchange rate, is termed 'the exchange rate regime'. This is one of the most consequential economic policy choices.

In most advanced economies, the answer is straightforward: the exchange rate is set by financial markets, and the government stays out. In India, it is more complicated. The RBI regularly intervenes in the foreign exchange market. India's exchange rate regime needs to be deciphered from the data using statistical tools.

At any point in time, to understand the Indian economy, knowing the present exchange rate regime is central. Looking back at economic history, knowing the dates and characteristics of the changing exchange rate regime is central.

Inferring the true exchange rate regime from the data

We now have mature tools for deciphering the exchange rate regime using exchange rate data, without requiring information about the actions taken by the government. This runs in two steps: the first is a sweet linear regression called 'the exchange rate regression' and the second is the econometrics of structural change through which structural breaks in the regression coefficients and the residual standard deviation are detected. This idea for structural breaks in linear regression models where the residual standard deviation can also change is taken from Zeileis, Shah and Patnaik (2010) and implemented in the R package fxregime which now has numerous applications into fields well beyond exchange rate regimes and structural change.

In this article we will first rev up this tool chain for the Indian rupee, offering measures of the present exchange rate regime and of the history of Indian macroeconomic policy. We will then turn to a comparison against RBI and IMF statements about the Indian exchange rate regime. Finally, we will offer ready access to reproducible research so that everyone can perform these calculations.

Reading the data: six distinct regimes since 2000

The exchange rate regression estimates how much of the movement in the rupee is explained by movements in the world's major floating currencies - the US dollar, the euro, the British pound, and the Japanese yen. The greater the role of these foreign currencies in explaining the rupee's movement, the less independently the rupee is floating. Alongside this, we get the residual standard deviation: the extent to which the movements of the rupee reflect none of the above. The dates of structural breaks mark the boundaries between different exchange rate regimes.

We apply this method to weekly exchange rate data from the BIS, covering the period from 1 January, 2000 to the most recent data available at the time of publication (15 May, 2026). The analysis shows six distinct exchange rate regimes. This gives us an updated version of the knowledge in Patnaik and Sengupta (2022) and Pandey, Patnaik and Sengupta (2024).

Figure 1: USD/INR exchange rate with structural breaks.

Figure 2: Annualised volatility of USD/INR (6 month rolling window) with structural breaks.

The six periods are as follows:

Regime 1 (14 January 2000 - 19 March 2004): This was a tight peg to the dollar. The rupee moved very little independently. The annualised INR-USD volatility averaged just 2.2%.

Regime 2 (26 March 2004 - 16 March 2007): This was a move towards greater flexibility. The rupee was moderately pegged to a basket of currencies. The volatility rose to 4.1%.

Regime 3 (23 March 2007 - 13 December 2013): This was the most flexible period in the 25 years under examination. This was the era when India came closest to a genuinely market-determined exchange rate. The USD/INR volatility was 8.7%. There were many months in this period where RBI trading on the currency market was 0. This gives us an interesting conjecture: If the rupee were to float, it would have an annualised vol of about 9%.

Regime 4 (20 December 2013 - 25 August 2023): This was a retreat to greater currency management. This was the longest single regime in our sample - nearly a decade. The INR-USD volatility fell back to 5%, and the RBI's interventions in the foreign exchange market grew steadily. It is ironic that inflation targeting came into India in February 2015, with the signing of the Monetary Policy Framework Agreement. This was roughly the same time that rupee flexibility was in retreat.

Regime 5 (1 September 2023 - 20 December 2024): A remarkable de-facto peg; the lowest volatility in 25 years. For this 15-month period, INR-USD volatility was just 1.5%: the lowest in our 25-year sample, lower even than Regime 1 which reflected the macroeconomics knowledge of long ago. The rupee barely moved against the dollar, even as other emerging market currencies fluctuated.

Regime 6 (27 December 2024 - 15 May 2026): Finally, we got a partial retreat from the peg. Volatility rose to 5%, comparable to Regime 4. In our analysis, this regime ends on 15 May 2026, because that is the latest available data.

What the RBI says

In 1993, India officially moved towards a "market-determined exchange rate". The RBI website states that its "exchange rate policy focuses on ensuring orderly conditions in the foreign exchange market" - implying that it intervenes only to prevent excessive volatility, not to target any particular level of the rupee.

The empirical evidence, however, shows that the Indian economy experienced six different exchange rate regimes without any changes in official statements, announcements, or rationale.

What the IMF says

The International Monetary Fund, which classifies every member country's exchange rate regime every year, had long described India's regime as "floating", noting that the rupee is "largely market determined" and that the RBI intervenes only to manage "excessive volatility". The IMF classification does not see the six regimes that the data reports.

Figure 3: USD/INR exchange rate with regime classification from IMF AREAER.

The econometrics of structural change shows the recent nearly-fixed exchange rate regime as running from 1 September 2023 - 20 December 2024. This event was so large and remarkable that the IMF picked it up. In its 2023 Annual Report on Exchange Arrangements and Exchange Restrictions (released in December 2024), the IMF reclassified India's de-facto exchange rate regime retroactively:

"Since December 2022, the exchange rate stabilized within a 2% band against the US dollar, with one realignment in August 2023. Therefore, the de facto exchange rate arrangement was reclassified retroactively to 'stabilized' from 'floating', effective December 6, 2022."

The structural change econometrics picks up different dates compared with these statements. The statistical techniques isolate precise dates for structural breaks down to the week, in contrast to the IMF classification, which is updated annually.

The centrality of the exchange rate regime in the Impossible Trinity

The Impossible Trinity is a foundational concept in economics. It states that a country can achieve at most two of the following three objectives simultaneously: an open capital account (allowing money to flow freely in and out of the country), a fixed or managed exchange rate, and an independent monetary policy. It is impossible to have all three at once.

India adopted inflation targeting in February 2015, which means it chose to have autonomy in domestic monetary policy with the legal mandate to keep CPI inflation at 4%. India also has a substantially open capital account after three decades of gradual liberalisation. According to the Trilemma, these two choices leave no room for a managed exchange rate. India cannot simultaneously target 4% inflation, maintain an open capital account, and stabilise the rupee against the dollar.

Yet the data show that from late 2022 to late 2024, that is what the RBI attempted to do. In this period, India's nominal anchor - what the monetary system was supposed to be anchored to - quietly shifted from the inflation target to the exchange rate. In effect, RBI's legal mandate under IT was temporarily displaced by an unannounced exchange rate objective. These attempts induce many difficulties; financial restrictions impeded economic growth, and inflation was excessively volatile owing to the pursuit of extraneous objectives.

Macroeconomic stability requires credibility of monetary policy. Under inflation targeting, the authorities must say what they will do, and then do what they just said. Even if all the right things are done immediately, it would take decades for private persons to learn to trust that there is a stable framework of macroeconomic policy.

It is easy to do these calculations

We have made this analysis a self-contained Google Colab notebook, which can be used by you to do runs or classroom teaching.

References

Radhika Pandey, Ila Patnaik and Rajeswari Sengupta (2024) "The journey of inflation targeting in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2024-022, Indira Gandhi Institute of Development Research, Mumbai, India.

Patnaik, Ila and Rajeswari Sengupta (2022) "Analyzing India's Exchange Rate Regime," India Policy Forum, National Council of Applied Economic Research, vol. 18(1), pages 53-85.

Zeileis, Achim, Ajay Shah and Ila Patnaik (2010) "Testing, monitoring, and dating structural changes in exchange rate regimes", Computational Statistics & Data Analysis, Volume 54, Issue 6.


The authors are researchers at IGIDR, Bombay and XKDR Forum, Bombay, respectively. The authors thank Rounak Hande for excellent research assistance with the data and analysis, and Anjali Sharma for valuable discussions and comments.

Monday, May 11, 2026

Market Reaction to Insider Trading: Evidence from Regulatory Orders in India

by Arjun Gupta, Sonam Patel, and Renuka Sane.

Introduction

Market integrity depends on effective enforcement against market abuse. When regulators credibly sanction violations, they reinforce investor confidence and reduce the risk premiums that markets impose for uncertain governance. In developed markets, evidence suggests that enforcement achieves this objective: SEC enforcement actions in the United States produce abnormal stock price declines of $-0.5\%$ (Persons, 1997), and UK sanctions trigger reputational losses that far exceed the direct penalties (Armour et al., 2017). This is especially true for insider trading enforcement: Persons (1997) documents significant negative abnormal returns following the SEC's announcements of insider trading enforcement actions. (Engelen, 2012) finds that a clear negative abnormal return on the day of even newspaper coverage of the illegal insider trading practice of CEOs.

An open question, however, is whether this pattern extends to India. We investigate this by examining stock price movements around two types of insider trading enforcement actions in India: final SEBI adjudicatory orders and appellate decisions by the Securities Appellate Tribunal (SAT). We focus on insider trading orders as they can be a signal about the quality of the firm's internal governance. If insiders are trading on privileged information, it suggests that boards, compliance functions, and internal controls are weak, leading to investors discounting the stock accordingly. Further, when the firm and its executives face potential penalties, disgorgement, or other sanctions, these can impose direct costs on the firm and may affect its ability to attract capital and talent. The insider trading laws in India are quite expansive, and cover not only connected persons, but also those who just have access to unpublished price sensitive information, or if there have been some minor disclosure violations. All orders, therefore, may not signal governance issues within a firm. We therefore also look at orders by violation severity and type of insider relationship.

Empirical Strategy

We use an event-study methodology to test whether Indian stock markets react to SEBI enforcement actions and outcomes challenged before SAT. We compile a list of individuals and entities against whom an insider-trading order was issued, then identify the companies whose scrip was alleged to have been insider traded, map them to their corresponding order dates (event dates), and use these firm-event pairs to check for market reaction.

Estimation Procedure

We estimate each firm's normal return using the market model over an estimation window of 210 trading days ending 11 days before the event ($t = -210$ to $t = -11$):

\( R_{it} = \alpha_i + \beta_i R_{mt} + \varepsilon_{it} \)

where $R_{it}$ is the daily return of stock $i$ on day $t$ and $R_{mt}$ is the daily return on the Nifty~50 Index. The Abnormal Return (AR) on event day $t$ is the difference between the actual return and the predicted normal return:

\( AR_{it} = R_{it} - \left(\hat{\alpha}_i + \hat{\beta}_i R_{mt}\right) \)

Cumulative Abnormal Returns (CARs) are computed by summing $AR_{it}$ over a 21-day event window centred on the insider trading announcement date:

\( CAR_i = \sum_{t=-10}^{+10} AR_{it} \)

We test whether the cross-sectional average $\overline{CAR}$ is statistically different from zero using a $t$-test; a negative $\overline{CAR}$ indicates an adverse market reaction to the announcement.

Data and Sample

Our sample is drawn from the data set used by Aggarwal et al., (2025). It comprises two types of regulatory actions from 2009 to 2023, restricted to firms listed on the National Stock Exchange (NSE). After removing duplicates and cases with missing stock price data, our final sample contains:

  1. SEBI Orders: Final adjudicatory orders; $N = 176$ firm-event pairs.
  2. SAT Orders: Appellate Tribunal decisions; $N = 42$ firm-event pairs.

We further look for heterogeneity in market reactions by partitioning the sample along four dimensions of interest:

  • Sanction status: Sanctioned ($N = 119$) vs. not sanctioned ($N = 57$). An order may or may not result in a sanction. Here, we examine a reaction based on whether an order resulted in a sanction.

  • Violation severity: Major violations ($N = 74$) vs. minor violations ($N = 122$). We classify insider trading violations as Major (e.g., sharing or using unpublished price information for trading) or Minor (e.g., code-of-conduct breaches, delayed disclosures).

  • Insider relationship: Connected persons ($N = 44$), deemed connected ($N = 21$), and those with access to UPSI ($N = 19$). Connected persons are loosely defined as those associated with a company (contractual, fiduciary, or employment), while those deemed to be connected persons include their relatives or cohabitants. UPSI access refers to knowledge of information materially impacting the stock price.

  • Monetary outflow: Above-median ($N = 59$) vs. at-or-below-median ($N = 60$) alleged illegal gains. Monetary outflow is the total penalty and disgorgement paid to SEBI. We analyze market reaction based on the magnitude of this outflow to see if the amount paid affects the reaction.

Results

Baseline Event-Study Findings

Our event-study results indicate that Indian stock markets exhibit no statistically significant reaction to any type of insider trading enforcement announcement. CARs are indistinguishable from zero across all two regulatory action types at the 95% confidence level, with point estimates close to zero in magnitude. For comparison, SEC insider trading enforcement actions in the US produce average CARs of $-3.47\%$ (Muradoglu and Clark Huskey, 2008).

Figures display the CAR trajectories. In all two cases, the CARs fluctuate around zero with no discernible trend before, during, or after the announcement date.

Cumulative Abnormal Returns (CARs) around SEBI final order announcements ($N = 176$). The shaded region represents the 95% confidence interval.

The result for SEBI final orders is striking: these orders contain explicit findings of misconduct and penalties, yet markets do not react. We discuss four candidate explanations below: high appeal and reversal rates, long enforcement delays, low penalty amounts, and pre-existing credibility discount.

Cumulative Abnormal Returns (CARs) around SAT order announcements ($N = 42$). The shaded region represents the 95% confidence interval.

SAT orders, on the other hand, are more final in nature. They may affirm, modify, or overturn SEBI sanctions, and should lead to a market reaction. In our dataset, they also produce no detectable market reaction. However, this result should be interpreted with caution, given the small sample size. With only 42 events, our test has limited statistical power to detect abnormal returns. It is possible that these may be further appealed at the Supreme Court, but given the small sample size, we do not test for the impact of those decisions.

Subsample Analysis

We examine whether the aggregate result masks heterogeneous effects by partitioning the sample along the four dimensions described above. Across all subsample splits, CARs remain statistically and economically insignificant. Even for high-severity cases, directors trading on confidential information, monetary outflows above the median of Rs.~12.83 lakh, and third quartile of Rs.~5.27 crore, abnormal returns remain proximate to zero. Also, there is no evidence of a significant market reaction even in the subsample of cases where the insider relationship is more direct (connected persons). This suggests the null result is not an artefact of averaging across heterogeneous effects; rather, it is pervasive across subgroups.

One caveat to our analysis is if the true information release occurred earlier (e.g., via media leaks), our tests measure the reaction to information from informal sources rather than to the announcement itself.

Interpreting the results

One interpretation of this result is that markets may rationally discount the significance of SEBI enforcement actions. Several institutional features of Indian capital markets lend support to this interpretation:

  1. High appeal and reversal rates: Aggarwal et al., (2025) find that a substantial fraction of SEBI orders (30-41%) are appealed to SAT, and around 50% result in modifications or reversals. Investors who have learned that sanctions are frequently overturned will rationally discount any announced penalty. This is probably compounded by the fact that several SEBI orders are not able to demonstrate the unfair gains or loss avoided, or provide reasons for imposing sanctions as debarment, reducing the credibility of its enforcement actions (Aggarwal et al., 2024).
  2. Long enforcement delays: Damle and Zaveri (2022) find a median of over three years between violation and SCN, and a further 18 months to a final order. This is reinforced by the findings of Aggarwal et al., (2025), who find similar timelines for insider trading orders. By the time enforcement is announced, investors may have already moved on.
  3. Low penalty amounts: The median penalty is Rs 12.83 lakhs, with approximately 40 cases involving amounts under Rs 10 lakhs. Such low penalties suggest a lower perceived severity of the offense, and consequently signal the market to treat this news as immaterial.
  4. Pre-existing credibility discount: If years of weak or delayed sanctions have already led investors to assign a low probability to effective enforcement, individual announcements convey little new information, and markets have stopped paying attention.

Another possibility is that markets receive the enforcement information but do not regard insider trading as material to firm valuation. Under this view, it reflects an investor judgment that insider trading by management is not indicative of broader governance failure or future cash-flow risk.

Conclusion

Indian stock markets exhibit no statistically significant response to insider trading enforcement, in contrast to the negative abnormal returns documented in the US and UK. This result is robust across SEBI final orders and SAT appellate decisions, and persists even for high-severity violations involving senior insiders and large monetary outflows.

The functioning of SEBI entails considerable public expenditure, and the Board has, over time, sought progressively wider powers - including expanded surveillance capabilities. Given this, the question of what is actually being achieved warrants serious scrutiny. A stock price reaction to an enforcement order is one observable signal of whether the market believes the enforcement actions carry some significance. A null result across many orders suggests the market does not view these actions as conveying meaningful new information. It is, therefore, worth questioning if enforcement actions are advancing the goal that justified the expenditure in the first place.


The authors are researchers at Trustbridge Rule of Law Foundation.

Wednesday, April 15, 2026

Announcements

Call for papers: Alt Data Workshop 2026

Date: 21st & 22nd August 2026

Organisers: Chennai Mathematical Institute and XKDR Forum
Venue: XKDR Forum, Mumbai, India

Mode: In-Person

Overview

The Alt Data Workshop 2026 focuses on the use of "alternative data" -- the remarkable world of novel and clever data sources bubbling up outside the traditional official statistical machinery.

We seek to bridge the gap between STEM researchers (Computer Science, Statistics, Engineering) and domain experts in Economics, Public Policy, and Law. We will de-prioritise data from one-off field experiments and emphasise the use of widely available datasets that are predictably updated through time thus permitting long-term longitudinal research and the development of a research community surrounding each dataset. Examples of this include satellite imagery, digital footprints, high-frequency transaction data, and large-scale web-scraping to solve complex problems in the Indian context. Some examples are at https://www.xkdr.org/field/statistics-computer-science

The Scope of Alternative Data

For the purposes of this workshop, alternative data refers to non-traditional datasets that are, in principle, accessible to the broader research community on a sustained basis over the years, through which a literature can emerge on one dataset at a time.

We prioritise papers that address:

  • Methodological Rigor: Novel approaches to ground-truthing, signal extraction from noisy data, and bias correction.

  • Scalability: Techniques that can be applied across regions or time periods rather than isolated case studies.

  • Substantive Applications: Practical use in agricultural monitoring, urban heat stress, fiscal analytics, or market microstructure.

Themes and Topics

We welcome submissions from STEM and social science researchers on topics including, but not limited to:

  • Remote Sensing: Applications of satellite imagery for economic activity or environmental monitoring.

  • Digital Footprints: Analysis of transaction, payment, or transport data.

  • Automated Data Collection: Large-scale web scraping and crowdsourcing frameworks.

  • High-Frequency Proxies: Using alternative indicators to track fiscal or macroeconomic variables in real-time.

  • Computational Infrastructure: Engineering challenges in processing and storing large-scale alternative datasets for public policy.

Submission Guidelines

We invite both formal academic papers and industry-led technical talks.

  • Abstracts: Maximum 500 words. Must clearly state the research question, data sources, methodology, and results.

  • Full Papers: Maximum 10,000 words.

  • Format: Submissions should be in PDF. Include a separate cover page with author names, affiliations, and contact details.

  • Submission Portal: Submission Form

Review Process

Submissions will be reviewed for originality, technical rigor, and relevance. We value work that is reproducible and contributes to the public discourse on data-driven governance.

Review Committee

Travel Funding

We will fund authors and discussants to stay in Mumbai for two nights.

Important Dates

  • Submission Deadline: 15 May 2026

  • Notification of Acceptance: 15 June 2026

  • Full Paper/Presentation Submission: 31 July 2026

  • Workshop Date: 21 August 2026

Contact

Email: outreach@xkdr.org

Web: https://www.xkdr.org/event/alt-data-workshop-2026

Tuesday, April 14, 2026

Announcements

Call for Papers: Cross-Border Flows and Frictions in India

Dates: 03-05 July, 2026
Venue: Goa, India
Mode: In-person

Overview

XKDR Forum invite submissions for its upcoming conference on â€Å“Cross-Border Flows and Frictions in India” The conference aims to bring together academics, market participants, legal experts and policymakers to examine the empirical, institutional, and legal foundations shaping the case for a more open and resilient capital account in India. It proceeds from the view that cross-border flows are central to India’s financial development. The conference will feature original research papers, thematic talks, and panel discussions.

Submissions are encouraged that advance theoretical, empirical, legal, or policy-oriented debates on the nature, sources, and consequences of cross-border frictions. Interdisciplinary approaches and comparative perspectives are particularly welcome.

Themes and Topics

The conference will focus on, but is not limited to, the following themes:

  • International Capital & Investment: Capital flows, home bias, push/pull factors; EM flow maladies; capital controls; corporate finance, and internationalisation of high-productivity firms, cross-border payments.
  • Exchange Rates & Currency Markets: Currency markets, risk, and institutions; exchange rate regimes; costs and benefits of managed rates.
  • Financial Stability & Crisis: Contagion from international crises; the impossible trinity; conventional Indian crisis management; systemic risk under open capital accounts.
  • Regulation, Compliance & Governance: Laws, rule of law, and public administration for capital controls; tax policy and administration; CFT/PMLA/FATF.

Submissions beyond these themes that align with the overall scope of the conference will also be considered.

Submission Guidelines - Only Abstract Essential

  • Abstract:
    • 300 - 500 words
    • Should clearly state the research question, methodology, and expected key findings/arguments.
  • Full Paper (if available):
    • No word limit.
  • Submission Portal:

Review Process

All submissions will undergo a review by the program committee of the conference. Selection will be based on originality, rigor, and relevance to the conference themes.

Program Committee

  • Shubho Roy, Shiv Nadar University
  • Renuka Sane, TrustBridge
  • Rajeswari Sengupta, IGIDR
  • Manish Singh, IIT Roorkee
  • Ajay Shah, XKDR Forum
  • Susan Thomas, XKDR Forum
  • Harsh Vardhan, Independent
  • Bhargavi Zaveri-Shah, The Professeer

Funding

Paper presenters and discussants will be provided with travel support.

Important Dates

  • Abstract submission deadline: 15 May, 2026
  • Notification of acceptance: 31 May, 2026
  • Full paper & presentation slides submission: 15 June, 2026
  • Conference dates: 3-5 July, 2026

Contact

For queries, please contact:
E-mail: outreach@xkdr.org
Web: xkdr.org

Monday, April 13, 2026

Announcements

Call for Papers: 17th Emerging Markets Conference

13th - 16th December, 2026

XKDR Forum in collaboration with Vanderbilt law School is inviting papers to be submitted for the 17th Emerging Markets Conference, 2026. In the past, the audience for these events has comprised of academics, participants from the legal and financial industry, policy makers from government and regulators.

Details of the previous conferences can be viewed at https://emergingmarketsconference.org/. The conference aims to cover presentations and discussions across the following set of research topics:

  • The sources of economic success or failure in EMs.
  • Finance in EMs (households, financial markets, financial intermediaries, firms and finance, finance and growth).
  • Political economy, law, public administration, regulation in EMs.
  • The impact of populism upon the possibility of sustained growth.
  • Insights into large EMs that matter in and of themselves.
  • Insights from narrow research projects that illuminate EMs in general.
  • The new phase of globalisation and its consequences for international trade, international finance and the nature of the EM firm.
  • Features of a society that enable or disable convergence into the 'normal' package of high levels of freedom and prosperity.
  • The puzzles faced by all kinds of decision makers: individuals, civil society actors, firms, all levels of government.
  • Grand challenges such as climate change: implications for EMs and ramifications of choices made in EMs.
  • State capability in EMs.
  • The interplay of military affairs, foreign policy and economics for EMs.

The ideal papers for EMC shed light on the great questions of the age, while being analytically sound and persuasive.

Conference design

For EMC 2026, we intend to bring on board a wider research papers, panels on contemporary policy and keynotes by experts in the area of finance, economics and law. The conference this year will be completely in - person mode.

Best Discussant Award

Each year, we award the Emerging Markets Conference discussant award for the best discussant and the first runner up discussant of the papers presented on each day of the EMC. The discussants are selected by an audience poll.

Program Committee

  • Adam Feibelman, Tulane University
  • Ajay Shah, XKDR Forum
  • Bidisha Chakraborty, Saint Louis University
  • Dan J Awrey, Cornell Law School
  • Harsh Vardhan, Independent
  • Indradeep Ghosh, Dvara Research
  • Joshua Felman, J. H. Consulting
  • Kose John, NYU Stern
  • Kumar Venkataraman, SMU – Cox School of Business
  • Marios Panayides, The University of Oklahoma
  • N. Prabhala, Johns Hopkins University
  • Pab Jotikasthira, SMU - Edwin L Cox School of Business
  • Pradeep Yadav, The University of Oklahoma
  • Rambhadran Thirumalai, ISB
  • Rajeswari Sengupta, IGIDR
  • Renuka Sane, TrustBridge
  • Sanjay Kallapur, ISB
  • Susan Thomas, XKDR Forum
  • Tanika Chakraborty, IIM Calcutta
  • Vimal Balasubramaniam, Queen Mary University of London
  • Yesha Yadav, Vanderbilt University

Important dates

  • Paper submission deadline: 24th August 2026.
  • Expected date for notification of acceptance: 30th September 2026.
  • Dates of the conference: 13th - 16th December 2026.

Support

Academic authors whose papers have been accepted for the conference will be provided accommodation at the conference venue for three nights (13th to 16th December).

Registration and contact details

Submissions: Please submit your papers in pdf format by following this link here
For any clarifications, please reach out to Jyoti at announcements@emergingmarketsconference.org