How political connections shield firms during an economic crisis

Editor’s note: For a broader synthesis of themes covered in this article, check out our VoxDevLit on Bureaucracy.

Political connections have long been known to shape firm behaviour and performance. From emerging markets to advanced economies, politically connected firms operate across a wide range of institutional and political contexts, making the intersection of business and politics a topic of continued interest for both research and policy.

A substantial body of evidence has explored the potential benefits and costs of these connections (Acemoglu et al. 2016, Faccio et al. 2006, Fisman 2001, Heitz et al. 2021, Khwaja and Mian 2005, Sapienza 2004, Xu 2023). For example, political connections provide firms with easier access to credit, regulatory advantages, or preferential treatment in public procurement. However, such connections also lead to political rent-seeking, inefficient allocation of resources, or greater exposure to political risk.

Despite this, little is known about how such connections impact firm behaviour during a macroeconomic crisis–when financial resources become scarce, institutional pressures rise, and firms face more operational risk. Do firms use political ties to access scarce inputs? Or, do those connections become liabilities in volatile environments, putting them at regulatory and rent-seeking risks? Even less is understood about the specific mechanisms at play.

Studying these questions is particularly important in light of recent global downturns such as the COVID-19 pandemic and the ongoing global macroeconomic uncertainty. In recent work (Chen et al. 2025), we explore these questions using India’s 2016 demonetisation episode—a sudden and severe macroeconomic liquidity shock—as a natural experiment. We combine detailed firm-level financial data with a novel, machine learning-based measure of political connections to examine how connected firms responded to the crisis and whether these responses translated into longer-term performance gains.

Using machine learning to measure firms’ political connections

Political connections are difficult to measure. Existing studies often rely on coarse proxies such as name-matching between firm directors and politicians, or assume connections based on shared caste or other social identity. We instead construct a novel, more precise measure that combines over five million news articles from seven leading Indian newspapers, with structured data on politicians, bureaucrats, and firm directors from official sources. 

Using a machine-learning algorithm, we identify connections not only based on ‘name matches’, but also via ‘context matches’, allowing us to detect connections through direct mentions, familial ties, professional affiliations, and social networks—such as shared appearances, meetings, or references in media reports. A firm is then classified as ‘politically connected’ if any of its directors are: (i) current or former politicians or bureaucrats, (ii) close relatives of one, or (iii) linked through professional or social networks. 

Around 2.75% of firms in our dataset are classified as politically connected based on this methodology, which is a substantially lower and arguably more credible estimate than the 29% yielded by conventional name-matching techniques. It reduces both false positives and false negatives and captures an additional 13% of political ties that would otherwise be missed, enabling a more accurate empirical analysis of these connections. 

Studying the impact of political connections during India’s demonetisation

Our empirical context is India’s demonetisation policy, announced in November 2016, which invalidated 86% of the country’s currency in circulation overnight. The move created a sudden and severe liquidity crunch, disrupting financial flows, supply chains, and business operations. We use this setting as a natural experiment to assess how connected and unconnected firms responded to the shock. We combine our political connections data with financial data from the Prowess database, which tracks more than 40,000 Indian formal sector firms from 2012 to 2019. This rich panel provides detailed information not only on firm performance indicators (such as income, sales, expenses, etc.), but also on their assets, liabilities, and borrowing structures.

Notably, politically connected firms in our sample are larger, older, and more financially active than unconnected firms even before the crisis. This raises concerns about whether differences in their post-crisis performance are driven by these firm characteristics rather than political connections. To mitigate this, we use a synthetic difference-in-differences  approach (Arkhangelsky et al. 2021), which combines elements of traditional difference-in-differences and synthetic control methods. It creates a reweighted control group that closely mirrors the pre-crisis trends of connected firms. We further account for potential confounding factors by including a rich set of firm, industry-year, and district-year fixed effects to control for both time-invariant differences and time-varying shocks.

Did politically connected firms perform better post-crisis?

We find that politically connected firms not only navigated the crisis more effectively, but also emerged stronger in the years that followed. Compared to their non-connected counterparts, connected firms reported 9-12% higher income, sales, and expenses over the three years after demonetisation. They also exhibited 3-9% higher total factor productivity, likely driven by an expanded product scope and greater investment in intangible assets. Interestingly, these gains were persistent over time, suggesting that the benefits of political connections could extend beyond just surviving the crisis, but impact longer-term growth and competitiveness.

Why were politically connected firms more successful in navigating crisis?

We find that politically connected firms pursued a range of strategies that differed from their non-connected counterparts:

1. Borrowing patterns: Connected firms reduced overall borrowing after demonetisation and strategically restructured their debt portfolios. They shifted away from costlier long-term bank loans—where interest rates had risen—and turned to long-term loans from central and state governments. They also increased their reliance on short-term borrowing and were more likely to secure unsecured loans, suggesting privileged access to credit even in a restricted financial environment.
2. Delaying payments: To ease liquidity constraints, connected firms were able to increase their short-term liabilities by postponing payments to suppliers, vendors, and creditors. This allowed them to defer immediate payment outflows during a time of macroeconomic crisis.
3. Asset expansion and acquisitions: Remarkably, despite a downturn, connected firms expanded their asset base. They invested more in intangible assets like software, patents, and marketing rights, and were more likely to acquire other firms. However, we find no significant increase in spending on inventories, cash balances, or fixed capital like machinery or property.

Policy implications for economic recovery post-shock

As economic shocks become more frequent, understanding what makes some firms more resilient than others is increasingly important. Our findings suggest that political connections can provide firms with privileged access to scarce resources, enabling them to better survive periods of macroeconomic downturn and recover more quickly.

At the same time, these results raise concerns about the fairness and efficiency of resource allocation. If political connections influence access to public support or financial relief, they risk undermining inclusive recovery, which highlights the need for greater transparency and accountability in business-government relationships. Future research should further unpack the specific channels through which political influence operates—whether through reputation, implicit favours, or regulatory discretion. Understanding these dynamics is essential not only for India, but for other emerging economies where political connections remain an influential force in shaping markets and economic outcomes.

References

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Arkhangelsky, D, S Athey, D A Hirshberg, G W Imbens, and S Wager (2021), “Synthetic difference-in-differences,” American Economic Review, 111(12): 4088–4118.

Chen, Y, G Chiplunkar, S Sekhri, A Sen, and A Seth (2025), “How do political connections of firms matter during an economic crisis?” Journal of Development Economics, 103471.

Faccio, M (2006), “Politically connected firms,” American Economic Review, 96(1): 369–386.

Faccio, M, R W Masulis, and J J McConnell (2006), “Political connections and corporate bailouts,” The Journal of Finance, 61(6): 2597–2635.

Fisman, R (2001), “Estimating the value of political connections,” American Economic Review, 91(4): 1095–1102.

Heitz, A, Y Wang, and Z Wang (2021), “Corporate political connections and favorable environmental regulatory enforcement,” Management Science.

Khwaja, A I, and A Mian (2005), “Do lenders favor politically connected firms? Rent provision in an emerging financial market,” The Quarterly Journal of Economics, 120(4): 1371–1411.

Sapienza, P (2004), “The effects of government ownership on bank lending,” Journal of Financial Economics, 72(2): 357–384.

Xu, G, E Deserranno, D Moreira, and E Teso (2023), “Bureaucracy,” VoxDevLit, 8(1).