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The question of whether immigrants from countries with low levels of political trust bring those attitudes with them to their host societies has long been debated. This column leverages survey data from 38 countries, and exploits variation across countries, cohorts, and survey rounds, to show that immigrants exposed to institutional corruption during early adulthood (ages 18-25) before migrating exhibit higher levels of political trust in their destination country. This effect is confined to national political institutions and does not extend to supra-national bodies or interpersonal trust. Elevated trust persists over time, translating into greater electoral participation and political engagement.

The integration of immigrants into host societies remains a recurring concern for both policymakers and the public. A common narrative holds that immigrants from countries with weak institutions and high corruption bring these norms with them, eroding trust in political systems. This fear has shaped debates on immigration policies, with some advocating for restrictions to protect institutional integrity (Borjas 2014, Clemens and Pritchett 2019).  What if the story is more complex? Could exposure to corruption in home countries actually foster greater trust in host-country institutions?

In a recent study (Aksoy et al. 2024), we examine this question using data from eight waves of the European Social Survey (2004–2018), which includes a range of questions on political trust in the destination country. Our analysis covers 38 European countries. To measure immigrants’ exposure to corruption in their home countries, we use data from the Varieties of Democracy (V-DEM) project.

Our empirical strategy leverages variation within origin countries, within host countries, and across age cohorts. Simply put, we compare immigrants with similar observable characteristics, originating from the same country, living in the same host country, but exposed to differing levels of corruption in their home countries prior to migration. This is achieved by incorporating fixed effects for origin-host country pairs, origin country by year, host country by year, and age cohorts.

Main results

We find that immigrants’ exposure to corruption in early adulthood (i.e. at ages 18-25) in their origin country is an important determinant of the trust they place in the parliaments, political parties and politicians of their country of immigration. Strikingly, exposure to more corruption in the origin country affects trust in the political institutions of the host country positively, not negatively (Figure 1). An immigrant from a highly corrupt environment is six percentage points more likely to trust these institutions compared to someone from a less corrupt country – a significant difference, given that average trust levels hover around 61%.  Importantly, this trust is specific to national political institutions. Immigrants’ broader social trust or trust in supranational organisations, such as the United Nations, remains unaffected. Additionally, the impact of corruption exposure persists over time, indicating that early-life experiences shape enduring attitudes (consistent with Eichengreen et al. 2021 and 2024).

Figure 1 Impact of corruption exposure on political trust

Figure note:  This figure presents OLS estimates of the baseline model, where the independent variable is Corruption Exposure18-25, corresponding to the cumulative V-DEM Corruption Index in the country of origin when individuals are between ages 18 and 25. Each line represents a separate regression with a different outcome variable. The Political Trust Index is defined as the average trust in parliament, political parties, and politicians. The regressions include a comprehensive set of fixed effect, control for demographic and labour market characteristics (see Table 1 in the paper for details). Whiskers corresponds to two-way clustered standard errors by host and origin country.
Data Sources: European Social Survey and V-DEM.

Media consumption as a mediating factor

Interestingly, this increase in trust is not uniform and is strongly influenced by media exposure in the host country. Immigrants who consume more host-country media – such as newspapers, television, or online sources – tend to develop a more nuanced understanding of institutional quality. This additional information reduces reliance on their home-country experiences as a reference point, tempering their levels of trust. Specifically, immigrants with high media consumption in the destination are likely more exposed to institutional shortcomings and political controversies in their host countries, diminishing the contrast with their previous experiences.

Political engagement and broader impacts

There is, in addition, a link between increased political trust and political engagement. Immigrants exposed to corruption in their home countries are more likely to vote or participate in political organisations in their host countries (Figure 2). This suggests that the heightened trust translates into tangible political involvement, further integrating such immigrants into the democratic fabric of their new societies.

Figure 2 Impact of corruption exposure on political behaviour

Political trust among immigrants vs natives

Interestingly, natives exposed to corruption during their formative years respond differently. While immigrants develop greater trust when encountering better institutions abroad, natives exposed to corruption exhibit lower trust in their own institutions. This divergence underscores the unique role that migration plays in shaping political trust through comparative experience. For second-generation immigrants, however, the patterns align more closely with those of natives, as their trust levels are shaped by host-country conditions rather than foreign reference points.

Why does this happen? 

We interpret this result through the ‘reference point hypothesis’, which draws on insights from Kahneman and Tversky’s prospect theory (Kahneman and Tversky 1979). Immigrants from corrupt regimes form low expectations about political institutions, based on their formative experiences. On encountering stronger institutions in their host countries, they perceive these institutions more positively relative to their previous experiences.

The effect we identify is amplified when the gap between home and host countries is wider. Immigrants from countries with weaker democratic practices or lower income levels display notably higher trust in host-country institutions compared to those from countries with more similar conditions. This suggests that significant contrasts between home and host environments play a critical role in shaping immigrants’ perceptions.

Concluding remarks

Political trust is essential for effective governance and societal stability. Trust in institutions encourages compliance with public policies, political engagement, and overall integration into civic life. Distrust, on the other hand, can lead to disengagement, civil unrest and support for populist movements (Levi and Stoker 2000, Papaioannou 2013). Fostering trust among immigrant populations is thus critical to achieving social cohesion and democratic resilience.

Our findings challenge common fears about immigrants from corrupt countries eroding trust in political systems. In fact, such immigrants often show higher confidence in host-country institutions. Policymakers can build on this trust by promoting active democratic engagement through political education and media literacy initiatives, helping immigrants contribute more effectively to their new communities.

While digitalisation has revolutionised the accessibility and administration of pension schemes in India, AI-driven predictive models can allow pension fund managers to make more informed decisions about investment strategies, risk management, and asset allocation.

India’s pension sector has historically been limited in scope, with coverage predominantly available to government employees and a small fraction of the private- sector workforce. In the past, pension services were riddled with bureaucratic challenges, requiring beneficiaries to fill in complex paperwork, endure long delays, and often travel to distant government offices to collect their pensions. These barriers were particularly significant for India’s rural population, which struggled to access pension schemes due to limited infrastructure and awareness.

India’s population today has surpassed 1.4 billion (World Bank, 2023). While a significant portion of the population remains young, with those aged 15-29 comprising around 27% (UNFPA, 2023), the number of senior citizens has also surged to more than 10% of the population, or roughly 140 million people (Ministry of Statistics, 2023).

Current demographic trends, such as the shift from joint to nuclear families, emphasise the need for a robust pension system as projections suggest 20.8% of the population will be over 60 by 2050 (UN World Population Prospects, 2022). Digitalisation and artificial intelligence (AI) will play a pivotal role in transforming this system to improve accessibility and sustainability.

Digitalisation: A catalyst for expanding pension coverage

The advent of digitalisation has revolutionised the accessibility and administration of pension schemes in India. Digital platforms such as eNPS and the unified portal have simplified pension management, reducing the administrative burden and increasing transparency. The Pension Fund Regulatory and Development Authority (PFRDA) reported more than five crore National Pension System (NPS) subscribers by March 2023 because of such advancements.

Additionally, automation in back-end processes, like fund reconciliation and benefit disbursement, minimises human error and expedites procedures. However, with the growing gig economy and labour mobility, pension policies must adapt to support workers in flexible employment structures and the informal sector.

The transformative power of AI in pension management

While digitalisation has paved the way for greater access and efficiency, the use of AI is transforming how pensions are managed in India. AI’s ability to analyse large datasets and provide predictive insights makes it a powerful tool to improve decision-making in pension fund management.

One of the key areas where AI can have a significant impact is in predictive analytics. Pension funds are responsible for ensuring that the contributions they manage are sufficient to meet future obligations, which requires accurate predictions of future liabilities.

AI-driven predictive models allow pension fund managers to make more informed decisions about investment strategies, risk management, and asset allocation. As of March 2023, PFRDA managed nearly ₹9 trillion in pension assets and has been harnessing AI to optimise its investment portfolio, enhancing long-term sustainability and delivering improved returns for subscribers.

AI tools like machine learning can analyse how individuals interact with pension systems, helping develop targeted, personalised pension schemes and delivery mechanisms. This personalisation allows pension systems to better meet the needs of different demographic groups, including the elderly and women, addressing gender gaps and promoting gender parity in pension coverage.

Fraudulent activities, such as identity theft and false claims, have long plagued pension schemes, particularly in systems with large numbers of beneficiaries. By analysing patterns in pension transactions and beneficiary data, AI algorithms can detect anomalies that may indicate fraud.

This proactive approach to fraud detection will help prevent financial losses and ensure that pension payouts reach the intended recipients. The EPFO has already begun using AI-based systems to verify the authenticity of pensioners’ Aadhaar-linked accounts, significantly reducing the likelihood of identity duplication or fraudulent claims.

In addition to improving the efficiency and security of pension systems, fraud detection and risk management, AI has the potential to offer personalised retirement solutions. Traditional pension schemes often offer standardised plans that may not align with the specific financial goals or needs of individual subscribers. AI can analyse an individual’s income, spending patterns, lifestyle, and long-term financial goals to recommend customised pension plans.

Such personalisation improves financial inclusion by catering to the needs of different income groups, including low-income earners who are often excluded from formal pension systems. Robo-advisors, or AI-powered financial advisory platforms, are gaining traction in India. They offer personalised pension planning advice, helping individuals choose the best pension products and strategies.

AI-powered chatbots have also emerged as a critical tool in enhancing customer service for pension subscribers. These chatbots provide real-time responses to common queries, such as checking contribution status, explaining withdrawal procedures, or providing account updates quickly, freeing up human agents to handle more complex cases.

Expanding coverage and ensuring security

Although schemes such as the Atal Pension Yojana (APY) have been launched to target informal workers, there is still a large gap in pension coverage. Digitalisation and AI also have immense potential to transform the pension sector by expanding coverage, particularly in the informal sector. Over 90% of India’s workforce is in the informal sector, where access to pension schemes is limited (ILO Report, 2022). Digital platforms and AI tools can help bridge this gap by simplifying the registration process, offering low-cost pension products, and reducing administrative costs. Moreover, through gamification, proper financial knowledge and skills, more young people can be attracted to this sector.

Digital marketing can also play a crucial role in increasing financial literacy and educating the public about pension options, driving engagement with non-traditional audiences. By leveraging digital channels, pension providers can better reach underserved communities, promoting participation among lower-income groups and rural populations.

Challenges

Pension funds handle sensitive financial data, and any breach of this data could have serious repercussions for subscribers. It is essential that pension providers invest in robust cybersecurity frameworks and comply with regulations such as India’s Digital Personal Data Protection (DPDP) Act to protect user information. Ensuring the security of digital pension platforms is critical to maintaining trust in these systems and encouraging more people to use them.

Secondly, there is the need to improve both financial and digital literacy, particularly among senior citizens and the rural population. Although smartphone penetration in India has increased significantly, many pensioners still face difficulties accessing digital services. Government initiatives such as Digital India aim to promote digital literacy and encourage the use of digital financial services.

Thirdly, the young people need to be brought into the pension system early in their careers to ensure they have a secure future. Continued efforts are needed to ensure that everyone, regardless of age or location, can benefit from the digitalisation of pension services.

Way forward

Digitalisation and AI are revolutionizing the pension sector in India by improving accessibility, efficiency, and security. As the country grapples with a growing elderly population and an expanding informal workforce, these technologies will play a crucial role in ensuring that pensions are accessible, efficient, and sustainable for all citizens.

While there are challenges related to coverage, expansion, cybersecurity, and digital literacy, the ongoing adoption of digital tools and AI in the pension sector promises to create a more inclusive and future-ready system, making the youth of this country understand that pension is not something only meant for senior citizens to think. The benefits of investing in this sector are equally important. By leveraging these technologies effectively, India can ensure a more secure retirement for millions of its citizens.

Dr CS Mohapatra is the chair professor – IEPF, and Depannita Ghosh a research analyst – IEPF, at the National Council of Applied Economic Research.

US President-elect Donald Trump’s incoming administration will likely seek to weaken the greenback’s exchange rate. But whether doing so would enhance the competitiveness of US exports and strengthen America’s trade balance is another matter.

BERKELEY – One of the more jaw-dropping policy ideas gaining political steam in the United States recently has President-elect Donald Trump and his team, on taking office, actively depressing the dollar with the goal of boosting US export competitiveness and reining in the trade deficit. If Trump tries, will he succeed? And what could – and probably would – go wrong?

On the question of whether Trump could weaken the dollar, the answer is clearly yes. But whether doing so would enhance the competitiveness of US exports and strengthen America’s trade balance is another matter.

The brute-force method of pushing down the dollar would entail leaning on the Federal Reserve to loosen monetary policy. Trump could replace Fed Chair Jerome Powell and push Congress to amend the Federal Reserve Act to compel the central bank to take marching orders from the executive branch. The dollar exchange rate would weaken dramatically, which is presumably the point.

But the Fed would not go quietly. Monetary policy is made by the Federal Open Market Committee’s 12 members, not just by the chair. Financial markets, and even a lapdog Congress, would see abrogating the Fed’s independence or packing the FOMC with compliant members as a bridge too far.

And even if Trump succeeded in “taming” the Fed, a looser monetary policy would cause inflation to accelerate, neutralizing the impact of the weaker dollar exchange rate. There would be no improvement in US competitiveness or the trade balance.

Alternatively, the Treasury Department could use the International Emergency Economic Powers Act to tax foreign official holders of Treasury securities, withholding a portion of their interest payments. This would make it less attractive for central banks to accumulate dollar reserves, driving down demand for the greenback. The policy could be universal, or US friends and allies, and countries that obediently limit their further accumulation of dollar reserves, might be exempt.

The problem with this approach to weakening the dollar is that by driving down demand for US Treasuries, it would drive up US interest rates. This radical step might reduce demand for Treasuries quite dramatically indeed. Foreign investors could be led not merely to slow their accumulation of dollars but to liquidate their existing holdings entirely. And while Trump could attempt to deter governments and central banks from liquidating their dollar reserves by threatening tariffs, a substantial share of US government debt held abroad – on the order of one-third – is held by private investors, who are not easily swayed by tariffs.]

More conventionally, the Treasury could use dollars in its Exchange Stabilization Fund to buy foreign currencies. But increasing the supply of dollars in this way would be inflationary. The Fed would respond by draining those same dollars from the markets, sterilizing the impact of the Treasury’s action on the money supply.

Experience has shown that “sterilized intervention,” as this combined Treasury-Fed operation is known, has very limited effects. Those effects become pronounced only when the intervention signals a change in monetary policy, in this case in a more expansionary direction. Given its fidelity to its 2% inflation target, the Fed would have no reason to turn in a more expansionary direction – assuming its continued independence, that is.

Finally, there is talk of a Mar-a-Lago Accord, an agreement by the US, the eurozone, and China, echoing the historic Plaza Accord, to engage in coordinated policy adjustments to weaken the dollar. Complementing steps taken by the Fed, the European Central Bank, and the People’s Bank of China would raise interest rates. Or China and Europe’s governments could intervene in the foreign exchange market, selling dollars to strengthen their respective currencies. Trump could invoke tariffs as a lever, much as Richard Nixon used an import surcharge to compel other countries to revalue their currencies against the dollar in 1971, or as Treasury Secretary James Baker invoked the threat of US protectionism to seal the Plaza Accord in 1985.

In 1971, however, growth in Europe and Japan was strong, so their revaluing was not a problem. In 1985, inflation, not deflation, was the real and present danger, predisposing Europe and Japan toward monetary tightening. In contrast, the eurozone and China currently confront the dual specters of stagnation and deflation. They would have to weigh the danger to their economies from monetary tightening against the damage from Trump’s tariffs.

Faced with this dilemma, Europe would probably give in, accepting a tighter monetary policy as the price for rolling back Trump’s tariffs and preserving security cooperation with the US. China, which sees the US as a geopolitical rival and seeks to decouple, would probably take the opposite course.

Thus, a supposed Mar-a-Lago Accord would degenerate into a bilateral US-European agreement that did the US little good while inflicting considerable harm on Europe.

Barry Eichengreen, Professor of Economics and Political Science at the University of California, Berkeley, is a former senior policy adviser at the International Monetary Fund. He is the author of many books, including In Defense of Public Debt (Oxford University Press, 2021)