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HONG KONG – The gap between productivity growth in the United States and Europe paints a stark and, for Europeans, depressing picture. In the two decades since 2004, US productivity growth, as measured by the value of output per hour worked, has been more than double that of the eurozone. Whereas eurozone productivity has flat-lined and even fallen slightly since the outbreak of the COVID-19 pandemic, US non-farm output per hour has risen by more than 6% over the same period – more than adequate performance by America’s own historical standards.

Something seems to be going seriously right in the US and seriously wrong in Europe. Some accounts point to the strong fiscal stimulus applied in the US since the outbreak of the pandemic. For Europeans this explanation is reassuring, because it suggests that the differential is transitory. After all, the US can’t run massive budget deficits and live beyond its means indefinitely.

But while strong spending stimulus can trigger rapid output and employment growth, it is not clear why it should produce faster productivity growth. On the contrary, given strong employment growth and tight labor markets, one might expect US companies to be forced to take on less productive workers, with negative implications for output per hour. More likely, tight labor markets in the US may mean that firms, unable to find an adequate supply of workers at any price, are impelled to substitute capital for labor – to invest in labor-saving technology.

Americans visiting a bank branch will encounter plenty of ATMs but sometimes not a single human teller. They are compelled to order meals, even at white-tablecloth restaurants, using a QR code. Patrons of Parisian bistros horrified by this thought may argue that a Franco-American cultural difference is at work. But it is hard to deny that tight labor markets also play a role.

Recall, however, that US productivity growth had accelerated relative to Europe’s already in the decade leading up to the pandemic, when labor markets were not so tight. Both the US and Europe turned to fiscal consolidation following the 2008 global financial crisis. Europe might have been slightly more hell-bent on austerity, but there was not enough difference in demand conditions to explain their different productivity outcomes.

Moreover, while American firms have been quicker to capitalize on digital technologies, the timing is wrong here, too: US outperformance in computer producing and using sectors was most pronounced in the decade preceding the global financial crisis, not in the period since.

And it is not as if European managers are unaware of the labor-saving and productivity-enhancing potential of digital technologies. It could be that Europe’s strong trade unions, fearing job destruction, resist their adoption, although Germany, with a tradition of strong unions, has some of the most robot-intensive factories in the world.

Alternatively, restrictive European Union rules may be impeding adoption. The EU’s data-privacy regulations, and now its proposed AI rulebook, if adhered to strictly, may slow the development of AI applications.

Finally, it could simply be that Europe has had bad luck, specifically in the form of Russian President Vladimir Putin and his energy-price shock. The US, being self-sufficient in energy, has not been vulnerable to energy-supply disruptions to the same degree. European firms, in contrast, have been forced to suspend their most energy-intensive operations or else to engage in costly restructuring, which is not good for productivity.As for the latest round of new digital technologies, firms are only just now beginning to explore how large language models and generative artificial intelligence can be used to boost productivity. In other words, AI and related developments can’t explain America’s unusually strong productivity performance in the last four years. In fact, history suggests that capitalizing on radical new technologies requires firms to reorganize how they do business, a trial-and-error process that takes time. The inevitability of errors means that productivity is likely to fall before rising, a phenomenon economists call the “productivity J-curve.”

Mario Draghi, Europe’s senior economic statesman, will present the EU with a set of proposals later this year for boosting productivity. No doubt, he will recommend completing Europe’s capital-markets union so that firms can more easily finance investments in new technologies.

Draghi will recommend removing barriers to competition, which would intensify the pressure on firms to innovate in order to survive. He will advocate greater energy efficiency and self-sufficiency to free Europe from more Putin-like disruptions.

Observers like me can confidently predict what Draghi will recommend because such proposals have been around for years. Europe should move now to implement these old ideas. And it desperately needs to come up with new ones.

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).

EVs’ growth may suffer due to problems of battery availability and disposal, just as biofuel has been hit by feedstock constraint.

E-mobility seems to be the buzzword in India now. Almost every other day, some news comes out on how much progress India has made in the use of electric vehicle in the transport sector and how it helps in reducing carbon emission. While the progress in the use of e-vehicle is a fact, the carbon saving due to use of the same is highly exaggerated for the simple fact that India is still heavily dependent on fossil-based electricity for recharging e-vehicles.

Thus, unless we can tilt the balance sharply in favour renewables-based electricity, there will be a net increase in carbon emissions, as per IEA analysis, when considering life-cycle emissions. Moreover, as e-vehicles weigh more than internal-combustion (IC) vehicles, it may lead to higher tyre-related particulate emissions, even though it removes tailpipe emission of IC-vehicles.

Range anxiety, in terms of availability of charging infrastructure for an e-vehicle is a concern in India, especially in rural/ remote areas and highways, and also the charging time is longer than refuelling an IC vehicle. Setting up a charging station is capital intensive, both in terms of land and technology. Widespread adoption of e-vehicle can affect electricity grids, especially at peak hour of demand. Battery swapping, where a depleted battery can be replaced with a pre-charged one, can save time for full charging, but the technology is yet at a nascent stage in India, and significant investment and co-ordination among the stakeholders are required to develop the infrastructure.

Additionally, it also requires standardisation of the battery design, efficient testing and compliance for compatibility adherence. With the growth of e-vehicles, there is a need to increasingly focus on supply-chain related issues, particularly batteries. The manufacture of batteries for e-vehicles is growing at a much slower pace than the adoption of vehicle use, and thus India is following an import dependent pathway. This is a very risky proposition.

As all countries move towards e-mobility and most of them bank on imports for sourcing of battery, the prices of batteries may skyrocket in the coming years, especially as some of the raw materials are sourced from limited geographic regions. Thus, near self- sufficiency in batteries is a must for faster adoption of e-vehicles. This would not only safeguard India from the vagaries of global battery price, just like crude oil prices, but will also pave the way for growth of jobs in the sector. Surely, the job prospects will be higher if the domestic supply chain of e-vehicles is developed as far as possible.

CBAM effect

With growth of e-vehicles, the disposal of batteries will be a matter of environmental concern. India is not paying enough attention to this. It appears India has yet to learn the lesson from the CBAM (Carbon Border Adjustment Mechanism) experience. Looking back, developing countries like India were quite happy when ‘dirty’ industries from the EU moved to their shores following the Kyoto Protocol. Three decades later, the EU comes up with CBAM, which is likely to affect some of our industries. The EU has already announced that the reach of CBAM will be expanded to other sectors. Most likely e-waste, particularly batteries, will be on top of their agenda. The EU’s policy is stringent on the same and to create a level-playing field, it will expect partner countries to be on the same page in this respect.

A decade back, the kind of hype currently being witnessed in the case of e-mobility was observed in the case of biofuel. Down the line, however, we are yet to achieve 20 per cent blending target, even though at one point the government gave tax incentives for flexi-IC vehicles so that it is technically possible to run a vehicle on 100 per cent biofuel, just like in Brazil.

However, biofuel growth did not take off like in Brazil. The weakness in feedstock for biofuel was the real bottleneck, even though India is self- sufficient in other parts of the supply chain for biofuel.

On the jobs front, e-mobility is no match to the biofuel sector. However, not much attention has been paid to increase the feedstock supply of biofuel by way of scientific research to increase the oil-bearing capacity of biofuel feedstock. While India has achieved success in food crops through the Green Revolution, this sector has not receive similar attention. Productivity, and not land, probably is the principal constraint for its growth.

Unless sufficient attention is paid to supply bottlenecks and the battery disposal issue, e-mobility may go the biofuel route. A collective and co-ordinated effort is required from the government, industry and other stakeholders to develop infrastructure, facilitate a supply-chain that includes domestic manufacturing, increase awareness about battery disposal, and incentivise adoption to cater to the increasing demand for fuels triggered by a large and growing population and expansion of urbanisation in the country.

Sanjib Pohit is Professor at NCAER and Chetana Chaudhuri is Fellow at NCAER. Views are personal.

While the methodology for the Household Consumption Expenditure Survey is more refined now, the survey needs to address some methodological challenges.

The National Sample Survey (NSS) Office released the key results of the Household Consumption Expenditure Survey (HCES) 2022-23 in late February. These primarily include all-India estimates of the average household monthly per capita consumption expenditure (MPCE) for rural and urban areas, its distribution bybroad item groups for food and non-food categories, the variation in the average MPCE of households with different standards of living (by appropriately grouping them into 12 ‘fractile classes’ of MPCE), and the trend in the composition of MPCE since the 1999-2000 survey (55th round of the NSS). So far as the State-level estimates are concerned, the factsheet gives only estimates of average MPCE — total of food and non-food items — for each State and Union Territory (UT) for rural and urban areas.

As the earlier available results pertain to 2011-12, the latest results have bridged the data vacuum of more than a decade on an important subject that also goes into the compilation of poverty estimates. While the methodology for the HCES is more refined now, there are still challenges that need to be addressed. This will ensure that apart from producing much firmer estimates of the average MPCE, the new series has an in-built mechanism to maintain comparability of the current estimates with those of the earlier ‘quinquennial series’ available from 1972-73 to 2011-12.

Changes and implications

One change in the new HCES is the updated item coverage, which has been done keeping in view the latest consumption behaviour.

Another significant change is the splitting of the single questionnaire into three parts covering food items, consumables and services items, and durable goods. The three questionnaires have been used at random in a selected household during three separate monthly visits contrary to the past when the team would visit a household just once.

Using the single questionnaire during one visit often resulted in long interviews. As a result, respondents were fatigued and there was a possibility of under-reporting consumption expenditure, particularly in respect of items like durable goods which were placed towards the end of the questionnaire. While the latest change will help us derive more reliable estimates of the average MPCE, we are also now unable to compare the current estimates of the average MPCE, and the share of poor that may be derived from it based on the survey data, with the estimates of the past, given the likelihood of under-reporting of household consumption expenditure in the previous surveys.

A third change is in the method of stratification of villages and urban blocks for the purpose of sampling. While in HCES 2011-12, every district was considered as a basic stratum for rural and urban areas, the new HCES considers a State/UT as the basic stratum. While every district with some minimum sample allocation got represented in both the rural and urban samples of the 2011-12 survey, the new HCES does not ensure the same. Such a change does not affect the generation of State-wise estimates.

There is also a change in stratification of households. All the households of a selected village/urban block are classified into three groups depending on a criterion. The criterion in rural areas is possession of land and in urban areas it is possession of four-wheeler cars for non-commercial use on the date of the survey. The total sample of 18 households with proportional representation from the three groups have been selected. Given that the proportion of urban households possessing four-wheelers is as low as 6% in States like Andhra Pradesh, Bihar and West Bengal as per the National Family Health Survey-5 (2019-21), adequate number of rich households in the sample may not get ensured in such States as intended. It is worthwhile to note that the said stratification in the HCES 2011-12 was based on the average MPCE of the households with the top 10%, middle 60% and bottom 30% forming the three strata, and a sample of two, four, and two households, respectively, was allotted to these strata.

Methodological issues

The splitting of the questionnaire and visiting a sample household thrice now have led to non-comparability of the current estimates with those of the past, although the current estimates appear to be much firmer ones. One way to address this issue is to replicate the traditional approach of ‘one schedule with a one-time visit to a household’ in an independent random sample of households to be drawn from the same villages and urban blocks of at least one of the panels for which the fieldwork is yet to commence. In this context, it is important to note that the sample in the new HCES for a year is in the form of 10 panels, each comprising consecutive three months, with an equal number of sample villages/urban blocks allotted to each panel. This add-on module will facilitate generation of two independent estimates of the average MPCE and other associated correlates based on the current approach vis-à-vis the earlier one. This information will be useful to study the extent of divergence between the two alternative estimates of MPCE and build a comparable series.

Further, to ensure adequate representation of rich households, it will be worthwhile to develop a frame of such households based on administrative data and a random sample of households drawn from this frame for enquiry on consumption expenditure of rich households through a dedicated survey. This database in conjunction with those from the HCES will be useful to derive an improved distribution of households by their average MPCE.

G.C. Manna is Professor at the Institute for Human Development (IHD), New Delhi, and a senior adviser at the National Council of Applied Economic Research. He was earlier the Director General of the Central Statistics office and the National Sample Survey Office and a member of the National Statistical Commission. Views are personal.

The aggregation of personal and financial data through fintech platforms presents an attractive target for hackers, leading to concerns over data privacy and security.

The digitalized payment landscape, while making transactions more efficient and cost-effective, has unintendedly heightened the risk of cyber frauds and personal data misuse. Cybercriminals exploit vulnerabilities in the system, engaging in phishing attacks, exploiting software flaws, or deceiving users into revealing sensitive information. The aggregation of personal and financial data through fintech platforms presents an attractive target for hackers, leading to concerns over data privacy and security.

Hacktivism, that combines “hacking” and “activism” to use hacking skills for promoting specified objectives, presents multifaceted challenges to India’s financial sector, notably through operational disruptions from denial-of-service attacks and website defacement, exposing data security vulnerabilities that could be exploited for cybercrime. These activities pose regulatory and compliance risks besides inflicting reputational damage, undermining customer trust and potentially leading to financial losses.

In the digitalized world, Application Programming Interfaces (APIs) are important elements of innovation, efficiency and seamless connectivity. These enables different software applications to communicate with each other, playing a crucial role in the functionality of the digital experiences of social media platforms like Facebook, Instagram, eCommerce platforms, YouTube, ChatGPT, etc.

The increasing reliance on APIs, however, has escalated the risk of cyber threats, highlighting the critical need for advanced security measures, including the financial sector. APIs are the unsung heroes of the digital age, enabling the rapid exchange of data and functionality across diverse platforms. In the financial sector, APIs have been instrumental in driving mobile commerce and the Internet of

Things (IoT), with Akamai estimating that APIs drive roughly 83% of internet traffic. The financial sector, a vital component of national infrastructure, has witnessed a surge in API-related cyberattacks.

Cybercriminals exploit vulnerabilities to access or corrupt sensitive data, posing significant risks to consumer trust and financial stability. This widespread adoption underscores the urgency for robust API security mechanisms to safeguard sensitive financial data and consumer privacy.

A proactive and well-coordinated cybersecurity posture, with an emphasis on resilience and collaboration with national cybersecurity bodies like CERT-In and specific financial sector organization, i.e., CSIRT-FIN to safeguard against the evolving threat landscape posed by hacktivism is thus essential.

CSIRT-Fin and CERT-In have been instrumental in protecting India’s financial sector through vigilant monitoring, advisories, and collaboration, yet the dynamic nature of cyber threats demands ongoing enhancements to their efforts. Besides, financial service providers and regulators have to allocate significant resources towards enhancing cybersecurity defences, including adopting advanced threat detection technologies, comprehensive employee training, and developing robust incident response strategies.

AI: A Game-Changer in API Security

Conventional security measures, while necessary, are increasingly insufficient against sophisticated cyber threats that target the business logic of APIs. AI-based security systems are a game-changer, as they are capable of analyzing vast amounts of data to identify patterns and detect anomalies that deviate from normal behavior and allows for the early detection of potential threats, including those that traditional security measures are likely to overlook.

Government, regulatory authorities, and financial service providers, including fintech companies alike are collectively seized with a significant shift towards prioritizing cybersecurity initiatives for investor protection, marking a departure from conventional challenges to embrace a new paradigm where digital security is at the forefront of strategic planning. With cybersecurity steering the course of investor protection, these initiatives will underscore the commitment to shield investors’ interests and assets in an increasingly digital financial realm.

The Digital Personal Data Protection (DPDP) Act, 2023 is all set to bolster consumer protection in the financial sector against malicious threats by enforcingvstrict data privacy regulations, including explicit consent for data collection, data minimization, and stringent security measures to safeguard personal data. It mandates timely breach notifications, ensuring consumers can act swiftly to secure their information.

The DPDP Act aims to create a more secure and privacy-conscious digital financial ecosystem, significantly reducing the risk of cyberattacks and data misuse. In addition, the adoption of AI and ML technologies offers a promising path forward as these technologies provide dynamic, intelligent systems capable of real-time monitoring and threat detection, ensuring that API security evolves in tandem with emerging threats.

Way Forward

It’s crucial for organizations to integrate advanced technologies like AI for real-time critical threat detection, foster stronger public-private partnerships to leverage private sector expertise, and conduct more frequent cybersecurity drills to identify and mitigate vulnerabilities.

Secondly, expanding awareness and training programmes can empower both organizations and consumers to navigate the digital landscape safely. Thirdly, modernizing the regulatory framework by financial sector regulators to reflect the latest cyber threats and ensuring compliance across the sector is the need of the hour.

Additionally, strengthening domestic as also international collaboration for sharing threat intelligence and best practices can provide a preemptive edge against globally coordinated attacks. By adopting these strategies, we can significantly improve the resilience of India’s financial sector against evolving cyber risks.

Thus, the future of financial security lies in leveraging AI to develop adaptive, intelligent systems that can anticipate and neutralize cyber threats. Updating the curriculum, more digital literacy awareness programmes, case-study based learning, addressing different target groups by class-oriented module structure can help address cybersecurity issues. The National Strategy for Financial Education (NSFE) needs to be revamped to orient towards handling the modern issues and complexities of financial world.

As digital financial services continue to underpin the fabric of financial sector today, ensuring their security against cyber threats has never been more important. Hence, there is an urgency of adopting AI-driven security measures by which the financial sector can navigate the complex cyber threat landscape with confidence, ensuring the integrity and resilience of its digital ecosystems, while simultaneously facilitating a robust and stable growth of the financial sector.

The author is a former official of the Indian Economic Service and IEPF Chair at National Council of Applied Economic Research, Views are personal.