Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Monday, May 6, 2019

AI Summary. A tightened U.S. labor market with unemployment at 3.6%, the lowest in nearly 50 years, has lifted wages 3.2% over the past year, outpacing inflation. Labor demand continues to exceed supply in sectors such as construction and healthcare, prompting employers to offer higher pay and better benefits.

Ben Casselman The New York Times
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A decade after the recession, the US labor market has tightened, leading to notable wage growth. Unemployment rates have fallen to 3.6%, driving wages up by 3.2% over the past year, outpacing inflation.

Does a tighter labor market explain faster wage growth?

Core argument: U.S. wages rose 3.2% over the past year, outpacing inflation and delivering real income gains, as unemployment fell to 3.6%, the lowest in nearly 50 years.

A decade after the recession, the U.S. labor market has tightened significantly, leading to notable wage growth. Unemployment rates have fallen to 3.6%, the lowest in nearly 50 years, creating a competitive environment for employers seeking skilled workers. This scarcity of labor has driven wages up by 3.2% over the past year, outpacing inflation and providing real income gains for workers. The labor force participation rate [LFP] has also seen a modest increase, indicating more individuals are entering the workforce. However, the demand for labor continues to exceed supply, particularly in sectors like construction and healthcare, where job openings have surged by 20% since 2018. This imbalance is prompting companies to offer higher salaries and better benefits to attract and retain talent, marking a significant shift from the stagnant wage growth observed in the years immediately following the recession.

Takeaways by Macro Roundup® AI

  1. U.S. wages rose 3.2% over the past year, outpacing inflation and delivering real income gains, as unemployment fell to 3.6%, the lowest in nearly 50 years.
  2. Job openings in sectors including construction and healthcare have risen 20% since 2018, with labor demand exceeding supply and prompting employers to offer higher salaries and better benefits.
  3. The U.S. labor force participation rate has increased modestly, indicating more individuals are entering the workforce.

Ben Casselman, "Why Wages Are Finally Rising, 10 Years After the Recession,"The New York Times, May 2, 2019, https://www.nytimes.com/2019/05/02/business/economy/wage-growth-economy.html

AI Summary. The global pool of advanced analytics workers is projected to double to 1m from 500,000, with India tripling its candidates for such roles to over 200,000 from 65,000. The US is projected to face shortages of data engineers and architects alongside a potential oversupply of data scientists.

Chris Brahm Bain & Company
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The global demand for data analytics workers is set to rise significantly, with the talent pool expected to double by 2020, reaching 1m people from 500,000 in 2018.

Is the growing analytics talent pool matching where skills are needed?

Core argument: The global pool of advanced analytics talent is projected to double from 500,000 in 2018 to 1m by 2020, amid rising demand for data analytics workers.

The global demand for data analytics workers is set to rise significantly, with the talent pool expected to double by 2020, reaching 1m people from 500,000 in 2018. India is leading this growth, tripling its candidates for advanced analytics roles from 65,000 in 2018 to over 200,000 by 2020. Despite this increase, the US will face shortages in critical roles like data engineers and architects, while potentially having an oversupply of data scientists. Companies are advised to adopt a tiered talent strategy, combining new hires, internal retraining, and leveraging external resources such as offshore data hubs and third-party firms. This approach helps address talent bottlenecks and supports the growing analytic intensity across sectors like retail, media, and technology, where advanced analytics roles are increasingly vital.

Takeaways by Macro Roundup® AI

  1. The global pool of advanced analytics talent is projected to double from 500,000 in 2018 to 1m by 2020, amid rising demand for data analytics workers.
  2. India is projected to triple its candidates for advanced analytics roles from 65,000 in 2018 to over 200,000 by 2020, leading global growth in the talent pool.
  3. The US is projected to face shortages of data engineers and architects alongside a potential oversupply of data scientists, and companies are advised to combine new hires, internal retraining, offshore data hubs, and third-party firms.

Chris Brahm, Arpan Sheth, Velu Sinha and Jessica Dai, "Solving the New Equation for Advanced Analytics Talent," Bain & Company, April 30, 2019, https://www.bain.com/insights/solving-the-new-equation-for-advanced-analytics-talent/

Solving the New Equation for Advanced Analytics Talent

At a Glance

In the next two years, the global supply of advanced analytics talent will double, with India’s talent pool growing especially quickly.
In the US, talent shortages will persist for experienced hires and certain key jobs, like data engineers and architects.
Companies will struggle to hire experts away from the analytically mature sectors that are the most attractive to employees and that themselves plan to expand quickly.
A successful tiered talent strategy incorporates new hires and internal retraining, while also tapping data hubs, third-party service firms and crowdsourcing.

Innovation in analytics is a priority for almost every organization today. Yet bottlenecks in the key areas of talent, data and analytics strategy often block progress. In order to better understand the talent bottleneck and how to release it, Bain & Company assessed the global market for analytics talent—both supply and demand—interviewing practitioners and experts, reviewing job boards and professional community listings, and studying educational program statistics.

We found a workforce on the verge of dramatic change.

For years, companies have been stuck chasing either a limited supply of experienced professionals or new university graduates. Today, however, the global supply of advanced analytics talent is about to explode. By 2020, the advanced analytics talent pool is expected to reach 1 million people, up from half a million in 2018.

The growth in advanced analytics talent arises from a pivot in traditional and nontraditional education so rapid that it’s hard to find a historical precedent. The best comparison may be the 1990s, when India invested heavily in training programmers, especially in legacy systems, ahead of Y2K systems upgrades. That was when the subcontinent became the outsourcing giant it remains today.

Once again, India is taking the lead, but this time through a combination of retraining and a flood of graduates with advanced degrees in subjects suited to advanced analytics work, like computer science and data science. By the end of 2020, Bain estimates that India will have three times as many candidates for advanced analytics work as it did in 2018, expanding from 65,000 people to more than 200,000 in just two years. The analytics talent supply will climb in China, Western Europe and North America as well, but not quite as quickly.

This ramp-up, however, won’t entirely solve the advanced analytics talent challenge. Many countries will still have fewer analytics experts than needed. Most available advanced analytics talent has recently graduated, but people with greater tenure, who are needed to lead and manage these teams, are in short supply. The United States will suffer shortages in certain critical roles, like data engineers and architects, while facing a possible oversupply of data scientists.

Additional long-term demand will come from sectors like retail, media, consumer goods, and industrial goods and services, as companies apply analytics capabilities to their businesses. According to Bain’s research, among banks today, slightly more than 1% of white-collar employees work in advanced analytics, on average. By contrast, technology companies average nearly 3% of staff aligned with advanced analytics, and the most analytically advanced digital native companies have 10% (see Figure 1). The business models differ greatly across these sectors, of course, but it’s clear that, in nearly every large enterprise, the analytic intensity of the employee base is increasing.

Solving the New Equation for Advanced Analytics Talent: Extended Excerpt Image 1


Building an advanced analytics team

Companies should not expect to fill this gap entirely by wooing experienced talent from other employers. The most analytically mature sectors plan to expand their teams fastest, and employees are most interested in working for companies with well-established track records in analytics, our recent survey of more than 200 industry participants found.

Creative, flexible approaches for expanding the talent base include building centers of excellence for pools of hired analytics experts, and also retraining capable existing employees and giving them access to automation tools. Importantly, rather than trying to do everything in-house, a tiered talent strategy should focus a core, in-house analytics team on strategic tasks while tapping offshore data hubs, third-party service firms and crowdsourcing for other work. Even the most sophisticated companies leverage a combination of internal and external supply chains for analytics capabilities.

What is the optimal blend of advanced analytics roles? How are teams best configured? The exact balance varies depending on the sector and maturity of a company’s analytics practice, but teams will draw from eight key roles (see Figure 2). With companies hiring to create balanced advanced analytics teams, certain skills are in higher demand.

Solving the New Equation for Advanced Analytics Talent: Extended Excerpt Image 2


A mixed global outlook

The growth in advanced analytics-trained talent will occur primarily outside the US (see Figure 3). Long the largest market for analytics talent, the US will retain that top spot, but other global tech powers are catching up.

Solving the New Equation for Advanced Analytics Talent: Extended Excerpt Image 3


The outlook is especially bright in India, where two trends are simultaneously expanding the talent pool. First, STEM undergraduate and graduate degree holders, whose programs of study emphasize data and analytics skills, continue to join the workforce in increasing numbers. Augmenting that is India’s deep existing ecosystem in information technology, especially in programming and systems integration. Outsourcing firms and the India IT centers of global corporations house many ideal candidates for learning new advanced analytics skills. These two sources have combined to make India a vital hub of analytics expertise and have fueled the growth of its analytics outsourcing industry.

The future is less clear for China. Thanks to its relatively supportive regulatory environment and access to consumer data, China is often described as winning the race to dominate artificial intelligence and advanced analytics. But on advanced analytics talent, the country may need to accelerate. Recent trends point to a growing focus on talent in China, including a significant expansion in data science bachelor's degree programs and high levels of US recruiting and pay among Chinese digital natives and technology companies. Without an expansion in supply, talent could become a bottleneck, slowing analytics progress in China, especially for companies in traditional sectors.

Breaking the talent bottleneck

The historical shortage of analytics talent has caused many organizations to rely on a combination of internal and external advanced analytics expertise. This hybrid model also turns out to be a good match for the breadth of advanced analytics expertise needed in the future. A multilayered approach will continue to make more sense than full vertical integration for many companies. When possible, companies should develop critical mass internally in the most important aspects of advanced analytics, such as data-science team leadership and model development, and tap the external supply chain for less-critical skills, like tactical data management and model maintenance. Today, only 30% of companies are fully integrated in advanced analytics. The other 70% augment their internal skills with some combination of offshore outsourcing, freelancers, advanced analytics consultants and crowdsourcing.

Part of developing this talent ecosystem involves harnessing shadow analytics talent—that is, taking people currently walking the halls and helping them develop new analytical skills. Existing employees already know the company, the industry and how to operate effectively across the organization. Many have the quantitative background to learn analytical skills, and nearly a quarter of Bain survey respondents report that their companies have implemented advanced analytics training programs.

IBM’s Data Scientist Academy, for example, is an eight-day boot camp followed by individual online learning, and includes shadowing IBM data scientists and a capstone project. Airbnb’s Data University offers more than 30 classes in data awareness, collection, visualization and data at scale, and more than 500 employees (1 out of every 8) took part during the university’s first six months. Other training options include free MOOCs—massive open online courses—and paid retraining programs.

Some companies with a good data science workbench and the right set of data engineering tools also use advanced analytics automation to enable people without strong coding skills to build models and engineer data. Of survey respondents currently using technologies to automate advanced analytics tasks, more than half say these technologies enable existing staff to be rapidly trained to take on responsibilities of a data scientist or data engineer.

Fostering the talent ecosystem

Embracing this tiered approach will help companies today and in the future. It allows them to tap into the rapidly growing global talent supply and to create a more flexible model, all while leaving room to redeploy existing talent in new and creative ways. Companies cannot afford to let a bottleneck in analytics talent slow them down, and they don’t have to.

Chris Brahm is a Bain & Company partner in San Francisco and leads the firm’s Global Advanced Analytics practice. Arpan Sheth is a Bain partner based in the Bangalore office and leads the firm’s Information Technology practice in Asia-Pacific. Velu Sinha is a Bain partner in Shanghai, and Jessica Dai is a principal based in San Francisco.

Tuesday, May 7, 2019

AI Summary. A proposed $2tn infrastructure bill may shift existing labor rather than create new jobs given very low unemployment, and any stimulus could prompt the Federal Reserve to raise interest rates, offsetting gains. The share of structurally deficient bridges has been declining for decades, and the bill's multiple competing policy goals may dilute value for money.

Ramesh Ponnuru Bloomberg
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The proposed $2tn infrastructure bill may not deliver expected economic benefits. Unemployment at its lowest since 1969, increased spending might shift existing labor rather than create new jobs @RameshPonnuru

Is large-scale infrastructure spending a poor use of $2 trillion?

Core argument: With unemployment at its lowest since 1969, the proposed $2tn infrastructure bill might shift existing labor rather than create new jobs, and any stimulus it delivers could prompt the Federal Reserve to raise interest rates, negating potential gains.

The proposed $2tn infrastructure bill may not deliver the expected economic benefits. With unemployment at its lowest since 1969, increased spending might merely shift existing labor rather than create new jobs. If the bill stimulates the economy, it could prompt the Federal Reserve to raise interest rates, negating potential gains. Although infrastructure improvements can boost productivity, political challenges often misdirect funds away from necessary maintenance to new projects. The percentage of structurally deficient bridges has been declining for decades, suggesting that the state of infrastructure is better than political rhetoric implies. Additionally, the bill's multiple policy goals, such as immediate job creation and diversity in contract awards, may dilute its economic effectiveness by not prioritizing value for money.

Takeaways by Macro Roundup® AI

  1. With unemployment at its lowest since 1969, the proposed $2tn infrastructure bill might shift existing labor rather than create new jobs, and any stimulus it delivers could prompt the Federal Reserve to raise interest rates, negating potential gains.
  2. The percentage of structurally deficient bridges has been declining for decades, suggesting infrastructure is in better condition than political rhetoric implies, while political challenges often misdirect funds from necessary maintenance toward new projects.
  3. The infrastructure bill's multiple policy goals, including immediate job creation and diversity in contract awards, may dilute its economic effectiveness by not prioritizing value for money.

Ramesh Ponnuru, "Infrastructure Bill Might Be a Bad Use of $2 Trillion,"Bloomberg, May 6, 2019, https://www.bloomberg.com/opinion/articles/2019-05-06/infrastructure-bill-might-be-a-waste

Infrastructure Bill Might Be a Bad Use of $2 Trillion

Little green shoots of bipartisanship are sufficiently rare these days that it feels mean to stomp on them. But I’m afraid that it’s very unlikely that the $2 trillion infrastructure bill that congressional Democrats and President Donald Trump are discussing will amount to a good use of taxpayer money.

The promises are big and numerous. House Speaker Nancy Pelosi explains:

It’s about jobs, jobs, jobs. It’s about promoting commerce. It’s about clean air, clean water, so therefore a public health issue. It’s a quality of life issue, getting people out of their cars not being on the road so much. And in every way, it is a safety issue.

The jobs are to be created “immediately,” Pelosi and Senate Democratic leader Charles Schumer clarified in a joint statement.

There is reason to doubt that increased federal spending on infrastructure would increase employment on net. With the unemployment rate already at its lowest level since 1969, such spending could simply redeploy labor that is already active. If the bill did stimulate the economy significantly, it would also make the Federal Reserve more likely to resume its course of raising interest rates, leaving us roughly where we started.

Would new spending at least help us “rebuild our crumbling roads, aging bridges, crowded airports and other infrastructure,” as the White House hopes? Maybe. But the condition of our infrastructure is already better than the political rhetoric suggests. The percentage of structurally deficient bridges has, for example, been falling for decades.

While money could certainly buy improvements, which could enhance the economy’s productivity, the political obstacles to directing the money in the most useful ways would be formidable. New building is more politically attractive than repairing or maintaining existing infrastructure even when the latter makes more sense. Such incentives will tend to warp spending decisions in many ways.

President Trump illustrated the pitfall in his State of the Union address last year: “We will build gleaming new roads, bridges, highways, railways, and waterways across our land.” If he had said, “we will refurbish the power grid,” it wouldn’t have had quite the same ring, even if that would have been a more intelligent use of money.

The many policy aims that the Democratic leaders have identified also militate against the rational allocation of resources. (Ryan Bourne of the Cato Institute counts nine distinct goals.) The projects that create jobs “immediately” might not be the ones with the best long-term payoff. Making sure that businesses owned by women, minorities and veterans get contracts also means not focusing single-mindedly on value for the dollar.

In theory, then, a burst of infrastructure spending could accomplish some good for the country. There are reasons to doubt it would work out that way in practice. One of those reasons is that neither the president nor the congressional Democrats seem to be thinking through the issues clearly.