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IMF sees less severe global contraction but trouble in emerging markets – The Globe and Mail

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A man wearing a face mask walks in Madrid on Oct. 7, 2020.

Bernat Armangue/The Associated Press

Forecasts for the global economy are “somewhat less dire” as rich nations and China have rebounded quicker than expected from coronavirus lockdowns, but the outlook for many emerging markets has worsened, the International Monetary Fund said on Tuesday.

The IMF forecast a 2020 global contraction of 4.4 per cent in its latest World Economic Outlook, an improvement over a 5.2 per cent contraction predicted in June, when pandemic-related business closures reached their peak.

The global economy will return to growth of 5.2 per cent in 2021, the IMF said, but the rebound will be slightly weaker than forecast in June, partly due to the extreme difficulties for many emerging markets and a slowdown in the reopening of economies due to the continued spread of the virus.

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Gita Gopinath, the IMF’s chief economist, said some US$12-trillion in fiscal support and unprecedented monetary easing from governments and central banks had helped to limit the damage from the pandemic and support must be maintained.

Even then, ending the worst economic crisis since the Great Depression of the 1930s depends on conquering the virus, she said in a news conference.

“The virus is resurging with localized lockdowns being reinstituted,” Gopinath said. “Now, if this worsens and prospects for treatments and vaccines deteriorate, the toll on economic activity would be severe and likely amplified by severe financial market turmoil”

She warned of a divergent path between wealthier countries and China, which are recovering more quickly, and poorer countries that “are headed towards worse futures than advanced economies.”

The IMF’s new forecast for Canada calls for GDP to contract by 7.1 per cent in 2020 – below the average among advanced economies of 5.8 per cent. The new projection is a substantial upgrade from the agency’s June call of 8.4 per cent, but it’s considerably lower than the most recent estimates from Canadian private-sector economists, who expect that GDP will decline by slightly less than 6 per cent this year.

The IMF predicted that Canada’s economy will enjoy an oversized rebound in 2021 of 5.2 per cent, a 0.3-percentage-point improvement from the June forecast, and well above the advanced-economy average of 3.9 per cent.

The IMF projected the United States will see a 4.3 per cent contraction in its 2020 gross domestic product, considerably less severe than the 8% contraction forecast in June.

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But the U.S. rebound next year will be somewhat weaker at 3.1 per cent growth – a forecast that assumes no additional federal government aid beyond around US$3-trillion approved by Congress in March.

The eurozone’s economy will shrink by 8.3 per cent in 2020, an improvement from a 10.2 per cent contraction predicted in June, but there is wide divergence within the group, the IMF said. Export powerhouse Germany will see a contraction of 6 per cent this year, while Spain’s economy, more dependent on tourism, will contract 12.8 per cent. The eurozone will resume growth of 5.2 per cent in 2021, the IMF said.

China, which saw a strong early reopening and rebound from the pandemic, will be the only economy to show positive growth in 2020, of 1.9 per cent – nearly double the rate predicted in June – and reach 8.2 per cent growth in 2021, its highest rate in nearly a decade, the IMF said.

China, where the coronavirus first surfaced late last year, had reopened most of its economy by April and has seen strong demand for exports of its medical supplies and technology products needed to aid remote working, the IMF said.

But emerging markets other than China will see a contraction of 5.7 per cent in 2020, worse than the 5 per cent predicted in June. The IMF said the virus was continuing to spread in large countries including India and Indonesia, and those economies are far more dependent on hard-hit sectors including tourism and commodities as well as on remittances and other sources of external finance.

The IMF also said economic ‘scarring’ from job losses, bankruptcies, debt problems and lost schooling will hold back medium-term global growth after 2021 to about 3.5 per cent, with a cumulative loss in output of up to US$28-trillion from 2020 to 2025 compared to pre-pandemic growth paths.

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With a file from The Globe’s Dave Leeder

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What would delayed election results mean for the economy? – Marketplace

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It’s likely we won’t know who won the presidency on Election Day this year, and some people are concerned about the possibility of a contested election. Last week, Fitch Ratings wrote in a report that it will be watching the election for “any departure” from the U.S.’s history of accepting election results and the orderly transition of power. If there’s any departure from this norm, it could affect the country’s AAA credit rating, which influences the interest rate the U.S. pays on its national debt.

All the uncertainty surrounding this presidential election could affect the economy in other ways, too. “Marketplace” host Kai Ryssdal talked with Wendy Edelberg, a senior fellow at the Brookings Institution and director of its Hamilton Project, about what might happen. The following is an edited transcript of their conversation.

Kai Ryssdal: So broad brush, lay it out for me. We have been told that we’re probably not going to know who won the election on election night. What do you think that means writ large for the American economy in the next two months?

Wendy Edelberg: I suspect it means that it will take too long to get the kind of fiscal support that we need to support this really fragile recovery. And that frustrates me because doing it now is too late. Doing it a month from now is much too late.

Ryssdal: So I will stipulate that that is a thing that could or will happen on election night or afterward. What happens if it becomes contested and challenged and acrimonious?

Edelberg: So right now, measures that tell us how uncertain things are for businesses, for investors, for households, those measures are through the roof. And uncertainty is generally really bad for economic activity. It prevents firms from putting investments in place and expanding and putting in hiring decisions. And it prevents households from making decisions about the future. And we’re just going to create one more really significant headwind if November and December, for that matter, is that much more an environment of uncertainty, layered on top of the immense uncertainty we have because of the pandemic.

Ryssdal: I say on this program all the time, and regular listeners know this, the stock market is not the economy. I do wonder though, beyond the real economy measures that you have laid out in that answer, what do you imagine stock markets will do? Just because a lot of people look at that as an indicator.

Edelberg: So you’re absolutely right. The stock market is not the economy and the stock market is giving us all sorts of incorrect signals right now. And it wouldn’t really surprise me if it continued to give us really incorrect signals. As much as uncertainty and a contested election would be really bad for small businesses, for individual households, it may well be good for some of the large firms that are driving the stock market gains. That’s really hard to know. And I’m also guessing that people who hold equities are pretty aware of the issues that you and I just talked about. And so my thought is that that’s mostly baked into the stock market. And so those investors are expecting things to be pretty chaotic for a couple of weeks after the election, and I would expect things to basically move sideways, which is to say the flip side, that if we get a clear outcome, and uncertainty is largely resolved very quickly, yeah, I can imagine that being fabulous for the stock market.

Ryssdal: Huh. Let me point out that if he loses, President Trump will still be president for two and a half months, right, Election Day to the 20th of January. Contested election aside, challenged election aside, random tweets aside, he’s still the president with full executive authority to influence this economy.

Edelberg: So maybe this means that with all of these issues leading up to the election off the table, because that uncertainty is resolved, I don’t know, maybe we can hope, maybe policymakers will then come together and do the right thing. I’ve been asked before, “What would you tell policymakers on January 20th to do to support our economy?” And the first thing I’ll say is get in a time machine and go back six months to support the economy then. So I have grave concerns about policymakers waiting until January to pass the kind of fiscal support that the economy needs right now.

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Algorithms Are Making Economic Inequality Worse – Harvard Business Review

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Executive Summary

There is a code ceiling that prevents career advancement — irrespective of gender or race — because, in an AI-powered organization, junior employees and freelancers rarely interact with other human co-workers. Instead, they are managed by algorithms. As a result, a global, low-paid, algorithmic workforce is emerging. You will increasingly find a gap between top executives and an outer fringe of transient workers, even within organizations. Whether in retail or financial services, logistics or manufacturing, AI-powered organizations are being run by a small cohort of highly paid employees, supported by sophisticated automation and potentially millions of algorithmically managed, low-paid freelancers at the periphery. Job polarization is only part of the problem. What we should really fear is the algorithmic inequality trap that results from these algorithmic feedback loops.

HBR Staff/Oleksandr Shchus/Getty Images

The risks of algorithmic discrimination and bias have received much attention and scrutiny, and rightly so. Yet there is another more insidious side-effect of our increasingly AI-powered society — the systematic inequality created by the changing nature of work itself. We fear a future where robots take our jobs, but what happens when a significant portion of the workforce ends up in algorithmically managed jobs with little future and few possibilities for advancement?

One of the classic tropes of self-made success is the leader who comes from humble beginnings, working their way up from the mailroom, the cash register, or the factory floor. And while doing that is considerably tougher than Hollywood might suggest, bottom-up mobility was at least possible in traditional organizations. Charlie Bell, former CEO of McDonalds, started as a crew member flipping burgers. Mary Barra, chairman and CEO of General Motors, started on the assembly line. Doug McMillon, CEO of Walmart, started in a distribution center.

By comparison, how many Uber drivers do you think will ever have the chance to attain a managerial position at the company, let alone run the ride-sharing giant? How many future top Amazon executives will start their careers by delivering packages or stacking shelves? The billionaire founder and CEO of Instacart may have personally delivered the company’s first order, but how many others will follow in his footsteps?

Insight Center

Here’s the problem: There’s a “code ceiling” that prevents career advancement — irrespective of gender or race — because, in an AI-powered organization, junior employees and freelancers rarely interact with other human co-workers. Instead, they are managed by algorithms.

In this new era of digitally mediated work, there is typically a hierarchical information flow, in which the company decides the information they choose to share with you. Unlike driving a taxi, where there is open radio communication between drivers and the dispatch operator, and among the drivers themselves, when you work for Uber or Lyft, the content of your interactions is the output of an optimization function designed to maximize efficiency and profit.

To be managed algorithmically is to be subject to constant monitoring and surveillance. If you are one of the millions of food delivery workers in China working for Meituan or Ele.me, an algorithm determines how long it should take you to drop off an order, reducing your pay if you fail to meet your deadline. Similarly, employees in Amazon distribution centers are also carefully tracked by algorithms; they must work at “Amazon pace” — described as “somewhere between walking and jogging.”

When you are a gig economy worker, it is not only your AI bosses that should concern you; your co-workers are often also your competition. For example, Chicago residents who live near Amazon’s distribution points and Whole Foods stores reported the strange appearance of smartphones hanging from trees. The reason? Contract delivery drivers were desperate to trump their rivals for job assignments. They believed that hanging their devices near delivery stations would help them game the work allocation algorithm; a smartphone perched in a tree could be the key to getting a $15 delivery route mere seconds before someone else.

Work has been changing over the last few decades. The labor market has grown increasingly polarized, with middle-skill jobs being eroded relative to entry-level, low-skill work, and high-level employment that requires greater skill levels. The Covid-19 crisis has likely accelerated the process. Since 1990, every U.S. recession has been followed by a jobless recovery. This time, as AI, algorithms, and automation reshape the workforce, we may end up with something worse: a K-shaped recovery — where the prospects of those at the top soar, and everyone else sees their fortunes dive.

The new digital divide is a widening gap between workers with access to higher education, leadership mentoring, and job experience — and those without. In my recent book, The Algorithmic Leader, I explore one particularly dire scenario: a class-based divide between the masses who work for algorithms, a privileged professional class who have the skills and capabilities to design and train algorithmic systems, and a small, ultra-wealthy aristocracy, who own the algorithmic platforms that run the world.

A global, low-paid, algorithmic workforce is already emerging. In Latin America, one of the fastest-growing startups is Rappi, a mix of Uber Eats, Instacart, and TaskRabbit. Customers in cities like Bogotá and Mexico City pay about $1 an order or a flat $7 a month. In return, they can access a vast on-demand network of couriers who deliver food, groceries, and just about anything else you want. Amazon has an informal network of delivery people, called Amazon Flex, ready to drop packages right to your door — and soon even hand them to you in the street, place them in your car trunk, or open the door to your house and store your groceries in your fridge.

In his 1930 lecture Economic Possibilities for Our Grandchildren, John Maynard Keynes predicted that by around 2030, the production problem would be solved, and there would be enough of everything for everyone. The catch, however, is that machines would cause technological unemployment. The scenario that Keynes didn’t fully anticipate was our present case of high technological employment, with an accompanying degree of high inequality.

The workforce is changing; so too is the workplace. You will increasingly find a gap between top executives and an outer fringe of transient workers, even within organizations. Whether in retail or financial services, logistics or manufacturing, AI-powered organizations are run by a small cohort of highly paid employees, supported by sophisticated automation and potentially millions of algorithmically managed, low-paid freelancers at the periphery.

Job polarization is only part of the problem. What we should really fear is the algorithmic inequality trap that results from feedback loops. Once you are a gig economy worker reliant on assignments meted out by your smartphone, not only are there few opportunities for promotion or development, but other algorithms may further compound your situation. Think of it as a digital poorhouse. With their earnings and work assignments held hostage by market fluctuations, the new AI underclass may be penalized by automated systems that determine access to welfare, lending, insurance, or health care, or that set custodial sentences.

Nevertheless, it is dangerous to seek quick fixes for a problem that has yet to fully manifest, especially if it means grafting 20th-century worker protections onto 21st-century business models. Already, governments and regulators supported by populist platforms are focused on attacking global digital giants. They seek to prevent them from avoiding tax liabilities and are working to regulate their freelance workforce’s labor conditions, to apply restrictions on their collection of data, and even to tax their robots. Some of these ideas have merit. Others are premature, or worse, just political theater.

The longer-term solution to algorithmic inequality will not lie in just taxation and regulation, but rather in our ability to provide an adequate education system for the 21st century. Rebooting education will not be easy. Rather than looking for ways to use AI in teaching, the real question is: How do we teach people to harness machine intelligence in their careers? And how do we teach people to be prepared for a lifetime of constant learning and retraining?

Business leaders have a crucial role to play. Not only should they carve out channels of communication, feedback, and advancement for freelancers at the edge of their organizations, they need to get serious about retraining and community engagement. For example, AT&T is retraining half of its workforce, while Cisco, IBM, Caterpillar, McKinsey, and JPMorgan are offering internships to high school students and are working with local schools to upgrade their teaching curriculums. These are all good initiatives, but more will be needed — not just for social cohesion, but also to ensure the diversity and agility of tomorrow’s workforce.

We need a better plan for the future. Without one, the algorithmic inequality trap will be a story told not in statistics and wealth ratios, but in distress signals — smartphones hanging from trees, tent cities for the homeless, and human couriers scanning the skies for the delivery drones that spell their impending end.

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Next Saskatchewan government will have to juggle budget, pandemic economy – Global News

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Saskatchewan voters are facing different options of how the province should recover from the economic downturn caused by the COVID-19 pandemic.

The COVID-19 pandemic has led to the largest global economic crisis since the Great Depression.

Economists agree an economic stimulus is the best first move to help businesses rebound as many continue to operate with safety precautions.

“Some of the (historical) lessons we’ve learned is that temporary spending seems to work pretty well and allows you to get your financial house back in order,” University of Regina’s Jason Child’s said.

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A recent Scotiabank report found Saskatchewan’s economy is in a relative position of strength despite those precautions.

Last week’s report noted oil production was down 8.6 per cent, but there has been a 33 per cent increase in agricultural crop exports compared to this time last year.

Those exports combined with a bump in the potash and uranium sectors has helped ease some of the concerns.

In August, the province reported its deficit for this year went from $2.4 billion to $2.1 billion.

Read more:
Saskatchewan’s economy will return to pre-coronavirus level in 2022: finance minister

A Scotiabank senior economist believes one of the ultimate tests in order for the economy to flourish is how well the province handles the virus.

“How businesses respond to it, how households respond to it and ultimately to support growth for the longer run, this is the most important thing to get under control,” Marc Desormeaux said.

Before the campaign, the province committed to spending $7.5 billion in infrastructure over two years, which included a $2 billion stimulus package after pandemic measures kicked in.

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Read more:
Saskatchewan tops up economic stimulus package by $2 billion

The Saskatchewan Party has made several promises to help spur economic recovery including a temporary elimination of the business tax rate, and decreasing power bills by 10 per cent.

Leader Scott Moe also promised a balanced provincial budget by 2024.

The NDP’s Ryan Meili has not committed to a timeline to balance the budget.

The New Democrats have promised to help the economic recovery by introducing a $15 per hour minimum wage and a Saskatchewan first procurement policy to offer public contracts to workers living in the province.

Read more:
Saskatchewan election tracker 2020: Here’s what the parties are promising

Childs noted while striving for a balanced budget in that time span is a good goal to set, the province shouldn’t be committed to it noting circumstances can change fairly quickly.

He added simultaneously making sure the government’s cheque book is stable and the province’s economy is in a better position will be a task for whoever forms government.

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The associate professor said one can suffer at the hands of the other, but both can’t afford to take sharp downward trends.

Read more:
Saskatchewan will shut down parts of economy should daily COVID-19 cases continue to rise

Childs went on to say the shotgun approach of providing funding to all sectors is a common one and will help temporarily but ensuring long-term growth is generally more stable when it comes from grassroots initiatives.

“If you’re trying to grow an economy, that’s a different story. And again that’s going to require a much defter touch than just trying to keep the lights on,” he said.

Childs said spending during an economic crisis makes sense, but the real direction for the budget and economy will be more clear once Saskatchewan is on the backside of the virus.

In August the province reported its debt could reach $33.6 billion by 2024-2025.

© 2020 Global News, a division of Corus Entertainment Inc.

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