China Slips Into Deflation in Warning Sign for World Economy

HONG KONG—China’s consumer prices tipped into deflationary territory in July for the first time in two years, as a deepening economic malaise in the world’s second-largest economy enters a potentially dangerous new phase.

The data released Wednesday adds to a darkening picture for China, where the economic recovery has been losing momentum because of a host of problems. A drop in exports is accelerating, youth unemployment has hit record highs and the housing market is mired in a protracted downturn.

Now, the country is suffering an unusual bout of falling prices on a range of goods, from commodities such as steel and coal to daily essentials and consumer products such as vegetables and home appliances. It is the opposite of what happened in most of the rest of the world when Covid-19 restrictions eased, with many countries still trying to tame inflation.

Chinese consumer prices fell 0.3% in July compared with a year earlier. This could be transitory, however. Stripping out volatile food and energy prices, so-called core inflation rose to 0.8% in July, the highest level since January, from 0.4% in June.

The danger is that if the expectation of falling prices becomes entrenched, it could further sap demand, exacerbate debt burdens and even lock the economy into a trap that will be hard to escape using the stimulus measures Chinese policy makers have traditionally turned to.

Deflation is particularly risky for countries with high debt burdens such as China, since it will add to debt servicing costs for borrowers and likely prompt them to spend and invest less.

China’s total debt reached nearly three times the size of its gross domestic product in 2022, higher than that in the U.S., according to the Bank for International Settlements.

“The reality looks increasingly grim,” said Eswar Prasad, a Cornell University economist who once headed the International Monetary Fund’s China division. “The government’s approach of downplaying the risks of deflation and stalling growth could backfire and make it even harder to pull the economy out of its downward spiral.”

For now, Chinese policy makers say they are sanguine about falling prices, dismissing suggestions that deflation is here to stay.

Dong Lijuan, a statistician at China’s National Bureau of Statistics, on Wednesday said consumer prices will likely rebound gradually later this year as the high base effect begins to fade.

China’s predicament stands in contrast to those of the U.S. and other Western countries, where soaring inflation prompted central banks, including the Federal Reserve, to raise interest rates in an effort to cool growth without triggering a recession.

In the U.S., consumer prices rose 3% in June compared with a year earlier, the slowest pace of increase in more than two years, while annual inflation in the European Union stood at 6.4%, easing from 7.1% in May.

Falling prices in China may help ease inflationary pressure elsewhere around the globe, as Chinese exports become cheaper. They also pose a risk: a flood of low-price Chinese-made goods could hurt foreign competitors and lead to job losses in developed countries.

For China, the absence of inflation reflects an imbalance in the economy characterised by ample supply and dormant domestic demand, which economists say is partly the result of Beijing’s paltry social security support for households.

Wang Lei, who works at a video gaming company in Beijing, said his and his wife’s overall expenditures have fallen compared with last year’s. Seeing colleagues and friends get laid off spooked him into reining in any unnecessary expenditures, apart from renovating an apartment that he purchased two years ago.

“It’s better to save more and be cautious now,” said 40-year-old Wang. “The economic outlook is not certain.”

China’s central bank has trimmed interest rates several times this year, but fiscal and monetary policy makers haven’t launched any larger-scale stimulus measures, in part because of constraints such as elevated debt levels.

Prices charged at the factory gate, which have been contracting on a year-over-year basis since last October, fell 4.4% in July from a year earlier, narrowing from June’s 5.4% decline, according to data published by China’s National Bureau of Statistics on Wednesday.

But it was the consumer-price reading, which has remained positive even as producer prices turned negative, that marked the bigger shift.

After flatlining in June, last month’s 0.3% decrease in consumer prices represents the first negative print since February 2021, when the reading was thrown off by year-over-year comparisons to the early days of the pandemic when supply chains and food prices were in disarray.

Apart from a single month in the first year of the pandemic, both consumer and producer prices haven’t been in deflationary territory at the same time since 2009, at the depths of the global financial crisis.

July’s negative consumer inflation result was mainly driven by a drop in food prices from a year earlier, when food prices were pushed up by extreme weather conditions, a spokeswoman for China’s statistics bureau said Wednesday. Prices of pork, a staple of Chinese dinner tables, plunged 26% in July from a year earlier. Vegetable prices also fell last month.

Even so, consumer inflation isn’t likely to pick up much this year, economists say. The reason is consumer confidence, or rather the lack of it, as households continue to feel the lingering impact of three years of Covid uncertainty, regulatory uncertainty and ongoing concern about the health of the property market. The real-estate sector, one of China’s main drivers of growth for decades, is in a deep funk, with fresh worries stoked this week by default concerns around one of China’s biggest property developers.

Unlike many countries in the West, where government cash handouts to consumers during the pandemic fuelled a spending boom on physical goods such as furniture and personal electronics, Beijing so far has offered no such direct support to its households.

On top of that, a renewed downturn in the housing market has curbed Chinese consumers’ appetite for consumption, since many households have treated apartment units as their main store of wealth, and are highly sensitive to fluctuations in home prices, said Wei Yao, chief China economist at Société Générale.

“The problem is there’s no obvious driver to power recovery at the moment,” she said.

Even if consumer prices begin to pick up again, Chinese factory owners and exporters are likely to struggle with pricing power for some time, eroding their profit margins and hurting their willingness to expand production or hire more workers.

While producer price deflation eased in July, the 4.4% drop was worse than 4.1% expected by economists polled by the Journal.

During the pandemic, many factories in China ramped up production to accommodate a surge of overseas orders. Now, as demand in the West fades, producers of automobiles, consumer goods and other products are being saddled with excess inventory, forcing many to slash prices to reduce stockpiles.

One manufacturer of robot vacuum cleaners based in the southern Chinese city of Shenzhen is looking to sell more overseas, in part because domestic rivals are offering cheaper options and the sluggish recovery in consumer demand has eroded sales at home, according to a company executive.

The ultimate challenge for Chinese policy makers is how to forestall a self-reinforcing spiral in which a fall in prices leads to reduced production, lower wages and suppressed demand.

Economists expect China’s central bank to lower interest rates further in the coming months, though many are skeptical that such moves alone can dispel deflationary pressures.

That is because confidence among businesses and households has been slow to recover, resulting in limited appetite for them to invest and spend more. Such an environment renders moderate stimulus measures largely ineffective, argues Arthur Budaghyan, chief emerging markets strategist at BCA Research.

“The Chinese government has to do something very big to confront deflation,” he said. “I don’t think they’ve done enough yet.”

—Grace Zhu and Xiao Xiao in Beijing contributed to this article.

Read the news, and it won’t take long to find a story about the latest feat of artificial intelligence. AI passed the bar exam! It can help diagnose cancer! It “painted” a portrait that sold at Sotheby’s for $1 million!

My own great hope for AI: that it might simplify the everyday problem of meal planning.

Seem a bit unambitious? Think again. For more than two decades as a food writer, I’ve watched families struggle to get weeknight meals on the table. One big obstacle is putting in the upfront time to devise a variety of easy meals that fit both budget and lifestyle.

Meal planning poses surprisingly complex challenges. Stop for a minute and consider what you’re actually doing when you compile a weekly grocery list. Your brain is simultaneously calculating how many people are eating, the types of foods they enjoy, ingredient preferences (and intolerances), your budget, the time available to cook and so on. No wonder so many weeknights end with mediocre takeout.

Countless approaches have tried to “disrupt” the meal-plan slog: books, magazines, apps, the once-vaunted meal kits, which even delivered the ingredients right to your door. But none could offer truly personalized plans. Could AI succeed where others failed?

The Weird Old Days

I conducted my first tests of AI in the summer of 2023, with mixed results. Early versions of Open AI’s ChatGPT produced some usable recipes. (I still occasionally make its gingery pork in lettuce wraps.) But the shopping lists it created were sometimes missing an ingredient or two. Bots! They’re just like us!

Eager to please, the chatbot also made some comical culinary suggestions. After I mentioned I had a blender, it determinedly steered me to use the blender…for everything, including fried rice, which it recommended I whiz into a kind of gruel. While it provided a competent recipe for pasta with zucchini, thyme and lemon, it thought it would be brilliant to add marshmallows, which I’d mentioned I had in my pantry, to the sauce. As a friend said: “If you’re having AI plan the recipes for you, it should definitely be doing something better than what your stoned friend would make you at two in the morning.”

Early AI could plan meals for the week, but required a lot of hand-holding. Like an overconfident intern.

More Fully Baked

Eighteen months after those first attempts—about 1,000 years in AI time—I was ready to try again. In January, DeepSeek AI, a Chinese chatbot, grabbed headlines around the world for its capabilities and speed (and potential security risks). There were also new and improved versions of the chatbots I’d found wanting.

This time, I decided to experiment with ChatGPT, Anthropic’s Claude and DeepSeek. (To see how they compared to one another, see “Bytes to Bites,” below.)

From my first AI rodeo, I knew to use short, direct sentences and get very specific about what I wanted. “Think like an experienced family recipe developer,” I told DeepSeek. “Create a week’s worth of dinners for a family of four. At least three meals should be vegetarian. One person doesn’t like fresh tomatoes. We like Italian, Japanese and Mexican cuisine. All meals should be cooked within 60 minutes.”

For the next 24 seconds, the chatbot “reasoned” through my request, spelling out concerns as I watched, rapt: Would the person who doesn’t like fresh tomatoes eat marinara sauce? Black bean and sweet potato tacos are a nice vegetarian entree, but opt for salsa verde to avoid tomatoes. Lemony chicken piccata is fast, but serve with broccolini. It was…amazing. The consolidated shopping list the chatbot provided was error free.

I tried the same prompt with Claude and ChatGPT, with curiously similar results. With all the options in the world, both bots suggested black bean and sweet potato tacos, and chicken piccata. The recipes’ instructions varied, as did suggested side dishes.

Relationship Counselling

I decided to write a more detailed request. “Long prompts are good prompts,” said Dan Priest, chief AI officer for consulting firm PwC in the U.S. The more information you provide, the more the AI can “align with your expectations.” Don’t try to get everything right the first time, Priest said: “Have a conversation.”

Good advice. I admit, when I first began my tests, I was searching for weak spots. But I learned it’s crucial to refine requests. As Priest said, AI will consider your various demands and make trade-offs—though perhaps not the ones you’d make.

So I started talking to AI. I said I like to cook with seasonal ingredients—that my dream dinner is a night at Chez Panisse, the Berkeley restaurant where chef Alice Waters redefined rustic-French cooking as California cuisine. Within seconds I had gorgeous recipes for spring lamb chops with fresh herbs, and miso-glazed cod with spring onions and soba. When I asked to limit the budget to $200, the bot swapped in pork for pricey lamb and haddock for cod. I requested meals that adhered to guidelines from the American Heart Association, and recipes that used only what was in my fridge. No problem.

But would the recipes work? Chatbots don’t have experience cooking; they are Large Language Models trained to predict what word should follow the last. As any cook knows, a recipe that reads well can still end in disaster. To my surprise, the recipes I tested worked exactly as written by the chatbots—and took no longer than advertised. Even my luddite husband called Claude’s rigatoni with butternut squash, kale and brown butter “a keeper.”

As yet no chatbot can compete with Alice Waters—or my husband, for that matter—in the kitchen. (For more on that, see “How Do Real Cooks Rate AI?” below.) But I’ll keep asking AI to, say, create shopping lists for recipes I upload, or come up with a recipe for what I happen to have in the refrigerator—as long as I’m there to whisper in the chatbot’s ear.

Bytes to Bites

Which chatbot is right for your kitchen?

Any of the three chatbots we tested can deliver a working meal plan—if you know how to talk to it. My personal pick was Anthropic’s Claude, for its intelligent tone and creativity, followed by DeepSeek AI for its “reasoning.” AI “agents” such as Open AI’s Operator, can, in theory, order the food needed to cook your recipes, but the consensus is they need a bit more time to develop.

Open AI’s ChatGPT • I had quibbles with ChatGPT’s first round of recipes. The seasoning skewed bland—only one tablespoon of soy sauce for a large veggie stir fry. It had me start by sautéing my chicken piccata, which then got cold while the pasta cooked. ChatGPT was also annoyingly chipper in its interactions. Still, with a few requested revisions, its lemon and pea risotto was perfection.

DeepSeek AI • I was impressed with this chatbot’s “reasoning” and the way it balanced sometimes-conflicting requests. Its recipes were seasonal (without prompting) and easy to follow; its shopping list, error free. Its one unforgivable mistake: presuming a paltry number of stuffed pasta shells would feed my hungry family. Some have voiced security concerns over using a Chinese chatbot; I felt comfortable sharing my meal preferences with it.

Anthropic’s Claude • I felt like Claude “got” me. This encouraged me to chat with it, resulting in recipes I liked and that worked, like a Mexican pozole for winter nights. This bot does need prompting; its initial instructions for brown butter and crispy sage leaves would have flummoxed an inexperienced cook. But when I suggested it offer step-by-step instructions, it praised me, which made me think it was even smarter.

Try This at Home

Have a conversation. Even a very specific meal-planning prompt requires AI to make assumptions and choices you might oppose. Ask it to revise. Add additional requirements. Follow up for more specific instructions. Time spent up front will deliver a more successful plan.

Role-play. Ask AI to think like a cook whose food you enjoy. (Told I like writer Tamar Adler’s recipes, Claude instantly offered one for wild mushroom bread pudding.) If you aren’t a skilled cook, it’s probably unwise to ask AI to mimic a three-star chef. Instead, ask it to simplify recipes inspired by your idol.

Read carefully and use common sense. It is always important to read through a recipe before you shop or set up in the kitchen, and this is especially true with AI. Recipes are invented on the fly and not tested. Ask for clarification if necessary, or a rewrite based on your skills, equipment or time.

Ask for a consolidated shopping list. In seconds, AI can aggregate the ingredients for your recipes into a single grocery list. Ask for total pounds or number of packages needed. (This saves you having to figure out, for example, how many red peppers to buy for 2 cups diced.)

Request cook times and visual cues. A good recipe writer lets you know how things will look or feel as they cook. Ask AI for the same. This will improve a vague “Bake for 20 minutes” to “bake for 20 minutes or until golden brown and the cake springs back to the touch.”

How Do Real Cooks Rate AI?

We asked AI to create dishes in the style of three favourite cooks, which it does base on text from the Internet and elsewhere it’s been trained on. And then we asked the cooks to judge the results. Verdict: The recipes didn’t reflect our panel’s expertise or attention to detail. Seems AI can’t replace them—yet.

Tamar Adler undefined Trained to cook at seminal restaurants including Prune and Chez Panisse; food writer, cookbook author, podcaster

AI dishes inspired by Tamar: Winter Squash and Wild Mushroom Bread Pudding; Braised Lamb Shoulder With White Beans and Winter Herbs; Pan-Roasted Cod With Leeks and Potatoes

Assessment: “Superficially, the recipes seem great and like recipes I would write.”

Critiques: “So much of everything I’ve written has been geared toward helping cooks build community and capability. Here, a cook is neither digging in and learning by trying and failing and repeating and growing; nor are they talking to another person, exchanging advice, smiles, jokes, ideas, updates.”

GRADE: C

Nik Sharma undefined Molecular biologist turned chef; editor in residence, America’s Test Kitchen; cookbook author

AI dishes inspired by Nik: Black Pepper and Lime Dal With Crispy Shallots; Roasted Spring Chicken With Black Cardamom and Orange; Roasted Winter Squash and Root Vegetables With Maple-Miso Glaze

Assessment: “A bit creepy. It’s trying too hard to imitate me but leaving out my intuition and propensity to experiment.”

Critiques: “Ingredients are not listed in order of use, and quantities and cook times are off. Black cardamom would kill that chicken. Also: I always list volumes for liquids and weights, whenever possible.” (AI did not—but you could ask it to!)

GRADE: C

Andrea Nguyen undefined Leading expert on the cuisine of Vietnam, cookbook author, cooking teacher, creator of Viet World Kitchen

AI dishes inspired by Andrea: Quick Lemongrass Chicken Bowl; Winter Vegetable Banh Mi With Spicy Mayo; Quick-Braised Ginger Pork with Winter Citrus

Assessment: “Machine learning is good for certain things, like getting factual questions answered. AI mined my content near and far, and got some things right but not others. Good recipes contain nuances in instructions that offer visual and taste cues.”

Critiques: “Quantities were off—often way off. The rice bowl is only good for a desperate moment. The ginger pork is an awful mash up of ideas. Yuck.”

GRADE: C/C+