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Yahoo
21-05-2025
- Business
- Yahoo
Opinion - Looking back at election forecasts
Predicting future events is difficult. The Babylonians discovered this nearly 2,700 years ago, when they began trying to predict the weather. We have been working to improve those forecasts ever since. Lives, crops and more depended on them. It took until 1859 for a country (Britain) to offer its first official weather forecast (for shipping, the lifeblood of the maritime empire). After millennia of refinement, just how accurate are weather forecasts? The National Oceanic and Atmospheric Administration tells us that five-day forecasts are accurate nearly 90 percent of the time. Ten-day forecasts and longer are only correct about half the time. When it comes to where hurricanes will make landfall, even a 48-hour forecast has a margin of error around 50 nautical miles. Humans can be even less predictable than weather patterns. Yet here, too, the stakes can be sky-high. Billions, if not trillions, of dollars are at stake in economic forecasts. Corporations, stock market investors and even the Federal Reserve rely on them to make consequential decisions. Two Berkeley business school researchers analyzed responses to the Survey of Professional Forecasters, conducted by the Federal Reserve Bank of Philadelphia since 1968. They found forecasters were correct a mere 23 percent of the time. To take just one recent example, economists predicted U.S. gross domestic product would grow by 1.3 percent in 2024. In fact, the growth rate was more than twice the forecast. A dear friend who spent a few years working at a prominent econometric forecasting firm decades ago, reported their staff motto was 'we predicted 10 of the last three recessions.' Election forecasting has a shorter history. It is both more difficult and less consequential, since the forecasts have no effect on the real world. But it has grown into a cottage industry. Given the difficulties, it is surprising just how accurate these forecasts have proven to be, especially when they employ data collected many months prior to the event itself. The American Political Science Association recently published a journal with a dozen forecasts all completed well before the election, each of which used somewhat different data and varying methodologies. Most of them foresaw the close popular vote finish. The high-end prediction for then-Vice President Kamala Harris's share of the popular vote was 54.5 percent and the low-end was 45 percent — the first based on online betting data, the second on the expectations of ordinary people, techniques that I would caution against. Still, most of the predictions clustered within a few points of the actual results. Of the 11 entrants who forecast the popular vote, five foresaw victory for President Trump and six a win for Harris. Five predicted an Electoral College victory for Trump, whereas three wrongly anticipated that Harris would win the electoral vote. As regular readers would expect, the predictions based on fundamentals (the economy, partisanship, presidential approval) tended to be the most accurate. As I have described before, Ray Fair's model, the longest running such forecast (but not included in the American Political Science Association collection), and based largely on hard economic indicators, was within a quarter point of the actual result. Charles Tien and Michael Lewis-Beck added presidential approval to a smaller array of economic variables, producing a forecast also less than a point off the mark. Models employing poll data tended to be slightly farther off. I have previously quoted statistician George Box saying that 'all models are wrong. Some are useful.' Models are (over-) simplifications of the world. To be wholly right, they'd have to be as rich, complex, and confusing as the world itself. But these simplifications can tell us something about the 'whys' of this and other presidential elections. For example, despite the conventional wisdom asserting elections are about the future, most of the accurate models use retrospective information about the past, not data about future expectations. None of these models use information about the candidates' personalities, abilities or issue positions. Which is to say, the 2024 election was destined to be close, but any Democrat would have had a difficult time winning it. The situational deck was stacked against us, and neither candidate had a secret formula for greatly exceeding expectations. An exceptional candidate backed by an exceptional campaign may have been able to overcome the odds, but that's exactly what would have been required — beating the odds. Would a different candidate, or one who had faced a primary, have done better? We have no way of knowing, but there is no evidence or suggestion Harris blew a race that was hers to lose. Would former President Biden have done better or worse? Again, we cannot know, though one of the American Political Science Association modelers claims evidence that Biden himself would have done slightly worse than Harris did. It is no longer fashionable to quote Karl Marx, but he was right in saying that individual people 'make history, but not in circumstances of their own choosing.' Psychology teaches us that humans put too much weight on personal factors while underrating the power of circumstances and situations in shaping behavior. These models remind us that circumstances count for a lot and that the new science of presidential election forecasting stacks up pretty well, as predictions go. Mark Mellman is president of The Mellman Group a consultancy that has helped elect 30 U.S. senators, 12 governors and dozens of House members. He served as pollster to Senate Democratic leaders for over 30 years and is a member of the American Association of Political Consultants' Hall of Fame. Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
The Hill
21-05-2025
- Business
- The Hill
Looking back at election forecasts
Predicting future events is difficult. The Babylonians discovered this nearly 2,700 years ago, when they began trying to predict the weather. We have been working to improve those forecasts ever since. Lives, crops and more depended on them. It took until 1859 for a country (Britian) to offer its first official weather forecast (for shipping, the lifeblood of the maritime empire). After millennia of refinement, just how accurate are weather forecasts? The National Oceanic and Atmospheric Administration tells us that five-day forecasts are accurate nearly 90 percent of the time. Ten-day forecasts and longer are only correct about half the time. When it comes to where hurricanes will make landfall, even a 48-hour forecast has a margin of error around 50 nautical miles. Humans can be even less predictable than weather patterns. Yet here, too, the stakes can be sky-high. Billions, if not trillions, of dollars are at stake in economic forecasts. Corporations, stock market investors and even the Federal Reserve rely on them to make consequential decisions. Two Berkeley business school researchers analyzed responses to the Survey of Professional Forecasters, conducted by the Federal Reserve Bank of Philadelphia since 1968. They found forecasters were correct a mere 23 percent of the time. To take just one recent example, economists predicted U.S. gross domestic product would grow by 1.3 percent in 2024. In fact, the growth rate was more than twice the forecast. A dear friend who spent a few years working at a prominent econometric forecasting firm decades ago, reported their staff motto was 'we predicted 10 of the last three recessions.' Election forecasting has a shorter history. It is both more difficult and less consequential, since the forecasts have no effect on the real world. But it has grown into a cottage industry. Given the difficulties, it is surprising just how accurate these forecasts have proven to be, especially when they employ data collected many months prior to the event itself. The American Political Science Association recently published a journal with a dozen forecasts all completed well before the election, each of which used somewhat different data and varying methodologies. Most of them foresaw the close popular vote finish. The high-end prediction for Harris's share of the popular vote was 54.5 percent and the low-end was 45 percent — the first based on online betting data, the second on the expectations of ordinary people, techniques that I would caution against. Still, most of the predictions clustered within a few points of the actual results. Of the 11 entrants who forecast the popular vote, five foresaw victory for President Trump and six a win for Kamala Harris. Five predicted an Electoral College victory for Trump, whereas three wrongly anticipated that Harris would win the electoral vote. As regular readers would expect, the predictions based on fundamentals (the economy, partisanship, presidential approval) tended to be the most accurate. As I have described before, Ray Fair's model, the longest running such forecast (but not included in the American Political Science Association collection), and based largely on hard economic indicators, was within a quarter point of the actual result. Charles Tien and Michael Lewis-Beck added presidential approval to a smaller array of economic variables, producing a forecast also less than a point off the mark. Models employing poll data tended to be slightly farther off. I have previously quoted statistician George Box saying that 'all models are wrong. Some are useful.' Models are (over-) simplifications of the world. To be wholly right, they'd have to be as rich, complex, and confusing as the world itself. But these simplifications can tell us something about the 'whys' of this and other presidential elections. For example, despite the conventional wisdom asserting elections are about the future, most of the accurate models use retrospective information about the past, not data about future expectations. None of these models use information about the candidates' personalities, abilities or issue positions. Which is to say, the 2024 election was destined to be close, but any Democrat would have had a difficult time winning it. The situational deck was stacked against us, and neither candidate had a secret formula for greatly exceeding expectations. An exceptional candidate backed by an exceptional campaign may have been able to overcome the odds, but that's exactly what would have been required — beating the odds. Would a different candidate, or one who had faced a primary, have done better? We have no way of knowing, but there is no evidence or suggestion Vice President Kamala Harris blew a race that was hers to lose. Would former President Joe Biden have done better or worse? Again, we cannot know, though one of the American Political Science Association modelers claims evidence that Biden himself would have done slightly worse than Harris did. It is no longer fashionable to quote Karl Marx, but he was right in saying that individual people 'make history, but not in circumstances of their own choosing.' Psychology teaches us that humans put too much weight on personal factors while underrating the power of circumstances and situations in shaping behavior. These models remind us that circumstances count for a lot and that the new science of presidential election forecasting stacks up pretty well, as predictions go. Mark Mellman is president of The Mellman Group a consultancy that has helped elect 30 U.S. senators, 12 governors and dozens of House members. He served as pollster to Senate Democratic leaders for over 30 years and is a member of the American Association of Political Consultants' Hall of Fame.
The Guardian
24-04-2025
- Business
- The Guardian
Is a US recession on the horizon amid Trump's tariffs?
Imagine you are sailing a ship through dense fog, looking out for land. Your lookout spots species of birds typically found offshore. It now seems likely that you are approaching land, but it is impossible to know for sure until you see the coastline. If a US recession is land, the 'birds' are already swooping into view. But these sightings offer no guarantees of what lies ahead, only probabilities. An inverted yield curve, when the long-term interest rate falls to or below the short-term rate, is commonly considered to be a predictor of recession. The 10-year bond rate did fall below the three-month Treasury rate in March, although the two are now at about the same level. In any case, the yield curve does not actually tell us much. It simply reflects financial market expectations that the US Federal Reserve might cut short-term interest rates in the future, which in turn reflects expectations that economic activity might falter. Consumer confidence is a more direct indicator – particularly for predicting household demand. Two long-established measures of consumer confidence, conducted by the University of Michigan and the Conference Board, showed sharp declines in March, when Donald Trump's tariff threats began to materialise. The Michigan survey's index of consumer sentiment, which has been falling since the start of the year, plummeted another 11% on 11 April – well below the average in past recessions and the second-lowest level since records began in 1952. The Federal Reserve Bank of New York's survey of consumer expectations likewise reports that households' year-ahead expectations about their financial situations deteriorated in March. Similarly, business confidence – which guides firms' hiring and investment decisions – 'collapsed' on 4 April, not only in the US but globally, owing to uncertainty over Trump's 'reciprocal' tariffs. In seeking to determine whether a recession is imminent, one might also look to professional forecasts, about 50 of which are aggregated by the Blue Chip Financial Forecasts. Two other sources that aggregate forecasts are the Survey of Professional Forecasters and the Wall Street Journal. On 17 April, the latter showed a mean forecast of 0.44% annualised for the first quarter, and much higher recession probabilities than at the start of the year. But the WSJ and SPF surveys are published only once a quarter and can become stale rapidly. In any case, what people say may be less meaningful than where they put their money. Prediction markets tripled the odds they placed on recession after 3 March, when Trump applied 25% tariffs against Canada and Mexico, and 2 April, when he announced his 'reciprocal tariffs.' As of 19 April, Polymarket shows a 57% chance of recession in the coming year, and Kalshi comes in at 59% – about four times the level in a normal year (15%). If I had to look at only one type of estimate, it would probably be the prediction markets. Forecasting a possible recession is one thing; identifying when one has already begun is another. Rather than telegraphing a downturn before it happens, the Sahm rule recession indicator says that the economy is in recession if a three-month moving average of the unemployment rate rises by at least 0.5 percentage points, relative to its lowest point from the previous 12 months. For now, the indicator does not signal a recession: unemployment remains low by historical standards. But firms sometimes hold off on the decision to lay off workers in response to falling demand, especially in times of heightened uncertainty such as now, until after they have accumulated some unwanted inventory, and/or cut back on their output and workers' weekly hours. A number of other early measures of actual economic activity can help us identify a recession. Purchasing managers' indices (PMI) survey private sector firms to learn, for example, whether they have seen new orders rise or fall over the preceding month. The Institute for Supply Management's US manufacturing PMI fell to 49 in March. Readings below 50 indicate contraction. The Census Bureau's retail sales data – the earliest data on household consumption to become available – are also revealing, since private consumption accounts for nearly two-thirds of US GDP. The March report indicated continued growth, albeit driven largely by elevated motor vehicle sales to consumers who were trying to get ahead of impending tariffs. Of course, the criterion that comes closest to defining a recession is a period of negative GDP growth (in most countries, lasting two consecutive quarters). But GDP is reported only quarterly, with a substantial lag (and it is often revised later). So, 'nowcasts' have emerged to provide real-time estimates of GDP, based on the most up-to-date relevant indicators, such as the PMI, industrial production, and retail sales. The estimate of first-quarter GDP growth by the most prominent US nowcast, the Atlanta Fed's GDPNow, fell off a cliff at the end of February, from above +2% to below -2%. Even after adjusting for an unusual increase in gold imports, GDPNow shows a fall in growth to slightly below zero in April. Whereas the birds that augur a recession offer no guarantees, the nowcast indicators can suggest that we may have arrived there. They can thus be thought of as clusters of rocks or shoals. But even then, they may or may not be attached to a larger landmass. In fact, even while the recession is under way, we do not know for sure that this is what we are experiencing. Sign up to Business Today Get set for the working day – we'll point you to all the business news and analysis you need every morning after newsletter promotion The official arbiter of US recessions is the National Bureau of Economic Research's Business Cycle Dating Committee, which looks at variables like gross domestic output, real personal income (excluding social transfers), nonfarm payroll employment, real personal consumption expenditure, manufacturing and trade sales (adjusted for price changes), and industrial production. Only when all the data is in – typically a year or so after the fact – does the committee declare a turning point. This does not help the sailor who is navigating through fog. Based on current information, I would put the odds of a US recession as high as 60% for the coming year – in line with prediction markets – and even higher for the next four years. While nothing is certain, we should not be surprised if we run aground. Jeffrey Frankel is a professor of capital formation and growth at Harvard University. He served as a member of President Bill Clinton's Council of Economic Advisers. © Project Syndicate
Business Recorder
23-04-2025
- Business
- Business Recorder
European shares close higher as financials, L'Oreal rise
FRANKFURT: European shares ended slightly higher on Tuesday on the back of rising financials and post-earnings gains in L'Oreal, though sentiment remained shaky after US President Donald Trump's critique of Federal Reserve Chair Jerome Powell. The pan-European STOXX 600 index ended 0.2% higher, well off session lows, with L'Oreal jumping 6.3% for its best single-day gain in nearly seven months. The beauty giant reported a rise in first-quarter sales, beating expectations - a bright spot in the sector after luxury group LVMH reported slower growth at its beauty retailer Sephora last week. European banks kicked off the week 0.7% higher. The basic resources index - which includes Europe's biggest mining companies - gained 1.2% on the back of higher metal prices. However, heightened global trade tensions remained at the heart of investor concerns as they returned from an extended Easter weekend. The International Monetary Fund slashed its forecasts for growth in the United States, China and most countries, citing the impact of US tariffs now at 100-year highs, and warning that further trade tensions would slow growth further. Meanwhile, Trump's repeated criticisms of Powell, urging the central bank to cut interest rates quickly, aggravated fears for the independence of the Fed. 'It's just a picture of uncertainty out there. Nothing really has changed,' said Daniela Hathorn, senior market analyst at Back in Europe, the ECB's Survey of Professional Forecasters indicated euro zone inflation could be a touch higher this year than earlier thought, but will then stabilise at the European Central Bank's 2% target. Shares in Swiss insurers Helvetia and Baloise rose 2.6% and 4.7% respectively after they said they plan to merge, creating Switzerland's second-largest insurance group with a combined market share of about 20%. On the downside, Danish drugmaker Novo Nordisk dropped 7.4% to its lowest since October 2022, after trial results from US rival Eli Lilly's experimental pill for weight loss and blood sugar showed it working just as well as Novo Nordisk's blockbuster drug Ozempic.
Gulf Today
22-04-2025
- Business
- Gulf Today
Eurozone inflation to stabilise at the 2 per cent target of ECB
Eurozone inflation could be a touch higher this year than earlier thought but will then stabilise at the European Central Bank's 2 per cent target, the bank's Survey of Professional Forecasters showed on Tuesday. The ECB cut interest rates for the seventh time in a year on Thursday, arguing that disinflation was well on track and risks were on the rise that price growth comes even lower than earlier thought. The ECB's survey, often a key input into policy deliberations, showed 2025 inflation averaging 2.2 per cent, above the 2.1 per cent predicted three months ago while the 2026 number was lifted to 2.0 per cent from 1.9 per cent. However, these numbers may be less significant than in the past since the ECB's cut off for collecting projections was April 4 and financial markets have shifted significantly since then due to the US's erratic trade policy. The euro has firmed sharply against the dollar and energy prices have fallen, changes that could significantly slow inflation. Trade barriers and tensions with the US could also sharply slow economic growth and weigh on prices. The survey, however, only showed a small revision in the growth outlook, putting the 2025 expansion at 0.9 per cent versus the previous 1.0 per cent number, suggesting that not all of the trade tension is yet factored in. ECB President Christine Lagarde earlier argued that a full trade war could deduct up to 0.5 percentage point of growth. Eurozone government bond yields steadied on Tuesday as traders returning from the long weekend reassessed their outlook for the economy after the European Central Bank's rate decision on Thursday and comments that US tariffs would knock growth. Investors were also digesting US President Donald Trump's Monday warning that domestic growth could slow unless the Federal Reserve cut interest rates immediately, which triggered a sell-off in long-dated Treasuries. German 10-year bond yields, the benchmark for the Eurozone bloc, inched up 0.5 basis points to 2.47 per cent. Italy's 10-year yield was 1.4 basis points higher at 3.66 per cent. Trump repeated his criticism of Fed Chair Jerome Powell, who says rates should not be lowered until it is clearer Trump's tariff plans won't lead to a persistent surge in inflation. The spread between US 10-year Treasuries and German Bunds widened to 195 bps. The premium investors demand to hold US debt rather than German has increased by 48 basis points so far in April, heading for its biggest monthly rise since June 2003, according to LSEG data. Germany's two-year bond yield, which is more sensitive to ECB rate expectations, extended its slide on Tuesday, falling by 2.9 bps to 1.64 per cent. It dropped about 7 bps on Thursday after investors priced in more rate cuts by the ECB after the central bank lowered interest rates to 2.25 per cent last week.
