Economic Forecasts

"While local economies may experience significant price imbalances, a national severe price distortion seems most unlikely in the United States, given its size and diversity."

Alan Greenspan, October 2004, playing down the threat of a national housing bubble.

Economic forecasts is certainly more of an art than a science. Put 10 economists in a room and the joke goes, you will get 11 different answers; that's certainly true for forecasting. Economists often have difficulty calculating existing statistics, let alone predicting future economic variables. For example, examining current account deficits suggest that the World has a current account deficit with itself. As we have not yet started trading with other planets, this must reflect statistical inaccuracies. When it comes to making forecasts, economists are even more likely to be wrong; but, just because some economic forecasts are wrong, doesn't mean we should ignore this branch of economics. It just means trying to make a better job of it.

What Determines the Success of Economic Forecasts?

• Current Data. Firstly, it is important to be aware of the correct current data. If we cannot be aware of how the economy is doing at the moment, it is very difficult to determine future trends. One difficult factor in predicting oil prices is that statistics on current oil stocks are hard to ascertain. For example, Saudi Arabia does not publish a full picture of its available reserves. There is much debate about the real rate of inflation see:
• Looking at All Variables. It is easy for people to look at only one aspect of an issue and come to a certain conclusion based on that. For example, in 2006, the ratio of mortgage payments to income was relatively low, compared to historical trends. This meant many felt house prices were not overvalued and due to fall. However, looking at house prices to earnings painted a different picture. House price to earnings had reached an all time high making it difficult for people to afford to purchase a house; when interest rates increased, the whole picture quickly changed.

• Understanding how Quickly Things Can Change. The problem with making economic forecasts is assuming that some variables will stay put. For example, the ratio of mortgage payments to income in the years 2004-06 was low, however, this was helped by record low interest rates. As soon as interest rates increased this cause the situation to change and mortgage payments rose changing the situation of the US Housing market.
• The Unexpected. This is the difficult thing to include in the equation. For example, oil price rises are notoriously difficult to predict, especially when sparked by political issues. The continued rise in oil has definitely led to higher inflation than most people would have predicted 12 months ago.
• Hidden Statistics. Banks and financial institutions are adept at hiding the true extent of their assets and liabilities. For example, the credit crunch took some by surprise because many were simply not aware of the risks that many subprime mortgage companies had exposed themselves to. Nor were most people aware of how mortgage debt had been sold around the global financial system. There are more than one examples, of companies who share price collapses as investors suddenly realise the true balance sheet.
• Hysteresis. It is often said, that if you listen to the predictions of top economists, you would actually get a more accurate forecast by just using last years statistic. For example, if inflation was 3% last year; there's a good chance it will be close to 3% again. Of course, economic statistics change from year to year; however, it is argued that using last years figure is often more accurate than choosing a forecast from others.

Economic Fundamentals Do Influence Forecasts. Despite all the difficulties careful analysis of economic fundamentals can help create good forecasts. If you look at the American economy a few years ago. There were many factors putting a downward pressure on the dollar

• Large current account deficit. 6.7% of GDP
• High levels of personal debt
• Low interest rates
• Growing uncertainty with economy.

All these made it easier to predict the dollar was likely to fall.