Real gross domestic product (GDP), or goods produced minus inflationary impacts, is the economic measure that most clearly identifies a recession. Income, employment, manufacturing, and wholesale retail sales are some of the other major indicators. Each of these areas suffers a drop during a recession.
What are the early warning signs of a recession?
In the past, indexes that integrate numerous macroeconomic variables have done a better job than other indicators at predicting recessions up to a year ahead of time. Economists monitor a variety of economic and financial data series to assess the current state of the economy and future possibilities. According to the National Bureau of Economic Research, leading indicators are indications of U.S. recessions (NBER). I look at how useful various economic and financial indicators have been in the past at “predicting” recessions and what these indications signal for the future. I show that indexes that integrate numerous macroeconomic variables have historically outperformed other indicators in terms of predicting recessions (and expansions) up to a year ahead of time. Furthermore, I confirm that financial market indicators, particularly the slope of the Treasury yield curve, have proven reliable predictors of recessions one to two years in advance. I also calculate recession prediction criteria for all of the leading signs I analyze using historical data. Then, to aggregate the data from these indicators, I create a new index that indicates the percentage of leading indicators that anticipate a recession at any particular period. This basic index exceeds existing indicators in predicting a recession six to nine months ahead of time.
How to evaluate leading indicators
In this study, I evaluate numerous leading indicators to see which ones have been more successful in the past at predicting recessions based on their historical classification abilities of data aligned with future recessions and expansions. I specifically assess a list of leading indicators compiled by the Conference Board from a range of sources. Data on employment, manufacturing activity, housing, consumer expectations, and stock market returns are among these indicators. However, I substitute the more commonly used difference between the ten-year yield and three-month yield (the long-term spread)3 and another version of the yield curve designed to capture monetary policy expectations for the Conference Board’s measure of differences in Treasury securities’ interest rates across maturities (or the slope of the yield curve) (the near-term forward spread). 4 I also substitute the Chicago Fed’s National Financial Conditions Index (NFCI) and its nonfinancial leverage subindex for the Conference Board’s measure of credit conditions. 5 I look at the Conference Board Leading Economic Index for the United States (the average of its list of indicators); the Brave-Butters-Kelley (BBK) Leading Index, which two collaborators and I recently created from a panel of 500 monthly time series and quarterly U.S. real gross domestic product growth;6 the University of Michigan’s Index of Consumer Expectations; and the value of debit balances in broker-dealers’ s accounts (GSCI). 7 The 17 indicators I evaluate have been normalized throughout this analysis, so that negative values reflect a decline in economic activity. 8
Finally, I’d like to be able to compare a specific observation for any of these indicators to historical levels and determine whether or not a recession is imminent. This means I’m looking for a threshold below which the indicator has always been while indicating a recession (or always above when signaling an expansion). These forecasts will inevitably be flawed, and there will be instances during a recession when an indicator exceeds the selected threshold (and times during an expansion when it is less than the threshold). The accuracy of an indicator refers to the total number of times it correctly defines a certain period based on a set of criteria. Unfortunately, for the purposes of recession prediction, accuracy is a problematic metric because successfully diagnosing a recession is viewed the same as correctly classifying an expansion. In the most extreme example, predicting that a recession will never happen is 88% accurate because recessions have only happened in 12% of all months since 1971. Obviously, having a predictor that delivers a meaningful signal about impending recessions, even if it is less than 88 percent accurate, would be desirable.
A statistic known as the area under the receiver operating characteristic (ROC) curve, or AUC value, is a superior criterion for evaluating these indicators.
9 An indicator’s categorization ability based on a pair of data points is measured by its AUC value. Assume we were given two indicators and informed that one is connected with a recession and the other is associated with an expansion. The AUC value represents the likelihood that the lower observation is linked to a recession. AUC values range from zero to one, as with any probability; a value of one indicates that an indicator perfectly classifies a random pair of observations. 10 Even if an indicator is unrelated to future recessions, it has a 50-50 chance of properly predicting one, resulting in an AUC of 0.5.
The imbalance in the number of recessionary vs expansionary periods observed has no effect on the AUC value because it is related to random pairs of observations. Furthermore, the AUC value may be computed without first deciding on a threshold (unlike accuracy), making it a more reliable measurement of how much information an indicator transmits about future economic conditions.
AUC values of leading indicators
I alter the indicators’ observations to correspond with whether or not a recession happened a specific number of months in the future up to two years ahead of time to evaluate each indicator’s AUC value. The results are shown in figure 1 as colored lines, with composite indexes and Treasury yield curve measures (those with generally larger AUC values) in panel A and the remaining measures in panel B. Based on these findings, I’ve come to the following conclusion:
- The Conference Board Leading Economic Index for the United States is the best at predicting recessions and expansions up to nine months ahead of time. I reject the idea that other indicators are similarly good at predicting a recession one to six months ahead of time, based on a statistical test11. The Conference Board’s leading index remains the strongest predictor for seven to nine months ahead, but I can’t rule out the possibility that three other indicators are just as good (the BBK Leading Index and the two yield curve measures). In the short term, the Conference Board’s leading index is extremely accurate, with an AUC value of 0.97 one to three months ahead.
- The long-term Treasury yield spread (i.e., ten-year minus three-month Treasury yields) is the best predictor of a recession or expansion far in advance. At a 16 to 20-month horizon, I can rule out the possibility that alternative indications are just as excellent. The long-term yield curve slope remains the best predictor for 14 to 15 and 21 to 24 months ahead, but I can’t rule out the possibility that at least one of three other indicators (the NFCI’s nonfinancial leverage subindex, the S&P GSCI, and the University of Michigan’s Index of Consumer Expectations) is just as good. The AUC values are lower than those for short horizons because to the added uncertainty that comes with longer horizon predictions: At 14 months ahead, the long-term yield spread reaches an AUC of 0.89, then steadily drops to 0.75 at 24 months ahead.
- Several leading indicators generate similar AUC values ten to thirteen months ahead. At these horizons, the AUC values of the Conference Board Leading Economic Index for the United States, the BBK Leading Index, the two yield curve slopes, and the NFCI’s nonfinancial leverage subindex are all between 0.84 and 0.89. Statistical tests are ambiguous as to which one performs best at these horizons, emphasizing that both should be taken into account for forecasting medium-term recessions.
- The Conference Board’s leading index and the BBK Leading Index in panel A perform a better job of predicting recessions than the macroeconomic indicators in panel B, as seen in figure 1. Panel B’s macroeconomic indicators perform so poorly over longer time horizons that I can’t rule out the possibility that many of them are similar to random noise more than a year ahead. The AUC values of these leading indices approach 0.5 over extended time periods as well, but take longer than the macroeconomic indicators. These findings suggest that the indexes are operating as expected: they provide a clearer indication of future economic activity by reducing noise in their component indicators.
Recession prediction thresholds
While the AUC value provides information about a leading indicator’s ability to classify data in the past, it does not provide information about the threshold that should be utilized to anticipate a recession. The earlier problem, which I correctly identified, shows that a different strategy is required. To figure out which option is best, keep in mind that the threshold for each indicator has two effects: 1) the true positive rate, or how many months it correctly labels as a recession, and 2) the false positive rate, or how many months it incorrectly classifies as an expansion.
My goals for these two indicators are in conflict with each other regardless of the threshold I pick. I want to predict as many recessions as possible (a high true positive rate), but I also want to have as few cases as possible where the indicators are wrong “yell “wolf” (avoiding a high false positive rate). If I wanted to ensure that an indicator predicted every probable recession, I’d pick a high threshold to build a sensitive predictor with a high true positive rate at the cost of many false recession forecasts. In contrast, if I wanted to be sure that a recession was coming when an indicator predicted one, I would set a low threshold so that only the lowest values of the indicator predicted one; while this approach would miss some recessions, it would give me more confidence that one was coming when one was predicted.
Consider the scenario of an indicator that provides no information about a looming recession to resolve this problem. Whatever criterion is chosen, it merely alters the percentage of time when a recession is expected. Assume this random guess correctly forecasts a recession 20% of the time. This prediction would correctly predict 20% of recessions when the results are known whether a recession occurred or not. This assumption, on the other hand, would falsely forecast a recession 20% of the time when an expansion happened. This indicates that the genuine positive rate and the false positive rate will always be the same for such an indicator. The more informative a threshold indication is, the more it will deviate from this connection. Choosing a threshold that maximizes the difference between true positive and false positive rates gives you the most information about previous recessions for a given indicator. 12
Let me give you an illustration of what this threshold criterion means in terms of a single indicator: This is a good example “For the long-term Treasury yield spread (i.e., ten-year minus three-month Treasury yields) at 12 months ahead, the “maximum information” criterion is slightly higher than the frequently stated value of zero. Only 57 percent of recession months and 5% of expansion months are accurately classified using the zero threshold (also known as a yield curve inversion13). The highest information threshold fluctuates slightly among the horizons studied, but remains constant at 0.94 for the next eight to fifteen months. The long-term spread one year ahead correctly diagnoses 88 percent of recession months, but erroneously classifies 19 percent of boom months, according to this criteria.
The circumstance determines which of these levels to use. The lower false positive rate of the zero threshold is appealing to individuals who want to be more convinced that a recession is approaching when one is forecast. Instead, the maximum information strategy focuses on the true positive/false positive rate trade-off. The maximum information technique raises both rates by raising the threshold, but the true positive rate rises faster than the false positive rate, making it easier to discern prior recessions from expansions. 14
A summary index
To determine an optimal recession prediction threshold, the maximum information threshold criterion can be applied to each of the indicators at each horizon from zero to 24 months ahead. I calculate the fraction of the 17 indicators that are below their ideal threshold and anticipate a recession to present all of the indications under consideration as succinctly as feasible. This is, in effect, a new approach of generating a leading index to forecast future recessions. This “ROC threshold index” is notable in that it is merely the fraction of the indicators analyzed that have passed their recession prediction thresholds, rather than an estimated chance of a recession. I computed the AUC values for each of the 25 ROC threshold indexes at the corresponding horizon to evaluate them, and the results are represented as the black line in panel A of figure 1.
The ROC threshold indexes are better predictors of approaching recessions than any of the other variables studied throughout time horizons of up to 11 months.
15 Using the same statistical test as before, I can rule out the possibility that any of the indicators considered here are as good as these indexes over a six- to nine-month timeframe. The predictive power of the ROC threshold indexes falls below that of the yield curve measurements over longer time horizons, but they remain moderately helpful. Intuitively, the ROC threshold indexes’ performance deteriorates as the predictive power of the leading indicators used to create them deteriorates. Because just a few indicators are substantially predictive more than a year in advance, the ability of the ROC threshold indexes to distinguish between recessions and expansions deteriorates when the prediction is made longer in advance.
Nine months ahead of schedule, the ROC threshold indices greatly surpass all other indicators. Figure 2 shows the ROC threshold index time series at this horizon, with the series pushed nine months ahead to exhibit the most recent data observation from August 2019 in May 2020. Because the goal isn’t necessary to extract as much information as possible, determining the right threshold to assess this index against is difficult (as it was with the individual indicators to construct the index). Using the maximum information strategy, a 50% threshold is obtained. This indicator properly forecast a recession in 83 percent of recession months based on the 50% threshold, but mistakenly projected a recession in 15% of expansion months. A generally used, more conservative criterion16, on the other hand, yields an 80 percent barrier. The genuine positive rate of the 80 percent threshold is 26%, whereas the false positive rate is only 3%. The decision between these criteria, as before, is determined by the purpose of the forecast. The 50 percent barrier is better if one is ready to accept a higher chance of misclassifying an expansion; the 80 percent level is better if it is more vital to be highly convinced that a forecasted recession is genuinely coming. Both criteria are presented in figure 2 since they are possibly beneficial.
ROC threshold index at nine months ahead
While the ROC threshold index for the next nine months rose beyond 50% based on data collected in December 2018 (plotted in September 2019 in figure 2), it has remained close to but below 50% for all data collected since then. Since around the end of the previous recession, this indicator has been significantly below the 80% mark. Given how volatile this indicator is, these slightly higher recent readings are worth noting, but it remains below the 50% level that is nearly invariably connected with a historical recession.
To be clear, the entire study is based on the assumption that when data is observed, it is known with confidence. This is obviously not the case, as data is released slowly and frequently changed months later. To better understand our abilities to foresee recessions before they happen, we need to do a real-time analysis of this technique.
Conclusion
The findings of this article reveal that the long-term Treasury yield spread has historically been the most accurate available “predictor” of recessions for timeframes of one year and longer. However, leading indexes have done a better job of predicting recessions in the short term than individual leading indicators or financial data. Because they are basically leading indexes that combine the information in the inputs to create a more precise evaluation of coming economic activity, the ROC threshold indexes constructed here have also performed well as recession predictions in the near term.
What are the signs of a recession?
The business cycle includes recessions, which are a normal, albeit unpleasant, part of the process. A spate of corporate failures, including often bank failures, weak or negative growth in production, and high unemployment characterize recessions. Even if recessions are only temporary, the economic misery they create can have significant consequences that transform an economy. This can happen as a result of structural changes in the economy, such as vulnerable or obsolete firms, industries, or technologies failing and being swept away; dramatic policy responses by government and monetary authorities, which can literally rewrite the rules for businesses; or social and political upheaval caused by widespread unemployment and economic distress.
How can you tell if a country’s economy is in a slump?
A recession is a prolonged period of low economic activity that might last months or even years. When a country’s economy faces negative gross domestic product (GDP), growing unemployment, dropping retail sales, and contracting income and manufacturing metrics for a protracted period of time, experts call it a recession. Recessions are an inescapable element of the business cycle, which is the regular cadence of expansion and recession in a country’s economy.
What three economic indicators are there?
Leading indicators predict future economic changes. They’re particularly valuable for predicting short-term economic trends because they frequently shift before the economy does.
Lagging indications are those that appear after the economy has changed. They’re most useful when they’re utilized to corroborate specific patterns. Patterns can be used to create economic predictions, but lagging indicators cannot be utilized to anticipate economic change directly.
Because they occur at the same time as the changes they signal, coincident indicators provide useful information on the current state of the economy in a certain area.
What are the five economic indicators?
The most useful leading indications to follow are the following five. The yield curve, durable goods orders, the stock market, factory orders, and building permits are all examples of these indicators.
What are the five reasons for a recession?
In general, an economy’s expansion and growth cannot persist indefinitely. A complex, interwoven set of circumstances usually triggers a large drop in economic activity, including:
Shocks to the economy. A natural disaster or a terrorist attack are examples of unanticipated events that create broad economic disruption. The recent COVID-19 epidemic is the most recent example.
Consumer confidence is eroding. When customers are concerned about the state of the economy, they cut back on their spending and save what they can. Because consumer spending accounts for about 70% of GDP, the entire economy could suffer a significant slowdown.
Interest rates are extremely high. Consumers can’t afford to buy houses, vehicles, or other significant purchases because of high borrowing rates. Because the cost of financing is too high, businesses cut back on their spending and expansion ambitions. The economy is contracting.
Deflation. Deflation is the polar opposite of inflation, in which product and asset prices decline due to a significant drop in demand. Prices fall when demand falls, as sellers strive to entice buyers. People postpone purchases in order to wait for reduced prices, resulting in a vicious loop of slowing economic activity and rising unemployment.
Bubbles in the stock market. In an asset bubble, prices of items such as tech stocks during the dot-com era or real estate prior to the Great Recession skyrocket because buyers anticipate they will continue to grow indefinitely. But then the bubble breaks, people lose their phony assets, and dread sets in. As a result, individuals and businesses cut back on spending, resulting in a recession.
What are the two most important indicators that the economy is expanding?
- Expansion: The economy is emerging from its slump. Borrowing money is cheap, firms restock their stocks, and consumers begin to spend again. GDP rises, per capita income rises, unemployment falls, and stock markets perform well in general.
- The expansion phase finally reaches its apex. As a result of the increased demand, the cost of commodities rises, and economic indicators begin to stagnate.
- Contraction: The economy begins to slow down. Companies halt hiring as demand declines, and then start laying off employees to cut costs.
- Trough: The economy moves from a period of decline to one of expansion. The economy reaches a nadir, opening the path for a comeback.
Lower Prices
Houses tend to stay on the market longer during a recession because there are fewer purchasers. As a result, sellers are more likely to reduce their listing prices in order to make their home easier to sell. You might even strike it rich by purchasing a home at an auction.
Lower Mortgage Rates
During a recession, the Federal Reserve usually reduces interest rates to stimulate the economy. As a result, institutions, particularly mortgage lenders, are decreasing their rates. You will pay less for your property over time if you have a lower mortgage rate. It might be a considerable savings depending on how low the rate drops.
How is the probability of a recession determined?
A recession is defined as a drop in real GDP over two quarters in a row. After six months of declining national income, an economy is officially in recession. Higher unemployment, reduced confidence, declining housing values, lower investment, and lower inflation are all common outcomes of a recession.
However, while this may appear to be a simple task, it might be challenging to determine in practice. GDP statistics may not tell us till a long time after the event has occurred.
For policymakers, knowing whether or not you’re in a recession is critical. The Central Bank can decrease interest rates as soon as it becomes aware that a recession is underway or is expected to develop, and the government may decide to pursue expansionary fiscal policy. Because monetary and fiscal policy can have a temporal lag, the sooner you know, the better.
Real GDP is the most relevant figure. This indicates that the UK experienced negative economic growth in the second quarter of 2008. Because it is the second quarter of negative economic growth, the UK is ‘officially’ in recession by Q3 2008.
The Central Bank, on the other hand, did not lower interest rates until September 2008, and rates did not reach 0.5 percent until March 2009. The Federal Reserve took a long time to recognize the severity of the recession. (However, cost-push inflation from rising oil prices added to the complexity.)
The first factor is that GDP statistics are published after a few months’ delay. The statistics for the first quarter (January to March) are released on April 27 over two months later. The second problem is that preliminary GDP figures are approximations based on incomplete data. Later, when the picture becomes clearer, they are altered (more firms send in data). Initial estimations may overlook any significant shift in the trend. The initial estimates of GDP in 2008 were dramatically revised down subsequently.
Economic growth in Q2 2008 was estimated to be 0.2 percent in the first month. Three years later, this positive increase has been lowered to -0.6, indicating a significant decline.
For the third quarter of 2008, the first-month estimate was -0.5 percent. However, this was amended three years later to a far more catastrophic -1.7 percent.
To put it another way, when the second quarter of 2008 numbers were released two months after the end of June it appeared like the economy was still increasing. However, the economy was already in a downturn. This is a drawback of relying on real GDP figures.
2. Consumer assurance
Consumer confidence measures whether people are optimistic or pessimistic about the future of the economy. This is frequently a reflection of the state of the economy. Consumers will lose confidence if they see people being laid off, if getting a bank loan is difficult, or if housing prices are declining. They will spend less in this situation, resulting in lower aggregate demand and, as a result, negative economic growth.
This illustrates that consumer confidence has been declining since September 2007. At the start of 2008, this decrease in confidence becomes even more pronounced, with consumer confidence reaching new lows. This proved to be a strong economic leading indicator. When confidence levels plummet like this, a recession is almost certain to follow.
Because of the financial turbulence, such as banks running out of cash, confidence has plummeted. Consumers have become risk-averse and have increased their savings and reduced their expenditure.
Business confidence is similar to consumer confidence. Businesses will reduce borrowing and investment if they are harmed by financial instability. This results in a reduction in economic activity.
The Bank of England took a year to respond to the drop in consumer confidence.
The OECD produces a combined measure of corporate and consumer confidence.
A drop in consumer confidence is not proof that the economy is in trouble. Consumer confidence may decline as a result of political factors that are only temporary and have no impact on an economy’s underlying economic fundamentals. For example, there was a reduction in consumer confidence following 9/11, but this did not result in a long-term economic downturn.
Consumer confidence has been declining since July 2016 as a result of Brexit, and this trend has continued since the beginning of the year. Will this be enough to send the economy into a tailspin? Consumer confidence is crucial, but you could argue that the uncertainty around Brexit is not the same as the change in economic fundamentals that occurred in 2008, when the regular banking system collapsed. A significant drop in consumer confidence, on the other hand, can become self-fulfilling. We get a drop in overall demand when we combine a delay in company investment with more cautious consumer purchasing, which could result in a negative multiplier effect. (Will there be a recession as a result of Brexit?)
Unemployment will increase during a recession. Unemployment, on the other hand, is frequently a lagging indication. Firms strive to postpone firing workers to see whether they can weather the downturn without incurring the costs of firing and rehiring. A decrease in average hours worked may be a more immediate indicator of an economic downturn. This is one method businesses can save money without having to lay off employees.
A drop in stock markets could signal a deterioration in economic morale. The stock market, on the other hand, is a poor predictor of economic growth. For example, despite strong economic development, the stock market saw a lengthy fall in 2002-04. (See the sections on the stock market and the economy.)
Investors may expect lesser growth, poorer returns, and lower interest rates in the future if long-term bond yields decline. Negative bond rates have risen in 2016, indicating poorer global growth predictions. Other factors, such as the availability of investment options and investor views of investment security, have an impact on bond yields. It’s not a foolproof way of indicating that you’re in a slump.
Technically, we can have economic growth, but people believe they are in a recession because their situation is deteriorating. Although Britain escaped recession in 2012/13, average wages were decreasing. Because ordinary employees’ salaries are declining, some may consider this a sort of recession.
House prices in the United Kingdom are susceptible to economic developments. During a downturn in the economy, the UK’s unpredictable housing market sees prices decline. Even the uncertainty of Brexit caused people to begin making lower house offers. House prices that are falling are an indicator of economic sentiment, but they can also have an impact on the economy. House prices falling produce a negative wealth effect and a reduction in consumer expenditure.
One cause may not be sufficient, but having more than a couple is a strong indicator of recession.