The answer is that the National Bureau of Economic Research (NBER) is in charge of identifying when a recession starts and stops. The Business Cycle Dating Committee of the National Bureau of Economic Research makes the final decision.
The National Bureau of Economic Research (NBER) reported on Friday, November 28, 2008, that the United States entered its most recent recession in December 2007.
Many people use an old rule of thumb to define a recession: two consecutive quarters of negative Gross Domestic Product (GDP) growth equals a recession. This isn’t fully correct, though. According to the National Bureau of Economic Research (NBER),
“A recession is a sustained drop in economic activity that affects all sectors of the economy and lasts more than a few months, as evidenced by production, employment, real income, and other indicators. When the economy reaches its peak, a recession begins, and it ends when the economy reaches its trough.”
When determining whether or not we are in a recession, the NBER considers a number of criteria. However, because “The committee emphasizes economy-wide measures of economic activity because a recession is a broad downturn of the economy that is not confined to one sector. Domestic output and employment, according to the committee, are the primary conceptual metrics of economic activity.”
– Domestic Manufacturing: “The committee believes that the quarterly estimates of real Gross Domestic Product and real Gross Domestic Income, both issued by the Bureau of Economic Analysis, are the two most credible comprehensive estimates of aggregate domestic output.”
– Workplace: “The payroll employment measure, which is based on a broad survey of employers, is considered by the committee to be the most trustworthy comprehensive estimate of employment.”
What criteria are used to declare a recession?
Industrial production, employment, real income, and wholesale-retail commerce all show signs of a recession. Although the National Bureau of Economic Research (NBER) does not require two consecutive quarters of negative economic growth as measured by a country’s gross domestic product (GDP) to declare a recession, it does use more frequently reported monthly data to make its decision, so quarterly GDP declines do not always coincide with the decision to declare a recession.
Who announces a downturn?
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.
How can you tell when a recession is over?
A recession is a large drop in overall economic activity that lasts for a long time. Unemployment rises and real income falls during recessions.
FRED helps put the data into context by displaying when these recessions occurred: Since 2006, every FRED series of US data has had the option of displaying shaded areas on the graph to show business cycle peaks and troughs, according to the National Bureau of Economic Research (NBER).
The NBER’s Business Cycle Dating Committee assigns a lag of several months to the onset of each recession and an even longer lag to the end of a recession: According to the National Bureau of Economic Research, business cycle peaks are publicized 7.8 months after their dating, while business cycle troughs are revealed 15.8 months after their dating.
Any new information is rapidly updated in the FRED database. On the FRED graph above, the recession that began in February 2020 is now visible. The apex of the business cycle is denoted by a bar set on February 1, 2020 in graphs containing data at a daily frequency. It is indicated as a vertical line in graphs with monthly data.
Because FRED is unable to predict when the recession will finish, the graph is colored from February 2020 onward. However, if you want to predict when the current recession will end (before the NBER issues an official statement), examine these FRED series: Marcelle Chauvet and Jeremy Piger’s recession likelihood index and the real-time Sahm Rule Recession Indicator. The recession has most certainly ended when the recession likelihood index has significantly fallen or the Sahm indicator has peaked. Check the FRED data on a frequent basis to ensure you get the good news as soon as possible.
This graph was made in the following way: Increase the date range to include the recession that lasted from December 3, 2007, to June 3, 2009. Search for “10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity” and expand the date range to include the recession that lasted from December 3, 2007, to June 3, 2009.
How are economic crises assessed?
The conventional version is straightforward: An economic crisis begins with a decrease in GDP per capita 4 and ends when GDP per capita is equal to or higher than it was prior to the crisis.
Which of the following organisations is responsible for announcing the start and end of recessions in the United States?
The National Bureau of Economic Research (NBER) is usually regarded as the judge of when recessions in the United States begin and conclude. The NBER defines a recession as “…a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales,” according to its website page listing recessions and expansions dating back to the 1850s. A sizable majority of the Bureau’s Business Cycle Dating Committee believes the recession that began in late 2007 is still ongoing.
Robert Gordon and Jeffrey Frankel are correct in their assessment that the recession ended in the second half of 2009. The NBER committee’s hesitancy in proclaiming the recession over is understandable. Businesses would clearly signal that we are in the midst of an expansion if they were convinced that we are in the midst of one with substantial and sustained increases in payroll employment. Such increases have yet to be seen. Only one of the preceding four months’ payroll reports indicated noticeable payroll improvements as of mid-April. Employers have only added 0.06 percent to their payrolls since November 2009. Unemployment insurance claims continue to exceed 450,000 every week. While these figures will almost definitely be amended, the changes may point to a weaker labor market rather than a stronger one.
According to the most recent data on income, output, and consumption, the economy has resumed growth. However, there’s a chance that the uptick is only transitory. Although I believe this risk is low, I am a labor economist and public finance expert, not a macroeconomist. Some of the nation’s most distinguished economic statisticians and macroeconomists make up the NBER’s Business Cycle Dating Committee. It’s difficult to imagine a more reliable group of experts to determine when the Great Recession officially ended.
Why is it so difficult to predict when a recession will begin?
It’s impossible to tell if you’re in a recession just by looking at your GDP. As a result, the NBER tracks the following statistics on a monthly basis. These provide a more up-to-date estimate of economic growth. GDP will fall if these economic indices fall.
What causes a downturn?
Most recessions, on the other hand, are brought on by a complex combination of circumstances, such as high interest rates, poor consumer confidence, and stagnant or lower real wages in the job market. Bank runs and asset bubbles are two further instances of recession causes (see below for an explanation of these terms).
What is the most reliable predictor of a downturn?
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.
Is there going to be a recession in 2021?
Unfortunately, a worldwide economic recession in 2021 appears to be a foregone conclusion. The coronavirus has already wreaked havoc on businesses and economies around the world, and experts predict that the devastation will only get worse. Fortunately, there are methods to prepare for a downturn in the economy: live within your means.
What are the warning indicators of a financial meltdown?
It is well understood how an increase in oil prices can have a knock-on effect on practically everything in the market. Consumers lose purchasing power as a result, which might lead to a drop in demand.
Loss of consumer confidence
Consumers will change their purchasing habits and eventually limit demand for goods and services if they lose faith in the economy.
Signs of an upcoming economic depression
There are several things that individuals should be aware of before an economic downturn occurs so that they can be prepared. The following are some of them:
Worsening unemployment rate
A rising unemployment rate is frequently a precursor to a coming economic downturn. Consumers will lose purchasing power as the unemployment rate rises, resulting in decreasing demand.
Rising inflation
Inflation can be a sign that demand is increasing due to rising wages and a strong workforce. Inflationary pressures, on the other hand, can deter individuals from spending, resulting in decreasing demand for goods and services.
Declining property sales
Consumer expenditure, including property sales, is often high in an ideal economic condition. When an impending economic downturn occurs, however, home sales decline, reflecting a loss of trust in the economy.
Increasing credit card debt defaults
When people use their credit cards a lot, it usually means they’re spending money, which is good for the economy. When debt defaults mount, however, it may indicate that people are losing their ability to pay, signaling an economic downturn.
Ways to prevent another economic depression
There is always the worry of another ‘Great Depression,’ which is why economists recommend the following strategies to prevent it from happening.