As a result, the output gap (the difference between Actual and Potential GDP) divided by Potential GDP equals the negative Okun coefficient (negative denotes an inverse link between unemployment and GDP) multiplied by the change in Unemployment.
If we follow traditional Okun’s law, the Okun coefficient will always be 2. However, in today’s context, this coefficient will not always equal two and may vary depending on economic conditions.
In economics, what is Okun’s Law?
Okun’s law examines the statistical relationship between unemployment and economic growth rates in a country. According to Okun’s law, a country’s gross domestic product (GDP) must expand at a pace of around 4% for one year in order to achieve a 1% reduction in unemployment.
How is the unemployment rate calculated using Okun’s law?
According to Okun’s law, if the unemployment rate is 1% higher than its potential, GDP will be 2% lower. Because GDP is 2% lower in the question, unemployment is 1% higher than the normal rate of unemployment. As a result, the actual rate is equal to 5%.
What is the difference between potential and real GDP?
Gross domestic product (GDP) potential is a theoretical notion that has diverse meanings for different people. To some, it represents a world in which each employee is matched with the ideal job, where every good idea is realized and the bad ones are ignored. Resources are allocated optimally in this environment, with no distortions caused by the tax system, information frictions, or inefficient government policies. However, this hypothetical “ideal world” is not the real world, and the scenario just described is not the concept of potential GDP that monetary planners normally employ when making decisions. Instead, they calculate potential GDP using metrics of real GDP trend that smooth out business cycle swings. Potential production is reasonably easy to measure when looking back in time because we have proven methods for extracting smooth patterns from historical data. However, evaluating prospective production in real time is more difficult because the trend can only be estimated from prior data. We can’t be sure about the prospective GDP estimate for 2012 until several years have passed and we’ve seen how GDP has changedthe accuracy of our estimate is dependent on the accuracy of our long-term projection.
But what is the significance of potential GDP? What will we do with it? The output gapthe difference between actual and potential GDPis used by monetary policymakers to decide whether the economy requires more or less monetary stimulus. A glance at current data from the Congressional Budget Office (CBO) demonstrates how estimates of the output gap can shift over time. According to CBO projections of potential GDP, actual GDP in the United States fell around 10% short of potential in 2009:Q1. Since then, actual GDP has followed in the footsteps of economists’ potential GDP series forecasts from 2007albeit at a much lower level. The graph depicts logged actual GDP figures as well as two CBO estimates of potential GDP. In 2007, a higher level of potential GDP was estimated, then in 2011, a lower level was estimated. The lower 2011 estimate reflects the impact of three years of weak GDP growth.
A glance at recent data from the Congressional Budget Office demonstrates how estimates of the output gap can shift over time.
We may now calculate the 2009:Q1 output gap to be 7.1% based on improved estimates. What’s more intriguing is how the change affects production gap estimates for 2011:Q4. The output gap for 2011:Q4 would be 11.3 percent if we adopt 2007 figures. When we take the most recent estimates, the difference is substantially smaller: only 5.6%. If I growth remains moderatesay, less than 3%and (ii) inflation continues to rise, potential GDP is likely to be revised downward once more. Over the next few years, GDP is expected to expand at a moderate pace. The participants at the January Federal Open Market Committee meeting projected real GDP growth of around 3% over the next three calendar years on average, according to the minutes. This rate of growth is insufficient to bring GDP back to current trend estimates. If the forecasts are correct, the estimated amount of potential GDP will drop much more. This pessimistic attitude is backed up by Keynesian (and New Keynesian) theory, which predicts that a negative production gap will result in lower inflation. Instead, we’ve seen a slight increase in inflation. If the theory is right, the gap may be narrowing faster than we thought due to lower potential GDP. In addition, if potential GDP is lower than projected, interest rates may need to rise sooner than expected to keep inflation from accelerating.
For the stated time interval, the gap between a country’s prospective gross domestic product and its actualized gross domestic product. Potential GDP is a measure of an economy’s maximum, ideal output, which includes high employment in all sectors while ensuring currency and product price stability. Actual GDP refers to a country’s output as measured over time. The GDP gap is a measure of squandered potential output due to a country’s unemployment rate combined with corporate and government inefficiencies, as Actual GDP rarely reaches Potential GDP.
How do you calculate potential growth?
The sum of the average increase of labor and capital inputs, as well as the efficiency with which these resources are utilised, namely total factor productivity, is the prospective growth rate (TFP).
How is the potential output determined?
Potential output is defined by the CBO as the trend growth in the economy’s productive capacity. It employs a model that relates real GDP growth to the growth of three factor inputs: capital, labor, and technical progress, to predict potential output.
In macroeconomics, what is potential GDP?
The Gross Domestic Product (GDP) is a metric that measures the total value of all products and services generated in an economy over a certain time period. The Bureau of Economic Analysis of the federal government calculates it every quarter. Potential GDP is a theoretical construct that estimates the value of the output that the economy would have created if labor and capital were utilized at their maximum sustainable ratesthat is, rates that are consistent with stable growth and inflation. Figure 1 shows how real GDP and potential output have changed over time. The economy functions close to potential in general, but prolonged recessions are notable exceptions. During these periods, GDP might lag behind potential for long periods of time.
The output gap is the difference between the level of real GDP and potential GDP. When the output gap is positivewhen GDP exceeds potentialthe economy is functioning at a higher capacity than it can sustain, and inflation is imminent. The output gap is negative when GDP falls short of its potential. Figure 2 depicts recessions with GDP well below potential, such as the Great Recession of 2007-2009 and the COVID-19 recession.
How do you figure out the GDP gap?
The output gap is calculated as YY*, where Y represents actual output and Y* represents potential output. If the result is a positive number, it is referred to as an inflationary gap, and it shows that aggregate demand is exceeding aggregate supply, perhaps resulting in inflation; if the result is a negative number, it is referred to as a recessionary gap, and it could suggest deflation.
The actual GDP minus the potential GDP is divided by the potential GDP to get the percentage GDP gap.
As an economist, Arthur Okun undoubtedly had a talent for making the extremely obvious seem just that. His two most famous contributions to the field are prime examples of this. Indeed, it was Arthur Okun who took two indicators (inflation and unemployment), combined them, and created the Misery Index. Hardly groundbreaking, but it’s still in common use today. Likewise, the eponymous Okun’s Law, which simply regresses changes in the unemployment rate on economic growth, remains a mainstay of 21st-century macroeconomics, albeit a controversial one.
So, what exactly is Okun’s Law, and why is it so contentious? For starters, it isn’t a law. It isn’t even a hypothesis. In reality, it’s probably better stated as a rule of thumb based on experience. It simply states that for every 0.3 percentage point rise in quarterly GDP growth, the jobless rate drops by 0.3 percentage points. It’s a great, simple result that’s held up over time. So, what’s the big deal?
The good
Let’s start with the positive. When evaluating the merits of any economic model, the first question to ask is whether it works. And, let’s face it, Okun’s Law works. In fact, the -0.3 coefficient calculated in 1962 still holds true today. True, it has fluctuated over time, but not significantly; at its weakest, the ‘Okun Coefficient’ momentarily went below -0.2, but it has remained near to the initial estimate on average, and the link has always been statistically significant.
Furthermore, Okun’s Law appears to exist in a number of other countries, and while the intensity of the association varies, its long-term stability does not. Indeed, the association does not hold in Japan, a country with a persistently low unemployment rate, out of the nine countries indicated below.
The Bad
So, what’s the deal with the skepticism? For one thing, theory suggests that the relationship between employment and GDP should be larger than the one between economic activity and unemployment. Indeed, a direct link between growth and unemployment would exist only if increased labor demand was met solely by the pool of unemployed employees, rather than those who were economically inactive. This assumption definitely does not true, as evidenced by the graph below, which shows that in the third quarter of 2018, flows between economic inactivity and employment outpaced those between unemployment and inactivity.
The ugly
The underlying issue with regressing unemployment on GDP is that it suffers from endogeneity, as economists call it. Endogeneity is a scary word for economists since it suggests that the Okun Coefficient will be skewed (that is, not equal to its real value) by additional information not included in the model.
The demand for cigarettes is frequently used in economics textbooks to help understand endogeneity. In this situation, a simple regression of the quantity sold on the price could result in a positive relationship between the two, notwithstanding the rule of demand. (Demand should be reduced as prices rise.) However, because higher prices tend to increase supply, the underlying relationship is likely to be disguised. As a result, just the prices and quantities at which the market clears are noted. Economists frequently employ the technique of instrumental variables to draw out the true shape of the demand curve (or the supply curve, for that matter).
The same dilemma exists with Okun’s Law: both output and unemployment are most likely codetermined.
This is the relationship’s negative side.
Ordinarily, the presence of endogeneity would be enough to warn economists away, but this does not appear to be the case with Okun’s Law. Indeed, the ECB’s Survey of Professional Forecasters (SPF) shows that economists’ use of the link has gotten stronger, not weaker, in recent years. And it’s easy to see why, warts and all, it works exceptionally well. Of course, more sophisticated models might function better, but Okun’s Law’s parsimony has a certain beauty to it. Should pragmatism, however, take precedence above academic rigor? Perhaps.
‘Potential GNP: Its Measurement and Significance,’ by A.M. Okun. 89-104 in Proceedings of the American Statistical Association’s Business and Economic Statistics Section (Vol. 7, 1962).
It’s so short that the now-famous law is summarized in only two paragraphs. In fact, rather than linking unemployment and growth, the paper’s primary focus was on predicting potential production.
‘Disaggregating Okun’s law: dissecting the impact of the spending components of GDP on euro area unemployment,’ ECB Working Paper No. 1747, by Robert Anderton, Ted Aranki, Boele Bonthuis, and Valerie Jarvis (2014).
ECB Economic Bulletin (1/2019), Rupert de Vincent-Humphreys, Ivelina Dimitrova, Elisabeth Falck, and Lukas Henkel, ‘Twenty years of the ECB Survey of Professional Forecasters’.