Coincident Indicator: What it is, How it Works, Impact

What Is a Coincident Indicator?

A coincident indicator is a metric that shows the contemporaneous state of economic activity within a particular area. Coincident indicators do not necessarily reflect current conditions because they usually involve some data collection and reporting lag. However, they are important because they show economists and policymakers the recent past state of the economy. Coincident indicators include employment, real earnings, average weekly hours worked in manufacturing, and gross domestic product (GDP).

Understanding Coincident Indicators

Coincident indicators are macroeconomic measures that are as reflective as possible of economic performance for the time period that they cover (usually the previous week, month, or quarter). Economic indicators can be classified into three groups based on the time period that is being measured. Lagging indicators change after the economy collectively changes, coincident indicators define the status of the business cycle for the time period in which they are collected, and leading indicators show where the economy is going.

Coincident indicators are often used in conjunction with leading and lagging indicators to get a full view of where the economy has been and how it is expected to change in the future. Leading indicators help predict the future movements of coincident indicators, and lagging indicators help confirm trends and turning points in coincident indicators.

The Federal Reserve (Fed) publishes coincident economic indexes compiled from a variety of coincident indicators. By compiling several indicators into an index, some of the short-term noise associated with individual indicators can be eliminated, giving a more reliable measure.

What Coincident Indicators Reveal About the Economy

Coincident indicators define the business cycles of the economy. This means that they are the primary indicators that are used to define whether the economy is in a recession or expansion in a given quarter, a process known as business cycle dating.

Coincident indicators do not typically reflect present economic conditions but report on data from the recent past. Different coincident indicators may have a long or short lag time between the reported indicator and the real underlying phenomenon that the indicator is meant to measure. These lags occur because it takes time to collect, tabulate and report the data, and can range from anywhere between one day and up to one year (for final or revised data).

The metrics that fall into this category, such as personal income and industrial production, help to give a snapshot perspective of what has recently been happening and how markets and economies have responded to the factors that affect their direction. By their nature, coincident indicators will change in parallel with the cycles of industry, commerce, and the economy. Taking an assessment of coincident indicators is a way to realize what effect policies and trends are actually having.

For example, if an upsurge in solar panel manufacturing is reported, it may show the effect that incentive programs for alternative energy sources are having. Payroll data can show the kind of recent demand companies have had for employees and their levels of productivity. If salaries have increased from a comparable period, it may indicate that companies are lately engaging in more business, seeing increased revenue, and can afford to pay higher salaries to attract skilled workers.

Referring to current payroll data as a coincident indicator can also show the capacity that employees have to spend money back into the economy. Increases in salary could allow for flexible expenses to increase, as well as create the potential for luxury expenditures. This would show that the economy has been robustly productive recently and which segments of it are expressing the most strength and stability.