Because inflation is a rather long-term process, present and historical data should be useful in anticipating future inflation. We build two basic models that utilize information buried in past CPI inflation readings using that intuition. Each employs a different method for forecasting CPI inflation for the coming year: One is based on regression analysis, while the other is based on Atkeson and Ohanian’s nave specification (2001). We then add and remove different factors, as well as alternative techniques of measuring these variables, to arrive at different specifications.
The first specification is a regression that uses CPI lags to anticipate one-year-ahead CPI inflation (specifically, past values of the quarterly annualized percent change in the CPI).
1 This regression is estimated in a recursive fashion, starting with a sample of 40 quarters of data and adding an additional data point to the sample in each subsequent quarter.
2 This method equates to claiming that the next year’s inflation is a function of all previous inflation levels up to four quarters prior. The parameters of that function are determined through regression analysis.
The second specification uses a naive specification to estimate one-year-ahead CPI inflation, in which the projection for the year ahead is simply the CPI’s past four-quarter growth rate. For example, through the third quarter of 2010, the CPI’s four-quarter increase rate was 1.2 percent. Using the naive method, we anticipate 1.2 percent inflation for the next four quarters (through the third quarter of 2011). This method translates to suggesting that inflation in the following year will most likely be the same as it was the previous year.
We examine the predicting effectiveness of these models over a number of time periods because the underlying inflation process may have altered over time. Beginning in 1960, we look at forecast accuracy by decade. We next divide the data series into two time periods, one pre-1983 and one post-1983, because monetary policy altered in the 1980s. After a period of disinflation in the early to mid-1980s, known as the “Volcker-era” disinflation, both inflation and inflation expectations became less volatile, the inflation process may have been altered. We also look at forecast accuracy from 1984 to 2006 (excluding the last four years) to examine what has changed in the most recent era, which includes the 20072009 recession. The most recent time period we look at is 19952010, which allows us to look at inflation expectations as predictors for time periods where we have minimal data.
We compute the root mean squared error (RMSE) statistic, a measure of forecast error, for each specification to compare its accuracy. Positive numbers reflect differences between expected and realized values, whereas an RMSE of 0 denotes perfect forecasting performance. The greater the RMSE, the greater the average variation between projected and realized values. The forecast accuracy for our backward-looking regression and naive specification is shown in Table 1.
Table 1 shows a couple of patterns worth noting. To begin with, neither model consistently outperforms the other over time, while the naive strategy clearly has the advantage. Second, the predicting performance of these specifications, which are only based on previous inflation, fluctuates significantly over time and has decreased in recent years.
As a result of this recent loss in forecasting skill, inflation appears to be explained by past inflation to a lower amount than it used to be. The underlying inflation process may have changed, which could explain the decline. According to Carlstrom, Fuerst, and Paustian (2007), inflation has grown less persistent. Lagged inflation’s loss of explanatory power could be linked in part to the mid-2008 energy price shock. The CPI’s four-quarter growth rate had soared to 5.3 percent (a 17-year high) by the third quarter of 2008, only to plummet to 0.0 percent two quarters later. A big swing like that had not been seen in recent memory, and it is likely to have contributed to a larger forecast inaccuracy because backward-looking methods could not account for such severe fluctuation.
Full employment
The quantity of spare capacity and the rate of economic growth are important factors in predicting inflation.
Assume a country like the United Kingdom has a long-run trend rate of 2.5 percent. This suggests that growth of less than 2.5 percent is unlikely to result in inflation. If, on the other hand, growth exceeds 3% to 4%, the economy would swiftly approach full capacity, and inflation will be inevitable.
Rising AD is putting inflationary pressure on the economy. For example, in the late 1980s, the United Kingdom experienced annual growth of 4%, but this resulted in rising inflation.
In the UK, the long-run trend rate of economic growth is around 2.5 percent. Demand-pull inflation will be very low if growth is less than 2.5 percent (or the equivalent of 0.6 percent per quarter). This indicates that the UK has been experiencing below-trend growth for the past four quarters, resulting in mild inflationary pressures.
Global growth is slowing, which means that global inflationary pressures will remain modest. There will be less demand for exports if global growth slows. Also, reduced global growth tends to lower commodity prices, resulting in less cost-push inflation.
Unemployment and Inflation Predictions
Some economists argue that unemployment and inflation are mutually exclusive. If unemployment lowers, it could signal an increase in inflationary pressures.
Inflationary pressures are usually triggered by a decrease in unemployment. Wage-pull inflation occurs when unemployment reduces and job vacancies rise, allowing employees to demand greater salaries. However, the work market in the United Kingdom is uncommon in that unemployment is low, but wage growth is also low. There has been a steady decrease in the natural rate of unemployment (structural unemployment). Workers have little negotiating power, and there is a significant proportion of underemployment.
What can you use to predict future inflation?
It is commonly assumed that the slope of interest rates’ term structure provides information about inflation’s predicted future direction. Mishkin (1990) recently demonstrated that the gap between 12-month and 3-month interest rates can help anticipate the difference between 12-month and 3-month inflation rates. Apart from the (rejected) hypothesis that the real interest rate is constant, his approach lacks a theoretical grounding. This paper applies a simple existing theoretical framework to the problem of predicting the inflation spread, which permits the real interest rate to vary in the short run but converge to a constant in the long run. It is demonstrated that, rather than being limited to a spread between two points, the proper indicator of predicted inflation can employ the full length of the yield curve, in particular by calculating the steepness of a specific nonlinear transformation of the curve. Apart from having a stronger theoretical base, the derived indicator does a decent job at predicting inflation rates from 1960 to 1988.
What is the formula for calculating inflation?
Last but not least, simply plug it into the inflation formula and run the numbers. You’ll divide it by the starting date and remove the initial price (A) from the later price (B) (A). The inflation rate % is then calculated by multiplying the figure by 100.
How to Find Inflation Rate Using a Base Year
When you calculate inflation over time, you’re looking for the percentage change from the starting point, which is your base year. To determine the inflation rate, you can choose any year as a base year. The index would likewise be considered 100 if a different year was chosen.
Step 1: Find the CPI of What You Want to Calculate
Choose which commodities or services you wish to examine and the years for which you want to calculate inflation. You can do so by using historical average prices data or gathering CPI data from the Bureau of Labor Statistics.
If you wish to compute using the average price of a good or service, you must first calculate the CPI for each one by selecting a base year and applying the CPI formula:
Let’s imagine you wish to compute the inflation rate of a gallon of milk from January 2020 to January 2021, and your base year is January 2019. If you look up the CPI average data for milk, you’ll notice that the average price for a gallon of milk in January 2020 was $3.253, $3.468 in January 2021, and $2.913 in the base year.
Step 2: Write Down the Information
Once you’ve located the CPI figures, jot them down or make a chart. Make sure you have the CPIs for the starting date, the later date, and the base year for the good or service.
What is creating 2021 inflation?
As fractured supply chains combined with increased consumer demand for secondhand vehicles and construction materials, 2021 saw the fastest annual price rise since the early 1980s.
In Excel, how do you do inflation?
Let’s look at a basic example of a commodity that had a CPI of 150 last year and has now risen to 158 this year. Calculate the current year’s rate of inflation for the commodity using the given data.
What causes price increases?
- Inflation is the rate at which the price of goods and services in a given economy rises.
- Inflation occurs when prices rise as manufacturing expenses, such as raw materials and wages, rise.
- Inflation can result from an increase in demand for products and services, as people are ready to pay more for them.
- Some businesses benefit from inflation if they are able to charge higher prices for their products as a result of increased demand.
What will be the rate of inflation in 2022?
According to a Bloomberg survey of experts, the average annual CPI is expected to grow 5.1 percent in 2022, up from 4.7 percent last year.
RELATED: Inflation: Gas prices will get even higher
Inflation is defined as a rise in the price of goods and services in an economy over time. When there is too much money chasing too few products, inflation occurs. After the dot-com bubble burst in the early 2000s, the Federal Reserve kept interest rates low to try to boost the economy. More people borrowed money and spent it on products and services as a result of this. Prices will rise when there is a greater demand for goods and services than what is available, as businesses try to earn a profit. Increases in the cost of manufacturing, such as rising fuel prices or labor, can also produce inflation.
There are various reasons why inflation may occur in 2022. The first reason is that since Russia’s invasion of Ukraine, oil prices have risen dramatically. As a result, petrol and other transportation costs have increased. Furthermore, in order to stimulate the economy, the Fed has kept interest rates low. As a result, more people are borrowing and spending money, contributing to inflation. Finally, wages have been increasing in recent years, putting upward pressure on pricing.