Excel for Economics Students: The Skills Coursework Needs

Excel for economics students comes down to a handful of skills that appear in almost every problem set: growth rates, index numbers, real versus nominal values, elasticities, summary statistics, charts, simple regression and PivotTables. Each one is a short formula or a few clicks once you know the pattern. This guide shows each skill on small example data you can type in, so you can use it in coursework now and in an analyst job later.

The numbers below describe an imaginary economy. They are for practice, not real statistics.

Percent change and growth rates#

Percent change is the most used formula in economics: the new value minus the old value, divided by the old value. Here is nominal GDP for the example economy, in billions:

In D3, type:

=(B3-B2)/B2

Format it as Percent. Nominal growth is 8.0% in 2023 and, after filling down, 7.4% in 2024. The guide to the percent change formula covers negative values and the "percentage points" trap.

For growth over several years, use the compound annual growth rate (CAGR):

=(B4/B2)^(1/2)-1

The result is about 7.7% a year over two years. The ^ sign raises to a power. The CAGR formula guide explains how to count the periods correctly. Some courses use log growth instead: =LN(B3/B2) returns about 0.077 for 2023.

Index numbers with a base year#

An index number shows each value relative to a base year set to 100. Divide each value by the base-year value and multiply by 100:

=B2/$B$2*100

Fill it down: 2022 is 100, 2023 is 108 and 2024 is 116. The $ signs lock the base year, so every row divides by B2 while the top of the fraction moves. Without them, every row would divide by itself and show 100. Indices make series with different units easy to compare on one chart.

Real vs nominal values#

Real values remove the effect of price changes. Divide the nominal value by the price index for the same year and multiply by 100:

=B3/C3*100

Real GDP in 2023 is about 519.2, in 2022 prices. For 2024 it is about 537.0. Put these real values in column E by typing =B2/C2*100 in E2 and filling down, then calculate real growth on that column: =(E4-E3)/E3 returns about 3.4% for 2024. That is much lower than the 7.4% nominal growth, because prices rose too.

How to calculate elasticity in Excel#

Price elasticity of demand compares the percent change in quantity with the percent change in price. The midpoint (arc) method divides each change by the average of the two values, so the answer is the same whether the price rises or falls:

=((C3-C2)/AVERAGE(C2:C3))/((B3-B2)/AVERAGE(B2:B3))

The quantity changes by -20 / 90 = -0.222 and the price by 2 / 11 = 0.182, so the elasticity is about -1.22. Its absolute value is above 1, so demand is elastic over this range. The simple method, =((C3-C2)/C2)/((B3-B2)/B2), gives -1.0 instead, which is why textbooks prefer the midpoint version. The AVERAGE function guide covers the averaging part.

Summary statistics and charts#

Describe a data series before you analyse it. The core functions are:

For charts, use a line chart for a time series, such as GDP by year, and a scatter chart for the relationship between two variables, such as price and quantity. Select the data and go to Insert > Charts. The guide to making a scatter plot in Excel shows how to add a trendline and its equation.

Simple regression in Excel#

Excel handles the regressions most undergraduate courses start with. With x values in B2:B21 and y values in C2:C21:

• =SLOPE(C2:C21,B2:B21) returns the slope coefficient.
• =INTERCEPT(C2:C21,B2:B21) returns the constant.
• =RSQ(C2:C21,B2:B21) returns R squared.

Note that y comes first in all three. For several explanatory variables, LINEST returns all the coefficients at once. For a full output table with standard errors, t statistics and p-values, turn on the Analysis ToolPak (Windows: File > Options > Add-ins > Excel Add-ins > Go; Mac: Tools > Excel Add-ins), then use Data > Data Analysis > Regression.

For large panel datasets or advanced econometrics, a dedicated statistics package is the better tool. Excel is ideal for checking results, small datasets and presenting findings.

PivotTables for data by country and year#

Economic data often comes as a long list: one row per country, year and variable. A PivotTable turns that into a summary table in seconds. Click inside the data, choose Insert > PivotTable, then drag Country to Rows, Year to Columns and the value to Values. Change the summary from Sum to Average when the values are rates, such as unemployment, because adding rates gives a meaningless number.

PivotTables, percent change and clean formulas are also what employers test. The guides to Excel skills for fresh graduates and Excel skills for data analysts show how these skills appear in job applications. To see where you stand now, take the Excel level test.

Practise it#

The fastest way to get comfortable is to type these formulas yourself. Practise percent change in a live spreadsheet, practise AVERAGE, MIN and MAX, and build your first PivotTable: you type the formula and it checks it instantly. Or try the exercise on this page and calculate a midpoint elasticity.