**CONTENTS**

The contents of this article are outlined below. If you already know what you're looking for, click on a link to advance to a specific section!

**INTRODUCTION**

We get a lot of questions about specific metrics and how they relate to one another within the context of impact analyses with IMPLAN. Users are often interested in what's captured within certain values to ensure that they're both inputting data into IMPLAN correctly and interpreting the results they pull out of IMPLAN correctly. The remainder of this article delves into one specific metric: *Output (O)*. The graphic below (featured image) illustrates the breakdown of *Output* visually.

Featured image: *The Components of Output (O)*

**WHAT IS IT?**

* Output* represents the total value of all goods and/or services produced throughout a defined economy during a specified period of time. Because it represents the total value of production, *Output (O)* encompasses all other representative metrics by which the defined economy is measured during that period, including *Value Added (VA)*, *Labor Income (LI)*, *Proprietor Income (PI)*, *Employee Compensation (EC)*, *Other Property Income (OPI)*, *Taxes on Production and Imports (TOPI)*, and the cost of *Intermediate Expenditures (IE)*. The graphic below (fig. 1) illustrates the capture of all economic production by *Output* visually.

Fig. 1

**WHY IS IT IMPORTANT?**

* Output (O)* values communicate a lot of information in just one number. Because they represent the collective value of so many other economic measurables, *Output (O)* values are always the largest representative metrics included in a given regional data set (relative to their granularity) or produced by a given impact analysis. This often results in them becoming some of the most (if not *the* most) widely publicized—and heavily scrutinized—figures from users' completed reports. For this reason, establishing a thorough understanding of what *Output (O)* values truly represent and exactly how they're calculated is one of the most effective steps that an IMPLAN user can take in preparing to defend their study's findings against possible critique. Plus, a comprehensive grasp of *Output*, its components, and the relationships between them enables users to interpret resulting *Output (O)* values with more accuracy.

**WHERE CAN I FIND IT IN IMPLAN?**

As with any economic indicator, *Output (O)* values exist at many different levels of granularity. While *Output* represents the value of total production, a given *Output (O)* value may represent the total production of an entire regional economy, a single industry, a single commodity, and more. So, because such a variety of different *Output (O)* values can exist, they reside in multiple locations in the IMPLAN tool. Generally speaking, the two locations where *Output (O)* values can be found in IMPLAN are on the *REGIONS* screen and on the *RESULTS* screen. Below is a brief discussion about the difference between the types of values in each location.

**...On the REGIONS screen**

**...On the REGIONS screen**

If modeling an economic impact with IMPLAN is akin to examining an economy in a hypothetical "before and after" scenario, then think of the metrics on the *REGIONS* screen (fig. 2) as the "before" numbers. The *REGIONS* screen offers a massive assortment of data points which allow users to examine defined economies inside and out by browsing industry- and/or commodity-specific figures like employment numbers, wages paid, spending behavior, and much, much more in one centralized location.

Fig. 2

**...On the RESULTS screen**

**...On the RESULTS screen**

If metrics found on the *REGIONS* screen reflect the resting state of a defined economy (the "before" numbers), then those found on the *RESULTS* screen (fig. 3) reflect the state of it after the occurrence of the real-life project being modeled (the "after" numbers). As with any economic indicator, *Output (O)* values exist at multiple levels of granularity, so there are many different tabular locations on the *RESULTS* screen at which *Output (O)* values of specific granularities may be found.

Fig. 3

**HOW IS IT CALCULATED?**

There are multiple ways to calculate an *Output (O)* value. Because it represents total production, *Output *is made up of many components which may form other composite metrics in their own right when grouped or combined in specific ways. So, calculating *Output *requires exploiting the relationships between any components of it which are explicitly known and any which are not since each component represents a different "piece of the same numerical whole".

**...When you know EVERY component**

**...When you know EVERY component**

The five most granular components of an *Output (O)* value are *Other Property Income (OPI)*, *Proprietor Income (PI)*, *Employee Compensation (EC)*, *Taxes on Production and Imports (TOPI)*, and the cost *Intermediate Expenditures (IE)*. Think of these metrics as the individual "atoms" which collectively form *Output*—the numerical building blocks of each and every *Output (O)* value. The graphic below (fig. 4) illustrates this concept visually.

Fig. 4

Knowing the explicit values of each of its five most granular components always offers the most transparency into a given *Output (O)* value. Mathematically speaking, such transparency makes defending values easy because their demonstrable calculations can simply be replicated as proof. Analytically speaking, such transparency puts users in the most powerful position possible because with such a wealth of detail about how values are composed, more informed and comprehensive conclusions can ultimately be drawn from them.

#### **Example 1**

The formula below (fig. 5) expresses the breakdown of *Output* into *OPI*, *PI*, *EC*, *TOPI*, and *IE*.

Fig. 5

Let's use the information provided in the scenario below (fig. 6) to manually calculate total *Output* for the featured industry.

Fig. 6

*The values presented in the scenario above are entirely fictional and do not reflect those from any actual regional economy. Any similarities to those of an actual regional economy are purely coincidental.

In the scenario above (see fig. 6), the explicit values of each of the five most granular components are known. So, calculating total *Output* is simple: just add them all up! Their sum total collectively represents *Output (O)*. The graphic below (fig. 7) summarizes the information provided in the scenario visually.

Fig. 7

Using the formula above (see fig. 5), total *Output* can be calculated by "solving for X", where "X" represents * O*,

*OPI*equals

**,**

*3,673,625.97**PI*equals

**,**

*51,930.16**EC*equals

**,**

*1,594,288.36**TOPI*equals

**, and**

*108,550.63**IE*equals

**. The calculation below (fig. 8) reveals**

*6,591,286.23**Output (O)*to equal

*.*

**12,019,681.35**Fig. 8

**...When you only know SOME components**

**...When you only know SOME components**

*Example 1* demonstrates how simple calculating an *Output (O)* value is when the explicit values of each of its five most granular components are known. However, there are many instances in which users don't have access to large volumes of data. In fact, more often than not, users' access to data is limited and the values of one or more components are not explicitly known to them. Fortunately, by using metrics which are known to derive the values of others which are not, it may still be possible to calculate *Output (O)* values in many of these cases. You'll notice in the graphic below (fig. 9) that *Proprietor Income (PI)* and *Employee Compensation (EC)* each serve as one half of a larger composite metric called *Labor Income (LI)*.

Fig. 9

Given that *LI* represents the sum total of *PI* and *EC*, in cases where *LI* is explicitly known (but *PI* and *EC* are not), *Output (O)* values can be calculated by adding *OPI*, *LI*, *TOPI*, and *IE*. The resulting sum also represents *Output (O)*.

#### **Example 2**

The formula below (fig. 10) expresses the breakdown of *Output* into *OPI*, *LI*, *TOPI*, and *IE*.

Fig. 10

Let's use the information provided in the scenario below (fig. 11) to manually calculate total *Output *for the featured industry.

Fig. 11

*The values presented in the scenario above are entirely fictional and do not reflect those from any actual regional economy. Any similarities to those of an actual regional economy are purely coincidental.

In the scenario above (see fig. 11), despite not knowing the explicit values of all five of its most granular components, we still have enough information to calculate total *Output*. Because we understand the relationships between *OPI*, *LI*, *TOPI*, and *IE*, we know that *Output (O)* values can be calculated by summing them. The graphic below (fig. 12) summarizes the information provided in the scenario visually.

Fig. 12

Using the formula above (see fig. 10), total *Output *can be calculated by "solving for X", where "X" represents ** O**,

*OPI*equals

**,**

*3,673,625.97**LI*equals

**,**

*1,646,218.52**TOPI*equals

**, and**

*108,550.63**IE*equals

**. The calculation below (fig. 13) reveals**

*6,591,286.23**Output (O)*to equal

**.**

*12,019,681.35*Fig. 13

*Example 2* demonstrates how an *Output (O)* value may be calculated when the explicit values of only some of its components are known—more specifically, when only three of them are known: *OPI*, *TOPI*, and *IE*. In these cases, the other two, *PI* and *EC*, are simply fused together from the outset to provide the value of *LI*. While this combination of components still provides us with enough information to calculate an *Output (O)* value, it doesn't grant us the same degree of mathematical or analytical transparency that we gained in *Example 1*. To make matters more challenging, there are many instances in which a user's access to data is so limited that even an *LI* value will not be known to them. However, there's still hope...because even in cases like these, it may still be possible to calculate *Output (O)* values. You'll notice in the graphic below (fig. 14) that *Other Property Income (OPI)*, *Proprietor Income (PI)*, *Employee Compensation (EC)*, and *Taxes on Production and Imports (TOPI)* each serve as one quarter of an even larger composite metric called *Value Added (VA)*.

Fig. 14

Given that *VA* represents the sum total of *OPI*, *PI*, *EC*, and *TOPI*, in cases where *VA* is explicitly known (but its components are not), *Output (O)* values can be calculated by adding *VA* and *IE*. The resulting sum also represents *Output (O)*.

**Example 3**

The formula below (fig. 15) expresses the breakdown of *Output* into *VA* and *IE*.

Fig. 15

Let's use the information provided in the scenario below (fig. 16) to manually calculate total *Output *for the featured industry.

Fig. 16

*The values presented in the scenario above are entirely fictional and do not reflect those from any actual regional economy. Any similarities to those of an actual regional economy are purely coincidental.

In the scenario above (see fig. 16), despite knowing the explicit values of only two data points, we still have enough information to calculate total *Output*. Because we understand the relationship between *VA* and *IE*, we know that *Output (O)* values can be calculated by summing them. The graphic below (fig. 17) summarizes the information provided in the scenario visually.

Fig. 17

Using the formula above (see fig. 15), total *Output *can be calculated by "solving for X", where "X" represents ** O**,

*VA*equals

**, and**

*5,428,395.12**IE*equals

**. The calculation below (fig. 18) reveals**

*6,591,286.23**Output (O)*to equal

**.**

*12,019,681.35*Fig. 18

**ADDITIONAL RESOURCES**

Below are some additional resources which may prove helpful in your pursuit of a more comprehensive understanding of *Output*, its components, and/or the relationships between them.

Related to: *Output*

- For information on
*Output*, see.*Understanding Output (O)*

Related to: *Value Added*

- For information on
*Value Added*, see*Understanding Value Added (VA)*.

Related to: *Labor Income*

- For information on
*Labor Income*, see*Understanding Labor Income (LI)*.

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