**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: *Value Added (VA)*. The graphic below (featured image) illustrates the breakdown of *Value Added* as a contributor to *Output* visually.

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

**WHAT IS IT?**

* Value Added* represents the difference between *Output* and the cost of *Intermediate Expenditures* throughout a defined economy during a specified period of time. Because it represents such a large portion of *Output*, *Value Added (VA)* encompasses many other representative metrics by which the economy is measured during that period, including *Labor Income (LI)*, *Proprietor Income (PI)*, *Employee Compensation (EC)*, *Other Property Income (OPI)*, and *Taxes on Production and Imports (TOPI)*, The graphic below (fig. 1) illustrates their contributions to *Value Added* visually.

Fig. 1

**WHY IS IT IMPORTANT?**

* Value Added (VA)* figures communicate a lot of information in just one number. Because they represent the collective value of so many other economic measurables, *Value Added (VA)* figures are always among 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 widely publicized—and heavily scrutinized—figures from users' completed reports. For this reason, establishing a thorough understanding of what *Value Added (VA)* figures 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 *Value Added*, its components, and the relationships between them as contributors to *Output* enables users to interpret resulting *Value Added (VA)* figures with more accuracy.

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

As with any economic indicator, *Value Added (VA)* figures exist at many different levels of granularity. Because *Value Added* represents the difference between *Output* and the cost of *Intermediate Expenditures*, a given *Value Added (VA)* figure may represent that difference throughout an entire regional economy, a single industry, relative to the production of a single commodity, and more. So, because such a variety of different *Value Added (VA)* figures can exist, they reside in multiple locations in the IMPLAN tool. Generally speaking, the two locations where *Value Added (VA)* figures 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, *Value Added (VA)* figures exist at multiple levels of granularity, so there are many different tabular locations on the *RESULTS* screen at which *Value Added (VA)* figures of specific granularities may be found.

Fig. 3

**HOW IS IT CALCULATED?**

There are multiple ways to calculate a *Value Added (VA)* figure. Because it represents such a large portion of total production, *Value Added* 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 *Value Added* 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 four most granular components of a *Value Added (VA)* figure are *Other Property Income (OPI)*, *Proprietor Income (PI)*, *Employee Compensation (EC)*, and *Taxes on Production and Imports (TOPI)*. Think of these metrics as the individual "atoms" which collectively form *Value Added*—the numerical building blocks of each and every *Value Added (VA)* figure. The graphic below (fig. 4) illustrates this concept visually.

Fig. 4

Knowing the explicit values of each of its four most granular components always offers the most transparency into a given *Value Added (VA)* figure. Mathematically speaking, such transparency makes defending figures 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 figures are composed, more informed and comprehensive conclusions can ultimately be drawn from them.

**Example 1**

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

Fig. 5

Let's use the information provided in the scenario below (fig. 6) to manually calculate total *Value Added* 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 four most granular components are known. So, calculating total *Value Added* is simple: just add them all up! Their sum total collectively represents *Value Added (VA)*. The graphic below (fig. 7) summarizes the information provided in the scenario visually.

Fig. 7

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

*OPI*equals

**,**

*3,673,625.97**PI*equals

**,**

*51,930.16**EC*equals

**, and**

*1,594,288.36**TOPI*equals

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

*108,550.63**Value Added (VA)*to equal

**.**

*5,428,395.12*Fig. 8

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

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

* Example 1* demonstrates how simple calculating a *Value Added (VA)* figure is when the explicit values of each of its four 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 *Value Added (VA)* figures 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), *Value Added (VA)* figures can be calculated by adding *OPI*, *LI*, and *TOPI*. The resulting sum also represents *Value Added (VA)*.

**Example 2**

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

Fig. 10

Let's use the information provided in the scenario below (fig. 11) to manually calculate total *Value Added *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 four of its most granular components, we still have enough information to calculate total *Value Added*. Because we understand the relationships between *OPI*, *LI*, and *TOPI*, we know that *Value Added (VA)* figures 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 *Value Added *can be calculated by "solving for X", where "X" represents ** VA**,

*OPI*equals

**,**

*3,673,625.97**LI*equals

**, and**

*1,646,218.52**TOPI*equals

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

*108,550.63**Value Added (VA)*to equal

**.**

*5,428,395.12*Fig. 13

**...When you use Output (O) as a reference**

**...When you use Output (O) as a reference**

*Example 2* demonstrates how a *Value Added (VA)* figure may be calculated when the explicit values of only some of its components are known—more specifically, when only two of them are known: *OPI *and *TOPI*. 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 a *Value Added (VA)* figure, 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 *Value Added (VA)* figures. You'll notice in the graphic below (fig. 14) that *Value Added (VA)* and the cost of *Intermediate Expenditures (IE)* each serve as one half of the largest composite metric, *Output (O)*.

Fig. 14

Given that *O* represents the sum total of *VA* and *IE*, in cases where *O* and *IE* are explicitly known, *Value Added (VA)* figures can be calculated by subtracting *IE* from *O*. The resulting difference also represents *Value Added (VA)*.

**Example 3**

The formula below (fig. 15) expresses the relationship between *Value Added (VA)* and *IE* as contributors to *O*.

Fig. 15

Let's use the information provided in the scenario below (fig. 16) to manually calculate total *Value Added *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 *Value Added*. Because we understand the relationship between *VA* and *IE* as contributors to *O*, we know that *Value Added (VA)* figures can be calculated by subtracting *IE* from *O*. The graphic below (fig. 17) summarizes the information provided in the scenario visually.

Fig. 17

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

*O*equals

**, and**

*12,019,681.35**IE*equals

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

*6,591,286.23**Value Added (VA)*to equal

**.**

*5,428,395.12*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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