Deflators

What are deflators and when are they used in IMPLAN?

The purchasing power of a dollar changes over time (typically decreasing) due to inflation, a cyclical phenomenon by which prices of goods and services increase[1], which spurs workers to demand higher wages, which in turn increases demand for goods and services, thereby spurring additional price increases, and so on.  Due to inflation, a dollar in 2017 cannot purchase as much as did a dollar in 2001, for example; as such, a 2017 dollar is not the same thing as a 2001 dollar.  IMPLAN’s deflators are indexes of inflation, with the deflator for the model data year set at 1.00. 

The deflators are not used to create the social accounts or multipliers but are necessary for impact analysis whenever the dollar year of the event differs from the year of the model data.  The same model year multipliers are used regardless of the dollar year of the event; it is the value applied to those multipliers that changes when the dollar year of the event differs from the year of the model data.  Indeed, if one were to run an un-customized event using an event year that differs from the model year but views the results in the same year as the model, the multipliers calculated from these results will match the multipliers displayed in the multipliers tables of the model.

Why is this adjustment needed?

All the relationships in the multipliers are based on model year prices, so the direct effects applied to those multipliers need to also be in model year dollars – this is accomplished via the deflators.  The value applied to the multipliers is the user-entered value divided by the deflator.  The deflators also allow impact results to be viewed in years other than the model year, regardless of whether or not the dollar year of the event differs from the year of the model data. 

While the event values and/or result values can be inflated or deflated, depending on whether the index value being applied is less than 1.00 or greater than 1.00 (i.e., depending on the industry/commodity and whether one is adjusting to a future or past value), we use a single term – deflators – to refer to all of these index values.

The output deflators are specific to the industry/commodity and are applied to the output value, while the same GDP deflators are the same for every industry/commodity and are applied to all of the value-added components.

Source data

The Bureau of Economic Analysis (BEA) provides historical output deflators which we use for past to current years.  For projections into the future, we use the annual rate of change from the Bureau of Labor Statistics’ (BLS) employment growth model.  The BEA also has historical GDP deflators which we use for past to current years.  For projections into the future, we use the annual rate of change from the BLS employment growth model for “All Industries”. 

 

[1] Not all goods and services are inflationary every year.  For example, the prices of consumer electronics often decrease over time.  As another example, the prices of agricultural commodities rise and fall in response to many factors, including weather.

Exporting data from IMPLAN to GAMS

Event Template

Template for specifying Events for importing into an IMPLAN Pro Model.

 

Template for specifying Events for importing into an IMPLAN (V5) Model.

 

2013-2017 Common Margins and Deflators

2013 Common Margins

 

2014 Common Margins

 

2015 Common Margins

 

2016 Common Margins

 

2017 Common (PRO) Margins

 

2017 Common (IMPLAN5) Margins

 

2016 Common Deflators

 

2017 Common Deflators

 

536 Sector Bridges and Conversions

440 to 536 Bridge

This bridge allows you to convert from the 440 sectoring scheme (2007-2012 data years) to the new 536 sectoring scheme. Note that the ratios only work one way: The 440 to 536 bridge is useful for converting 440-based sectors to 536-based sectors, but is not useful for converting 536-based sectors to 440-based sectors.

In the 440 to 536 bridge, a ratio of 1 means that 100% of the 440 sector should be classified as the corresponding 536 sector. In theory, there could be any number of sectors with a ratio of 1 merged into a single sector. So, the ratio of 1 for two different 440-based sectors simply means that both fit entirely into the same 536-based sector. In general, this happens rarely since we disaggregated more sectors than we aggregated.

 
 

536 Definitions of Construction Sectors

Spreadsheet of the new sectoring scheme for 2013 data.

 

536 FTE & Employee Compensation Conversion Table (2013)

IMPLAN jobs are not FTE equivalents. This spreadsheet allows you to convert between IMPLAN jobs and FTEs or FTEs and IMPLAN jobs with simple ratios for each Industry.

Also, many people are given wage and salary data, but not Employee Compensation (which is a fully loaded payroll value) or prefer to report in W&S.
This sheet also provides information for making these conversions. Data on the original federal data sources used in these derivations is also provided.

 

536 FTE & Employee Compensation Conversion Table (2015)

IMPLAN jobs are not FTE equivalents. This spreadsheet allows you to convert between IMPLAN jobs and FTEs or FTEs and IMPLAN jobs with simple ratios for each Industry.

Also, many people are given wage and salary data, but not Employee Compensation (which is a fully loaded payroll value) or prefer to report in W&S.
This sheet also provides information for making these conversions. Data on the original federal data sources used in these derivations is also provided.

 

536 FTE & Employee Compensation Conversion Table (2017)

IMPLAN jobs are not FTE equivalents. This spreadsheet allows you to convert between IMPLAN jobs and FTEs or FTEs and IMPLAN jobs with simple ratios for each Industry.

Also, many people are given wage and salary data, but not Employee Compensation (which is a fully loaded payroll value) or prefer to report in W&S.
This sheet also provides information for making these conversions. Data on the original federal data sources used in these derivations is also provided.

 

536 Government Enterprises Descriptions

Government Enterprise Sectors 518-526 can incorporate multiple NAICS descriptions. This spreadsheet provides the NAICS description breakdowns for these specialty Sectors.

 

536 List of Industry & Commodities

The attached spreadsheet has the final industry list (same list of industries as the previous version, but with a few re-worded titles). It also has the list of commodities and includes NAICS codes (not NAICS descriptions).

 

Bridge 536 to 440 Sectors

This bridge allows you to convert from the 536 Sectoring scheme (2007-2012 data years) to the 440 Sectoring scheme. Note that the ratios only work one way: The 536 to 440 bridge is useful for converting 536-based Sectors to 440-based Sectors, but is not useful for converting 440-based Sectors to 536-based Sectors.

In the 536 to 440 bridge, a ratio of 1 means that 100% of the 536 Sector should be classified as the corresponding 440 Sector. In theory, there could be any number of Sectors with a ratio of 1 merged into a single Sector. So, the ratio of 1 for two different 536-based Sectors simply means that both fit entirely into the same 440-based Sector. In general, this happens rarely since we disaggregated more Sectors than we aggregated.

 

IMPLAN 536 to Default Sectoring Scheme Breakdown

This Excel sheet associates each of the 536 Sectoring Scheme sectors with one of the eight Default Sectoring Scheme sectors.

 

Investment FFE Only by 536 Sector

Investment Spending Pattern (Furniture, Fixtures, and Equipment only) with 536 commodities.

 

Investment with Structures by 536 Sector

Investment Spending Pattern with Structures 536 Sector includes the not only the FFE splits based on construction type but also includes a split of total cost to include the primary structure types.

 

NAICS (2012) to IMPLAN 536 Bridge

This sheet provides the conversion from BEA’s 2012 NAICS to IMPLAN 536 Sectors.

 

NAICS (2017) to IMPLAN 536 Bridge

This sheet provides the conversion from BEA’s 2017 NAICS to IMPLAN 536 Sectors.

 

IMPLAN to Aggregated NAICS

This sheet provides the conversion from 2-digit and 3-digit NAICS codes to IMPLAN Sectors. 

 

PCE by NIPA Category 536 Sector

 

SLGovt spending by program 536 Sector

 

546 Sector Industries, Conversions, Bridges, & Construction – 2018 Data

The following downloads are for the 2018 data. They are not valid for the 536 Sectoring scheme used in datasets from 2013-2017.

 

IMPLAN 546 Industries and Commodities

 

 

2017 NAICS to IMPLAN 546 Sectors

Convert BEA’s 2017 NAICS codes to IMPLAN Sectors (546 scheme) using this downloadable spreadsheet.

 

2012 NAICS to IMPLAN 546 Sectors

Convert BEA’s 2012 NAICS codes to IMPLAN Sectors (546 scheme) using this downloadable spreadsheet.

 

Definitions of IMPLAN’s 546 Construction Sectors

View the breakdown of IMPLAN’s construction sectors (546 scheme) using this downloadable spreadsheet. 

 

536 TO 546 BRIDGE

This bridge allows you to convert from the 536 sectoring scheme (2013-2017 data years) to the new 546 sectoring scheme. Note that the ratios only work one way: The 536 to 546 bridge is useful for converting 536-based sectors to 546-based sectors, but is not useful for converting 546-based sectors to 536-based sectors.

In the 536 to 546 bridge, a ratio of 1 means that 100% of the 536 sector should be classified as the corresponding 546 sector. In theory, there could be any number of sectors with a ratio of 1 merged into a single sector. So, the ratio of 1 for two different 536-based sectors simply means that both fit entirely into the same 546-based sector. In general, this happens rarely since we disaggregated more sectors than we aggregated.

 

546 TO 536 BRIDGE

This bridge allows you to convert from the 546 sectoring scheme to the old 536 sectoring scheme (2013-2017 data years) . Note that the ratios only work one way: The 546 to 536 bridge is useful for converting 546-based sectors to 536-based sectors, but is not useful for converting 536-based sectors to 546-based sectors.

In the 546 to 536 bridge, a ratio of 1 means that 100% of the 546 sector should be classified as the corresponding 536 sector. In theory, there could be any number of sectors with a ratio of 1 merged into a single sector. So, the ratio of 1 for two different 546-based sectors simply means that both fit entirely into the same 536-based sector. In general, this happens rarely since we disaggregated more sectors than we aggregated.

Utility Purchases & Energy Rebates

INTRODUCTION:

IMPLAN economists are often asked about best practices when modeling changes in utility prices and rebates on energy purchases.  This article gives some general guidance on how to best proceed when investigating these situations.  

 

DETAILS:

The first step in looking at changes in energy prices is to determine who is the producer and the consumer. In IMPLAN, utilities are produced by both Industries (Sectors 41-51) and Government (Sectors 519, 522, & 525).  Consumers of utilities can be Households, Industries, and Government.

Perhaps you want to model a price change in the Commodity, not knowing if it will be produced by a firm or the government.  If this is the case, consider using a Commodity such as 3041 – Electricity.

Next, you will need to make assumptions about the price increases or decreases that will be modeled – who will be affected and if that change is positive or negative.  This will frame your analysis.

 

House.png  HOUSEHOLDS:

A popular case to examine is modeling increased income that households would see from a decrease in utility pricing or from utility rebates.  To model this, a Household Income Change (HHIC) is a great option. The HHIC will remove personal taxes and savings before calculating the results.  

Any changes to household spending will be at the same rate across all spending categories.  This means that even though the savings might be spent on increased retail shopping or entertainment, the spending pattern will allocate the savings across all household purchases, which doesn’t always make sense.  Just because someone saved money on their utility bill doesn’t mean their rent increased. Each analyst must determine how the savings will be spent.

In the case of a rate hike, you would see a reduction or negative impact in households.  Be careful in this case as well. Giving a household less disposable income doesn’t necessarily mean they won’t pay their student loans or buy groceries. They may instead cut their utility usage or decrease their entertainment budget. If the increase is small enough it may have little to no impact on household spending for any group. 

Remember, different households may respond differently, depending on the size of the rate increase, their needs, and income level. A larger increase will likely affect the spending of lower income households but may not affect the spending of higher income households as these payments may come from savings (leakages in IMPLAN). 

 

Plug.png INDUSTRIES:

PRODUCING

As a producer, Industries can be positively or negatively affected by price changes.  If the cost of inputs skyrockets or bottoms out, these price changes can’t immediately be passed on to the consumer, so short-term losses may occur.

Changes in Industries can be modeled through:

  • Sector 41 – Electric power generation – Hydroelectric
  • Sector 42 – Electric power generation – Fossil fuel
  • Sector 43 – Electric power generation – Nuclear
  • Sector 44 – Electric power generation – Solar
  • Sector 45 – Electric power generation – Wind
  • Sector 46 – Electric power generation – Geothermal
  • Sector 47 – Electric power generation – Biomass
  • Sector 48 – Electric power generation – All other
  • Sector 49 – Electric power transmission and distribution
  • Sector 50 – Natural gas distribution
  • Sector 51 – Water, sewage and other systems

CONSUMING

Estimating a change in Industry price or profit is outside of the scope of Input-Output analysis. Therefore, the analyst must make assumptions about where the price changes would occur and how to model them.

For a price reduction or rebate, the likelihood is that this savings would go into Other Property Income (OPI).  OPI in IMPLAN is treated as leakage. However, you may know that this savings is allowing the affected Industries to hire more staff or produce more widgets. This can be modeled in IMPLAN.

If you want to assume that the businesses cannot control the price of their products, any increase in utility costs could show a loss in profit. It might even be enough to shutter some businesses altogether.  More likely, however, they will just raise the price of their products to offset the higher bills.

 

Govt.png  GOVERNMENT:

PRODUCING

As a producer of utilities in many areas, the changing cost of inputs can affect the operating margin of government-run utilities.  Changes to government utility production can be modeled through one of the government utility Sectors:

  • Sector 519 – Federal electric utilities
  • Sector 522 – State government electric utilities
  • Sector 525 – Local government electric utilities

CONSUMING

Governments can be affected negatively by increased utility costs, as well.  More money being spent on electricity, for example, decreases the overall budget and might lead to program cuts or elimination.  Often this is just in the short-run, however, as increased costs will likely be passed onto the consumer.

Governments can see savings as well when utility costs decrease. Analysts will need to determine how to model these cost savings. Knowing how the savings will be spent is key to being able to modeling the impact. If a new school is built with the savings, then a simple construction Event is appropriate.  Perhaps you may only know which government entity will spend the savings, in which case you should choose from the Institutional Spending Patterns.  When using an Institutional Spending Pattern, remember to modify it to remove the purchases of Commodities related to the utility generation you are examining.

 

Wrench.png  CONSTRUCTION:

Although temporary in nature, construction projects conducted by utility companies are often large and costly.  Consider modeling this as a separate impact from operations or price changes.

 

Double_Arrow.png  NET ANALYSIS:

If a government entity is considering building a new facility to produce utilities more efficiently in the long-term, a Net Analysis should be used to model both the losses to private Industry and the cost savings to Government (increased spending) or Households (additional HH income).  This assumes, however, that the utility company would not continue to produce that Commodity and that the previous local consumption could not be replaced by non-local consumption (exports).

 

RELATED TOPICS:

Electricity Generation + Distribution FAQ

Methodology for Development of the 2017 Detailed Production Functions for IMPLAN’s Nine Electrical Power Sectors