BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM

DIVISION OF RESEARCH AND STATISTICS

For release at 9:15 a.m. EST

February 14, 2014

Industrial Production and Capacity Utilization:

The 2012 Annual Revision

February 2014
Industrial Production and Capacity Utilization:

The 2012 Annual Revision

Justin Pierce, of the Board’s Division of Research and Statistics, prepared this article.

The Federal Reserve published revisions to its index of industrial production (IP) and

related measures of capacity and utilization on March 30, 2012. Revisions were minor and the

overall contour of total IP was little changed. In particular, a decline of 17 percent from

December 2007 to June 2009 was followed by steady gains beginning in the second half of 2009

and continuing through early 2012. Measured from fourth quarter to fourth quarter, total IP was

reported to have dropped about 1/4 percentage point more in 2009, while its gains in both 2010

and 2011 were essentially unchanged from what was previously reported. From the trough of the

most recent recession in June 2009 through February 2012, total IP reversed about three-fourths

of its peak-to-trough decline.

Table 1. Industrial Production and Capacity

Utilization: 2007-11

2007 2008 2009 2010 2011

Industrial production - rates of change

Revised 2.5 -9.0 -5.7 6.3 3.9

Previous 2.5 -9.1 -5.5 6.2 3.8

Capacity utilization rates

Revised 80.4 73.2 69.5 75.4 77.7

Previous 81.1 73.6 70.3 76.1 78.1

Note: Rates of change are from the fourth quarter of the

previous year to the fourth quarter of the specified year.

Utilization rates are for the fourth quarter of the specified

year.

The revised IP indexes incorporated from the U.S. Census Bureau’s Annual Survey of

Manufactures (ASM) detailed data on factory activity for 2010 and revised data for 2009. In

addition, the revised estimates include annual data for 2010 both from the Census Bureau’s

Current Industrial Report (CIR) program and from the U.S. Geological Survey regarding metallic

and nonmetallic minerals (except fuels). The monthly estimates of production were updated to

incorporate late-arriving or revised monthly or quarterly data on indicators (either outputs from or

inputs to production), and they also reflect recalculations of seasonal factors. New data sources

were also incorporated into the revised estimates, including replacements for the data from the

CIR program, which was discontinued in mid-2011.

NOTE: Charles Gilbert directed the 2012 revision and, with Kimberly Bayard, David Byrne, Norman

Morin, and Daniel Vine, prepared the revised estimates of industrial production. Norman Morin and Jessica Stahl

prepared the revised estimates of capacity and capacity utilization. Eliot Fuchs provided research assistance.

1
Capacity utilization rates for recent years were revised down. The revisions showed that

the rate of capacity utilization for total industry was 0.7 percentage point lower in the fourth

quarter of 2010 and 0.4 percentage point lower in 2011 than previously estimated, primarily as a

result of small upward revisions to estimates of industrial capacity. The capacity utilization rate

for the fourth quarter of 2008 was revised down 0.3 percentage point, and the rate in the final

quarter of 2009 was revised down about 0.8 percentage point. Nonetheless, the revisions did not

affect the broad contour of capacity utilization. In 2008, the capacity utilization rate for total

industry, at 73.2 percent, was 7.1 percentage points below its long-run (1972–2011) average.

Utilization rates fell in the first half of 2009 and then steadily increased through the end of 2011.

The level in the fourth quarter of 2011, at 77.8 percent, was 2.5 percentage points below its

long-run average.

The revised estimates of capacity and capacity utilization incorporated data for the fourth

quarter of 2011 from the Census Bureau’s Quarterly Survey of Plant Capacity Utilization

(QSPC), which covers the manufacturing sector; new data on capacity in the energy and mining

sectors from the U.S. Geological Survey, the U.S. Department of Energy (DOE), and other

organizations; physical data on capacity for some manufacturing industries from government and

trade organizations; and data on industry capital spending from the 2010 ASM.

TECHNICAL ASPECTS OF THE REVISION

This revision incorporated new comprehensive data from the 2010 ASM and revised data

from the 2009 ASM for production and value added by manufacturing industries. Revised price

indexes from the Bureau of Economic Analysis (BEA) and updated price indexes constructed by

the Federal Reserve for a few selected industries were also incorporated.1In addition, the updated

production indexes include revisions to the measures of employment and production-worker

hours from the monthly Current Employment Statistics survey by the Bureau of Labor Statistics

(BLS). The benchmark indexes for logging and publishing (included in the IP index for

manufacturing but no longer included under manufacturing in the North American Industry

Classification System (NAICS)) were updated through 2010 based on data from the U.S. Forest

Service and the Census Bureau.

The revised IP indexes incorporated information from selected CIRs for 2011, the QSPC

for 2011, and other annual industry reports. The indexes also incorporated revised or late-arriving

monthly and quarterly source data on production, shipments, and inventories.

1 Price indexes for pharmaceuticals (NAICS 325412), semiconductors (NAICS 334413), and four of the six

components of communications equipment (NAICS 3342) are constructed by the Federal Reserve from alternative

sources. A table that lists annual and quarterly price indexes for the networking equipment component of

communications equipment can be found in table 14 of the published annual revision.

2
Annual Benchmark Output Indexes and the Conversion to the 2007 North

American Industry Classification System

As part of the annual revision, a benchmark output index—defined as nominal gross

output divided by a price index—was constructed for each six-digit industry under the NAICS. In

this revision, the benchmark indexes were calculated for 1972 forward based on industries defined

by the 2007 NAICS; previously the benchmark indexes had been based on the 2002 NAICS

definitions of industries. Likewise, the industry basis for capacity and utilization was changed to

the 2007 NAICS. The 2007 NAICS included 16 six-digit manufacturing industries that had

different coverage than in the 2002 NAICS. For example, one industry included in the 2002

NAICS—laboratory apparatus and furniture manufacturing (NAICS 339111)—was eliminated;

its various components were distributed among seven different six-digit industries in the 2007

NAICS.

The conversion to the 2007 NAICS did not affect the number or the structure of individual

IP series that are published because the changes to the NAICS occurred at a finer level of

industrial detail than the corresponding published IP series. For example, the most-disaggregated

IP index that included NAICS 339111 is the IP series for medical equipment and supplies

(NAICS 3391), which includes several other six-digit industries (NAICS 339112, 339113,

339114, 339115, and 339116) that are present in both the 2002 NAICS and the 2007 NAICS.

Although the number and structure of the published IP series were not affected by the

transition to the 2007 NAICS, the benchmark indexes for some industries needed to be updated.

Looking again to the eliminated NAICS 339111, establishments that were assigned to this

industry under the 2002 NAICS were reassigned to one of a handful of other industries in the

2007 NAICS. To create a consistent history, the Federal Reserve needed to construct new

benchmarks for each receiving industry. The construction of these new benchmarks made use of a

concordance between industries under the 2007 NAICS and those under the 2002 NAICS that

was issued in 2011 by the Census Bureau as part of the 2007 Economic Census. This

concordance showed how shipments from 2002 NAICS industries would have been allocated to

2007 NAICS industries, and vice versa. These estimated allocations were then applied to

historical data to construct both gross output estimates and price indexes on a 2007 NAICS basis

going back to 1972.2 Some of the adjustment factors used to align monthly production indicators

with benchmarks of IP series were also re-estimated. These new estimates were applied to IP

indexes for recent years, as well as to those used only in earlier periods.3

Benchmark indexes are measures of real gross output at the six-digit NAICS level. The

Census Bureau provides annual values for value added and the cost of materials, which can be

2 The Census of Manufactures and the ASM report their data based on the most recent industry classification

system. Ideally one would like to allocate each establishment that responded to past versions of these surveys to a

2007 NAICS industry. When NAICS superseded the Standard Industrial Classification system in 1997, previous

Censuses of Manufactures were recomputed by assigning each respondent to a NAICS industry. For the smaller

changes to NAICS since 1997, it has been assumed that the proportion of establishments that moved from one

NAICS industry to another under the new classification was constant historically.

3 The monthly production indicators include product data, production-worker-hour data, and, from the 1960s

to 1997, electric power use by industry.

3
summed to obtain nominal gross output.4 The benchmark indexes for this revision incorporated

new estimates of nominal gross output for 2010, as well as revisions to the 2009 estimates, from

the ASM. The IP index is a Fisher index and the individual real gross output benchmarks are

aggregated using value-added weights. To obtain real gross output, the measures of nominal gross

output were deflated by annual price deflators. Most of the deflators for the IP benchmarks were

derived from the industry shipments deflators issued by the BEA in December 2011. The BEA

deflators were available on a 2002 NAICS basis, so they needed to be converted to the 2007

NAICS structure before being applied to the detailed nominal gross output data.

Since 2003, the ASM has not included separate data for every six-digit manufacturing

industry; some industries are accounted for only in the aggregate data for a larger group of

industries. The 2007 Economic Census, however, still contained separate data for each six-digit

industry. For 2003 through 2006, the IP benchmark indexes were calculated by allocating the data

from these combined industries to their six-digit components based on interpolation between each

component’s share of the total in the 2002 and 2007 Economic Censuses. Data from the 2008,

2009, and 2010 ASMs were allocated to the component six-digit industries solely based on shares

from the 2007 Economic Census.

Changes to Individual Production and Capacity Series

Computers

This revision updated the methods used to calculate four IP series for computers: business

desktop computers, consumer desktop computers, business mobile computers, and consumer

mobile computers. These four IP series are all components of NAICS 334111. The source data

for computers come from the International Data Corporation (IDC) and measure quarterly U.S.

domestic absorption of computers. The 2010 annual revision reported that the Federal Reserve

received absorption data only for total desktops and total mobiles but had ceased to acquire

detailed information on the business and consumer components of these platforms. With this

revision the Federal Reserve resumed the acquisition from the IDC of absorption data on business

and consumer desktops and mobiles.5In addition to current-quarter data, the IDC has provided

historical information, so the four IP series can be constructed with a consistent methodology

from the beginning of the IDC data in 1994 and continuing through the present. As shown in chart

1, the relative importance of production for the business market varies significantly over time, and

the newly acquired IDC data revised down the share for business computer output appreciably.

To construct the IP indexes, the Federal Reserve seasonally adjusted the IDC information

on quarterly domestic absorption and smoothed the data using a model of the relationship

4 Historically, the Census Bureau also provided measures of the cost of resales at the six-digit level, which

were included in the nominal benchmark. In recent years, however, the cost of resales has not always been available,

so to maintain consistency, the Federal Reserve has excluded the cost of resales from the rates of change for the

benchmark indexes from 2003 forward.

5 Production of multi-user computers, such as servers, is assumed to be exclusively sold to the business

market.

4
2006 2007 2008 2009 2010 2011 2012

68

70

72

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76

78

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82

84

86

68

70

72

74

76

78

80

82

84

86

Percent Percent

Previous

Revised

1. Business Share of Computer Production (NAICS 334111)

between shipments and production. These estimates of nominal production for the U.S. market

were then multiplied by an estimate of the ratio of domestic production to domestic absorption by

product, based on the Census Bureau’s CIRs and additional outside research.

Prior to this revision, the production indexes for computer storage devices and computer

terminals (NAICS 334112 and NAICS 334113) and for other computer peripheral equipment

(NAICS 334119) were based on nominal shipments data from the quarterly CIR deflated by the

relevant BLS producer price indexes for 2007 through the second quarter of 2011, the date of the

last published CIR data. For the period after the final CIR data, these IP indexes were extended

based on statistical models that predict changes in output based on changes in the production of

personal computers and of servers.6

Natural gas extraction

This revision incorporated new and timelier information to supplement the primary

source data for the IP series for natural gas extraction (NAICS 211111, part). The main source

data for this IP series are billions of cubic feet of U.S. natural gas marketed production (wet) from

the DOE’s Natural Gas Monthly report. The DOE report is generally issued with a three-month

lag; for example, when IP is published in mid-April, natural gas data are only available through

6 Approximately half of the annual variation in the output of storage and terminals and of peripherals is

explained by the domestic absorption of personal computers and servers as reported by IDC.

5
January even though the IP window runs through March.

With this revision, the data from the DOE were augmented by data from Bentek Energy.

Bentek provides daily information on the production of natural gas, and the data are available

with a lag of only one day. The Federal Reserve converts the data from Bentek to a monthly

frequency and uses them as a secondary source to inform early estimates for natural gas extraction

until the data from the DOE become available. The timeliness of the Bentek data allows for IP

estimates based on source data through the most recent month of the publication window. The

incorporation of the Bentek data has been shown to reduce revisions to earlier months for the

natural gas extraction index, a series that represented more than 4 percent of total IP in 2011.

Trucks

This revision incorporated new data and methods for estimating the shares of light truck

output associated with business output and with consumer output. The IP indexes for light trucks

(NAICS 336112) are constructed from data on total assemblies from WardsAuto. Because the IP

structure parses industry output into demand-based segments called market groups, it is necessary

to assign vehicle assemblies into business and consumer components. The IP indexes use data

from the BEA and annual data from CNW Research on the number of leased trucks to help

determine the business and consumer shares of both car and truck production. With this revision,

the Federal Reserve incorporated monthly data from the National Truck Equipment Association

(NTEA) on factory shipments of class 2 and 3 truck chassis and from WardsAuto on factory

shipments of light trucks in classes 1 through 3 to extend and interpolate the annual figures for the

business share of overall light truck production.7

The monthly variable used for this interpolation is a weighted average of indexes (base

year 2002) derived from the NTEA data and the WardsAuto data, with a two-thirds weight given

to the WardsAuto data (derived from regression results estimating the relative correlation of the

two monthly data series with the target annual index). The data from the NTEA are monthly

factory shipments of class 2 and class 3 chassis that subsequently have bodies installed and are

used by businesses. The data from WardsAuto are shipments of trucks in classes 1, 2, and 3, with

a weight of 0.1 attached to class 1 trucks, a weight of 0.4 attached to class 2 trucks, and a weight

of 1.0 attached to class 3 trucks to reflect estimates of the percentages of the different classes of

trucks being sold to businesses.

Veneer, plywood, and engineered wood product

The capacity series for veneer, plywood, and engineered wood product (NAICS 3212)

has been updated with this revision. Previously, the series only used data from the Composite

Panel Association (CPA) on the capacity of particleboard and fiberboard producers. With this

revision, the capacity estimates continued to use the CPA data but also incorporated information

7 Trucks are split into eight classes on the basis of vehicle weight, with class 1 trucks being the lightest and

class 8 trucks the heaviest. Light trucks comprise classes 1 through 3.

6
on the capacity of producers of plywood and oriented strand board from APA, the Engineered

Wood Association. As a result, the data used to calculate capacity represent a greater share of the

industry.

Discontinuation of the U.S. Census Bureau’s CIRs

In mid-2011, the U.S. Census Bureau discontinued its CIR program. The CIR data

releases provided detailed product information at monthly, quarterly, and annual frequencies for a

variety of industries. The last release of monthly data was for July 2011, and the last release of

quarterly data was for the second quarter of 2011. The Federal Reserve extensively used the CIRs

in its indexes of industrial production and capacity utilization, and their elimination necessitated

changes in underlying source data for several IP series. Taken together, the monthly and quarterly

CIRs provided physical product data for slightly more than 2.5 percent of total IP.

The following list shows the monthly CIRs that were used in industrial production and, in

parentheses, their corresponding IP series:

1. M311J: Fats and Oil: Oilseed Crushings (Corn oil; Soybean and other oilseed processing)

2. M311K: Fats and Oils: Production, Consumption, and Stocks (Fats and oils refining and

blending)

3. M313P: Consumption on the Cotton System and Stocks (Fiber, yarn, and thread mills)

With this revision, each of these three affected IP series used production-worker hours to extend

the discontinued monthly CIR data.

The list below shows the discontinued quarterly CIRs that were used in industrial production

with their associated IP indexes in parentheses:

1. MQ311A: Flour Milling Products (Flour milling and malt)

2. MQ325A: Inorganic Chemicals (Acids, phosphates, and sulfates; Other inorganic chemicals)

3. MQ325B: Fertilizers and Related Chemicals (Other inorganic chemicals; Fertilizer)

4. MQ325F: Paint, Varnish, and Lacquer (Construction paints; Industrial paints)

5. MQ327D: Clay Construction Products (Ceramic tile and refractory; Brick and structural clay

tile; Other structural clay product)

6. MQ333W: Metalworking Machinery (Machine tools)

7. MQ334P: Telecommunications (Data networking equipment; Transmission, local loop, and

legacy central office equipment; Enterprise and home voice equipment; Satellites and earth station

equipment; Wireless system equipment; Radio and TV broadcasting equipment excluding

satellites and other communications equipment)

7
8. MQ334R: Computers and Peripheral Equipment (Computer storage and terminals, business;

Computer storage and terminals, consumer; Computer printers and peripheral equipment,

business; Computer printers and peripheral equipment, consumer).

Other than the changes to IP series described in the next section, this revision used

production-worker hours to extend the IP series associated with the discontinued quarterly CIRs.

Updated Data Sources for Quarterly Series Formerly Covered by CIRs

For some of the IP series that previously relied on quarterly CIRs, the Federal Reserve

used alternate measures of physical output to replace the discontinued data. These series and the

replacement data sources are described in the following paragraphs.

Fertilizer

With this revision, the IP series for fertilizer (NAICS 32531) used monthly data on

nitrogen and phosphate fertilizer from the Fertilizer Institute (TFI) as the primary source of data

on output. Previously, the monthly TFI data were used as a secondary source for months for

which the quarterly CIR data were not yet available, and they were also used to interpolate the

quarterly data to a monthly frequency.

Communications equipment

The IP aggregate index for communications equipment (NAICS 3342) comprises six

product-based indexes. Each of the six indexes incorporated quarterly data on nominal shipments

at the detailed product level from the Census Bureau’s relevant CIRs from the first quarter of 2007

to the second quarter of 2011. With this revision, data from the QSPC are used to extend each of

the six IP series from the third quarter of 2011 through the present.

The QSPC, conducted since 2007, reports capacity utilization rates for manufacturing

industries at a quarterly frequency. In recent years, the utilization rates from the QSPC for

communications equipment have tracked nominal output—as measured by the discontinued

CIR—fairly well. With this revision, the nominal data on communications equipment from the

CIR were extended based on the change in the industry operating rate from the QSPC and the

change in a quarterly interpolation of annual capital services for this industry (constructed from

historical investment data and a survey of investment plans).

The deflators for the resulting estimates of nominal output continued to be producer price

indexes from the BLS and price indexes constructed by the Federal Reserve staff from price data

from Dell’Oro. The four IP indexes within communications equipment for which nominal output

is deflated by the Federal Reserve price indexes are Data networking equipment; Enterprise and

home voice networking equipment; Wireless network equipment; and Transmission, local loop,

and legacy central office equipment. These four product classes accounted for approximately

8
18 percent of overall communications equipment production in 2011, a share that has declined

markedly over the past several years. To construct the quarterly indicator price indexes, the

Federal Reserve staff use information on quarterly worldwide unit shipments and revenue for

detailed product categories to construct unit values and then aggregate them using a Fisher index

formula. At the time of annual benchmarking, information on additional products is included to

expand coverage and refine these estimates. The deflators for the remaining two IP indexes

(Satellites and earth station equipment; Radio and TV broadcasting equipment (excluding

satellites) and other communications equipment) are constructed from BLS producer price

indexes and a price index for satellites estimated by the Federal Reserve staff.

Computers

Prior to this revision, the now-discontinued quarterly CIR for computers and peripheral

equipment (NAICS 3341) was used for four IP indexes (Computer storage and terminals,

business; Computer storage and terminals, consumer; Computer printers and peripheral

equipment, business; Computer printers and peripheral equipment, consumer). These four indexes

cover all of NAICS 3341 except for Electronic computers (NAICS 334111). Six other IP indexes

cover NAICS 334111. These six indexes rely on data from the IDC on U.S. domestic absorption

of desktops, mobiles, and servers. In the absence of the CIR data, IDC data on personal

computers were used to extend the IP indexes for computer storage and terminals, and IDC data

on non-x86 servers were used to extend the IP indexes for computer printers and peripherals.

Weights for Aggregation

The IP index is a Fisher index. The weights for manufacturing industries are derived from

value-added measures from the Census of Manufactures and the ASM. The Federal Reserve

derives estimates of value added for the electric and gas utility industries from annual revenue and

expense data issued by other organizations. The weights for aggregation, expressed as value

added per unit, were estimated with the latest data on producer prices for the period after 2010.

Table 12 of the published annual revision release shows the annual value-added proportions in the

IP index from 2004 through 2011.

Revised Quarterly and Monthly Data

This revision incorporated product data that became available or were revised after the

regular six-month reporting window for monthly IP was closed. These data were released with

too great a lag to be included with monthly IP estimates but were available for inclusion in the

annual revision.

9
Revised Seasonal Factors

Seasonal factors for all series were re-estimated using data that extend into 2012. Factors

for production-worker hours—which adjust for timing, holiday, and monthly seasonal

patterns—were updated with data through January 2012. The updated factors for the physical

product series, which include adjustments for holiday and workday patterns, used data through

December 2011 where available. Seasonal factors for unit motor vehicle assemblies were updated

prior to the revision, and projections are on the Board’s website.8

Pre-adjustment of data to account for the effects of recessions

Seasonal factors for IP were primarily estimated with the Census Bureau’s X-12-ARIMA

program. Generally speaking, the X-12 procedure separates a time series into three components:

trend plus cycle, seasonal, and irregular. The trend-plus-cycle component is based on a moving

average of the data, but for some series the moving average does not adequately capture the

abruptness of the swings that occur during a recession and subsequent recovery. Consequently,

some of the pattern of the recession may bleed into the estimated seasonal factors for the

recession period as well as the factors for the years around it. Should that occur, the resulting

seasonally adjusted series might look strong both before and after the recession in the calendar

months around the month in which the trough of the recession was reached. With the 2010 annual

revision, the Federal Reserve introduced a pre-adjustment for many indexes to account for the

effects of the recent recession prior to running X-12. The 2012 revision continued those

pre-adjustments where necessary.

It has long been known that recessions affect the results of seasonal adjustment

procedures that use the ratio-to-moving-average method.9 Prior to the advent in the 1950s of the

Census Bureau’s computer programs for estimating seasonal factors, the Federal Reserve’s

seasonal adjustment procedure estimated the trend-plus-cycle component of the data by fitting a

freehand curve (based on a 12-month moving average of the original data) to the major

nonseasonal movements in the series. With this technique, sharp movements in the series could

be incorporated in the curve without distorting the combined seasonal and irregular components

(known as the S-I ratios).

With the adoption of the Census computer programs for estimating seasonal factors,

additional measures have occasionally been taken to limit the impact that a recession might have

on estimated seasonal factors. In the course of the 1959 revision to IP, the 1957–58 recession was

recognized as distorting the seasonal factors, so only data through 1957 were used in the

estimation of the seasonal factors.

8 See Board of Governors of the Federal Reserve System, “Federal Reserve Seasonal Factors for Domestic

Auto and Truck Production,” Board of Governors, www.federalreserve.gov/releases/g17/mvsf.htm.

9 Most of the following material on previous work to remove recession-related distortions from the estimated

seasonal factors for IP is condensed from the 1986 manual on Industrial Production. Board of Governors of the

Federal Reserve System (1986), Industrial Production, 1986 Edition, with a Description of the Methodology

(Washington: Board of Governors), pp. 80–83.

10
Likewise, when working on the 1976 revision to IP, the Federal Reserve staff deemed that

the sharp drop in IP in late 1974 and the subsequent recovery were distorting the factors, so the

estimated factors only used data through 1974. In the work on the subsequent 1976–78 revision,

however, the 1973–74 recession continued to distort the seasonal factors, but the staff determined

that if they only used data up to the recession period they would discard too much information

from the period subsequent to the downturn. Two procedures were used to attempt to offset this

problem. In the first, the indexes from 1967 to 1973 were linked to the indexes from 1976 to

1978, and seasonal factors were calculated from that series. The second technique involved

replacing the values for 1974 and 1975 with more-typical values based on data for the preceding

and subsequent years. The results of both procedures were similar.

The 1985 annual revision to IP incorporated the Box-Tiao intervention technique. The

procedure involved estimating an autoregressive integrated moving average (ARIMA) model with

additive outliers specified for the recession period. The values for the additive outliers were then

subtracted from the values for the recession period before X-11 was run.10 For all practical

purposes, the resulting series contained values for the recession period that reflected their typical

seasonal patterns outside of the recession.

The Box-Tiao intervention technique continued to be used in subsequent annual revisions

for periods severely affected by a recession. In addition, some indicator series were filtered using

a robust detrending procedure before being fed into X-12. The robust detrending procedure uses a

mixture of moving medians and moving averages to estimate a trend for a series (see details in the

appendix). The removal of this trend from a series often reduces the spurious recession effect on

the seasonal factors.

The 2010 annual revision to IP relied on extensive use of the robust detrending procedure

along with the specification of additive outliers for the 2008–09 recession for many indexes. The

staff determined the additive outliers on a judgmental basis. The staff compared the existing

seasonally adjusted indexes with the indexes that were seasonally adjusted after incorporation the

recession-period data but that did not have additive outliers specified. Interventions were then

specified for those IP indexes for which the revision to the seasonally adjusted series tended to

temper the depth of the recession in the period around the trough.

A prime example of the need for pre-adjustment of some series to minimize the impact of

the recession on the estimated seasonal factors is the IP index for raw steel, which dropped

abruptly in late 2008 and early 2009. The decrease, which averaged about 10 percent a month

from October 2008 through April 2009, was then followed by gains that averaged 5 percent a

month through the rest of 2009. During this period of rapid contraction and recovery, the output

gains and losses did not exhibit their normal seasonal pattern. The solid line in chart 2 represents

the average daily output of raw steel for the months from 2004 to 2011 as available when the

seasonal factors for IP were estimated for the revision. The dashed line shows its trend,

determined by X-12. The unusual pattern of the output swings in 2008 and 2009 is most easily

seen in chart 3: The solid line shows the ratio of raw steel output to its trend from X-12 (the S-I

10 At the time of the 1985 annual revision, X-11 was the current version of the Census computer program for

estimating seasonal factors.

11
2004 2005 2006 2007 2008 2009 2010 2011

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2. Raw Steel Output

2004 2005 2006 2007 2008 2009 2010 2011

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S-I ratio

X-12 seasonal factors

3. Raw Steel Output: S-I Ratio and X-12 Seasonal Factors

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2004 2005 2006 2007 2008 2009 2010 2011

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X-12 after preadjustment

4. Raw Steel Output: Seasonal Factors

ratio). After being automatically adjusted for extreme values by X-12, this ratio is used to

estimate the seasonal factors for the series. The S-I ratio gyrates in a more extreme fashion

around the end of 2008 and into 2009 than it does during other periods shown; it also does not

exhibit the typical seasonal pattern in that the timing of the crash and rebound leaves the third

quarters of both 2008 and 2009 well above their trend. The dashed line in chart 3 represents the

seasonal factors estimated by the default X-12 settings. Because X-12 calculates seasonal factors

using moving averages, the effect of an anomaly in any period’s data diminishes as the estimates

move further away from the anomaly. Comparing factors from 2007 forward to those up to 2006,

one can see that X-12 translated the new data into factors that are stronger in the third quarter and

weaker in the second quarter.

In estimating seasonal factors for the raw steel index, the Federal Reserve pre-adjusted

the index with the robust detrending procedure and treated the data from November 2008 through

October 2009 as additive outliers—in effect replacing the actual values with more-typical values

based on periods outside those 12 months. Chart 4 shows the resulting factors. The solid line

represents the seasonal factors from the default X-12 specification, and the dashed line represents

the factors calculated by applying X-12 to the pre-adjusted series. Although there is some

evolution in the seasonal pattern based on the pre-adjusted series, the basic pattern of a strong

early part of the year and a weaker third quarter is evident throughout the time span. Chart 5

shows the raw steel output series seasonally adjusted using default X-12 specifications (solid line)

and the series that results from factors estimated using the pre-adjusted data (dashed line). For

2010 and 2011, the series based on default specifications appears strong early in the year only to

13
2004 2005 2006 2007 2008 2009 2010 2011

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Tons

Default X-12

X-12 after preadjustment

5. Raw Steel Output: Seasonally Adjusted Series

fall back by the third quarter, whereas some of this pattern is ameliorated in the series using

factors that were estimated with the pre-adjusted data.

APPENDIX: ROBUST DETRENDING ALGORITHM

The robust detrending algorithm comprises the following steps:

1. Let V1 be the logarithm of variable V.

2. For every period t, let V2 be the median of the following 13 terms: (V1[t-5], V1[t-4], ...,

V1[t+5], median(V1[t-6],... V1[t+5]), median(V1[t-5],..., V1[t+6])).

3. Let V3 be V2 augmented by forecasts and backcasts of V2 using the latest and earliest

six-month averages of 12-month rates of change for V1.

4. Let V4 be the 2x12 centered moving average of V3.

5. Let V5 be 0.4*V4+0.6*V3 for periods when abs(V4-V3) is greater than 0.4*std. dev.(V4-V3) and

otherwise be V4.

6. Let V6 be the 13-term Henderson moving average of V5, normalized to have the same average

over the entire date span as V1.

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7. The final trend is V6 exponentiated.

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