Consumer Price Index

Hedonic Quality Adjustment Methods

For Clothes Dryers In the U.S. CPI

Paul R. Liegey

1

Preface

As previously announced, BLS is extending the use of quality adjustments derived from hedonic models in the CPI. A hedonic model decomposes the price of a consumer product into implicit prices for each of its important features and components, thereby providing an estimate of the value for each price-influencing feature and component.

Effective with the CPI for October 2000, BLS has extended hedonic quality adjustments to washing machines and clothes dryers, two products in the Major Appliances item stratum.2 The relative importance (share of weight), as of December 1999, for this stratum was 0.205 percent in the CPI for all Urban Consumers (CPI-U) and 0.236 percent in the CPI for Urban Wage Earners and Clerical Workers (CPI- W). Within Major Appliances, washing machines are estimated to represent 18 percent of the weight and clothes dryers about 13 percent. Other products employing hedonic quality adjustments in the Major Appliances item stratum are refrigerator/freezers and microwave ovens.3 The remaining products in this stratum—those that are not subject to hedonic quality adjustment at this time—include freezers and stoves and ovens.

Of the three different approaches or methods that use the results from hedonic regression models to quality adjust price indexes, the Bureau of Labor Statistics (BLS) employs the 'matched model' method in its official indexes.4 This method controls for quality changes based on the difference in product specifications or characteristics between two items when a substitute observation, or quote, occurs in the price index sample. It is important to note that under the 'matched model' approach only substitution price changes are eligible for hedonic quality adjustments.

The U.S. Consumer Price Index (CPI) for Major Appliances would have remained unchanged instead of the official index decline of 0.1 percent if hedonic quality adjustment methods had been applied to clothes dryer (substitution) price changes from October 1999 through June 2000 (see attachment 1). During the study period, clothes dryer prices accounted for approximately 15 percent of the monthly Major Appliances sample, and averaged only two (substitution) price changes per month (see attachment 2).

Background

The first clothes dryer was invented in France by Pochon in 1799 and was called ventilator for drying clothes.5 This apparatus required wet clothes be wrung out by hand, placed in a cylindrical metal drum pierced with holes or slits, and hand driven by a crank over a fire. The clothes would dry out, but they might burn, and would always smell strongly of smoke and possibly pick up soot from the smoke.

In 1930, J. Ross Moore built the first electronic drying device for clothes.6 Moore developed both gas and electric clothes dryers and patented his invention in 1936. Financial difficulties led Moore to sell his clothes dryer design to the Hamilton Manufacturing Company in 1937. Between 1938 and 1941, Hamilton Manufacturing Company sold more than 6,000 clothes dryer units.

In 1947, the first post war year of full production, Hamilton Manufacturing Company, General Electric and other entrants into the clothes dryer market sold approximately 41,000 and 20,000 units of electric and gas clothes dryers, respectively.7 Currently, factory shipments of clothes dryers total around six million units per year and sales of electric units are three times as great as those of gas clothes dryers (see attachment 3).

By the mid-1950s, about ten percent of U.S. households owned a clothes dryer at a price of around $230 per unit—roughly $1600 in calendar year 2000 dollars. Ownership of clothes dryers increased to about 45 percent of U.S. households by 1970 and the unit price at that time was around $190—approximately $850 in calendar year 2000 dollars. By 1997, about 78 percent of U.S. households owned a clothes dryer with a unit price of around $340—about $370 in calendar year 2000 dollars.8 Measuring in calendar year 2000 dollars, the unit price for clothes dryers has declined by about 77 percent from the mid-1950s to 1997.

The steep decline in (modern) clothes dryer prices—as measured in calendar year 2000 dollars—reflects the increase in consumer purchasing power over these appliances while numerous quality improvements have occurred over the last 50 years. Attachment 4 provides a brief chronology of (modern) clothes dryer quality characteristic improvements since their creation in the 1930s.

Clothes dryers were introduced into the CPI sample in 1963.9 Since their inclusion in the CPI, clothes dryers have been represented in three item stratum price indexes over four CPI revisions:

  • Finally, with the release of the revised CPI in January 1998, clothes dryers became part of the Major Appliances item stratum. The index level for this item stratum in December 1997 was 100.0 (its base year), and through October 2000 is 96.5 — an overall price index decline of 3.5 percent for the most recent 34 month period.
  • Clothes dryers were selected as a product that would benefit from hedonic regression modeling since manufacturers provide a selection of types, brands, sizes, and features. In the August 2000 Consumer Report issue, the latest annual review on clothes dryers notes that "compared with washers, dryers are relatively simple. Their major distinctions are how they heat the air (gas or electric) and how they're programmed to shut off once the load is dry (thermostat or moisture sensor). Both will affect how much you'll pay to buy and run your machine."10

    Newer models of clothes dryers are included for price index calculations only if older models being used in the price index sample are no longer available (in the CPI outlets) for CPI pricing. When a newer model replaces an older model in the CPI, the price change that is used in the index is referred to as substitution price change. Substitution price change can be either "pure" (directly compared or quality adjusted) or "imputed" (not compared).

    From October 1999 through June 2000 Major Appliances employed, on average, 218 price changes to calculate the U.S. level monthly price index (see attachment 2). Approximately nine percent, or 19, of these price changes were substitution price changes. In comparison, clothes dryers accounted for, on average, 32 of the 218 price changes used to calculate the Major Appliances index, and averaged (just) two substitutions per month from October 1999 through June 2000.

    Data

    Sample selection for the Hedonic Model

    The official CPI sample of clothes dryer prices used to calculate the Major Appliances CPI was too small for hedonic regression estimation. Using a process that mimics the official CPI sample selection process, an additional sample of 194 consumer businesses, or outlets, was chosen to augment the official CPI sample for clothes dryers. This additional outlet sample was used to select a sample of clothes dryer prices. The supplementary sample was used only for estimating the hedonic regression model for clothes dryers.11

    CPI field economists were instructed to collect a total of 400 clothes dryer prices in the sample of 194 additional outlets. Individual clothes dryer brand and models were selected by grouping all clothes dryers in a particular outlet into two groups—the "standard" clothes dryers and "better model" or higher quality clothes dryers. Once categorized into these two groups, the CPI field economist was instructed to select a "good selling" clothes dryer from each of the "standard" and "better model" groups.

    About 69 percent of the additional sample price quotes that were collected for clothes dryers had price and characteristic data that could be used in the regression model. The most common reason that CPI field economists could not collect the additional sample price quotes for clothes dryers was respondent refusal.12 A total of 341 prices—and characteristic descriptions—were used to estimate the hedonic model for clothes dryers. This total sample consists of 64 official CPI observations and 277 additional sample observations.

    Price and Characteristics Data for the Hedonic Model

    All of the price and characteristics data used for the clothes dryer hedonic model were captured on CPI data collection documents, or checklists, for this item (see last attachment).

    The prices that were collected for the clothes dryer sample represent "retail offer" prices. As the name suggests, a retail offer price represents what a consumer business is willing to sell an item for which may, or may not, differ from the transaction price—what a consumer actually paid for the item. Retail offer prices, like transaction prices, may change through time depending on whether the item being sold is offered at a "regular" price or a "sale" price.

    The set of quality attributes collected for each of the 341 clothes dryers in the sample are represented on the CPI checklist for this item (see last attachment). In each of the quality characteristic categories, CPI field economists selected the specific characteristic element that best described the item they were pricing. For example if an electric clothes dryer with a (drum volume) capacity of 6.0 cubic feet had been selected by the field economist, this would be designated on the CPI data collection document by selecting the A1 and D5 specification elements—see last attachment.

    When possible, secondary source information such as manufacturer websites and consumer information magazines—including Consumer Digest’s and Consumer Reports—were used to verify the accuracy of the characteristic data collected on the CPI checklist for clothes dryers.

    Model

    The hedonic model that is specified for clothes dryers in this study uses the quality characteristics that were collected on the CPI checklist for this item (see last attachment). The independent variables in the model fall into three groups similar to the hedonic model for dishwashers referenced by Greenlees (2000).13 In particular, technical appliance characteristics, product brands and outlet types—as well as other control type variables—are tested in iterative regressions to determine their impact on the natural logarithm of price, the dependent variable. Twelve preliminary regressions are presented in Attachment 5 to give the reader a sense of the model development through completion.

    The CPI prices that are collected in this sample represent "retail offer" prices, and approximately 38 percent of these prices were collected "on sale." The mean price for all clothes dryers in the sample is $488.78. The mean price for "regular" priced clothes dryers in the sample is $511.36 and the mean price for "sale" priced clothes dryers is $452.86. Since type of price (that is, regular or sale) is thought to have an impact on the overall price level, a dummy variable for sale price is included in the model to capture this effect, and its expected coefficient sign is negative.

    A priori

    expectations about which clothes dryer characteristics influence price were developed, when possible, from industry information, manufacturer websites, and consumer information magazines and websites.

    Clothes Dryer Types

    Two types of clothes dryers—electric and natural gas—are sold in today's market. Electric models are sold more frequently by retailers and account for approximately 65 percent of the clothes dryers in the sample. Typically, retail offer prices for electric dryers are less then gas dryers. An August 2000 Consumer Reports study on clothes dryers finds that "the saving in energy costs should cover the slightly higher purchase price (of gas models) within the first year."14

    Mean prices for the 223 electric models and 118 gas models in the hedonic sample were $418.54 and $620.42, respectively. By way of comparison, the Consumer Reports article (referenced above) on clothes dryers shows that the electric models they tested retailed for an average of $489.09 while the natural gas models retailed for an average of $560.00. Dummy or indicator variables are created for both types of clothes dryers. The gas variable included in preliminary hedonic models is expected to have a large, positive impact on price.

    Clothes Dryer Capacity

    A fact sheet issued by the University of Nebraska maintains that "differences between clothes dryers are largely capacity, price and dryer size (physical dimensions of the dryer)."15 Manufacturers and retailers advertise drum capacity in terms of cubic feet. Drum capacity can assume a wide range of numeric values—see the CPI checklist for clothes dryers (last attachment). To accommodate this potential wide range of values, a continuous variable is created for capacity (in cubic feet). It is assumed that the price of clothes dryers increases with increasing values of this variable. For example, a 7.0 cubic foot dryer is assumed to sell for a higher price than a 5.0 cubic foot dryer ceteris paribus.

    Clothes Dryer Dry Cycles

    As noted in Shepler (2001) "the cycle category was difficult for the data collectors since manufacturers do not always list every single (wash) cycle and they also use different terminology for similar cycles."16 The dry cycle specification category on the clothes dryer checklist—see last attachment—proved to be just as problematic as the wash cycle category for clothes washers in terms of obtaining a complete and consistent description across specific brands and model numbers. In addition to the eight dry cycles listed on the checklist, there is also a specification category for number of dry cycles. Manufacturers and retailers tend to do a better job at reporting the number of dry cycles rather than listing each cycle. Secondary source information was used to verify / overwrite the information in the sample data set and a variable for number of dry cycles is created. It is assumed that dryers with a greater number of dry cycles provide consumers with greater drying functionality and have a positive impact on price.

    Preliminary models are specified with two dummy variables, sale price and gas dryer, and two continuous variables, capacity (in cubic feet) and number of dry cycles (see Attachment 5, Iterative regressions 1 and 2). The first model specification with sale price, gas dryer and capacity (in cubic feet) proved to explain a significant portion of the variation in (the natural log of) price with an R2 of slightly less than 54 percent. The magnitude, direction and significance of the parameter estimates in this first preliminary model generally conformed to a priori expectations

    Inclusion of the number of dry cycles variable resulted in somewhat lower tolerance values for the capacity (in cubic feet) and number of dry cycles parameter estimates and indicates that multicollinearity might be present in the model. Further investigation revealed that the pearson correlation coefficient, or measure of collinearity, for these two variables is positive and strong at 0.74—they tend to move together and can serve as a proxy for each other. The existence of multicollinearity causes the standard errors of the correlated variables to increase and the associated parameter estimates to be imprecise.17 Subsequent variations of these preliminary models—not included in Attachment 5—revealed that the variable for capacity (in cubic feet) provides a better overall fit for the model; therefore, this variable was included in the final model.

    Clothes Dryer Drying Mechanisms, Number of Temperature Settings and Control Types

    Other 'technical' clothes dryer characteristics are included in the "Drying Mechanisms," "Number of Temperature Settings," and "Control Types" specification categories on the CPI checklist (see last attachment) and are next considered in specifying the hedonic regression model for clothes dryers.

    According to the Department of Energy, "the best dryers have moisture sensors in the drum for sensing dryness, while most only infer dryness by sensing the temperature of the exhaust air. Compared with timed drying, you can save about 10% with a temperature sensing control, and 15% with a moisture sensing control."18 The moisture sensor characteristic is found in 54 percent of the clothes dryer sample while the temperature sensor and timed drying characteristics occur throughout the entire sample. It is assumed that the presence of a moisture sensor would have a positive impact on price.

    The number of temperature settings specification category on the CPI checklist—see last attachment—designates how many drying temperatures a user can select from on a specific brand and model.

    Most dryers have at least three temperature settings: regular, low, and cool. The more sophisticated the dryer, the greater the choice one has in temperature setting. Top-of-the-line models may have infinitely variable temperature settings. This allows users to fine-tune the temperature to the type of fabric being dried. Clothes dryers with three to five temperature settings comprise more than 80 percent of the sample. Secondary source information was used to verify / overwrite the information in the sample data set and a continuous variable for number of temperature settings is created. It is assumed that dryers with a greater number of temperature settings provide consumers with greater drying functionality and have a positive impact on price.

    In the "Control Types" specification category, dummy variables were created for electronic controls and push button or rotary dial manual controls. While most of the clothes dryers in today's appliance market possess push button or rotary dial manual controls some manufacturers are offering models with touch sensitive or electronic controls on their top of the line dryers. Electronic controls offer conveniences such as stored, customized temperature / cycle settings and easy to read displays. More than 90 percent of the clothes dryer price sample contained models with push button or rotary dial manual controls while the remaining 10 percent reflected electronic controls. It is expected that the electronic controls variable has a positive impact on price.

    The moisture sensor, number of temperature settings and electronic controls variables are tested in iterative regressions 3, 4 and 5—see Attachment 5. All three variables provide a positive and significant impact on (the natural log of) price while increasing the explanatory power of the successive hedonic models. The pearson correlation coefficient, or measure of collinearity, for the moisture sensor and number of temperature settings variables is positive and somewhat high at 0.55, but is deemed acceptable and the level of multicollinearity does not warrant exclusion of either variable. Representation of the "Drying Mechanisms," "Number of Temperature Settings," and "Control Types" specification categories from the CPI checklist (see last attachment), increases the overall explanatory power of the preliminary hedonic models from an R2 of slightly less than 54 percent—iterative regression 1—to an R2 of slightly more than 74 percent—iterative regression 5.

    Clothes Dryer Brands

    Brand

    is the next category of quality characteristics considered for use to specify the clothes dryer hedonic model. Of the 17 brands listed on the CPI checklist for this item (see last attachment), dummy or indicator variables are created for 11 brands that are collected in the clothes dryer hedonic sample. Triplett and McDonald (1977) note that "the interpretation and treatment of company (brand) effects in hedonic regressions is a perplexing problem for which there is not a straightforward solution."19 In this study, brand is thought to serve as a proxy for subtle and / or difficult-to-collect quality characteristics that represent the general level of quality for a given brand. Triplett and McDonald (1977) go on to include brand in their refrigerator hedonic regressions "because statistical tests revealed them relevant and important."20 Other hedonic studies on appliances have also found it beneficial to include brand.21

    Some a priori information about clothes dryer brands is found at ApplianceAdvisor.com, a consumer information website, which references 19 different brands of dryers.22 Of the 11 brands that are collected in the clothes dryer hedonic sample, 10 are included in iterative regression 6—see Attachment 5—excluding the most frequently occurring brand which accounted for a little more than 44 percent of the sample. In addition, three of the 10 brands included in preliminary models are excluded since they exhibited statistically insignificant parameter estimates.

    Inclusion of brand variables in preliminary model specifications yields a better explanatory fit with an R2 of slightly more than 84 percent—iterative regressions 6 through 12—from an R2 of slightly more than 74 percent—iterative regression 5. The seven brands that remained in iterative regressions 7 through 12 emerge as two distinct groups—the "medium" and "low" quality groups.23 These two distinct groups are clearly delineated in iterative regression 12 where the parameter estimates for each of the seven individual brands are listed in descending magnitude. The "medium" and "low" quality groups are compared to the "base" group—the "high" quality brands that are the most frequently occurring and not included in the preliminary models.

    An F test for brand equivalence is conducted for the brands in both the "medium" and "low" quality groups—see Attachment 5 after iterative regression 12. For both groups, the F tests fail to reject the null hypothesis that the brands are equivalent. The parameter estimates for both the "medium" and "low" quality groups are (highly) statistically significant and add just as much explanatory power to the model as the individual brands variables. Both the "medium quality" and "low quality" brand groups were included in the final model specification.

    Other Clothes Dryer Physical Characteristics and Features

    Both the "Number of Motor Speeds" and "Drying Drum Material" specification categories on the CPI checklist (see last attachment) proved to be difficult to collect in the field. The data for these specification categories had little variation when reported and is suspect since manufacturer websites did not consistently report this information in their product descriptions for clothes dryers. Subsequently, a decision was made not to use the data from these specification categories.

    Unlike washing machines, all clothes dryers are front loading.24 The "Door Style" category is included on the CPI checklist to collect information about whether the specific clothes dryer being priced is a side-pull (opens left or right) model or a front-pull (opens down) model. Side-pull doors can usually be purchased as either a left-swing or a right-swing door. A front-pull or hamper door saves lateral space and offers an additional 'shelf' on which to lay clothes for cooling down or folding. Dummy variables are created for both the side-pull and front-pull variables. The front-pull variable is assumed to have a positive impact on price and is tested in iterative regression 7. While the front-pull parameter estimate is positive and statistically significant, it has a (somewhat) high correlation with capacity (in cubic feet)—the pearson correlation coefficient is positive with magnitude of 0.64—and does not add any substantial explanatory power to the model. A judgment was made to exclude the "Door Style" specification category from the model.

    Manufacturers and retailers of clothes dryers offer and advertise a variety of features on their products. Clothes dryer features are represented in the "Features" specification categories on the CPI checklist (see last attachment). Dummy or indicator variables are created for all characteristics in this specification category. Each of the dummy variables is tested to see whether the overall fit of the model could be enhanced. Basic preliminary models used to test each of the features are presented in Attachment 5, iterative regressions 8 through 11.

    Of the seven dummy variables that are created for the "Features" specification category, all are excluded from the final regression model because of their poor performance in preliminary and subsequent regression models. In particular, the lint filter indicator and sound insulation variables are excluded from the final model because of statistical insignificance. Sound insulation is another example of a characteristic that is difficult to collect due to varying terminology and limited product descriptions in retail outlets. Secondary source information was used to verify / overwrite the sound insulation information collected for the sample data set but the parameter estimate for sound insulation remain insignificant.

    The drying rack, drum light and end of cycle signal variables are excluded from the final model because of multicollinearity with the capacity (in cubic feet) and moisture sensor variables. Inclusion of the drying rack, drum light and end of cycle signal variables produce (significant) movement in the magnitude of the parameter estimates for the capacity (in cubic feet) and moisture sensor variables—see iterative regression 9. The capacity (in cubic feet) and moisture sensor variables are thought to be more germane to the final model specification and the drying rack, drum light and end of cycle signal variables are excluded.

    The easy access lint filter variable is also excluded from the final model because it was assumed a priori that this variable should have a positive impact on price but its parameter estimate is consistently negative—see iterative regressions 8 through 11. Finally, the leveling legs feature was collected for 55 percent of the sample but increased to more than 90 percent of the sample when secondary source information was used to verify / overwrite this quality characteristic. Although the parameter estimate for leveling legs remained positive and statistically significant it was thought that this featured occurred even more frequently than reflected in the sample and is excluded from the final model.

    Clothes dryer features—like those collected on the CPI checklist for this product—are frequently touted by retailers and manufacturers as value enhancing but have not contributed (substantially) to the price, or value, of clothes dryers in this study.

    Clothes Dryer Miscellaneous Specifications

    Other CPI checklist specification categories that are examined for hedonic model development include manufacturer warranty, country of origin, as well as clothes dryer color. These CPI categories of specifications are found to have little variation in the clothes dryer sample. In particular, almost all clothes dryers that are sold in today's market come with a standard one year parts and labor manufacturer warranty. About 10 percent of the clothes dryer sample reflected a warranty other than one year parts and labor. Dummy variables were created for these other types of warranties but each of the parameter estimates for these other warranties tested statistically insignificant—see iterative regression 10. Subsequently, manufacturer warranty is excluded from the final hedonic model for clothes dryers.

    Similarly, the country of origin specification category on the CPI checklist is tested to see if the hedonic model for clothes dryers could be fitted with any of these variables. Country of origin represents the country in which the product—in this case clothes dryers—was constructed and is believed to serve as a proxy for the quality of a good and service. In the sample used in this study, over 98 percent of the 341 clothes dryers were constructed in the USA. The remaining clothes dryer models in the sample were made in Canada.

    Finally, about 90 percent of the clothes dryers in the sample are white while about three percent are almond and the remaining seven percent are described as graphite. It was thought that since some outlets charge extra for colors other than white, that color might be a price factor.

    Like the manufacturer warranty variables, both the country of origin and color variables do not seem to have a statistically significant impact on price—see iterative regression 11. Both the country of origin and color characteristics are excluded from the final hedonic model.

    On Clothes Dryer Energy Efficiency

    As the reader may have already noticed, clothes dry energy efficiency does not appear (explicitly) on the CPI checklist nor in the hedonic model for this product. As noted by the Department of Energy:

    The efficiency of a clothes dryer is measured by a term called the energy factor. It is somewhat similar to the miles per gallon for a car, but in this case the measure is pounds of clothing per kilowatt-hour of electricity. The minimum rating for a standard capacity electric dryer is 3.01. For gas dryers the minimum energy factor is 2.67. The rating for gas dryers is provided in kilowatt-hours though the primary source of fuel is natural gas.

    Unlike most other types of appliances, energy consumption does not vary significantly among comparable models of clothes dryers. Clothes dryers are not required to display EnergyGuide labels.25

    Proxy measures for clothes dryer efficiency include clothes dryer type—electric or gas—and clothes dryer drying mechanisms—moisture sensors versus temperature sensors and timed drying.

    Control Variables

    Various control variables are tested representing region of the country, city size, and type of business as defined in the CPI. The most consistently performing and statistically significant control variables that are included in the final clothes dryer model are hardware outlets and warehouse outlets. The purpose of control variables is to minimize the unexplained variation that might remain after the model has been fitted with price determining characteristics.

    Attachment 5, iterative regressions 1 through 12, are included in this study to give the reader a sense of how the hedonic model for clothes dryers progressed as more categories of CPI quality characteristics are considered for model inclusion. Iterative regressions—both included and not included in Attachment 5—are performed until the remaining parameter estimates in the model below exhibited relative robustness to the inclusion and deletion of other variables not included. The direction and magnitude of the parameter estimates seem reasonable, and the statistics pertaining to fit, significance, and collinearity are within generally accepted limits.

    Variable Category

    Variable Name

    Parameter Estimate

    T Statistic

    Tolerance

    Intercept

    5.295815

    46.235

    Type of Price: Sale Price

    -0.103660

    -7.257

    0.8797381

    Dryer Type: Gas

    0.170917

    10.641

    0.7268179

    Electric

    Base

    Drum Capacity

    (in cubic feet)

    Capacity

    0.113937

    6.943

    0.5924369

    Drying Mechanism Moisture sensor

    0.082960

    3.920

    0.3817178

    Temp sensor / Timed dry

    Base

    Number of Temperature Settings Number of temperatures

    0.025726

    6.255

    0.5668198

    Dryer Control Types Electronic controls

    0.181387

    7.544

    0.8441393

    Rotary / Push button controls

    Base

    Brand: High quality

    Base

    Medium quality

    -0.200536

    -10.915

    0.6747474

    Low quality

    -0.305682

    -12.153

    0.6655662

    Type of Outlet: Hardware outlet

    -0.110854

    -3.038

    0.9439328

    Warehouse outlet

    -0.292446

    -3.366

    0.9692976

    R2=0.8481 Adjusted R2=0.8436 F value=184.87 Number of observations=341

    Hedonic Quality Adjustments and Price Index Simulation

    BLS employs the 'matched model' method of quality adjustment in its official indexes. This method controls for quality changes based on the difference in product specifications or characteristics between two items when a substitute observation, or quote, occurs in the price index sample. It is important to note that under the 'matched model' approach only substitution price changes, or quotes, are eligible for hedonic quality adjustments.

    During the study period from October 1999 through June 2000, a total of 20 clothes dryer substitution price changes—an average of just two per month—occurred in the Major Appliances price index sample. For each clothes dryer substitution price quote, differences in the specification or characteristic data of the old and new items were identified to see if the parameter estimates in the hedonic model could be utilized to quality adjust the official price change.

    Fifty percent, or 10, of the 20 clothes dryer substitute price changes in the study are quality adjusted based on specification differences between substitute items. The most common type of quality adjustment performed for clothes dryers in this study is for changes in capacity—represented in 80 percent of the quality adjusted (substitution) prices. Other quality differences such as changes in number of temperature settings and brand specifications are also adjusted for in the hedonic indexes. The table below provides a summary of mean price changes for clothes dryer substitutions in both the official and quality adjusted Major Appliances indexes.

    Summary of mean price changes for Clothes Dryer substitutions

    Type of Substitution Published Index Quality Adjusted Index
    Number Mean Price Change Number Mean Price Change
    All Substitutions 20 +10.41 % 20 +9.29 %
    Comparable 19 +10.75 % 10 +12.59 %
    Quality Adjusted 0 NA 10 +5.98 %
    Non-comparable (Imputed) 1 +3.90 % 0 NA

    Substitution price change can be either "pure" (directly compared or quality adjusted) or "imputed" (non-comparable). The empirical results above reveal that not only was all "imputed" price change replaced with "pure" price change in the quality adjusted index but that almost half of the "comparable" substitution price changes in the published index were made "more comparable or pure" in the quality adjusted index. In addition, the mean price change for all substitutions is lower after quality adjustment than in the published indexes. This result implies that some price increases due to quality change may have been reflected in the published indexes.

    Monthly price indexes are simulated for October 1999 through June 2000 to determine the impact of quality adjusted clothes dryer substitution price changes on the Major Appliances CPI. First the published indexes, or without quality adjustment indexes, are recreated by Statistical Analysis System (SAS) computer programs using historical CPI data. The duplication of the published indexes provides a "control" environment from which the quality adjusted Major Appliances indexes are compared.

    U.S. level price indexes, such as those examined in this study, are obtained by summing elementary, or local area, price indexes using aggregation weights derived from the Consumer Expenditure Survey (CE). The results of the index simulation, with and without hedonic quality adjustments, are presented in Attachment 6. In addition, graphical representations of the simulated price indexes for Major Appliances are presented in Attachments 1 and 7.

    Attachments 1 and 6 indicate that the U.S. CPI for Major Appliances would have remained unchanged instead of the official index decline of 0.1 percent if hedonic quality adjustment methods had been applied to clothes dryer (substitution) price changes from October 1999 through June 2000. Given the small representation that clothes dryer substitution price changes have in the Major Appliances CPI during the study period—an average of just two price quotes per month—the impact at the U.S. level is relatively large.

    Attachments 6 and 7 illustrates the differences between the published and quality adjusted indexes on a monthly basis for the nine-month period in the study—October 1999 through June 2000. Comparisons of the quality adjusted and published Major Appliances price indexes reveal the following: In months when the index increased, the quality adjusted index rose at the same rate for three months (November, March and April). In addition, in the remaining six months when the index fell, there are three months (February, May and June) in which both indexes fell at the same rate; two months (December and January) in which the quality adjusted index fell (slightly) less than the published index; and one month (October) in which the quality adjusted index fell (slightly) more than the published index.

    Two factors may account for the empirical results reported on in this study:

    First, the small number of clothes dryer substitution price quotes that are quality adjusted may have been too few to make a representative impact on the Major Appliances indexes in 1999-2000. Clothes dryer substitution price quotes accounted for less than one percent—on average, two of 218 prices—of the monthly CPI sample for Major Appliances from October 1999 to June 2000 and only half of these dryer substitutions had their price changes adjusted using the hedonic technique.

    Second, CPI data collection procedures direct BLS field economists to select substitution or replacement items that are the "same or similar" in quality as the old item they had been pricing. This procedure tends to yield substitution price quotes that have fewer bona fide characteristic changes (between substitute items) than might have occurred if the procedures had instructed field economists to collect (substitute item) data for the most technologically advanced or best selling clothes dryers.

    This second factor is important in developing expectations as to the direction and magnitude of quality adjusted indexes when compared to indexes without quality adjustments for consumer appliance goods. If BLS field economists are instructed to substitute to the best selling or most technologically advanced clothes dryer products, one might expect that the Major Appliances indexes with and without hedonic quality adjustments would diverge further from each other than in this study.

    BLS is considering additional ways to more quickly bring a greater number of new goods quotes into the CPI rather than just relying on the current Telephone Point of Purchase Survey (TPOPS) rotations. Lane (2000) provides a summary of additional methods for bringing new goods into CPI samples more quickly.26 In particular, both the directed item rotation and directed item replacement methods of updating price index samples instruct field economists to "select a new set of (sample) items representing a more recent period's purchases" for target groups of goods or services that are constantly changing in quality with successive generations of product introductions.

    Conclusion

    The clothes dryer hedonic model developed in this study represents a snapshot of how the average consumer values quality for clothes dryers in today’s appliance market. Iterative regressions for clothes dryers are included in this study to give the reader a sense of hedonic model development as more categories of CPI characteristics were considered for model inclusion. The current rate of quality change for this consumer appliance product is not as fast as other retail products—for example, cellular and wireless telephones or DVD players in the consumer electronics market.

    The parameter estimates in the final hedonic model for clothes dryers exhibit relative robustness to the inclusion and exclusion of other variables not included in the final model. The direction and magnitude of the parameter estimates seem reasonable, and the statistics pertaining to fit, significance and collinearity are within expected limits. It is being used in conjunction with commodity analyst judgment to quality adjust CPI quote level clothes dryer substitution data when possible.

    Notes

    1. Thanks to Charles Fortuna, Mary Kokoski and Rick Devens for helpful comments.
    2. See BLS October 2000 News Release for the Consumer Price Index under "Extending the use of hedonic models to adjust prices for changes in quality" heading on page 4; ftp://ftp.bls.gov/pub/news.release/History/cpi.11162000.news.
    3. See BLS July 2000 News Release for the Consumer Price Index under "Extending the use of hedonic models to adjust prices for changes in quality" heading on page 4; ftp://ftp.bls.gov/pub/news.release/History/cpi.08162000.news. Also, papers describing hedonic quality adjustments in the US CPI for refrigerator/freezers and microwave ovens can be found on the BLS website at http://www.bls.gov/cpirfr.htm and http://www.bls.gov/cpimwo.htm, respectively.
    4. Silver (1998) notes that there are " three different approaches to the use of hedonic regressions for measuring quality-adjusted price changes. The first complements the existing matched models approach generally used by statistical offices, by helping to identify key quality characteristics and, when matches are not available, providing adjustment factors to allow ‘like’ to be compared with ‘like’. The second is the direct method, found in the academic literature, which uses the coefficients on the dummy variables for time in a hedonic regression as estimates of quality-adjusted price changes. The third method requires quite extensive data for the compilation of ‘exact’ hedonic price indices as defined from economic theory."—Page 1 from reference below.
    5. Source, The World Almanac Book of Inventions, distributed in the United States by Ballantine Books (ISBN 0-911818-96-0), a division of Random House, Inc. Copyright 1985, under the Clothes dryer heading on page 167.
    6. Source, "Appliance Histories Milestones in Appliance History: The White Goods Story," Association of Home Appliance Manufacturers (AHAM); December 1998; page 2; http://www.aham.org/cf-dbm/business/businessfirst.cfm (accessed June 2000).
    7. The author would like to thank Jill A. Notini, Communications Manager, of the Association of Home Appliance Manufacturers (AHAM) for background materials on the development of clothes dryers including data on factory shipments (including exports) from 1946 to present. Clothes dryer background materials and data on factory shipments (including exports) from 1946 to present are available from the author upon request.
    8. The information about per unit clothes dryer prices and percent of ownership in US households of clothes dryers are from Exhibits 5 and 8, respectively, in the 1997 Dallas Federal Reserve Annual Report entitled, "Time Well Spent: The Declining Real Cost of Living in America," by W. Michael Cox and Richard Alm found at http://www.dallasfed.org/htm/pubs/pdfs/anreport/arpt97.pdf (accessed June 1998). The conversion to calendar year 2000 dollars was done using the BLS inflation calculator found at http://data.bls.gov/cgi-bin/cpicalc.pl.
    9. See Gordon, The Measurement of Durable Goods Prices; 1989, page 294.
    10. See Consumer Reports August 2000; "Clean Machines: Washers and Dryers," page 36.
    11. For additional information about the hedonics project on quality change in the U.S. CPI see Fixler, Fortuna, Greenlees and Lane (1999), "The Use of Hedonic Regressions to Handle Quality Change: The Experience in the U.S. CPI," Presented at the Fifth Meeting of the International Working Group on Price Indices; August 1999; Pages 1-20. http://www.statice.is/ottawa/bls.rtf (accessed November 1999).
    12. The collection of hedonic price data by CPI field economists coincided with the collection of official CPI price data and TPOPS price data. Reports from the field indicated that some respondents simply did not have the time to assist CPI field economists with hedonic data collection.
    13. See John Greenlees, "Consumer price indexes: methods for quality and variety change," in Statistical Journal of the United Nations ECE 17 (2000), pages 59-74. Reference to hedonics on page 64.
    14. With recent spikes in U.S. natural gas prices in the winter of 2000-2001, the long term operational savings of using a natural gas dryer maybe be diminished or eliminated.
    15. Source: "Making Decisions: Buying a Clothes Dryer," Issued March 1998 by the University of Nebraska in cooperation with the U.S. Department of Agriculture; page 2; http://www.ianr.unl.edu/pubs/housing/nf348.htm (accessed December 1999).
    16. Source: Shepler (2001) in "Development and Application of a Hedonic Regression Model For Washing Machines In the U.S. CPI," in the Data and Regression Model section; at http://www.bls.gov/cpiwas.htm
    17. Source: Shepler (2000) in "Developing a Hedonic Regression Model For Refrigerators in the U.S. CPI," in the Data and Regression Model section on page 3; http://www.bls.gov/cpirfr.htm.
    18. Source: "Tips for Buying a New Clothes Dryer," Department of Energy's Office of Codes and Standards Energy Efficient Appliances; Updated May 24, 2000; http://www.eren.doe.gov/buildings/consumer_information/dryers/drytips.html (accessed June 2000).
    19. Triplett, Jack E., and Richard J. McDonald. 1977. "Assessing the quality error in output measures: The case of refrigerators," Journal of Review of Income and Wealth, No. 23 (June), pages 127-56.
    20. Ibid; page 145.
    21. In addition to the dishwasher study referenced in Greenlees (2000)—see 1) Bascher and Lacroix, "Dishwashers and PCs in the French CPI: hedonic modeling, from design to practice," August 1999; http://www.statice.is/ottawa/lacroix.rtf. See also, 2) Hoffmann, "The Treatment of Quality Changes in the German Consumer Price Index," August 1999; http://www.statice.is/ottawa/hoffmann.rtf. See also, 3) Silver and Heravi, "The Measurement of Quality-Adjusted Price Changes," September 2000; http://www.nber.org/~confer/2000/criwf00/silver.pdf. See also, 4) Shepler, "Developing a Hedonic Model For Refrigerators in the U.S. CPI," August 2000; http://www.bls.gov/cpirfr.htm. See also, 5) Liegey, "Hedonic Quality Adjustment Methods For Microwave Ovens In the U.S. CPI," August 2000; http://www.bls.gov/cpimwo.htm.
    22. Specifically, see http://www.applianceadvisor.com/brandadvisor.htm.
    23. Some information from the ApplianceAdvisor.com website supported the placement of individual brands into either the "medium" quality or "low" quality groups.
    24. Source: "Making Decisions: Buying a Clothes Dryer," Issued March 1998 by the University of Nebraska in cooperation with the U.S. Department of Agriculture; page 2; http://www.ianr.unl.edu/pubs/housing/nf348.htm (accessed December 1999).
    25. Source: "About Clothes Dryer Efficiency," Department of Energy's Office of Codes and Standards Energy Efficient Appliances; Updated May 24, 2000; http://www.eren.doe.gov/buildings/consumer_information/dryers/dryabout.html (accessed June 2000).
    26. See Walter Lane, "Addressing the New Goods Problem in the Consumer Price Index," Presented at the Issues in Measuring Price Change and Consumption Conference, Bureau of Labor Statistics, Washington, D.C., June 5-8, 2000, pages 1-26.

    References

    Consumer Reports

    August 2000 Issue, pages 36-38.

    Silver, M.S. (1998), "An evaluation of the use of hedonic regressions for basic components of consumer price indices," Third Meeting of the International Working Group on Price Indices, Statistics Netherlands, Voorburg: Netherlands (1998) 1-12.

    http://www.statcan.ca/secure/english/ottawagroup/pdf/23SIL3.pdf(accessed November 1999).

    Lane, Walter (2000), "Addressing the New Goods Problem in the Consumer Price Index," Presented at the Issues in Measuring Price Change and Consumption Conference, Bureau of Labor Statistics, Washington, D.C., June 5-8, 2000, pages 1-26.

    Attachment 1

    Index levels for HK01 with and without hedonic QAs for clothes dryers (ELI HK012-cluster 02A)

    Attachment 2

    Number and Distribution of CPI Price Changes for Major Appliances (HK01) and

    Clothes Dryers (HK012 - 02A)

    Major Appliances (HK01)
    Month Total Prices Collected Substitutions

    # / (% of Total Prices)

    Comparable

    # / (% of Subs)

    Non-comparable

    # / (% of Subs)

    October 1999 233 33 / (14) 30 / (91) 03 / (09)
    November 1999 208 16 / (08) 11 / (69) 05 / (31)
    December 1999 209 15 / (11) 09 / (60) 06 / (40)
    January 2000 213 22 / (10) 17 / (77) 05 / (33)
    February 2000 208 08 / (04) 07 / (88) 01 / (12)
    March 2000 210 19 / (09) 14 / (74) 05 / (26)
    April 2000 209 20 / (10) 19 / (95) 01 / (05)
    May 2000 231 18 / (08) 07 / (39) 11 / (61)
    June 2000 245 16 / (07) 15 / (94) 01 / (06)
    Average 218 19 / (09) 15 / (79) 04 / (21)

    Clothes Dryers

    (HK012 - 02A)

    Month Total Prices Collected Substitutions

    # / (% of Total Prices)

    Comparable

    # / (% of Subs)

    Non-comparable

    # / (% of Subs)

    October 1999 20 03 / (15) 03 / (100) 0
    November 1999 29 01 / (03) 01 / (100) 0
    December 1999 33 03 / (09) 02 / ( 67) 01 / (33)
    January 2000 32 06 / (19) 06 / (100) 0
    February 2000 34 0 0 0
    March 2000 30 02 / (07) 02 / (100) 0
    April 2000 36 02 / (06) 02 / (100) 0
    May 2000 33 01 / (03) 01 / (100) 0
    June 2000 43 02 / (05) 02 / (100) 0
    Average 32 2.2 / (07) 2.1 / (95) 0.1 (05)

    Attachment 3

    U.S. Factory Shipments of Clothes Dryers

    Data Source: Association of Home Appliance Manufacturers

    Attachment 4

    Brief Chronology of Clothes Dryer Improvements

    
                                              
     BUREAU OF LABOR STATISTICS             U.S. DEPARTMENT OF LABOR
       CONSUMER PRICE INDEX - ELI CHECKLIST                                                     
     collection             outlet                       quote           arranging
     period: __ __ __ __    number: __ __ __ __ __ __ __ code: __ __ __  code:    __ __ __ __
     _________________________________________________________________________________________
     ELI No./                                                                     cluster
     title        HK012 WASHERS AND DRYERS                                         code   02A
     item availability:    1-AVAILABLE    2-ELI NOT SOLD     3-INIT INCOMPLETE
     purpose of checklist: 1-INIT   2-INIT COMPL  3-SPEC CORR   4-SUB   5-REINIT   6-CHECK REV
     _________________________________________________________________________________________
               CURRENT PERIOD                    |      SALES TAX
                                                 |
               price _ _ _ _ _ _ . _ _ _         |      included:        YES    NO
                                                 |
               type of price:  REG   SALE        |
                                                 |
                                                 |
                                                 |
                                                 |
                                                 |
                                                   |                                            
                 |
     YEAR-ROUND  |  in-season:  JAN  FEB  MAR  APR  MAY  JUN  JUL  AUG  SEP  OCT  NOV  DEC
     ____________|____________________________________________________________________________
     respondent:                                   location:
     _________________________________________________________________________________________
     field message:
     _________________________________________________________________________________________
      CLUSTER 02A - DRYERS
      TYPE                                        CAPACITY CUBIC FEET
        A1  Electric                             (Super-capacity and models)
        A2  Gas                                     D1  7.4 cubic feet or greater
                                                    D2  7.0 to 7.3 cubic feet
     BRAND                                       (Extra large and large-capacity models)
        B1  Admiral                                 D3  6.6 to 6.9 cubic feet
        B2  Amana                                   D4  6.2 to 6.5 cubic feet
        B3  Crosley                                 D5  5.8 to 6.1 cubic feet
        B4  Fridgidaire                             D6  5.4 to 5.7 cubic feet
        B5  General Electric (GE)                   D7  5.0 to 5.3 cubic feet
        B6  Gibson                               (Compact-capacity models)
        B7  Hot Point                               D8  4.6 to 4.9 cubic feet
        B8  Jenn-Air                                D9  4.2 to 4.5 cubic feet
        B9  Kelvinator                             D10  3.8 to 4.1 cubic feet
       B10  Kenmore                                D11  3.7 cubic feet or less
       B11  Kitchenaid
       B12  Magic Chef                            ** SPECIFIC CAPACITY IN CUBIC FEET
       B13  Maytag
       B14  RCA                                    E99  ______________________________
       B15  Roper
       B16  Whirlpool
       B17  White-Westinghouse
       B99  Other brand,
     
            ______________________________
     
     ** MANUFACTURER'S MODEL NUMBER
     
       C99  ______________________________
     
       
     
     ZZ99
     _________________________________________________________________________________________
                                              
                                                                           
      
    
    HK012-02A - DRYERS - CONTINUED
    CYCLES(Must agree with next DOOR STYLE specification category) AE1 Front-pull (opens down) F1 Regular AE2 Side-pull (opens left or right) G1 Permanent press H1 Gentle/knits/delicates FEATURES I1 Air fluff/no heat AF1 Drying rack J1 Damp dry AG1 Drum/interior light K1 Easy/extra care AH1 Easy access lint filter on dryer top L1 Wrinkle free/wrinkle release AI1 Lint filter indicator M1 Press care/wrinkle prevent AJ1 Leveling legs N99 Other dry cycle, AK1 Sound dampening package AL1 End of cycle signal ______________________________ AM1 Stackable unit P99 Other dry cycle, AN99 Other features, ______________________________ ______________________________ Q99 Other dry cycle, AP1 None ______________________________ MANUFACTURER WARRANTY AQ1 One year parts and labor NUMBER OF DRY CYCLES(Must agree with AQ99 Other warranty, previous specification category) R99 Specific number of dry cycles, ______________________________ ______________________________ COUNTRY OF ORIGIN AR1 United States DRYING MECHANISMS AR99 Other country of origin, S1 Automatic moisture sensor (electronic sensor) ______________________________ T1 Automatic temperature sensor U1 Timed drying DELIVERY V99 Other, AS1 Delivery available, no extra charge AS2 No delivery available ______________________________ AS79 Delivery available for extra charge, NUMBER OF TEMPERATURE SETTINGS __________________// $________ W1 Two settings W2 Three settings COLOR W3 Four settings AT1 White W4 Five settings AT2 Almond W5 Six settings AT99 Other color, W6 Seven settings W7 Variable or infinite settings ______________________________ W99 Other number of temperature AU1 No extra charge for color settings, collected in AT spec AU79 Extra charge for color, ______________________________ __________________// $________ CONTROL TYPES X1 Touch pad or electronic controls Y1 Rotary controls AA1 Push button controls AB99 Other control types, ______________________________ NUMBER OF MOTOR SPEEDS AC1 One speed AC2 Two speeds AC3 Three speeds AC99 Other number of motor speeds ______________________________ DRYING DRUM MATERIAL AD1 Porcelain enamel drum AD2 Stainless steel drum AD99 Other drum material, ______________________________
    HK012-02A - DRYERS - CONTINUED
    OTHER PRICE FACTORS AV99 ______________________________ AW99 ______________________________ AX99 ______________________________ SERIES OR LINE NAME (IF APPLICABLE) AY99 ______________________________ **OTHER CLARIFYING INFORMATION BA99 ______________________________ BB99 ______________________________ BC99 ______________________________ PRICE CALCULATION BOX BD79 Dryer base price, ______________________________// $__________ BE89 TOTAL PRICE (AS79 + AU79 + BD79), ____________________________// $__________

    Last Modified Date: April 22, 2003

    Recommend this page using: