Quality-Adjusting Computer Prices in the Producer Price Index: An Overview
|
Coefficient |
Standard error |
T-statistic |
P-value |
|
Constant |
619.925 |
81.685 |
7.589 |
0.000 |
CPU per MHz |
3.533 |
0.079 |
44.9270 |
0.000 |
Celeron CPU* |
-277.538 |
11.558 |
-24.013 |
0.000 |
SDRAM/MB |
1.686 |
0.079 |
21.232 |
0.000 |
HD/MB |
0.020 |
0.001 |
19.221 |
0.000 |
100MB ZIP* |
96.702 |
11.430 |
8.460 |
0.000 |
DVD (4.6/6.0)* |
95.459 |
16.039 |
5.952 |
0.000 |
Video/MB |
5.076 |
0.948 |
5.357 |
0.000 |
Sound card and 2 Speakers* |
24.184 |
14.070 |
1.719 |
0.086 |
Speakers and Sub* |
77.246 |
12.238 |
6.312 |
0.000 |
Speakers and Premium Sub* |
172.473 |
14.842 |
11.621 |
0.000 |
56.6 fax modem* |
27.919 |
9.364 |
2.982 |
0.003 |
10/100Mbs NIC* |
49.287 |
11.165 |
4.414 |
0.000 |
Monitor, 15 inch* |
246.919 |
21.733 |
11.362 |
0.000 |
Monitor, 17 inch* |
296.941 |
15.763 |
18.838 |
0.000 |
Monitor, 17" Trinitron* |
370.599 |
16.135 |
22.969 |
0.000 |
Software Office Suite* |
62.568 |
18.614 |
3.361 |
0.001 |
MS Office Suite SBE* |
228.880 |
14.088 |
16.246 |
0.000 |
MS WIN NT OS* |
111.235 |
10.911 |
10.195 |
0.000 |
Business Market |
268.988 |
21.689 |
12.402 |
0.000 |
3-year On-Site Warranty* |
155.622 |
16.225 |
9.591 |
0.000 |
Company A* |
257.225 |
13.549 |
18.984 |
0.000 |
Company B* |
139.632 |
21.100 |
6.618 |
0.000 |
Company C* |
-121.727 |
18.676 |
-6.518 |
0.000 |
* Dummy variable |
Observations = 685
Dependent variable: Price
Standard Error = 85.2
Adjusted R-Square = 0.963
F = 773.6
The regression results in table 1 are from June 1999 and include 685 observations of desktop computers obtained from producer websites on the Internet.7 These Internet sites have evolved over time to include online processing of direct sales from the producer to the end user. Typically, a buyer can view technical specifications and prices for a range of pre-configured computers and then complete the purchase online or through a toll-free telephone number. However, most computer producers offer buyers greater flexibility by providing a broad customization of features that can be added to, or deleted from, the pre-configured models. For instance, a pre-configured model that includes a 500MHz CPU is also available with a faster or slower CPU, more memory, or a monitor upgrade. A buyer can chose options most appropriate for their application and budget, and the producer will instantly recalculate a price based on the buyer's selection of those computer characteristics. A variety of producer websites representative of the PPI sample will typically be used to build a data base.
The number of sites used in PPI models will vary, according to the type of product. Desktop computer models will generally include five or more sites and require an average of 2 weeks of data review and entry for the industry analyst to build a completely specified model of 600 or more observations. Then, another 2 weeks are used to explore data relationships, run various regressions, and analyze the results. Proper analysis is approached from both a statistical and industry knowledge perspective. Because of the extensive resource requirements that are used to build models that are representative of the current composition of the PPI, the Bureau is only able to update the desktop computer database on a quarterly basis. Each database is structured to ensure that the most important PPI computer producers are included. (The majority of the top 10 domestic producers are represented in the PPI.) Several dummy variables are used in the model. For example, the Celeron CPU coefficient8 in table 1 is relative to the presence of a Pentium II CPU. Company-effect dummy variables are also used, in this case referred to as Company A through C, to avoid the possibility of disclosing companies that are in the database but also report prices directly to the PPI. Only companies that tested as statistically significant are included as dummies. The interpretation of a company-effect variable is that it may capture otherwise unspecified price determining factors, such as name recognition, buyer loyalty, and warranty policy; factors that provide a limited company-specific price differentiation that go beyond the explanatory powers of the explicitly defined characteristics. To illustrate how regression results are used in the PPI to obtain the quality-adjusted price relatives that make up the desktop computer index, a hypothetical example is described below.
Computer Reported to PPI, Period (t-1) |
Computer Reported to PPI, Period (t) |
|
Desktop personal computer |
Desktop personal computer |
|
Model 100 |
Model 100 |
|
Pentium II 400MHz with 512K L2 cache |
Pentium II 400MHz with 512K L2 cache |
|
32MB SDRAM system memory |
64MB SDRAM system memory |
|
4.5GB EIDE hard drive |
4.5GB EIDE hard drive |
|
4MB SGRAM video |
4MB SGRAM video |
|
20X CD-ROM |
20X CD-ROM |
|
16-bit sound card |
16-bit sound card |
|
56.6 fax-modem |
56.6 fax-modem |
|
15-inch monitor (0.26 dot pitch) |
15-inch monitor (0.26 dot pitch) |
|
Windows 95 and MS Office SBE |
Windows 95 and MS Office SBE |
|
|
|
|
Reported net price in period (t-1) = $1,500 |
Reported net price in period (t) = $1,500 |
Estimated Value of Improvement from Period (t-1) to Period (t)
System memory increase from 32MB to 64MB
32MB additional SDRAM * $1.686 (unit value from table 1) = $53.95
Quality adjusted (QA) price change = (P(t) - QA) / P(t-1)
= (1,500 - 53.95) / 1,500
= -3.6 percent
This example is based on the assumption that the PPI is repricing a computer configured with 32 megabytes of SDRAM that sold in period (t-1) for $1,500 that the producer upgrades to 64 megabytes of SDRAM in period (t). The reporter indicates that the current period price for the upgraded model is still $1,500, and that the producer cannot provide a value for the change in production cost that is directly attributable to the additional 32 megabytes of SDRAM. If the PPI did not have a hedonic model, prices would be directly compared and, in effect, would show no price change for this product despite the quality improvement. With the implicit unit memory price generated by the hedonic model, the PPI has a method for valuing this change. The implicit price of $1.686 per unit of SDRAM is obtained from the SDRAM variable in table 1 and multiplied by the 32 unit (megabyte) increase in period (t), to yield a total quality change valuation of $53.95. The hedonic model is simply a tool that estimates the average change in price for the 685 observations (minus df) for a unit change in a continuous variable or the absence or presence of a dummy variable. The remaining quality adjustment calculation is straightforward, as shown in the example. Of course, if more than one quality change had occurred; and the relevant characteristics were specified in the model, we could sum the implicit prices for these changes and calculate a multi-factor quality adjusted price relative from the nominal prices reported to the PPI.
The PPI continues to use Internet-based data sources to update computer models, because of the improved accuracy of technical descriptions and pricing data. However, the PPI maintains its traditional index construction methods that are based on directly reported producer prices for specified products sold under specified terms. The PPI does not attempt to use hedonic models for any purpose other than to obtain valuations (implicit prices) for changes in specific computer technical characteristics reported to the PPI.
Michael Holdway is an economist with the Office of Prices and Living Conditions at the Bureau of Labor Statistics.
References
Berndt, E. R., and Griliches, Z. (1990), "Price Indexes for Microcomputers: An Exploratory Study," Working Paper 3378, National Bureau of Economic Research, Cambridge, MA.
Berndt, E. R., Griliches, Z., and Rappaport, N. R., "Econometric Estimates of Price Indexes for Personal Computers in the 1990's," Journal of Econometrics, 68, 1995, pp. 243-268.
Chow, G. C. (1967), "Technological Change and the Demand for Computers," American Economic Review, 57, 1117-1130.
Diewert, W. E. (1980), "Aggregation Problems in the Measurement of Capital," ed. D. Usher, Chicago: The University of Chicago Press, pp. 433-528.
Gordon, R. J. (1989), "The Postwar Evolution of Computer Prices", in Technology and Capital Formation, editors D. W. Jorgenson and R. Landau, Cambridge, MA; MIT Press, pp. 77-125.
Nelson, R. A., Patterson, C. D., and Tanguay, T. L., "A Quality-Adjusted Price Index for Personal Computers," Journal of Business and Economic Statistics, January 1994, pp. 23-31.
Triplett, J. E. (1989), "Price and Technological Change in a Capital Good: A Survey of Research on Computers," in Technology and Capital Formation, editors D. W. Jorgenson and R. Landau, Cambridge, MA; MIT Press, pp. 127-213.
Triplett, J. E. (1986), "Economic Interpretation of Hedonic Models," Survey of Current Business, January 86, pp. 36-40.
Notes
1 On an experimental basis, computer price indexes were calculated by the PPI from 1987 to 1990. The PPI introduced computer price indexes on an operational basis, effective December 1990. See James Sinclair and Brian Catron, "An experimental price index for the computer industry," Monthly Labor Review, October 1990, pp. 16-24.
2 Biased index movement in the PPI can directly introduce bias into other measures of economic performance, such as gross domestic product (GDP) and productivity.
3 Consumers commonly focus on CPU clock speed when judging a computer's performance potential, quoted in megahertz (MHz). This single number is more confusing than enlightening in today's environment of multiple competitive processors; one processor running at a particular MHz can significantly outperform another processor rated at the same MHz, and processors based on different architectures are difficult to compare, without objective benchmarking. Relative to 1993, current-generation CPUs have larger caches, much deeper pipelines, branch prediction, out-of-order execution, and several other architectural enhancements that allow more instructions to be executed per clock cycle.
4 As defined by the Standard Industrial Classification System (SIC) that in turn, is based on research provided by the multi-agency Technical Committee on Industrial Classification (TCIC) chaired by the Office of Management and Budget (OMB).
5 Berndt, Griliches, Rappaport, in Econometric Estimates of Price Indexes for Personal Computers in the 1990's, referred to the matched model problem in their database. They describe an index based on the matched model premise as including only " those models which survive unchanged year-to-year, any incremental improvements in a particular model (e.g., a faster processor) disqualify it from the index." They also discovered that a matched model index for computers is impractical. Their database included computer observations from 1989 to 1992. Only 8 percent of the 1989 models survived in 1990, using the matched model restriction. The situation worsened in 1992, when only 3 percent of the 1991 models were intact. Personal desktop computers in the PPI experience about a 3-month average life expectancy, based on the matched model definition.
6 The PPI has also developed models that are used to quality-adjust the rapidly growing disk storage array product category (PPI code 3572-1145).
7 Computer resellers (retail or wholesale) that market computers through online stores are excluded from our databases. This type of transaction is out-of-scope for the PPI's coverage of SIC 3571.
8 Which is why the coefficient for the Celeron dummy variable has the correct negative sign. (See table 1.)
Last Modified Date: October 16, 2001
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