Erwin Diewert

Residential Property Price Indexes for Tokyo

The paper uses hedonic regression techniques in order to decompose the price of a house into land and structure components using real estate sales data for Tokyo. In order to get sensible results, a nonlinear regression model using data that covered multiple time periods was used. Collinearity between the amount of land and structure in each residential property leads to inaccurate estimates for the land and structure value of a property. This collinearity problem was solved by using exogenous information on the rate of growth of construction costs in Tokyo in order to get useful constant quality subindexes for the price of land and structures separately.

Estimation of R&D Depreciation Rates: A Suggested Methodology and Preliminary Application

The 2008 version of the SNA will recommend capitalization of R&D expenditures. To implement this recommendation, measures for the stock of R&D capital must be constructed, and this implies a need to determine the depreciation rate of R&D capital. In this paper, we develop a simple model, based on a production function method that allows for monopolistic competition, to estimate the annual depreciation rate of R&D capital. We treat R&D capital as a technology shifter instead of as an explicit input factor. Both the R&D stock and the time variable are used to capture technological progress. Modeling R&D capital in this manner can better represent the role R&D plays in economic growth. Estimated R&D depreciation rates and markup factors are presented for the U.S. manufacturing sector and four U.S. knowledge intensive industries, namely chemical products (SIC 28), non-electrical machinery (SIC 35), electrical products (SIC 36) and transportation equipment (SIC 37).

Notes on Unit Value Index Bias

Summary It is often the case that the value of a number of somewhat similar units (e. g., automobiles of a certain general type) is divided by the number of units in order to form a unit value price and these unit value prices are compared over two periods in order to form a unit value price index. This unit value price index or Drobisch price index can then be compared with other standard index number formulae and the bias in the index can be determined. The present paper presents most of the known results on this bias (and derives some new ones) in a coherent framework using a simple identity from the statistics literature. A related question first considered by Párniczky (1974) is also considered: does disaggregation of a unit value into more homogeneous subgroups reduce the unit value bias? The answer seems to be: probably yes.