Comments on “Land Prices and Fundamentals”
by Koji Nakamura and Yumi Saita
Masahiko Shibamoto
Research Institute for Economics and Business Administration
Kobe UniversityDecember 1, 2007

The 9th Macroeconomics Conference

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This paper ...
• exmamines long-run relationship between macro economic fundamentals
and the weighted-average land price indicators, which are supposed to beappropriate indicators in the context of the macro economic analysis.
• cointegration between the land price and DPV.
⇒ explosive ‘bubble’ doesn not exist, although the actual land prices can be
deviate the theoretical land prices.
• error-correction analysis:
convergence of actual land prices to the long-term equilibrium level1

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Keio UniversityMy comments:
1. Fundamentals‘myopic expectations of the future income’⇒ (defensible speciﬁcation?) Economic fundamentals ﬂuctuate dramatically!!
2. Empirical Approach
3. Are weighted-average land price indicators really appropriate in the context ofthe macro economic analysis?

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Comment 1: Fundamentals• Discouted Presented Value (DPV) of Land Price
Yt + EtPt+1, and rt = it + τt + RPt
1 + rtYt⇒ Pt =(6)eit − gt + τt + RPt
Pt =• Authors use the estimation speciﬁcations in line with the theory of land pricedetermination. However, I think that the theoretical values obtained by authors
has some problems, although authors point out in p. 40.

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Keio University• gte: constant growth rate (static expectation for future income growth)
growth rate of the quarterly nominal GDP ﬁltered by HP ﬁlter (λ = 100instead of λ = 1600)⇐ Is people’s expectation really myopic?
Can you use HP ﬁlter as the proxie? Are there some persuasive reasons and/orprevious studies?
smoothing parameter λ = 100 ?
• cf. Campbell and Siller (1987, JPE) estimate DPV based on the VAR model.
• Risk Premium: RPt = RP = 6% ⇐ Constant !!
bubble: low
before and after bubble: high4

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30

20100-10-2060

6570758085909500

GROWTH_ANNUAL
HPTREND_100
HPTREND_1600

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Keio Universitygte㪍㪌㪋㪊㪉㪈㪇㪄㪉㪟㪧㪶㫋㫉㪼㫅㪻㪈㪇㪇㪟㫇㪶㫋㫉㪼㫅㪻㪈㪍㪇㪇㪈㩷㫐㪼㪸㫉㩷㪸㪿㪼㪸㪻㪊㩷㫐㪼㪸㫉㫊㩷㪸㪿㪼㪸㪻㪌㩷㫐㪼㪸㫉㫊㩷㪸㪿㪼㪸㪻

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Comment 2: Empirical Approach• Speciﬁcation of the Cointegration Regression 3,4 (p.26)
pt = β0 + β1T rendt + β2 N P Vt + et(15)Economic interpretation that you relax the restriction on the coeﬃcient of theDPV of land of one ?
β2 = 1 imply Equation (6).
β2 > 1, β2 < 1 ???
• Should test whether or not the coeﬃcient of the DPV is one (instead of 0).
(In fact, its coeﬃcient is signiﬁcantly deﬀerent from one in many case.)
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Keio University• Can the trend term represent the structural decline in demand for lands dueto the changes in the economic structure?
deterministic? I think that this is represented by the stochastic.
• Estimation of Cointegrating Vectors
p.30 “DOLS is the ordinary least squares method with leads and lags of thedependent variables” or 日本語バージョン p.29「説明変数の階差のラグ項を加えた」???
⇒ the OLS method with leads and lags of the ﬁrst diﬀerence of theregressors!!

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The 9th Macroeconomics ConferenceKeio University• Estimation of Error-Correction Models
Δpt = β0 + β1ECt−1 + β2ΔN P Vt + β3Δpopt + β4 Δct + t
I recomend IV estimation, instead of OLS (because ΔN P Vt etc is notexogenous), or OLS estimation including some lags of Δpopt, ΔN P Vt andΔct instead of ΔN P Vt, Δpopt, and Δct.

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Comment 3: Are the weighted-average land price really appropriate?
(Figure 1) Long-Term Trends of Land Price Indicators5350

㧔1980=100㧕
SNA Land Value
Weighted-Average Land Price Index
Published Land Prices(Official Publication)
Urban Land Price Index

300
250
200
150
100
500
1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005
year

Sources: Cabinet Office, “National Accounts”; Ministry of Land, Infrastructure and Transportation,“Published Land Prices,”; Japan Real Estate Institute, “Urban Land Price Index.”

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Keio University• “If we used the oﬃcial land price indicators, we would underestimate theimpact of the land price ﬂuctuations for high land price areas · · · ”⇐ I think that, if we used the weighted-average land price indicators, we wouldunderestimate the impact of the land price ﬂuctuations for low land price areas,
and overestimate the impact of the land price ﬂuctuations for high land priceareas. I think that this is arbitrary.
Is it a problem so much that the weights of the oﬃcial land price indicators
are in line with the population weights?

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