Estimation of the Rental Adjustment Process

Hendershott, Patric H.; Macgregor, Bryan D.; Tse, Raymond Y. C.

doi:10.1111/1540-6229.00036

Cited by 89 publications

(91 citation statements)

References 20 publications

(27 reference statements)

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“…7 are less frequent in empirical research for European real estate due to limited attention from local professionals for gathering supply side data. Hendershott et al (2002a) include a supply side variable in their model of the London office market but find insignificant results for changes in office supply. Similar results were found in the Hendershott et al (2002b) paper for a panel of regions in the UK excluding London.…”

Section: Modelling Office Rentsmentioning

confidence: 98%

“…Widely used demand side variables are changes in GDP, service sector employment, lagged short-term interest rates and unemployment rates. One of the earliest works in this respect is Giussani et al (1992) Hendershott et al (2002a, b) elegantly combine the two continental strands of office literature in an ECM. In this paper we apply this methodology for a panel of international cities of different importance to the national economy and apply both national and local economic activity variables.…”

Section: Modelling Office Rentsmentioning

confidence: 99%

See 1 more Smart Citation

Local Office Rent Dynamics

Brounen

Jennen

2008

J Real Estate Finan Econ

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This study applies rent adjustment models for ten major European office markets. We capture long-run equilibrium relationships of demand and supply variables and their short-term corrections in a two equation error correction model. We test whether the local nature of office markets makes a model based on national economics inaccurate if local and national markets do not move in tandem. For this we employ a unique dataset, which includes both disaggregated and national variables to model changes in real prime rents for a group of premier and second tier office market cities across Europe for the period 1990-2006. We explicitly compare results that are derived from models that include different levels of geographic aggregation. Results of the two stage error correction model indicate that international office rents adjust to short-run changes in office related economic activity, lagged rent changes, and to the deviation of rents from their long-run values. At the same time our results offer no proof that error correction mechanism models for office rents improve significantly by specifying economic growth figures beyond the national aggregated level for the cities included in our analysis.

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Section: Modelling Office Rentsmentioning

confidence: 98%

Section: Modelling Office Rentsmentioning

confidence: 99%

Local Office Rent Dynamics

Brounen

Jennen

2008

J Real Estate Finan Econ

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“…Empirical evidence about the demand elasticity is scant and, partly due to the variety of existing house price measures, varies considerably across housing markets (Hanushek and Quigley 1980, Mayo 1981, Hendershott et al 2002, Riddel 2004. Overall, demand elasticities seem to be well below one, and thus ) .8 0 , 2 .…”

Section: Parameter Calibrationmentioning

confidence: 99%

Heterogeneous Expectations, Boom-Bust Housing Cycles, and Supply Conditions: A Nonlinear Dynamics Approach

Dieci

Westerhoff

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe combine a standard stock-flow housing market model, incorporating explicit relationships between house prices, the housing stock, and the rent level, with a parsimonious expectation formation scheme of housing market investors, reflecting an evolving mix of extrapolative and regressive expectation rules. The model results in a two-dimensional discrete-time nonlinear dynamical system. Based on realistic parameters, the model is able to generate endogenous boom-bust housing market dynamics with lasting periods of overvaluation and overbuilding. We thus exploit our model to investigate how real forces, in particular supply conditions, interact with expectations-driven housing market fluctuations.

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“…These are theoretically not unrelated to the concept of error correction applied in a reduced form modelling framework which is discussed more fully below. Hendershott et al (2002a) examine the rental adjustment process in London and Sydney office markets. They apply equations similar to (5) above and test for stationarity and cointegration.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A value smaller than -1 implies over-adjustment. Hendershott et al (2002a) report results (for London offices) for a range on models based upon (8) and (10) above. In general results accord with a priori expectations.…”

Section: Literature Reviewmentioning

confidence: 99%

An econometric analysis of Shanghai office rents

White

2009

Journal of Property Investment &Amp; Finance

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PurposeShanghai is the most important economic centre in China. It also has the nation's largest modern office market in terms of floorspace and investment values. However, as with office markets in other cities and countries, the Shanghai market displays rental volatility. This paper aims to examine this issue.Design/methodology/approachRental volatility is examined by econometrically constructing a long‐run equilibrium relationship between rent and underlying demand and supply side factors. In order to establish the validity of this model, it is tested for the presence of a cointegrating vector. From this a short‐run dynamic adjustment model is constructed. This is an error correction mechanism that links the short‐ and long‐run models. The impact of office vacancies, foreign direct investment, and changes in the real interest rate on the office market are explicitly considered.FindingsThe results indicate that both demand (as represented by gross domestic product (GDP)) and supply (stock) are significant determinants of rents. Space demand is found to be both price and income elastic. In the short‐run model the error correction term is significant and correctly signed. In comparison to other office markets, the Shanghai market adjusts rather slowly. Foreign direct investment is found to have a positive impact on long‐run rents and the vacancy rate is found to impact on short‐term rental adjustment.Originality/valueThe Shanghai office market is the most important in China. However, it has displayed significant rental volatility. This paper is the first to examine explicitly the rental adjustment process in this office market. The results suggest a market that is performing as expected by economic theory but which nevertheless displays relatively slow adjustment to market imbalances.

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Estimation of the Rental Adjustment Process

Abstract: We thank seminar participants at the Universities of Southern California and Wisconsin for their helpful comments.

Cited by 89 publications

References 20 publications

Local Office Rent Dynamics

Local Office Rent Dynamics

Heterogeneous Expectations, Boom-Bust Housing Cycles, and Supply Conditions: A Nonlinear Dynamics Approach

An econometric analysis of Shanghai office rents

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