Kuznets’ swings and intangible investments in forecast: the case of Greece

Tubadji, Annie; Angelis, Vassilis; Nijkamp, Peter

doi:10.1080/13504851.2015.1049332

Cited by 1 publication

(1 citation statement)

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“…The other generally accepted theory for economic cycles involves Kuznets swings (K-swings). Each K-swing lasts for about 20 years and is facilitated by demographic changes, spatial mobility and infrastructural investments (Tubadjia et al, 2016). Yet another type of economic cycle, the Juglar cycle, is a fixed business cycle of investment in equipment and technological structures with a length of six years.…”

Section: Literature Reviewmentioning

confidence: 99%

International Real Estate Review

Hu¹,

Tiwari²

2021

IRER

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This paper identifies the impact of macroeconomic determinants of commercial property investment and development markets in Australia. A Hodrick-Prescott (HP) filter is used to filter the cyclical components of commercial property investment and development time series. In order to identify the long-run relationships and short-run dynamics, coupled with causality between these factors and property cycles, the investment and development property cycles are analyed with respect to the movement of nine macroeconomic factors by using time series data from 1987 to 2016. The empirical results suggest that the Australian commercial property market is often in an overdemand situation rather than oversupply, which can be explained by the different patterns of the property cycles on the demand and supply sides. Property investment cycles are shorter and more volatile than development cycles at around 8-10 years and more than 20 years, respectively, since there is a larger elasticity of the macroeconomic factors that underlie the investment market with short-term dynamics, while the development cycle is mainly affected by such factors moderately in the long run. Both the investment and development markets are intensively affected by financing related variables rather than market-sentiment and economic-cycle related variables.

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Section: Literature Reviewmentioning

confidence: 99%