View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Research Papers in Economics A Frequency Domain Analysis of Common Cycles in Property and Related Sectors Author Peijie Wang Abstract This study examines cycles and common cycles in property and related sectors in the frequency domain. The findings indicate that property shares common cycles with a number of economic sectors and, in particular, with those sectors that are the user markets of property, and lags behind in business cycle phases. Property has large coherence at most frequencies with most economic sectors, but seems to have large discrepancy with them in the cycles at the annual frequency. The property market swings more severely than the economy as a whole. However, fluctuations in the property market are considered moderate relative to those in the housing market. Introduction This study examines cycles and common cycles in the property market and the economy using an econometric approach in the frequency domain. The common cycle is one type of common factors that have attracted much attention in contemporary econometric modeling. The other common factors include, prominently, the common trend and cointegration, which focus on the long-run comovement between two or more time series. While there have been several studies of common factor analysis involving property and other economic and financial variables, they exclusively adopt the cointegration procedure, and are predominantly on the cointegration relationship between direct property investment and indirect property investment. The latter is usually represented by Real Estate Investment Trusts (REITs) in the United States and property company shares in the United Kingdom. Examples of such research can be found in Lizieri and Satchell (1997) and Wang, Lizieri and Matysiak (1997), among others. Currently, none have studied common cycles in property and other sectors in the economy in a modern business cycle framework, incorporating contemporary econometric modeling strategies. Lack of empirical research on common cycles of property and other sectors in the economy arises from the fact that it is hard to quantify or even qualitatively confirm the characteristics of the interaction using the traditional time domain method, which has motivated this study adopting a non-conventional approach in JRER ͉ Vol. 25 ͉ No. 3 – 2003 326 ͉ Wang the frequency domain to discover common cycle features and patterns of interaction between property and economic sectors. The existing literature has highlighted the state of present research that recognizes a close link between property and the economy but is yet to go further to identify the patterns of association between them. Examining the price-income relationship, Bjorklund and Soderberg (1999) suggest that Swedish property market cycles may have been partly driven by a speculative bubble during the 1980s. The results of Wang (2000), derived from the analysis of capital value and rent relationships, suggest that there are no bubbles in the office, retail and aggregate property cycles in the U.K., but the existence of bubbles in the industrial property market cannot be ruled out. Pyhrr, Roulac and Born (1999) review extensively the literature and research relevant to property cycles. In their discussion of macroeconomic relevance of cycles, they summarize and make comments on research on cycles in the national economy, national economy linked to real property and macro property cycles. The study presents fundamental cycle concept and recognizes the relevance of phases in property supply and demand cycles, but stops short of establishing a link with the national economy and providing empirical results. The demand cycle leads the supply cycle, and the occupancy rate is found to be the best indicator of the phase of the cycle. Dokko, Edelstein, Lacayo and Lee (1999) develop a property cycle model linking property value and net operating income. Although there are no economic fundamentals, other than value and income, involved in their statistical equations, the relationship between value and income is the kind for the fundamentals. They claim that twenty office markets, that exhibit different cyclical behavior, may be represented by their three-parameter econometric specification, with the three parameters being for the value variable, the change in value and a time trend. Varied approaches are adopted in the investigation of property cycle behavior, e.g., Wheaton (1999) applies a theoretical stock-flow model incorporating agents’ expectations to demonstrate various cyclical features, and Grenadier (1995) examines the prolonged cycles, or persistence, in property markets. The study by Grissom and DeLisle (1999) is truly linked to the national economy and the financial market, using standard time domain regression with relevant augmentation. Included in the macro-financial market analysis are variables of GNP, the interest rate, unanticipated inflation, tax shelter and capital gains, all of them being contemporary, neither leading nor lagging property returns. Dividing the entire time period into several time segmentations, the role of these variables in explaining property returns vary. Further analysis of the results indicates that these variables and the relationships help distinguish property cycle stages and the relationships are stable in identifying cyclical changes. The most significant variables over the entire period to have an influence on property returns have been identified as changes in GNP and the interest rate, which reflects anticipated inflation. The sign of the coefficient for GNP is, reasonably, always positive. While the sign of the coefficient for the interest rate alters during different time segmentations, it is always the same as the coefficient for unanticipated inflation. Common Cycles in Property and Related Sectors ͉ 327 Clayton (1996) shows that the risk premium on Canadian property varies over time and is strongly related to general economic conditions. The study adopts the appraisal-based Morguard Property Index and Russell Canadian Property Index (MRCPI) and the indirect property investment on the Toronto Stock Exchange (TSE 300 real estate index) in the empirical investigation where the indexes are unsmoothed prior to statistical estimation. Using a VAR that includes the total return, income return and net operating income level of MRCPI and the TSE 300 real estate index, the study suggests that time variation in property risk is partly predictable, and thus can help forecast future movements in commercial property values. In an international setting, Renaud (1997), prompted by the phenomenal effect of the globalization of financial markets on property markets around the world, documents the international and domestic factors that contributed to this strong global property cycle. The above analysis of the literature indicates that extensive efforts have been made in recent years to examine property performance in association with the economy and financial markets. However, while a few do so in establishing some kinds of links between property performance and macroeconomic variables and using the latter to help explain the former, a fair portion of the studies are still confined within the property market itself. Nevertheless, the concepts and methodologies of these studies can be claimed to be those used in modern economic research based on fundamental relationships between economic variables, with the relationship between income and value being the most commonly referred one. All the statistical procedures used are time domain regressions, which, as will be discussed later, are not powerful when the variables are featured by cycles and, in a multivariate setting, by common cycles and phases. Subsequently, the results from the above-mentioned studies have little to offer with regard to the cycle components in the variables, which does not appear to be particularly encouraging when the study is intended to focus on cycles and common cycles. The findings of the above studies on property cycles are generally better explained and as expected when they are confined to the property sector itself than in a multi-sectoral setting. These findings have the following strands: (1) how cycles or fluctuations develop and whether they are bound by the price-income relationship; (2) what are the phase relations in demand cycles and supply cycles; (3) whether there exist identifiable stages of property cycles; and (4) whether macroeconomic variables help explain property cycles and performance. The first two sets of investigations and associated findings, though multivariate, involve only property variables that represent the fundamental economic relationship as in the former, and the market mechanism and process as in the latter. The third set of investigations is specific applications of business cycle phases to property, typically including peak, trough, declining and recovery and their evolution processes. Only the fourth set of investigations links property returns and cycles to macroeconomic variables and attempts to explain the former with the help of the latter. The present study goes beyond establishing a link between property and the economy. It attempts to identify common cycle characteristics and patterns in the JRER ͉ Vol. 25 ͉ No. 3 – 2003 328 ͉ Wang interaction between property and the real sectors of the economy, covering the whole spectrum of short, medium and long cycles and the phase relations. Moreover, the article pays attention