آیا بازارهای دارایی واقعی تضمین شده، کارآمد هستند؟: شواهد جدید بین المللی بر اساس آزمون سردستی بهبود خودکار
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6850||2012||7 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 6533 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Modelling, Volume 29, Issue 3, May 2012, Pages 684–690
We re-examine the efficiency of real estate markets based on the Escanciano-Lobato (2009) autocorrelation test which we improved by means of wild bootstrapping. Through Monte Carlo simulation, we find that the wild bootstrap-based autocorrelation test has very good performance even in small samples. We apply the improved test to examine the efficiency of 14 international securitized real estate markets—Australia, Canada, France, Germany, Hong Kong, Italy, Japan, Netherlands, Norway, Singapore, Sweden, Switzerland, United Kingdom and the United States. Our results show that only six of these markets—Australia, Hong Kong, Italy, Japan, Sweden and the United States are efficient while the rest are inefficient. We also find that the degree of efficiency or inefficiency of each of these markets varies considerably across time. These findings indicate that real estate markets are relatively less efficient as compared to stock and bond markets in general and may also offer an explanation as to why existing studies on real estate market efficiency have mixed results.
This paper re-examines the issue of efficiency of the real estate markets based on the use of a new methodology—the automatic portmanteau test of Escanciano and Lobato (2009; EL, hereafter) for no autocorrelation, which we improve through wild bootstrapping. In doing so, this paper makes two contributions to the literature—first, to the financial economics literature and additionally, to the econometrics literature. First, in relation to the economics and finance literature, we contribute by providing new and more robust evidence relating to market efficiency in the context of the real estate market. The issue of market efficiency is one that is very important and one that continues to be debated in the literature since it is at the core of financial economics theories and models. It has also very important practical implications. If markets are found to be efficient, then prices are not predictable and it is not possible to gain abnormal returns (Reilly and Brown (2009)). If markets are efficient, it also means that resources are efficiently allocated since prices reflect rational and fundamental factors. Ever since the issue of market efficiency was brought to the forefront by the work of Fama in the 1970s, a voluminous amount of studies has been conducted on this issue in different financial and economic markets ever since. Overall, the evidence show that markets, particularly developed ones, are efficient, although some pockets of inefficiencies exist, especially in less developed markets (Reilly and Brown (2009)). The scale of research on this issue in the real estate markets, however, is still much less as compared to those in other markets (Schindler et al. (2010) and Schindler (2011)). Furthermore, the research on efficiency in this market has yielded mixed results depending on the specific real estate markets and time period covered and methodology used (Schindler (2011); Schindler et al. (2010) and Serrano and Hoesli (2009)). Thus, there is a need for further research on market efficiency in the real estate market. Our paper therefore addresses this need in the literature. It is well-accepted that real estate is very important as it can affect very significantly the performance of the economy and financial markets. The recent global financial crisis is a clear testimony to this. The crisis started as a real estate crisis but it then developed into a financial market and economic crisis (Hellwig (2008) and Greenlaw et al. (2008)). Real estate is an important financial asset of households, particularly in developed countries but even in less developed economies (The Economist, March 5th-11th 2011 issue). It is one that differs from other economic commodities or investment products as it serves both as an investment and consumption good. Unlike other investments such as stocks, it is also lumpy and hence, is more illiquid. Investors are also not able to short sell it. There is now, however, the existence of securitised real estate markets which in a sense overcome some of the limitations associated with real estate. The behaviour of prices of these securitised real estate markets would still, of course, factor in the basic properties of real estate. Hence, prices in these markets would still reflect the nature of real estate to a certain extent. Given these unique properties of real estate, the real estate markets provide a good new laboratory for the testing of market efficiency. Autocorrelation test is highly utilised as a test of market efficiency. If prices are random and exhibit no autocorrelation, then this is taken as an indication that the market is efficient (Fama (1970)). However, it is well-known in the econometric literature that standard autocorrelation tests could suffer from a number of problems due to, among others, heteroskedasticity and the need of (autocorrelation) lag selection (which can be quite arbitrary). Thus, as a result of these limitations, it is possible that the results of autocorrelation tests may show that markets are efficient (inefficient) when in fact they are inefficient (efficient). This situation could have been one of the major sources of the variation in evidence produced by existing studies on the efficiency of real estate markets as it is well-recognised that many economic and financial time series exhibit conditional heteroskedasticity or stochastic volatility (see Chunchachinda et al. (1997); Liu et al. (2003); Poon et al. (2004), among others). The second contribution of this paper is to the econometric literature. As mentioned earlier, this paper examines the issue of market efficiency in real estate markets through the application of a new test—the EL (2009) automatic portmanteau test for no autocorrelation, which we improve through wild bootstrapping. As discussed in the methodology section, the EL autocorrelation test overcomes a number of limitations associated with standard autocorrelation tests, such as heteroskedasticity and the use of automatic (data-driven) lag selection. However, this test is subject to non-trivial over-rejection in small-sample size applications under the null hypothesis of no autocorrelation (market efficiency). We show by Monte Carlo simulation evidence in this paper that the small-sample properties of the test improve with wild bootstrapping. In particular, the wild bootstrap-based test has desirable size properties and shows a competitive power. The wild bootstrap is a re-sampling method that approximates the sampling distribution of a (test) statistic and has been found useful in econometrics — such as autoregressions with heteroskedasticity in Goncalves and Kilian (2004), multiple variance ratio test in Kim (2006), spectral tests for the martigale difference hypothesis in Escanciano and Velasco (2006) and unit root tests in Cavaliere and Taylor (2008). In theory, as shown in Liu (1988) and Davidson and Flachaire (2008), the wild bootstrap can yield asymptotic refinements in the distributions of pivotal statistics. Also, small-sample simulations in many studies such as Kim (2006) and Cavaliere and Taylor (2008) show that wild bootstrap-based tests are accurate in size and with good power properties. In this paper, we therefore address the gap that we have identified in the real estate markets efficiency literature through the use of an improved portmanteau test that overcomes the limitations associated with standard autocorrelation tests. We improve the small-sample properties of the EL (2009) autocorrelation test by means of wild bootstrapping which we then utilise in our analysis of 14 securitised real estate markets — Australia, Canada, France, Germany, Hong Kong, Italy, Japan, Netherlands, Norway, Singapore, Sweden, Switzerland, United Kingdom and the United States. As far as we know, our paper is the first to apply this improved autocorrelation test in the study of market efficiency. Furthermore, in addition to the use of a more reliable test, we also utilised a more updated and longer data set as compared to recent studies on this issue such as those of Schindler, et al. (2010) and Schindler (2011). Thus, the results from this paper provide new and more robust evidence on efficiency in real estate markets. As an overview, first, our results show that by means of wild bootstrapping, we were able to improve the small-sample size properties of the EL (2009) autocorrelation test. When we applied this improved test to the analysis of the efficiency of 14 securitised real estate markets, we found that only six of these markets are efficient — Australia, Hong Kong, Italy, Japan, Sweden and the United States and the others are not. In line with Schindler et al. (2011), our findings show that real estate markets seem to be less efficient as compared to stock and bond markets in general. We also find that the degree of efficiency (inefficiency) of each of the markets varies across time which may explain why existing studies on real estate market efficiency have mixed results. The rest of the paper is organised as follows. Section 2 discusses the methodology while Section 3 presents the empirical results. Section 4 concludes the study.
نتیجه گیری انگلیسی
In this paper, we re-examine the issue of market efficiency using a wild-bootstrapping version of the EL (2009) automatic portmanteau test in the context of 14 different securitised real estate markets - Australia, Canada, France, Germany, Hong Kong, Italy, Japan, Netherlands, Norway, Singapore, Sweden, Switzerland, the United Kingdom and the United States. It is found that, via simulation, the wild bootstrap-based EL (2009) test has desirable size properties and shows a competitive power. Previous studies on this issue have yielded mixed results and to our knowledge, this paper is the first to use this improved new test. Thus, our paper provides more robust evidence on the issue of market efficiency in the real estate market which provides a contribution to the financial economics literature and additionally, through its improvement of an existing new method, also contributes to the econometrics literature. Our results show that only six—Australia, Hong Kong, Italy, Japan, Sweden and the United States, of the 14 markets turned out to be efficient with the other eight being shown not to be efficient. These six markets are known to be the most liquid,10 globalised and with better standards of regulation that ensure a more transparent functioning of the market, when compared to the other eight markets (Bardhan and Kroll, 2007 and Serrano and Hoesli, 2009). Hence, it appears that real estate markets, in line with Schindler (2011), are relatively less efficient as compared to stock and bond markets in general which could be a reflection of the nature of real estate. This implies that there are opportunities for international investors in the securitised real estate to earn excess returns in the inefficient markets using appropriate trading strategies. However, this could also mean that the market price mechanism in the inefficient real estate markets may not be able to allocate resources in the most productive way. Given the importance of the real estate sector to the economy, this provides a great challenge for policy makers. Our results also show that the efficiency (inefficiency) of each market is time varying which may explain why previous studies have mixed results as they are based on different time periods. Again, this may be a reflection of the regulatory changes which have occurred in the real estate markets primarily after financial crises periods for both developed and less developed markets, although these reforms were more successfully implemented in the developed markets. Financial crises often had significant links with the real estate sector and hence, financial sector reforms arising out of these crises also spilled over into the real estate sector (Dell'Ariccia et al., 2008, IMF, 2011 and Krinsman, 2007). The recent global financial crises spurred a series of regulatory reforms worldwide which cut across financial as well as real estate markets. The Asian crisis in 1998 also led to significant structural changes in the financial markets of Asia which also involved the real estate sector.