Information Aggregation Bias and Samuelson's Dictum

Under the assumption of incomplete information, idiosyncratic shocks may not dissipate in the aggregate. An econometrician who incorrectly imposes complete information and applies the law of large numbers may be susceptible to information aggregation bias. Tests of aggregate economic theory will be misspecified even though tests of the same theory at the microlevel deliver the correct inference. A testable implication of information aggregation bias is “Samuelson's Dictum” or the idea that stock prices can simultaneously display “microefficiency” and “macroinefficiency;” an idea accredited to Paul Samuelson. Using firm-level data from the Center for Research in Security Prices, we present empirical evidence consistent with Samuelson's dictum. Specifically, we conduct two standard tests of the linear present value model of stock prices: a regression of future dividend changes on the dividend-price ratio and a test for excess volatility. We show that the dividend price ratio forecasts the future growth in dividends much more accurately at the firm level as predicted by the present value model, and that excess volatility can be rejected for most firms. When the same firms are aggregated into equal-weighted or cap-weighted portfolios, the estimated coefficients typically deviate from the present value model and “excess” volatility is observed; this is especially true for aggregates (e.g., S&P 500) that are used in most asset pricing studies. To investigate the source of our empirical findings, we propose a theory of aggregation bias based on incomplete information and segmented markets. Traders specializing in individual stocks conflate idiosyncratic and aggregate shocks to dividends. To an econometrician using aggregate data, these assumptions generate a rejection of the present value model even though individual traders are efficiently using their available information.     

存量房交易计税价格批量评估典型技术路线比较

针对我国存量房交易中存在的买卖双方低报交易价格问题,税务部门提出应将评税技术应用于房地产交易计税价格核定。丹东、杭州、南京作为试点城市建立了各自的存量房交易计税价格批量评估体系,其他城市可以学习和借鉴这三个城市的经验,再结合本地房地产市场情况,建立符合本地实际的应用房地产估价技术评估存量房交易价格申报工作的路径与方法。房地产评税技术的完善,一方面可以打击当前存量房交易中普遍存在的用“阴阳合同”逃避交易税费的行为;另一方面可以为正在推进的房产税改革以及住房保有环节征税等提供技术支持。     

Risks for the long run: Estimation with time aggregation

The discrepancy between the decision and data-sampling intervals, known as time aggregation, confounds the identification of long-, short-run growth, and volatility risks in asset prices. This paper develops a method to simultaneously estimate the model parameters and the decision interval of the agent by exploiting identifying restrictions of the Long Run Risk (LRR) model that account for time aggregation. The LRR model finds considerable empirical support in the data; the estimated decision interval of the agents is 33 days. Our estimation results establish that long-run growth and volatility risks are important for asset prices.     

The Structure of Chinese Urban Land Prices: Estimates from Benchmark Land Price Data

Taking the recent benchmark land prices published by the Chinese city governments, the paper estimates commercial and residential land price curves of Chinese cities using cross-sectional data, controlling for urban population size and income level. The urban land leasing price–distance relationship is estimated based on the argument that monocentric urban structure is representative for Chinese cities. Both population size and income level are found to positively affect urban land price and price–distance gradients. Commercial land prices are higher than residential land prices except in suburbs or outer central urban areas, where the land prices of different uses converge. In most situations, commercial use price gradients are larger than those of residential use.

The Geography of Equity Analysis

I provide evidence that geographically proximate analysts are more accurate than other analysts. Stock returns immediately surrounding forecast revisions suggest that local analysts impact prices more than other analysts. These effects are strongest for firms located in small cities and remote areas. Collectively these results suggest that geographically proximate analysts possess an information advantage over other analysts, and that this advantage translates into better performance. The well‐documented underwriter affiliation bias in stock recommendations is concentrated among distant affiliated analysts; recommendations by local affiliated analysts are unbiased. This finding reveals a geographic component to the agency problems in the industry.     

Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes

In this article I study the statistical properties of a bias-correctedrealized variance measure when high-frequency asset prices arecontaminated with market microstructure noise. The analysisis based on a pure jump process for asset prices and explicitlydistinguishes among different sampling schemes, including calendartime, business time, and transaction time sampling. Two mainfindings emerge from the theoretical and empirical analysis.First, based on the mean-squared error (MSE) criterion, a biascorrection to realized variance (RV) allows for the more efficientuse of higher frequency data than the conventional RV estimator.Second, sampling in business time or transaction time is generallysuperior to the common practice of calendar time sampling inthat it leads to a further reduction in MSE. Using IBM transactiondata, I estimate a 2.5-minute optimal sampling frequency forRV in calendar time, which drops to about 12 seconds when afirst-order bias correction is applied. This results in a morethan 65% reduction in MSE. If, in addition, prices are sampledin transaction time, a further reduction of about 20% can beachieved.     

Removing biases in computed returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.     

Aggregation of Local Housing Markets

This article explores the implications of spatial aggregation for parameter estimates in models of the housing sector. Using illustrative static and dynamic models and realistic assumptions about the true parameter values at the level of the local market, the article characterizes and quantifies the bias resulting from spatial aggregation and then uses the results to shed light on some previous findings from aggregate modeling of the housing sector.     

Pricing,exit, and location decisions of firms: Evidence on the role of debt and operating efficiency

We compare pricing and exit decisions of discounters across the business cycle. Cities containing high debt and/or low efficiency firms display higher prices during non-recession years. During recessions, prices increase in cities with less efficient incumbents, but decrease in cities with a mix of high and low debt firms. High debt firms are more likely to exit cities with lower prices, and high debt exiting firms are more likely to be efficient. Apparently, low debt firms strategically lower prices during recessions to force exit of efficient, financially constrained rivals. Weaker competitors face another cost. New entrants locate closer.     

房价对城镇居民收入差距的影响研究

依据我国33个大中城市2000—2017年的面板数据构建动态面板模型,考量房价对城镇居民收入差距的影响及区域性差异。结果表明：房价上涨对于城镇居民收入差距扩大具有显著正向影响,且对东部城市的影响显著高于非东部城市,人均GDP、政府教育投入、城镇人口比重和第三产业比重也对城镇居民收入差距具有一定影响。鉴此,宜从税收政策、产业结构、政府教育投入及居住成本等方面合理控制城镇居民收入差距。     

Temporal aggregation and purchasing power parity persistence

This paper uses a unique new monthly US-UK real exchange rate series for the January 1794-December 2009 period to reexamine the academic debate over purchasing power parity (PPP). The consensus view described by Rogoff (1996) is that PPP holds in the long-run, but short-run deviations are very persistent, with half-lives ranging from 3 to 5 years. Most of the literature using long time series relies on the annual data developed by Lee (1976) and Lothian and Taylor (1996), which were both constructed from underlying higher-frequency data sources. Estimates of purchasing power parity persistence using these series may therefore be subject to temporal aggregation bias. We find evidence of aggregation bias which indicates the half-life of PPP deviations has been overestimated in much of the previous literature. We also find that estimates of the half-lives are further reduced once we account for the Harrod (1933)-Balassa (1964)-Samuelson (1964) effect. The result of aggregation bias appears to be robust even when considering the case that real exchange rates exhibit nonlinear dynamics.     

On the relationship between classical chain ladder and granular reserving

We connect classical chain ladder to granular reserving. This is done by defining explicitly how the classical run-off triangles are generated from individual iid observations in continuous time. One important result is that the development factors have a one to one correspondence to a histogram estimator of a hazard running in reversed development time. A second result is that chain ladder has a systematic bias if the row effect has not the same distribution when conditioned on any of the aggregated periods. This means that the chain ladder assumptions on one level of aggregation, say yearly, are different from the chain ladder assumptions when aggregated in quarters and the optimal level of aggregation is a classical bias variance trade-off depending on the data-set. We introduce smooth development factors arising from non-parametric hazard kernel smoother improving the estimation significantly.     

Constraints on short-selling and asset price adjustment to private information

This paper models effects of short-sale constraints on the speed of adjustment (to private information) of security prices. Constraints eliminate some informative trades, but do not bias prices upward. Prohibiting traders from shorting reduces the adjustment speed of prices to private information, especially to bad news. Non-prohibitive costs can have the reverse effect, but this is unlikely. Implications are developed about return distributions on information announcement dates. Periods of inactive trade are shown to impart a downward bias to measured returns. An unexpected increase in the short-interest of a stock is shown to be bad news.     

Real Estate Valuation and Cross-Boundary Air Pollution Externalities: Evidence from Chinese Cities

Within an open system of cities, compensating differentials theory predicts that local real estate prices will be higher in cities with higher quality non-market local public goods. In this case, more polluted cities will feature lower home prices. A city’s air pollution levels depend on economic activity within the city and on cross-border pollution externalities. In this paper, we demonstrate that air pollution in Chinese cities is degraded by cross-boundary externalities. We use this exogenous source of variation in a city’s air pollution to present new robust estimates of the real estate impact of local air pollution. We find that reductions in cross-boundary pollution flows have significant effects on local home prices. On average, a 10 % decrease in imported neighbor pollution is associated with a 0.76 % increase in local home prices. We also find that the marginal valuation of clean air is larger in richer Chinese cities, and hukou barrier of labor migration has been further phased out.     

Pass-Through of Exchange Rates and Competition between Floaters and Fixers

This paper studies how a rise in the share of U.S. imports from China, or any country with a fixed exchange rate, can explain a disproportionate fall in exchange rate pass-through to U.S. import prices. A theoretical model provides an explanation working through changes in markups, showing that a particular "local bias" condition is necessary and that free entry amplifies the effect. The model produces a structural equation for pass-through regressions including the China share; panel regressions over 1993–2006 indicate that the rising share of trade from China or other exchange rate fixers can explain as much as one-half of the observed decline in pass-through for the United States.     

On quality bias and inflation targets

Does Ramsey optimal policy call for adjusting the inflation target by the size of the quality bias in measured inflation? We find that if it is nonhedonic (or sticker) prices that are sticky, the conventional view, according to which it is optimal to adjust the inflation target upward by the size of the quality bias, is misguided. Furthermore, we establish that quality improvement is crucial for the determination of the optimal inflation target even in the absence of quality bias. In this case, if nonhedonic prices are sticky, sticker prices should fall at the rate of quality growth.     

Leverage,Consumer Finance,and Housing Prices in China

In this article, we focus on the effect of household borrowing behavior on housing prices in China, under the background of rapid growth of consumer finance during the past decade. We build a micromodel to deduce the relationship between consumers’ leverage, housing enterprises’ leverage, and housing prices and use a dynamic panel model and panel error correction model to do the empirical work. The results show that the first- and second-tier cities of China are greatly influenced by leverages, the second-tier cities also by local growth, and the third-tier cities are weakly affected by leverages but greatly affected by the land prices. Further explanations and discussions of the empirical results are given accordingly.     

产业集聚对中国房地产价格影响的实证研究

中国房地产价格持续上涨的成因一直是学界研究的热点。产业集聚作为市场经济活动的必然现象,是否会对房地产价格产生影响?以中国35个大中城市2000~2016年的数据为样本,构建静态面板模型和动态面板模型实证检验产业集聚对房地产价格的影响。研究表明,产业集聚对房地产价格具有显著的正向影响;进一步研究发现,人口集聚和土地成本是产业集聚影响房地产价格的重要中介,即产业集聚能够通过人口集聚和土地价格上涨来推动房价上涨。基于研究结论,为保证我国房地产市场健康发展,应采取促进区域均衡协调发展、多渠道保障城市新流入人口住房和加快土地市场改革等政策措施。     

中国房地产市场价格泡沫与空间传染效应

本文使用对数周期性幂律(Log Period Power Law, LPPL)模型对房地产市场价格泡沫进行测度,运用空间计量模型对我国房地产市场价格泡沫和空间传染效应进行研究。LPPL模型认为由价格泡沫产生并最终破裂的金融市场与地震系统具有很多相似之处,即金融资产的价格呈周期性变化规律,价格持续上涨到临界状态直至反转。本文采用2010年6月至2017年11月间我国100个城市的房地产市场数据对各城市房地产价格泡沫进行测度和物理/经济空间传染效应研究。研究发现,LPPL模型能够对我国100个城市房地产价格泡沫进行甄别且主要存在两种泡沫状态:正向泡沫(房价持续上升)和反转泡沫(房价整体下降却存在反转点)。各个城市(地区)房地产价格具有较强的空间传染性;存在正向泡沫区域的空间传染性相较反转泡沫区域更为明显,在考虑经济空间测度而不是物理空间测度的情况下,各城市间的空间传染性更强。与现有文献不同,我们发现反转泡沫区域的新房价格指数特别是二手房价格指数的上升对周边城市的房地产价格指数存在强烈的正向推高影响。最后,本文发现城市的房地产调控政策在一定程度上抑制了房价传统影响(比如信贷、新房、二手房价等)因素的推高影响,但各城市房地产价格之间的联动变化特征应该引起监管部门的注意。     

Inferring Price Information from Mortgage Payment Behavior: a Latent Index Approach

Existing price indices are based on real estate sales. This approach encounters problems when (1) sales are infrequent or (2) when these differ systematically from the overall market (selection bias). Relative to the number of properties sold on the market, a much greater number of properties have borrowers who need to make monthly mortgage payment decisions. Therefore, each month borrowers cast a vote of confidence or no confidence in their price relative to the loan balance. Based on this behavior, we invert the relation between mortgage performance and prices to derive a latent price index. Using a large sample of individual mortgages across the 10 cities investigated, the latent index in each city has a high correlation with the respective Case-Shiller index. In addition, the latent index is partially explained by the housing expectations (derived from futures on the respective Case-Shiller index) which indicates that it is not a purely reactive measure. Overall the results show that the latent index has potential to boost information resources for tracking the important real estate sector.