Analysis of Spatial Autocorrelation in House Prices

This article examines spatial autocorrelation in transaction prices of single-family properties in Dallas, Texas. The empirical analysis is conducted using a semilog hedonic house price equation and a spherical autocorrelation function with data for over 5000 transactions of homes sold between 1991:4 and 1993:1. Properties are geocoded and assigned to separate housing submarkets within metropolitan Dallas. Hedonic and spherical autocorrelation parameters are estimated separately for each submarket using estimated generalized least squares (EGLS). We find strong evidence of spatial autocorrelation in transaction prices within submarkets. Results for spatially autocorrelated residuals are mixed. In four of eight submarkets, there is evidence of spatial autocorrelation in the hedonic residuals for single-family properties located within a 1200 meter radius. In two submarkets, the hedonic residuals are spatially autocorrelated throughout the submarket, while the hedonic residuals are spatially uncorrelated in the remaining two submarkets. Finally, we compare OLS and kriged EGLS predicted values for properties sold during 1993:1. Kriged EGLS predictions are more accurate than OLS in six of eight submarkets, while OLS has smaller prediction errors in submarkets where the residuals are spatially uncorrelated and the estimated semivariogram has a large variance.     

Spinoffs and clustering

Geographic clustering of innovative industries is associated with the entry and success of spinoff firms. We develop a model to explain the multiple empirical patterns regarding cluster growth and spinoff formation and performance, without relying on agglomeration externalities. Clustering naturally follows from spinoffs locating near their parents. In our model, firms grow and spinoffs form through the discovery of new submarkets based on innovation. Rapid and successful innovation creates more opportunities for spinoff entry and drives a region's growth. Our model provides baseline estimates of levels of agglomeration that can be attributed to this process of innovation and spinoff formation.     

Anisotropic Autocorrelation in House Prices

This article examines anisotropic spatial autocorrelation in single-family house prices and in hedonic house-price equation residuals using a spherical semivariogram and transactions data for one county in the Philadelphia, Pennsylvania, MSA. Isotropic semivariograms model spatial relationships as a function of the distance separating properties in space. Anisotropic semivariograms model spatial relationships as a function of both the distance and the direction separating observations in space. The goals of this article are (1) to determine whether there is spatial autocorrelation in hedonic house-price equation residuals and (2) to empirically examine the validity of the isotropy assumption. We estimate the parameters of spherical semivariograms for house prices and for hedonic house-price equation residuals for 21 housing submarkets within Montgomery County, Pennsylvania. These housing submarkets are constructed by dividing the county into 21 groupings of economically similar adjacent census tracts. Census tracts are grouped according to 1990 census tract median house prices and according to characteristics of the housing stock. We fit the residuals of each submarket hedonic house price equation to both isotropic and anisotropic spherical semivariograms. We find evidence of spatial autocorrelation in the hedonic residuals in spite of a very elaborate hedonic specification. Additionally, we have determined that, in some submarkets, the spatial autocorrelation in the hedonic residuals is anisotropic rather than isotropic. The empirical results suggest that the spatial autocorrelation in Montgomery County single-family house-price equation residuals is anisotropic in submarkets where residents typically commute to a regional or local central business district.     

The Dynamics of Location in Home Price

It is well established that house prices are dynamic. It is also axiomatic that location influences such selling prices, motivating our objective of incorporating spatial information in explaining the evolution of house prices over time. In this paper, we propose a rich class of spatio-temporal models under which each property is point referenced and its associated selling price modeled through a collection of temporally indexed spatial processes. Such modeling includes and extends all house price index models currently in the literature, and furthermore permits distinction between the effects of time and location. We study single family residential sales in two distinct submarkets of a metropolitan area and further categorize the data into single- and multiple-transaction observations. We find the spatial component is very important in explaining house price. Moreover, the relative homogeneity of homes within the submarket and the frequency with which homes sell affects the pattern of variation across space and time. Differences between single and repeat sale data are evident. The methodology is applicable to more general capital asset pricing when location is anticipated to be influential.     

Disaggregation of Local Apartment Markets by Unit Type

Recent market segmentation research has begun to delve into the issue of whether traditional property-type categories are sufficiently homogeneous to be modeled as aggregate real estate markets. This article extends the research on rental-property market segmentation by investigating the existence of apartment submarkets determined by unit type. The study finds that one-bedroom, one-bath units; two-bedroom, one-bath units; and two-bedroom, two-bath units function as distinct submarkets differentiated by property features, neighborhood location, and temporal changes in market rent.     

Repeat Sales Regression on Heterogeneous Properties

This paper proposes a generalized repeat sales regression (GRSR) that uses repeat sales from the entire market, in which properties may have heterogeneous value appreciation processes, to estimate price indices for not only the entire market, but also submarkets or customized portfolios of properties that only have small numbers of value observations. Monte Carlo simulations provide strong evidence that the GRSR indices more accurately measure the index for the entire market as well as individual property value appreciation than conventional RSR indices. This paper also proposes a Chi-square test to detect the heterogeneity in property value appreciation across submarkets/portfolios, and use simulations to show that the test is powerful in small samples. This paper finally illustrates the application of the GRSR using a historical dataset of the Chicago housing market from 1970 to 1986.     

Manufacturing versus Distribution: Implicit Pricing of Real Property Characteristics by Submarket

This article develops and tests the idea that the industrial real estate market is an aggregate market consisting of at least two submarkets—manufacturing and distribution. While there is no observable difference in implicit pricing of most industrial property characteristics across these two submarkets, some property-characteristic implicit prices do differ. Therefore, manufacturing and distribution submarket property-pricing functions are best estimated in aggregate, while making allowances for variability of coefficients on some property characteristics. For this sample of 331 industrial property sales from the southeastern region of the United States, the two submarkets vary with regard to implicit pricing of building volume, below-average building condition, site area, and dock-high doors.     

The Effect of Regulatory Announcements on the Cost of Equity Capital of British Telecom

This paper examines the impact of regulatory announcements which affect competition, pricing policy and the supply of services in the telecommunications industry on British Telecom's (BT) systematic risk, as measured by the beta coefficient of a market model. Changes in investors' perception of a company's systematic risk will of course also change its cost of equity capital. Since BT's beta coefficient is found to be unstable over the estimation period, the market model is estimated using a time-varying parameter model. The results suggest that announcements which allow the price of BT's services to increase and announcements affecting its supply of services are likely to have an impact on BT's cost of equity capital, since they affect the investor's perception of BT's systematic risk. However, our analysis does not detect any effect from the other types of announcements tested. Further examination of the individual announcements included in the groups reveals that, within the non-significant groups, many individual announcements are significant, but they affect beta in opposite directions and thus no prediction can be made on the sign of their aggregated impact. These findings suggest that when one company dominates the industry, such as in the case of the UK telecommunications industry, the actions of the regulator do not always have the expected effect and problems of regulatory capture are likely to be present.     

Spatial variation of nonmetropolitan industrial location

This study examines economic development and industrial location in the rural Southeast using a varying coefficient model. Empirical results generated with a Poisson regression show that the varying coefficient model is appropriate and that the posited variables help explain the number of manufacturing firms which have located to a rural county. The model distinguishes between the ability of a county to attract industry both independent of distance and as a function of the distance to the nearest strategic urban center. Differences exist between the locational preferences of traditional industry and nontraditionial (diversification-enhancing) industry.     

Are Accruals during Initial Public Offerings Opportunistic?

We find evidence that initial public offering (IPO) firms, on average, have high positive issue-year earnings and abnormal accruals, followed by poor long-run earnings and negative abnormal accruals. The IPO-year abnormal, and not expected, accruals explain the cross-sectional variation in post-issue earnings and stock returns. The results are robust with respect to alternative abnormal accruals and earnings performance measures. IPO firms adopt more income-increasing depreciation policies when they deviate from similar prior performance same industry non-issuers, and they provide significantly less for uncollectible accounts receivable than their matched non-issuers. The results taken together suggest opportunistic earnings management partially explains the new issues anomaly.     

Prospect theory and the effectiveness of price limits

Assuming that traders are risk-neutral, Brennan (1986) shows that price limits are effective in improving the efficiency of futures contracts with limited accessibility to information because they obscure the exact loss when they are triggered. However, Brennan's (1986) model fails to explain why price limits also exist in contracts with abundant information like those of financial futures. We show that when traders are loss-averse, the effectiveness of price limits is strengthened even in the presence of precise information. Thus, our analysis provides a theoretical foundation explaining why price limits can be useful when market participants are not fully rational.     

Capital, corporate income taxes, and catastrophe insurance

We provide estimates of the equity capital needed and the resulting tax costs incurred when supplying catastrophe insurance/reinsurance using a partial equilibrium model that incorporates a specific loss distribution for US catastrophe losses. After consideration of insurer investment in tax-exempt securities, tax loss carry-back/forward provisions, and personal taxes, our results imply that the tax costs of equity finance alone have a substantial effect on the cost of supplying catastrophe reinsurance. These results help explain a variety of industry developments that reduce tax costs. Also, when coupled with non-tax costs of capital, these results help explain the limited scope of catastrophe insurance/reinsurance.     

Intra-lndustry Effects of Corporate Capital Investment Announcements

We examine how announcements of corporate capital investments by one firm affect the stock prices of its competitors. We find that on average, rivals experience a signifi cantly negative valuation effect. The results suggest that for the sample as a whole, the competitive effect dominates the contagion effect. We further examine various factors that could potentially explain the heterogeneous intra-industry effects of capital investment announcements. We find that rivals' share prices are more adversely affected when the announcer experiences a higher announcement effect or is the first mover in the industry. We also show that rivals experience a greater wealth loss when they have poorer investment opportunities or higher financial leverage.     

基础设施产业生态的市场化演化研究

依据生态学的基本原理,结合基础设施产业的特征,构建了基础设施产业生态系统。文章基于演化博弈视角通过构造基础设施产业生态的演化博弈模型,分析其市场化进程中的影响因素;基于生态学的种群理论和耗散结构理论,分析其市场化演化方向下的平衡增长模式,使系统稳定发展;最后基于以上分析提出了在市场化进程中优化基础设施产业生态的环境的思路。     

How industries change

It's fairly obvious: To make intelligent investments within your organization, you need to understand how your whole industry is changing. But such knowledge is not always easy to come by. Companies misread clues and arrive at false conclusions all the time. To truly understand where your industry is headed, you have to take a long-term, high-level look at the context in which you do business, says Boston University professor Anita McGahan. She studied a variety of businesses from a cross section of industries over a ten-year period, examining how industry structure affects business profitability and investor returns. Her research suggests that industries evolve along one of four distinct trajectories--radical, progressive, creative, and intermediating--that set boundaries on what will generate profits in a business. These four trajectories are defined by two types of threats. The first is when new, outside alternatives threaten to weaken or make obsolete core activities that have historically generated profits for an industry. The second is when an industry's core assets--its resources, knowledge, and brand capital--fail to generate value as they once did. Industries undergo radical change when core assets and core activities are both threatened with obsolescence; they experience progressive change when neither are jeopardized. Creative change occurs when core assets are under threat but core activities are stable, and intermediating change happens when core activities are threatened while core assets retain their capacity to create value. If your company's innovation strategy is not aligned with your industry's change trajectory, your plan for achieving returns on invested capital cannot succeed, McGahan says. But if you understand which path you're on, you can determine which strategies will succeed and which will backfire.     

Land Development: Risk, Return and Risk Management

We model and examine the financial aspects of the land development process incorporating the industry practice of preselling lots to builders through the use of option contracts as a risk management technique. Using contingent claims valuation, we are able to determine endogenously the land value, presale option value, credits spreads and the effects of presales on debt pricing and equity expected returns. We show that using presales options effectively shift market risk from the land developer to the builder. Results from the model are consistent with the high rates of return on equity observed in empirical surveys; they also suggest that developers may be justified in pursuing projects with substantially lower expected returns to equity when a large number of lots can be presold. Additionally, we show that presales reduce default risk dramatically for leveraged projects and can support a considerable reduction in the cost of construction financing. Large debt risk premiums are justified for highly levered projects, which helps explain the use of mezzanine financing in the land development industry to reduce expected default costs.

The timing of initial public offerings

We study the dynamics of IPOs by examining the tradeoff between an entrepreneur's private benefits, which are lost whenever the firm is publicly traded, and the gains from diversification. We characterize the timing dimension of the decision to go public and its impact on firm value and the evolution of firm risk over time. By endogenizing the timing of the decision to go public, we explain the clustering of IPOs and buyouts in time, the industry concentration of IPO waves, the high incidence of reprivatization of recent IPOs, and the long-run underperformance of recently issued stock relative to the shares of longer-listed companies.     

Customer anger at price increases, changes in the frequency of price adjustment and monetary policy

While firms claim to be concerned with consumer reactions to price increases, these often do not cause large reductions in purchases. The model developed here fits this by letting consumers react negatively only when they become convinced that prices are unfair. This can explain price rigidity, though its implications are not identical to those of existing models of costly price adjustment. In particular, the frequency of price adjustment can depend on economy-wide variables observed by consumers. This has implications for the effects of monetary policy and can explain why inflation does not fall immediately after a monetary tightening.     

INTANGIBLE ASSETS,BOOK‐TO‐MARKET,AND COMMON STOCK RETURNS

I examine two anomalies where the Fama and French three‐factor model fails to adequately explain monthly industry and index returns. Both anomalies are consistent with a bad model problem where the book‐to‐market factor introduces a negative bias in the intercepts. I propose the intangibles model as an alternative where the three‐factor model is known to have difficulty. This alternative model, which replaces the book‐to‐market factor with zero investment portfolio returns based on prior investments in intangible assets, is well specified in random samples, has comparable power, and fully explains both anomalies.     

Integrating Credit Models Using Accounting Information With Loan Officers' Decision Processes

This paper focuses on loan officers' cognitive processes of problem detection and problem-hypothesis formulation, which are incorporated into a credit model when they are confronted with loan decisions. Prior credit models in banking have not directly addressed loan officers' internal processes in a loan situation. The integration of both loan officers' cognitive processes and information used in a credit model can better help explain their decision-making biases. The results presented in this paper showed that information derived from a credit model influences loan officers' problem detection and problem-hypothesis formulation, and these processes are important factors in their loan approval. To identify loan officers' decision-making processes, the approach used in this paper integrates principles from financial management, economics, and cognitive psychology with methodological developments from psychometrics and econometrics.