Uses and Abuses of Residential Building Permits in Forecasting Private Housing Starts

This paper examines the commonly held view that the Census Bureau's monthly series for residential building permits issued is a leading indicator of the series for private housing starts. A close study of the residential building permits and housing starts series shows that on a quarterly basis the series are coincident, with cyclical peaks and troughts in the seasonally adjusted data occurring in the same period. On the monthly basis for the period 1960 through 1976, the peaks and troughs in the building permits series have usually followed those in the housing starts series. Also, evidence presented in the paper shows that monthly changes in the residential building permits series are not highly correlated with changes in the housing starts series one to five months in the future. Finally, the analysis suggests that changes in the backlog of unused residential building permits are not indicative of future changes in the rate of housing starts. The major implication of these results is that permits data offer little or no information about future month-to-month changes in the rate of housing starts. However, because the building permits series is less irregular than the housing starts series and the cyclical movements of the series are basically the same, permits data can be used to identify irregular monthly movements in the starts series.     

A Regional Model of Multifamily Housing Starts

This paper presents a regional time series model of multifamily housing activity. The theoretical model, based on a profit-maximizing builder or investor is used as a basis for estimating housing start and completion equations for each of the four Census regions and the U.S. as a whole. The empirical estimates show that new housing construction is highly responsive to profitability consideration, with the elasticity being between 5 and 14. The empirical estimates also demonstrate that there is substantial variance between regions in terms of parameter estimates.     

Macroeconomic Determinants of Multifamily Housing Starts: A Descriptive Analysis

The multifamily component of residential construction has received relatively little attention in the existing literature on macro-economic housing markets. In those studies where single and multifamily starts have been treated separately [ Kawaller (1976) , Arcelus and Meltzer (1973) , Brady (1973) , Kalchbrenner (1972) Smith (1969) , the greater share of attention and background discussion has been directed toward the singlefamily sector. Such treatment probably is due to the fact that multifamily starts have traditionally accounted for the smaller fraction of total private starts. Since the Census Bureau began recording the starts breakdown in 1959, however, this fraction has not fallen much below a fifth in any quarter, and it has been as high as 48 percent. Moreover, with a growing acceptance of the condominium and cooperative housing concepts, expanding Federal rental assistance initiatives, and changing life style preferences, it would appear that increased attention given to the multifamily sector, may significantly enhance our understanding of housing markets in general.     

Forecasting Housing Markets: Lessons Learned

Forecasting changes in housing finance (instruments and institutions), housing demand (tenure, quantity, and real price), and housing production requires forecasting numerous exogenous factors—inflation, government policy, and demographic forces being the most obvious—and interpreting their impacts on the housing market. We use forecasts made over the last two decades to illustrate the importance of these variables and of interpreting their impacts appropriately.     

The Impact of Unseasonable Weather on Housing Starts

This study tests the effects of unseasonable weather on housing starts at the national and regional level. Goodman [1] examined this issue and concluded that abnormal weather conditions have little or no effect on the pace of housing starts. The models presented in this study allow the impact of unseasonable weather on starts to vary over each month of the year whereas the specification in Goodman constrained these effects to vary between only the summer and winter. In addition, lagged weather deviations are included in the model to determine if unseasonable weather affects the demand for housing or merely the timing of housing starts. The results suggest that unseasonable weather does affect the pace of housing starts in the months of the first quarter. Oddly enough, however, the results indicate that the effects of weather on starts are not offset in following months.     

Reducing the Error in Monthly Housing Starts Estimates

This paper describes a method for developing estimates of total monthly housing starts that are more accurate than the published Census Bureau figures. The technique makes use of the facts that (1) estimated building permit issuance is subject to far less sampling error than is the starts estimate and (2) permit issuance and starts bear a strong contemporaneous correlation. The conclusion is that monthly housing starts and monthly building permit issuance should be assigned nearly equal weights in developing an improved estimate of total housing starts.     

Mortgage Credit Availability, Housing Starts and the Integration of Mortgage and Capital Markets: New Evidence Using Linear Feedback

This paper employs linear feedback measures to examine the relationship between housing starts and the availability of mortgage credit. Estimates are obtained using monthly data with samples ending with May 1978 and beginning with June 1978. The results indicate that mortgage credit availability contributed significantly to short-run cycles in housing starts in the earlier sample. Such feedback is considerably smaller, however, in the later sample. The results suggest the housing finance sector has become integrated with the overall capital market as the result of the deregulation of thrift deposit rates and the development of the securitized mortgage market.     

Forecasting Prices and Excess Returns in the Housing Market

The paper uses quarterly indexes of existing single-family home prices estimated with microdata on properties that sold more than once to estimate excess returns to investment in owner-occupied housing. Housing prices and excess returns are estimated over the period 1970:1 to 1986:3 for Atlanta, Chicago, Dallas, San Francisco. Using time-series cross-section regressions we test for the forecastability of prices and excess returns using a number of independent variables. Price changes in one year tend to continue for more than one year in the same direction. The ratio of construction costs to price, changes in adult population and increases in real per capita income all are positively related to excess returns or price changes over the subsequent year. The results add weight to the argument that the market for single-family homes is inefficient.     

Alternative Housing Price Indices: An Evaluation

This paper reports on research in which eleven alternative housing price indices are constructed for two Vancouver neighbourhoods for the period from 1957 to 1979. Three criteria for good indices are presented, and the eleven indices, as well as several government and industry indices are evaluated in accordance with those criteria. It is determined that, almost surprisingly, an index based on mean sales values performs well, as do several of the hedonic price equation based indices. Several policy implications of the analysis are then discussed.     

The Demand for Housing Additions: An Empirical Analysis

Little is known of a household's decision to make a housing addition despite the large and growing size of these expenditures. This paper examines this decision in a two-step empirical process: first, those factors that influence the probability of a housing addition are determined, and second, the value of the addition made is analyzed. Preliminary results indicate that unmet housing consumption needs, but not the investment potential of housing additions, have a significant impact on both the probability of an addition and the value of an addition made. Furthermore, ceteris paribus, non-white households have a greater probability of making a housing addition, and on average, spend more on housing additions than do white households.     

Tencel织物在多种染整工艺下的表现

自从上世纪90年代Tencel纤维投入商业应用以来,Tencel织物以其原纤化的特性、优美的光泽和柔软的手感而被广泛应用。本文介绍了Tencel纤维的原纤化特性及其产生的机理,着重讲述了在不同的染整工艺下,Tencel织物所能展现的多样化的外观风格。     

Forecasting the Commercial Attractiveness of User‐Generated Designs Using Online Data: An Empirical Study within the LEGO User Community

Web 2.0 technologies and the rapid emergence of virtual user communities have created new challenges and opportunities for producer firms. The challenges concern the problem of idea overload when a large number of users are empowered to develop their own design creations. At the same time, opportunities arise because firm‐hosted user communities offer a promising source of creativity outside the firms' boundaries. In this paper, we study which data present in firm‐hosted online communities on user‐generated designs and user‐designers can be used to help a focal producer firm to reduce its workload in the selection phase by predicting which user‐generated designs it would most likely perceive as commercially attractive. Prior research emphasizes that among the vast amount of ideas generated in online user communities, it is the lead users' ideas that tend to stick out in terms of commercial attractiveness. Our paper aims to provide the next step by developing a heuristic for filtering commercially attractive ideas that are generated in online user communities. Therefore, prior lead user research is used as a point of reference for our study. This research stream has produced rich insights into the characteristics of users who are capable of developing new products that are commercially attractive from the perspective of a focal producer firm, as well as the characteristics of artifacts that such users tend to develop. Based on prior lead user research, we use theories on problem solving, creativity, and new product adoption to develop hypotheses on the factors that might influence the attractiveness of user‐generated designs from the focal producer firm's perspective in such a setting. Applying multilevel generalized linear modeling, 1799 designs from 116 user‐designers in the LEGO user community are analyzed. Our findings show that three prominent variables, the complexity of a given design, positive feedback from the community on specific designs, and the intensity of design activity by a user‐designer, can be used by a focal producer firm as filtering heuristics for the selection of promising user‐generated designs. We find an inverted U‐shaped relationship between the complexity of a user‐generated design and its perceived commercial attractiveness. Furthermore, we find a positive relationship between the positive feedback received by a given user‐generated design within the peer community and its perceived commercial attractiveness, as well as a U‐shaped relationship between the intensity of a certain user‐designer's activities and the likelihood that a given design by that user will be perceived as commercially attractive. The study is a first step toward a new Web‐based marketing research approach that can enable firms to filter vast numbers of user‐generated designs more effectively and efficiently.     

An Empirical Comparison of Sales Forecasting Models

There has been a veritable industry of forecasting models in recent decades, spurred partly by planners' search for certainty and partly by the data crunching capabilities of computers. In this article, Sanjay-kumar Rao tests two families of models on some common data sets to see how they compare. He examines how well the models fit the data and how reliable they are as forecasting tools.     

Impact Fees and the Price of New Housing: An Empirical Study

Development exactions in the form of impact fees are being used increasingly by local governments to fund the cost of providing public services necessitated by growth and development. This paper presents the results of an empirical study designed to ascertain the extent to which impact fees are capitalized into the price of new, single-family dwellings. On June 3, 1974, the city of Dunedin, located in Pinellas County, Florida, began assessing impact fees of $1,150 against all new, single-family construction. Using data on 5,839 new home sales in Dunedin and three other cities in Pinellas County from 1971–1982, it was found that builders were able to pass forward the total cost of impact fees to new home buyers. However, the price differential due to impact fees for new dwellings in Dunedin compared to the price of new dwellings in the other three cities disappeared after approximately six years. This is explained by the nature of the fee structure in Dunedin, adjustments in factor costs, increases in the price of housing in competing cities, and unrealized expectations regarding the benefits to be provided by impact fee collections.     

Consumer Preferences in Housing Market Analysis: An Application of Multidimensional Scaling Techniques

The value of single–family housing is a function of demographic, economic and psychographic variables. Much work has been done on the objectively measurable criteria, but virtually none on the subjective, perceptual criteria. This study uses consumer-supplied similarity measures of housing alternatives to develop a multidimensional perceptual "map" of the way consumers view housing choices. The dimensions of this perceptual space represent the evaluative criteria utilized, consciously or unconsciously, during the housing evaluation process. The analysis, although exploratory in nature, suggests that all perceptually defined market segments use the same evaluative construct; that market segments may be defined in terms of differences in the relative importance of each criterion; that market segments do not necessarily correspond to simple demographic measures; and that the major evaluative criteria in the perceptual process generally agree with those found in the literature based on objective measurements.     

Permits, Starts, and Completions: Structural Relationships Versus Real Options

Real estate development from raw land to completed structures is a multistage process. Given the current view of development as the exercise of a real option, the question arises whether development should be modeled as a compound option. This paper tests the validity of the compound option characterization by determining whether builders start units for which they have permits and then complete units started consistent with the predictions of the real options model. To do so, I first identify a reduced form relationship between permits and starts and then between starts and completions. The parameters of this relationship indicate how well permits proxy for starts and starts for completions. Then, I determine whether controlling for this structural relationship, new information, and uncertainty in returns affect permit exercise and completion rates, as in the exercise of real options. I find that current and previous quarter permits forecast current single-family starts, while multifamily starts require more quarterly lags of permits. More than one and two year's worth of lagged starts numbers are needed to estimate current quarter completions for single- and multifamilys buildings, respectively. The principal result is that once building permits have been obtained, the development process proceeds to completion. While there is no evidence that completion is the exercise of an option embedded in a start, some aspects of permits are consistent with builders treating them as an option for starts. However, even if they do, given permits obtained, it takes large changes in market conditions to affect small changes in starts.     

一个投资方案的优化实例

根据某大型联合企业的现状和生产发展规划项目表,探讨如何使有限的自有资金发挥尽可能大的经济效益。根据规划模型的解,得出了企业在有限的资金条件下,应考虑新上哪 些技术和基本建设项目。