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Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The need for projections in city planning and the social sciences were examined. The differences between forecasts and projections were discussed and various forecasting methods surveyed. The relationship between forecast types and planning applications was described. The Potential Housing Demand Model (PHD Model) of Canada Mortgage and Housing Corporation was examined in detail. An overview of the functioning of the model was presented along with an examination of the three main components of the model: the population projection model, the household projection model and the potential housing demand projection model. Methods of forecast appraisal were reviewed. The main criteria used by researchers were discussed. Accuracy and theoretical coherence were considered the primary criteria of appraisal by all major researchers in this field of inquiry. Correlates of accuracy were presented and discussed. Finally, a representative sample of past research was summarized and the main findings of these investigations presented. The rationale of the study was addressed and the following two objectives were stated: (1) To appraise the performance of the Potential Housing Demand Model in a manner consistent with past research. (2) To determine the performance of the PHD model with respect to the following two general findings of past research: (A) A forecast time horizon is the strongest and most consistent correlate of its accuracy. (B) The essential importance of the validity of core assumptions. The results of the case study analysis generally agreed with the two findings of past research except in the household demand component of the model which did not overestimate the overall level of households less accurately as the forecast horizon extended farther out. Also, in contrast to past research, the PHD model actually predicted a more accurate value for household growth for the entire 25 year period than it did for any 5 year census period.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The need for projections in city planning and the social sciences were examined. The differences between forecasts and projections were discussed and various forecasting methods surveyed. The relationship between forecast types and planning applications was described. The Potential Housing Demand Model (PHD Model) of Canada Mortgage and Housing Corporation was examined in detail. An overview of the functioning of the model was presented along with an examination of the three main components of the model: the population projection model, the household projection model and the potential housing demand projection model. Methods of forecast appraisal were reviewed. The main criteria used by researchers were discussed. Accuracy and theoretical coherence were considered the primary criteria of appraisal by all major researchers in this field of inquiry. Correlates of accuracy were presented and discussed. Finally, a representative sample of past research was summarized and the main findings of these investigations presented. The rationale of the study was addressed and the following two objectives were stated: (1) To appraise the performance of the Potential Housing Demand Model in a manner consistent with past research. (2) To determine the performance of the PHD model with respect to the following two general findings of past research: (A) A forecast time horizon is the strongest and most consistent correlate of its accuracy. (B) The essential importance of the validity of core assumptions. The results of the case study analysis generally agreed with the two findings of past research except in the household demand component of the model which did not overestimate the overall level of households less accurately as the forecast horizon extended farther out. Also, in contrast to past research, the PHD model actually predicted a more accurate value for household growth for the entire 25 year period than it did for any 5 year census period.
Author: N. H. Lithwick Publisher: ISBN: Category : Housing forecasting Languages : en Pages : 99
Book Description
The primary purpose of this study is to review several model-based forecasting methods that can be used for forecasting the housing sector and mortgage markets.
Author: Soo-Bin Park Publisher: ISBN: Category : Housing Languages : en Pages : 174
Book Description
This report is organized into two parts. In part I of the report a description of the basic structure of an econometric model of the Canadian housing sector and mortgage market is presented. The model is a result of the effort of the Canada Mortgage and Housing Corporation to enhance its forecasting ability in the area of the housing sector and mortgage market in the Canadian economy. Structural equations of the model have been estimated using available quarterly data in the period from 1963:1 to 1990:4. Time series data on many housing and mortgage market variables are not available for the entire 30 year period. Thus the sample period used in the model estimation varies from one equation to another, depending on the availability of data for the variables included in the equation. Part II presents a series of autoregressive integrated moving average (ARIMA) models of Canadian housing sector and mortgage market variables. It includes a brief summary of ARIMA modeling techniques. Appendix A at the end of the report contains a list of variables and their data sources and Appendix C, a selected bibliography of ARIMA modeling.
Author: Philip Hans Franses Publisher: Cambridge University Press ISBN: 1316124010 Category : Business & Economics Languages : en Pages : 145
Book Description
To what extent should anybody who has to make model forecasts generated from detailed data analysis adjust their forecasts based on their own intuition? In this book, Philip Hans Franses, one of Europe's leading econometricians, presents the notion that many publicly available forecasts have experienced an 'expert's touch', and questions whether this type of intervention is useful and if a lighter adjustment would be more beneficial. Covering an extensive research area, this accessible book brings together current theoretical insights and new empirical results to examine expert adjustment from an econometric perspective. The author's analysis is based on a range of real forecasts and the datasets upon which the forecasters relied. The various motivations behind experts' modifications are considered, and guidelines for creating more useful and reliable adjusted forecasts are suggested. This book will appeal to academics and practitioners with an interest in forecasting methodology.
Author: Erdener Kaynak Publisher: ISBN: Category : Delphi method Languages : en Pages : 259
Book Description
The objective of this research is to forecast changes in the demand for housing in Atlantic Canada over the next twenty years. This research provides an educative appraisal of what experts in the Atlantic Provinces view as the future direction and trends of housing in this region. Specifically, the study's objective can be divided into three main sections: 1) analyzing the potential demand structure in Atlantic Canada's housing market, through study of the possible value changes which will affect the housing market within the next 20 years; 2) the appraisal of needs and priorities viewed in relation to changing social, economic and political factors; 3) suggestions for the characteristics, design and development of the type of home which would reflect the needs and desires of major target groups among households of Atlantic Canada by the year 2005.
Author: Canada Mortgage and Housing Corporation. Research Division Publisher: ISBN: Category : Housing forecasting Languages : en Pages : 160
Book Description
This paper describes population, household, and potential housing demand projections generated using the CMHC Potential Housing Demand Projection Model.
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Author: Canada Mortgage and Housing Corporation
Author: N. H. Lithwick
Author: Soo-Bin Park
Author: Philip Hans Franses
Author: Canada Mortgage and Housing Corporation
Author: Erdener Kaynak
Author: Canada Mortgage and Housing Corporation. Research Division
Author: Canada Mortgage and Housing Corporation