Method for determining house prices indices
First Claim
1. A computer-implemented method for determining a real estate price index based on a repeat sales model, the method comprising the steps of:
- a processor executing in a first stage regression, regressing the difference in a log price of a second sale minus a log price of a first sale for a property on a set of dummy variables, each log price representing a time period except a base period;
a processor executing in a second stage regression, using a quadratic formula to model, and estimate a dispersion of residual values with respect to time interval and determining a modified dispersion by determining a minimum dispersion value corresponding to a first point in time and a maximum dispersion value corresponding to a second point in time, wherein the modified dispersion is configured such that the dispersion value is not below zero at times less than, the first point in time and is held at the maximum dispersion value at times greater than the second point in time;
a processor executing in a third stage regression, repeating the first stage regression using the inverse of the square root of fitted values from the quadratic formula from the second stage regression as weights;
determining the real estate price index resulting from the first, second and third stage regressions; and
storing the determined real estate price index in a computer memory.
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Abstract
A method for estimating a real estate price index based on a repeat sales model. The method includes the steps of eliminating corrupt portions of data used to determine price indices; regressing a difference in a log price of a second sale minus a log price of a first sale for a property on a set of dummy variables, eliminating the observations with zero residuals for estimating the dispersion function; using a quadratic formula to model a dispersion of residual values with respect to time interval; using the quadratic formula to solve for a dispersion for each time interval starting with a minimum positive value; determining a minimum dispersion value that is a value calculated from the quadratic formula; determining a maximum dispersion value that is calculated from the quadratic formula for each time interval starting with a minimum positive value, wherein the dispersion values are prevented from decreasing with increasing time intervals; repeating the step of regressing using the inverse of the square root of fitted values from the quadratic formula as weights; identifying and selecting the time periods and associated data for estimating a price index that covers a particular time period; excluding the index values which are determined to be unreliable; and obtaining an index series for a lower geographic level by using the index series of a higher geographic level.
43 Citations
20 Claims
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1. A computer-implemented method for determining a real estate price index based on a repeat sales model, the method comprising the steps of:
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a processor executing in a first stage regression, regressing the difference in a log price of a second sale minus a log price of a first sale for a property on a set of dummy variables, each log price representing a time period except a base period; a processor executing in a second stage regression, using a quadratic formula to model, and estimate a dispersion of residual values with respect to time interval and determining a modified dispersion by determining a minimum dispersion value corresponding to a first point in time and a maximum dispersion value corresponding to a second point in time, wherein the modified dispersion is configured such that the dispersion value is not below zero at times less than, the first point in time and is held at the maximum dispersion value at times greater than the second point in time; a processor executing in a third stage regression, repeating the first stage regression using the inverse of the square root of fitted values from the quadratic formula from the second stage regression as weights; determining the real estate price index resulting from the first, second and third stage regressions; and storing the determined real estate price index in a computer memory. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A computer-implemented method for obtaining an index series based on a repeat sales model, the method comprising the steps of:
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eliminating corrupt portions of data used to determine price indices; a processor executing in a first stage regression, regressing a difference in a log price of a second sale minus a log price of a first sale for a property on a set of dummy variables, each log price representing a time period except a base period; eliminating the observations with zero residuals for estimating the dispersion function; a processor executing in a second stage regression, using a quadratic formula to model and estimate a dispersion of residual values with respect to time interval and determining a modified dispersion by determining a minimum dispersion value corresponding to a first point in time and a maximum dispersion value corresponding to a second point in time, wherein the modified dispersion is configured such that the dispersion value is not below zero at times less than the first point in time and is held at the maximum dispersion value at times greater than the second point in time; repeating the first stage regression using the inverse of the square root of fitted values from the quadratic formula from the second stage regression as weights; identifying and selecting the time periods and associated data for estimating a price index that covers a particular time period; excluding the time periods for which the index values are determined to be unreliable; obtaining an index series for a relatively small geographic area by using an index series of a relatively large geographic area; and storing the obtained index series for the relatively small geographic area in a computer memory. - View Dependent Claims (18)
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19. A computer system for determining a real estate price index based on a repeat sales model, the system comprising:
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a memory; and a processor, for executing program instructions stored in the memory, the program instructions executed to provide operations comprising; in a first stage regression, regressing the difference in a log price of a second sale minus a log price of a first sale for a property on a set of dummy variables, each log price representing a time period except a base period; in a second stags regression, using a quadratic formula to model and estimate a dispersion of residual values with respect to time interval and determining a modified dispersion by determining a minimum dispersion value corresponding to a first point in time and a maximum dispersion value corresponding to a second point in time, wherein the modified dispersion is configured such that the dispersion value is not below zero at times less than the first point in time and is held at the maximum dispersion value at times greater than the second point in time; in a third stage regression, repeating the first stage regression using the inverse of the square root of fitted values from the quadratic formula from the second stage regression as weights; determining the real estate price index resulting from the first, second and third stage regressions; and storing the determined real estate price index in a computer memory. - View Dependent Claims (20)
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Specification