An intertemporal analysis of the shifting of FHA discount points to buyers

1984 ◽  
Vol 5 (4) ◽  
pp. 242-250
Author(s):  
William M. Taylor ◽  
Dean W. Wichern ◽  
Craig E. Stanley
Keyword(s):  
Discount Points

FHA AND VA MORTGAGE DISCOUNT POINTS AND HOUSING PRICES

1977 ◽  
Vol 32 (5) ◽  
pp. 1766-1773 ◽  
Author(s):  
Robert H. Zerbst ◽  
William B. Brueggeman
Keyword(s):  
Housing Prices ◽  
Discount Points

The Shifting of FHA Discount Points: Actual Vs. Expectations

1984 ◽  
Vol 12 (2) ◽  
pp. 153-161 ◽  
Author(s):  
Stanley D. Smith ◽  
G. Stacy Sirmans
Keyword(s):  
Discount Points

Discount Points and Housing Prices: A Reply

1979 ◽  
Vol 34 (4) ◽  
pp. 1055-1060 ◽  
Author(s):  
WILLIAM B. BRUEGGEMAN ◽  
ROBERT H. ZERBST
Keyword(s):  
Housing Prices ◽  
Discount Points

scholarly journals Do Minorities Pay More for Mortgages?

2020 ◽  
Author(s):  
Neil Bhutta ◽  
Aurel Hizmo
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Racial Discrimination ◽  
Race And Ethnicity ◽  
Three Dimensions ◽  
Data Set ◽  
Unique Data ◽  
Discount Points ◽  
The Interest Rate ◽  
Mortgage Lenders

Abstract We test for racial discrimination in the prices charged by mortgage lenders. We construct a unique data set from which we observe the three dimensions of a mortgage’s price: the interest rate, discount points, and fees. Although we find statistically significant gaps by race and ethnicity in interest rates, these gaps are offset by differences in discount points. We trace out point-rate schedules and show that minorities and whites face identical schedules, but sort to different locations on the schedule. Such sorting may reflect systematic differences in liquidity or preferences. Finally, we find no differences in total fees by race or ethnicity.

Discount Points and Housing Prices: Comment

1979 ◽  
Vol 34 (4) ◽  
pp. 1049-1054 ◽  
Author(s):  
PETER F. COLWELL ◽  
KARL L. GUNTERMANN ◽  
C. F. SIRMANS
Keyword(s):  
Housing Prices ◽  
Discount Points

Cryptography

2030 ◽  
2010 ◽  
Author(s):  
Rutger van Santen ◽  
Djan Khoe ◽  
Bram Vermeer
Keyword(s):  
World War Ii ◽  
Mobile Communication ◽  
Prime Numbers ◽  
Purchasing Behavior ◽  
Electronic Payments ◽  
Intelligence Services ◽  
Discount Points ◽  
The Right ◽  
Regular Contact ◽  
Mathematical Operations

Electronic payments, Internet shopping, and mobile communication have fundamentally changed our society and not only because digital services have made our lives more convenient. Never before in our history has our behavior been tracked in such detail as it is today. The bank remembers precisely where and when we withdraw cash from the machine, the phone company keeps a list of all our calls, and the online bookstore knows exactly what we like to read. Stores use loyalty cards and discount points to record their customers’ purchasing behavior. These databases have proved extremely useful. Companies can present us with attractive offers at just the right moment. All those data are useful for the authorities, too. They tell them if someone is in regular contact with a suspect or where a person was located at a particular time. The information helps the police and intelligence services prevent bombings or trace pedophiles. Much of this information is protected so that not just anyone is able to poke around our personal digital records. But protecting our privacy is increasingly difficult because the number of databases and communication channels continues to grow rapidly. Messages have been protected since the beginning of written communication. For a couple of millennia now, military dispatches have been translated into an incomprehensible alphabet soup in case they should fall into enemy hands. Breaking codes was and is a challenge. The course of World War II would probably have been entirely different if military codes had been more robust. The process of encoding and decoding can, of course, be performed much faster and more effectively in the computer age than was ever possible with pen and paper. Cryptography—the science of encryption—has perfected its techniques over the past decades. Cryptographers are constantly searching for mathematical operations that will allow insiders to decode a message easily and make it so hard for outsiders that it’s no longer worth the effort of even trying. Several important security techniques use prime numbers—numbers that are only divisible by 1 and by themselves. Examples are 2, 3, 5, and 13 but also 7,901 and 16,769,023.

Sign in / Sign up

Export Citation Format

Share Document