Identification of Mortgage Demand Function with Heterogeneous Preferences

2016 ◽  
Author(s):  
Evgeniy M. Ozhegov
Keyword(s):  
Demand Function ◽  
Heterogeneous Preferences ◽  
Mortgage Demand

scholarly journals Household mortgage demand: a study of the UK, Australia and Japan

2019 ◽  
Vol 12 (1) ◽  
pp. 110-130 ◽  
Author(s):  
Michio Naoi ◽  
Piyush Tiwari ◽  
Yoko Moriizumi ◽  
Norifumi Yukutake ◽  
Norman Hutchison ◽  
...  
Keyword(s):  
Demand Function ◽  
Income Elasticity ◽  
Ordinary Least Squares ◽  
Housing Demand ◽  
Mortgage Market ◽  
Data Sets ◽  
Content Type ◽  
Institutional Structures ◽  
The Uk ◽  
Mortgage Demand

PurposeHomeownership has been the main focus of housing policies in most countries. Typical means that households use to achieve homeownership is to take out a loan and supplement this with accumulated wealth for a downpayment. This paper aims to analyze the mortgage demand behavior of households in the UK, Australia and Japan.Design/methodology/approachUsing three panel data sets, HILDA for Australia, KHPS for Japan and USS for the UK, the paper estimates three equations using ordinary least squares: mortgage demand function, housing demand function and initial loan to value ratio function.FindingsThough homeownership is a preferred tenure and the mortgages are “recourse” loans, housing markets in these three countries operate in different mortgage market institutional structures. Results indicate that income elasticity of mortgage demand differ despite income elasticity of housing demand being similar. Different mortgage institutions in countries that pose constraints for borrowers also determine mortgage demand. Other factors such as demography and economic conditions have also played an important role in determining mortgage and housing demand.Originality/valueThe paper is first, to the authors’ knowledge, that explores the role of institutions in mortgage demand in a comparative framework for the UK, Japan and Australia.

scholarly journals Effects of Ad-hoc Data Truncation and Homogeneous Preferences on Recreational Demand and Values: An Application to the George Washington and Jefferson National Forests

2021 ◽  
pp. 1-15
Author(s):  
Kavita Sardana ◽  
John C. Bergstrom ◽  
J. M. Bowker
Keyword(s):  
Latent Class ◽  
Ad Hoc ◽  
Cost Model ◽  
Consumer Surplus ◽  
Poisson Model ◽  
Travel Cost ◽  
National Forests ◽  
Heterogeneous Preferences ◽  
George Washington ◽  
Travel Cost Model

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.

scholarly journals Complete subset averaging with many instruments

2020 ◽  
Author(s):  
Seojeong Lee ◽  
Youngki Shin
Keyword(s):  
Demand Function ◽  
Simulation Experiment ◽  
Mean Squared Error ◽  
Asymptotic Optimality ◽  
Weighted Average ◽  
Subset Size ◽  
Extensive Simulation ◽  
Squared Error ◽  
Many Instruments ◽  
Class Of Estimators

Summary We propose a two-stage least squares (2SLS) estimator whose first stage is the equal-weighted average over a complete subset with k instruments among K available, which we call the complete subset averaging (CSA) 2SLS. The approximate mean squared error (MSE) is derived as a function of the subset size k by the Nagar (1959) expansion. The subset size is chosen by minimising the sample counterpart of the approximate MSE. We show that this method achieves asymptotic optimality among the class of estimators with different subset sizes. To deal with averaging over a growing set of irrelevant instruments, we generalise the approximate MSE to find that the optimal k is larger than otherwise. An extensive simulation experiment shows that the CSA-2SLS estimator outperforms the alternative estimators when instruments are correlated. As an empirical illustration, we estimate the logistic demand function in Berry et al. (1995) and find that the CSA-2SLS estimate is better supported by economic theory than are the alternative estimates.

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