Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- and individual-level data that underlies official estimates of poverty and health. For this reason, developing countries often do not have the budget to update their estimates of poverty and health regularly, even though these estimates are most needed there. One way to reduce the financial burden is to substitute some of the real data with predicted data. An approach referred to as double sampling collects the expensive outcome variable for a sub-sample only while collecting the covariates used for prediction for the full sample. The objective of this study is to determine if …
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- and individual-level data that underlies official estimates of poverty and health. For this reason, developing countries often do not have the budget to update their estimates of poverty and health regularly, even though these estimates are most needed there. One way to reduce the financial burden is to substitute some of the real data with predicted data. An approach referred to as double sampling collects the expensive outcome variable for a sub-sample only while collecting the covariates used for prediction for the full sample. The objective of this study is to determine if …
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- andindividual-level data that underlies official estimates of poverty and health. Forthis reason, developing countries often do not have the budget to update their estimatesof poverty and health regularly, even though these estimates are most neededthere. One way to reduce the financial burden is to substitute some of the realdata with predicted data. An approach referred to as double sampling collectsthe expensive outcome variable for a sub-sample only while collecting thecovariates used for prediction for the full sample. The objective of this studyis to determine if this would indeed allow for realizing meaningful reductionsin …
New Methodology For Constructing Real Estate Price Indices Applied To The Singapore Residential Market, Liang Jiang, Peter C. B. Phillips, Jun Yu
New Methodology For Constructing Real Estate Price Indices Applied To The Singapore Residential Market, Liang Jiang, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This paper develops a new methodology for constructing a real estate price index that utilizes all transaction price information, encompassing both single-sales and repeat-sales. The method is less susceptible to specification error than standard hedonic methods and is not subject to the sample selection bias involved in indexes that rely only on repeat sales. The methodology employs a model design that uses a sale pairing process based on the individual building level, rather than the individual house level as is used in the repeat-sales method. The approach extends ideas from repeat-sales methodology in a way that accommodates much wider datasets. …
Halbert White Jr. Memorial Jfec Lecture: Pitfalls And Possibilities In Predictive Regression, Peter C. B. Phillips
Halbert White Jr. Memorial Jfec Lecture: Pitfalls And Possibilities In Predictive Regression, Peter C. B. Phillips
Research Collection School Of Economics
Financial theory and econometric methodology both struggle in formulating models that are logically sound in reconciling short-run martingale behavior for financial assets with predictable long-run behavior, leaving much of the research to be empirically driven. The present article overviews recent contributions to this subject, focusing on the main pitfalls in conducting predictive regression and on some of the possibilities offered by modern econometric methods. The latter options include indirect inference and techniques of endogenous instrumentation that use convenient temporal transforms of persistent regressors. Some additional suggestions are made for bias elimination, quantile crossing amelioration, and control of predictive model misspecification.
A New Hedonic Regression For Real Estate Prices Applied To The Singapore Residential Market, Jiang Liang, Peter C. B. Phillips, Jun Yu
A New Hedonic Regression For Real Estate Prices Applied To The Singapore Residential Market, Jiang Liang, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This paper develops a new hedonic method for constructing a real estate price index that utilizes all transaction price information that encompasses both single-sale and repeat-sale properties. The new method is less prone to specification errors than standard hedonic methods and uses all available data. Like the Case-Shiller repeat-sales method, the new method has the advantage of being computationally efficient. In an empirical analysis of the methodology, we fit the model to all transaction prices for private residential property holdings in Singapore between Q1 1995 and Q2 2014, covering several periods of major price fluctuation and changes in government macro …
Cost-Effective Estimation Of The Population Mean Using Prediction Estimators, Tomoki Fujii, Roy Van Der Weide
Cost-Effective Estimation Of The Population Mean Using Prediction Estimators, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
This paper considers the prediction estimator as an efficient estimator for the population mean. The study may be viewed as an earlier study that proved that the prediction estimator based on the iteratively weighted least squares estimator outperforms the sample mean. The analysis finds that a certain moment condition must hold in general for the prediction estimator based on a Generalized-Method-of-Moment estimator to be at least as efficient as the sample mean. In an application to cost-effective double sampling, the authors show how prediction estimators may be adopted to maximize statistical precision (minimize financial costs) under a budget constraint (statistical …
Forecasting The Car Penetration Rate (Cpr) In China: A Nonparametric Approach, Sainan Jin, Liangjun Su
Forecasting The Car Penetration Rate (Cpr) In China: A Nonparametric Approach, Sainan Jin, Liangjun Su
Research Collection School Of Economics
With strong economic growth, the auto industry has made great breakthroughs in recent years and has become a backbone industry in China, while cars play an increasingly important role, and are now the principal part of the auto industry. Both China's government and academic circles take strong interest in the prediction of CPR (i.e. car penetration rate or cars per thousand people), which will be the main guidance for the future industry policy. We summarize the existing problems in recent research and propose to use nonparametric methods to estimate the CPR and its elasticity with respect to GDP per capita …