scholarly journals Real estate listings and their usefulness for hedonic regressions

2021 ◽  
Author(s):  
Jens Kolbe ◽  
Rainer Schulz ◽  
Martin Wersing ◽  
Axel Werwatz
Keyword(s):  
Real Estate ◽  
Willingness To Pay ◽  
Price Index ◽  
Error Variance ◽  
Large Error ◽  
Data Sets ◽  
Transaction Data ◽  
Market Values ◽  
Research Areas ◽  
Implicit Prices

AbstractReal estate platforms provide a new source of data which has already been used as a substitute for transaction data in hedonic regression applications. This paper asks whether it is valid to do so in the established research areas of (1) willingness to pay estimation, (2) automated valuations, and (3) price index construction. It therefore compares listings and transaction data and regression results derived from them. We find that ask prices stochastically dominate sale prices, mainly because the composition of characteristics differs between the two data sets. But estimates of implicit prices also differ. As a result, willingness to pay estimates from listings data can be widely off when compared with estimates from transaction data. Listings data are not very useful to predict market values of individual houses either, as these predictions suffer from upward bias and large error variance. We find, however, that an ask price index complements a sale price index, as it is useful for nowcasting.

Estimating the Willingness to Pay to Avoid Violent Crime: A Dynamic Approach

2011 ◽  
Vol 101 (3) ◽  
pp. 625-629 ◽  
Author(s):  
Kelly C Bishop ◽  
Alvin D Murphy
Keyword(s):  
Real Estate ◽  
Willingness To Pay ◽  
Decision Maker ◽  
Violent Crime ◽  
Hedonic Model ◽  
Negative Bias ◽  
Percent Reduction ◽  
Dynamic Approach ◽  
Implicit Prices

The hedonic model, which has been used extensively in the Environmental, Urban, and Real Estate literatures, allows for the estimation of the implicit prices of housing and neighborhood attributes, as well as households' demand for these non-marketed amenities. A recognized drawback of the existing hedonic literature is that the models assume a myopic decision-maker. In this paper, we estimate a dynamic hedonic model and find that the average household is willing to pay $472 per year for a ten percent reduction in violent crime. In addition, we find that the traditional, myopic model suffers from a 21 percent negative bias.

scholarly journals Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

2021 ◽  
pp. 089443932110122
Author(s):  
Dennis Assenmacher ◽  
Derek Weber ◽  
Mike Preuss ◽  
André Calero Valdez ◽  
Alison Bradshaw ◽  
...  
Keyword(s):  
Social Media ◽  
Data Sharing ◽  
Algorithm Design ◽  
Computational Social Science ◽  
Evaluation Framework ◽  
Social Media Analytics ◽  
Data Sets ◽  
The Public ◽  
Research Areas ◽  
Media Data

Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.

scholarly journals Dampak Perubahan Nilai Tukar terhadap Indeks Harga Konsumen Bahan Makanan di Indonesia

2016 ◽  
Vol 17 (1) ◽  
pp. 1-14
Author(s):  
Siti Suarsih ◽  
Noer Azam Achsani ◽  
Nunung Nuryartono
Keyword(s):  
Exchange Rate ◽  
Error Correction ◽  
Price Index ◽  
Consumer Price Index ◽  
Error Variance ◽  
Correction Model ◽  
Vector Error Correction ◽  
Forecasting Error ◽  
Vector Error ◽  
Pass Through

Exchange Rate Change Effects on Indonesia’s Foodstuff Consumer Price IndexThe fluctuation in exchange rate Indonesia may have an impact on the price of imported goods both consumer goods (finished goods) and raw materials. The aim of this study is to analyze the impact of exchange rate changes on the Consumer Price Index (CPI) of foods categories and analyze the role of the exchange rate in explaining fluctuations in the CPI of food category in Indonesia. Econometric analysis using vector error correction model, indicates that the greatest degree of pass-through occurs in the consumer price index groups of milk and eggs. Contributions of exchange rate as the result of decomposition of forecasting error variance is largest in the meat category.Keywords: Exchange Rate Pass-Through; Consumer Price Index of Foodstu; Vector Error Correction ModelAbstrakPerubahan nilai tukar dapat berdampak pada harga barang-barang yang diimpor baik barang konsumsi (barang jadi) maupun bahan baku. Penelitian ini bertujuan untuk menganalisis dampak perubahan nilai tukar terhadap Indeks Harga Konsumen (IHK) kelompok bahan makanan dan menganalisis peranan nilai tukar dalam menjelaskan fluktuasi IHK bahan makanan di Indonesia. Analisa ekonometri menggunakan vector error correction model, menunjukkan bahwa derajat pass-through terbesar terjadi pada kelompok indeks harga konsumen susu dan telor. Kontribusi nilai tukar hasil decomposition of forecasting error variance terbesar terjadi pada kelompok daging.

scholarly journals Human Gaze Assisted Artificial Intelligence: A Review

2020 ◽  
Author(s):  
Ruohan Zhang ◽  
Akanksha Saran ◽  
Bo Liu ◽  
Yifeng Zhu ◽  
Sihang Guo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cognitive State ◽  
Data Sets ◽  
Common Goal ◽  
Research Areas ◽  
Future Challenges ◽  
Potential Applications ◽  
High Level ◽  
And Robotics

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.

Hedonic Price Analysis in Food Markets

2011 ◽  
pp. 151-180 ◽  
Author(s):  
Marco Costanigro ◽  
Jill J. Mccluskey
Keyword(s):  
Large Data ◽  
Data Sets ◽  
Hedonic Price ◽  
Long Term Effects ◽  
Food Markets ◽  
Regulatory Policies ◽  
Hedonic Price Analysis ◽  
Trade Offs ◽  
Price Relationship ◽  
Implicit Prices

This article presents the basic theory of hedonic modeling, its empirical application and relevance, and the principal limitations and challenges. Agricultural economists have long utilized the hedonic price relationship, and the hedonic price technique has been utilized to estimate the implicit prices of attributes for numerous food products. It provides a framework of the hedonic models that can be used to quantify the long-term effects of exogenous shocks on quality, or implementation of regulatory policies. This article discusses the whole armamentarium of econometric models and methods familiar to applied economists, including parametric, semi-parametric, and non-parametric approaches. The objective is to describe briefly each econometric model within the hedonic context and provide an understanding of the implications and trade-offs inherent to the choice of each alternative. This is a fruitful area of research with increased customization of products and the increasing availability of large data sets.

A Stable Transaction Based Price Index for Real Estate Thin Market

2021 ◽  
Vol 27 (4) ◽  
pp. 21-40
Author(s):  
Young-Sun Song ◽  
Hye-Young Shin ◽  
Chang-Moo Lee
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Thin Market

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

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