scholarly journals International Real Estate Review

2007 ◽  
Vol 10 (2) ◽  
pp. 66-93
Author(s):  
Charles Ka Yui Leung ◽  
◽  
Kelvin Siu Kei Wong ◽  
Patrick Wai Yin Cheung ◽  
◽  
...  
Keyword(s):  
Structural Breaks ◽  
Structural Break ◽  
Housing Prices ◽  
Hedonic Pricing ◽  
Future Research ◽  
Large Set ◽  
Auto Regressive ◽  
Structural Break Test ◽  
Implicit Prices ◽  
Housing Attributes

Given the dramatic fluctuations in aggregate housing prices, this paper attempts to examine whether the implicit prices of different housing attributes are “stable.” Theoretically, this paper provides perhaps the first dynamic, general equilibrium model in which housing attributes’ implicit prices fluctuate. Empirically, this paper models the time paths of different implicit prices as auto-regressive processes by employing a hedonic pricing model on a large set of housing transaction data over a relatively long period of time. An endogenous structural break test is then performed. Except for a few attributes, structural breaks are not detected. Directions for future research are discussed.

EUROPEAN FISCAL DISCIPLINE BEFORE AND AFTER EMU: CRASH DIET OR PERMANENT WEIGHT LOSS?

2008 ◽  
Vol 12 (3) ◽  
pp. 404-424 ◽  
Author(s):  
ANDREW HUGHES HALLETT ◽  
JOHN LEWIS
Keyword(s):  
Weight Loss ◽  
Structural Breaks ◽  
Structural Break ◽  
Fiscal Policies ◽  
Dynamic Effects ◽  
Fiscal Discipline ◽  
Stability Pact ◽  
Before And After ◽  
Structural Break Test ◽  
The Stability

This paper studies the evolution of European fiscal policies in three periods: the pre-Maastricht phase (to 1991); the runup to monetary union (1992–1997), and the stability pact phase (1998 onward). Using three separate indicators, we search for structural breaks that could signify a change in the average level of discipline in these periods. We find increased fiscal discipline only up to 1997. We conclude the new fiscal discipline was a temporary phenomenon, a product of the sanction of being denied entry to the Euro. After EMU, fiscal policy gradually loosened. A single structural break test will miss these dynamic effects, and could easily generate the false conclusion that fiscal discipline had tightened since the start of phase two of EMU.

scholarly journals Modelling Inflation Uncertainty with Structural Breaks Case of Turkey (1994–2013)

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Pınar Göktaş ◽  
Cem Dişbudak
Keyword(s):  
Structural Breaks ◽  
Structural Break ◽  
Inflation Uncertainty ◽  
Macroeconomic Indicators ◽  
Asymmetric Garch ◽  
Break Points ◽  
Mean And Variance ◽  
Causality Relationship ◽  
Structural Break Test ◽  
The Relationship

In recent years, the importance attached to the concept of volatility has increased and become a phenomenon frequently encountered in every field ranging from financial markets to macroeconomic indicators. In this study, inflation data obtained from CPI index for the period of 1994:01–2013:12 in Turkey was used to determine the best representative of the inflation uncertainty. To realize this, both symmetric and asymmetric GARCH-type models were employed. Since there are many factors that may lead to structural change within the economic course of Turkey, a structural break in the series has first been investigated. By administering Bai-Perron structural break test, two different break points both in mean and variance have been detected to be in February 2002 and in June 2001, respectively. The inclusion of those break points to the related equations, appropriate forecasting models were projected. Moreover it was found that, while in the periods prior to the break in both variance and mean the inflation itself was the reason for inflation uncertainty, following the dates of the break, the relationship changed bidirectionally. In the meantime, when the series was taken as a whole without considering the break, bidirectional causality relationship was also detected in the series.

scholarly journals A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
TD Randeniya ◽  
Gayani Ranasinghe ◽  
Susantha Amarawickrama
Keyword(s):  
Sri Lanka ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Urban Neighborhood ◽  
Location Factors ◽  
Property Development ◽  
Housing Attributes

Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

scholarly journals Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)

Data ◽  
2021 ◽  
Vol 6 (11) ◽  
pp. 113
Author(s):  
Pradeep Mishra ◽  
Khder Alakkari ◽  
Mostafa Abotaleb ◽  
Pankaj Kumar Singh ◽  
Shilpi Singh ◽  
...  
Keyword(s):  
Economic Policy ◽  
Structural Breaks ◽  
Structural Break ◽  
Consumer Price Index ◽  
Important Variable ◽  
Mixed Data ◽  
Large Set ◽  
Policy Uncertainty ◽  
Data Sampling ◽  
Economic Policy Uncertainty

Economics suffers from a blurred view of the economy due to the delay in the official publication of macroeconomic variables and, essentially, of the most important variable of real GDP. Therefore, this paper aimed at nowcasting GDP in India based on high-frequency data released early. Instead of using a large set of data thus increasing statistical complexity, two main indicators of the Indian economy (economic policy uncertainty and consumer price index) were relied on. The paper followed the MIDAS–Almon (PDL) weighting approach, which allowed us to successfully capture structural breaks and predict Indian GDP for the second quarter of 2021, after evaluating the accuracy of the nowcasting and out-of-sample prediction. Our results indicated low values of the RMSE in the sample and when predicting the out-of-sample1- and 4-quarter horizon, but RMSE increased when predicting the 10-quarter horizon. Due to the effect of the short-term structural break, we found that RMSE values decreased for the last prediction point.

scholarly journals International Real Estate Review

2014 ◽  
Vol 17 (1) ◽  
pp. 63-107
Author(s):  
Charles K. Leung ◽  
◽  
Wai Yip Ma ◽  
Jun Zhang ◽  
◽  
...  
Keyword(s):  
Interior Design ◽  
Hedonic Pricing ◽  
Future Research ◽  
Pricing Model ◽  
Large Dataset ◽  
Hedonic Pricing Model ◽  
High Rise ◽  
Market Values ◽  
Design Variables ◽  
Housing Attributes

How much do the market values of housing reflect its interior design? Does the interior design interact with other housing attributes? By following recent research based on the ¡§graph theory,¡¨ this paper confirms the importance of internal design variables in a hedonic pricing model, which is applied to a large dataset of high-rise apartment buildings in Asia. The evidence is consistent with a simple theory in that developers strategically use interior design to ¡§dilute¡¨ the effect of location, which leads to a form of endogenous multicollinearity. Directions for future research are also discussed.

Willingness to Pay in Hedonic Pricing Models

2021 ◽  
Author(s):  
David Wolf ◽  
H. Allen Klaiber
Keyword(s):  
Housing Price ◽  
Hedonic Pricing ◽  
Data Availability ◽  
Second Stage ◽  
Nonmarket Goods ◽  
Welfare Evaluation ◽  
Hedonic Pricing Method ◽  
Implicit Prices ◽  
Housing Attributes ◽  
Function Information

The value of a differentiated product is simply the sum of its parts. This concept is easily observed in housing markets where the price of a home is determined by the underlying bundle of attributes that define it and by the price households are willing to pay for each attribute. These prices are referred to as implicit prices because their value is indirectly revealed through the price of another product (typically a home) and are of interest as they reveal the value of goods, such as nearby public amenities, that would otherwise remain unknown. This concept was first formalized into a tractable theoretical framework by Rosen, and is known as the hedonic pricing method. The two-stage hedonic method requires the researcher to map housing attributes into housing price using an equilibrium price function. Information recovered from the first stage is then used to recover inverse demand functions for nonmarket goods in the second stage, which are required for nonmarginal welfare evaluation. Researchers have rarely implemented the second stage, however, due to limited data availability, specification concerns, and the inability to correct for simultaneity bias between price and quality. As policies increasingly seek to deliver large, nonmarginal changes in public goods, the need to estimate the hedonic second stage is becoming more poignant. Greater effort therefore needs to be made to establish a set of best practices within the second stage, many of which can be developed using methods established in the extensive first-stage literature.

scholarly journals Housing loans and domestic credit in the Baltic States and Poland: Structural breaks and macroeconomic determinants

2020 ◽  
Vol 42 ◽  
pp. 48-69
Author(s):  
Scott W. Hegerty ◽  
◽  
◽  
Keyword(s):  
Structural Breaks ◽  
Global Financial Crisis ◽  
Structural Break ◽  
Real Effective Exchange Rate ◽  
Future Research ◽  
Data Series ◽  
Price Inflation ◽  
Growth Series ◽  
Baltic Countries ◽  
The Baltic

Aim/purpose – This study examines the time-series properties of home loans and do-mestic credit in Poland and the three Baltic countries, first in the univariate sense by identifying structural breaks in the series, and then using a multivariate model to identify the key drivers of loan growth.Design/methodology/approach – Structural break tests are conducted using the method of Bai & Perron (1998), while orthgonalised VARs are used for the macroeconomic model.Findings – The Estonian and Lithuanian home lending growth series have structural breaks in 2007, preceding the onset of the 2008 Global Financial Crisis. Estonian home lending has two additional structural breaks in 2009 and 2013. Neither of the two Polish lending series has any break after the sample begins in 2009, indicating more stability in the country’s markets. In the macroeconomic model, consumer price inflation and real effective exchange-rate appreciations have the largest influence on lending and credit growth, and Poland more affected than the Baltic countries.Research implications/limitations – This study opens the door to future research be-hind the specific causes of structural breaks in these series. While there is some evidence of an ‘early warning’ before the 2008 crisis, longer data series are needed for Poland and especially in the case of Latvia.Originality/value/contribution – This study offers insight into the lending markets in an area of the world that was significantly impacted by the 2008 crisis. Understanding the behaviour and causes of lending growth will help avoid future problems.

scholarly journals Selecting a Model for Forecasting

Econometrics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 26
Author(s):  
Jennifer L. Castle ◽  
Jurgen A. Doornik ◽  
David F. Hendry
Keyword(s):  
Structural Breaks ◽  
Simulation Experiment ◽  
Structural Break ◽  
Static Model ◽  
Forecast Period ◽  
Forecast Performance ◽  
Significance Level ◽  
Forecasting Models ◽  
Theoretical Results

We investigate forecasting in models that condition on variables for which future values are unknown. We consider the role of the significance level because it guides the binary decisions whether to include or exclude variables. The analysis is extended by allowing for a structural break, either in the first forecast period or just before. Theoretical results are derived for a three-variable static model, but generalized to include dynamics and many more variables in the simulation experiment. The results show that the trade-off for selecting variables in forecasting models in a stationary world, namely that variables should be retained if their noncentralities exceed unity, still applies in settings with structural breaks. This provides support for model selection at looser than conventional settings, albeit with many additional features explaining the forecast performance, and with the caveat that retaining irrelevant variables that are subject to location shifts can worsen forecast performance.

scholarly journals The time-varying effects of oil prices on oil–gas stock returns of the fragile five countries

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Begüm Yurteri Kösedağlı ◽  
Gül Huyugüzel Kışla ◽  
A. Nazif Çatık
Keyword(s):  
Stock Returns ◽  
Positive Impact ◽  
Structural Break ◽  
Oil Prices ◽  
Time Varying ◽  
Asset Pricing Model ◽  
Daily Data ◽  
Structural Break Test ◽  
The Impact ◽  
Oil Gas

AbstractThis study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study. Moreover, the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market. The results further suggest that, except for Indonesia, oil prices have a positive impact on the sectoral returns of all markets, whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.

Absence of the weekend effect and industry-style portfolios

2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman
Keyword(s):  
New York ◽  
Stock Market ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Structural Break ◽  
Weekend Effect ◽  
Content Type ◽  
Market Portfolio ◽  
The Us ◽  
Using Data

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

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