Time-varying spillovers among first-tier housing markets in China

Urban Studies ◽  
2019 ◽  
Vol 57 (4) ◽  
pp. 844-864 ◽  
Author(s):  
Chien-Fu Chen ◽  
Shu-hen Chiang
Keyword(s):  
National Level ◽  
Housing Price ◽  
Housing Markets ◽  
Control Policy ◽  
Sufficient Evidence ◽  
Time Varying ◽  
Ripple Effects ◽  
Chinese Characteristics ◽  
Rolling Window ◽  
Window Approach

Numerous efforts have over the last few years been devoted to studying spillovers (ripple effects) among cities as a means of evaluating overheated housing markets. What seems to be lacking, however, is the application of a rolling-window approach to further explore time-varying spillovers in a timely manner in order to look more closely at a housing market with Chinese characteristics; for example, a market with rapidly increasing prices and a sequence of policy recommendations. By focusing on total, directional and net spillovers, and using 2000–2017 monthly housing price data across six Chinese cities, this study’s results indicate that time-varying spillovers provide a better understanding of the interactions among first-tier cities. It is interesting to note that, following the downside risk faced by the economy in 2014, the spillovers among cities have been abruptly transformed into those exhibiting bilateral co-movements based on high total spillovers and low net spillovers, and these results are also confirmed by the frequency dynamics of spillovers. Based on the above, there is sufficient evidence to conclude that the housing frenzies in China, which have become a national-level issue, deserve a more explicit macro-control policy in relation to real estate assets.

Optimal time-varying tail risk network with a rolling window approach

2021 ◽  
pp. 126127
Author(s):  
Xingmin Zhang ◽  
Shuai Zhang
Keyword(s):  
Optimal Time ◽  
Time Varying ◽  
Tail Risk ◽  
Rolling Window ◽  
Window Approach

Financial Integration in Asia: A Systemic View on Currency Markets

2020 ◽  
Vol 19 (2) ◽  
pp. 41-58
Author(s):  
Dayong Zhang ◽  
Wanli Zhao ◽  
Fei Wu ◽  
Qiang Ji
Keyword(s):  
Financial Integration ◽  
Time Varying ◽  
Currency Markets ◽  
Vector Autoregressive ◽  
Republic Of China ◽  
Rolling Window ◽  
Causality Tests ◽  
The Republic ◽  
Window Approach ◽  
Systemic View

Using a systemic approach, this study investigates the time-varying linkages among currency markets of Japan, the People's Republic of China, the Republic of Korea, and the five core ASEAN economies to understand financial integration in Asia. We first construct a vector autoregressive model and use the Diebold and Yilmaz ( 2014 ) approach to quantitatively identify the connectedness within the system, accompanied by a rolling-window approach to allow for time-varying dynamics and pairwise Granger causality tests to check the robustness of our main results. We find that though systemic interconnectedness varies over time, the Singapore dollar is constantly a top net contributor, explaining most of the variation in East Asian currency markets.

Time‐varying causal nexuses between economic growth and CO 2 emissions in G‐7 countries: A bootstrap rolling window approach over 1820–2015

2020 ◽  
Author(s):  
Md. Samsul Alam ◽  
Sajid Ali ◽  
Naceur Khraief ◽  
Syed Jawad Hussain Shahzad
Keyword(s):  
Economic Growth ◽  
Time Varying ◽  
Rolling Window ◽  
Window Approach

scholarly journals Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions

2018 ◽  
Vol 53 (3) ◽  
pp. 1371-1390 ◽  
Author(s):  
Marco Valerio Geraci ◽  
Jean-Yves Gnabo
Keyword(s):  
Dynamic Network ◽  
Spillover Effects ◽  
Time Varying ◽  
Vector Autoregressions ◽  
Crisis Events ◽  
Time Varying Parameter ◽  
Rolling Window ◽  
The 2008 Financial Crisis ◽  
Window Approach

We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor’s 500 index and estimate interconnectedness at the sectoral and institutional levels. At the sectoral level, we uncover two main events in terms of interconnectedness: the Long-Term Capital Management crisis and the 2008 financial crisis. After these crisis events, we find a gradual decrease in interconnectedness, not observable using the classical rolling-window approach. At the institutional level, our framework delivers more stable interconnectedness rankings than other comparable market-based measures.

Economic Institutions and Growth Nexus: The Role of Governance and Democratic Institutions—Evidence from Time Varying Parameters’ (TVPs) Models

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 675-688
Author(s):  
Ghulam Murtaza ◽  
Muhammad Zahir Faridi
Keyword(s):  
Structural Changes ◽  
Jel Classification ◽  
Economic Institutions ◽  
Time Varying ◽  
Democratic Institutions ◽  
Main Hypothesis ◽  
Dynamic Relationship ◽  
Rolling Window

The present study has investigated the channels through which the linkage between economic institutions and growth is gauged, by addressing the main hypothesis of the study that whether quality of governance and democratic institutions set a stage for economic institutions to promote the long-term growth process in Pakistan. To test the hypothesis empirically, our study models the dynamic relationship between growth and economic institutions in a time varying framework in order to capture institutional developments and structural changes occurred in the economy of Pakistan over the years. Study articulates that, along with some customary specifics, the quality of government and democracy are the substantial factors that affect institutional quality and ultimately cause to promote growth in Pakistan. JEL Classification: O40; P16; C14; H10 Keywords: Economic Institutions, Growth, Governance and Democracy, Rolling Window Two-stage Least Squares, Pakistan

scholarly journals Time-Varying Convergences of Environmental Footprint Levels between European Countries

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1813
Author(s):  
Durmuş Çağrı Yıldırım ◽  
Seda Yıldırım ◽  
Seyfettin Erdoğan ◽  
Işıl Demirtaş ◽  
Gualter Couto ◽  
...  
Keyword(s):  
Ecological Footprint ◽  
Unit Root Test ◽  
Data Availability ◽  
European Countries ◽  
Time Varying ◽  
Cross Sectional ◽  
Ecological Footprints ◽  
Window Method ◽  
International Policies ◽  
Rolling Window

This study proposes the time-varying nonlinear panel unit root test to investigate the convergence of ecological foot prints between the EU and candidate countries. Sixteen European countries (such as Albania, Austria, Belgium, Denmark, France, Germany, Greece, Italy, Luxembourg, Netherlands, Poland, Portugal, Romania, Spain, Sweden and Turkey) and analysis periods are selected according to data availability. This study proposes a cross-sectional Panel KSS with Fourier to test the convergence of the ecological footprints. Then, we combine this methodology with the rolling window method to take into account the time-varying stationarity of series. This study evaluated sub-components of ecological footprints separately and provided more comprehensive findings for the ecological footprint. According to empirical findings, this study proves that convergence or divergence does not show continuity over time. On the other side, this study points out the presence of divergence draws attention when considering the properties of the sub-components in general. As a result, this study shows that international policies by EU countries are generally accepted as successful to reduce ecological footprint, but these are not sufficient as expected. In this point, it is suggested to keep national policies to support international policies in the long term.

scholarly journals Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sahamoddin Khailaie ◽  
Tanmay Mitra ◽  
Arnab Bandyopadhyay ◽  
Marta Schips ◽  
Pietro Mascheroni ◽  
...  
Keyword(s):  
Structural Changes ◽  
Reproduction Number ◽  
National Level ◽  
Transmission Dynamics ◽  
Federal State ◽  
Parameter Estimates ◽  
Time Varying ◽  
Short Term ◽  
Robert Koch Institute ◽  
Federal States

Abstract Background SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. Methods We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. Results The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2–3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. Conclusions The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

Excess Volatility in Bitcoin: Extreme Value Volatility Estimation

2021 ◽  
pp. 227797522098768
Author(s):  
Parthajit Kayal ◽  
G. Balasubramanian
Keyword(s):  
Investment Decisions ◽  
Extreme Value ◽  
Time Varying ◽  
Price Changes ◽  
Volatility Estimation ◽  
Policy Choices ◽  
Rolling Window ◽  
Excess Volatility ◽  
High Volatility ◽  
Over Time

This article investigates the excess volatility in Bitcoin prices using an unbiased extreme value volatility estimator. We capture the time-varying nature of the excess volatility using bootstrap, multi-horizon, sub-sampling and rolling-window approaches. We observe that Bitcoin price changes are almost efficient. Although Bitcoin prices exhibit high volatility and show signs of excess volatility for a few periods, it is decreasing over time. After controlling for the outliers, we also notice that the Bitcoin market shows signs of increasing maturity. Overall, Bitcoin prices show a sign of increasing efficiency with decreasing volatility. Our findings have implications for investors making investment decisions and for regulators making policy choices.

scholarly journals EVALUATING MEASURES OF MARKET RISK IN CIRCUMSTANCES OF GLOBAL FINANCIAL CRISIS – EMPIRICAL EVIDENCE FROM FIVE COUNTRIES

2013 ◽  
Vol 1 ◽  
pp. 75-81
Author(s):  
Ivica Terzić ◽  
Marko Milojević
Keyword(s):  
Value At Risk ◽  
Global Financial Crisis ◽  
Market Risk ◽  
Var Models ◽  
Risk Models ◽  
Historical Simulation ◽  
Rolling Window ◽  
Independence Properties ◽  
Window Approach ◽  
Metrics Model

The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.

DOES THE CAUSAL RELATIONSHIP BETWEEN THE TWIN DEFICITS VARY OVER TIME? EVIDENCE FROM A BOOTSTRAP ROLLING WINDOW APPROACH

2020 ◽  
pp. 1-23
Author(s):  
TIE-YING LIU ◽  
ZI-CHEN GU
Keyword(s):  
World War Ii ◽  
Causal Relationship ◽  
Structural Breaks ◽  
Negative Impact ◽  
Positive Impact ◽  
Trade Deficit ◽  
Fiscal Deficit ◽  
Rolling Window ◽  
Oil Crisis ◽  
Window Approach

This paper uses the bootstrap rolling window approach to analyze the dynamic causal relationship between the fiscal deficit and the trade deficit in the US from 1901 to 2018. We find the origination and termination of each causality period by considering the structural breaks. The results show that the fiscal deficit had a positive impact on the trade deficit from 1946 to 1956, from 1982 to 1998, in 2000 and from 2002 to 2008, which is in accord with the results of the Mundell–Fleming model, while it had a negative impact from 1937 to 1945. The trade deficit had a positive impact on the fiscal deficit from 1940 to 1942, from 1959 to 1975 and from 1981 to 1994, mainly due to the World War II, oil crisis and trade friction with Japan. It means that the fiscal policy of American federal government can affect the external imbalance.

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