Evidence and Implications of Regime Shifts: Time-Varying Effects of the U.S. and Japanese Economies on House Prices in Hawaii

AbstractThis paper analyzes the time-varying impact of macroeconomic forces on the synchronization in housing movements across all the U.S. states. Using a Bayesian modeling approach, the house price movements are decomposed into national, regional and state-specific factors. We then analyze the time-varying impact of macroeconomic forces on these national and regional factors. Evidence suggests that in several Western and Eastern states the house price variations are dominated by the national factor, whereas the regional factor dominates the Southern and Midwestern markets. These factors are found to have a time-varying relationship with most macroeconomic indicators with particularly pronounced time-variation caused by national house prices, inflation rate and consumer sentiments.

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Has tourism driven house prices in Germany? Time-varying evidence since 1870

Tourism Economics ◽

10.1177/13548166211008832 ◽

2021 ◽

pp. 135481662110088

Author(s):

Sefa Awaworyi Churchill ◽

John Inekwe ◽

Kris Ivanovski

Keyword(s):

World War Ii ◽

Historical Data ◽

House Prices ◽

Housing Prices ◽

Time Varying ◽

Data Set ◽

Time Series Modelling ◽

The Impact ◽

Tourism Flows ◽

Non Parametric

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.

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House Prices, Home Equity-Based Borrowing, and the U.S. Household Leverage Crisis

SSRN Electronic Journal ◽

10.2139/ssrn.1397607 ◽

2010 ◽

Cited By ~ 2

Author(s):

Atif R. Mian ◽

Amir Sufi

Keyword(s):

House Prices ◽

Home Equity ◽

The U.S

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Time-varying role of macroeconomic shocks on house prices in the US and UK: evidence from over 150 years of data

Empirical Economics ◽

10.1007/s00181-018-1581-x ◽

2018 ◽

Vol 58 (5) ◽

pp. 2249-2285 ◽

Cited By ~ 2

Author(s):

Vasilios Plakandaras ◽

Rangan Gupta ◽

Constantinos Katrakilidis ◽

Mark E. Wohar

Keyword(s):

House Prices ◽

Time Varying ◽

Macroeconomic Shocks ◽

The Us

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The Time-Varying Effects of Monetary Policy on House Prices in China: An Application of TVP-VAR Model with Stochastic Volatility

International Journal of Business and Management ◽

10.5539/ijbm.v13n4p149 ◽

2018 ◽

Vol 13 (4) ◽

pp. 149 ◽

Cited By ~ 1

Author(s):

Weina Cai ◽

Sen Wang

Keyword(s):

Monetary Policy ◽

Interest Rate ◽

House Prices ◽

Var Model ◽

Time Varying ◽

Credit Channel ◽

Monetary Policy Shocks ◽

Time Varying Parameter ◽

Policy Shocks ◽

Interest Rate Channel

The boom of housing market in China in recent years has attracted great concerns from all over the world. How monetary policy affects house prices in China becomes an essential topic. This paper studies the time-varying effects of monetary policy on house prices in China during 2005.7-2017.10, by using a time-varying parameter VAR model. This paper obtains three interesting results. First, there are time-varying features of the responses of house prices to monetary policy shocks half-year and 1-year ahead, no matter through interest rate channel or through credit channel. Second, interest rate channel and credit channel have been enhanced since financial crisis in 2008. Third, the responses of nominal house prices to monetary policy in China are mainly driven by the responses of real house prices, instead of inflation. Finally, this paper gives proper suggestions for each finding respectively to central bank in China.

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Complexity In Psychological Self-Ratings: Implications for research and practice

10.31234/osf.io/fbta8 ◽

2020 ◽

Author(s):

Merlijn Olthof ◽

Fred Hasselman ◽

Anna Lichtwarck-Aschoff

Keyword(s):

Complex Systems ◽

Systems Approach ◽

Complex Dynamics ◽

Initial Conditions ◽

Regime Shifts ◽

Fundamental Aspect ◽

Time Varying ◽

Term Prediction ◽

Sensitive Dependence

Background: Psychopathology research is changing focus from group-based ‘disease models’ to a personalized approach inspired by complex systems theories. This approach, which has already produced novel and valuable insights into the complex nature of psychopathology, often relies on repeated self-ratings of individual patients. So far it has been unknown whether such self-ratings, the presumed observables of the individual patient as a complex system, actually display complex dynamics. We examine this basic assumption of a complex systems approach to psychopathology by testing repeated self-ratings for three markers of complexity: memory, the presence of (time-varying) short- and long-range temporal correlations, regime shifts, transitions between different dynamic regimes, and, sensitive dependence on initial conditions, also known as the ‘butterfly effect’, the divergence of initially similar trajectories.Methods: We analysed repeated self-ratings (1476 time points) from a single patient for the three markers of complexity using Bartels rank test, (partial) autocorrelation functions, time-varying autoregression, a non-stationarity test, change point analysis and the Sugihara-May algorithm.Results: Self-ratings concerning psychological states (e.g., the item ‘I feel down’) exhibited all complexity markers: time-varying short- and long-term memory, multiple regime shifts and sensitive dependence on initial conditions. Unexpectedly, self-ratings concerning physical sensations (e.g., the item ‘I am hungry’) exhibited less complex dynamics and their behaviour was more similar to random variables. Conclusions: Psychological self-ratings display complex dynamics. The presence of complexity in repeated self-ratings means that we have to acknowledge that (1) repeated self-ratings yield a complex pattern of data and not a set of (nearly) independent data points, (2) humans are ‘moving targets’ whose self-ratings display non-stationary change processes including regime shifts, and (3) long-term prediction of individual trajectories may be fundamentally impossible. These findings point to a limitation of popular statistical time series models whose assumptions are violated by the presence of these complexity markers. We conclude that a complex systems approach to mental health should appreciate complexity as a fundamental aspect of psychopathology research by adopting the models and methods of complexity science. Promising first steps in this direction, such as research on real-time process-monitoring, short-term prediction, and just-in-time interventions, are discussed.

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MO050GLYCEMIC CONTROL AND THE RISK OF AKI IN PATIENTS WITH DIABETES AND CKD: PARALLEL POPULATION-BASED COHORT STUDIES IN U.S. AND SWEDEN ROUTINE CARE

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa140.mo050 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Yang Xu ◽

Aditya Surapaneni ◽

Jim Alkas ◽

Alexander Chang ◽

Morgan Grams ◽

...

Keyword(s):

Glycemic Control ◽

Cohort Studies ◽

Proportional Hazards ◽

Cox Proportional Hazards ◽

Sensitivity Analyses ◽

Time Varying ◽

Baseline Hba1c ◽

Patients With Diabetes ◽

Swedish Cohort ◽

The U.S

Abstract Background and Aims Patients with diabetes and chronic kidney disease (CKD) have increased susceptibility to acute kidney injury (AKI), but the underlying mechanisms are not well known. We here explore the association between glycemic control and risk of AKI. Method We created two parallel observational cohort studies of Swedish (SCREAM project, Stockholm, 2006-2011) and U.S. (Geisinger Heath system, Pennsylvania, 1996-2018) adult patients with diabetes mellitus and confirmed CKD stages G3-G5. Glycemic control was evaluated through repeated HbA1c measurements, which were categorized into 5 levels of glycemic control intensity, with HbA1c 6-6.9% as referent category, and continuously using cubic splines. We evaluated the association between baseline and time-varying HbA1c levels with AKI (defined as increase in creatinine >=0.3 mg/d over 48 hours or 1.5x creatinine over 7 days) using Cox proportional hazards regression and, in sensitivity analyses, Fine and Gray competing risk models accounting for death. Results In the Swedish cohort, there were 13932 patients with median age 76 years, 51% women, median eGFR 50.8 (Interquartile Range (IQR) 41.4-57.1) ml/min/1.73. In the U.S. cohort, there were 26520 patients with median age 71 years, 55% women and 52.1 (IQR 43.4-57.5) ml/min/1.73 m2. During a median of 2.3 and 3.1 years of follow up, 3172 and 8671 AKI events were recorded in the Swedish and US cohorts, respectively. The adjusted association between baseline HbA1c and AKI was similar in both cohorts, with the lowest risk between 6-6.9% and higher risk at higher levels of HbA1c. Compared to baseline HbA1c 6-6.9%, baseline HbA1c>9% associated with a 1.28 fold (95% CI 1.11-1.47) higher risk of AKI in the Swedish cohort, and a 1.14 (95% CI 1.04-1.25) higher risk in the U.S. cohort. Conversely, baseline HbA1c<6% did not associate with AKI. When using time-varying HbA1c, AKI risk was higher for HbA1c>9% (HR 1.18, 95% CI 1.03-1.37 in Swedish cohort and 1.27, 1.17-1.37 in U.S. cohort); AKI risk was also higher for HbA1c<6% in the U.S. cohort (1.12, 1.04-1.19), but not in the Swedish cohort (1.06, 0.97-1.16)). Conclusion Higher A1c was associated with AKI in adults with diabetes and CKD, suggesting that better glycemic control may also reduce risk of AKI.

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The Time-Varying Effect of Monetary Policy on Asset Prices

Review of Economics and Statistics ◽

10.1162/rest_a_00840 ◽

2020 ◽

Vol 102 (4) ◽

pp. 690-704 ◽

Cited By ~ 8

Author(s):

Pascal Paul

Keyword(s):

Monetary Policy ◽

Asset Prices ◽

House Prices ◽

The United States ◽

Model Parameters ◽

Time Varying ◽

Real Economy ◽

Monetary Policy Shocks ◽

Vector Autoregressive ◽

Policy Shocks

This paper studies how monetary policy jointly affects asset prices and the real economy in the United States. I develop an estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks. This is achieved by integrating the surprises into a vector autoregressive model as an exogenous variable. I use current short-term rate surprises because these are least affected by an information effect. When allowing for time-varying model parameters, I find that compared to the response of output, the reaction of stock and house prices to monetary policy shocks was particularly low before the 2007–2009 financial crisis.

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