What drives metropolitan house prices in Bork/Mller California? - - PowerPoint PPT Presentation
CA house prices What drives metropolitan house prices in Bork/Mller California? Motivation Research question Takeaway Overview Model Lasse Bork, Aalborg University Empirical results: Overview Stig V. Mller, Aarhus University &
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Updated paper to appear on my webpage and SSRN
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Many potential determinants of regional house prices:
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Many potential determinants of regional house prices:
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Many potential determinants of regional house prices:
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Many potential determinants of regional house prices:
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Many potential determinants of regional house prices:
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
1990 1995 2000 2005 2010 2015 100 150 200 250 300 350 400 450 US house price index (1986:III = 100) Californian house price index (1986:III = 100)
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Visalia−Porterville Merced San Luis Obispo−Paso Robles−Arroyo Grande Santa Rosa San Rafael Eureka−Arcata−Fortuna Crescent City, CA MiSA Oakland−Hayward−Berkeley Sacramento−−Roseville−−Arden−Arcade Yuba City Hanford−Corcoran Susanville Clearlake Red Bluff San Francisco−Redwood City−South San Francisco Madera SRAA Santa Maria−Santa Barbara Vallejo−Fairfield Oxnard−Thousand Oaks−Ventura Santa Cruz−Watsonville YC Sonora Napa SRAA San Jose−Sunnyvale−Santa Clara Salinas San Diego−Carlsbad Truckee−Grass Valley Ukiah SRAA El Centro Modesto Bakersfield OHB Fresno SJSSC SFRCSSF Chico Stockton−Lodi Redding Riverside−San Bernardino−Ontario Los Angeles−Long Beach−Glendale Anaheim−Santa Ana−Irvine RSBO
−20.00 −16.00 Low −12.00 −8.00 −4.00 0.00 4.00 8.00 12.00 16.00 High 20.00
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Visalia−Porterville Merced San Luis Obispo−Paso Robles−Arroyo Grande Santa Rosa San Rafael Eureka−Arcata−Fortuna Crescent City, CA MiSA Oakland−Hayward−Berkeley Sacramento−−Roseville−−Arden−Arcade Yuba City Hanford−Corcoran Susanville Clearlake Red Bluff San Francisco−Redwood City−South San Francisco Madera SRAA Santa Maria−Santa Barbara Vallejo−Fairfield Oxnard−Thousand Oaks−Ventura Santa Cruz−Watsonville YC Sonora Napa SRAA San Jose−Sunnyvale−Santa Clara Salinas San Diego−Carlsbad Truckee−Grass Valley Ukiah SRAA El Centro Modesto Bakersfield OHB Fresno SJSSC SFRCSSF Chico Stockton−Lodi Redding Riverside−San Bernardino−Ontario Los Angeles−Long Beach−Glendale Anaheim−Santa Ana−Irvine RSBO
−20.00 −16.00 Low −12.00 −8.00 −4.00 0.00 4.00 8.00 12.00 16.00 High 20.00
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Is there a homogeneous or very heterogeneous response
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
What is the role of standard aggregate shocks in
Is the loose monetary policy the recent decade to be
Structural dynamic factor model that involves a very
US aggregate economic and financial variables Californian economic variables and metro house prices The almost 400 time series are driven by a number of
We identify aggregate shocks (AS, AD, Credit, mon.
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Historical decomposition of SanFranciscoRedwoodCitySouthSanFranciscoCA (black) into shocks. Jun-86 Jun-88 Jun-90 Jun-92 Jun-94 Jun-96 Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10 Jun-12 Jun-14 Jun-16
0.05 0.1 Quarterly nominal growth rate MP RD RS RHD RHS AD AS CS undef.( 9) undef.(10) data
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Response of regional house prices to structural shocks Historical decomposition of house prices the identified
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
RHS: We also consider a regional housing supply shock,
RHD: We also consider a regional housing demand
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
++
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
++
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Fed Funds
12 24 36
0.05 0.1
CPI-U housing
12 24 36
0.2 0.4
Emp: total priv
12 24 36
0.5 1
U: all
12 24 36
0.05 0.1
C and I loans comm bank
12 24 36
0.2 0.4
M1
12 24 36
0.5
NAPM new ordrs
12 24 36
0.1
Starts: nonfarm
12 24 36
0.05
NAPM com price
12 24 36
0.1
Pers Cons Exp total Qnt
12 24 36
0.5 1
Consumer expect
12 24 36
0.1 0.2
Spread MBS
12 24 36
0.05
Reserves tot
12 24 36
0.2
CPI-U: All items, LA/R/O
12 24 36
0.2
12 24 36
0.5
12 24 36
0.05 0.1
12 24 36
0.5 1
Emp: construction
12 24 36
0.5 1
Building Permits CA total
12 24 36
0.05
Consumer conf Pac
12 24 36
0.05 0.1
LosAngelesLongBeachGlendaleCA
12 24 36
0.5 1
OaklandHaywardBerkeleyCA
12 24 36
0.5 1
SanDiegoCarlsbadCA
12 24 36
0.5 1
SanFranciscoRedwoodCitySouthSanFranciscoCA
12 24 36
0.5 1
RiversideSanBernardinoOntarioCA
12 24 36
0.5 1
MS72172Sign4ACCandRSR RHD CS 2MP r10 p2|----> California
Remark: The dotted line is the single model closest to the median; cf. Fry and Pagan (2011).
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Fed Funds
12 24 36
0.1
CPI-U housing
12 24 36
0.5
Emp: total priv
12 24 36
0.5
U: all
12 24 36
0.1 0.2
C and I loans comm bank
12 24 36
0.5
M1
12 24 36 1 2 3 4
NAPM new ordrs
12 24 36
0.2
Starts: nonfarm
12 24 36
0.1 0.2
NAPM com price
12 24 36
0.1 0.2
Pers Cons Exp total Qnt
12 24 36
0.5
Consumer expect
12 24 36
0.1
Spread MBS
12 24 36
0.1 0.2
Reserves tot
12 24 36
0.5 1 1.5
CPI-U: All items, LA/R/O
12 24 36
0.5
12 24 36
12 24 36
0.1 0.2
12 24 36
0.5
Emp: construction
12 24 36
0.5
Building Permits CA total
12 24 36
0.1
Consumer conf Pac
12 24 36
0.1
LosAngelesLongBeachGlendaleCA
12 24 36
0.5
OaklandHaywardBerkeleyCA
12 24 36
0.5
SanDiegoCarlsbadCA
12 24 36
0.5
SanFranciscoRedwoodCitySouthSanFranciscoCA
12 24 36
0.5
RiversideSanBernardinoOntarioCA
12 24 36
0.5
MS72172Sign4ACCandRSR RHD CS 2CS r10 p2|----> California
Remark: The dotted line is the single model closest to the median; cf. Fry and Pagan (2011).
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
12 24 36
0.05 0.1
12 24 36
0.05 0.1
12 24 36
0.1
12 24 36
0.1
12 24 36
0.05
12 24 36
0.5 1 1.5
12 24 36
0.5 1
12 24 36
0.5 1 1.5
Empl NP in Riv/SB/Ont
12 24 36
1 2 3
Empl NP in Stockton
12 24 36
0.5 1 1.5
Building Permits CA total
12 24 36
0.1 0.2
New permits SF/O/F
12 24 36
0.05 0.1 0.15
Housing starts : 1-U for LA/LB/SanA
12 24 36
0.05 0.1 0.15
Housing starts : 1-U for Riv/SB/O
12 24 36
0.05 0.1 0.15
New permits Sacr/A/A/R,
12 24 36
0.05 0.1 0.15
CPI: All, CA
12 24 36 0.5 1 1.5
CPI-U: All items, SF/O/SJ
12 24 36
0.5 1
CPI-U: All items, LA/R/O
12 24 36 0.5 1 1.5
CPI-U: Non-dbles, LA/R/O
12 24 36
0.2 0.4 0.6
CPI-U: All items, San Diego
12 24 36 0.5 1 1.5 2
LosAngelesLongBeachGlendaleCA
12 24 36
2 4 6
SanFranciscoRedwoodCitySouthSanFranciscoCA
12 24 36
1 2 3
LosAngelesLongBeachGlendaleCA
12 24 36
2 4 6
FresnoCA
12 24 36
2 4
ReddingCA
12 24 36
2 4
MS72172Sign4ACCandRSR RHD CS 2RD r10 p2Remark: The dotted line is the single model closest to the median;cf. Fry and Pagan (2011).
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
12 24 36
0.05
12 24 36
0.05
12 24 36
0.05
12 24 36
0.1
12 24 36
0.1
12 24 36
0.5 1 1.5
12 24 36
0.5 1
12 24 36
0.5 1 1.5
Empl NP in Riv/SB/Ont
12 24 36
1 2 3
Empl NP in Stockton
12 24 36
0.5 1 1.5
Building Permits CA total
12 24 36
0.1 0.2
New permits SF/O/F
12 24 36
0.05 0.1
Housing starts : 1-U for LA/LB/SanA
12 24 36
0.1 0.2
Housing starts : 1-U for Riv/SB/O
12 24 36
0.1 0.2
New permits Sacr/A/A/R,
12 24 36
0.05 0.1 0.15
CPI: All, CA
12 24 36
0.5 1
CPI-U: All items, SF/O/SJ
12 24 36
0.5 1
CPI-U: All items, LA/R/O
12 24 36
0.5 1
CPI-U: Non-dbles, LA/R/O
12 24 36
0.2 0.4
CPI-U: All items, San Diego
12 24 36
0.5 1 1.5
LosAngelesLongBeachGlendaleCA
12 24 36 2 4 6
SanFranciscoRedwoodCitySouthSanFranciscoCA
12 24 36
1 2 3
LosAngelesLongBeachGlendaleCA
12 24 36 2 4 6
FresnoCA
12 24 36 2 4 6
ReddingCA
12 24 36 2 4 6
MS72172Sign4ACCandRSR RHD CS 2RHD r10 p2Remark: Here the dotted line is the single model closest to the median; cf. Fry and Pagan (2011).
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Historical decomposition of SanFranciscoRedwoodCitySouthSanFranciscoCA (black) into shocks. Jun-86 Jun-88 Jun-90 Jun-92 Jun-94 Jun-96 Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10 Jun-12 Jun-14 Jun-16
0.05 0.1 Quarterly nominal growth rate MP RD RS RHD RHS AD AS CS undef.( 9) undef.(10) data
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Historical decomposition of StocktonLodiCA (black) into shocks. Jun-86 Jun-88 Jun-90 Jun-92 Jun-94 Jun-96 Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10 Jun-12 Jun-14 Jun-16
0.05 0.1 Quarterly nominal growth rate MP RD RS RHD RHS AD AS CS undef.( 9) undef.(10) data
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
Historical decomposition of Nonfarm payr. CA (black) into shocks. Jun-86 Jun-88 Jun-90 Jun-92 Jun-94 Jun-96 Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10 Jun-12 Jun-14 Jun-16
0.005 0.01 0.015 Quarterly growth rate MP RD RS RHD RHS AD AS CS undef.( 9) undef.(10) data
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion
CA house prices Bork/Møller Motivation Research question Takeaway Overview Model Empirical results: Overview
IRF Historical decomposition
Conclusion