What drives metropolitan house prices in California? Lasse Bork, Aalborg University Stig V. Møller, Aarhus University & CREATES. Housing, household debt and policy conference 27, RBNZ Updated paper to appear on my webpage and SSRN
in general Are regional house prices primarily driven by regional economic conditions? Or, are there significant spillover effects from the aggregate economy to the regional house prices? In general, we are interested in getting a better understanding of the links between regional house prices and the aggregate-regional economy The challenge in addressing these research questions: Many potential determinants of regional house prices: income, various (un)employment measures, short-term and long-term interest rates, credit, building permits, houses sold relative to houses for sale, consumer sentiment, housing sentiment, etc, etc In this paper we try to uncover - using a large dimensional dynamic factor model - the main structural drivers (shocks) behind a particular regional housing market (California).
in general Are regional house prices primarily driven by regional economic conditions? Or, are there significant spillover effects from the aggregate economy to the regional house prices? In general, we are interested in getting a better understanding of the links between regional house prices and the aggregate-regional economy The challenge in addressing these research questions: Many potential determinants of regional house prices: income, various (un)employment measures, short-term and long-term interest rates, credit, building permits, houses sold relative to houses for sale, consumer sentiment, housing sentiment, etc, etc In this paper we try to uncover - using a large dimensional dynamic factor model - the main structural drivers (shocks) behind a particular regional housing market (California).
in general Are regional house prices primarily driven by regional economic conditions? Or, are there significant spillover effects from the aggregate economy to the regional house prices? In general, we are interested in getting a better understanding of the links between regional house prices and the aggregate-regional economy The challenge in addressing these research questions: Many potential determinants of regional house prices: income, various (un)employment measures, short-term and long-term interest rates, credit, building permits, houses sold relative to houses for sale, consumer sentiment, housing sentiment, etc, etc In this paper we try to uncover - using a large dimensional dynamic factor model - the main structural drivers (shocks) behind a particular regional housing market (California).
in general Are regional house prices primarily driven by regional economic conditions? Or, are there significant spillover effects from the aggregate economy to the regional house prices? In general, we are interested in getting a better understanding of the links between regional house prices and the aggregate-regional economy The challenge in addressing these research questions: Many potential determinants of regional house prices: income, various (un)employment measures, short-term and long-term interest rates, credit, building permits, houses sold relative to houses for sale, consumer sentiment, housing sentiment, etc, etc In this paper we try to uncover - using a large dimensional dynamic factor model - the main structural drivers (shocks) behind a particular regional housing market (California).
in general Are regional house prices primarily driven by regional economic conditions? Or, are there significant spillover effects from the aggregate economy to the regional house prices? In general, we are interested in getting a better understanding of the links between regional house prices and the aggregate-regional economy The challenge in addressing these research questions: Many potential determinants of regional house prices: income, various (un)employment measures, short-term and long-term interest rates, credit, building permits, houses sold relative to houses for sale, consumer sentiment, housing sentiment, etc, etc In this paper we try to uncover - using a large dimensional dynamic factor model - the main structural drivers (shocks) behind a particular regional housing market (California).
: Regional differences in house prices in 6 graphs 45 4 35 3 25 US house price index (986:III = ) Californian house price index (986:III = ) 2 5 99 995 2 25 2 25
: Regional differences in house prices in 6 graphs Mean growth rate in house prices: 986Q3-26Q3. Nominal. Annualized.
: Regional differences in house prices in 6 graphs Boom: Mean growth rate in house prices: 2Q-26Q2. Nominal. Annualized.
: Regional differences in house prices in 6 graphs Bust: Mean growth rate in house prices: 26Q3-29Q3. Nominal. Annualized.
: Regional differences in house prices in 6 graphs 2. Crescent City, CA MiSA Eureka Arcata Fortuna Redding Susanville Red Bluff Chico Ukiah Truckee Grass YC Valley Clearlake Yuba City SRAA Sacramento Roseville Arden Arcade SRAA Santa Rosa Napa SRAA Vallejo Fairfield San Rafael Sonora OHB Stockton Lodi San Francisco Redwood City South San Francisco Oakland Hayward Berkeley Modesto SFRCSSF SJSSC Merced Madera Santa Cruz Watsonville Fresno San Jose Sunnyvale Santa Clara 6. High 2. 8. 4.. Salinas Hanford Corcoran Visalia Porterville 4. San Luis Obispo Paso Robles Arroyo Grande Bakersfield RSBO 8. Santa Maria Santa Barbara Oxnard Thousand Oaks Ventura Los Angeles Long Beach Glendale Riverside San Bernardino Ontario Anaheim Santa Ana Irvine 2. San Diego Carlsbad El Centro 6. Low 2.
: Regional differences in house prices in 6 graphs 2. Crescent City, CA MiSA Eureka Arcata Fortuna Redding Susanville Red Bluff Chico Ukiah Truckee Grass YC Valley Clearlake Yuba City SRAA Sacramento Roseville Arden Arcade SRAA Santa Rosa Napa SRAA Vallejo Fairfield San Rafael Sonora OHB Stockton Lodi San Francisco Redwood City South San Francisco Oakland Hayward Berkeley Modesto SFRCSSF SJSSC Merced Madera Santa Cruz Watsonville Fresno San Jose Sunnyvale Santa Clara 6. High 2. 8. 4.. Salinas Hanford Corcoran Visalia Porterville 4. San Luis Obispo Paso Robles Arroyo Grande Bakersfield RSBO 8. Santa Maria Santa Barbara Oxnard Thousand Oaks Ventura Los Angeles Long Beach Glendale Riverside San Bernardino Ontario Anaheim Santa Ana Irvine 2. San Diego Carlsbad El Centro 6. Low 2.
- structural shocks We seek a structural understanding of the links between the US macroeconomy and the Californian housing market Monetary policy: What is the scope for accommodating developments in the housing markets by monetary policy (if desired)? Is there a homogeneous or very heterogeneous response of house price across regions (metropolitan areas)? Del Negro/Otrok (JME 27) find that house prices are determined primarily by local latent house price factors Aggregate shocks & regional house prices: The role played by aggregate and regional demand/supply shocks Credit shocks? Spillover effects form house prices (collateral channel effects) on regional activity: Real estate is a major part of the collateral value of households and firms and is important for the transmission mechanism, cf. Iacoviello (AER 25). What is the empirical role of this channel?
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
s : What are the aggregate and regional structural sources of the variation in regional house prices, in particular in Californian metro level house prices? What is the role of standard aggregate shocks in explaining the variation of regional (Californian) housing prices? And what is the role of regional shocks? Is the loose monetary policy the recent decade to be blamed for the boom and bust of housing prices? Our Approach: Structural dynamic factor model that involves a very large set of US aggregate economic and financial variables Californian economic variables and metro house prices The almost 4 time series are driven by a number of economically motivated aggregate factors, regional factors, and and regional house price factors. We identify aggregate shocks (AS, AD, Credit, mon. pol.) and regional shocks.
Main takeaway Credit shocks and regional shocks are the most important drivers of house prices in California - monetary policy shocks and AD/AS shocks play a minor role.. of SanFranciscoRedwoodCitySouthSanFranciscoCA (black) into shocks. Quarterly nominal growth rate.5 -.5 -. MP RD RS RHD RHS AD AS CS undef.( 9) undef.() data Jun-86 Jun-88 Jun-9 Jun-92 Jun-94 Jun-96 Jun-98 Jun- Jun-2 Jun-4 Jun-6 Jun-8 Jun- Jun-2 Jun-4 Jun-6
of the remaining presentation : Structural dynamic factor model with aggregate and regional factors Quarterly data: 986:III - 26:III. 223 US macroeconomic and financial time series. 38 Californian economic series and 29 house price series from metropolitan areas in California. Results: Response of regional house prices to structural shocks of house prices the identified shocks Possible extensions
Dynamic factor model (DFM) - outline Consider a general dynamic factor model (DF) X t = λ f t +... + λ s f t s + ξ t f t = φ f t +... + φ h f t p + u t () that can be written as in a first-order state space representation: X t = ΛF t + ξ t F t = ΦF t + U t (2) where X t is N, Λ = [λ,..., λ p ] is a N qp loading [ matrix, F t = ft,..., ft p+] is a qp vector of dynamic factors and their lags, ξ t is a N vector with the idiosyncratic error terms, Φ is qp qp matrix with autoregressive parameters, and the reduced form VAR [ residuals reside in U t = ut, q(p ) ].
DFM: identifying the factors Partition the observed data, X t, into: (Z t, i t ) : US aggregate observed time series, C t : regional (Californian) economic variables H t : Californian metro-level house prices Define aggregate ( dynamic factors ) and regional dynamic factors, i.e. f t = vec ft Z, ft C, fh,t H, i t Z t C t H t i t f Z t f C t f H t i t = λ ZZ λ Zi λ CZ λ CC λ CH λ Ci λ HZ λ HC λ HH λ Hi = Φ (L) f Z t f C t f H t i t + u Z t u C t u H t u i t f Z t f C t f H t i t + ξ Z t ξ C t ξ H t (3) (4) In the end( we work with: ) f t = vec fπ,t Z, f y Z,t, f y Z 2,t, f bp,t Z, f π,t C, f y C,t, f y C 2,t, f bp,t C, f t H, i t
Structural dynamic factor model (SDFM) Recall the arguments from the motivating section of this presentation, that the structural shocks are AS: Aggregate supply shock, ε AS AD: Aggregate demand shock, ε AD AC: Aggretate credit shock, ε AC MP: Monetary policy shock, ε MP. Zero lower bound shadow rate. RS: Regional supply shock, ε RS RHS: We also consider a regional housing supply shock, ε RHS RD: Regional demand shock, ε RD RHD: We also consider a regional housing demand shock, ε RHD The shocks are identified from the reduced form VAR residuals u t using a combination of zero and sign restrictions. See next slide.
Structural identification by zero and sign restrictions () Based on the work by Binning (23) and Arias, Rubio-Ramirez & Waggoner (24). Central to their work is the correct conditioning on the zero restrictions before drawing sign restrictions. Crucial for the intended identification is the requirement that each identified shock is associated with a unique sign pattern. Shocks MP AS AD AC RS RD Response at horizon j =...J Aggregate inflation Z π + Aggregate output Z y + + Money aggregate Z m + HY spread Z s + + Defaults Z δ ++ Regional (CA) inflation C π ++ Regional (CA) output C y ++ ++ Federal funds rate i t + +
Structural identification by zero and sign restrictions (2) Are there significant shocks originating in the regional housing market? Consider regional housing demand shocks (RHD) and supply shocks (RHS) Shocks MP AS AD AC RS RD Empirical RHS results: RHD Response at horizon j =...J Aggregate inflation Z π + Aggregate output Money aggregate Z y Z m + + + HY spread Z s + + Defaults Z δ ++ Regional (CA) inflation C π ++ Regional (CA) output C y ++ ++ Construction employment (CA) C e + + Building permits (CA) C bp + + House prices (CA) C h + Federal funds rate i t + + AC: the (impulse) responses in corp. spread over and above the response in expected defaults
of empirical results Impulse response analysis:. Monetary policy shock: Response of US and CA key variables to a monetary policy shock 2. Credit shock: Response of US and CA key variables to a credit shock 3. Regional demand shock: Response of CA key variables to a regional demand shock 4. Regional housing demand shock: Response of CA key variables to a regional housing demand shock structural of selected variables:. House prices for San Francisco metropolitan area 2. House prices for Stockton metropolian area 3. Californian non-farm payrolls
MS7272Sign4ACCandRSR RHD CS 2MP r p2 ): monetary policy shock Fed Funds CPI-U housing Emp: total priv U: all..4..2.5.5.5 -.2 -.5 -.4 -.5 -.5 2 24 36 2 24 36 2 24 36 2 24 36 M NAPM new ordrs Starts: nonfarm NAPM com price.5..5. -. -.5 -. -.5 -.2 - -.2 -. -.3 2 24 36 2 24 36 2 24 36 2 24 36 ----> California Consumer expect Spread MBS Reserves tot CPI-U: All items, LA/R/O.2.5.2.2 C and I loans comm bank.4.2 -.2 -.4 2 24 36 Pers Cons Exp total Qnt.5 -.5 2 24 36 Empl. CA.5. -. 2 24 36 Unem. rate, CA. -.5 2 24 36 Empl. SJ/SF/Oak -.2 -.4 2 24 36 Emp: construction -.2 -.4 -.6 2 24 36 Building Permits CA total.5 -.5 2 24 36 Consumer conf Pac..5.5.5 -.5.5 -.5 -.5 2 24 36 -.5 2 24 36 -.5 2 24 36 -. 2 24 36 -. 2 24 36 LosAngelesLongBeachGlendaleCA OaklandHaywardBerkeleyCA SanDiegoCarlsbadCA SanFranciscoRedwoodCitySouthSanFranciscoCA RiversideSanBernardinoOntarioCA.5.5.5.5.5 -.5 -.5 -.5 -.5 -.5-2 24 36-2 24 36-2 24 36-2 24 36-2 24 36 Remark: The dotted line is the single model closest to the median; cf. Fry and Pagan (2). Federal funds rate replaced by the Wu/Xia shadow rate. Aggregate responses broadly as expected. No significant effect on house prices.
MS7272Sign4ACCandRSR RHD CS 2CS r p2 2) : credit shock Fed Funds CPI-U housing..5.5 Emp: total priv.2 U: all.5 C and I loans comm bank. -. -.5 -.5 -.5 -.2 2 24 36 M 4-2 24 36 NAPM new ordrs.2-2 24 36 Starts: nonfarm.2 -. 2 24 36 NAPM com price.2-2 24 36 Pers Cons Exp total Qnt.5 3 2 2 24 36 Consumer expect. -.2 -.4 2 24 36 Spread MBS.2. -. -.2 2 24 36 Reserves tot.5. -. -.2 2 24 36 ----> California CPI-U: All items, LA/R/O.5 -.5-2 24 36 Empl. CA -. -.2 -.3 2 24 36 Unem. rate, CA.2. -. 2 24 36 Empl. SJ/SF/Oak.5.5 -.5 2 24 36 Emp: construction.5 -.5-2 24 36 Building Permits CA total. -.2 -.4 -.6 -.8 2 24 36 Consumer conf Pac.. -.5 -.5 -. -. -. 2 24 36-2 24 36-2 24 36 -.2 2 24 36 -.2 2 24 36.5 LosAngelesLongBeachGlendaleCA.5 OaklandHaywardBerkeleyCA.5 SanDiegoCarlsbadCA SanFranciscoRedwoodCitySouthSanFranciscoCA.5.5 RiversideSanBernardinoOntarioCA -.5 -.5 -.5 -.5 -.5-2 24 36-2 24 36-2 24 36-2 24 36-2 24 36 Remark: The dotted line is the single model closest to the median; cf. Fry and Pagan (2). Credit shock is defined similarly to Meeks (JEDC 22) Adverse credit shock has important negative effects on the real economy and house prices
MS7272Sign4ACCandRSR RHD CS 2RD r p2 2) : Regional demand shock Unem. rate, CA Unem. rate, SanJ//SF/Oak Unem. rate, LA/LB/Riv Unem. rate, Fresno/Md.....5.5 -. -. -.5 -.5 -. -. -.2 -.2 2 24 36 2 24 36 2 24 36 2 24 36 Empl. CA Empl. SJ/SF/Oak Empl. LA/LB Empl NP in Riv/SB/Ont.5.5 3.5 2.5.5 -.5 -.5 - -.5-2 24 36 2 24 36 2 24 36 2 24 36 Building Permits CA total New permits SF/O/F Housing starts : -U for LA/LB/SanA Housing starts : -U for Riv/SB/O.2.5.5.5 Unemp. rate - Yuba City.5 -.5 -. -.5 2 24 36 Empl NP in Stockton.5.5 -.5 2 24 36 New permits Sacr/A/A/R,.5. -. 2 24 36 CPI: All, CA.5..5 -.5 2 24 36 CPI-U: All items, SF/O/SJ..5 -.5 2 24 36 CPI-U: All items, LA/R/O.5..5 -.5 2 24 36 CPI-U: Non-dbles, LA/R/O.6..5 -.5 2 24 36 CPI-U: All items, San Diego 2.5.5.5.4.2.5.5 2 24 36 -.5 2 24 36 2 24 36 -.2 2 24 36 2 24 36 6 LosAngelesLongBeachGlendaleCA SanFranciscoRedwoodCitySouthSanFranciscoCA 3 6 LosAngelesLongBeachGlendaleCA 4 FresnoCA 4 ReddingCA 4 2 4 2 2 2 2-2 2 24 36-2 24 36-2 2 24 36-2 2 24 36-2 2 24 36 Remark: The dotted line is the single model closest to the median;cf. Fry and Pagan (2). A favourable regional demand shock, house prices, (un)employment improves In contrast, the effect on regional variables from an
MS7272Sign4ACCandRSR RHD CS 2RHD r p2 4) : regional housing demand shock Unem. rate, CA Unem. rate, SanJ//SF/Oak Unem. rate, LA/LB/Riv Unem. rate, Fresno/Md.5.5.5.. Unemp. rate - Yuba City -.5 -. -.5 -. -.5 -. -. -. -.5 2 24 36 Empl. CA.5 -.5 2 24 36 Empl. SJ/SF/Oak.5 -.5 2 24 36 Empl. LA/LB.5 -.2 2 24 36 Empl NP in Riv/SB/Ont 3 2 -.2 2 24 36 Empl NP in Stockton.5.5 -.5.5.5 -.5 2 24 36 Building Permits CA total.2. -. 2 24 36 CPI: All, CA - 2 24 36 New permits SF/O/F..5 -.5 -. 2 24 36 CPI-U: All items, SF/O/SJ -.5 2 24 36 Housing starts : -U for LA/LB/SanA.2. -. 2 24 36 CPI-U: All items, LA/R/O - 2 24 36 Housing starts : -U for Riv/SB/O.2. -. 2 24 36 CPI-U: Non-dbles, LA/R/O.4 -.5 2 24 36 New permits Sacr/A/A/R,.5..5 -.5 2 24 36 CPI-U: All items, San Diego.5.5.5.5.2.5 -.2 -.5 2 24 36 -.5 2 24 36 -.5 2 24 36 -.4 2 24 36 -.5 2 24 36 6 LosAngelesLongBeachGlendaleCA SanFranciscoRedwoodCitySouthSanFranciscoCA 3 6 LosAngelesLongBeachGlendaleCA 6 FresnoCA 6 ReddingCA 4 2 4 4 4 2 2 2 2 2 24 36-2 24 36 2 24 36 2 24 36 2 24 36 Remark: Here the dotted line is the single model closest to the median; cf. Fry and Pagan (2). A favourable regional housing demand shock, (un)employment improves.
) HD: House prices in San Francisco area. of SanFranciscoRedwoodCitySouthSanFranciscoCA (black) into shocks. Quarterly nominal growth rate.5 -.5 -. MP RD RS RHD RHS AD AS CS undef.( 9) undef.() data Jun-86 Jun-88 Jun-9 Jun-92 Jun-94 Jun-96 Jun-98 Jun- Jun-2 Jun-4 Jun-6 Jun-8 Jun- Jun-2 Jun-4 Jun-6
2) HD: House prices in Stockton area. of StocktonLodiCA (black) into shocks. Quarterly nominal growth rate.5 -.5 -. MP RD RS RHD RHS AD AS CS undef.( 9) undef.() data Jun-86 Jun-88 Jun-9 Jun-92 Jun-94 Jun-96 Jun-98 Jun- Jun-2 Jun-4 Jun-6 Jun-8 Jun- Jun-2 Jun-4 Jun-6
2) HD: Nonfarm payrolls in CA Quarterly growth rate of Nonfarm payr. CA (black) into shocks..5..5 -.5 -. -.5 -.2 -.25 MP RD RS RHD RHS AD AS CS undef.( 9) undef.() data Jun-86 Jun-88 Jun-9 Jun-92 Jun-94 Jun-96 Jun-98 Jun- Jun-2 Jun-4 Jun-6 Jun-8 Jun- Jun-2 Jun-4 Jun-6
Work in progress Split the house price factor into ) coastal house price factor and 2) interior house price factor. This allows us to study spillover effects from coastal house prices to interior counties.
This paper makes a structural of regional US house prices, specifically Californian metropolitan house prices. Empirically, we could not uncover a prominent role for monetary policy shocks in explaining the historical house prices in metropolitan areas of California. The same applies for AD and AS On the other hand, credit shocks play a major role in explaining the metropolitan house prices. Somewhat surprisingly (?) they did not play as big a role during the recent GFC as we expected. A positive regional housing demand shock increases personal income, and improves regional employment. Moreover, regional bank charge-offs decrease. The effects from shocks originating in the regional housing markets are generally more pervasive than general the aggregate counterparts.
This paper makes a structural of regional US house prices, specifically Californian metropolitan house prices. Empirically, we could not uncover a prominent role for monetary policy shocks in explaining the historical house prices in metropolitan areas of California. The same applies for AD and AS On the other hand, credit shocks play a major role in explaining the metropolitan house prices. Somewhat surprisingly (?) they did not play as big a role during the recent GFC as we expected. A positive regional housing demand shock increases personal income, and improves regional employment. Moreover, regional bank charge-offs decrease. The effects from shocks originating in the regional housing markets are generally more pervasive than general the aggregate counterparts.
This paper makes a structural of regional US house prices, specifically Californian metropolitan house prices. Empirically, we could not uncover a prominent role for monetary policy shocks in explaining the historical house prices in metropolitan areas of California. The same applies for AD and AS On the other hand, credit shocks play a major role in explaining the metropolitan house prices. Somewhat surprisingly (?) they did not play as big a role during the recent GFC as we expected. A positive regional housing demand shock increases personal income, and improves regional employment. Moreover, regional bank charge-offs decrease. The effects from shocks originating in the regional housing markets are generally more pervasive than general the aggregate counterparts.
This paper makes a structural of regional US house prices, specifically Californian metropolitan house prices. Empirically, we could not uncover a prominent role for monetary policy shocks in explaining the historical house prices in metropolitan areas of California. The same applies for AD and AS On the other hand, credit shocks play a major role in explaining the metropolitan house prices. Somewhat surprisingly (?) they did not play as big a role during the recent GFC as we expected. A positive regional housing demand shock increases personal income, and improves regional employment. Moreover, regional bank charge-offs decrease. The effects from shocks originating in the regional housing markets are generally more pervasive than general the aggregate counterparts.
This paper makes a structural of regional US house prices, specifically Californian metropolitan house prices. Empirically, we could not uncover a prominent role for monetary policy shocks in explaining the historical house prices in metropolitan areas of California. The same applies for AD and AS On the other hand, credit shocks play a major role in explaining the metropolitan house prices. Somewhat surprisingly (?) they did not play as big a role during the recent GFC as we expected. A positive regional housing demand shock increases personal income, and improves regional employment. Moreover, regional bank charge-offs decrease. The effects from shocks originating in the regional housing markets are generally more pervasive than general the aggregate counterparts.
Thank you!