Land-Price Dynamics and Macroeconomic Fluctuations
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1 Land-Price Dynamics and Macroeconomic Fluctuations Zheng Liu, Pengfei Wang, and Tao Zha; Econometrica (2013) UC3M Macro Reading Group - Discussion by Omar Rachedi 28 May 2014
2 Land price and business investment
3 This paper Shocks to land prices main source of business cycles Two premises: Fluctuations in real estate prices are mostly driven by land prices Real estate is a big component of US firms tangible assets Key ingredient: Households and entrepreneurs compete for land Households value land (housing services). Entrepreneurs borrow by using land as a collateral asset Positive housing demand shock (households value land more) Price of land rises, so also the entrepreneurs collateral value Entrepreneurs borrow more, expand investment and production, thus demand more land, land price further rises Households supply more labor, get richer, and demand more land, land price rises and so on...
4 Sketch of the model (1/2) Households Supply labor and value consumption goods, land and leisure E 0 t=0 β t A t {log C ht + ϕ t log L ht ψ tn ht } Budget constraint C ht + q lt (L ht L ht 1 ) + St R t = w tn ht + S t 1
5 Sketch of the model (1/2) Households Supply labor and value consumption goods, land and leisure E 0 t=0 β t A t {log C ht + ϕ t log L ht ψ tn ht } Budget constraint C ht + q lt (L ht L ht 1 ) + St R t Entrepreneurs = w tn ht + S t 1 Value consumption goods E 0 t=0 βt A t log C et [ ] α Produce using capital, labor and land Y t = Z t L φ et 1 K 1 φ N 1 α Budget constraint C et + q lt (L et L et 1) + B t 1 = Y t w tn et It Q t + Bt R t Can borrow up to a fraction of value of their assets (land and capital) B t θ te t [q lt+1 L et + q kt+1 K t] t 1 et
6 Sketch of the model (2/2) Market clearing Goods: C ht + C et + It Q t Labor: N et = N ht Land: L ht + L et = L Bonds: S t = B t Shocks: = Y t Shock to household s preference for housing: ϕ t Shock to household s labor disutility: ψ t Patience shock: A t Permanent and transitory shocks to TFP: Z t Permanent and transitory shocks to investment-specific technology: Q t Financial shock: θ t
7 Mechanism (1/2) Consider the optimal choices of land Households: Entrepreneurs: q lt = ϕtc ht L ht + βe t q lt = µt C et θ te t [q lt+1 ] + βe t [ Cet [ ] Cht q lt+1 C ht+1 C et+1 ( )] αφ Yt+1 + q lt+1 L et Which shock can make land price fluctuate? TFP shock affects q l through Y, but in data Var(q l ) > Var(Y ). By directly affecting q l, housing and financial shocks could do the job. In the quantitative evaluation ϕ t explains = 90% of Var(q l ), θ t irrelevant.
8 Mechanism (2/2)
9 Mechanism (2/2)
10 Mechanism (2/2)
11 Mechanism (2/2)
12 Mechanism (2/2)
13 Estimation Loglinearize the model around the steady state in which the credit constraint is binding Estimate by Bayesian methods Data: quarterly time series for the US (1975:Q1-2010:Q4) real price of land; real per capita consumption; real per capita investment; real per capita nonfarm nonfinancial business debt; per capita hours worked; quality-adjusted relative price of investment.
14 a Columns 2 to 9 report the contributions of a patience shock (Patience), permanent and transitory shocks to neutral technology (Ngrowth and Nlevel), permanent and transitory shocks to biased technology (Bgrowth and Blevel), ahousingdemandshock(housing),alaborsupplyshock(labor),andacollateralshock(collateral). driving fluctuations in the land price and macroeconomic variables. We do this through variance decompositions. Table III reports variance decompositions Relative importance of the shocks Variance decompositions of aggregate quantities TABLE III VARIANCE DECOMPOSITIONS OF AGGREGATE QUANTITIES a Horizon Patience Ngrowth Nlevel Bgrowth Blevel Housing Labor Collateral Land price 1Q Q Q Q Q Investment 1Q Q Q Q Q Output 1Q Q Q Q Q Hours 1Q Q Q Q Q
15 Role of housing demand shock in the last recession Actual path (thin line) and simulated data using housing shock only (thick line)
16 Sensitivity analysis Robustness checks and extensions Allow land supply to grow. Add working capital. External capital producers. Drop patience shock Investment-specific shocks as latent variable Different land-price series (based on CoreLogic rather than FHFA) Occasionally binding credit constraint Weighed collateral constraint: Bt θ te t [ω l q lt+1 L et + ω k q kt+1 K t] Allow for time-varying volatility of housing demand shock Results do not drastically change.
17 Conclusions Recent literature emphasizes role real estate prices in driving cycles Here the authors take a step back by focussing on land prices. Housing demand shock triggers fluctuations in land prices. Firms borrowing tied to value of land Land competition, amplify and propagate the shock. Housing demand shocks are quantitatively relevant, TFP and financial shocks are marginal.
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