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Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting...

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PRE-CRISIS DEVELOPMENTS IN THE HUNGARIAN HOUSING MARKET; A MODEL WITH QUALITY DIFFERENTIAL Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.
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Page 1: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

PRE-CRISIS DEVELOPMENTS IN THE HUNGARIAN HOUSING

MARKET;A MODEL WITH QUALITY

DIFFERENTIAL

Áron Horváth – János Vincze

Helmut Schmidt University – HamburgReal Estate Forecasting Workshop

November 24., 2011.

Page 2: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

CONTENTS1. Overview of the Hungarian

residential real estate market. 2. The paper

2.1. The observation: quality differential

2.2. The model2.3. Impulse responses2.4. Calibration strategy

Page 3: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

Overview of the Hungarian residential

real estate market

Page 4: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

1.1. HOUSING MARKET IN THE SOCIALIST ERA – UNTIL 1989

One family – one flat rule. Few available investment assets. Unprofessional (governmental or

family built) construction industry - low quality homes.

Page 5: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

1.2. HOUSING MARKET IN THE NINETIES

Mass amount of privatized flats. The flats were of deteriorated quality. Lack of credit market. Low supply and

demand also.

Page 6: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

HOUSING MARKET AFTER THE MILLENNIUMThree pillars of the

change Overall economic

and financial stabilization.

More professional construction industry.

Huge governmental subsidy system.

Page 7: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

HOUSING MARKET DURING THE CRISIS The crisis hit the Hungarian economy

severely. Three channels of the effect:

Decreasing income of households. Diminishing credit supply: banks had to

deal with their problem on the liability side.

Almost disappearing governmental subsidies because of the financial consolidation.

The prospects are still not very good.

Page 8: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

The paper: a model with quality differential

Page 9: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

OBSERVATION 1-2.

Page 10: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

OBSERVATION 3! price of more expensive homes relative to the typical (median) home price

Page 11: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

MODEL simple framework:

endogenous variables: price, quantity dynamic structure: lagging supply duplication by quality level: „good”

quality homes and „bad” quality homes

Page 12: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

DEMAND Budget constraint

income wealth consumption expenditure

Quadratic utility function

Page 13: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

SUPPLY Profitmaximizing company with

adjustment costs

Supply functions

Page 14: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

THE DYNAMIC SYSTEM 6 equations

6 variables

Page 15: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

SIMULATION: INCREASING INCOME

Page 16: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

SIMULATION: INCREASING INCOME It explains the rise in house prices and

the construction boom. But its effect on relative prices is

positive.

Page 17: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

SIMULATION: QUALITY SHORTAGE Anecdotical evidence on quality

shortage could explain the relative price pattern.

Page 18: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

CALIBRATION STRATEGY I.(STEADY STATE) amortization parameters: technical

values. interest rate: expected yield of the

worse homes. supply parameters: based on the

relative price of the two kinds of flats transition parameter from good to worse

homes: expected yield of better homes

Page 19: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

CALIBRATION STRATEGY II.(DYNAMICS)

adjustment cost parameters:To replicate the one and a half years’

reaction of the construction industry demand parameters: demand

elasticity characteristics in the distinct groups

income parameters: quadratic structure is narrow, other specifications should be applied

Page 20: Áron Horváth – János Vincze Helmut Schmidt University – Hamburg Real Estate Forecasting Workshop November 24., 2011.

Thanks for your attention!

[email protected]


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