We study housing dynamics in China using vector autoregressions identified with theoryconsistent sign restrictions. We study five potential drivers: 1) Population increases ; 2) a relaxation of credit standards, for example, due to the shadow banking system; 3) increasing preferences towards housing, for example, due to a housing bubble, or to housing being a status asset in the marriage market; 4) an increase in the savings rate; and 5) expected productivity progress. Our results show that fundamental shocks (population, credit and productivity) played a major role in the dynamics of house prices and residential investment before 2009. Preference shocks seem especially relevant in the last several years.

We study housing dynamics in China using vector autoregressions identified with theoryconsistent sign restrictions. We study five potential drivers: 1) Population in-creases; 2) a relaxation of credit standards, for example, due to the shadow banking system; 3) increasing preferences towards housing, for example, due to a housing bubble, or to housing being a status asset in the marriage market; 4) an increase in the savings rate; and 5) expected productivity progress. Our results show that fundamental shocks (population, credit and productivity) played a major role in the dynamics of house prices and residential investment before 2009. Preference shocks seem especially relevant in the last several years.

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