This paper analyses the time-to-built (gestation lag) technology on a multi-sector growth model that includes a housing sector. Gestation lags are explicitly modelled for the real estate sector (developers) so as to investigate the dynamics of property investments as well as the dynamics of business cycles. I have two .nal-goods sectors in my model. A consumption (and business investment) good is produced in the .rst sector. The second sector produces residential structures which are combined with newly available land to establish the real estate good. I incorporate a time-to-built technology in the property sector to better account for stylized facts such as (i) Property investment co-moves with investment in business capital. (ii) Investment in real estate is twice as volatile as business investment. (iii) Residential investment is leading the business cycle. I calibrate the model to US and German data and use standard linearization methods to solve the model near the steady state. I use policy functions that were obtained from numerical solutions to perform Monte Carlo experiments to approximate moments of the system. I then compare the moments of artificial data with the moments of real world date. My initial results indicate that construction lags in the property sector helps to better match the stylized facts mentioned above.