مقاله انگلیسی رایگان در مورد زمان ساخت و کانال اختیارات حقیقی سرمایه گذاری مسکونی – الزویر 2019

1- Introduction

2- Model of time to build

3- Data

4- Model simulation and estimation

5- Housing supply implications

6- Conclusion

References

Abstract

A standard real-options model predicts that time-to-build investment could be delayed by uncertainty over future revenue. We quantify the first-order importance of this mechanism in the 2002–2011 housing boom-bust cycle by developing and estimating a model of sequential irreversible investment with stochastic bottlenecks. We find that the main driver of construction delays during the boom is construction bottlenecks. However, further delay in construction during the bust is caused by an increase in uncertainty, which grew by 21.6% between 2002 and 2009. The model can account for more than one-third of the decline in residential investment between 2002 and 2009.

Introduction

Many investment projects are irreversible, their future payoffs are uncertain, and the timing of investment is flexible. The real-options theory of investment considers optimal investment decisions under such conditions, as articulated in Dixit and Pindyck (1994). The models predict that the option value of waiting for new information influences the optimal investment decision. This paper investigates residential investment in the 2002–2011 housing boom-bust cycle through the lens of the real-options mechanism. A key observation that motivates our paper is shown in Fig. 1. The average times from start to completion for both single-family and multifamily houses were stable between 1984 and 2002, but those times shifted upward by two and four months between 2002 and 2009, respectively. This translates into a 25% to 40% slowdown in average construction intensity per house under construction. This study quantitatively assesses the role of uncertainty in accounting for the sizable delay in construction during the housing cycle. To this end, we develop and estimate a sequential irreversible investment model with stochastic bottlenecks based on Majd and Pindyck (1987). The key predictions of the model are that low price level, high price uncertainty, and high bottleneck probability all delay the completion of a project. Using micro-data on residential construction, we estimate our model based on simulated method of moments (SMM).