مقاله انگلیسی رایگان در مورد سرریزی در خلال ابهامات کلان اقتصادی، امور مالی و اموال غیر منقول – الزویر 2020

1- Introduction

2- Data

3- Methodology

4- Empirical results and discussion

5- Concluding remarks

References

Abstract

We investigate the spillover across real estate (REU), macroeconomic (MU) and financial uncertainties (FU) in the United States based on monthly data covering the period of July, 1970 to December, 2017. To estimate the propagation of uncertainties across the sectors, a time-varying parameter vector autoregression (TVP-VAR)-based connectedness procedure has been applied. In sum, we show that that since the 1970s, FU has been the main transmitter of shocks driving both, MU and REU, with MU dominating the REU. Our results support the need for better macroprudential policy decisions.

Introduction

Following the ‘Great Recession’ a burgeoning literature has aimed to develop time-varying measures of economic uncertainty (risk), and quantify its impact on the macroeconomy and financial markets (Gupta et al., 2018). In this regard, while studies like Jurado et al. (2015), Baker et al. (2016) and Rossi and Sekhposyan (2015) develop measures of macroeconomic and financial uncertainties, Nguyen Thanh et al. (2018) obtained timevarying estimates of uncertainty associated with the US real estate sector, considered as a leading indicator for US business cycles (Leamer, 2015). Against this backdrop, the objective of our paper is to utilize the connectedness approach of Diebold and Yılmaz (2009, 2012, 2014), but based on a fully-fledged time-varying parameter vector autoregression with heteroscedastic volatility (TVP-VAR), as suggested by Antonakakis and Gabauer (2017) and Korobilis and Yilmaz (2018), to analyse the spillovers across the measures of macroeconomic, financial and real estate uncertainties. The TVP-VAR framework improves the widely-used above-mentioned traditional methodology of spillovers analysis substantially, since we do not need to arbitrarily set the size of the rolling-window and hence, there is no loss of observations. In addition, the results are not sensitive to outliers as the approach is build on multivariate Kalman filters (Durbin and Koopman, 2012). Given the historical interconnectedness across the real, financial and housing sectors of the US economy (Emirmahmutoglu et al., 2016; Li et al., 2015), this analysis of time-variation in spillover of corresponding uncertainties is, understandably, of paramount importance to policy authorities. This is because, if indeed these measures are connected, then uncertainty of a particular sector can end up increasing even when the shock did not originate in that sector. In addition, the effects of the uncertainty shocks are likely to be prolonged via the feedbacks across the measures of sectoral uncertainties. In sum, interrelatedness is likely to deepen the well-established negative impacts of uncertainty shocks (Bloom, 2009) on the economy as a whole.