Showing posts with label Global Housing Watch. Show all posts
Friday, August 5, 2022
Conferences
On cross-country:
On the US:
On China:
On other countries:
Conferences
On cross-country:
Posted by 8:02 AM
atLabels: Global Housing Watch
Thursday, August 4, 2022
From RICS:
” – Construction Activity Index stalls in Europe and APAC, but remains a little more resilient elsewhere
– Overwhelming majority of respondents still report material costs and shortages to be impediments
– Global workloads still anticipated to rise across all sectors, albeit expectations are being scaled back”
From RICS:
” – Construction Activity Index stalls in Europe and APAC, but remains a little more resilient elsewhere
– Overwhelming majority of respondents still report material costs and shortages to be impediments
– Global workloads still anticipated to rise across all sectors, albeit expectations are being scaled back”
Posted by 8:13 AM
atLabels: Global Housing Watch
Monday, August 1, 2022
Posted by 8:34 AM
atLabels: Global Housing Watch
From a new IMF working paper by Yang Liu, Di Yang, and Yunhui Zhao:
“Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-rising house prices. We then apply machine learning methods to forecast inflation in two housing components (rent and owner-occupied housing cost) of the headline inflation and draw tentative inferences about inflationary impact. Our results suggest that for most of these countries, the housing components could have a relatively large and sustained contribution to headline inflation, as inflation is just starting to reflect the higher house prices. Methodologically, for the vast majority of countries we analyze, machine-learning models outperform the VAR model, suggesting some potential value for incorporating such models into inflation forecasting.”
From a new IMF working paper by Yang Liu, Di Yang, and Yunhui Zhao:
“Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-rising house prices. We then apply machine learning methods to forecast inflation in two housing components (rent and owner-occupied housing cost) of the headline inflation and draw tentative inferences about inflationary impact.
Posted by 8:18 AM
atLabels: Global Housing Watch
From a VoxEU post by Sahil Gandhi, Matthew Kahn, Rajat Kochhar, Somik Lall, and Vaidehi Tandel:
“Climate change is increasing the frequency and intensity of disasters, but the ability to cope varies widely across the globe. This column examines how city death tolls and economic activity are affected by flooding. Richer places with the resources and infrastructure to cope with disasters tend to be more resilient. Compared to cities in low-income countries, those in high-income countries suffered fewer deaths per disaster, adapted over the years to better mitigate the effects of flooding, and recovered faster from economic damage.
The major floods in India and Australia in 2022 have once again drawn attention to the destructive capacity of disasters. Climate change is likely to increase the frequency and intensity of these shocks. At the same time, the ability to cope with disasters will vary widely across places and over time. The living conditions of households in India are very different from those in Australia. In India, a large proportion of urban households live in slums on hillslopes or other unsafe areas. The impact of similar disasters would be different for the two countries. Given that a majority of people around the world now live in cities, it is important to measure the vulnerability and adaptive capacity of such productive areas to disasters.
Research on the impact of extreme weather predicts that the developing world, especially the poor and vulnerable populations, will be disproportionately affected (Mendelsohn et al. 2000, Mendelsohn et al. 2006, Tol 2009).
In our new paper (Gandhi et al. 2022), we use data on floods for 9,468 cities in 175 countries to examine the differential impact of floods on cities in high- and low-income countries. We combine monthly night light (VIIRS) data for these cities from 2012 to 2018 with a global dataset of geocoded disasters. Figure 1 shows that after a flood event, night lights fall and then recover. Floods disrupt life in cities through temporary power failures, disruption of essential services, damage to property, and temporary closure of offices and factories. These are reflected in the lights seen at night (Kocornik-Mina et al. 2016).”
Continue reading here.
From a VoxEU post by Sahil Gandhi, Matthew Kahn, Rajat Kochhar, Somik Lall, and Vaidehi Tandel:
“Climate change is increasing the frequency and intensity of disasters, but the ability to cope varies widely across the globe. This column examines how city death tolls and economic activity are affected by flooding. Richer places with the resources and infrastructure to cope with disasters tend to be more resilient. Compared to cities in low-income countries,
Posted by 8:14 AM
atLabels: Global Housing Watch
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