Showing posts with label Global Housing Watch. Show all posts
Friday, December 17, 2021
Please note that Housing View will be on hiatus for the last two week of December and will resume back in January 2022.
On cross-country:
On the US:
On China
On other countries:
Please note that Housing View will be on hiatus for the last two week of December and will resume back in January 2022.
On cross-country:
On the US:
Posted by 5:00 AM
atLabels: Global Housing Watch
Monday, December 13, 2021
From MacroPolo:
“With China’s Evergrande moving into what appears to be a managed default process, as we had previously anticipated, it’s time to look at the future of the property sector. Even without the Evergrande crisis, the property sector is bound to see a correction. The crisis simply made the writing on the wall clearer. Such a correction means that China’s notoriously outsized investment-driven model will have to be “right-sized.”
The right-sizing of investment, which mainly refers to fixed-capital formation that makes up about 43% of GDP, will inevitably hurt growth (see Figure 1). Getting a handle on the magnitude of the growth impact, therefore, will be key to any analysis of China’s economic future. To do so requires examining construction-related investment, which is composed mainly of private property investment and local government investment (including public housing and infrastructure).
Our baseline scenario assumes a 30% decline in private property construction through 2025. In total construction volume terms, that means a correction from 100 million units to roughly 70 million units. Such a correction will lead to annual property sales falling from 15% to 10% of GDP by 2025, which is basically the same level as in 2010. In other words, China intends to roll back the decade of rapid property sector growth in the next five years.
As a result, local government investment, which is basically public spending on infrastructure that depends largely on land revenue derived from private property investment, will likely decline by 3% of GDP over the same period. Combined with the property correction, we expect overall construction investment to be down by 6% of GDP.”
From MacroPolo:
“With China’s Evergrande moving into what appears to be a managed default process, as we had previously anticipated, it’s time to look at the future of the property sector. Even without the Evergrande crisis, the property sector is bound to see a correction. The crisis simply made the writing on the wall clearer. Such a correction means that China’s notoriously outsized investment-driven model will have to be “right-sized.”
The right-sizing of investment,
Posted by 8:10 AM
atLabels: Global Housing Watch
Saturday, December 11, 2021
From a VoxEU post by Orsetta Causa, Maria Chiara Cavalleri, Michael Abendschein, and Nhung Luu:
“The capacity of workers to move regions in response to local economic shocks is a key dimension of labour market dynamism that could contribute to recovery from the COVID-19 crisis and support the green transition. This column presents new empirical evidence on how policies can shape the responsiveness of inter-regional migration to regional economic conditions, with a particular focus on housing markets, social policies, and business regulations. It highlights the need for articulating place-based policies to help prospective movers as well as stayers
Inter-regional migration can contribute to the smooth and inclusive recovery from the COVID-19 crisis (for instance, by helping to match workers and jobs) as well to the green transition (for instance, by helping labour reallocation towards low-carbon activities). Mobility across regions can also contribute to upward social mobility, for instance by allowing workers to move out of disadvantaged areas or declining sectors. While promoting mobility is not an end in itself, managing mobility is an important policy challenge, especially in countries with large and persistent spatial disparities between regions.
Recent work by the OECD (Causa et al. 2021, Cavalleri et al. 2021, OECD 2021a) examines the levels and trends of inter-regional migration within and across OECD countries. It presents novel cross-country and country-specific empirical evidence on economic and housing-related factors affecting people’s decisions to move to a different region within the same country. This work shows how policies influence the responsiveness of regional migration to regional economic conditions and shocks. It also contributes to the renewed interest in regional inequalities and placed-based policies (Siegloch et al. 2021, Ku et al. 2020, Iammarino et al. 2019).
We find that inter-regional migration varies significantly across OECD countries (Figure 1). In high-mobility countries, such as Hungary and Korea, around 5% of the population moves to another region each year. By contrast, mobility rates are below 1% in some Eastern and Southern European countries, such as Slovakia, Poland and Italy.”
Continue reading here.
From a VoxEU post by Orsetta Causa, Maria Chiara Cavalleri, Michael Abendschein, and Nhung Luu:
“The capacity of workers to move regions in response to local economic shocks is a key dimension of labour market dynamism that could contribute to recovery from the COVID-19 crisis and support the green transition. This column presents new empirical evidence on how policies can shape the responsiveness of inter-regional migration to regional economic conditions,
Posted by 7:29 AM
atLabels: Global Housing Watch
Friday, December 10, 2021
On cross-country:
On the US:
On China
On other countries:
On cross-country:
On the US:
Posted by 5:00 AM
atLabels: Global Housing Watch
Wednesday, December 8, 2021
From a NBER paper by Rebecca Diamond and Enrico Moretti:
“Income differences across US cities are well documented, but little is known about the level of standard of living in each city—defined as the amount of market-based consumption that residents are able to afford. In this paper we provide estimates of the standard of living by commuting zone for households in a given income or education group, and we study how they relate to local cost of living. Using a novel dataset, we observe debit and credit card transactions, check and ACH payments, and cash withdrawals of 5% of US households in 2014 and use it to measure mean consumption expenditures by commuting zone and income group. To measure local prices, we build income-specific consumer price indices by commuting zone. We uncover vast geographical differences in material standard of living for a given income level. Low-income residents in the most affordable commuting zone enjoy a level of consumption that is 74% higher than that of low-income residents in the most expensive commuting zone.
We then endogenize income and estimate the standard of living that low-skill and high-skill households can expect in each US commuting zone, accounting for geographical variation in both costs of living and expected income. We find that for college graduates, there is essentially no relationship between consumption and cost of living, suggesting that college graduates living in cities with high costs of living—including the most expensive coastal cities—enjoy a standard of living on average similar to college graduates with the same observable characteristics living in cities with low cost of living—including the least expensive Rust Belt cities. By contrast, we find a significant negative relationship between consumption and cost of living for high school graduates and high school drop-outs, indicating that expensive cities offer a lower standard of living than more affordable cities. The differences are quantitatively large: High school drop-outs moving from the most to the least affordable commuting zone would experience a 26.9% decline in consumption.”
From a NBER paper by Rebecca Diamond and Enrico Moretti:
“Income differences across US cities are well documented, but little is known about the level of standard of living in each city—defined as the amount of market-based consumption that residents are able to afford. In this paper we provide estimates of the standard of living by commuting zone for households in a given income or education group, and we study how they relate to local cost of living.
Posted by 12:59 PM
atLabels: Global Housing Watch, Inclusive Growth
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