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http://localhost:8080/xmlui/handle/123456789/430| Title: | Impact of macroprudential policies on house price expectations- evidence from survey data |
| Authors: | Banerjee, Anurag |
| Keywords: | Survey Data |
| Issue Date: | 2024 |
| Publisher: | Economics Letters |
| Abstract: | This paper investigates the impact of macroprudential policies (MPP) on house price expectations using novel data from the Inflation Expectation of Households survey across 19 major Indian cities released by the Reserve Bank of India. MPP negatively impacts house price expectations, especially borrower-based macroprudential policies. We also find that tightening MPP impacts the retired group more than other occupational groups. |
| Description: | Housing is one of the key components of household wealth, consumption, and collateral (Hjalmarsson and Osterholm, 2020). It is also one of the crucial sectors in many economies across the globe (Leamer, 2015). One prime factor determining the housing ownership decision is house price expectations (Landvoigt, 2017). The expectations of future house prices also play pivotal roles in forming actual house prices, mortgage choices, and leverage decisions (De Stefani, 2021; Bailey et al., 2019). The above studies, therefore, provide evidence of the importance of house price expectations in the housing market and their association with leverage decisions. Following the global financial crisis, macroprudential policies are one of the critical tools that are being increasingly applied in many economies to regulate the housing market finance, directly impacting the home buyers’ leverage decisions (Kuttner and Shim, 2016; Saha et al., 2023). Several studies also show that MPP tools such as minimum capital adequacy ratio and LTV limits are also effective in moderating house prices (Kuttner and Shim, 2016). However, there is limited evidence of MPP’s role in house price expectations (Igan and Kang, 2011). Therefore, we aim to examine the role of MPP on house price expectations for an emerging economy like India using novel survey data. 2. Data We use the individual-level data from the Inflation Expectation of Households (IESH) survey by the Reserve Bank of India (RBI) across several survey rounds spread over 19 major Indian cities.3 . This study uses data from Round 13 (September 2008) to Round 66 (January 2022). In every round, approximately 5,500 respondents are asked to express their opinion about their inflation expectations, including their expectations on house prices three months ahead and one year ahead. We define EHP3M=-1 if the households expect house prices to decline, 0 if they expect no changes in price, and +1 if they expect prices to increase from the current rate in the next three months. Similarly, EHP1Y=-1 if the households expect house prices to decline, 0 if they expect no changes in price, and +1 if they expect prices to increase from the current rate in the next year. Furthermore, the survey also records certain demographic information of the respondents, such as age, gender, and occupation (Table 1). |
| URI: | http://localhost:8080/xmlui/handle/123456789/430 |
| Appears in Collections: | PGDM |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Impact of macroprudential policies on house price expectations- evidence from survey data.pdf | 240.6 kB | Adobe PDF | View/Open |
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