Does Tourism Contribute to Real Estate Boom? A DSGE Modeling in Small Open Economy

2020 ◽  
Vol 45 (1) ◽  
pp. 257-279
Author(s):  
Hongru Zhang ◽  
Yang Yang
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Open Economy ◽  
Driving Forces ◽  
House Prices ◽  
Small Open Economy ◽  
Policy Implications ◽  
Tourism Demand ◽  
Inbound Tourism ◽  
Dynamic Stochastic

This article aims to investigate the relationship between inbound tourism and housing market along with the recent boom in Icelandic real estate sector, in which both house and rental prices have been rising dramatically. To this end, we construct a small open economy dynamic stochastic general equilibrium model enclosing a tourism sector and a housing market with owner-occupied and rental sections. The simulation results unveil a transmission channel that indicates the higher inbound tourism demand raises both house prices and rental prices. Variance decomposition and historical decomposition show that both inbound tourism demand shock and manufacturing technology shock are the key driving forces of the fluctuations of Icelandic house prices, consumption, and investment, whereas housing preference shock plays the most important role in determining the volatility of rental prices. The policy implications indicate that any shocks to tourism could easily spillover to housing market dynamics and aggregate fluctuations.

scholarly journals Housing and Consumption in New Zealand:  A Financial Accelerator DSGE Model  and SVAR Analysis

2021 ◽  
Author(s):  
◽  
Andrew D Fung
Keyword(s):  
New Zealand ◽  
Housing Market ◽  
Open Economy ◽  
Government Spending ◽  
Negative Impact ◽  
House Prices ◽  
Small Open Economy ◽  
Financial Accelerator ◽  
Dsge Model

<p>This thesis examines the role of a financial accelerator mechanism for housing in the context of a small open economy. Following the seminal financial accelerator framework in a Dynamic Stochastic General Equilibrium (DSGE) model set out by Bernanke, Gertler and Gilchrist (1999) (BGG), Aoki, Proudman and Vlieghe (2002, 2002a, 2004) (APV) examine the role of the financial accelerator for the housing market. In my basic model (Chapter 2), I extend the analysis of APV from a closed economy to a small open economy in which imports are used as intermediate inputs into the production process and foreign demand for domestically produced goods is influenced by the real exchange rate. Unlike APV, I set the endowment of housing to be consistent with the nature of consumer behaviour, in that “rule of thumb” (ROT) consumers (who do not save) are renters, further differentiating them from “permanent income hypothesis” (PIH) consumers. I find that in contrast to APV, the financial accelerator effect does not increase the responsiveness of consumption and output to various shocks. This is due in part to the endowment of housing being restricted to PIH households. I find that the presence of a financial accelerator increases the responsiveness of the housing market to nominal interest rate, technology, and foreign shocks. Moreover, even though the financial accelerator reduces the reaction of the nonhousing variables to shocks, there is still a positive correlation between house prices and consumption, consistent with the widely observed empirical relationship between the two. Furthermore, given that PIH households have access to the capital markets, the model does not rely on a wealth effect to generate this correlation even though homeowners can engage in housing equity withdrawal. In Chapter 3 I extend the DSGE model to include a more fully specified fiscal sector. I find that consistent with the RBC view of fiscal policy, a positive government spending shock has a negative impact on the housing market. Using the type of fiscal rule proposed by Gal´ı, Vall´es and L´opez-Salido (2004), I find that government spending crowds out private consumption, including the purchase of housing services and has a negative impact on house prices. Despite the positive short-term impact on output, tax increases that would ultimately fund the spending shock act as a drag on consumption. In Chapter 4 I examine the New Zealand empirical data in order to see whether a financial accelerator effect can be detected. Using a small seven variable Structural Vector Auto-Regression model I find that shocks to house prices do not have a significant impact on the mortgage rate-benchmark interest rate spread in the manner suggested by the financial accelerator model. This may be due to other costs (such as funding mortgage lending through the international swap market by New Zealand banks) having a significant impact on the setting of mortgage rates and thus the spread. I also find that government spending does not appear to have a significant impact on house prices and the median response is mildly negative - consistent with the result from the DSGE model. Nevertheless, the SVAR does detect a significant relationship between shocks to house prices and household consumption.</p>

scholarly journals Housing and Consumption in New Zealand:  A Financial Accelerator DSGE Model  and SVAR Analysis

2021 ◽  
Author(s):  
◽  
Andrew D Fung
Keyword(s):  
New Zealand ◽  
Housing Market ◽  
Open Economy ◽  
Government Spending ◽  
Negative Impact ◽  
House Prices ◽  
Small Open Economy ◽  
Financial Accelerator ◽  
Dsge Model

<p>This thesis examines the role of a financial accelerator mechanism for housing in the context of a small open economy. Following the seminal financial accelerator framework in a Dynamic Stochastic General Equilibrium (DSGE) model set out by Bernanke, Gertler and Gilchrist (1999) (BGG), Aoki, Proudman and Vlieghe (2002, 2002a, 2004) (APV) examine the role of the financial accelerator for the housing market. In my basic model (Chapter 2), I extend the analysis of APV from a closed economy to a small open economy in which imports are used as intermediate inputs into the production process and foreign demand for domestically produced goods is influenced by the real exchange rate. Unlike APV, I set the endowment of housing to be consistent with the nature of consumer behaviour, in that “rule of thumb” (ROT) consumers (who do not save) are renters, further differentiating them from “permanent income hypothesis” (PIH) consumers. I find that in contrast to APV, the financial accelerator effect does not increase the responsiveness of consumption and output to various shocks. This is due in part to the endowment of housing being restricted to PIH households. I find that the presence of a financial accelerator increases the responsiveness of the housing market to nominal interest rate, technology, and foreign shocks. Moreover, even though the financial accelerator reduces the reaction of the nonhousing variables to shocks, there is still a positive correlation between house prices and consumption, consistent with the widely observed empirical relationship between the two. Furthermore, given that PIH households have access to the capital markets, the model does not rely on a wealth effect to generate this correlation even though homeowners can engage in housing equity withdrawal. In Chapter 3 I extend the DSGE model to include a more fully specified fiscal sector. I find that consistent with the RBC view of fiscal policy, a positive government spending shock has a negative impact on the housing market. Using the type of fiscal rule proposed by Gal´ı, Vall´es and L´opez-Salido (2004), I find that government spending crowds out private consumption, including the purchase of housing services and has a negative impact on house prices. Despite the positive short-term impact on output, tax increases that would ultimately fund the spending shock act as a drag on consumption. In Chapter 4 I examine the New Zealand empirical data in order to see whether a financial accelerator effect can be detected. Using a small seven variable Structural Vector Auto-Regression model I find that shocks to house prices do not have a significant impact on the mortgage rate-benchmark interest rate spread in the manner suggested by the financial accelerator model. This may be due to other costs (such as funding mortgage lending through the international swap market by New Zealand banks) having a significant impact on the setting of mortgage rates and thus the spread. I also find that government spending does not appear to have a significant impact on house prices and the median response is mildly negative - consistent with the result from the DSGE model. Nevertheless, the SVAR does detect a significant relationship between shocks to house prices and household consumption.</p>

Financial openness, bank capital flows, and the effectiveness of macroprudential policies

2021 ◽  
pp. 1-32
Author(s):  
Hao Jin ◽  
Chen Xiong
Keyword(s):  
Open Economy ◽  
Capital Flows ◽  
Open Economies ◽  
Small Open Economy ◽  
Empirical Support ◽  
Bank Capital ◽  
Macroprudential Policy ◽  
Funding Sources ◽  
Macroprudential Policies ◽  
Dynamic Stochastic

Abstract This paper quantitatively examines the macroeconomic and welfare effects of macroprudential policies in open economies. We develop a small open economy dynamic stochastic general equilibrium (DSGE) model, where banks choose their funding sources (domestic vs. foreign deposits) and are subject to financial constraints. Our model predicts that banks reduce leverage in response to a macroprudential policy tightening, but increasingly rely on foreign funding. This endogenous shifts of funding composition significantly undermine the stabilizing effect and welfare gains of macroprudential policies. Our results also suggest macroprudential policies are less effective in financially more open economies, and optimal policy should take capital flows into consideration. Finally, we find empirical support for the model predictions in a group of developing and emerging economies.

External Shocks and Their Transmission Channels in Nigeria: A Dynamic Stochastic General Equilibrium Approach

2022 ◽  
pp. 097491012110673
Author(s):  
Titus Ayobami Ojeyinka ◽  
Dauda Olalekan Yinusa
Keyword(s):  
General Equilibrium ◽  
Open Economy ◽  
Dynamic Stochastic General Equilibrium ◽  
Policy Implications ◽  
Output Gap ◽  
External Shocks ◽  
Transmission Channels ◽  
Dynamic Stochastic ◽  
Trade And Exchange ◽  
The Impact

The study examines the sources of external shocks and investigates their transmission channels in Nigeria using the trade-weighted variables from the country’s five top trading partners. Based on the assumption of the small open economy model, the study adopts the New Keynesian Dynamic Stochastic General Equilibrium Model on quarterly data between 1981 and 2018 using the Bayesian estimation technique. Findings from the study reveal that external shocks have a temporary and short-lived effect on the Nigerian economy. In addition, the article shows that oil price, foreign output, and foreign inflation shock have positive impacts on output gap and inflation, while the impact of foreign interest rate shock on the output gap and inflation is negative and not significant. The study also reveals that external shocks collectively explain 86% and 39%of total fluctuations in the output gap and inflation, respectively. Lastly, the study finds that external shocks transmit to the Nigerian economy via different channels. The study, therefore, concludes that terms of trade and exchange rate channels are the dominant transmitters of external shocks in Nigeria. Based on the findings from the study, important policy implications are highlighted.

scholarly journals The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Phuong V. Nguyen
Keyword(s):  
Business Cycle ◽  
Open Economy ◽  
Small Open Economy ◽  
Research Paper ◽  
New Keynesian ◽  
Dsge Model ◽  
Content Type ◽  
Business Cycle Fluctuations ◽  
Dynamic Stochastic ◽  
The Business Cycle

PurposeThe primary purpose of this paper is to investigate the sources of the business cycle fluctuations in Vietnam. To this end, the author develops a small open economy New Keynesian dynamic stochastic general equilibrium (SOE-NK-DSGE) model. Accordingly, this model includes various features, such as habit consumption, staggered price, price indexation, incomplete exchange-rate pass-through (ERPT), the failures of the law of one price (LOOP) and the uncovered interest rate parity. It is then estimated by using the Bayesian technique and Vietnamese data 1999Q1–2017Q1. Based on the estimated model, this paper analyzes the sources of the business cycle fluctuations in this emerging economy. Indeed, this research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.Design/methodology/approachA SOE-NK-DSGE model—Bayesian estimation.FindingsThis paper analyzes the sources of the business cycle fluctuations in Vietnam.Originality/valueThis research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.

scholarly journals TECHNOLOGY SHOCKS AND BUSINESS CYCLES IN INDIA

2017 ◽  
Vol 23 (5) ◽  
pp. 1721-1756 ◽  
Author(s):  
Shesadri Banerjee ◽  
Parantap Basu
Keyword(s):  
Interest Rate ◽  
Open Economy ◽  
Emerging Market ◽  
Small Open Economy ◽  
Annual Data ◽  
Technology Shocks ◽  
Demand Side ◽  
Aggregate Fluctuations ◽  
Dsge Model ◽  
Dynamic Stochastic

In this paper, we develop a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model to understand the relative importance of two key technology shocks, Hicks neutral total factor productivity (TFP) shock and investment specific technology (IST) shock for an emerging market economy like India. In addition to these two shocks, our model includes three demand side shocks such as fiscal spending, home interest rate, and foreign interest rate. Using a Bayesian approach, we estimate our DSGE model with Indian annual data for key macroeconomic variables over the period of 1971–2010, and for subsamples of pre-liberalization (1971–1990) and post-liberalization (1991–2010) periods. Our study reveals three main results. First, output correlates positively with TFP, but negatively with IST. Second, TFP and IST shocks are the first and the second most important contributors to aggregate fluctuations in India. In contrast, the demand side disturbances play a limited role. Third, although TFP plays a major role in determining aggregate fluctuations, its importance vis-à-vis IST has declined during the post liberalization era. We find that structural shifts of nominal friction and relative home bias for consumption to investment in the post-liberalization period can account for the rising importance of the IST shocks in India.

scholarly journals Information Opportunities of Administrative Data on Residential Real Estate Transactions for Calculating the House Prices in Russia’s Housing Market

2021 ◽  
Vol 18 (6) ◽  
pp. 60-72
Author(s):  
A. B. Dukhon ◽  
O. I. Obraztsova ◽  
N. D. Epshtein
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
Information Source ◽  
Residential Property ◽  
National Accounts ◽  
System Of National Accounts ◽  
Registration Data ◽  
State Register ◽  
Property Price

Purpose of the study. Development, justification and testing of a methodology for improving statistical monitoring of average prices in the Russian housing market, based on the use of registration information of the Unified State Register of Real Estate (USRN) on transactions for the purchase of residential real estate, in accordance with international statistical standards for Residential Property Price statistics.Materials and methods. The theoretical basis of the study was the United Nations system of national accounts (version of 2008), including the European system of accounts as amended in 2010. The research methodological base was made up of official statistical sources: metadata and international statistics guidelines in the field of national accounting, Handbook on Residential Property Price Indices and related housing indicators, as well as methodological provisions and an album of Rosstat forms, and methodological materials of the administrative statistics of the Federal Service for State Registration, Cadastre and Cartography of the Russian Federation (Rosreestr). The depersonalized registration data on households’ market transactions of the Unified State Register of Property Rights and Transactions maintaining by Rosreestr were used as an information database of the research.Results. The main result of the study is the design and substantiation of a system of indicators for the construction of an integrated information source for Residential Property Price statistics, on the base on interdepartmental information interaction.Conclusion. The proposed system of indicators will provide a highquality database that could be used in order to construct constant quality House Prices for various types of homogeneous residential property in the housing market, complying with the concepts of international statistical standards.

scholarly journals Retail Space for Rent! Macroeconomic Determinants of Shopping Complex Occupancy Rate

2021 ◽  
Vol 21 (1) ◽  
pp. 268-284
Author(s):  
Shan-Shan Goh ◽  
Tuck-Cheong Tang ◽  
Alex Hou-Hong Ng
Keyword(s):  
Interest Rate ◽  
Gross Domestic Product ◽  
Open Economy ◽  
Inflation Rate ◽  
Positive Impact ◽  
Small Open Economy ◽  
Policy Implications ◽  
Occupancy Rate ◽  
Causality Tests ◽  
Macroeconomic Determinants

This study proposes anad hoc equationwhich isapplied to estimatethe impactsof macroeconomic variableson occupancy rate of shopping complex. Thecandidatemacroeconomic determinantsare interest rate, inflation rate, share priceand Gross Domestic Product (GDP), whileasupply-sidevariable, total spaceis included.Using quarterly databetween 1992and 2015 froma small open economy-Malaysia, this study findsthat interest rate,and GDP both havea positive impact on shopping complex’s occupancy rate, and total space of shopping complex shows anegative sign.The non-causality tests offer that inflation rate indirectlycauses the occupancy rate of shopping complex. This study highlights somerelevant policy implications.

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