A review of an article on Policy impact analysis of housing policies using housing cycles, notably on research approaches: for Housing Studies students

A review of an article on Policy impact analysis of housing policies using housing cycles, notably on research approaches: for Housing Studies students

 

How to describe the article in Harvard reference format?

The article can be cited in Harvard reference format as follows:

Bang, D.W. and Kwon, H.S., 2022. Policy impact analysis of housing policies using housing cycles. SAGE Open, July-September, pp.1–14. DOI: 10.1177/21582440221113844.

 

Highlight the main research issues and research objectives, 2 main academic theories used and the main research methods used in this article.

Based on the article "Policy Impact Analysis of Housing Policies Using Housing Cycles" by Bang and Kwon (2022), here is a summary of the main research issues, objectives, academic theories, and research methods:

Main Research Issues:

• Korea's housing market shows significant regional differences in apartment price fluctuations.
• Lack of a comprehensive housing market cycle index by region in Korea to understand these fluctuations.
• Need to analyze the effectiveness and time lag of various Korean housing policies (financial, tax, and transaction policies) implemented since 2007 on the housing market.
• The housing market's sensitivity to location and regional economic conditions necessitates region-specific analysis.

Research Objectives:

• To develop regional housing cycles across 16 metropolitan regions in Korea using a statistical model that isolates real estate related information.
• To analyze the impact of the Korean government’s housing policies on these housing cycles, including possible time lag effects.
• To provide policy implications for tailored interventions considering regional characteristics and policy timing.

Main Academic Theories Used:

1.    Factor-Augmented Vector Autoregressive Model (FAVAR) — This econometric approach, proposed by Bernanke et al. (2005), is used to capture latent factors influencing the housing market by incorporating a large set of economic variables while minimizing omitted variable bias.

2.    Four Quadrants Model of DiPasquale and Wheaton (1996) — Provides a conceptual framework considering rent, price, construction, and stock variables to represent the housing market from multiple perspectives and dimensions.

Additional conceptual foundations include:

• Housing supply elasticity and economic downturn relation (Glaeser et al., 2008; Mian et al., 2013).
• Spatial dependence and heterogeneity in housing markets (Meen, 1996) for understanding local market interactions and regional characteristics.

Main Research Methods:

• Use of a Factor-Augmented Vector Autoregressive (FAVAR) model to construct regional housing cycles that reflect latent systematic factors associated with real estate markets while controlling for macroeconomic factors.
• Panel data analysis to estimate the net effects of various types of housing policies on housing cycles, considering regional and macroeconomic variables.
• Analysis of policy time lags by testing policy impacts at period t-1 (one month ahead), due to policy announcements being made in advance.
• Robustness checks comparing results using the housing cycle index versus housing price fluctuation rates as dependent variables.

This synthesis outlines the key focus on developing and applying a FAVAR-based regional housing cycle for Korea and empirically testing government housing policies’ effectiveness with spatial and temporal considerations.

 

What research approaches (reasoning) [inductive/ deductive/ abductive] and research approaches (methods) [qualitative/ quantitative/ mixed methods research] have been used in this study?

From the content and methodology described in the article "Policy Impact Analysis of Housing Policies Using Housing Cycles" by Bang and Kwon (2022), the following research reasoning and approaches are identified:

Research Reasoning Approach:

• Deductive reasoning: The study starts from existing economic theories and models (e.g., FAVAR model, four quadrants model of DiPasquale and Wheaton, housing supply elasticity concepts) and applies these theoretical frameworks to empirical data on Korean housing markets to test hypotheses about housing cycles and policy impacts. The structured modeling and hypothesis testing based on theory indicate a primarily deductive approach.

Research Method Approach:

• Quantitative research: The study employs quantitative methods involving statistical modeling (FAVAR modeling, panel data regression analysis), analysis of time-series data on housing prices and cycles, and the use of macroeconomic and regional economic variables to quantify policy effects and cyclical patterns. The reliance on econometric models and numerical data analysis classifies this work as quantitative research.

No evidence was found of qualitative or mixed methods (combining qualitative and quantitative) research in this study; the work is centered on quantitative empirical analysis using econometric approaches.

Summary:

• Reasoning approach: Deductive
• Research approach: Quantitative

 

Describe 2 main research limitations of the study.

The study identifies the following two main research limitations:

1.    Lack of Comparative Analysis Before and After the 2008 Financial Crisis: The study does not perform a comparative analysis of housing market dynamics and policy effects for periods before and after the 2008 global financial crisis. This limits understanding of how the structural changes induced by the crisis may have affected housing cycles and policy effectiveness in Korea.

2.    Insufficient Detailed Analysis of Regional Policy Effects: While the study analyzes overall policy effects on regional housing cycles, it acknowledges the need for a more detailed and granular examination of how different policies impact specific regions differently. The heterogeneity of regional responses to housing policies is not fully captured, which constrains developing tailored regional policy recommendations.

These limitations point to potential avenues for further research to deepen understanding of temporal changes and regional differentiation in housing market dynamics and policy impacts.