Housing occupies an unusual position as a commodity that’s at the same time a major component of wealth. On one hand, housing prices and demand have been shown to positively correlate across countries, which means that, across the world, demand for property drives prices up. On the other hand, prices have a variable impact on a family’s and individual’s tendency to buy. For example, it has been noted that regional house prices can negatively affect residents’ consumption, in some cases leading to “crowding out” whereby families move to cheaper cities if the rise in housing prices in their region outpaces the growth of wages.
Economic development, wages and employment are among variables that have been identified as possible moderators of housing costs. Nevertheless, the exact mechanisms through which various thresholds and transmission channels moderate housing prices – and how these, in turn, affect consumption – has largely been ignored in existing literature. Dr Yiming He, Weikum Zhang and Zhipeng Du from South China Agriculture University aimed to fill this gap in a study that uses a dynamic optimal general equilibrium model and spatial panel data analysis to better understand what drives housing consumption in China.
Real estate in China
Previous research has suggested that predictable changes in house prices are correlated with predictable changes in housing consumption, particularly if households can’t take on significant debt. These changes tend to be national rather than regional trends and often affect owners and renters in equal measure. As housing is a growing sector of China’s economy – with some sources describing it as “ballooning” even though many of the available homes remain unoccupied – it’s important to understand what drives housing prices in China.
Dr He and colleagues’ model was based on an assumption that families in a given economic environment conform to the assumption of a rational economic person, that is, they act rationally and with complete knowledge, seeking to maximise personal utility and satisfaction. As such, for families, general commodity and housing consumption are two key factors for consideration. Furthermore, as an investment product, property in China has great value-added capabilities. Although when current housing prices rise, families are likely to curtail their consumption of housing, if prices are expected to increase in the future, they’re more likely to choose to increase real estate consumption in the present. This is often offset by lowering of the value of average consumer goods, which frees up some investment capital that is not spent on daily necessities.
In addition, the researchers considered manufacturing constraints noting that manufacturers need to make decisions regarding product quantities, factor inputs and product prices as well as the structure of assets and level of dividend payments. In general, manufacturers seek to maximise profits, while considering demand for labour, capital stock, and specific level of technology.
Finally, Dr He’s group introduced the identity of the national income so that consumption (family) and production (enterprise) are united together. To simplify the model, family income was assumed to be fixed. The output of a city was composed of capital endowment and family labour. Excessively high land lease payments will lead to an increase in house prices while a high transfer cost per capita will have a crowding-out effect on per capita income. If the gap between the city prices and family income becomes too large, the assets of the family will flow to the lower price city.
Looking for clarity
In their work, Dr He and colleagues wanted to separate impact from each of the variables and shed more light on what drives housing consumption in China. To achieve this, they used the dynamic general equilibrium theory, which was developed to understand how an economy may function as a whole rather than as a collection of individual market phenomena.
The theory proposes that, over the long term, free markets tend toward equilibrium, which means that, assuming no external influences, supply will tend to equal demand resulting in a balance of economic forces. The dynamic general equilibrium model that derives from the theory estimates how the overall economy of a country might react to a change.
In addition, the researchers applied spatial panel data analysis. This is a statistical method used in econometrics to examine datasets with a particular reference to a specific time and place from where the data originates.
Assumptions and hypotheses
The analysis aimed to test three hypotheses. First, that real estate consumption is related to expected future house prices; if prices are expected to increase, real estate turnover increases. Second, that the rate of unemployment has a negative impact on real estate consumption. Third, that per capita GDP has a positive impact on real estate consumption.
The analysis included real estate sales, house price levels, individual income, China’s urbanisation rate, government fiscal expenditure, employment rate, import-export index, and coal consumption as a measure of GDP. Data was derived from the national statistical yearbook and included 30 administrative provinces in China. Time cut-offs for the analysis were 2004, that is, the beginning of the Chinese real-estate marketisation process, and 2015.
Buyers go on price
The territory of China is vast and so are the disparities in real estate development between provinces, including price fluctuations. Nevertheless, Dr He and colleagues’ analysis shows that housing prices have a significant role in promoting housing consumption, at least in the short term. Equally, GDP also has a significant positive impact on real estate consumption, while the consumption itself has positive but non-significant effects on GDP. In addition, house prices have a significant positive impact on sales, but sales impact house prices only in the short term (first and second period). This study also suggests a significant positive interaction between economic growth and sales. All these things combined, the authors predict that the rapid economic growth will increase residents’ enthusiasm for property investment in the short term. Though, in the long term, this enthusiasm is likely to cool down resulting in a wait-and-see situation. Lagged sales will likely have a positive impact on current sales, which has been the real situation in China, and optimism based on the sales on a previous period will increase purchasing desire of the current period.
Overall, the results of this study suggest that as the economy in China continues to grow, demand for housing is likely to increase although house prices will ultimately determine the decision to buy.
- Du Z, Zhang W, He Y. (2018). What drives housing consumption in China? – Based on a dynamic optimal general equilibrium model and spatial panel data analysis. Journal of Economics and Political Economy, 5(1):1-26.
Dr Yiming He investigates the driving forces behind housing consumption in China.
This work was supported by National Ten Thousand Outstanding Young Scholar Program(Grant Number: W02070352) as well as Key Project of National Natural Science Foundation in China (Grant Number: 71742003)
- Weikum Zhang and Zhipeng Du
Dr He is a South China Agriculture University PhD, Professor and PhD Advisor, who won the Ten Thousand Program of the national youth talent support project, national natural science twice, national social science three times, and China Scholarship Council visiting scholar program. He has published more than one hundred papers on Man and the Economy and Energy Economics. Dr Yiming He is also the Ronald Coase Institute Young Fellow, Hong Kong Baptism University Adjunct Researcher and The University of Texas Visiting Professor.
Prof Yiming He
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