The Relationship Between Unemployment And Housing

Unemployment and Housing

Question:

Discuss about the Impact of Unemployment on Housing in Australia.

Unemployment is a state where a person that is qualified to work, and is actively seeking work/ employment, is not able to find work. Unemployment is measured using the unemployment rate; the unemployment rate refers to the total number of unemployed persons, divided by the number of persons within a given labor force jurisdiction. In general, housing refers to the accommodation of people which entails an authority or members of the public planning to provision accommodation to the society/ members of the public. In the month of November 2017, the Australian unemployment rate was 5.4%, remaining unchanged from the 5.4% rate experienced in October. This, however, is a decline from the average rate of 5.6% experienced between June and August of 2017. In the past two years, there has been a general trend of decline in Australian home sales, after a steady increase from 2012 to mid-2015, from where new house sales started to decline. The third quarter of 2016 saw strong growth in the sales of new homes, from 7094 houses in 2016 to 7525 in November, and 7543 in December. This arte declined to 7379 new house sales in Jan 2017 and 7392 in February, before declining to 7313 in March. April saw a rise to 7369 houses, peaking in May at 7450 houses. June saw a sharp decline to 6934 houses being sold and a further decline to 6678 houses in July 2017. August saw an increase to 7285 houses, before declining to 6841 houses being sold.  In the backdrop of the statistics on unemployment and house sales; this paper seeks to establish any connection between the two

1. To evaluate and analyze the trend of new houses sales in Australia over a five year period
2. To evaluate and analyze the rate of unemployment in Australia in the same period
3. To establish, using scientific and statistical methods, if there is a correlation between the rate of unemployment and housing in Australia

• Is there a correlation between the unemployment rate and housing in Australia?
• How significant is the correlation between the rate of unemployment and housing in Australia, and is this correlation strong or weak?
• Value of research

The two aspects; unemployment and housing may be interrelated; however, this needs to be scientifically established and ascertained through research. Establishing the correlation between the two will be useful to investors, developers, and planners on how to manage the housing situation in the context of the unemployment rate. The findings will increase the existing body of knowledge on how the macroeconomic factors of unemployment rate affects the general economy, with housing being used as an indicator.

Research shows, using a model, that high levels of unemployment are associated with higher owner occupation rates, which is paradoxical, given that home owners are usually unemployed less often. The housing tenure choice impacts moving costs, and therefore regional mobility and unemployment (Dohmen, 2005). An increase in taxes and the unemployment benefits does not result in a strong decline in mobility; however, it results in increased unemployment in standard models, such as the Mortensesn and Pissarides model. Further, taxes and housing regulations that have an impact on commuting costs have an effect on mobility rates (Rupert & Wasmer, 2012). According to the Oswald hypothesis, inferior outcomes in the labor market are linked with home ownership, yet research shows otherwise. Home ownership hinders the tendency to move for job reasons; however, it improves chances of getting local jobs. The hazard rate into unemployment is much higher for homeowners, so that the correlation between unemployment duration and home ownership, which contradicts the Oswald Hypothesis even though the Oswald concept that mobility is hindered by home ownership (Munch, Rosholm, & Svarer, 2006). Research shows that while there is lower likelihood of homeowners being unemployed, their wages are lower, compared to those that rent houses, if all other factors are kept equal. Further, higher regional rates of home ownership is associated with higher wages and a higher probability of individual workers being unemployed (Coulson & Fisher, 2009).  

Correlation between Unemployment and Housing

Out of the various components of GDP, residential investments by far, offer the best early warning signs of an impending economic recession, and this can be proven by data from the US, where out of the eight recessions experienced after the Second World War, all have been preceded by significant problems in the housing and consumer durables (Learner, 2013). The propagation of changes in the housing sector/ housing market is governed by three main factors, namely income effects, wealth effects, and through the financial markets.  In an economy like the US, when the decade long housing boom started declining, the small wealth effects were transmitted into the economy; however, income effects had a greater effect the rest of the economy, while market effects were be substantial (Case & Quigley, 2008).  The findings demonstrate that unemployment that directly impacts/ influences incomes, have a very significant effect on the housing sector. Unemployment has a significant impact on the real estate market of an economy; and this impact can be huge. A high unemployment rate implies that many more people are unable to afford to buy houses/ homers; this in turn discourages developers from developing new real estate (houses). The impact is cyclical because when developers are not building new houses; more people (construction workers) lose their jobs and become unemployed, leading to an increase in the general unemployment rate.

Another effect of high unemployment on housing is that it drags demand down, because of the forces of demand and supply, low demand results in deceased prices and homeowners are discouraged form placing their homes on to the market (Griffith, Harrison, , & Macartney, 2007). In the long run, the real prices for houses are positively and significantly determined by the consumer price index and the real disposable income. The real mortgage rates, the housing stock, equity prices, and the unemployment rate significantly and negatively affect the long run prices of houses (Abelson, Joyeux, Milunovich, & Chung, 2005). Research on the UK housing sector on the relationship between house prices and unemployment shows that there is a significant negative correlation between them, such that high unemployment results in reduced house prices. Further, the research established that there is no real relation between unemployment and regional house prices (Qingyu, 2010). In a thick market structure, an increase in the rate of unemployment has the effect of creating a thinner market; this result in the transactions volume and the prices of houses both declining more, than would happen in a thick market effect. A model shows that a 3% rise in the unemployment rate results in transaction volumes declining by 9.9% while the prices of houses decline by 7.7% (Gan & Zhang, 2013)

The research will be undertaken by first getting the proposal topic approved and making changes based on lecturer feedback. From this point, a research design suitable for the research objectives will be developed. Sources of information to be used in the research will be identified and evaluated, before commencing the research. The collected data will be evaluated and analyzed using various mathematical, graphical, and statistically models, before discussing the findings and making a conclusion. A draft research report will then be written and consultation sought from the lecturer, before changes are made and the final draft report generated and presented.

Because this research will be evaluating historical data, secondary data collection methods will be used. Specifically, national data on unemployment and housing in Australia will be obtained online and used for the purposes of this research. This method of data collection entails obtaining data collected initially by another party, but which are suitable for the purposes of a current research, and where primary data collection would be impossible.

The data will be analyzed using mathematical and statistical models; the aim is to establish if there is a relation between unemployment and housing in Australia. Specifically, after collecting and cleaning the data, the two variables (Housing and unemployment) will be tested for correlation using the correlation coefficient. The findings will then be analyzed for variance and reliability through a Student T test to ensure the sample size gives valid results 

The following is the list of tasks to be undertaken in order of progression to complete the assignment

For the literature and theoretical reviews, this paper will obtain data from peer reviewed scholarly sources. The empirical (quantitative) data will be obtained from respective government and other body’s websites on the unemployment rate and housing numbers in Australia.

References

Abelson, P, Joyeux, R, Milunovich, G. E. & Chung, D. (August 01, 2005). Explaining House Prices in Australia: 1970-2003*. Economic Record, 81.

Case, K. E., & Quigley, J. M. (June 01, 2008). How housing booms unwind: Income effects,

wealth effects, and feedbacks through financial markets. European Journal of Housing Policy, 8, 2, 161-180.

Coulson, N. E., & Fisher, L. M. (May 01, 2009). Housing tenure and labor market impacts: Th search goes on. Journal of Urban Economics, 65, 3, 252-264.

Dohmen, T. (August 01, 2005). Housing, mobility and unemployment. Sage Urban Studies Abstracts, 33, 3.)

Gan, L., & Zhang, Q. (2013). Market Thickness and the Impact of Unemployment on Housing

Market Outcomes (pp. 34-35). Cambridge: National Bureau of Economic Research. Retrieved from https://www.nber.org/papers/w19564.pdf

Griffith, R., Harrison, R., & Macartney, G. (March 01, 2007). Product Market Reforms, LabourMarket Institutions and Unemployment. The Economic Journal, 117, 519.)

Learner, E. (2013). Housing in the Business Cycle, In the Evidence and Impact of Financial Globalization, pp 589 – 643

Munch, J. R., Rosholm, M., & Svarer, M. (January 01, 2006). Are Homeowners Really More Unemployed?. Economic Journal London-, 116, 514, 991-1013.

Qingyu, Z. (2010). Regional unemployment and house price determination (pp. 16-17). Munich:

Munich Personal RePEc Archive. Retrieved from https://mpra.ub.uni-muenchen.de/41785/1/MPRA_paper_41785.pdf

Rupert, P., & Wasmer, E. (January 01, 2012). Housing and the labor market: Time to move andaggregate unemployment. Journal of Monetary Economics, 59, 1, 24-36.

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