The Impact of Changes in Government Macroeconomic Policy on the Housing Market

The housing market is undoubtedly connected to the economy; to an extent, it is regarded as a sector that significantly influences the market. According to Antonakakis and Floros (2016), the housing market (prices) has always played a significant role in determining macroeconomic policies in economic policies and economic research. For example, economic studies have established that an increase in housing prices or residential properties’ value also increases a country’s combined GDP (Bouchouicha and Ftiti, 2012). In the same context, previous studies have also revealed that, across Europe, nations have been experiencing record high housing prices relative to price-to-income ratios (Simo-Kengne et al., 2013). Essentially, economic research indicates a long-term interaction between macroeconomic variables and the housing market, specifically because the housing prices impact the performance of financial systems and business cycles dynamically (Nneji, Brooks and Ward, 2013). With the exact comprehension, the housing market is often used as an indicator to predict economic performance. From a different viewpoint, the housing market has also been established to be a source of financial crises, mainly because of the increased vulnerabilities associated with the banking sector (Kishor and Marfatia, 2017). Increased housing prices tend to promote consumer spending and thus stimulate economic growth; however, it adversely impacts the living standards for consumers who do not have residential properties (Tupenaite, Kanapeckiene and Naimaviciene, 2017). There is a vivid connection between macroeconomic variables and the housing market; macroeconomic policies are relevant determinants for housing prices.

In recent years, countries across Europe have been experiencing increasing housing prices. Following the great recession experienced in 2008, both policymakers and economists are convinced that the high housing prices are influenced by the interaction of the market and macroeconomic variables and policies (Zhang et al., 2016). In the same context, Tupenaite, Kanapeckiene and Naimaviciene (2017) clarified that the housing market plays a substantial role in shaping the monetary and fiscal policies and their interaction with other macro-economic variables. An empirical study conducted by Ghent and Owyang (2010) further noted that previous studies have evidenced that changes in housing prices play a crucial role in driving business cycles, with potentially detrimental effects on the economy. Additionally, economists widely recognise that the housing market, especially in developed nations, such as the UK, has experienced rapid growth because of favourable macroeconomic conditions (Kishor and Marfatia, 2017). Many studies have established that that drastic fall in housing prices during the financial crisis and the upward trends experienced later in 2012 was caused by favourable monetary policies implemented to stabilise the housing market (Bouchouicha and Ftiti, 2012; Nneji, Brooks and Ward, 2013).

Statement of the Problem 

In the UK, purchasing a house is one of the most significant and single economic transactions made for a majority of individuals; it is with the exact comprehension that there exists a strong public reaction to fluctuations of housing prices, relative to other goods and services in the economy (Bahmani-Oskooee and Ghodsi, 2016). In the UK, significant price changes have been experienced over the last few years; residential house prices have been observed to have risen by about 40%; compared to the total increase in the consumer price index, which is just over 5% over the recent past (Fraser, Hoesli and McAlevey, 2012). Consequently, considering the large proportion of economic value derived from the housing market, dramatic price changes in the housing market significantly affect general consumer behaviours (Manganelli and Tajani, 2015). With the exact comprehension, most economists view the housing market development as necessary for the wider macroeconomy and how the price fluctuations impact government macroeconomic policies and activities (Bahmani-Oskooee and Ghodsi, 2016). In the same context, there has also been little to no recent research delving into their macroeconomic policies on the housing market, house price movements or how the changes in residential house prices influence macroeconomic activities in an economy.

Research Aims and Objectives

The housing market is an indicator of economic growth and plays a significant role. Consequently, the study aims to assess how changes in macroeconomic variables influence the housing market’s growth and housing prices. The study aims to critically assess the effects of macroeconomic policies on the housing market. Specifically, the study is focused on revealing:

  • What is macroeconomic policy, and what are its aims and objectives?
  • What are the tools of macroeconomic policy (monetary and fiscal policy), and how has the implementation of these changed in recent years?
  • What has been the impact of these changes on the housing market?

Literature Review

The Link Between the Economy and the Housing Market

According to Vandenbussche, Vogel and Detragiache (2013), the cyclical nature of the housing market and properties is an essential topic in the economic discussion because a large proportion of the household populations and their respective wealth are invested in residential housing properties. In the same context, Beltratti and Morana (2010) further supported that the housing market represents more than 50% of the economy’s fixed capital stock in the UK. With the same comprehension, the economic theory also agrees with the findings, citing that wealth is one of the primary drivers of aggregate consumption in an economy; meaning a slump in the housing market is highly likely to be accompanied by a decrease in household consumption – this adversely impacts economic growth (Beltratti and Morana, 2010; San Ong, 2013). From a holistic perspective, Adams and Füss (2010) further posited that the behaviour of the housing market is influential in the economy because the housing prices impact the lending portfolio of financial institutions, such as commercial banks. In agreement, Zhang et al. (2016) and Cellmer, Cichulska and Bełej (2021) further explained that a drastic increase in mortgage rates often tails declines in housing prices – it’s a default response that negatively influences commercial banks’ profits. Understandably, the reduction in profitability of financial institutions and other lending institutions often leads to banks’ failure, followed by a slowdown of economic activities and growth rate.

Macroeconomic Policy and Housing Market

The majority of previous studies indicate that interest rates, a monetary policy variable, are an important macroeconomic factor affecting the housing market (Panagiotidis and Printzis, 2016; Li and Chand, 2013). According to Al-Masum and Lee (2019), macroeconomic factors, such as employment and interest rates, are significant variables that the government can influence housing prices and economic growth. In agreement with the findings, Zhang et al. (2016) further deliberated that, over time, the housing market has evolved to become more sensitive to interest rates changes, probably because of financial liberalisation in the UK and other European nations. In a comparable study, Bahmani-Oskooee and Ghodsi (2016) supported the findings, revealing that the interest rates are important variables in the housing market and changes in the macroeconomic variable are influential in housing prices. Glindro et al. (2018) further resonated that, in line with the established findings, over the recent past, the sensitivity of the housing market to interest rates, in the long run, tends to intensify when housing prices are relatively low. In a comparable finding, Fraser, Hoesli and McAlevey (2012) also pointed out that housing prices are even more sensitive to interest rate changes in large cities and developed nations, where value grows faster than in underdeveloped countries. In a bid to explain the literature findings, Cellmer, Cichulska and Bełej (2021) elaborated that changes in interest rates tend t negatively influence aggregate demand of the housing market because of their effects on the costs for financing real estate construction and mortgage rates. Overall, the literature consensus that interest rates, a monetary policy variable, are crucial policies that the government can employ to influence housing prices and economic growth.

Other studies also found out that, besides the interest rates, the price dynamics in the housing markets are also influenced by other macroeconomic factors. Manganelli and Tajani (2015) attributed that, in the short run, positive money shocks affect the housing price positive money shocks positively influence the housing prices in the short run. Manganelli and Tajani (2015) also reiterated that inflation and not the changes in interests rates affect the prince-rent ratios, economic indicators for a likely economic downturn in the future. From a different perspective, while focusing on establishing the correlation between macroeconomic changes and international housing prices among developed countries, Fraser, Hoesli and McAlevey (2012) found macroeconomic shocks cause more than 40% of fluctuations in residential housing prices. Chauvet and Senyuz, 2016 also provided additional evidence indicating that macroeconomic variables linked to the housing market include economic activities such as the level of money supply, employment rates and industrial production; all these factors influence the demand for residential houses and their prices. Essentially, the literature is further indicative that, besides the interests rates, other macroeconomic factors such as money supply and employment rates are significant macroeconomic variables that impact the housing market, specifically, the demand and prices of residential houses.

Rangel and Ng (2017) and Li and Chand (2013) also showed that monetary policy shocks often lead to house prices fluctuations in the long run in most European nations. The conclusion is based on the understanding that macroeconomic variables and monetary policy on the housing markets like money supply, mortgage rates, and employment rates inevitably impact the prices and demand in the long run. In agreement with the findings, Chen, Cheng and Mao (2014) also supported that inflation, employment rates and mortgage rates are the most significant and practical explanatory variables that can explain the fluctuation of actual house prices in the long run. To elaborate on the understanding, Manganelli and Tajani (2015) resonated that strict monetary policies play a crucial role in reducing housing market activities; however, it does not influence house prices. The author also clarified that real estate prices and residential housing productions react to economic shocks arising from housing demand and supply (Manganelli and Tajani, 2015). From a different viewpoint, Bahmani-Oskooee and Ghodsi (2016) also analysed the connection between money supply, housing prices, private sector loans, and economic activities. An increase in money supply significantly impacts housing prices, increasing the number of loans acquired privately. From the literature discussion attempting to elaborate on the connection between macroeconomic variables and the housing market, it is evident that macroeconomic policies, both fiscal and monetary policies, significantly influence the housing market, particularly the prices, demand and supply, mortgage and employment rates, however, in the long-run.

The nexus linking monetary policy changes and house prices has also been widely investigated. For instance, while exploring the role of monetary policy changes on house prices, Granziera and Kozicki (2015) established that unexpected interest rates drastically impact house prices. The comprehension is that when the monetary policy changes are employed to cause a 1% increase in interest rates, the resultant effects lead to a 3-5% decrease in housing prices (Granziera and Kozicki, 2015). In yet another relevant study, Chen, Cheng and Mao (2014) revealed that credit supply shocks constitute a significant factor that explains house prices fluctuations because of the effects on household loans, house prices and credits. Interestingly, besides the correlation between macroeconomic policies and the housing market, the literature also indicates that money has significant impacts on house prices but little effect on household credit loans.

Literature Gap

From the literature discussion, it has been established that very few studies have focused on investigating how the housing market and the associated residential houses prices relate to the economy, primarily because of insufficient, irregular and lack of reliable housing market data. It has also been observed that there is little to no recent research on the interaction between macroeconomic activities and the housing market. On both macro and micro levels, most studies conducted on the subject matter are based on secondary sources, mostly reviewing previous literature or case study analysis. Accordingly, with the identified gap and established finding that the housing market is a beneficial sector in economic growth, more primary studies should be conducted to understand further the causality of mortgage rates and fluctuations in nominal house prices.


Research Design

Research design is a sketch of a research study that showcases the researcher’s activities from writing the hypothesis and its underlying implications to analysing the collected data. A research design is a practice of organising conditions that involve collecting and analysing data to focus on combining research purpose to relevance with the economy in research procedure (Bell 2022). This chapter focuses on the methodology applied to conduct the research and collect data. It examines the study population and sample, research design employed, data collection, the analytical model used and data analysis.

The research applied the descriptive method as a research design, and they also used the secondary data analysis method due to the data availability. This research method is satisfactory where the research explores to portray and describe the attributes of a situation, an event, community, and a population (Mohajan 2018). The research also applied regression analysis to link government macroeconomic policy variables and the housing market. It was impossible to conduct primary research in this study because the information was readily available from the relevant organisations. In addition, there is a likelihood of collecting misleading information if the sample is not large enough (Karale 2020). The requirement of an extensive sample in primary research made it difficult to apply this method.

Data Collection Methods 

The study was conducted over a time frame of 10 years. The relevant information was gathered from secondary data such as property reports and magazines, documentation from previous studies, data from Housing Finance Corporation (THFC), journals, and data from the finance banks. The study applied documents and records data collection methods to gather information about various organisations. The information gathered included inflation rates, interest rates, real income, growth of GDP, population growth rate, and employment rate.

Data Sampling

Sampling is essential in research as it is the main factor determining the study result’s accuracy. The study applied systematic sampling to ensure an adequate sample size of the gathered data. The method makes it easy for the researcher to analyse the population or sample by collecting reliable information. This technique was employed to ensure only relatable information was available for research. The researcher calculated the power of the sample size by selecting the relatable information from among the information gathered.

Data Analysis

Data analysis is the practice that follows after the relevant data has been collected and culminates in the stage of processing and interpretation (Raskind et al., 2019). The regression analysis model was applied to determine how government macroeconomic policy variables affect the housing market. Regression analysis was expounded by Green (1997), and its formula is:

Y = a + bX1 + cX2 + dX3 + ϵ

Incorporating the variables into our study, we can apply the formula as seen below:

HM = βo + β1 INTR + β2GDP+ β3LMS + β4 INFR + ε

In this case, HM= Housing Market (monthly composite property)

β = Regression Coefficient

GDP- Gross Domestic Product

INTR- Bank of England Average Interest Rates

INFR = Inflation Rate

LMS = Level of Money Supply

ε = the error term.

Ethical Considerations

The researcher sought informed consent from the organisations involved to ensure ethical considerations in data collection. In addition, the researcher gathered information that was relevant to the topic under research. The organisation took part in giving information as a way of voluntary participation. The researcher also assured them of the confidentiality of the data collected. Ethical considerations are essential in research as they are significant in promoting the study’s objectives, encouraging values needed for collaborative work such as fairness and mutual respect and boosting public trust in the research. In addition, research ethics support crucial moral and social values, which increase the authenticity of the collected data.

Findings and Discussion

This chapter discusses the interpretation and analysis of the collected data. The study used descriptive and multivariate regression models to determine how GDP, money supply, inflation, interest rates impact the housing market. The study results have been presented in two sections, including descriptive statistics to make it easy for the researcher to determine statistical findings derived from the characteristics of the data and hypothetical statistics to determine the link connecting the independent and dependent parameters.

Descriptive Statistics

The segment focuses on the descriptive statistic of all the data collected to present the research finding. This information can be illustrated in a table as shown below:

N Minimum Maximum Mean Standard Deviation
HM 10 16.18 17.04 16.674 0.3206
INTR 10 6.5 15.44 9.075 2.36876
GDP 10 19.5 19.91 19.708 0.13164
LMS 10 19.91 21.41 20.688 0.53913
INFR 10 3.91 26.19 11.116 6.24547


Housing market (HM), gross domestic products at the market (GDP), monthly average interest rates (INTR), inflation rate (INFR) and Level of monthly supply (LMS) were applied in the research. The study considered their minimum, maximum, mean and standard deviation. Going by the results, it was found that there was a mean of 9.075 for INTR, 16.674 for HM, 19.708 for GDP, 11.116 for INFR and 20.688 for LMS. The findings show a standard deviation of 0.3206 for HM, 2.36876 for INTR, 0.13164 for GDP, 0.53913 for LMS and 6.24547 for INFR.


HM  Pearson Correlation 1 .797** -.664** .784** .881**
Sig. (2-tailed) 0.000 0.001 0.000 0.000
N 10 10 10 10 10
 INTR Pearson Correlation .797** 1 -.214 .347 .894**
Sig. (2-tailed) 0.000 0.353 0.292 0.000
N 10 10 10 10 10
 GDP Pearson Correlation -.664** -.214 1 .684** -.413
Sig. (2-tailed) 0.001 0.353 0.001 0.235
N 10 10 10 10 10
LMS Pearson Correlation .784** .347 .684** 1 .612**
Sig. (2-tailed) 0.000 0.292 0.001 0.002
N 10 10 10 10 10
INFR Pearson Correlation .881** .894** -.413 .612** 1
Sig. (2-tailed) 0.000 0.000 0.235 0.002
N 10 10 10 10 10


The researcher applied the Pearson correlation to determine the correlation between the various variables. Going by the results of the correlation examination between real estate prices and other variables such as level of money supply, inflation rate, interest rates and GDP, it was established that there is a robust connection linking interest rates and the housing prices, recording 0.797 as its correlation coefficient. Additionally, there exists a robust negative correlation linking GDF and the housing market, evident with a correlation coefficient of -0.664. A strong positive relationship was also found between the level of money and the housing market with a correlation coefficient of 0. 784. The same strong positive relationship was found between inflation rates and the housing market, recording a correlation coefficient of 0.881.

Discussions of Findings

In agreement with the study findings, there is a strong positive connection linking interest rates and real estate prices. Bahmani-Oskooee and Ghodsi (2016) echoed this finding, revealing that the interest rates are essential variables in the housing market and changes in the macroeconomic variable that impact housing prices. In a real-world scenario, prices are anticipated to change, and this expectation of changing is related to interest rates which affect the housing market. In addition, interest is directly proportional to the cost of borrowing capital within a specified period. In an ordinary business situation, interest rates significantly impact the affordability of housing and thus make it difficult to invest in real estate. Consequently, a surge in interest rates leads to high borrowing costs. As a result, mortgage repayments are likely to be higher, thus making it challenging to own homes. This notion agrees well with Cellmer, Cichulska and Bełej (2021) and Zhang et al. (2016), who have highlighted that a substantial rise in mortgage rates leads to lower housing prices. The results established a robust negative correlation linking GDP and housing prices. GDP is a well-known indicator due to the relationship between interest rates and government macroeconomic policy.

According to the findings, the study established that all the variables, mostly government macroeconomic policies, impact the housing market. This position was echoed by Li and Chand (2013), expounding that inflation rates, GDP, and interest rates are significant predictors of the housing market. Al-Masum and Lee (2019) research on the predictors of the housing market applying multivariate regression and descriptive models discovered a considerable connection linking the GDP, interest rates and money supply to the housing market.

According to the findings, it was established that there exists a robust positive correlation linking home prices and the money supply. This condition is brought about by the rise in money supply, which results in more significant inflation uncertainty leading to a severe impact on the housing market, thus increasing the prices(Panagiotidis & Printzis, 2016). An excessive rise in the money supply means the likelihood of an inflationary environment, which negatively impacts investment due to increased discount rates leading to increased costs.

The study established a strong positive correlation linking the level of money supply and the inflation rate. Cellmer, Cichulska and Bełej (2021) elaborated that with a reduction in the inflation rate, the investment in real estate will increase. In addition, a rise in housing investment results in a decrease in prices. A rise in the inflation rates increases the cost of acquiring capital, and this condition leads to lowering the country’s capital formation, thus negatively impacting investing, resulting in increased prices. Various studies on the effect of inflation rate on real estate investment have established that inflation positively affects house prices.

Conclusion and Recommendations

After analysing the data collected, discussions, recommendations, and conclusions were made. The study’s main objective was to establish the effect of adjustments in government macroeconomic policy on the housing market(prices). According to the descriptive statistics, it was realised that there was a mean of 9.075 for INTR, 16.674 for HM, 20.688 for LMS, 19.708 for GDP and 11.116 for INFR. House marketing (HM) had a standard deviation of 0.3206, GDP had 0.13164, INTR had 2.36876, INFR had 6.24547, while LMS had 0.53913. Financing banks’ monthly average interest rates (INTR) were found to have the highest standard deviation and thus the most significant variation from the mean.

Using the regression analysis, it was found that there exists a link between interest rates and the housing market. Consequently, the rise in the interest rates would automatically result in to increase in home prices. According to the study, an increase in the GDP results in a reduction in home prices. Consequently, when there is an increase in money circulation, there is a corresponding rise in home prices; a surge in inflation rates increases home prices. Generally, the inflation rate impacts home prices; a robust negative correlation exists between home prices and GDP.


According to the research, it is fair to conclusively point out that government macroeconomic policies such as inflation rates, GDP, interest rates, and money supply significantly impact the housing market. For instance, increasing interest rates will make it difficult to afford homes. As the interest rates rise, the borrowing costs also increase, leading to the demand for new homes going down. This condition is also occasioned by the high mortgage repayments, which reduce housing affordability due to the higher prices. The negative relationship between GDP and home prices is brought about by GDP being a significant indicator due to the relationship between government macroeconomic policies and housing prices. It has been found that a rise in GDP leads to a surge in investment in homes, leading to a rise in the supply of homes, therefore making the price of housing go down.

Policy Recommendations

In policy recommendations, the government should implement monetary policies that will regulate inflation and interest rates through the central bank. The policies should reduce the cost of investing and borrowing, eventually leading to the affordability of investment in the real estate sector, increasing housing supply, thus reducing prices. The government can also implement policies that will ensure quality and affordable housing. The strategy can be achieved by inviting companies with a long history of providing cheap and high-quality housing to invest in the country. To control the level of money supply, the government, through finance banks, should promote economic growth and regulate excessive price fluctuations.

Regulating the level of the money supply is a good way of controlling inflation and ensuring there is stability in interest rates, prices and exchange rates. The stability of these variables safeguards the purchasing power of the country’s currency, promoting economic growth and investment. An increase in economic growth will lead to more people resorting to investment in real estate, thus reducing housing prices.

Recommendations for future research

According to the study, there is a strong connection linked housing, economics and GDP; thus, it is reasonable to conduct more research on the connection between GDP and housing prices. GDP is a strong indicator of the economy of a country. A further study can be conducted on other factors impacting the growth of housing prices, such as how the cost of finance affects the housing sector. Interest rates directly affect the cost of financing; therefore, the study will focus on the impact of the cost of financing on the development of the housing sector. In addition, research can be conducted to establish the impact of population growth on housing investment in a country.