Analysis of the Link Between American Asset Prices and the Business Cycles - Example

Name: Professor: Title: Date: EXECUTIVE SUMMARY This report takes an in-depth look into the analysis of the link between American asset prices and the business cycles. It further uses the data derived from this analysis to predict, or rather forecast the anticipated growth of the United States’ economy. Undeniably, with the turbulent economic cycles, it has become increasingly clear throughout world economies that there is a need to use asset prices as benchmarks and indicators of the performance of the economy. The prices of assets are especially critical in predicting future changes in economic variables such as interest rates and more often, inflation and output figures. The report embarks on the use of econometric models to analyze the extent to which certain economic indicators affect asset price. ASSET PRICES AND THE BUSINESS CYCLES IN THE UNITED STATES OF AMERICA. INTRODUCTION. While the fundamental relationship between assets and output is somewhat empirically arduous to ascertain, it is still possible to safely assume that asset prices are reflective of current expenditures and therefore act as leading indicators in determining variations in future economic activities. By looking at the variation model hypothesis, it becomes evidently clear that in as much as empirical knowledge dictates that determination of the discounted value of dividend growth expected reflects the current price, the actual link between asset market and the future and current output barely exists (Koop, 27). In the study of the United States Asset Market, it important to carefully asses the various asset market indicators and the extent to which they can be reliably used to account for the various macroeconomic fluctuations. IDENTIFYING AND ANALYZING THE LINKS The fact that the U.S market is a multistate nation means that cross state heterogeneity, dependence, and asset markets are interconnected. The role that the Gross Domestic Product plays in combating changes in the asset market prices cannot be overlooked. While the dynamics in business cycles may fail to determine fluctuations in t asset prices, any over-heating of the economy automatically results in the future GDP of the United States of America getting volatile (Demary, 53). Moreover, the economic activities in the American market greatly affects house prices. The revenue received by household’s increases as a result of a shock on the output in the economy which consequently leads t firms increasing their demand for labor. Using the same analogy, when the economy is at a recovery and doing well, an individual with a job is easily able to obtain mortgages at relatively lower interest rates and this ultimately leads to a higher demand for housing therefore triggering a rise in the house prices. When the trend in stock prices is subjected to the same model, we find that a well performing economy may indicate it’s the right time to purchase stock, leading to a rise in the stock prices (Koop, 43). All these economic indicators point out to the reality that the linkage between asset prices and output should be analyzed from an empirical point of view. In the US, the two widely held assets are stocks and housing. Data indicates that stock wealth constituted 52.06% of the total net worth in US households while housing wealth constituted 37.77% of the total net worth in US households (Imf.org). An understanding of this relationship between incomes and asset prices is paramount as it helps in coming up with relevant policies in the event of shocks that may occur to any of the variables. Essentially, there are many empirical studies that have been done covering on the area of incomes and asset prices with a major leaning tending towards showing that major portfolio decisions embed the probability of either bring higher expected payoffs when the interest rates are relatively stable and lower payoffs during economically volatile markets (Hyman, 45). Undeniably, the great recession in 2008 added in more critical insights on the role that different market variables play in the predicting the business cycles. As such, important indicators such as the credit-output relationships were distinguished to be among the most fundamental variables contributing to the observed long run cycles in business progression. The findings reflect that business cycles and credit between 2 to 8 years were acceptably more volatile that those observed in a span of 9 to 20 years’ time (Hyman, 69). Apart from the credit-output relationships, other critical variables that also come to play in influencing business cycle patterns include investment expenditure as financed by companies. The studies intimated that 45% of American companies had alternative sources of financing other than debt finance. This means that for the majority of the American population, actual loans are a major source of financing and we can thus analyze the relationship between the economic activity growths and link it with the business cycles (Demary, 87). The link here, from data shown from Federal Reserve releases show the existence of a positive relationship between the growth in activities of the United States Markets and credit. The growth is computed in frequencies that are linked to cycles, indicating strongly that credit does predict cycles in economic activity are therefore a great contributor to the performance of organizations in making investment decisions. DEVELOPING A FORECASTING MODEL FOR ASSET PRICES. The analysis carried out in this paper takes into consideration the 52 states comprising the USA and covers data collected over the period ranging from 1976- 2013. The data on house prices are deduced from the United States Federal Housing fiancé agency and the prices or stock are readily available in the Federal Reserve releases, and so are the data on Gross Domestic Product and output (Newyorkfed.org). In econometric analysis of the data, it was important that the data be deflated to the Consumer Price Indices in order to obtain accurate figures of their corresponding prices. Due to the division of the United States economies, the analysis of the data was split between industrial and agricultural states, with the computed standard deviation in the variables ranging between 15.23 to 40.57 for industrial states and that of agricultural states ranging from 16.18 to 60.38 (Imf.org). While there are many techniques and models that can be used in analyzing how effective these variables are effective in determining business cycles, the model selected for this study is on the use of the variable interest model to highlight the performance of the of interest rates and their influence on business cycles. It might have been possible to combine the various variables such as the Gross Domestic Product and the output, become considering the great significance the interest rates play on the performance of the United States economy, primarily the impact of changing interest rates by the Federal Reserve, this variable was the most appropriate. Moreover, data on changing interest rates in the United States for the last 30 years was readily available in the WEO websites and the Federal Reserve Database. The variable interest model is one of the most valuable tools used in forecasting. In the model that we’re going to develop in evaluating the relationship between the interest rates and the asset prices over the span of years, it’s going to embark on determining the fluctuations over the given time contributable to the various factors. From the graph above we observe a slow but steady decline in the federal interest rates over the last eight years. This is attributable majorly to the need for increasing investments. As indicated in the use of this model, the interest rates have a direct impact and link on the business cycles. A case in study is the great economic depression that occurred in 2008. We find that to keep the interest rates at very high levels has an impact on the performance of the economy. This is further augmented on the shifting depreciation of asset prices as interest rates are increased. From the capital asset pricing model, it is well presumed that the interest rates have been adjusted for inflation. We do note that during periods where the interest rates are low for a long time, such that the interest rates on financial assets inclusive of mortgages, there is a gradual over purchasing and eventually, the asset prices rise. If these increases in the asset prices remains unchecked, it eventually leads to a great economic crash, as evidenced on the 2008 housing bubble that hit the US housing market. However, regulating the interest rates will therefore results in stability in asset prices in the next 3 years as evidenced by the relative stability in interest rates over the last five years since 2009 In analyzing this model, we further looked at the impact that the weighted average cost of capital had on the borrowing rate and the risk free interest rates, with the observation held indicating that as the interest rates lowered, it led to a reduction on the discount rate and ultimately increased the asset values. CONCLUSION In as much as the Federal Reserve keeps constant checks on the inflation rates, they remain relatively low. From application of the model presented above, it should be observable that for stability in asset prices to be attained, there should be checks to ensure that the dynamic interest rates landscape is kept in check. This means that prudence is required when responding to any changes in interest and the same time, the realization that responding too slowly to changing interest rates leads to an eventual inflation and directly affects the economic cycle and inevitably leads to inflation. On the other hand, response to changing interest rates, by keeping them at an equilibrium maintains an upwards trend in the business cycles. REFERENCES. Demary, Markus. 'The Interplay Between Output, Inflation, Interest Rates And House Prices: International Evidence'. Journal of Property Research 27.1 (2010): 1--17. Print. Hyman, Louis. Debtor Nation: The History of America in Red Ink. Princeton: Princeton University Press, 2011. Internet resource. Imf.org, 'World Economic Outlook Database April 2014'. N.p., 2014. Web. 13 Sep. 2014 Koop, Gary. Analysis of Economic Data. Chichester, West Sussex, England: Wiley, 2009. Print. Mauro, Paolo. Stock returns and output growth in emerging and advanced economies. IMF Working Paper, 2008. WP/00/89. Newyorkfed.org, 'Global Economic Indicators - Federal Reserve Bank Of New York'. N.p., 2014. Web. 13 Sep. 2014. Read More