Business Cycles

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Business Cycles

 

                                                                 Introduction
Economic recession occurs when a country experiences low economic activity. According to Tucker (2010), economic recession is influenced by actions that are taken to manage the supply of money in the economy. In America, the Federal Reserve is the government agency that is mandated by the Constitution to maintain a balance between the macroeconomic variables of money supply, inflation as well as the interest rates. If the delicate balance between these variables is not kept, the economy is forced to take corrective measures.

Bursting of the Housing Bubble in the U.S

The leading cause of the 2007/2008 financial turmoil was greed on the part of the investors who tried to capitalize on the housing boom (Quiry & Vernimmen, 2009). Competition in the real estate grew intense as each lender tried as much as possible to appeal to the customers to get a mortgage from them. Because of intense competition, interest rates went down significantly, forcing many people to acquire loans. In addition, lenders did not carryout background check to determine the creditworthiness of the borrowers. As a result, many people, with poor credit ratings, got loans. This opened a floodgate for banks and other institutions to woo agents to get more clients with promises of huge incentives and bonuses. The housing prices had gone up in the early months of 2006. However, they started going gown in late 2006 and in the following year (Tucker, 2010). Therefore, the housing bubble burst as prices went significantly down and interest rates shot upwards. Borrowers found themselves in a negative equity position. This is a situation where the mortgage debt exceeds the value of the property. People with low credit rating defaulted leading to many foreclosures. Moreover, lenders suffered massive losses as the homes recovered only attracted far less than the initial amount borrowed.

Macroeconomic Indicators

In relation to the business cycle, economic indicators are usually categorized into three groups. These include leading, lagging, and coincident indicators.

Leading Indicators

Before a change in an economy activity, there are usually those parameters that change or which precede such events. There are the ones referred to as the leading indicators (Tucker, 2010, p. 163). They are a precursor to a change in the direction that a given economy will take. In the case of the housing bubble, several activities can clearly be identified as leading indicators. One of these is the astronomical increase in the building permits in the preceding years. Building permits reflect the activity that takes place in the housing market. In the U.S., available data show that building permits increased by 50.2% between 2002 and 2005 (Byun, 2010, p. 7). This shows that many people applied to have permits to build houses several years before the bubble set in indicating that the demand for housing was increasing. The demand almost reached a plateau in the years 2006/2007 before falling by about 57.0% in 2008 (Byun, 2010, p. 7). Interest rates also fall under the category of leading indicators. Before the housing bubble, interest rates went significantly low prompting many people to seek loans. Usually, low interest rates encourage people to borrow. Yield curves, or the spread of interest rates over a period is a critical determinant of how an economy will fare in a given timeframe. Changes in the yield curve have been used to show downturns in a business cycle (Tucker, 2010). In summary, people were motivated by low interest rates to seek loans for building houses before the 2007 economic meltdown.

Lagging Indicators

As the name suggest, lagging indicators are variables that change after a change in the economic activity. They are the opposite of leading indicators. Most notable in this category is unemployment trends. Unemployment takes place when people are out of work for one reason or another, but at the same time are looking for work. After the crisis started, many people lost their jobs adding to the number of people already unemployed (Tucker, 2010). The prime rate also falls under this category because any change in this rate occurs within a few months once an economic trend has started. By definition, it is the rate used by banks to charge their most trusted clients at the best (Tucker, 2010). It is the most viable rate for which other loans products are made. However, over the years it has lost its intended purpose as big borrowers sometimes borrow below the prime rate.

Coincident Indicators

These include the economic variables that change almost at the same time as the change occurring in the economic activity in a country. They indicate the state of affairs of the current economy or the economic outlook of a country at that given time. One example is the reduction in the industrial production (Malgarini, 2011). At the onset of the 2007 crisis, manufacturing activity in America, and indeed the rest of the world experienced a dramatic fall (Malgarini, 2011). For instance, industrial production in Europe went down by 22% after the crisis started (Malgarini, 2011). Tied with the fall in the manufacturing activities is the decrease in personal income. Personal income went down by about 2% at the onset of the crisis in 2007 (Tucker, 2010). This shows that the crisis affected the earnings of individual households since many people lost their jobs.

Solution to Unemployment

As the President of the United States of America, I would be expected to provide a quick solution to the unemployment rate, currently standing at about 6%. It is clear in my mind that the solution to unemployment lies in the creation of jobs among the unemployed. A government can stimulate the economy and create more jobs through two ways. The first one is by the use of the monetary policy (Malgarini, 2011). This can be achieved by lowering interest rates so that people can borrow and buy what they need. With a clear regulatory framework, this can achieve positive results, than what happened in 2007. However, if this method were ineffective, the best option would be the fiscal policy approach. This entails cutting taxes so that can people can have more money in their pockets. If consumers have more money in their pockets, the demand for products would increase significantly. Increased demand means more production, hence retail outlets, and factories will require more workers. Another step is to increase welfare spending, especially on the jobless. This has the same effect as cutting taxes since the unemployed will have money to spend. This means more goods and services will be demanded. A combination of these two methods will see unemployment rates go down substantially. However, the most effective strategy that I would recommend and use is the funding of mass transit. It is estimated that one billion dollars can create employment to about 20, 000 people in the construction industry (Malgarini, 2011). One trillion dollars would do a wonderful job. Overall, an effective combination of these measures will drastically reduce unemployment rates in America.

Conclusion

In summary, this paper has provided a clear argument on the role the housing sector in the 2007 financial crisis. In doing so, several macroeconomic indicators have been defined and examples provided for each and how they played out in the crisis. These macroeconomic indicators happened before, concurrently, and after the crisis. At the end of the discussion, I have provided the best approach I would use as the President of America in tackling the unemployment problem in the country.

 

References

Byun, J. K. (2010). The U.S. Housing Bubble and the Bust: impacts on employment. Retrieved     from http://www.bls.gov/opub/mlr/2010/12/art1full.pdf

Malgarini, M. (2011). Industrial Production and Confidence after the Crisis: what’s going on?       Retrieved https://www.ciret.org/files/Malgarini_Marco_1.pdf

Quiry, P. & Vernimmen, P. (2009). Corporate Finance: theory and practice. New York:    Cengage Learning.

Tucker, B. I. (2010). Macroeconomics for Today. New York: Cengage Learning.

 

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