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The Relationship Between Fiscal Spending and Unemployment Essay


Introduction

The US economy plunged into a recession, with the real GDP growth rate falling to -3% in 2008. The Obama administration passed the American Recovery and Reinvestment Act of 2009 (ARRA 2009) in response to the financial crisis caused by the disappearance of the $5 trillion household wealth of the country in just 12 weeks (Carter, 2012). It was a reactionary policy that aimed to counter the effect of the Great Recession and boost output, consumer spending, and employment. It is expected to increase consumer spending and bring the economy out of the recession. However, the relationship between government spending and unemployment, which was presumed to be negative by the Obama government, was less apparent to many. Various studies have been conducted using econometric as well as modeling methods to establish a relationship between government stimulus and employment growth (Matthews, 2011).

However, none of the studies has conclusively stated if the stimulus measure by the US government successfully increased employment. Economists have an opposing opinion about the success of the fiscal stimulus. This has raised many questions regarding the relationship between government spending and the unemployment rate, in general. Therefore, in this paper, I will try to establish a relationship between government spending and the unemployment rate. For this purpose, I will first study the theoretical underpinning of the relation and then assess it using US government spending and unemployment rate data from 1960 to 2014 (BLS, 2016; CBO, 2015). Multiple linear regressions are used to understand the relationship between government spending and unemployment rate and then move on to see the relationship between the two as observed from the data analysis.

Theory

According to Keynesian theory of effective demand, when the aggregate demand and supply do not intersect, prices change to bring them to equilibrium, creating an employment trap (Skidelsky, 2010). Effective demand theory postulates changing output and income can equilibrate aggregate demand and supply (Skidelsky, 2010). This makes the economy stuck in the underemployment equilibrium. The theory of income and employment multiplier showed that demand must increase in a depressed economy in order to increase employment. Intuitively, sales expectation of a given stock of capital creates anticipation of employment and output. In other words, these are expected returns from new capital goods. Since demand is a function of investment in dynamic economies, employment will consequently depend on long-term expectations (Skidelsky, 2010).

According to Keynes, expected uncertainty about the future is the main cause of economic crisis. As the financial crisis in the US was caused due to the wrong risk assessment, the key to the elevation of the problem is better risk-management. Thus, the measure for elevating the economy from recession, according to Keynes, was to impose fiscal stimulus. He believed increasing fiscal stimulus would boost economic growth and employment.

Though Keynesian macro-recovery model was used during the Great Depression in the 1930s, many modern economists opined this theory ineffective to rescue the US economy from the Great Recession. Keynesian multiplier theory argued that when a dollar is infused into the economy, it would circulate in the economy, creating an aggregate effect that would be much larger than the initial amount of money spent (Carter, 2012). The amount by which the initial money is multiplied is called the multiplier. Therefore, when a large amount of money was pumped into the economy through ARRA 2009, a multiplier effect was expected to be created in the economy that would increase growth and in turn employment.

When the 2008 financial crisis dragged down the real income, the government created stimulus packages in the form of fiscal and monetary measure projected to boost market expectation (Skidelsky, 2010). However, many believe that for the 2007 recession, Keynesian multiplier theory did not work, as economic growth did not miraculously increase. Thus, the great recession has created a rift in the economists’ understanding of the impact of fiscal stimulus on growth and employment.

Methodology and Data

The economic strength of a country is determined by gross domestic product, which is an aggregate of consumption, investment, government spending, and net exports.

GDP = C + I + G + NX

Where, C is consumption, I is investment, G is government spending, and NX is net export i.e. export over import. GDP is a measure of the economic health of the country. So, according to this equation, if G is increased, it will raise GDP. Further, if there were real GDP growth in the economy, it would imply output growth. This economic growth would promote employment opportunities, reducing unemployment.

The following variables are considered to understand the effect of fiscal spending on unemployment. The unemployment rate is regressed using government spending as a percentage of GDP. As the paper aims to understand the effect of fiscal spending on the unemployment rate, the analysis will look into the effect of different types of fiscal spending on unemployment. Regressing unemployment rate to the defense, infrastructure, education, and health spending of the government, helps us to understand the underlying relation.

We use these components of government spending and not the total government spending because the latter consists of other variables parts such as pension and welfare schemes which do not have a direct underpinning on the GDP growth or employment. Infrastructure spending includes government spending on transportation and water infrastructure. We take these types of government spending as these are expected to directly affect output growth and therefore employment. We do not consider pension, interest, and other government spending, as they are welfare related schemes and have no direct relation to output growth. The paper concentrates mostly on the effect of government spending (along with its various types) on the unemployment rate. We take government spending as a percentage of GDP for this shows how unemployment rate changes with the shift in GDP. Thus, when the increase in government spending is equivalent or more to real GDP growth, unemployment is reduced.

Analysis

Taking annual US government spending data from 1960 to 2014 we conducted a multiple regression analysis on the unemployment rate. The first regression was done for the complete data ranging from 1960 to 2014. The regression analysis showed that the unemployment rate has a negative intercept but the relation with the other independent variables such as defense spending, infrastructure spending, education and health are positive. The coefficients of the independent variables can be seen in the equation below in table 1 (see Appendix). This regression was statistically significant with a p-value of 0.18 at 5% significance level. Unlike popular belief, infrastructure spending had a positive relation to the unemployment rate (3.78 coefficient). Thus, the regression results suggested that with higher infrastructure spending, there would be an increase in unemployment rate. However, here it is a ratio of infrastructure spending to GDP. Consequently, when the increase in GDP and infrastructure spending are at the same rate, their ratio of the two remains unaltered. This results in an excess output that can boost employment. However, this finding contradicts the argument presented by the theory.

The first regression is done for a period of more than 50 years. During this period, the economic growth has gone up and down. Thus, the second analysis is done from 2007, when the US economy officially went into a recession and the real GDP growth hit the negative mark. Similar results were found for other analysis done on the data from 2000 to 2014, taking into consideration the changes in economic and technological conditions. We found similar results even in this case (see table 2 in Appendix). When a regression is done for the annual spending data from 2000 to 2014, the results were marginally different. This result showed that the unemployment rate would reduce if more spending is done on education and all other components of government spending had a positive relation with the dependent variable.

Keynes pointed out that when the economy is in recession if the government increases spending to boost output then it would automatically increase GDP growth and in turn reduce unemployment. In other words, when the government spends more on infrastructure, education, health, and defense during a recession, these are supposed to increase output by boosting expectation of the people about the economy. So we conduct a regression analysis of unemployment rate for government spending from 2007 to 2014. The result of the regression analysis is statistically significant at the p-value at 0.02 (see table 3 in Appendix). The regression shows that the no other government-spending variable other than education spending had a negative relation with the unemployment rate. Therefore, from 2007 to 2014, only an increase in the education expenditure reduced the unemployment rate in the US economy. Expenditures on infrastructure, defense, or healthcare had a positive effect implying that they increased the unemployment rate.

The question that arises is why did the increase in infrastructure spending in 2009 with the Obama government fail to reduce the unemployment rate? Further, why was education the only component of government spending that statistically reduced unemployment rate? This is because education increases the skill sets required for the technologically advanced workplace of today. An increase in education as a percentage of GDP had grown substantially to create employment in the economy, which resulted in decreasing unemployment. Infrastructure, which is believed to be the most effective government spending tool that would increase GDP and in turn employment. Infrastructure spending has been the largest component of ARRA 2009 yet it is observed to have a positive effect on the unemployment rate implying, an increase in infrastructure spending would increase employment. Fiscal stimulus, especially an increased spending in infrastructure would increase the rate of economic growth and consequently, would reduce unemployment. Another reason to explain this discrepancy is a time lag. When a fiscal stimulus is implemented, it takes time for the benefits to trickle down, resulting in an increase consumption spending and subsequently raising employment.

Conclusion

The US economy has officially come out of recession in August 2009; however, the unemployment rate in the economy has been very high. Though it has come down marginally in 2015, but still, it is higher than the average unemployment rate in the 1990s. The average unemployment rate from 1990 to 1999 was 5.7% while that from 2007 to 2014 was 7.9 (BLS, 2016). Though it is believed that the fiscal stimulus of ARRA 2009 is creating a positive effect on the economy, the regression analysis shows that there has been a positive relation between the two. In other words, an increase in government spending has not been successful in decreasing unemployment rate.

Appendix

Table 1: Multiple Linear Regression of Unemployment rate from 1960 to 2014 vis-à-vis government spending (Infrastructure, Defense, Education, and Health

Regression Statistics
R 0.51
R-square 0.26
Adjusted R-square 0.2
S 1.41
N 55.
ANOVA
d.f. SS MS F p-level
Regression 4. 35. 8.75 4.3901 0.004
Residual 50. 99.65 1.99
Total 54. 134.64
Unemployment Rate (%) = – 7.98264 + 0.16508 * Defense + 3.78017 * Infrastructure + 1.95483 * Education + 0.72652 * Health
Coefficient Standard Error LCL UCL t Stat p-level H0 (5%)
Intercept -7.98 4.81 -17.65 1.68 -1.66 0.1 accepted
Defense 0.17 0.22 -0.27 0.6 0.76 0.45 accepted
Infrastructure 3.78 2.04 -0.31 7.87 1.85 0.07 accepted
Education 1.95 0.91 0.12 3.79 2.14 0.04 rejected
Health 0.73 0.21 0.3 1.15 3.43 0. rejected

Table 2: Multiple Linear Regression of Unemployment rate from 2000 to 2014 vis-à-vis government spending (Infrastructure, Defense, Education, and Health

Regression Statistics
R 0.95
R-square 0.91
Adjusted R-square 0.87
S 0.66
N 15
Unemployment Rate (%) = – 21.59274 + 0.59198 * Defense + 8.58641 * Infrastructure – 1.43274 * Education + 1.05218 * Health
ANOVA
d.f. SS MS F p-level
Regression 4. 43. 10.75 24.81 0.00004
Residual 10. 4.33 0.43
Total 14. 47.33
Coeff. SE LCL UCL t Stat p-level H0 (5%)
Intercept -21.59 4.91 -32.54 -10.65 -4.39 0. rejected
Defense 0.59 0.79 -1.16 2.34 0.75 0.47 accepted
Infrastructure 8.59 2.25 3.57 13.6 3.82 0. rejected
Education -1.43 1.73 -5.28 2.41 -0.83 0.43 accepted
Health 1.05 0.76 -0.65 2.75 1.38 0.2 accepted

Table 3: Multiple Linear Regression of Unemployment rate from 2007 to 2014 vis-à-vis government spending (Infrastructure, Defense, Education, and Health

Regression Statistics
R 0.98
R-square 0.96
Adjusted R-square 0.91
S 0.54
N 8
Unemployment Rate (%) = – 18.95888 + 2.46395 * Defense + 2.68731 * Infrastructure – 2.07545 * Education + 1.64254 * Health
ANOVA
d.f. SS MS F p-level
Regression 4 22.08 5.52 18.63 0.02
Residual 3 0.89 0.30
Total 7 22.97
Coeff. SE LCL UCL t Stat p-level H0 (5%)
Intercept -18.96 7.15 -41.72 3.80 -2.65 0.08 accepted
Defense 2.46 1.11 -1.08 6.01 2.21 0.11 accepted
Infrastructure 2.69 4.10 -10.36 15.73 0.66 0.56 accepted
Education -2.08 2.10 -8.76 4.61 -0.99 0.40 accepted
Health 1.64 0.75 -0.75 4.03 2.19 0.12 accepted

References

BLS. (2016). Databases, Tables & Calculators by Subject. Web.

CBO. (2015). , 1956 to 2014. Web.

Carter, R. E. (2012). The Relationship Between Fiscal Spending and Unemployment. Walden University. An Arbor: ProQuest LLC. Web.

Matthews, D. (2011). Did the stimulus work? A review of the nine best studies on the subject. Web.

Skidelsky, R. (2010). The relevance of Keynes. Cambridge Journal of Economics , 35 (1), 1-13.

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