Determining the Relationship between Unemployment Rate and Inflation Rate: The Case of U.S. Economy
Introduction
The research question, for this research project, is “How is to Determine the Nature of Relationship between Employment and Inflation in American Economy?”
For a state or government, the prime concern is to set and achieve important economic targets, as the realization of relevant economic targets ensures economic, political, social progress/stability. Some of the economic concerns or targets are universal, which implies that all governments/economies strive to address and achieve these concerns or targets respectively. For instance, for a government or economy, the full-employment level is a prime concern and a goal, which it must realize (Pollin 2012). Studies suggest that when unemployment in an economy increases, the economic activity in that economy slows down and the political system becomes volatile. Therefore, governments around the world are always very concerned about unemployment and they take different measures to ensure that unemployment remains at its natural rate (Eliasson and Karlson 2001).
Similarly, inflation is another major concern for economies and governments. Inflation directly and strongly affects both aggregate consumption and employment level in an economy (Castelnuovo and Surico 2010). In addition to that, inflation is directly associated with political and economic stability. For instance, when hyperinflation occurs, the economic system becomes volatile, and the local currency comes under enormous pressure (Bodea and Hicks 2015). The lack of economic stability during this period also mounts pressure on political and social systems, which affects socioeconomic and socio-political progress.
An unusual increase in the general price level is not the only concern of a government, but also of financial institutions, such as the Central Bank. For the government and major financial institutions of the state, deflation is also a major concern (Borio and Disyatat 2010). Deflation is a more serious concern than hyperinflation, as, during the deflationary period, both consumption and investment decline. It is imperative to acknowledge that consumption and investment strongly and directly affect economies. Consumption is considered the engine of economic growth. Economic growth in both developing and developed countries depends greatly on the size of consumption.
It is quite evident that there is an apparent relation between inflation and employment (Espinoza and Prasad 2010). For instance, inflation directly affects the size of investment in an economy, which is responsible for the fluctuation in the employment level. Therefore, studying the relationship between inflation and unemployment is essential (Omay and Kan 2010).
In this academic exercise, we study how changes in inflation affect unemployment in the United States; what is the nature of the relationship between the two variables. We have selected the United States’ economy, as it is one of the largest economies in the world, which is quite transparent and the data about its economy is quite authentic (Barboza 2010). Also, changes in the United States’ economy bring changes in the world economy, which it is it is prudent to select the American economy for this project. The subject is important and intriguing, and it pertains to the major economic variables/factors/indicators that influence the overall economy.
For this academic exercise, we will retrieve data, about unemployment and inflation, from World Ban, which is one of the largest data portals, from where data related to different economic indicators are available. There are other data portals too, which can provide the relevant data; however, our preference is the World Bank, because of the authenticity of the data that it has to offer.
Literature Review
Unemployment is generally understood as joblessness. For an individual, such a situation occurs when he/she does not find a job or employment when he/she is actively looking for it. The unemployment rate in an economy is measured as a percentage, and it is calculated by simply dividing a total number of unemployed individuals in an economy with the total individuals that constitute the current labor force (Hussain, Iqbal and Siddiqi 2010).
As the size of unemployment increases, overall economic activity starts to dull, which affects the size of investment and inflation. Studies reveal that there are different types of unemployment, which are caused by different factors. It is also imperative to acknowledge that there is the difference between voluntary and involuntary unemployment. Governments, its institutions, and economists only consider involuntary unemployment as voluntary employment is the decision of individuals not to seek employment. There could be several reasons for voluntary unemployment: social, physical, political or cultural (Hughes and Perlman 1984).
The most common types of unemployment that are acknowledged by the state, its institutions and economists are Keynesian unemployment, frictional unemployment, structural unemployment and classical unemployment.
Frictional unemployment occurs when an individual quits a job or voluntarily gets unemployed to find better employment or job. The size of this search unemployment is usually very small, which is why it does not affect the economy very strongly. However, the size of cyclical unemployment, which occurs every season, is usually large and it affects the economy considerably.
For developed economies, structural unemployment, which occurs because of the mismatch between skills offered and skills demanded, is not a major issue. However, for developing economies, structural unemployment is a major issue (Castelnuovo and Surico 2010).
The causes of unemployment are several, as many factors affect an economy. However, there are a few causes that are more relevant than the others. For instance, consumption and investment, which are correlated with one another, strongly impact the size of unemployment in an economy. When the size of consumption increases, inflation increases, which acts as an incentive for investors to invest in the economy. The increase in the size of investment increases demands the labor, which increases general employment level in an economy. However, when deflation sets in, the size of investment reduces significantly, which increases the unemployment rate during a particular period (Hussain, Iqbal and Siddiqi 2010).
Studies reveal that urban migration is also playing a major role in increasing the unemployment level, especially in developing countries. A major focus development is urban centers; therefore, urban centers produce more lucrative economic and financial opportunities. These financial and economic opportunities attract labor from the rural regions (urban migration), which causes a large gap between demand and supply of labor. Urban Migration is considered one of the major causes of unemployment in urban centers; both in developed and developing countries. However, inflation remains that most universal and potent fact that directly influences the size of unemployment (Borio and Disyatat 2010).
Inflation is generally understood as the upward fluctuation in the price of goods and services in an economy. These fluctuations in the general price level bring various kinds of changes in the economy, especially about consumption, investment, and employment. The decrease in the general price level or downward fluctuation in the general price level is called deflation, which also affects the economy (strongly), but differently (Hussain, Iqbal and Siddiqi 2010).
In both developed and developing economies, inflation is controlled through direct and indirect measures. The direct measures are part of the monetary policy that is devised and implemented by a central bank, which is a semi-autonomous financial/economic institution. The monetary policy of a particular time incorporates economic considerations and objectives of the government of the time. For instance, if the objective of the economy is to increase inflation and investment to meet the political-economic objectives, then the central bank employs an expansionary monetary policy that increases the money supply in economy reduce interest rates. The increase in the supply of money pushes inflation upwards, and the reduced interest rate increases the size of investment in an economy (Pollin 2012).
Inflation also directly affects real income. For instance, when the general price level decreases, the real income and purchasing power increase. It means that an individual can buy more than previous. This development usually leads to higher consumption, which intensifies industrial activities. However, when the price level decreases drastically, the size of profit reduces, which reduces the size of the incentive for producers to invest in the economy (Barboza 2010).
Another cause of inflation or deflation could be investment environment or financial developments. For instance, when the sub-prime mortgage crisis occurred, because of flaws in the financial-legal system, the size of investment decreased dramatically, which caused massive unemployment in the United States. To address the challenge, the Federal Reserve employed an expansionary monetary policy that aimed to address inflation, investment, and consumption.
It is very evident that because of changes in inflation rate or general price level, serious and major changes occurred in the American economic system. It is also apparent that the Federal Reserve targeted inflation to stabilize the economy and increase employment opportunities in the American economy. However, the process was very gradual, and it required a fiscal stimulus to bring about the desired change. The American Recovery and Reinvestment Act of 2009 which was enacted by the Obama administration that aimed to bring inflation and employment at the desired level. The $831 billion spent by the government in different sectors of the economy, such as education and health. Also, the large amount of $48.1 billion was spent on transportation infrastructure (Wilson 2012).
There is an ambiguity regarding the outcome of massive fiscal stimulus; however, it is plain that fiscal stimulus is intended to save the existing jobs and create new ones, which will affect consumption and thus inflation.
Data
For this academic exercise, we will retrieve data from the World Bank’s website, which is a data portal (World Bank 2018). From the section/page World Development Indicators, we will retrieve the pertinent data in the form of an excel file. The nature of the data will be secondary, rather than primary. In research works, about the subjects such as inflation, employment, GDP, etc. secondary data is used. To analyze secondary data and to run tests on it, different econometric related software is used. Some of this software is more precise and accurate than the others. Also, some provide better results in a more comprehensive manner than others. However, the use of particular statistical software for the analysis of data is usually at the discretion of a researcher.
With all these data-analysis and statistical software, variables must be defined as dependent and independent. Generally, a researcher can take more than one variable for particular research. Some contemporary statistical software also allows running tests on multiple dependent variables; a researcher can identify more than one dependent variable in a particular model.
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Data’s Starting Point and Span (time-period)
The starting point of the data is the year 1994, and it ends in the year 2017. During this period, major economic changes have occurred, and the American economic system has undergone many changes. Different kinds of economic-legal measures were taken, which affected different economic indicators that included inflation and employment. During this period, at least two recessions have occurred, which jolted the American economy quite badly. For these reasons, we have selected this period, during which evident changes have occurred in inflation and employment level.
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Level of Observations
The data, pertaining to the selected variables, will be national data. In addition, the nature of the data will be annual.
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Total Number of Observations
The total number of observations for each selected variable will be 24 and the size of data is moderate.
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Type of Data (Administrative or Survey)
The data, which we will retrieve from the data portal of World Bank’s website, will be secondary and administrative in nature. For instance, the unemployment and inflation statistics are national estimates.
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The time period covered by the data
The time period covered by the data is from 1994 to 2017.
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What Variables are Available
The data pertaining to 1580 variables is available on the World Bank’s website. Data related to all variables is in annual form. We will select annual data pertaining to Inflation and Unemployment (national estimates).
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Dependent Variable
For the statistical model, which we will devise, our dependent variable will be employment. We will see how the dependent variable is affected by the independent variable. Generally, the variable, which is the prime subject of an academic study, becomes a dependent variable in a statically model. During the methodical scrutiny of the literature review, we identify variable(s), which affect our prime subject (dependent variable). During the systematic study of literature, we identified various factors that directly and strongly affect employment. However, for this study, we have selected only one independent variable.
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Independent Variable
The independent variable, which we have selected for this statistical analysis is inflation. Inflation is a very strong fact, which influences the entire economy. A systematic study of the literature reveals that when the inflation rate increases, it positively affects the employment level and when the deflation sets in, the employment level in an economy decreases significantly. Therefore, we have selected inflation as an independent variable to learn how inflation is, and employment is connected. It is imperative to understand that inflation is partly an exogenous factor, as it is directly affected by the decisions taken by the Federal Reserve about the supply of money.
Statistical Analysis Criterion
The F and P values for the model must be lower than the critical value of 0.05 or 5%. (Note: The F-value reveals the overall health of the model, and the P-value provides understanding regarding the validity and authenticity of the relationship between the selected variables.)
The Tabular Representation of Data
| Year | Unemployment | Inflation | time1 |
| 1994 | 6.1 | 2.128133 | 1 |
| 1995 | 5.6 | 2.085677 | 2 |
| 1996 | 5.4 | 1.825553 | 3 |
| 1997 | 4.94 | 1.711504 | 4 |
| 1998 | 4.51 | 1.085256 | 5 |
| 1999 | 4.22 | 1.530322 | 6 |
| 2000 | 3.99 | 2.27552 | 7 |
| 2001 | 4.73 | 2.278901 | 8 |
| 2002 | 5.78 | 1.535125 | 9 |
| 2003 | 5.99 | 1.994056 | 10 |
| 2004 | 5.53 | 2.749721 | 11 |
| 2005 | 5.08 | 3.217638 | 12 |
| 2006 | 4.62 | 3.072267 | 13 |
| 2007 | 4.62 | 2.661336 | 14 |
| 2008 | 5.78 | 1.961612 | 15 |
| 2009 | 9.25 | 0.759435 | 16 |
| 2010 | 9.63 | 1.221349 | 17 |
| 2011 | 8.95 | 2.064628 | 18 |
| 2012 | 8.07 | 1.842052 | 19 |
| 2013 | 7.38 | 1.615007 | 20 |
| 2014 | 6.17 | 1.794674 | 21 |
| 2015 | 5.28 | 1.084433 | 22 |
| 2016 | 4.87 | 1.2758 | 23 |
| 2017 | 4.36 | 1.799317 | 24 |
The extreme left column represents the year; the starting year of this data is 1994, whereas the ending year is 2017. The next column is of the inflation variable, which is followed by the unemployment variable. The span of the data, in a time context, is 24 years; therefore, the total number of observations is 24, which is apparent from the extreme left column.
Statistical Test
The statistical test, which we will apply to the statistical model, is a simple regression test. It is because we only have two variables in this statistical model, which is why a simple regression test is appropriate.
Our focus, of the research will be the impact of inflation on unemployment. It implies that we will be studying the size of the impact on unemployment because of the changes in the inflation rate. The results which we intend to obtain will be produced through the process and during the statistical analysis certain parameters will be defined. Also, the post-estimation, test, Durban-Watson Test, will be employed to see how valid the results of our analysis.
Theory
In this section of the academic exercise, we will describe the cause-and-effect relationship between the selected variables. We will rely on statistical evidence and available literature to learn how inflation affects employment level in the American economy. However, it is imperative to acknowledge that causality runs in both directions, which implies that not only inflation affects employment, but also employment level or unemployment affects inflation.
According to the systematic study of these variables, when the rate of inflation increases in an economy, the employment level also increases or the unemployment in an economy decreases. It is because, with the increase in inflation, consumption increases, and interest rates decrease. Both play a major role in the intensifying of the economy. For instance, when interest rate is reduced, the demand for loans increase as the loans is now available at a lower cost or interest rates. As more capital is available, in the form of loans to invest (at a lower rate), the size of investment in the economy increases. As the size of investment increases, the demand for labor also increases. It pushes the demand curve rightwards, which increases both nominal and real wages. The increase in the wage expands the quantity supplied of labor. These developments increase both national output and level of employment in an economy.
Deflation, which is a systemic decrease in the general price level, increases purchasing power and real income. As the prices decline, say because of the competition, the real income of an individual increases. This increase in the real income translates into greater consumption or saving. In both forms, higher consumption and saving positively affects an economy. For instance, savings eventually translate into investment, which implies that at the lower rate capital or loans are available for potential investors. We have already mentioned that causality also runs from employment or unemployment towards inflation. It means that when the level of employment increases in an economy or when the unemployment rate in an economy decline, the size of consumption increases. It is because of the aggregate demand for goods and services shifts upwards (increase), which increases the general price level. It suggests that not only inflation affects employment or unemployment, but also the size of employment or unemployment in an economy affects the inflation rate. For that particular reason, fiscal stimulus was introduced so that employment could be generated at a massive scale in a little span of time. However, it is also a fact that fiscal stimulus complicates economic matters. As the employment of fiscal policy has a cost; therefore, governments usually rely on central banks (in case of United States Federal Reserve) to address the challenges about economic growth, desirable inflation rate, and full employment level.
Graph A
Graph B
Graph C
Graph 4
All four graphs reveal how changes money supply brings changes in investment and as the size of investment changes so does the wages and general price level. These graphs show that both employment and inflation affect one another. For instance, the increase in demand for labor because of the supply of funds at low rates increased the demand and the increase in aggregate demand acted as an incentive for producers to invest more (the period of the boom). The last graph shows the second increase in the nominal wage, which will soon diminish because of the increase in the general price level.
Estimation
For the statistical analysis, we have chosen STATA. This software is appropriate for both primary and secondary data. The results, which STATA produces, are more precise than most statistical software. The criterion which we have set for our economic model is the F-test value must be equal to or less than 0.05 or 5%, and the P-value must also be equal to or less than 0.05%. Our entire exercise will be based on two parts: 1) Descriptive Analysis and 2) Statistical Analysis. Descriptive Analysis will include the summary of statistics (mean, median, mode, standard deviation) and histograms, whereas the statistical analysis will be based on a simple regression test.
The Regression Equation for the model is;
Unemployment = Bo + B1 (Inflation) + et
Descriptive Statistics Table
| Unemployment | Inflation | ||
| Count (N) | 24 | Count (N) | 24 |
| Mean | 5.86875 | Mean | 1.898721 |
| Median | 5.465 | Median | 1.833802 |
| Standard Deviation | 1.620516 | Standard Deviation | 0.61572 |
| Minimum | 3.99 | Minimum | 0.759435 |
| Maximum | 9.63 | Maximum | 3.217638 |
Histograms
Inflation
Unemployment
Regress Unemployment and Inflation
Source | SS df MS Number of obs = 24
————-+—————————— F( 1, 22) = 3.17
Model | 7.61272152 1 7.61272152 Prob> F = 0.0887
Residual | 52.7869395 22 2.39940634 R-squared = 0.1260
————-+—————————— Adj R-squared = 0.0863
Total | 60.399661 23 2.62607222 Root MSE = 1.549
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Unemployment | Coef. Std. Err. t P>|t| [95% Conf. Interval]
————-+—————————————————————-
Inflation | -.934378 .5245713 -1.78 0.089 -2.022272 .1535163
_cons | 7.642874 1.044998 7.31 0.000 5.47568 9.810067
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Regress Unemployment Inflation (Robust)
Source | SS df MS Number of obs = 24
————-+—————————— F( 1, 23) = 89.63
Model | 705.879001 1 705.879001 Prob> F = 0.0000
Residual | 181.134099 23 7.87539562 R-squared = 0.7958
————-+—————————— Adj R-squared = 0.7869
Total | 887.0131 24 36.9588792 Root MSE = 2.8063
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Unemployment | Coef. Std. Err. t P>|t| [95% Conf. Interval]
————-+—————————————————————-
Inflation | 2.722379 .2875542 9.47 0.000 2.127528 3.31723
Post-analysis Test
Durban-Watson Statistic
Durbin-Watson d-statistic (1, 24) = .5752359
In this section of our academic exercise, we have provided the results of our estimations. Descriptive statistics provide an understanding regarding the data, whereas statistical analysis provides an understanding regarding the nature of the relationship between the selected variables.
It is essential for a researcher to have a good understanding of the data which he/she has collected. It allows him/her to comprehend the results more easily. For instance, whenresearch is familiar with his/her data, he/she knows why the statistical analysis has produced particular kind of results. Also, he/she would be able to understand the flaws of the devised model, which a researcher must know to improve the model.
It is a fact that the devised models are not always the most appropriate models. The health of the data may affect the overall model (in the form of homoscedasticity etc.), which in the result may produce biased results. For these reasons, it is essential to get familiar with data, as it allows understanding why statistical analysis has produced particular types of results.
Results
Results of Descriptive Analysis
Statistical Summary
From the table of statistical summary, we learn that total observations, for each variable, are 24. The table also reveals that no observation is missing; the numerical size of variables is identical (24 observations each). The table also reveals that for unemployment, the minimum value is 3.99% and the maximum value is 9.63%. It suggests that from 1994, the lowest unemployment rate in the United States was 3.99% (close to the natural rate of unemployment) and the highest was 9.63% (large-scale unemployment). We also learn that the mean value of inflation was 5.86% and from the mean value the deviation as a slight; only 1.62%.
Regarding inflation, the statistical summary unearths that the highest inflation figure is 3.21% and the lowest is 0.75%. As the extreme values (min and max) are not very far apart; therefore, we can assert that the American economy is quite stable, despite the frequent occurrences of recessions. The mean value for Inflation is 1.89%, and the standard deviation (deviation from the mean value) is 1.62%.
Histograms
Histogram about unemployment shows that since the start of the sub-prime mortgage crisis, unemployment has mostly remained within 4% to 6%; however, for a smaller period, it has remained between 7% and 9%.
The histogram for the variable inflation reveals that inflation has remained between 2% and 3% and for a brief period it has reached 3% and 1%, representing the maximum and minimum values respectively.
Statistical Analysis (regression test)
Our first statistical analysis test, in which unemployment was the dependent variable, produced apocryphal results. For instance, the F-value for the model was 0.08, which was greater than the critical value of 0.005. The value of R-square was only 0.12, and the value of the adjusted r-square was 0.08.
The p-value was also greater than the critical value of 0.05. The value of the coefficient was -0.934378 and the value of the standard error was 0.52. The value of the t-test was -1.78, which was quite interesting.
To address these issues, we employed another regression test (robust), which aimed to suppress the constant in the devised equation. The F-value of the robust regression was 0.000, which suggests the health of the overall model has improved. The R-square value is 0.79, and the value of the adjusted R-square is 0.78. The p-value is 0.000, and the value of the t – statistic is 9.47, and interestingly the value of the coefficient is 2.722379. The value of the Durban-Watson test for this model is 0.57.
Interpretation of Results
From the summary of statistical data and histograms, it is quite apparent that the American economy is quite stable. The figures pertaining to inflation reveal that despite the periodic occurring of recession, the inflation rate has remained quite stable between 2% and 3%. Economists use fluctuations in exchange and inflation rates to measure the depth of an economy. However, the unemployment statistics reveal that during the recession, the unemployment rate in the United States increases quite dramatically. For instance, soon after the sub-prime mortgage crisis, the unemployment rate increased to 9%, which was huge as per the standards of developed countries.
The health of the first model of statistical analysis, we devised to understand that the impact of inflation on unemployment, was poor (F-value greater than 0.05). Also, the value of the adjusted r-square was also very low (0.126). It means that our model only explains 12% of the relationship between inflation and unemployment. Furthermore, the p-value was also greater than the critical value, which was 0.08 (8%). The value of the coefficient was -0.93, which implies that with one unit increase in inflation, unemployment will decrease by around 93%. This result is by other results about the relationship between inflation and unemployment.
To address this issue, we used the robust regression model. The overall health of the model improved; however, the value of coefficient became apocryphal. For instance, the value of the coefficient was 2.72, which goes against the principles of economics and also against the studies on this subject. The value of the Durban-Watson is also low/not-desired, which is primarily because of the number of observations.
Conclusion
From descriptive and statistical analysis reveals that the American economy is stable and there is a negative relationship between inflation and unemployment. However, we cannot accept the results of statistical analysis, because of F and P values. I presume that if we increase the number of variables and the number of observations, we will be able to develop a healthy statistical model, which will be able to produce unbiased and valid results. In light of this academic/research exercise, I suggest that future research on this subject must include more variables and observations.
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