Impact Of Unemployment On Economic Growth In Queensland

Factors contributing to unemployment

Unemployment is considered as a multidimensional problem. Unemployment has both economic and social consequences. Unemployment in an economy is identified as a situation of imbalance between labor supply and labor demand. Various factors can be responsible for persistent unemployment problem (Mavromaras, Sloane & Wei, 2015). The paper discusses impact of unemployment on economic growth in Queensland. Australia though has achieved the fastest development in the last few decades but unemployment rate remains considerably high, above 5%. The spread of unemployment problem is not uniform. Some states like Queensland, Western Australia, Tasmania and South Australia has a higher unemployment rate than other (Ball, 2014). The paper focuses on unemployment problem in Queensland and its likely consequence on economic growth.

The paper intends to find the impact of unemployment on economic growth of Queensland. It compares the unemployment rate of Queensland in the last ten years with that of the national unemployment rate. Relation between labor force participation and unemployment has also been evaluated. With this, the paper also aims to find how the employment statistics changes in different industries between 2013 and 2017. It also attempts to find how labor force participation impacts rate of unemployment. Unemployment of the particular state has also been compared with that of other states and with national average unemployment rate.

Objectives of the research paper are as follows

• To find out the relation between unemployment and economic growth of Queensland
• To compare unemployment rate of Queensland with other states of Australia and that of national average
• To find out how number of employed person in different industries of Queensland has been changed between 2013 and 2017
• To find out the relation between labor force participation and unemployment rate

This section briefly discusses previous researches conduction in this area. The result of previous paper provides needful insights and a clear understanding regarding the research area and helps to design the present research in a convenient way.

Studies found an association of unemployment rate with that of the structural change and economic growth. Unemployment can directly or indirectly interrupt economic growth. In short run, there is an inverse relation between unemployment and economic growth associated with phases of business cycle (Stamatiou & Dritsakis, 2015). Persistently high unemployment imposes an economic cost that restricts long term economic growth. Unemployment not only imposes a social cost upon individual but it also entails cost to the entire economy (Yelwa, David & Awe, 2015).

High unemployment indicates inefficient allocation of resources. High unemployment rate reduces aggregate income of the nations (Meyer & Tasci, 2012). Lower income means a lower consumption and lower saving. Decline in saving reduces available funds for investment (Cortinovis & Van Oort, 2015). When investment reduces productivity declines and so is the economic growth.

Previous literature carried out tests to verify the relation between unemployment and economic growth for G7 countries (Dvoulety & Lukes, 2016). Data ranging from 1987-2007 revealed a consistent result with Okun’s law and forecast of professional economist. In the study a direct relation had been found between real output growth and unemployment rate (Owyang & Sekhposyan, 2012). Similar results had also been found when statistical test conducted on OECD nations (Benigno, Ricci & Surico, 2015).

Unemployment in Queensland

Mosikari (2013) tested relation between unemployment and gross domestic product for South Africa. In the study data has been considered for the period ranging between 1980 and 2011. In the study, gross domestic product was used as a dependent variable and inflation, investment, unemployment rate and government expenditures are taken as independent variables (Castells-Quintana & Royuela, 2012). The time series analysis found the variables and co-integrated among themselves with order one. This paper however failed to establish causal relation between unemployment and economic growth (Mosikari, 2013).

A paper developed by Ogueze & Odim (2015), examined unemployment cost in terms of Nigerian economic growth. Time series data of 40 years (1970-2010) had been used in the analysis. This paper considered variables such as real GDP, unemployment rate, investment rate, interest rate, money supply and import (Al-Habees & Rumman, 2012). This paper concluded an inverse relation between unemployment and economic growth (Ogueze & Odim, 2015).

Another study conducted by Onwachukwu (2015), evaluated relationship between unemployment and economic growth.  Data in the study used ranged from 1985 to 2010. This paper examined the association of economic growth with that of unemployment and inflation (Darma & Onimisi, 2017). Both the variables unemployment and inflation found to have a significant negative relation with economic growth (Onwachukwu, 2015).

The effect of unemployment on productivity growth of Nigeria had been examined in the paper designed by Ditimi & Ifeakachukwu (2013). The study was based on data ranging from 1986 to 2010. In the study productivity growth was taken as an independent variable. In addition to unemployment rate, other independent variables in the study included capital, labor, government expenditure and inflation rate (Abula & Ben,2016). This study found a positive relation between unemployment and economic growth. The result contrasted findings of previous studies (Ditmi & Ifeakachukwu, 2013).

Okun’s law had been empirically tested for Asian countries taking data from 1980- 2006 (Dellink et al., 2017). The Engel Granger Causality tests found a long term relation between unemployment and output growth of a nation. Chang-Shuai & Zi-Juan (2012), conducted a research to identify the relation between unemployment rate, inflation and economic growth for Chinese economy. Vector Auto Regression and Vector Error Correction models are used to estimate a causality relation between the variables. For China, unemployment was found to have an adverse effect on growth while inflation had a positive influence on economic growth (Chang-Shuai & Zi-Juan, 2012).   

Impact of unemployment on economic growth

Based on the insights from previous researches and objective of the current paper two hypotheses are developed.

Hypothesis 1

Null hypothesis (H0): No significant relation exists between unemployment rate and economic growth of Queensland

Alternative hypothesis (H1): There exists a statistically significant relation between unemployment rate and economic growth of Queensland.

Hypothesis 2

Null hypothesis (H0): No significant relation exists between unemployment rate and labor force participation rate of Queensland.

Alternative hypothesis (H1): There exists a statistically significant relation between unemployment rate and labor force participation rate of Queensland.

The paper attempts to find the association of unemployment with economic growth and labor force participation rate. A sample of twelve-year period (2006-2017) has been taken for consideration. Data are collected from official websites of Australia and then are analyzed using software package SPSS.

In the paper, the variable of interests are mainly unemployment rate, labor force participation rate and economic growth. Data on these three attributes are collected for the period 2006- 2017. In order to compare unemployment rate of Queensland to that of other states and that of national average unemployment data are collected for different states and that of Australia. Data has been also collected on number of employed person in some major industries between 2013 and 2017.

The collected data are analyzed using different statistical methods. Descriptive statistics are used to summarize major characteristics of the data (Peck, Olsen & Devore, 2015). Bivariate correlation indicates the relation between different variables. Finally, to estimate the relation between unemployment and economic growth and that of labor force participation rate linear regression is used. The ANOVA table provides significance of the estimated model (Larsen & Marx, 2017).

Table 1: Descriptive Statistics for unemployment rate, participation rate and economic growth rate

Statistics
	Unemployment_rate	Participation_rate	Economicgrowth_rate
N	Valid	12	12	12
Missing	0	0	0
Mean	5.4000	66.4417	3.0000
Std. Error of Mean	.27136	.29063	.57300
Median	5.6500	66.6000	2.4000
Mode	3.70a	65.80	1.40
Std. Deviation	.94002	1.00676	1.98494
Variance	.884	1.014	3.940
Skewness	-1.052	-.305	.665
Std. Error of Skewness	.637	.637	.637
Kurtosis	-.088	-1.481	-1.007
Std. Error of Kurtosis	1.232	1.232	1.232
Range	2.70	2.90	6.00
Minimum	3.70	64.80	.60
Maximum	6.40	67.70	6.60
Sum	64.80	797.30	36.00
a. Multiple modes exist. The smallest value is shown

From the descriptive statistics, the average unemployment rate in Queensland for the twelve years is found to be 5.4%. The average growth rate for the sample period is 3%. The mean value of labor force participation rate is 66.47 percent. For all the three variables standard deviation is smaller compared to the mean value. This indicate a smaller coefficient of variation implying a relatively stable distribution.

Table 2: Descriptive statistics for unemployment rate of Australia and Queensland

Statistics
	Queensland	Australia
N	Valid	12	12
Missing	0	0
Mean	5.3917	5.3042
Std. Error of Mean	.27136	.17436
Median	5.6100	5.3900
Mode	5.47	4.23a
Std. Deviation	.94001	.60399
Variance	.884	.365
Skewness	-1.025	-.553
Std. Error of Skewness	.637	.637
Kurtosis	-.137	-.624
Std. Error of Kurtosis	1.232	1.232
Range	2.72	1.84
Minimum	3.69	4.23
Maximum	6.41	6.07
Sum	64.70	63.65
Percentiles	25	4.7125	4.8550
50	5.6100	5.3900
75	6.1200	5.7100
a. Multiple modes exist. The smallest value is shown

As obtained from the descriptive statistics, the mean unemployment rate in Queensland is higher than that of the whole economy. Standard deviation of unemployment in Queensland is also higher than that of Australia as whole. A larger value of standard deviation indicates a greater variability. Therefore, unemployment rate fluctuates more in Queensland as compared to Australia.

Review of previous researches

As shown from the above figure, initially unemployment rate in Queensland was lower than that of national unemployment rate. However, from 2009 onwards unemployment rate in Queensland exceeds the national unemployment rate and remain above the unemployment rate in Australia.

As shown from the figure, among various states Queensland and Western Australia are the two states having highest unemployment rate of 6.5%. Tasmania and South Australia though have an unemployment rate higher than national average but unemployment rate is lower as compared to Queensland and Western Australia. In all other state unemployment is lower than national average.

Except manufacturing and retail trade employment is found to be lower in 2017 as compared to that in 2013. Massive reduction in employment has been occurred in mining industry with employment reduced to 56,000 in 2017 from 71, 300 in 2013.

Table 3: Correlation matrix for unemployment rate, participation rate and economic growth rate 

Correlations
	Unemployment_rate	Participation_rate	Economicgrowth_rate
Unemployment_rate	Pearson Correlation	1	-.670*	-.683*
Sig. (2-tailed)		.017	.014
N	12	12	12
Participation_rate	Pearson Correlation	-.670*	1	.208
Sig. (2-tailed)	.017		.517
N	12	12	12
Economicgrowth_rate	Pearson Correlation	-.683*	.208	1
Sig. (2-tailed)	.014	.517
N	12	12	12
*. Correlation is significant at the 0.05 level (2-tailed).

From the correlation matrix unemployment is found to have a negative significant association with both participation rate and economic growth rate. The correlation between labor force participation and economic growth rate is obtained as 0.208. This shows a positive association between economic growth and participation rate.

Relation between unemployment rate and economic growth rate

In order to find the relation between unemployment and economic growth a regression is run taking unemployment rate as independent variable and economic growth as dependent variable. Result of the regression is summarized below

Table 4: Regression between unemployment rate and economic growth

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.683a	.466	.413	1.52140
a. Predictors: (Constant), Unemployment_rate

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	20.193	1	20.193	8.724	.014b
Residual	23.147	10	2.315
Total	43.340	11
a. Dependent Variable: Economicgrowth_rate
b. Predictors: (Constant), Unemployment_rate

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	10.783	2.671		4.036	.002
Unemployment_rate	-1.441	.488	-.683	-2.954	.014
a. Dependent Variable: Economicgrowth_rate

The relation between labor force participation and unemployment rate can be modeled as 

The regression results produces R square value as 0.466. The square value indicates unemployment rate can influence 46.8% variation in rate of economic growth. The coefficient of unemployment rate is -1.1441. The negative coefficient suggests an inverse relation between economic growth rate and unemployment. That is an increase in unemployment rate reduces economic growth in Queensland. From the coefficient table, estimated p value is 0.014. As the p value is less than the significance level of 0.05 null hypothesis of significant relation between unemployment and economic growth rate has been rejected (Draper & Smith, 2014).

Relation between unemployment rate and labor force participation rate

In order to estimate the relation between unemployment and labor force participation a regression is run taking participation rate as independent variable and unemployment rate as dependent variable. Result of the regression is summarized below

Methodology

Table 5: Regression between unemployment rate and labor force participation rate

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.670a	.448	.393	.73230
a. Predictors: (Constant), Participation_rate

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	4.357	1	4.357	8.125	.017b
Residual	5.363	10	.536
Total	9.720	11
a. Dependent Variable: Unemployment_rate
b. Predictors: (Constant), Participation_rate

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	46.937	14.573		3.221	.009
Participation_rate	-.625	.219	-.670	-2.851	.017
a. Dependent Variable: Unemployment_rate

From the regression output relation between economic growth and unemployment rate can be modeled as 

The regression results produces R square value as 0.448. The square value indicates participation rate can influence 44.8% variation in unemployment rate. The coefficient of participation rate is -0.625. The negative coefficient suggests an inverse relation between participation rate and unemployment. That is an increase in participation rate reduces unemployment rate in Queensland. From the coefficient table, estimated p value is 0.017. As the p value is less than the significance level of 0.05 null hypothesis of significant relation between unemployment and participation rate has been rejected.

Hypothesis 1: Unemployment has a significant influence on economic growth

 The first hypothesis tries to establish a significant relation between unemployment rate and economic growth. Unemployment indicates incapability of labor market participants. Economic growth is measured from percentage change in gross domestic product from one year to another (Mankiw, 2014). From the correlation and regression analysis a statistically significant inverse relation is obtained between unemployment and economic growth. This means an increase in unemployment rate is unfavorable for prosperity of Queensland. The present study thus supports the finding from previous literature (Capaldo, 2015).

Hypothesis 2: Participation rate significantly influence unemployment rate

The second inference is drawn regarding the relation between unemployment rate and labor force participation rate. Labor force participation rate measured number of people actively participate in the labor market among the eligible working population (Bernanke, Antonovics & Frank, 2015). The analysis finds a negative significant relation between participation rate and unemployment rate. That is with increase in participation rate unemployment rate reduces. This a good sign for labor market performance. Therefore, as more and more people join the labor market, number of unemployed decreases indicating ability of new member of find jobs for them.

Employment has been reduced in almost all the industries in Queensland in between 2013 and 2017. Exception is observed only in manufacturing and retail trade. It is mining sectors that suffers most of job losses in the last few years.

The unemployment rate in Queensland when compared with national unemployment rate has shown that since 2009, unemployment rate in the state remain higher than overall unemployment rate. In terms of unemployment rate, Queensland has been accompanied with Western Australia. Tasmania and South Australia also have unemployment rate higher than national average. In other states unemployment remains around 4-5% but is lower than overall unemployment rate in the economy.

Data analysis and results

Conclusion, Limitation and Recommendation (500)

The first research question is to find how unemployment rate influences economic growth of Queensland. An inverse relation is obtained between unemployment and economic growth. That means persistent unemployment is not good for the health of the economy. With an increase in unemployment rate economic growth of the state reduces inhibiting growth of the state.

The second research question aims to compare unemployment rate of Queensland with that of other states and Australia as a whole. The average unemployment rate in the last twelve years is higher in Queensland than national average. Variability in unemployment is also higher in Queensland. Unemployment rate in Western Australia is equivalent to that in Queensland. South Australian and Tasmania also have a higher unemployment rate with unemployment rate being approximately 6 percent.

The third research question intends to see how employment statistics had been altered among different industries of Queensland. Employment in manufacturing and retail trade has increased while that in mining, agriculture, wholesale trade and other industries and services reduces.

The fourth and last research question is framed to find out the relation between unemployment rate and participation rate. Results finds unemployment and labor force participation moves in the opposite direction. With increase in participation unemployment rate reduces and vice versa.

First limitation of the paper is the relatively small sample period. Analysis of the paper has been based on data taken for only twelve years. In the estimated regression models, the independent variables are though found to be significant both a model has a relatively small R square value indicating a bad fit model. Consideration of a longer time period improve the regression result. Apart from unemployment there are several other variables that determine economic growth. Inclusion of only unemployment as an explanatory factor of economic growth points to another limitation of the study.

The paper finds harmful consequence of unemployment on economic health. A lower economic growth inhibits future economic growth and development. The state therefore should focus on reducing unemployment as much as possible. The state government of Queensland should take effective policies of employment generation to reduce unemployment. Mining sector has suffered from maximum job losses. People from the mining sector should be shifted to other sectors. Manufacturing and retail are the two sectors where employment increases significantly. Morea and more people should join these sectors. Focus needs to be given on enhancing skills of labor force so that they can join high tech manufacturing sector. Successful policies of employment generation will reduce unemployment ensuring a higher economic growth for Queensland.

Descriptive statistics

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