By Nwamuo, C (2022).

Greener Journal of Social Sciences

Vol. 12(1), pp. 16-24, 2022

ISSN: 2276-7800

Copyright ©2022, the copyright of this article is retained by the author(s)

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Government Expenditure and Unemployment Rate in Nigeria: An Empirical Analysis

 

 

Chukwuemeka Nwamuo (Ph.D)

 

 

Department of Economics, Rhema University, Aba.

 

 

 

 

ARTICLE INFO

ABSTRACT

 

Article No.: 070722068

Type: Research

Full Text: PDF, HTML, PHP, EPUB

 

The study investigated the impact of government expenditure on unemployment rate in Nigeria. Time series data spanning from 1991 to 2020 which were used in the study were sourced from the Central Bank of Nigeria (CBN) statistical bulletin and the World Development Indicators (WDI). The ARDL bounds testing approach to cointegration was used to analyse the data. Autoregressive Distributed Lag (ARDL) model and Error Correction Model (ECM) were utilized to address the main objectives of the study. The estimated short run coefficient result revealed that capital expenditure has a negative and significant impact on unemployment rate while recurrent expenditure and credit to private sector have a positive and significant impact on unemployment rate. The speed of adjustment for correcting disequilibrium from the previous year to equilibrium in current year is 37.23 percent as shown by the coefficient of ECM. The estimated long run coefficient showed that capital expenditure and recurrent expenditure have a negative relationship with unemployment rate. The result also showed that capital expenditure is statistically significant while recurrent expenditure is not statistically significant. The result also showed that credit to private sector has a positive and significant impact on unemployment rate.  Based on these findings, the study recommends proper management of government expenditure by ensuring that capital expenditures are channelled towards productive sectors and ensure that there is transparency in the management of such fund.

 

Accepted:  07/07/2022

Published: 04/08/2022

 

*Corresponding Author

Dr Chukwuemeka Nwamuo

E-mail: mekuzy2002@ yahoo.com

 

Keywords: Capital expenditure, recurrent expenditure, credit to private sector, unemployment rate.

 

 

 

 

 

 


1.1    INTRODUCTION

 

Bhatia (2009) defined public expenditure as those expenses that government incurs to maintain itself, the society and the economy and in helping other countries. In the words of Njoku (2009), public expenditure refers to all expenditures, both recurrent and capital expenditures which the government incurs in the course of performing its functions. Public expenditure is structured into two major categories which includes recurrent expenditure and capital expenditure. Recurrent expenditure are expenditures that occur regularly throughout the year while capital expenditure refers to all the expenditures on capital projects such as buildings, construction of roads, bridges and all permanent structures and assets.  The effects of public expenditure include making for economic stabilization, stimulation of production in the economy, creation of human skills through education and training development of basic infrastructures and stimulation of economic growth (Chijioke, 2014).

 

1.2 Statement of problem:

 

The Nigeria’s public expenditure has been increasing over time. Available data shows that total recurrent expenditure increased from N38.24 million in 1991 to N579.3 million in 2001 while total capital expenditure increased from N28.34 million in 1991 to N918.55 million in 2001. The available data  also showed that total recurrent expenditure further increased from N47799.99 million in 2017 to N8121.64 million in 2020  while total capital expenditure also rose from N1242.30 million in 2017 to N1614.89 million in 2020 (Central Bank of Nigeria statistical bulletin 2021). Given that one of the main objectives of increases in government expenditure is to stimulate investment so as to reduce unemployment rate, these increases in both recurrent and capital expenditure is expected to stimulate investment thereby reducing unemployment rate in Nigeria. Unfortunately, increases in government expenditure has not been to reduce unemployment rate in Nigeria as available statistics shows that unemployment rate increased from 3.1 percent in 1991 to 13.1 percent in 2001. It also continued to increase from 18.8 percent in 2017 to 30.33 percent in 2020 (World Development Indicators). The study therefore seeks to investigate the impact of government expenditure on unemployment rate in Nigeria.

 

1.3 Objectives of the study:

 

The broad objective of the study was to investigate the impact of government expenditure on unemployment rate in Nigeria. The specific objectives of the study were:

(i). To examine the impact of capital expenditure on unemployment rate in Nigeria.

(ii). To investigate the impact of recurrent expenditure on unemployment rate in Nigeria.

(iii).To examine the impact of credit to private sector on unemployment rate in Nigeria.

 

1.4 Hypothesis of the study:

 

In order to guide the study, the following null hypotheses were formulated:

HO1: Capital expenditure does not have any impact on unemployment rate in Nigeria.

HO2: Recurrent expenditure does not have any impact on unemployment rate in Nigeria.

HO3: Credit to private sector lending does not have any impact on unemployment rate in Nigeria.

 

 

2.0 LITERATURE REVIEW

 

2.1 Theoretical literature

 

2.1.1 The Wagner’s Law:  

 

the theory states that as per capita income of an economy grows, the relative size of government expenditure grows along with it. As the economy grows, there will be an increase in the number of urban centres with the associated social vices such as crime which require the intervention of the government to reduce such activities to the barest minimum. Large urban centres also require internal security to maintain law and order. These interventions by the government have cost leading to increase in public expenditure in the economy.

 

2.1.2 Rostow-Musgrave model: Rostow and Musgrave also carried out a research on the growth of public expenditure and conclude that at early stages of economic development, the rate of growth of public expenditure will be very high because government provides the basic infrastructural facilities (social overhead) and most of these projects are capital intensive, therefore the spending of the government will increase steadily. The investment in education , health, roads, electricity, water supply are necessities that can launch the economy from the traditional stage to the take off stage of economic development making government to spend an increasing amount with time in order to develop an egalitarian society.

 

2.1.3 Peacock-Wiseman’s model: they looked at increasing public expenditure on the socio-political perspective. Government expenditure will increase as income increases but because the leaders want re-election into political offices so more infrastructure must be provided in order to convince the electorate that their interest is being catered for by the people they voted into power. However, the citizens of the country are less willing to pay tax. The resistance of individuals to pay tax must be taken care of by the government in the form of increased spending to avoid social crisis in the economy. The resistance to pay tax by the people will make the state to have low revenue hence the cost of providing more facilities is borne by the government making government  expenditure to rise rapidly (Likita, 1999).

 

2.1.2 Conceptual literature: Public expenditure is the expenses or cost that government usually incurs for maintenance of itself as an institution, the economy and the society (Likita, 1999). Public expenditure, according to Chinwoke 2014, is the expenses of the government for its own maintenance and on the society and the economy as a whole.  Bhatia (2009) sees public expenditure as the expenses which a government incurs for its own maintenance the society and the economy and helping other countries. Anyanwu (1997) opined that public expenditure involves all the expenses which the public sector incurs for its maintenance, for the benefit of the economy, external bodies and for other countries. In the words of Likita (1999), public expenditure is made up of the capital and recurrent expenditure. Capital expenditure include  all investment in infrastructural projects, physical assets that are for long term purposes, mainly to improve the living conditions of the citizens and this includes housing, road construction, agriculture and water resources, these are generally productive investments. The recurrent expenditures are generally spending on service to maintain the existing facilities in the economy including wages and salaries, maintenances of social services and security.

 

There are principles that also govern the public expenditure decision. They include: (i) canon of sanction which advocates that public fund can only be used by proper authorization and for the purpose for which it approved. In a democratic set up, it is the legislature that sanctions the expenditure on demand by the executive authorities. The rationale is that such a restriction would avoid unscrupulous and unwanted expenditure and it will observe as a check against misappropriation of public funds.  (ii) canon of economy which suggests that necessary care must be taken to avoid wasteful usage of public funds. The process of public expenditure should not involve the use of resources more than what are just necessary. (iii) canon of benefit which suggests that expenditure is to incurred only if it is beneficial to the society. Expenditure is therefore judged by the benefit that will accrue from it. (iv)  canon of surplus which emphasizes on the fact  that government should avoid deficit budgeting at least for the greater part of the time, that is, persistent one. Government should be prudent and try to meet its current expenditure from current revenue. Government should not spend beyond its available resources into a debt (Chinweoke, 2014).

 

The effect of public expenditure   include: (a) it makes for economic stabilization. The economy is prone to fluctuations in income, employment and prices from time to time. During periods of depression, there is the need for a continuous injection of additional purchasing power in the market through stimulation of investment and consumption activities and through direct public investment  which a part of public expenditure. Such a public expenditure is meant to directly add to the effective demand in the market and generate a high value multiplier effect in the economy. Again during a boom, the need to curb extra demand arises. This may be done through the reduction in public expenditure while maintaining the same or slightly raising the level of taxation. (b) public expenditure in an economy accelerates the pace and development of economic activities in the economy thus leading to the attainment of higher levels of production and growth. Public expenditure can add to the effective demand directly and thus, generate conditions favourable for the market forces to push up production. Public expenditure aids private investments and production through measures which reduce the cost of production or remove particular bottle–necks creation and maintenance of social over heads lead to an all-round reduction in the cost of production and improvement in efficiency. (c) public expenditure stimulates research and development in an economy. New, effective and cheap method of production can be found whereby local resources are used in production and thus imports are reduced while foreign exchange is saved. New products can also be invented which will help the economy various productive activities. (d) public expenditure can be used to create human skills through education and training. The federal government through the education tax fund has developed infrastructures such as classroom blocks, laboratories, libraries, computer centers in many tertiary institutions public expenditure aids the development of basic infrastructures. This is for the development of selected economic activities, for example, roads, electricity, housing, public health. With these infrastructures in place, key and basic industries, power, irrigation, mines are developed. Through these, the economy is provided a firm basis for growth. (Chinweoke. 2014).

 

2.3 Empirical literature

 

Saraireh (2020) estimated the effect of government spending on unemployment in Jordan for the period 1990 to 2019. By using the ARDL co-integration test the study found a negative and statistically significant long-run relationship between government spending and unemployment rate in Jordan. An increase in government spending per a percent of the GDP is found to reduce unemployment by about 0.43 percentage points in the same year. The study also revealed that in the short run, government spending has positive and significant impact on unemployment.

 

Ebi and Ibe (2019) empirically examined the causal relationship between government expenditure and unemployment from 1981 to 2017. Data used was secondary and obtained from Central Bank of Nigeria (CBN) Statistical Bulletin of various years and other reports. Unemployment rate was the dependent variable. Government expenditure was decomposed into recurrent and capital expenditure (independent variables). Unit root test indicates the variables were integrated in order (I). Co-integration test results indicate a long-run equilibrium relationship between unemployment rate (UEMR), recurrent expenditure (REXR) and capital expenditure (CEXR). The study revealed that was a negative and significant relationship between unemployment rate (UEMR) and recurrent expenditure (REXR). The negative relationship agrees with a priori expectations. On the other hand, relationship between unemployment rate (UNER) and capital expenditure (CEXR) is positive and significant. However, the positive relationship was contrary to the a priori expectation. This means that a change in government expenditure will impact unemployment rate. Increased government capital expenditure results in increased unemployment rate instead of a decrease. The study showed that there was no causal relationship amongst all the variables of interest. The study among others recommended that there should be re-allocation of capital expenditure so as to enhance employment opportunities for unemployed people.

 

Nwaeze (2019) empirically investigated the direction and degree of relationship between government spending and reduction in unemployment Secondary data for the period 2005  to 2019 sourced from the CBN Statistical bulletin were used to experiment on the disaggregated impact of government expenditure on administration, economic services, social community services and transfers have on the rate of unemployment in Nigeria. The Error Correction econometric model (ECM), the Johansen co-integration and the Granger causality tests were the central analytical tools used in the study. The stationary test showed that the variables were non-stationary at levels but all were stationary at first difference. In the short-run, a positive relationship was observed. The short-run coefficient of economic service and unemployment was observed to be negative and the direction of causality was from government expenditure on economic services. Expenditure on social community service observed negative and statistically and observed a weak causal influence on unemployment. Government expenditure on Administration was found to be positive and statistically significant and the direction of causality was from government expenditure on administrative expenses. However, there was no causal relationship between government expenditure on transfers and unemployment. The study recommends the need for policy makers to keep an eye on the trend and effects of changes in expenditure on administration and economic services,

 

Egbulonu and Amadi (2016) examined the relationship between fiscal policy and unemployment rate in Nigeria for the period 1970 to 2013. Data for the study were sourced from the National Bureau of Statistics (NBS) and the Central Bank of Nigeria (CBN) Statistical Bulletin (various editions), and consists of Government Expenditure, Government Debt Stock (as proxy for Government borrowing), Government Tax Revenue and Unemployment rate. The data were tested for Stationarity using Augumented Dickey-Fuller (ADF) Unit Root test. The test revealed that all the variables used in the study are stationary at their first difference. The data were also subjected to co-integration test in order to know whether using the variables together in the model would produce reliable results. The test revealed that a long run relationship between unemployment rate and fiscal policy tools used in the study which satisfy the condition for fitting a parsimonious Error Correction Model (ECM) to the data. The study found a negative relationship between fiscal policy tools (government expenditure and government debt stock) and unemployment rate in Nigeria while government tax revenue exhibited a positive relationship with unemployment rate. The results also reveal that, there exist a long-run equilibrium relationship between unemployment and fiscal policy in Nigeria. The study recommended among others that government should increase her capital expenditure mostly on infrastructure as this will help improve national income and create more employment in the economy.

 

Selase (2019) investigated the impact of disaggregated public expenditure on unemployment rate in selected African countries with panel data spanning from 2000 to 2017. The data were majorly sourced from the World Bank Indicator. The study employed Generalized Method of Moments (GMM) techniques for empirical analysis. The findings of two-step system GMM showed that expenditure on infrastructure and education reduce unemployment rate, while expenditure on defense and health increase unemployment rate in the region. The short-run elasticity estimate showed that infrastructure and education expenditures reduce unemployment rate by 9% and 1.83%. A unit rise in defense and health expenditure increase unemployment rate by 5.2% and 84.5%. The long-run elasticity of infrastructure and education expenditure reduce unemployment rate by 3.8% and 7.89 %, while the long-run defense and health expenditure elasticity’s increase unemployment rate by 22.22% and 364.58% in the selected African countries.  Therefore, the study recommended among others a drastic measure to further improve the education sector through adequate investment in education that will help in skills, development and training.

 

Onuoha and Agbede (2019) examined the impact of disaggregated public expenditure on unemployment rate in Angola, Benin, Botswana, Cameroun, Central African Republic, Chad, Egypt, Equatorial Guinea, Ethiopia, Ghana, Kenya, Mauritius, Morocco, Namibia, Nigeria, South Africa, Sudan, Tanzania, Togo and Tunisia with panel data spanning from 2000 to 2017. The data were majorly sourced from the World Bank Indicator. The study employed Generalized Method of Moments (GMM) techniques for empirical analysis. The findings of two step system GMM showed that expenditure on infrastructure and education reduce unemployment rate, while expenditure on defense and health increase unemployment rate in the region. The short-run elasticity estimate showed that infrastructure and education expenditures reduce unemployment rate by 9% and 1.83%. A unit rise in defense and health expenditure increase unemployment rate by 5.2% and 84.5%. The long-run elasticities of infrastructure and education expenditure reduce unemployment rate by 3.8% and 7.89%, while the long-run defense and health expenditure elasticities increase unemployment rate by 22.22% and 364.58% in Angola, Benin, Botswana, Cameroun, Central African Republic, Chad, Egypt, Equatorial Guinea, Ethiopia, Ghana, Kenya, Mauritius, Morocco, Namibia, Nigeria, South Africa, Sudan, Tanzania, Togo and Tunisia. The study recommended among others a drastic measure to further improve the education sector through adequate investment in education that will help in skills, development and training.

 

Rahmat and Saeidi (2017) investigated the effect of government development expenditures on unemployment rate in the Provinces. The study period was from 1998 to 2013. In this period all provinces of the country with segregation in two provinces were divided into large and small provinces that were considered as a research population and statistics and relevant information were obtained from sources of information and the Statistical Center of Iran. In order to analysis data and the estimation of econometrics patterns, Excel and Eviews econometric softwares were  used. The results revealed that Government development expenditures have a significant negative effect on the unemployment rate in the province. Also, all logarithmic models on large and small provinces for the government development expenditures showed that on large provinces a negative coefficient 0.049 was obtained which was significant at 5% probability level and in small provinces negative coefficient of 0.07 was obtained which was significant at 5% probability level. So, the results relate to all algorithms models in large and small provinces showed that that the effect of government development expenditure in small provinces is more than the large provinces.

 

3.0 Methodology Multiple regression analysis was used in the study. Time series data spanning from 1991 to 2020 was sourced from the Central Bank of Nigeria statistical bulletin and World Bank Development Indicators. The data was analysed using E-views 10

 

3.1 Model specification: In order to investigate the impact of government expenditure on unemployment rate in Nigeria, the model for this study was specified thus;

 

UNEMP = f (CAP, REC, CRP) …. (1)

 

Where: UNEMP = Unemployment rate

CAP = Capital expenditure

REC =  Recurrent expenditure

CRP =  Credit to private sector

 

The model in its econometric linear form can be written as: UNEMP = b0 + b1CAP + b2REC + b3CRP + U …… (2)

 

U = stochastic or random error term

bo = constant intercept

b1 – b3 = coefficients of associated variables

 

The theoretical expectations about the signs of the coefficients of the parameters are as follows: b1<0, b2<0, b3<0,

 

The Augmented-Dickey Fuller (ADF) unit root test was employed to ensure data stationarity and avoid the problem of spurious regression since the data for the analysis is time series. Bound test was applied to determine the existence of long run equilibrium relationship among the variables

 


 

Table 1: Result of Augmented Dickey-Fuller unit root test

Variable

ADF test statistic

1% critical value

5% critical value

10% critical value

Order of integration

CAP

-5.004229

-4.339330

-3.587527

-3.229230

1(0)

REC

-4.474095

-4.467895

-3.644963

-3.261452

1(1)

CRP

-4.446231

-4.4356068

-3.595026

-3.233456

1(1)

UNEMP

-3.389460

-3.769597

-3.004861

-2.642242

1(0)

Source: Author’s computation using EViews 10

 


The unit test result presented on table 1 showed that CAP and UNEMP were stationary at level while REC and CRP were stationary at first difference. This is because their various ADF test statistic were greater than their various 1%, 5% and 10% critical values in absolute terms.

 


 

 

Table 2: ARDL Bounds Test

                                   Sample: 1991-2020

 

                         Included observations: 26

Null Hypothesis: No long run -relationships exist

Test Statistic

Value

K

F-statistic

14.40138

3

                          Critical value bounds

Significance

1(0) bound

1(1) bound

10%

2.37

3.2

5%

2.79

3.67

2.5%

3.15

4.08

1%

3.65

4.66

Source: Author’s computation using EViews 10

 

 

 


The unit test result showed that the data employed in the work is a combination of 1(0) and 1(1) meaning that the date set is a combination of stationarity and non- stationarity data as a result the applied Bound test to determine the existence  of long run equilibrium relationship among the variables. Table 2 shows that there is a presence of co-integrating relationship among the Variables in the model since the Null hypothesis of no long run relationship could not be accepted because the upper and lower Critical Value Bounds at all level of significance is less than the value of F-Statistic. This implies that UNEMP, CAP, REC and CRP have a long run relationship. This justifies the need to estimate both short run and long run relationship among these variables in this study.

 


 

 

                   Figure 1 : Model stability test

 


Source: Author’s computation using EViews 10

 

 

To investigate the existence of a possible structural instability, the study used the Cusum test on figure 1 and found that the cumulative sum remained within the area between the two critical lines showing that test did not detect any systematic eventual movements and that the coefficients values reflect structural stability.

 


 

Figure 2: Normality test  

 


 Source: Author’s computation using EViews 10

 

 

Figure 2 above, shows that there exists normal distribution of the residuals as the probability (0.713408) of Jaque-Bera statistics is greater than 5%. This is encouraging as it exposes that our OLS estimates are unbiased, t-statistics and confidence intervals are robust as well as prediction intervals.


 

 

 Table 3:  Estimated Short Run ARDL (1, 1, 2, 4)

 

 

 

 

 

Variable

Coefficient

Std. Error

t-Statistic

Prob.   

 

 

 

 

 

 

 

 

 

 

D(CAP)

-0.000738

0.000208

-3.549402

0.0032

D(REC)

0.000894

0.000211

4.233891

0.0008

D(REC(-1))

0.001823

0.000231

7.895898

0.0000

D(CRP)

0.000196

4.10E-05

4.770943

0.0003

D(CRP(-1))

.-9.11E-05

4.54E-05

-2.006286

0.0645

D(CRP(-2))

4.32E-06

4.73E-05

0.091262

0.9286

D(CRP(-3))

-0.000298

5.47E-05

-5.442355

0.0001

             ECM(-1)*

-0.372309

0.038694

-9.621864

0.0000

 

 

 

 

 

 

 

 

 

 

R-squared

0.883468

    Mean dependent var

0.199231

Adjusted R-squared

0.838150

    S.D. dependent var

0.612764

S.E. of regression

0.246519

    Akaike info criterion

0.284900

Sum squared resid

1.093885

    Schwarz criterion

0.672007

Log likelihood

4.296294

    Hannan-Quinn criter.

0.396373

Durbin-Watson stat

1.675453

 

 

 

Source: Author’s computation using EViews 10

 


The estimated short run coefficient result as showed in table 3 revealed that CAP has a negative and significant  impact on unemployment rate while REC, one period lag of REC and CRP have a positive and significant impact  on unemployment rate. The result also showed that one period lag of CRP and three periods lag of CRP have a negative and significant impact on unemployment rate while two periods lag of CRP has a positive and significant impact on unemployment rate. The error correction model (ECM) which shows the speed of adjustments back to equilibrium in the estimated model is correctly sign and is significant. The speed of adjustment for correcting disequilibrium from the previous year to equilibrium in current year is 37.23 percent as shown by the coefficient of ECM. In another words, this implies that an approximately 37.23 percent of disequilibrium from the previous year’s shock converge to the long-run equilibrium in the current year.


 

 

Table 4: Estimated Long Run Coefficient of ARDL (1, 2, 1, 4) Result

 

 

 

 

 

 

 

 

 

 

Variable

Coefficient

Std. Error

t-Statistic

Prob.   

 

 

 

 

 

 

 

 

 

 

CAP

-0.006172

0.002707

-2.279911

0.0388

REC

-0.001214

0.000732

-1.657740

0.1196

CRP

0.000653

0.000172

3.787971

0.0020

C

5.187444

0.631109

8.219573

0.0000

 

 

 

 

 

 

 

 

 

 

EC = UNEMP - (-0.0062*CAP  -0.0012*REC + 0.0007*CRP + 5.1874 )

Source: Author’s computation using EViews 10

 

 


The estimated long run coefficient result in table 4 showed that capital expenditure (CAP) and recurrent expenditure (REC) has a negative relationship with unemployment rate (UNEMP). The result also showed that CAP is statistically significant while REC is not statistically significant. The result also showed that credit to private sector (CRP) has a positive and significant impact on unemployment rate (UNEMP). A unit increase in capital expenditure will bring about 0.006172 units fall in unemployment rate while a unit increase in recurrent expenditure will bring about 0.001214 units reduction in unemployment rate. The result also showed that a unit increase in credit to private sector (CRP) will lead to 0.0000653 units increase in unemployment rate.

 

4.1 Summary:

 

The study examined the impact of government expenditure  on unemployment rate in Nigeria for the period 1991–2020.The estimated short run coefficient result revealed that CAP has a negative and significant  impact on unemployment rate while REC, one period lag of REC and CRP have a positive and significant impact  on unemployment rate. The result also showed that one period lag of CRP and three periods lag of CRP have a negative and significant impact on unemployment rate while two periods lag of CRP has a positive and significant impact on unemployment rate. The speed of adjustment for correcting disequilibrium from the previous year to equilibrium in current year is 37.23 percent as shown by the coefficient of ECM. The estimated long run coefficient showed that capital expenditure (CAP) and recurrent expenditure (REC) has a negative relationship with unemployment rate (UNEMP). The result also showed that CAP is statistically significant while REC is not statistically significant. The result also showed that credit to private sector (CRP) has a positive and significant impact on unemployment rate (UNEMP).

 

4.2 Recommendations:

 

Both the short run and long run result  of the study showed that there is a negative and significant relationship between capital expenditure and unemployment rate in Nigeria but a negative and insignificant relationship between recurrent expenditure and unemployment rate though positive and significant relationship between recurrent expenditure and unemployment rate in the short run. Based on these findings, the study recommends proper management of government expenditure by ensuring that capital expenditures are channeled towards productive sectors and ensure that such that there is transparency in the management of such fund.

 

 

REFERENCES

 

Anyanwu, J.C (1997). Nigerian Public Finance.  Joanee Educational Publishers.

Bhatia, H.L (2009). Public Finance. Vikas Publishing House PVT Ltd.

Chinwoke, N (2014) Public Finance in a developing world.  Reconciliation Publishers.

Ebi, R.O and Ibe, R.C (2019). Government Expenditure and Unemployment: Examination of the Nigerian Evidence.  International Journal of Business & Law Research 7(1): 25 – 33.

Egbulonu, K.G and Amadi, K.W (2016). Effect of fiscal policy on unemployment in the Nigerian economy. International Journal of Innovative Finance and Economic Research 4(3), 1 - 7.

Likita, O (1999). Elements of Public Finance. Abayomi Industrial packaging ltd.

Njoku, P.O (2009). Public Finance: Sources, Administration and Management. El ‘Demark Publishers.

Nwaeze, N.C (2019). Does Government Expenditure Stimulate Employment Generation? Disaggregated Empirical Evidence from the Nigerian Economy. Journal of Economics and Sustainable Development 10(16): 1 – 10.

Onuoha, F.C and Agbede, M.O (2019). Impact of Disaggregated Public Expenditure on Unemployment Rate of Selected African Countries: A Panel Dynamic Analysis. Journal of Economics, Management and Trade 24(5): 1-14.

Rahmat, D.M and Saeidi, K (2017). The Effect of Government Development Expenditures on Unemployment Rate in the Provinces. International Journal of Economics and Financial, 7(5): 71 – 77.

Saraireh, S (2020). The impact of government expenditure on unemployment: A case study of Jordan. Asian Journal of Modeling 8(3): 189 – 203.

Selase, A.E (2019). Impact of Disaggregated Public Expenditure on Unemployment Rate of Selected African Countries: A Panel Dynamic Analysis Approach.  American International Journal of Humanities, Arts and Social Sciences 1(2): 47 – 57.


 

 

Cite this Article: Nwamuo, C (2022). Government Expenditure and Unemployment Rate in Nigeria: An Empirical Analysis. Greener Journal of Social Sciences, 12(1): 16-24.