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Rising Unemployment in Nigeria-Public Debt to the Rescue?

Jude Chukwunyere Iwuoha *

1Department of Economics, Enugu State University of Science and Technology,, Nigeria .

Corresponding author Email: jiwuohac@gmail.com


DOI: http://dx.doi.org/10.12944/CRJSSH.3.2.14

Among the macroeconomic challenges facing Nigeria as a country are weak growth of the economy, ever increasing unemployment rate, and increasing inequality occasioned by increasing poverty. In trying to mitigate these challenges, the Nigeria government usually run aborrowing. In all these, the unemployment rate keep rising year-on-year. In this study, we tried to find out whether borrowing will come to the rescue in reducing unemployment in Nigeria, using time series data from 1981 - 2019. Employing the VECM model, we carried out the stationarity and cointegration tests respectively. While the stationarity test confirmed all variables being stationary at I(1), existence of cointegration was also confirmed indicating a relationship between public debt and unemployment which turned out to be an inverse relationship. A high value of ECM was recorded. It was found that unemployment granger causes government debt and debt servicing. The overall result shows that public debt have rendered little or no assistance in combating unemployment in Nigeria. While we do not discourage government from borrowing for the provision of critical infrastructures, corruption should be put in check so as to allow the amount of borrowing be reflected on the infrastructures available, as public debt also has some adverse effects on the economy.


External Debt; Government Expenditure; Public Debt; Unemployment; Vector Error Correction

Copy the following to cite this article:

Iwuoha J. C.Rising Unemployment in Nigeria: Public Debt to the Rescue?. Current Research Journal of Social Sciences and Humanities. 2020 3(2)

DOI:http://dx.doi.org/10.12944/CRJSSH.3.2.14

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Review / Publish History


Article Review / Publishing History

Received: 19-09-2020
Accepted: 19-10-2020
Reviewed by: Prof. Martin Etyang
Second Review by: Dr.JACOB WANYONYI NATO
Final Approval by: Dr Ricardo Pelizzo

Introduction

The sustained debate on the issue of economic growth as a panacea for the reduction of unemployment has been resolved by the Keynesians view of fiscal policy. In their view, the government’s intervention is necessary to enable market economies to stabilize by generating high aggregate demand that will be enough in advancing full employment levels. This is on the assumptions by the Keynesians in the 1930’s that as long as there is unemployment, public debt will not have a crowding-out effect on the private sector (Meedee & Nenbee, 2011; Fideli & Forte, 2012; Egbulonu & Amadi, 2016).1,2,3

The macroeconomic challenges facing Nigeria as a country includes ever-increasing unemployment level, increasing economic, health and social inequality occasioned by high level of poverty and weak growth of the economy (Igberi, Odo, Anoke & Nwachukwu, 2016)4 for which government usually intervenes to stabilize its economy. In trying to boost the economy, one of the strategies used by governments is debt accumulation by way of borrowing. This is done to increase the activities in the country’s economy (Hoag & Hoag, 2006; Ncanywa & Masoga, 2018).5,6 Government can owe money either offshore or onshore (domestic) and in most cases causes deficit financing of the economy (Bonga, Chirowa, & Nyamapfeni, 2015; Jaejoon & Manmohan, 2014; Ncanywa & Masoga, 2018).7,8,6 Accordingly public debt assist governments to invest in critical areas of the economy especially in cases that tax revenues cannot cover such investments. However, government expenditures financed using public debt has its detriments (Tsoulfidis, 2007).9

In Nigeria today, the debate has been on and is centred on merits, demerits and sustainability of the debts being accrued amid the incessant tax increments. According to Fideli & Forte (2012),2 amid the sustained increase in government taxes and deficit budget financing, resources from taxpayers is often shifted to bondholders even with a positive increase in the wealth of taxpayers occasioned by the interruption of the intergenerational equities. Accordingly, Obayori (2016)10 saw the fiscal policy as a tool used in mitigating the intricate economic problem of unemployment and persistent fiscal deficit. Since the fiscal policy is a tool used by governments to effectively control the economy, it can be said that the primary goal of fiscal policy is to address the high rate of unemployment.

Fiscal policy is a tool used in the redistribution of income and welfare. As such, the government has been defending the huge debts accruing to the country with this. Public spending remains a tool used in Nigeria to influence growth and development. These expenditures take either the form of capital expenditure, which includes public works and goods or recurrent expenditure, which includes salaries and allowances (Igwe, Edeh & Ukpere, 2015).11 According to Keynesian economics, increased public spending invigorates the economy by way of increased investment, income, growth and consequently improved economic well-being. However, in the case of Nigeria, the annual budgets have been increasing year-on-year, yet the economy is characterized by high unemployment, hunger, poor investments and poor infrastructural development.


In trying to finance the budget deficits in Nigeria, various governments embark on a borrowing spree. Therefore this paper investigated whether increased borrowing will come to the rescue in reducing the macroeconomic challenge of increasing unemployment in Nigeria. This is to test the impact of fiscal policy used by the government in trying to stem the ever-rising unemployment rate in Nigeria, hence attempt to decipher the causes of the ever-increasing unemployment and lack of provision of infrastructure in Nigeria that has become the government’s justification for the accumulation of huge debts. This study makes a contribution to knowledge by looking at the implications of increasing public debt as a fiscal policy tool on the reduction of unemployment in Nigeria. We briefly discussed relevant literature in section 2, presented and explained methodological issues in section 3, outlined, interpreted and discussed our empirical findings in section 4, while concluding the paper in section 5.

Review of literature

Theoretical Review

Classical Theory of Unemployment

According to the classics, the only unemployment is the number of persons wishing not to work at the prevailing wage rate and is determined as the difference between total working population (N) and the equilibrium labour (LE). The classicals saw total unemployment, U, as the sum of voluntary unemployment, UV and frictional unemployment, UF.

Thus U = UV + UF ………………………… (1)

The classical school treats labour market like any other market in which labour demand and supply is a function of prices. In a nutshell, LS = f(w/p) …………………….(2)

Also, LD = f(w/p) ……………………..(3)

Where w/p is the real wage rate, on the assumption that (a) producers who hire labour services are profit maximizers, and workers are utility maximizers and (b) wages and prices are flexible, (c) equilibrium labour and supply are independently determined in the labour market.

Keynesian Theory of Unemployment

In contrast to the Classical position, Keynes distinguished unemployment into either voluntary or involuntary. While he literally agreed with the classical on the definition of voluntary unemployment, he defined involuntary unemployment as the difference between labour demand and what labour demand would have been all things being equal. According to Keynes, labour demand is influenced by the money wage rate, and labour supply is influenced by the expected real wage rate. He went further to argue that for the fact that employees can predict their expected price, actual price, therefore, equals expected price.

The Keynesian Theory of Fiscal Policy

Keynesian fiscal policy is the management of government spending and taxation with the objective of maintaining full employment. According to Keynes, economies could languish indefinitely with high unemployment if aggregate demand is inadequate. He opined that increased government spending would not only boost demand directly but would also set off a chain reaction of increased demand, same way tax cuts would put more disposable income in the wallets of consumers. Keynes contended that increased government spending, on the other hand, would not only boost demand directly but would also set off a chain reaction of increased demand from workers and suppliers whose incomes had been increased by the government's expenditure. Similarly, a tax cut would put more disposable income in the wallets of consumers, and that too would boost demand. Keynes contended, then, that the appropriate fiscal policy during periods of high unemployment was to run a budget deficit. These ideas flew in the face of the conventional wisdom that budget deficits were always bad (David, Stanley & Rudiger, 2000).12

However, it should be of note that the effects of fiscal policy are not the same for everyone. Depending on the political orientations and goals of the policymakers, a tax cut could affect only the middle class, which is typically the largest economic group. In times of economic decline and rising taxation, it is this same group that may have to pay more taxes than the wealthier upper class. Similarly, when a government decides to adjust its spending, its policy may affect only a specific group of people.

Empirical Review

From the early 1930s, there has been discussions, theories and literature that support the use of fiscal policy in advancing economic growth and development. Keynesian economics proposes for the manipulation of receipts and expenditures sides of the budget by the government if it must achieve national objectives which is ultimate to stimulate growth. According to him, one of the permanent problems of a capitalist economy is demand deficiency and as such he made maintenance of full employment by enlarging the public sector and its associated expenditure the focus of his general theory (Dwyer, 2011; Abubakar, 2016; Aspromourgos, 2018).13,14,15 In the wake of the dwindling economic activity and revenue generation, governments face the challenge of reducing unemployment. However, the possibility of achieving full employment cannot be met without the government intervening by way of increasing budget deficits and rising public debt. Hence deficit financing yields positive result in the economy (Ogiogio, 2005; Appah, 2010; Egbulonu & Amadi 2016) 16,17,3 though there are dissenting voices to this (Omitogun & Ayinla, 2007).18

While Ricardian economics opined that public debt arises from the ordinary and extraordinary expenditures of the state on mostly unproductive labourers. Their position is that any savings from the government should form part of contributors’ capital or otherwise it becomes income addition. He concluded that wasteful nature public expenditure actually gives rise to the primary burden. The burden could not have arisen from the method of financing the public expenditure meaning that whether it is from loans or taxes makes no difference (Churchman, 2001).19 Buchanan economics on the other hand is more concerned with who bears the burden of public debt against the Keynesians position that receivers of interest payments and borrowers are the same country. His argument is that the issue of government debt is centred on the real cost of government spending that sacrifices private production and that except for transfer costs, debt financing is not futuristic. The classical economists viewed capital formation as a sacrifice for government expenditure costs though its unquestionability is never in doubt. It is obvious that Buchanan’s view is applicable whether under full employment or not (Tsoulfidis, 2007; Wagner, 2013).9, 20

The studies by Gregoriou & Ghosh (2007)21, Ranjin & Sharma (2008)22, Lui, Hsu & Younis (2008)23 all agree that irrespective of the degree of variation among countries, those that budget huge expenditures often experience a higher growth level. In Obayori’s study (2016)10 looking at the impact of fiscal policy on unemployment in Nigeria, he agreed that fiscal policy is effective in reducing unemployment in Nigeria with its attendant adverse effects on inflation thereby supporting expansionary policies corroborating the studies by Egbulonu & Amadi (2016)3, Nwosa (2014)24 in the case of Nigeria and Athanasius (2013)25 in the case of Greece, Shadi (2014)26 in the case of Jordan. However, some researchers found a negative relationship between fiscal policy and unemployment (Auerbach & Gorodnichwenko, 2012; Mehmood & Sadiq, 2010),27,28 while Holden & Sparrman (2011)29 found no effect of fiscal policy on unemployment in 20 Organisation for Economic Co-operation and Development, (OECD) countries studied.

Methodology

We specify the distributed lag model, showing the effect of rising debt on the macroeconomic variable, unemployment using time series data from 1981-2019. We adopted total external debt, debt servicing, government total debt – summation of domestic and external debts, and government expenditure - that is the summation of recurrent and capital expenditure.

Sources of Data and Description

All macroeconomic and fiscal policy variables data employed in this study were extracted from various editions of National Bureau of Statistics (NBS)30 in addition to 2019 edition of Central Bank of Nigeria (CBN)31 publications. While time-series data of the total external debt, debt servicing, government total debt and government expenditure are sourced from CBN statistical bulletin, 2019, the unemployment rate was sourced from NBS annual report, 2017 and 2019.

Theoretical Framework

John Maynard Keynes theory of fiscal policy forms the theoretical underpinning of this study. According to the Keynesian theory, to spur aggregate demand, governments usually uses an appropriate policy mix involving taxation and expenditure, but however, the totality of aggregate demand is determined by the level of employment. Keynes model expresses output (Y) in an open economy, such as Nigeria’s, as a positive function of consumption (C), investment (I), government expenditure (G) and trade balance or balance of payment (X-M). This is mathematically expressed as;

Y=C+I+G+ (X-M) ………………………… (4)

Given that, C + I + G = Aggregate demand (A) which implies that a positive change in government expenditure increases aggregates demand and vice versa. We, therefore, modified equation (1) to a functional format relevant to the study, taking into consideration key macroeconomic variables, such as real gross domestic growth rate, unemployment and inflation, as the dependent variables and fiscal policy variables, such as government expenditure, government debt stock and government revenue, as the independent variables.

Model Specification and Justification

This study focuses on a macroeconomic variable, unemployment. Taking into account the rising debt profile of the country, consequently, the predictors are made to capture the components of government debt and the burden of debt servicing in Nigeria – country’s external debt outstanding, country’s summation of government debts, the amount used in servicing debts and government expenditure as a control variable. This will be used to test the following hypothesis:

The model specified for the study is as follows:

?LogUEMPt= ?0 + ?1?LogTEDOt-i + ?2?LogGTDSt-i + ?3?LogTDSt-i + ?1?LogGEXPt-i + ?4ect + ?t ……..(5)

UEMP represent unemployment rate; TEDO represents external debt outstanding; GTDS represents the summation of Government debts – by this we mean the sum of domestic and offshore debts; TDS represents total debt servicing; the summation of government expenditure is represented by GEXP – the meaning sum of capital and recurrent expenditures; while ‘ect’ and ‘?’ are error correction term and stochastic error term respectively.

Estimation and Discussion of Results

Descriptive Statistics Test Results

Table I: Descriptive Statistic

Variable

UNEMP

TEDO

GTDS

TDS

GEXP

Mean

9.582051

1205.042

4771.112

397.5644

2064.192

Median

7.200000

633.1444

2608.530

131.0500

947.6900

Maximum

23.90000

4890.270

25712.45

2454.070

9714.840

Minimum

2.300000

2.331200

13.52000

1.010000

4.100000

Std. Dev.

6.353817

1303.502

6441.305

614.3064

2555.425

Skewness

1.083865

1.335349

1.942559

2.033373

1.211891

Kurtosis

2.853768

3.866697

6.135702

6.356718

3.611431

Jarque-Bera

7.670704

12.81116

40.50600

45.18472

10.15392

Probability

0.021594

0.001652

0.000000

0.000000

0.006239

Sum

373.7000

46996.64

186073.4

15505.01

80503.48

Sum Sq.Dev.

1534.097

64566496

1.58E+09

14340148

2.48E+08

Observation

39

39

39

39

39

Source: Authors computation using e-view 9

Statistical properties of the time series variables from 1981-2019 as used in the model is as shown in table I above. The highest and lowest values of unemployment (UNEMP) were 23.9 and 7.2 respectively. The value of external debt outstanding (TEDO), Government total debt stock (GTDS), total debt servicing (TDS) and government total expenditure (GEXP) peaked at 4,890.27, 25,712.45, 2,454.07 and 9,714.84 Billion naira respectively. The standard deviation of all the independent variables are high indicating that the data points are well spread out around the mean. This is supported by the substantial value of the difference between the maximum and minimum values of the independent variables showing the existence of large variance in all the variables.

Unit Root Test Results

Table II: Unit root test

Variable

Unit root test statistic

5% Critical value

8Integration order

ADF

PP

ADF

PP

ADF

PP

TEDO

-2.453241

0.1349

-2.108993

0.4983

-1.549109

0.0021

-3.825493

0.0059

I(1)

I(1)

GTDS

4.074071

1.0000

3.830128

1.0000

-4.256957

0.0093

-4.256826

0.0002

I(1)

I(1)

TDS

6.939715

1.0000

8.913718

1.0000

-3.981472

0.0003

-4.063408

0.0003

I(1)

I(1)

GEXP

4.642623

1.0000

4.231209

1.0000

-4.237467

0.0003

-3.937429

0.0044

I(1)

I(1)

UNEMP

1.062495

0.9963

-2.108993

0.2424

-6.106581

0.0000

-10.96373

0.0000

I(1)

I(1)

Source: Authors computation using e-view 9

Unit root tests were conducted using Augmented Dickney-Fuller (ADF) and Phillip-Perron (PP) based on Akaike Information Criterion (AIC) which resulted in all the variables being stationary at I(1). The result is presented in table II above.

Result of Lag Order Selection Criteria

Table III: Lag Order Selection Criteria

Lag

LogL

LR

FPE

AIC

SC

HQ

0

-1274.013

NA

4.98e+24

71.05626

71.27620

71.13302

1

-1120.450

255.9376

4.00e+21

63.91390

65.23350

64.37447

2

-1085.898

47.98842

2.56e+21

63.38325

65.80251

64.22764

3

-1019.794

73.44943*

3.29e+20*

61.09967*

64.61860*

62.32787*

* indicates lag order selected by the criterion; LR: sequentially modified LR test statistic; FPE: Final prediction error; AIC: Akaike information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion

Source: Authors computation using e-view 9

As presented in Table III above, the Akaike information criterion (AIC) recommends optimal lag length of lag 3. Based on the outcome, we, therefore, adopted lag 3 for our estimations.

Cointegration Test Results

Table IV: Johansen Cointegration Test

Hypothesized No of
CE(s)

Trace Statistic

0.05 Critical
Value

Max-Eigen
Statistics

0.05 Critical
Value

None *

167.9177

69.81889

73.66623

33.87687

At most 1 *

94.25143

47.85613

44.04910

27.58434

At most 2 *

50.20232

29.79707

27.98175

21.13162

At most 3 *

22.22057

15.49471

21.80836

14.26460

At most 4 *

0.412211

3.841466

0.412211

3.841466

Source: Authors computation using e-view 9

Table IV above is the outcome of the cointegration test. Using 5% level of significance, the result confirms the existence of a cointegrating relationship between the variables and this corresponds to the point at which the values of the trace statistic and Max-Eigen statistic is greater than their critical values at the 5% level of significance.

Long-Run Output

Table V: Long-Run VECM Cointegrating Result With Unempdep Variable)

Variable

Coefficient

Std. error

t-Statistic

TEDO

11.19173

21.8308

0.51266

GTDS

-49.75320

44.1737

-1.12631

TDS

-4.467274

2.45823

-1.81727

GEXP

-33.67393

7.92067

-4.2514

Source: Authors computation using e-view 9

Presented in table V above is the long-run result of the estimated VECM with UNEMP as the dependent variable. The coefficient of GTDS, TDS and GEXP are all insignificant and negatively signed, indicating an inverse relationship, while the coefficient of TEDO is positive and significant. This result shows that in the long run government total debt (GTDS), total debt servicing (TDS) and government expenditure reduces unemployment (UNEMP) in the long run while total external debt outstanding (TEDO) increases unemployment. Thus, a unit positive increase in GTDS, TDS and GEXP reduces UNEMP by 49.75%, 4.47% and 33.67% respectively while a 1% increase in TEDO increases unemployment by 11.19% in the long run. This supports the findings of Fideli & Forte (2012)2 that government expenditure and deficit financing in the long run negatively impacts on unemployment.

VECM Short-Run Output

Table VI: VECM short-run dynamics; UNEMP = Dep. Var.

Variables

Coefficient

T-Statistics

Probability

LOG(TEDO(-1))

0.00000

0.00000

0.00000

LOG(GTDS(-1))

0.00000

0.00000

0.00000

LOG(TDS(-1))

0.00000

0.00000

0.00000

LOG(GEXP(-1))

-0.804688

0.25889

-3.10821

ECTt-1

-1.120212

0.45676

-2.452531

C

0.181319

0.22234

0.81552

R2 = 0.777252 ;Adj R2 = 0.495103 ;F-Statistic = 2.754765

Source: Authors computation using e-view 9

From the short-run VECM output of the model, as shown in Table VI above, error correction term (ECT) has a negative value and is less than one (1) with a significant coefficient indicating a high speed of adjustment of 112%. The value of R2 is 0.777252 indicating that about 77.73% of the changes in the level of unemployment in Nigeria within this time period is explained by these variables. The most striking observation here is that the values of TEDO, GTDS and TDS are all zero (0) meaning that in the short run all these variables do not have any impact on unemployment. However, government expenditure is -0.804688 meaning that for a 1% increase in government expenditure there is a corresponding 0.81% decrease in unemployment. The value of the F-statistic is significant at 2.75. The sign and direction of government expenditure lay credence to the findings of Egbulonu and Amadi (2016)3 that government expenditure reduces unemployment in Nigeria marginally in the short-run.

Granger Causality Test Output

Table VII: Granger Causality

Null Hypothesis

F-Statistic

Prob %

GTDS Granger Causes UNEMP

3.37389

0.0317

TDS Granger Causes UNEMP

3.78762

0.0209

GEXP Granger Causes UNEMP

8.80819

0.0003

TEDO Granger Causes GTDS

3.73367

0.0220

TEDO Granger Causes TDS

5.41342

0.0044

GTDS Granger Causes TDS

8.38891

0.0004

GTDS Granger Causes GEXP

4.53139

0.0101

GEXP Granger Causes TDS

3.81473

0.0203

TDS Granger Causes GEXP

9.00214

0.0002

Source: Authors computation using e-view 9

Granger causality test conducted on the variables employing F-statistics constructed under the null hypothesis of no causality to measure the causality direction among variables is presented in table VII above. From the output, summation of government debt outstanding granger causes unemployment in Nigeria during the period under review, this is same for debt servicing and summation of government budgetary expenditutre as they both granger causes unemployment in Nigeria. However, within the study period, outstanding external debts (TEDO) granger causes outstanding summation of government debt while TEDO and GTDS granger causes TDS. GTDS granger causes TDS and GEXP. In same vein, GEXP and TDS granger causes each other. In all these cases the probability values is less than the 5% level.

Variance Decomposition of The Model Test Output

Table VIII: Results of Decomposition of Variance for Model

Forecast Year

Relative Variance In:

Percentage of Forecast Variance Explained by innovations in

  1. LOG(UNEMP) LOG(TEDO) LOG(GTDS) LOG(TDS) LOG(GEXP)

1

2

3

4

5

6

7

8

9

10

Log(UNEMP)

0.443824

0.472545

0.506865

0.569976

0.595787

0.639121

0.662446

0.716817

0.730804

0.750594

100.0000

88.92672

77.67559

64.38691

62.28299

58.12374

54.55690

50.09132

49.81008

48.45536

0.000000

8.295604

8.741129

6.981245

10.99168

10.08872

11.79237

10.71825

10.69269

10.29061

0.000000

1.770603

10.27975

9.247697

8.492601

11.82022

12.49285

16.02663

15.98213

18.35394

0.000000

0.753514

2.742834

18.36686

17.13611

16.91140

16.25378

17.19898

17.01009

16.64741

0.000000

0.253561

0.560697

1.017286

1.096623

3.055922

4.904107

5.964811

6.505008

6.252686

1

2

3

4

5

6

7

8

9

10

Log(TEDO)

0.394633

0.623569

0.793011

0.936047

1.024433

1.062030

1.081125

1.092322

1.101182

1.102247

46.85814

43.22127

30.82601

32.17222

35.99455

37.98644

37.90055

37.26695

36.68993

36.65015

53.14186

46.95719

42.16489

38.49796

35.40027

34.29068

34.04195

33.62951

33.18868

33.12713

0.000000

3.916403

16.77627

14.73069

12.98473

12.31131

11.93031

11.73410

11.58676

11.57743

0.000000

0.032973

0.777966

1.021535

1.104674

1.080055

1.868217

3.073818

4.051197

4.139419

0.000000

5.872158

9.454860

13.57759

14.51578

14.33151

14.25897

14.29562

14.48343

14.50587

1

2

3

4

5

6

7

8

9

10

Log(GTDS)

0.254085

0.396910

0.525521

0.594346

0.625500

0.634579

0.644211

0.657312

0.671080

0.681295

36.58567

26.25250

16.53437

17.30547

17.92606

18.31663

17.80747

17.29755

17.17263

17.27179

39.85867

38.08912

32.08961

31.29378

29.85710

29.62840

29.12780

28.10182

27.03276

26.22910

23.55567

31.03740

40.76707

38.08062

37.81575

37.73042

38.30408

39.08336

40.05253

41.11858

0.000000

0.087489

2.548324

1.994778

1.827646

1.831748

2.515444

3.695055

4.248386

4.218447

0.000000

4.533495

8.060627

11.32534

12.57344

12.49281

12.24521

11.82222

11.49370

11.16209

1

2

3

4

5

6

7

8

9

10

Log(TDS)

0.330652

0.432342

0.504969

0.608784

0.660161

0.696788

0.709793

0.724328

0.738418

0.749082

24.17763

16.26000

13.09935

9.119723

9.740529

8.838857

9.189594

8.890317

8.894177

9.077099

3.393065

16.78485

15.46186

13.09170

13.71944

12.59145

12.84637

12.52340

12.05257

11.71408

0.250998

23.00296

36.48913

49.77635

51.15473

54.77920

55.01083

55.90266

56.97115

57.64062

72.17830

43.49975

33.40678

25.77601

22.54268

21.13182

20.38342

19.99751

19.49712

18.99723

0.000000

0.452441

1.542889

2.236215

2.842613

2.658667

2.569787

2.686120

2.584979

2.570974

1

2

3

4

5

6

7

8

9

10

Log(GEXP)

0.306539

0.347297

0.406586

0.470685

0.537653

0.572689

0.616156

0.648294

0.689351

0.715952

1.079955

0.861544

7.094500

5.673547

5.778121

5.897803

5.130890

4.725483

4.510697

5.218909

24.76122

20.90294

16.89057

16.05022

16.52838

16.72711

17.01475

17.06098

17.47937

18.27445

7.088294

10.82610

17.60272

22.60328

29.38058

31.66144

36.91554

40.17424

43.52570

43.60087

3.053940

3.312423

9.465819

14.23468

13.57913

12.53917

10.98619

9.962376

8.817983

8.190642

64.01659

64.09700

48.94639

41.43827

34.73378

33.17447

29.95263

28.07692

25.66625

24.71512

Source: Authors computation using e-view 9

From the variance decomposition output in table VIII above, the variable unemployment, in forecast year 1 accounted for 100%. During the same forecasting period, shocks to total external debt servicing outstanding (TEDO) accounted for 0% of the variations in unemployment (UNEMP). Similar explanations hold for the variations in the total debt outstanding (TEDO) in the other forecast periods. The same applies for the other variables. Also while some variables like GTDS on TDS were increasing, UNEMP on TDS was decreasing. This is in line with what Ncanywa & Masoga (2018)6 who found that debt servicing imposes liquidity constraint, hence large payments of debt service deprives a country of needed funds thus becoming the opportunity cost by inducing low economic growth.

Conclusion and Recommendations

In investigating whether increased borrowing will assist in ameliorating the macroeconomic challenge of increasing unemployment in Nigeria in order to test the impact of fiscal policy used by the government in trying to stem the ever-rising unemployment rate in Nigeria, in an attempt to decipher the causes of the ever-increasing unemployment and lack of provision of infrastructure in Nigeria that has become the government’s justification for the accumulation of huge debts. The integration, VECM, Granger causality and variance decomposition functions have been employed in analysing time series data sourced from the National Bureau of Statistics (NBS)30 and the Central Bank of Nigeria (CBN)31 for the period from 1981 to 2019. A high value of ECM was confirmed at 112%. While GEXP and TDS granger causes each other, it is evident from the resulting output that GTDS, TDS and GEXP all granger causes UNEMP (Unemployment). The overall result is indicative that public debt has not in any way helped in reducing unemployment in Nigeria. In trying to solve the problem of unemployment using public debt, job creation, stronger growth of the economy and transparency should be the guiding principles in managing borrowed funds. Nigeria has been naturally endowed with both human and material resources, it should however vigorously pursue the diversification of the economy so as to explore other avenues of revenue generation rather than depending largely on borrowing. A situation where servicing of borrowed funds takes a greater percentage of the country’s revenue is not healthy enough especially in the face of the ever-increasing unemployment rate in Nigeria. While we do not totally toe the line of discouraging the government from borrowing for the provision of critical infrastructures, corruption should be put in check so as to allow the amount of borrowing is reflected by the availability of infrastructures having in mind the negative implications of huge borrowing on the economy. Borrowing for consumption should be discouraged at all cost. Thus, further studies should be on the effects of corruption on massive borrowing in Nigeria.

Acknowledgement

I/We acknowledge all the authors whose works were sighted here.

Conflict of Interest

I/We declare that I/We do not have any form of conflicting interest whatsoever.

Funding Sources

There was no form of financial assistance from any group, body or organization.

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