Selected Economic Policies on the Growth of Small and Medium Enterprises in Nigeria ()

Francis Sylvanus Udoh^{1}, Victor E. Inim^{2}, James Agama Emiesefia^{1}, Murat Akyuz^{1}

^{1}Department of Business Administration, Nile University of Nigeria, Abuja, Nigeria.

^{2}Department of Accounting, Nile University of Nigeria, Abuja, Nigeria.

**DOI: **10.4236/ojbm.2023.115108
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In Nigeria, economic policy should set the parameters in the economic system of the country, which should constitute the key part of the economic practice thereby creating an environment affecting the development and functioning of either collective or individual Small and Medium Enterprises (SMEs) operators and thus logically affecting the sector(s) of the economy. This work examines the effect of selected economic policies on the growth of SMEs in Nigeria. Notwithstanding the attention placed on monetary, fiscal and trade policies, in the overseeing of the economy, the SMEs sector all encompassing, Nigerian economy particularly SMEs are up until the present time of this study not growing as expected. The time frame was from 1986 to 2017, a thirty-two-year study. Research design employed was ex-post facto and a population of seventy-two thousand eight hundred and thirty-eight (72,838) SMEs in Nigeria were used. The sample size was the entire 72,838 SMEs of which the study relied on reports from Central Bank Statistical Bulletin and SMEDAN, thereby employing the Error Correction Mechanism (ECM) tool of analysis to analyze the time series data. The study found that economic policy (proxies: monetary policy, fiscal policy and trade policy) had no positive significant effect on the growth of SMEs in Nigeria. Therefore, the study recommends that economic policy should be design and formulated in such a way that the goals the SMEs want to achieve through monetary, fiscal and trade policies should be realistic and feasible in terms of growth.

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Udoh, F. , Inim, V. , Emiesefia, J. and Akyuz, M. (2023) Selected Economic Policies on the Growth of Small and Medium Enterprises in Nigeria. *Open Journal of Business and Management*, **11**, 1948-1970. doi: 10.4236/ojbm.2023.115108.

1. Introduction

All over the world, the field of economic policy has received increasing attention from both academics and non-academics practitioners. The literature on economic policy is broad and some researchers have made attempts to theorize on it e.g. Jack and Douglas (1990) . Every economic policy has both macroeconomic and non-economic components. The macroeconomic component is the total effect that a policy would have on economic growth, unemployment, and inflation, both in the short run and long run. The noneconomic component includes all other effects such as culture, religion and family. These two components then give rise to two types of policy decisions: 1) explicit economic policy and 2) derivative economic policy.

On the one hand, an explicit economic policy is one that is proposed to solve a specific macroeconomic problem. The economic component of the policy provides the impetus for action. Explicit economic policies include fiscal policy, monetary policy, wage and price controls, investment tax credits, countercyclical public works, or a revision of the tax code to stimulate work, savings, or investment (Douglas, 1990) . On the other, a derivative economic policy is a policy that someone proposes to ameliorate some other condition; although it also has macroeconomic effects. Derivative economic policies include all expenditure programmes, all attempts to modify the tax code to achieve noneconomic goals, and all regulatory or incentive programmes that unintentionally alter the way individuals work or save or the way firms invest (Douglas, 1990) .

Historically, on 1st October 1960, Nigeria gained her independence. During this period, the most influential economic sector was agriculture. Its contribution to Gross Domestic Product (GDP) was about 70% and the knock-on effect showed a similar percentage rise in employment of the working population, as well as about 90% of foreign earnings in revenue for the Federal Government. Early post-Independence period (1960s to mid-1970s) saw a rapid growth of industrial capacity and output as the contribution of the manufacturing sector to GDP rose from 4.8% to 8.2% (Nwajiuba, 2012) .

In general, Nigeria experienced economic and political issues during the 1980s as a result of an ongoing totalitarian military regime. Foreign currency was scarce, and the continual increase in the exchange rate also reduced agricultural output, which remained below levels attained in the early 1970s. Due to this, annual GDP growth abruptly slowed and became negative in 1981 (Hinchliffe, 2002) . The Shagari Government introduced severe budget cuts and steps to strengthen the external situation in April 1982 as a result of the economy’s dramatic deterioration. The business landscape from 1981 to 1982 was severely impacted by SAP’s austerity measures.

As the pain of a Structural Adjustment Program (SAP), which was put in place in 1986 into the Nigerian policy intensified, and with no proof of a turnaround of the economic recession, the nation embraced a policy of guided deregulation in the mid-1990s. Under SAP, efforts were made to check the length of liberalization. As a result, a dual exchange rate emerged: an official rate, which the government used for essential transactions; and a second rate, which served as the inter-market exchange rate (CBN, 1993) .

The intervention in the market operations by the military rulers’ in Nigeria largely dictated the economic policy that was guided by deregulation primarily to service their cronies. Although, the coming back of democracy in 1999 ushered in a new chance for economic liberation, which empowered some economic debates on and design for growth albeit poverty easing. By 2003, the macroeconomic policy apparatus had emphasized a path way of prominence of the economic restrictions and sincere obligation to personal enterprise-led development. The economic development policy was packaged as “National Economic Empowerment and Development Strategy” (NEEDS), (NPC, 2004) .

The experiences of both the 1980s and 2015 economic recessions in Nigeria, as well as the 2007/2008 global economic meltdowns, forced a rethink about the effectiveness of economic policies, especially regarding the reduction of uncertainty and risks faced by the SMEs sectors. In my own perspective, it was observed that reasonable economic policy should start out with realistic and feasible objectives such as stable and realistic exchange rate, interest rate, tariff and taxes. There are no examples of bad judgments of an existing situation resulting in successful economic policy.

Accordingly, both broad and narrow economic conditions such as low per capita income, high inflation rates, poor industrial production, sharply fallen currency value, poor innovations, research and development and weak macroeconomic variables, have worked to create instability within the growth of SMEs in Nigeria. As a result, the growth of SMEs has been met with important problems such as the collapse of SMEs within five to six years of operations and poor innovations. To combat the effects of this and other related problems, the Nigerian government has had to adopt a much-revised monetary, fiscal and trade economic policies.

Over recent decades, Nigerian governments had spent large amount of resources in economic policies to support SMEs. The expanded use of these policies may give grounds resting on notable challenges that SMEs face, which has hindered their growth. Nonetheless, small amount is recognized about the efficacy of these policies, and a mindful look at the assemble, mechanisms and inducements supplied by these policies put forward caution in their application, execution and, most importantly, the need to carefully and closely supervise the results. Based on this, it was observed that the principal problem for growth of SMEs is that the economic policy from past governments and current government are not properly tailored to SMEs, which in turn affect the quality of SMEs products in Nigeria and this makes SMEs finished goods unfit to be able to compete with other goods locally and foreign wise.

The main purpose of this study was to examine the effect of economic policies on the growth of SMEs in Nigeria. Other specific objectives are to: evaluate the effect of monetary policy on the growth of SMEs in Nigeria; examine the effect of fiscal policy on the growth of SMEs in Nigeria and determine the effect of trade policy on the growth of SMEs in Nigeria.

The hypotheses of the study are stated in null forms and tested from the objectives of the study:

H_{01}: Monetary Policy (interest rate, exchange rate and inflation) has no significant effect on the growth of SMEs in Nigeria.

H_{02}: Fiscal Policy (government expenditure and taxes) has no significant effect on the growth of SMEs in Nigeria.

H_{03}: Trade Policy (degree of openness and tariff) has no significant effect on the growth of SMEs in Nigeria.

Previous studies such as Adenikinju & Olofin (2000) found a negative effect on economic policy and growth in the manufacturing sector of the 17 African countries studied. Also, Halim et al. (2017) who studied SMEs in Malaysia on economic growth, utilizing multiple regression analysis, found positive relationship between both variables. Finally, Bekeris (2012) examined impact of macroeconomic indicators upon SME’s Profitability and using various measures found a statistical relationship between the variables. However, none of these studies focused on a combined effect of monetary policy, fiscal policy and trade policy to study economic policy and SMEs in Nigeria. With this, it fills the gulf by evaluating the effect of selected economic policies on the growth of SMEs in Nigeria.

2. Literature Review

2.1. Concept of Economic Policy

Economic policy often times are put together to identify, analyzed and then solve issues, which comes in conflict separating the economy and its objectives over a specific period of time. This of course abstracts from the aberration of self-interest motivated economic policies. Adedipe (2004) states that the preparation of an economic policy entails the collection, arrangement, analysis, summary and interpretation of economic data. The quality of data input into policy formulation then becomes critical to evolving policies that will impact the macro-economy in the most desired sectors for maximum benefit to the economy—whether National, State or Local Government, under the federal structure Nigeria operates (Adedipe, 2004) .

Economic policy differs significantly depending on whether the government is considering explicit economic policy or derivative economic policy (Douglas, 1990) . For derivative economic policy, legislators pay greater attention to the noneconomic components, which tend to be relatively large, than to the economic components, which are usually much smaller. For explicit economic policy, the emphasis is reversed. Legislators focus more on the economic components and give proportionally less attention to the noneconomic components. In both cases legislators’ calculations reflect the way in which the issues might enter citizens’ assessments in future business (Douglas, 1990) .

2.2. Concept of Small and Medium Enterprises

In the world all over, countries do not use the same definition to classify their SMEs sector, nor does a universal definition appear to be put in place. Nonetheless, there are three specifications that are overall put in place by so many nations, either combining them or single and they are: number of workers employed; capital investment on plant and machinery and volume of production or turnover of business. In U.S.A, a business that is little might be a bigger one in a nation like Nigeria. Moreover, the definition of SME also varies overtime from agencies or developing institutions to another, depending on their policy focus (Julius, Agbolade, & Johnson, 2016) .

Small and Medium Scale Enterprises (SMEs) is seen from two perspectives; qualitative and quantitative variables. These two criteria include: relative size within the industry, capital employed, market share, number of employees, turnover, available finance, and profit. Quantitative definitions mainly express the size of enterprises, mainly in monetary terms such as turnover, asset value, profit, as well as quantitative index like number of employees (Etuk, Etuk, & Baghebo, 2014) .

2.3. Empirical Review

Adenikinju and Olofin (2000) utilizing panel data for 17 African countries over the period 1976 to 1993, looked at the role of economic policy on the growth performance of the manufacturing sectors. Their proxies were external competitiveness of the economy, foreign direct investment and macroeconomic balance against manufacturing performance. Findings showed non-significant of both variables.

Halim, Malim, Derasit, Rani, & Rashid (2017) studies Small and Medium Enterprises (SMEs) in Malaysia on economic growth. Employing multiple regression to analyze the data, the research findings emphasized that the exchange rate had a small positive impact on SMEs growth rate (10.81%), while the interest rate had a positive impact of (60.74%). The inflation rate also negatively impacted SMEs at (−53.89%). They concluded that interest rate and exchange rate had a positive significant impact on the profitability of Malaysia SMEs.

Bekeris (2012) examines impact of macroeconomic indicators upon SME’s Profitability in Lithuania. The study used unemployment, average salary, population and firms’ number in a country, FDI, taxes paid, GDP, inflation, exports and imports, etc. There was a correlation between macro factors and corporate profitability. The chosen macroeconomic proxies (the number of enterprises, average wages, inflation and the monetary base) were negatively and statistically significant.

2.4. Theoretical Framework

Cause and Effect Theory

The theoretical base found adequate for this work is the cause and effect theory. The theory explains that, no occurrence takes place by chance but happens as a result of a cause. By implementing this to the study, it can be described that SMEs growth and performance is cause by economic policies. The firmness of the policies in a long run guarantees efficient growth of the sector while constant fluctuation of these policies could either make or mar the growth of the sector. According to Anghelache et al. (2016) , cause and effect links between macroeconomics variables and growth provide useful information for policy makers in the government and private agencies on the systematic relationship that reveals the influences of certain factors on growth. When these variables are not stable, it therefore becomes the function of the government to make certain that macroeconomics policies are carried through to manage and control these variables so as to spur growth in all sectors of the economy. The backbone of a nation’s development is her SMEs. With this, for macroeconomic variables to be stable, the nation has to strengthen or support the advantages gained from this sub-sector. This theory was also employed by Kebede and Simesh (2015) .

3. Methodology

The research design adopted for this study was the ex-post facto research design. According to Kerlinger and Howard (2013) , ex-post facto research design describes the statistical association between dependent and independent variables with a view to establishing a causal link between them. The population of this study comprised of all the registered SMEs in Nigeria, which according to SMEDAN and National Bureau of Statistics (NBS) (2017) is seventy-two thousand eight hundred and thirty-eight (72,838) as at 2018. Evaluating the cause-effect relationships is the significant point of this study; hence, the data are time series, gotten from CBN statistical bulletins and NBS, covering the period 1986-2017. The annualized secondary data was analysed using the Autoregressive Distributed lag (ARDL) and Error Correction Mechanism (ECM), as well as employing the co-integration method to test for the long-run effect among the series. In other words, the underlining postulation is that all variables are integrated of order 1 or I (1).

Unit Root Test

In this study, unit root tests (pre-estimation diagnostics tests) were conducted to ascertain the stationarity of the data before carrying out the Autoregressive Distributed Lag (ARDL) cointegration test. The unit root tests are valid if the time series *y _{t}* is well characterized by an AR (1) with white noise errors. Many financial time series, however, have a more complicated dynamic structure than is captured by a simple AR (1) model. Said and Dickey (1984) augment the basic autoregressive unit root test to accommodate general ARMA (p, q) models with unknown orders and their test is referred to as the augmented Dickey-Fuller (ADF) test. The ADF test tests the null hypothesis that a time series

${y}_{t}={\beta}^{\prime}{D}_{t}+\varphi {y}_{t-1}{\displaystyle \underset{j-1}{\overset{p}{\sum}}{\psi}_{j}\Delta {y}_{t-j}+{e}_{t}}$ (1)

where *D _{t}* is a vector of deterministic terms (constant, trend etc.). The

Model Specification

According to Reem (2009) , his policy is based on the theories of British economist John Magnard Keynes whose theory basically states that governments can influence macroeconomic productivity levels by increasing or decreasing tax levels and public spending. To establish the relationship between economic policy and growth of SMEs, the researcher adopted a growth model, which is in line with that applied by Adeoye (2006) , with slight modification to suit the adaptations to this study.

The mathematical specification of the implicit model that expresses the relationship between economic policy and growth of SMEs is expressed as:

$gsmep=f\left(mp\right)$ (2)

$gsmep=f\left(fp\right)$ (3)

$gsmep=f\left(tp\right)$ (4)

Factoring in the proxies of MP, FP and TP into the implicit functions of Equations (2) to (4), we have:

$gsmep=f\left(exr,intr,inf\right)$ (5)

$gsmep=f\left(taxes,govex\right)$ (6)

$gsmep=f\left(tarri,dto\right)$ (7)

Setting up Equations (5), (6) and (7) in a linear stochastic form (or econometric form) is expressed as:

$gsmep={\alpha}_{0}+{\alpha}_{1}exr+{\alpha}_{2}intr+{\alpha}_{3}inf+{\mu}_{t}$ (8)

$gsmep={\beta}_{0}+{\beta}_{1}taxes+{\beta}_{2}govex+{\upsilon}_{t}$ (9)

$gsmep={\phi}_{0}+{\phi}_{1}tarri+{\phi}_{2}dto+{\nu}_{t}$ (10)

The introduction of natural logs to Equations (8) (9) and (10) would be more efficient in estimating the parameters because:

1) It helps convert and integrate different values (of a variable) into a common denominator.

2) It brings different units to a common base for measurement.

3) Logarithm ensures that the coefficients of the variables are effective in analysing macro-economic behaviour, since the coefficients are elasticises used to explain the response of a change in one variable with respect to another. On the strength of these, taking the natural logs of both sides of Equations (8) (9) and (10) will result in the following Equations (11), (12) and (13):

$\mathrm{log}\left(gsmep\right)={\alpha}_{0}+{\alpha}_{1}\mathrm{log}\left(exr\right)+{\alpha}_{2}\mathrm{log}\left(intr\right)+{\alpha}_{3}\mathrm{log}\left(inf\right)+{\mu}_{t}$ (11)

$\mathrm{log}\left(gsmep\right)={\beta}_{0}+{\beta}_{1}\mathrm{log}\left(taxes\right)+{\beta}_{2}\mathrm{log}\left(govex\right)+{\upsilon}_{t}$ (12)

$\mathrm{log}\left(gsmep\right)={\phi}_{0}+{\phi}_{1}\mathrm{log}\left(tarri\right)+{\phi}_{2}\mathrm{log}\left(dto\right)+{\nu}_{t}$ (13)

where;

log = Natural Logarithms

*gsmep* = Growth of Small and Medium Enterprises (proxy for SMEs Productivity)

*exr* = Exchange Rate

*intr* = Interest Rate

*inf* = Inflation

*taxes* = Taxes

*govex* = Government Expenditure

*tarri* = Tariff

*dto* = Degree of Trade Openness

α_{0} = Intercept or autonomous parameter estimates for monetary policy

α_{0} − α_{3} = Coefficient of monetary policies (exchange rates, interest rates and inflation)

β_{0} = Intercept or autonomous parameter estimates for fiscal policy

β_{1} − β_{2} = Coefficient of fiscal policies (tax and government expenditure)

*φ*_{0} = Intercept or autonomous parameter estimates for trade policy

*φ*_{1} − *φ*_{2} = Coefficient of trade policies (tariff and degree of trade of openness)

μ* _{t}*, υ

Building Equations (11), (12) and (13) into an ARDL model, we have:

$\begin{array}{l}\Delta \mathrm{log}\left(gsmep\right)\\ ={\alpha}_{0}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\alpha}_{1}^{i}}\mathrm{log}{\left(gsmep\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\alpha}_{2}^{i}}\mathrm{log}{\left(exr\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\alpha}_{3}^{i}}\mathrm{log}{\left(intr\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\alpha}_{4}^{i}}\mathrm{log}{\left(inf\right)}_{t-i}+{\alpha}_{5}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\alpha}_{6}\Delta \mathrm{log}{\left(exr\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\alpha}_{7}\Delta \mathrm{log}\left(intr\right)+{\alpha}_{8}\Delta \mathrm{log}{\left(inf\right)}_{t-i}+{\mu}_{t}\end{array}$ (14)

$\begin{array}{l}\Delta \mathrm{log}\left(gsmep\right)\\ ={\beta}_{0}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\beta}_{1}^{i}}\mathrm{log}{\left(gsmep\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\beta}_{2}^{i}}\mathrm{log}{\left(taxes\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\beta}_{3}^{i}}\mathrm{log}{\left(govex\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\beta}_{4}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\beta}_{5}\Delta \mathrm{log}{\left(taxes\right)}_{t-i}+{\beta}_{6}\Delta \mathrm{log}\left(govex\right)+{\upsilon}_{t}\end{array}$ (15)

$\begin{array}{l}\Delta \mathrm{log}\left(gsmep\right)\\ ={\phi}_{0}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\phi}_{1}^{i}}\mathrm{log}{\left(gsmep\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\phi}_{2}^{i}}\mathrm{log}{\left(tarri\right)}_{t-i}+{\displaystyle \underset{i=1}{\overset{m}{\sum}}{\phi}_{3}^{i}}\mathrm{log}{\left(dto\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\phi}_{4}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\phi}_{5}\Delta \mathrm{log}{\left(tarri\right)}_{t-i}+{\phi}_{6}\Delta \mathrm{log}\left(dto\right)+{\upsilon}_{t}\end{array}$ (16)

Once a long-run association is established between the variables in Equations (14), (15) and (16) the research therefore moves forward to determine the long and short-run dynamics using unrestricted Error Correction Mechanism (ECM) approach.

$\begin{array}{c}\Delta \mathrm{log}\left(gsmep\right)={\alpha}_{0}+{\alpha}_{1}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\alpha}_{2}\Delta \mathrm{log}{\left(exr\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\alpha}_{3}\Delta \mathrm{log}\left(intr\right)+{\alpha}_{4}\Delta \mathrm{log}{\left(inf\right)}_{t-i}+\delta EC{T}_{-1}+{\mu}_{t}\end{array}$ (17)

$\begin{array}{c}\Delta \mathrm{log}\left(gsmep\right)={\beta}_{0}+{\beta}_{1}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\beta}_{2}\Delta \mathrm{log}{\left(taxes\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\beta}_{3}\Delta \mathrm{log}\left(govex\right)+\lambda EC{T}_{-1}+{\upsilon}_{t}\end{array}$ (18)

$\begin{array}{c}\Delta \mathrm{log}\left(gsmep\right)={\phi}_{0}+{\phi}_{2}\Delta \mathrm{log}{\left(gsmep\right)}_{t-i}+{\phi}_{2}\Delta \mathrm{log}{\left(tarri\right)}_{t-i}\\ \text{\hspace{0.17em}}\text{\hspace{0.05em}}+{\phi}_{3}\Delta \mathrm{log}\left(dto\right)+\xi EC{T}_{-1}+{\upsilon}_{t}\end{array}$ (19)

The $EC{T}_{t-1}$ further captures the output evolution process by which agents adjust for prediction errors made in the last period. Hendry’s (2005) general-to-specific modelling approach is adopted to derive a satisfactory parsimonious model for the economic policy and the growth of SMEs Equations (17), (18) and (19) which are data admissible, theory consistent and interpretable.

4. Data Analysis and Result

4.1. Descriptive Statistics

For us to have a view of the data used in this work, a quick look at the data employing descriptive statistics was carried out. This helps to emphasize the essence of the data for the variable and gives the average of the entire variables. With this outlook, a better perception of the arrangements concerning the data used was analysed. Herewith the summary is given in Table 1.

Giving the descriptive results in Table 1, the analysis of the means (M) and standard deviations (SD) emphasizes the following descriptive statistics GSMEP (*M* = 2249354, *SD* = 3146131); GOVEX (*M* = 1973.702, *SD* = 2184.382); EXR (*M* = 95.60707, *SD* = 79.07182); INF (*M* = 20.53268, *SD* = 19.14964), INTR (*M* = 18.78911, *SD* = 3.777349); TARRI (*M* = 197.1673, *SD* = 190.4593); TAXES (*M* = 1739.064, *SD* = 1998.436); TO (*M* = 0.332436, *SD* = 0.110999). The analysis indicates all the variables have their mean values been higher than their standard deviations with the exception of TARRI.* *

Skewness, which measures the shape of the distribution, shows that only TO have its value to be negative, which suggests the distribution tailed to the left of the mean. However, the skewness of the other seven variables has its values to be positive suggesting the distribution tails to the right of its means.

Proxies that have worth of kurtosis less than 3 are called platykurtic (fat or short-tailed), GSMEP, EXR, TARRI, TAXES and TO proxies passed for this as at

Table 1. Selected variables of descriptive statistics.

Source: Authors computation, 2022 (Eviews-10).

the time of this work. Also, a look at the proxies whose kurtosis worth is greater than 3 are known as leptokurtic (slim or long tailed) GOVEX, INF and INTR variables qualified for this during the study period.

The Jarque-Bera statistical test shows that it is normally distributed so as to be consistent with skewness test. The Jarque-Bera statistics here accepts the null hypothesis EXR, TARRI, TAXES and TO since their probability values are greater than 0.05. However, GOVEX, INF and INTR has no normal distribution as its probability value was found to be higher than 0.05. In summary, we can conclude that most of the variables are normally distributed during the period under study.

4.2. Unit Root Test Results

A stochastic pattern that can be removed by differentiation typically describes time series data. Therefore, the unit root is a test of whether the data used in this description are stationary or non-stationary. This aims to determine whether there is a fictitious or absurd correlation between economic policies and the expansion of SMEs in Nigeria. Thus, the study applied Augmented Dickey-Fuller (ADF) approaches to evaluate and verify the series unit root property and model stability.

From Table 2, it could be observed that only two variables GSMEP and INTR were found to be stationary at levels, that is, they are integrated at order zero {I (0)}. However, GOVEX, EXR, INF TARRI, TAXES and TO were all found to be stationary at first difference; that is integrated at order one. At this order of integration, their ADF test statistics, −5.194533, −3.645969, −6.975648 and −7.538953 were greater than the critical test statistics of (−4.309824 at 1%),

Table 2. Summary of unit root test results.

Note: MacKinnon critical values for the rejection of hypothesis of unit root are in parenthesis in Columns 1 and 2 and the tests include intercept with trend; * significant at 1%; ** significant at 5%; *** significant at 10; Mackinnon critical. Source: Authors Computation, 2022 (Eviews-10).

(−3.574244 at 10%), (−4.309824 at 1%) and (−4.309824 at 1%) significant level respectively. Since all the variables were found to be stationary at different orders, it was safe for the study to employed ARDL bound test approach to validate or test for the presence of co-integration.

4.3. Results of Co-Integration Test Results

4.3.1. Optimal Lag Length Test

The pick of optimal lag length is necessary so as to verify if enough lags is included in the ARDL. This can be seen in Table 3 where all the selection criteria (FPE, AIC, HQIC and SBIC) selected four (4) lags.

4.3.2. Co-Integration Test Results

To avoid a spurious regression, a pre-test has to be conducted. Tables 4-6 present the results of the co-integration test for Monetary policy model, Fiscal Policy model and Trade Policy model using the ARDL bound test approach to co-integration.

The result revealed that there is an existence of co-integration among the variables. The F-statistics values at 3.849232 (for monetary policy model), 5.260900 (fiscal policy model) and 4.351319 (trade policy model) are greater than the lower and upper bound values put at 5 percent level of significance. Hence, there is a sufficient proof of the existence of a long-run equilibrium relationship between monetary policy, fiscal policy, trade policy and the growth of SMEs in Nigeria 1986 to 2017. The result thus shows that macro-economic policy has long run effect on the growth of SMEs in Nigeria within the period under study.

Table 3. Lag order range criteria.

Note: * indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level). FPE: Final prediction error; AIC: Akaike information criterion. SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion. Source: Authors Computation, 2022 (Eviews-10).

Table 4. Results of ARDL-co-integration test on monetary policy and growth of SMEs.

Notes: ** significant at 5%. Source: Authors computation, 2022 (Eviews-10).

Table 5. Results of ARDL-co-integration test on fiscal policy and growth of SMEs.

Notes: ** significant at 5%. Source: Authors computation, 2022 (Eviews-10).

Table 6. Results of ARDL-co-integration test on trade policy and growth of SMEs.

Notes: ** significant at 5%. Source: Authors computation, 2022 (Eviews-10).

4.4. Statistical Test of Hypotheses

Hypothesis One (H_{01}): Monetary Policy (interest rate, exchange rate and inflation) has no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria.

The Wald-test in Table 7 indicated that the calculated F-value for the relationship between Monetary Policy and Growth of Small and Medium Enterprises (SMEs) in Nigeria is 1.793 and its *p*-value is 0.1745. Because the *p*-value is greater than 0.05% level of significance, it therefore falls in the acceptance region and thence, the 1st null hypothesis (H_{01}) was accepted. The outcome hence emphasizes that monetary policy (interest rate, exchange rate and inflation) has non-significant effect on the growth of SMEs in Nigeria from 1986 to 2017.

Hypothesis Two (H_{02}): Fiscal Policy (government expenditure and taxes) has no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria.

The Wald-test in Table 8, indicated that the calculated F-value for the relationship between fiscal policy and Growth of SMEs in Nigeria was revealed to be 2.04 and its *p*-value is 0.1226. For the fact that the *p*-value is greater than 5% level of significance (falling in the acceptance region) and with that, we accept the second null hypothesis (H_{02}) and say that fiscal policy (government expenditure and taxes) has no significant effect on the growth of SMEs in Nigeria between 1986 and 2017.

Hypothesis Three (H_{03}): Trade policy (tariff and degree of trade openness) has no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria.

Table 9 of the Wald-test, emphasize that the F-value for the relationship between Trade policy (tariff and degree of trade openness) and the growth of SMEs in Nigeria was seen to be 2.45 and its *p*-value is 0.0812. Since the *p*-value is greater than 0.05% level of significance (falling in the acceptance region); with

Table 7. Results of wald test on monetary policy and growth of Small and Medium Enterprises (SMEs) in Nigeria.

Source: Authors computation, 2022 (Eviews-10).

Table 8. Results of wald test on fiscal policy and growth of SMEs in Nigeria.

Source: Authors computation, 2022 (Eviews-10).

Table 9. Results of wald test for trade policy and growth of SMEs in Nigeria.

Source: Authors Computation, 2022 (Eviews-10).

that, the third null hypothesis is accepted (H_{03}), concluding that Trade policy (tariff and degree of trade openness) has a non-significant effect on the growth of SMEs in Nigeria between 1986 and 2017.

4.5. Stability Analysis of Macro-Economic Policy and Growth of SMEs in Nigeria

Different post estimation diagnostic tests were carried out to know the suitability and stability of the model as well as the robustness of the results. Accordingly, for reliability of estimates, the researchers acquired chains of residual and stability tests of a kind like heteroscedasticity test, serial correlation Lagragian Multiplier test (for higher order autocorrelation), and the normality test. Both the F-statistic and product of observation with the square coefficient of correlation (NR2) were obtained.

Monetary Policy result in Table 10 showed absence of indications of heteroscedasticity and serial correlation in the approximated ARDL-ECM mechanism were found to be greater than 0.05 or 5% as the *p*-values of both are (0.4092 and 0.8940). Also, the normal distribution, which used Jarque-bera test showed a normal distribution with a bell shaped symmetrical distribution at 5% significance level. The Jarque-bera probability holds its value at 0.685059 found to be greater than 0.05. Finally, the cumulative sum (CUSUM) stability tests (CUSUM and CUSUMSQ) in Figure 1 and Figure 2 revealed that the model is stable and the regression equation is correctly specified as the plots of the charts lie within the critical bounds at 5 percent significant level.

For the Residual Test of Fiscal Policy result presented in Table 11, it could be observed that there were no evidences of serial correlation and heteroskedasticity in the estimated ARDL-ECM model as the *p*-values of both (0.1441 and 0.1426) were found to be greater than 0.05 or 5 percent. In addition, Jarque-bera test for normal distribution revealed that the result attained a normal distribution with a bell-shaped symmetrical distribution at 5 percent significance level; while the cumulative sum (CUSUM) stability tests (CUSUM and CUSUMSQ) in Figure 3 and Figure 4 revealed that the model is stable and the regression equation is correctly specified as the plots of the charts lie within the critical bounds at 5 percent significant level.

Finally, the results of the post diagnostic test for the Trade Policy model, which are shown in Table 12, demonstrated that there is no evidence of serial correlation or heteroskedasticity in the estimated ARDL-ECM model, as both *p*-values (0.8610 and 0.6676) were determined to be greater than 0.05 or 5%. The

Figure 1. CUSUM stability tests of monetary policy and growth of Small and Medium Enterprises (SMEs) in Nigeria. Source: Authors Computation, 2022 (Eviews-10).

Figure 2. CUSUM square stability tests of monetary policy and growth of SMEs in Nigeria. Source: Authors computation, 2022 (Eviews-10).

Table 10. Results of residual test of monetary policy and growth of SMEs in Nigeria.

Source: Authors computation, 2022 (Eviews-10).

Figure 3. CUSUM stability tests of fiscal policy and growth of Small and Medium Enterprises (SMEs) in Nigeria. Source: Authors computation, 2022 (Eviews-10).

Figure 4. CUSUM Square stability tests of fiscal policy and growth of Small and Medium Enterprises (SMEs) in Nigeria. Source: Authors Computation, 2022 (Eviews-10).

Table 11. Results of residual test of fiscal policy and growth of SMEs in Nigeria.

Source: Authors computation, 2022 (Eviews-10).

Table 12. Results of residual test of trade policy and growth of SMEs in Nigeria.

Source: Authors computation, 2022 (Eviews-10).

probability value of 0.838075, which was determined to be greater than 0.05, indicated that the result satisfied the criteria for a normal distribution with a bell-shaped symmetrical distribution at the 5% level of significance.

And finally, the cumulative sum (CUSUM) stability tests (CUSUM and CUSUMSQ) in Figure 5 and Figure 6 revealed that the model is stable and the regression equation is correctly specified as the plots of the charts lie within the critical bounds at 5 percent significant level.

5. Data Analysis and Results

5.1. Monetary Policy and Growth of SMEs (ARDL-ECM Results)* *

The ARDL-ECM result evaluates how the final equation changes to the long-run equilibrium. Hendry’s (1987) methodology of “general-to-specific was employed to eliminate all insignificant lags. Accordingly, this led to an initial estimation of an ECM with three lagged differences of the explanatory variables, a constant term and error correction term lagged one (ECT_{t−1}) The dimensions of the parameter space were then reduced to a parsimonious ARDL-ECM specification by using omitted and redundant variable test to exclude the statistically insignificant lags. The results of the reduced short-run dynamic policy model are presented in Tables 13-15 for monetary policy model, Fiscal Policy model and Trade Policy model.

As expected, the lagged error correction term ECT (−1) is negative, less than unity and statistically significant at 5 percent. The coefficient revealed that once there is disequilibrium in the system, it takes an average (high) speed of 90.84% to adjust itself back towards long-run equilibrium level. This finding was collaborated by Banerjee, Dolado and Mestre (1998) who asserted that a highly significant lagged error correction terms proves the existence of long-run relationship between the variables and its ability to adjust from dis-equilibrium state towards equilibrium level. The coefficient of determination (R-square), which was used to measure the goodness of fit of the estimated model, indicates that the model is reasonably fit in prediction. It showed that 81.99 percent changes in GSMEP were collectively due to INTR, EXR and INF while 18.01 percent

Figure 5. CUSUM stability tests of trade policy and growth of SMEs in Nigeria. Source: Authors computation, 2022 (Eviews-10).

Table 13. Monetary model: ARDL (4, 4, 4, 1) ECM results. Dependent variable: DLOG (GSMEP).

Notes: ***, ** and * indicate statistical significance at 10%, 5% and 1% levels, respectively. Source: Authors Computation, 2022 (Eviews-10).

Table 14. Fiscal policy model: ARDL (4, 4, 2) ECM results. Dependent variable: DLOG (GSMEP).

Notes: ***, ** and * indicate statistical significance at 10%, 5% and 1% levels, respectively. Source: Authors computation, 2022 (Eviews-10).

Table 15. Trade policy model: ARDL (2, 4, 1) ECM results. Dependent variable: DLOG (GSMEP).

Notes: ***, ** and * indicate statistical significance at 10%, 5% and 1% levels, respectively. Source: Authors computation, 2022 (Eviews-10).

Figure 6. CUSUM Square Stability Tests of Trade Policy and Growth of SMEs in Nigeria. Source: Authors computation, 2022 (Eviews-10).

unaccounted variations was captured by the white noise error term. It showed that INTR, EXR and INF have an impact prediction on GSMEP within the period under review. The model also indicates that there is no autocorrelation among the variables as indicated by Durbin Watson (DW) statistic of 2.09. This shows that the estimates are unbiased and can be relied upon also for policy decisions.

5.2. Fiscal Policy and Growth of SMEs

The ECT (−1) represents the speed of adjustment to restore equilibrium in the dynamic model following a disturbance. The estimated coefficient of the ECT (−1) which equals −0.5496 suggests a relatively quick speed of adjustment back to the long-run equilibrium. The coefficient is highly significant at the 1 percent significance level and appropriately signed. The result suggests that about 54.96 percent of the deviation between the actual and the long-run equilibrium value of GSMEP is corrected each year. That is approximately more than 54.96 percent of the disequilibria from the previous year’s shock converge back to the long-run equilibrium in the current year. The coefficient of determination (R-square) indicates also that the model is reasonably fit in prediction. It showed that 74.74 percent changes in GSMEP were collectively due to TAXES and GOVEX while 25.26 percent unaccounted variations were captured by the error term. The model also indicates that there is no autocorrelation among the variables as indicated by Durbin Watson (DW) statistic of 2.44. This shows that the estimates are unbiased and can be relied upon for policy decisions

5.3. Trade Policy and Growth of SMEs

The ECT coefficient value of −0.7065 revealed that once there is disequilibrium in the system, it takes an average (annual) speed of 70.65 percent to restore a long-run relationship between the trade policy and Growth of Small and Medium Enterprises (SMEs) in Nigeria. The implication of this is that, once there is disequilibrium in the system, it takes an average speed of 70.65% to adjust itself back towards long-run equilibrium level as captured in Table 6. Furthermore, the coefficient of determination (R-square), used to measure the goodness of fit of the estimated model, indicates that the model is also reasonably fit in prediction. The (R-square) value of 0.6583 shows that TARRI and TO has a very good impact on GSMEP. It indicates that about 65.83 per cent of the variation in GSMEP is explained by TARRI and TO, while the remaining unaccounted variation of 34.17 percent is captured by the error term. The model also indicates that there is no autocorrelation among the variables as indicated by Durbin Watson (DW) statistic of 1.94. This shows that the estimates are unbiased and can be relied upon for policy decisions.

6. Discussion of Findings

Findings from the study revealed that monetary policy (interest rate, exchange rate and inflation) has no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria. This may be attributed to prime lending rate that witnessed relative instability after consolidation of 2005 and post-consolidation period of 2007. The results further imply that frequent depreciation of the naira due to fluctuations in exchange rates had adverse effects on the growth of small businesses in Nigeria. The findings are in agreement with Ishioro (2013) who observed that negative monetary shocks posed a constraint to the banking system’s capability to dispose deposits due to adjustability of price that lead to a fall in real money balances causing interest rates to rise thereby increasing the cost of capital. Also, Findings from the analysis in hypothesis two further revealed that fiscal Policy (government expenditure and taxes) has no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria. The implication of these results is that there is lack of information and awareness on the part of proprietors of SMEs about schemes that are meant to reduce their administrative and production costs of operation at the initial stage of operation. Most SMEs are not aware of the tax holiday granted by the Nigerian government under the pioneer status that grant five years tax holiday (and can be extended for a further two years) to a new company registered in Nigeria. This is in-line with Adegbie & Fakile (2011) whose findings revealed that there is an insignificant relationship between tax and SME development in Nigeria; and that high tax rates are the major hindrances to output growth among small-scale businesses. Finally, findings from the third hypotheses of this study showed that trade policy (tariff and degree of trade openness) have no significant effect on the growth of Small and Medium Enterprises (SMEs) in Nigeria. This is due to the fact that SMEs lack the needed technology and the capability to achieve large-scale production, which should help reduce cost of production. This has indirectly constrained their ability to gain access to the global market because their products are not price competitive and mostly not standardized. It shows that amount generated from tariff placed on imported and exported goods in Nigeria has not hugely influenced SMEs growth in Nigeria. This finding is in tandem with the findings of Ishola et al. (2015) who found an insignificant impact between trade openness and economic growth in Nigeria.

7. Conclusions and Recommendations

Having examined the selected economic policies on the growth of SMEs in Nigeria and found out that monetary, fiscal and trade policies had a negative and non-significant effect on SMEs in Nigeria, the study concludes that major determinants of SMEs growth are policies directed on interest rate stabilization, exchange rates management and inflations rate targeting, tax rate reduction and stability, and government expenditure (spending) on infrastructure targeting. The implication is that the interplay of these variables is important to keep SMEs alive in Nigeria. The policy insinuation therefore, is that monetary, fiscal and trade policy should be set in such a way that the objective it wants to achieve is clearly and transparently defined in response to the dynamics of the domestic and global economic developments. Based on these conclusions, the study therefore recommends that economic policy should be design and formulated in such a way that the goals the SMEs wants to achieve through monetary, fiscal and trade policies should be realistic and feasible in terms of growth.

Conflicts of Interest

The authors declare no conflicts of interest.

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