Institutional Financing of Small and Medium Enterprise and Economic Growth in Nigeria
Abstract
This study investigates the effect of institutional financing and economic growth in Nigeria. This study aims to evaluate the impact of SMEs financing on economic growth of Nigeria during the period 30 years from 1995 to 2024. Ex-post factor research design was adopted for this study. The population of the study consists of all twenty-two (22) quoted deposit money banks in Nigeria. The time series data for this study will be collected from secondary source. The data was obtained from the Central Bank of Nigeria Statistical Bulletin, National Bureau of statistic report and other relevant reports covering 30 years’ period from 1992-2022. The Autoregressive distribution Lag (ARDL) model was used in testing the research hypotheses for this study. Findings from this study shows that DMB Loan has a negative insignificant effect on gross domestic product in Nigeria. Micro Savings has a positive significant effect on gross domestic product in Nigeria. Micro Loan and Advances has a positive significant effect on gross domestic product in Nigeria. The study concludes that institutional financing of small and medium enterprise and economic growth in Nigeria had no significant effect from 1995-2024. The study recommends among others that financial credit institutions should increase and mobilize more funds through effective windows of financial intermediation and enhance a better policy that will make small and medium enterprises easy access to credit facilities.
Keywords
Small and medium enterpriseEconomic growthMicro- Loancredit institutions
References
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Business Management Dynamics, 2(2), 10-25. Sacerdoti, E (2015). Access to Bank credit in Sub-Sahara Africa: Key Issues and Reform Strategies. International Monetary Fund (IMF)Working Paper, 05166. SMEDAN (2007). “National policy on micro, small and medium scale enterprises”. Retrieved 20th July, 2024 from http://www.smedan.gov.ng/search.php? National%20policymsmes. Surbhi S. (2018), Difference between loans and advances. Key differences. https://keydifferences.com/difference-between-loans-and-advances.html APPENDIX Data on RGD[ (RGDP), DMB LOAN), Micro Savings (MFF), and Micro Loan and Advance (LOV from (1995-2024). Source: CBN Statistical Bulletin 2024. YEAR GDP DMB LOAN to SMEs Billion (N) MSAV Billion (N) LOV Billion (N) 1995 1,257.17 15.46 12017.8 9240.1 1996 1,768.79 20.55 31417.0 10150.3 1997 3,100.24 32.37 41368.1 19652.1 1998 4,086.07 42.30 56682.0 23511.3 1999 4,418.71 40.84 21746.3 32661.4 2000 4,805.16 42.26 246326.9 38920.3 2001 5,482.35 46.82 21418.5 40127.1 2002 7,062.75 44.54 71608.1 5435.6 2003 8,234.49 52.43 76692.0 52421.1 2004 11,501.45 82.37 39790.6 149326 2005 13,556.97 90.18 3375.9 101482.5 2006 18,124.06 54.98 3375.9 101482.5 2007 23,121.88 50.67 47523.7 28504.8 2008 30,375.18 25.71 34017.7 16450.2 2009 34,675.94 41.10 41217.7 22850.2 2010 39,954.21 13.51 61568.1 42753.1 2011 43,461.46 16.37 76662 58215.7 2012 55,469.35 12.55 75739.6 52867.5 2013 63,713.36 15.61 59375.9 50928.3 2014 72,599.63 13.86 98789.1 80127.9 2015 81,009.96 15.35 121788 94055.6 2016 90,136.98 16.07 110688 82421.1 2017 95,177.74 12.95 159454 149326 2018 102,575.42 10.75 122679.7 101482.5 2019 114,899.25 10.75 130940.6 111076.5 2020 129,086.91 44.82 137691.4 120628.3 2021 145,639.14 123.93 130437.2 111062.4 2022 154,252.32 62.51 133023.1 114255.7 2023 176,075.50 83.74 133717.2 115315.5 2024 190,089.30 94.81 132392.5 113544.53 Optimum lag selection VAR Lag Order Selection Criteria Endogenous variables: GDP Exogenous variables: C Date: 09/08/25 Time: 05:52 Sample: 1995 2024 Included observations: 26 Lag LogL LR FPE AIC SC HQ 0 -321.3014 NA 3.43e+09 24.79242 24.84080 24.80635 1 -243.8990 142.8967* 9604444.* 18.91531* 19.01209* 18.94318* 2 -243.2011 1.234821 18.93854 19.08371 18.98035 3 -242.5890 1.035826 10149854 18.96838 19.16194 19.02412 4 -241.8297 1.226574 10364235 18.98690 19.22884 19.05657 5 -241.3768 0.696822 10848845 19.02898 19.31931 19.11259 Null Hypothesis: GDP has a unit root Exogenous: Constant, Linear Trend Lag Length: 1 (Automatic - based on AIC, maxlag=1) t-Statistic Prob.* Augmented Dickey-Fuller test statistic 1.826853 1.0000 Test critical values: 1% level -4.309824 5% level -3.574244 10% level -3.221728 *MacKinnon (1996) one-sided p-values. Null Hypothesis: D(GDP) has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic - based on AIC, maxlag=1) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -5.885563 0.0002 Test critical values: 1% level -4.309824 5% level -3.574244 10% level -3.221728 *MacKinnon (1996) one-sided p-values. VAR Lag Order Selection Criteria Endogenous variables: DMBLOAN Exogenous variables: C Date: 09/08/25 Time: 06:01 Sample: 1994 2024 Included observations: 26 Lag LogL LR FPE AIC SC HQ 0 -125.7862 NA 1007.215 9.752783 9.801171 9.766717 1 -118.3781 13.67648* 615.4048* 9.259853* 9.356629* 9.287721* 2 -118.2612 0.206771 659.1434 9.327786 9.472951 9.369588 3 -118.2610 0.000403 712.8537 9.404691 9.598244 9.460427 4 -117.8100 0.728542 745.3795 9.446921 9.688863 9.516592 5 -117.2144 0.916301 771.7165 9.478029 9.768359 9.561634 Null Hypothesis: DMBLOAN has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic - based on AIC, maxlag=1) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -2.004425 0.5754 Test critical values: 1% level -4.296729 5% level -3.568379 10% level -3.218382 Null Hypothesis: D(DMBLOAN) has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic - based on AIC, maxlag=1) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -6.540854 0.0000 Test critical values: 1% level -4.309824 5% level -3.574244 10% level -3.221728 *MacKinnon (1996) one-sided p-values. VAR Lag Order Selection Criteria Endogenous variables: MSAV Exogenous variables: C Date: 09/08/25 Time: 06:05 Sample: 1995 2024 Included observations: 26 Lag LogL LR FPE AIC SC HQ 0 -320.8658 NA 3.31e+09 24.75891 24.807
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