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Effect of Interactive Engagement Strategy on Secondary School Students’ Performance in Metelwork in Ekiti State, Nigeria
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Effect of Interactive Engagement Strategy on Secondary School Students’ Performance in Metelwork in Ekiti State, Nigeria

Effect of Interactive Engagement Strategy on Secondary School Students’ Performance in Metelwork in Ekiti State, Nigeria

Ilesanmi Peter Ogundola Ekiti State University, Ado Ekiti, Nigeria

Received: 19 February 2023;  Accepted: 03 March 2023; Published: 31 March 2023

ABSTRACT

This study was designed to investigate the effect of interactive engagement strategy on the performance of secondary school students in metal work in Ekiti State, Nigeria. The study adopted a quasi-experimental pre-test and post-test non-equivalent experimental and control group design which involved groups of students in their intact classes was adopted. The population for the study was all 11 SSS II students offering metal work in all Senior Secondary Schools in Ekiti State. One research questions and one null hypothesis tested at 0.05 level of significance guided the study. The instrument used for data collection was the interactive engagement Strategy (IES) questionnaire, The IES instrument was subjected to face and content validation by three experts. The trial test for determining the coefficient of internal consistency and stability of the instrument was carried out using Pearson Product Moment correlation statistics, Kudder –Richardson-20. (K-R.20), the value was found to be 0.75. Mean was used to answer the research question, while ANCOVA was employed to test the hypothesis. The result of the study indicated that there was no significant difference between the effect of interactive engagement strategy and the conventional technique on students’ achievement in metalwork. A slight improvement was however observed in the achievement scores of students exposed to interactive engagement strategy. Recommendation was given on the usage of the teaching strategy at the secondary school level.

Keywords: Interaction Engagement, Metal work, Students performance, Secondary Schools, Nigeria

INTRODUCTION

Metalwork is the process of working with metals to create individual parts. It is indeed the process of forming and shaping metals to create useful tools, objects, equipment parts, and structures. Metalwork subject is designed to help the student to use hand and machine tools in the workshop to produce simple work pieces, demonstrate knowledge and understanding of materials used in the workshop, apply the principles of logical planning in the manufacture of items in the workshop and also observe safety precautions. Metalwork generally fall under three categories of forming, cutting, and joining. It may also involve techniques such as cutting, welding, casting, and molding. Materials used by metalwork worker may include ferrous and non-ferrous metals such as steel, aluminum, gold, silver, bronze, iron, and more. Accordingly, WAEC (2022) identify the objective of Metalwork to include observation of safe working practices in the workshop, demonstration of knowledge and understanding of tools, materials and equipment, apply basic processes for the care and maintenance of hand and machine tools, have the ability in identifying, analysing and evaluating a problem, apply their knowledge of processes and materials to the solution of problems, Demonstrate basic skills of good craftsmanship, apply knowledge of career opportunities in metalwork, have the ability to translate an idea into a project design. Thus the main purpose of the program is to prepare students for postsecondary education and or employment in the Metalwork industry. The importance of metalworking cannot be over emphasized, this is because it provides machinery and inputs to most economic activities for their reproduction. These include the manufacturing industry, construction, automotive, mining, agriculture, as well as many others (Kristin, 2022) While at the same time providing individual practitioners with a source of livelihood just like all other vocational trades

Metalwork is presently not a compulsory subject at the SSS level.  It is essentially chosen by students who intend to study science, engineering and technology related courses at the tertiary level or students wishing to practice after secondary level education. The realization of the objectives of metal work can only be achieved only when the trade is appropriately and effectively taught to learners.  This can be possible by making teaching/learning process to be student-centered as against being teacher-centered and by also viewing students as problem solvers rather than direction followers. Thus for a nation to develop technologically the study of metalwork must be encouraged as it is a very important foundation for all mechanical engineering related courses.

In order to achieve the objective of effective training of prospective competent engineers and technologist, government at both the federal and state levels expended huge amount of money on the procurement of equipment for use as technical education equipment in the secondary schools. In the same vein, such effort like curriculum review, policy shift, re-training, and production of technical education teachers by the government to ensure qualitative education at the Senior Secondary School (SSS) level and bring about high quality products both in academics and for employment have not yielded much dividend (Federal Government of Nigeria (FGN),2001). There have been persistent reports of high rate of failure in metalwork subject in the West African Senior School Certificate Examination (WASSCE). The analysis of West African Examination Council (WAEC) result compiled by the planning, Research and Statistics Department, Ekiti State Ministry of Education,  Science and  Technology  revealed that of the entire twenty two candidates that  sat  for  metalwork  in  2018,  no  single  candidate passed  at  credit  level.  In 2019, only 02 of the 13 students that sat for metalwork passed at credit level. In 2020, only a disturbing 06 (15.5%) of the 20 candidates that sat for the examination passed at credit level. One probable cause of the steady fall in the performance level in metalwork subject according to WAEC Chief Examiner’s report (2011) is indicative  of  a  serious  variance  between  the expectations  of  National  Policy  on  Education (NPE) and reality, and calls for an assessment of the   available   infrastructure   as   well as the teaching strategy adopted in imparting knowledge to the students. Thus, the poor performance of students in metalwork may be attributed to the use of conventional methods such as demonstration method adopted for teaching the trade subject. Obviously, the adoption of only lecturer-centered methods of teaching by the trade teachers may results into ineffective use of varieties of instructional materials and facility and inability of trade teachers to effectively implement the curriculum to naturally increase students’ involvement and commitment in learning. To this therefore  the learning environment should be transformed from one  that  is  predominantly  memory-based  and teacher-based learning environment, to one that promotes learner-centered learning (Agboghoroma, 2015) Such as interactive engagement strategy

Interactive engagement teaching strategy according to Starting Point (2023) are strategy designed to promote conceptual understanding through interactive engagement of students in heads-on (always) and hands-on (usually)activities which yield immediate feedback through discussion with peers and/or instructors.

Accordingly, Gergis (2011) describe IE as a means of instruction whereby the teachers actively involve the students in their learning process by way of regular teacher-student interaction, student-student interaction, use of audio-visuals, and hands-on demonstrations. To this therefore, the students are constantly encouraged to be active participants in their quest to acquire knowledge. Participating students are engaged in learning activities that lead to a higher level of understanding and result in the participants’ (students) ability to apply what they learned on the job. Interactive teaching is a two-way process of active participant engagement with each other, the facilitator, and the content.

The principles of interactive engagement assume that students receive knowledge not only from the teacher, but also interacting with each other using additional materials and tools. (Briolight, 2022). The main feature of interactive engagement teaching strategy is that new knowledge is not given ready-made, the student must obtain it on his own. In this case, not only the result becomes significant, but also the course of reasoning, which forms critical thinking. Briolight (2022) further identified brainstorming, projects with presentation, business games (role-playing and imitation), use of information and communication technologies, playback of audio and video materials (online tests, use of training sites, special programs or interactive equipment designed for training) as main methods and techniques for implementing interactive learning

Zamira Gashi Shatri (2016) in the study titled Implementation of Interactive Teaching Techniques in School Practice. The study involved a total respondents of 60 secondary school students and teachers in six different places in Kosovo. The results of the study indicates that a significant number of teachers practice interactive teaching techniques in schools. The study also revealed that Learning is more attractive to students. Students can evaluate each – other. With these methods encourage critical thinking and understanding, students collaborate with each other among other findings.

Furthermore in the study of Eiman and Matthew (2017) titled; Students’ perceptions of lecturing approaches: traditional versus interactive teaching. 60 first year dental students at the School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast (QUB), UK, were used for the study. The result indicated that interactive engagement promote interactivity, focused attention, and provide feedback on comprehension. A total of 95% of the respondents reported that it increased their participation and found that it clarified their thinking and helped to focus on key points. Another 81.7% mentioned that it increased their motivation to learn. Students regarded it as a useful method for giving real-time feedback, which stimulated their performance and participation and that the strategy was helpful in focusing students’ attention and in clarifying information among other findings.

In a related vein, the study conducted by Rimma, Aleksandrа and Marina (2016) titled; The Use of Interactive Methods in the Educational Process of the Higher Education Institution, The study was conducted to ascertain the influence of interactive methods on undergraduate students studying Psychological-pedagogical education at the Institute of Psychology and Pedagogy at the Sakhalin State University, Russia. The study indicated that interactive training is the most effective in the preparation of future psychologists. This because they observed that students exposed to the interactive methods, form professional competences, develop analytical thinking, mobilize their cognitive powers, and develop strong interest in new knowledge among other findings.

On the same vein Nataliia, Yuliia, Olha, Olena & Nelia (2021) also conducted a study titled the Ways of Developing Basic Competences in the Study of Foreign Languages through Interactive Methods. The effectiveness of the interactive engagement strategy was investigated in learning of the following foreign languages: English, German, French, Spanish, and Polish. It was found that the strategies have positive effect on improving the correctness of language, its purity, clarity, accuracy, logic, expressiveness, and conciseness. The need to inculcate in students’ the workplace basic and thinking skills that will enable them to fit properly in the world of work and improve their performance which is a source of concern in the senior secondary school certificate examination (SSSCE) called for effective instructional techniques such as the interactive engagement strategy. Based on the foregoing therefore, the study investigated the effect of interactive engagement strategy on secondary school students’ performance in metalwork in Ekiti State, Nigeria.

Purposes of the Study

The purpose of this study was to determine the effect of interactive engagement strategy on secondary school students’ performance in metal work in Ekiti state, Nigeria

Research Question

The below research question was posed to guide this study

What is the effect of interactive engagement strategy on secondary school students’ performance in metalwork?

Research Hypothesis

HO: There is no significant difference in academic achievement of students taught metalwork with interactive engagement strategy and those taught using conventional method.

METHODS

Design of the Study

This study adopted a quasi-experimental pre-test and post-test non- equivalent control group design. This design was considered suitable for the study because intact classes (non-randomized groups) were assigned to the two different groups in this studies (Interactive engagement strategy and control group)

EG, O1 x O1 CG, O1 O1

Where

EG   stands for experimental group CG   stands for control group

O1   stands for pre-test/post-test observation

X   stands for the Interactive engagement strategy treatments

–     stand for the use of the Conventional method

Research Subjects

The population for the study comprises of all the 11 senior secondary school two students in all the three senior secondary schools offering metalwork in Ekiti State. Six (6) of the students were in a school, four (4) are in another school while one (01) is in the third school. The reason for choosing SSS two is that the students have undergone the curriculum of the subject in their year one and they could respond to the test items. The sample for the study comprised of ten students purposively sampled. Thus 6 of the students were treated with Interactive engagement strategy in one school while 4 students were used as control group in another school.

Research Instrument

The instrument for data collection for this study was the Metalwork Interactive engagement test (MIET) developed by the researcher. The MIET instrument contained 25 multiple choice items with five options. The MIET items therein were adapted from the West African Examination Council (WAEC) syllabus paper 1 past question papers. The instrument was administered on the respondents during the pretest stage, it was thereafter reshuffled to be used for the posttest administration. This rearrangement was to curtail over familiarization of students with an arrangement pattern. The test items covered all the contents of the lesson plans developed to cover the major topics used for the study.

The Metalwork Interactive engagement lesson plans was used by the respective metalwork teachers who are also the research assistance in the experimental schools to teach the experimental groups while the control groups were taught with conventional lesson plans. The instrument was validated by one test and measurement expert and Two Mechanical Technology Education experts. The pilot tryout of the MEIT was conducted in a secondary school outside the state that did not take part in the study. The trial test for determining the coefficient of stability of the MIET was carried out using test re-test reliability technique. This is by administering the test on same students twice within the interval of two weeks. The reliability coefficient of the instrument was found to be .75 using Kuder Richardson formula 20 (K – R 20), since the test items are of multiple choice types

Experimental Procedure

The conduct of the study took place during the normal school lesson periods. The research was conducted in three stages. During the first stage ; intensive training programme was organized for the teachers involved in the study. The training exercise was based on the purpose of the study, the topic to be taught, the use of the lesson plans, the use of instrument and general conduct of the study. The MIET was thereafter administered as pretest on all the students (experimental and control).

The second stage lasted for four weeks. It witness the commencement of the experimental study. The prepared Metalwork Interactive engagement lesson plans was used to teach the experimental groups. The instructional procedures for the experimental groups includes;

Step 1: Introduction of the topic by giving pre-class assignment to the students. I.e. students to visit the laboratory to perform test on the metals

  1. identify colours of traditional wooden/metal hoes, spears and daggers,
  2. explain what they perceived is the cause of the colours of the metal
  3. identify reasons why bolts and gears are not easily cut with hack saw or dented by hammers just like some other ferrous metals i.e. mild or medium carbon steel of same size

Step 2: Introduction of the topic on the bases of the pre-class assignment given to the students i.e. Heat Treatment of Metals.

Step 3: Conceptual questions were posed to the students based on pre-class assignment and the sub topic being taught. i.e.

Step 4: The students were given ample time to respond to the pre-class assignment after which they are allowed to keep their responses to a later time when they will be called upon to criticise the answers themselves

Step 5: Use teaching aids that press for answers, and capture/hold the student’s attention for explaining concepts. These may include charts, drawings, various tools, worked project and samples. I.e. charts depicting heat treatment processes and samples of heat treated metals

Step 6: The students were asked to group themselves into groups of three (3) Students per group for interaction purposes especially with respect to the pre-class assignment and the topic at hand.

Step 7: The students carry out investigation on the concept explained by teacher by involving in practical activities (hands-on-activity) using all tools, machines and online materials provided under the guidance of the teacher and workshop attendance. I.e. carry out heat treatment of some metals.

 Step 7: more probing questions are thereafter asked as regard the practical class. I.e. explain characteristics exhibited by metals subjected to different heat treatment process.

Step 8: Based on the class activities, students are there after encourage to criticise their responses to the pre-class assignment earlier kept with them within the group. They are expected to seek clarification from the teacher where need be.

The third stage involved the administration of the rearranged MIET instrument on both the experimental and control groups. The process also lasted for one week.

Data Analysis

The data collected from the administration of pre- test, post-test was analyzed using Mean to answer the research questions. The hypotheses formulated for the study was tested at .05 level of significance using Analysis of Covariance (ANCOVA).  This is because ANCOVA as a statistical technique removed the initial differences between groups, so that the selected or pre-tested groups can be correctly considered as equated or equivalent by removing score difference in the pre-test performance across groups and reducing the between-group source variation (Statistics Solutions, 2023).

What is the effect of interactive engagement strategy on secondary school students’ performance in metalwork?

RESULTS AND DISCUSSION

Research Question: What is the effect of interactive engagement strategy on secondary school students’ performance in metalwork?

Table 1 – Mean of MIE test scores of students taught with interactive engagement strategy and conventional techniques

Test                                    Teaching Techniques
interaction engagement Conventional Method
N Mean      N Mean 
Pre-test 06 22.00 05 23.40
Post-test 06 70.00 05 67.80
Mean gain score 48.00   44.40

Table 1 shows that the students taught metalwork with interactive engagement strategy had a mean interest score of 22.00 in the pretest and a mean interest score of 70.00 in the posttest making a posttest mean gain in the treatment group to be 48.00. The group taught metalwork with conventional technique had a mean interest score of 23.40 in the pretest and a posttest mean of 67.80 with a posttest mean gain of 44.40. This result indicates that both the interactive engagement strategy and the conventional technique are effective in increasing students’ achievement in metalwork but the effect of interactive engagement strategy on students’ achievement in metalwork is higher than the effect of the conventional technique.

Figure 1

Research Hypothesis

HO: There is no significant difference in academic achievement of students taught metalwork with interactive engagement strategy and those taught using conventional method

Table 2 – Summary of Analysis of Covariance (ANCOVA) for Test of Significance of Treatments on Students’ Achievement in Metalwork

Source of Variation Sum of Squares DF Mean Square F Sig of F
Corrected Model 37.763a 2 18.881 .680 .534
Intercept 363.541 1 363.541 13.087 .007
Pretest 24.563 1 24.563 .884 .375
Treatment 23.743 1 23.743 .855 .382
Error 222.37 8 27.780
Total  52631.000 11
Corrected Total 260.000 10

*Significant at sig of F< .05

The data presented in Table 2 shows F-calculated values for effects of treatment on students’ achievement in metalwork.  The F-calculated value for treatment is .855 with a significance of F at .382 which is more than .05. The null-hypothesis is hereby accepted at .05 level of significance. With this result, there is no significant difference between the effect of interactive engagement strategy and the conventional technique on students’ achievement in metalwork.

Discussion of findings

The data on table 1 shows that students taught metalwork with interactive engagement strategy and those taught with conventional laboratory method both had improvement in their achievement in the metalwork achievement test but the effect of interactive engagement strategy was slightly  higher than the effect of the conventional technique by just a mean of 3.60. At the same time, Analysis of covariance was employed  to  test  the  hypothesis as indicated in  Table  2,  at  an calculated  F-  value  (.855) with a significance  of  F  (.382)  and confidence level of .05. This result, clearly indicated that there was no significant difference between the effect of interactive engagement strategy and the conventional technique on students’ achievement in metalwork. This thus implies that the interactive engagement strategy is not more effective than the conventional technique in improving students’ achievement in metalwork.

This finding corroborated the study conducted by Ali & Ömer (2018) who investigated the possible effects of blended learning on high school students’ physics achievements, science process skills, and attitudes towards physics. They observed that the effect of blended instruction is not dependent upon the teaching methods implemented with and as such there study indicated that expository teaching method is as effective as inquiry teaching method.

The findings of this study is at variance with those of Nataliia, Yuliia, Olha, Olena & Nelia (2021) who observed a significant increase in students’ achievement in language proficiency. This differences may be attributed to the fact that the present study is a practical oriented trade that is generally taught with the use of the laboratory method which can be said to be student centered to some extent. The findings is not also not in agreement with that of Eiman and Matthew (2017) and Rimma, Aleksandrа and Marina (2016) who all also observe a positive increase in achievement over the conventional method. Perhaps, this differences observed in this study and others being reviewed might be as a result of the fewness of the population of the respondent in this study. While the population all the reviewed study are mostly above a hundred that of this study stood at just eleven (11) with just ten (10) of them being used for the study, there is does every probability that students in the control group might unconsciously be collaborating together either during on-school or off-school hours. Though, the students are made not to stay together during classes because of the competitive nature of the group, they might indirectly be gaining collectively from one another and from the teacher’s responses to questions and answers.

CONCLUSION

The study revealed that there was no significant difference in the achievement of senior Secondary students in metalwork when taught using interactive engagement strategy as compared to the conventional teaching method. The slightly higher mean gain observed in the achievement test was therefore not significant.

RECOMMENDATIONS

The following recommendations are made Based on the findings.

Workshops and Seminars should be organized to educate Metalwork and other practical oriented vocational Education subject teachers on the use of interactive engagement strategy and other contemporary student centered teaching strategies.

REFERENCES

  1. Agboghoroma, T. E.(2015) Interaction Effects of Cognitive Style and Instructional Mode on Students’ Knowledge of Integrated Science. European Journal of Research and Reflection in Educational Sciences 3(1) https://www.idpublications.org/wp-content/uploads/2015/01/Interaction-effects-of-cognitive-style-and-instructional-mode-on-students%E2%80%99-knowledge-of-integrated-science.pdf
  2. Ali Ç & Ömer F. Ö. (2018) Mode-Method Interaction: The Role of Teaching Methods on The Effect of Instructional Modes on Achievements, Science Process Skills, and Attitudes Towards Physics. EURASIA Journal of Mathematics, Science and Technology Education, 14(5) https://www.ejmste.com/download/mode-method-interaction-the-role-of-teaching-methods-on-the-effect-of-instructional-modes-on-5388.pdf
  3. Briolight (2022) Advantages and disadvantages interactive technologies in education. The Briolight Blog. https://briolight.com/en/advantages-and-disadvantages-interactive-technologies-in-education/
  4. Federal Government of Nigeria. (2001) Technical and vocational education development in Nigeria:  The way forward, report of the Advisory panel of inquiry on TVE in Nigeria, Abuja: Federal Government Press.
  5. Girgis H. H. (2011) Interaction in teaching http://www.bchmsg.yolasite.com/interaction.php
  6. Rimma, A. K , Aleksandrа A. E & Marina, A. R (2017)The Use of Interactive Methods in the Educational Process of the Higher Education Institution. International Journal of Environmental & Science Education, 11(14) https://files.eric.ed.gov/fulltext/EJ1115891.pdf
  7. Kristin, A. (2022) Metalworking 101: The Basics of Metalworking. The Crucible https://www.thecrucible.org/guides/metalworking/
  8. Nataliia, A. L , Yuliia, O. Y, Olha, V. D , Olena, M. K & Nelia, O. M (2022)The Ways of Developing Basic Competences in the Study of Foreign Languages through Interactive Methods. Journal of Curriculum and Teaching, 11(1) https://files.eric.ed.gov/fulltext/EJ1340803.pdf
  9. Statistics Solutions (2023) General Uses of Analysis of Covariance (ANCOVA). Dissertation Consulting Blog. https://www.statisticssolutions.com/general-uses-of-analysis-of-covariance-ancova/
  10. The West African Examinations Council (2006), Executive Summary of Entries, Results and Chief Examiners’ Reports on the West African Senior School Certificate Examination (Wassce) Conducted in Nigeria. https://www.waecheadquartersgh.org/
  11. West African Examination Council (2022) WAEC Syllabus for Metal Work 2023/2024 https://studentship.com.ng/waec-metal-work-syllabus/

Publication Information

Journal Title: International Journal of Research and Innovation in Social Science (IJRISS)
Author(s): Ilesanmi Peter Ogundola
Published On: 31/03/2023
Volume: 7
Issue: 3
First Page: 246
Last Page: 253
ISSN: 2454-6186

Cite this Article

Ilesanmi Peter Ogundola, Effect of Interactive Engagement Strategy on Secondary School Students’ Performance in Metelwork in Ekiti State, Nigeria, Volume 7 Issue 3, International Journal of Research and Innovation in Social Science (IJRISS), 246-253, Published on 31/03/2023, Available at https://www.rsisinternational.org/journals/ijriss/articles/effect-of-interactive-engagement-strategy-on-secondary-school-students-performance-in-metelwork-in-ekiti-state-nigeria/

The Effect of Monetary Policy on Economic Growth in Nigeria (2004 – 2022)
Editor IJRISS

The Effect of Monetary Policy on Economic Growth in Nigeria (2004 – 2022)

The Effect of Monetary Policy on Economic Growth in Nigeria (2004 – 2022)

Adeneye Olawale Adeleke (Ph.D)1, Moses O. Anuolam (Ph.D)2 & Florence I. Ezeilo (Ph.D)3
1Admiralty University of Nigeria, Faculty of Art, Management & Social Science, Department of Accounting, Business Administration and Economics, Economics Programme
2Admiralty University of Nigeria, Faculty of Art, Management & Social Science, Department of Accounting, Business Administration and Economics, Accounting Programme
3Admiralty University of Nigeria, Faculty of Art, Management & social Science, Department of Accounting, Business Administration and Economics, Business Administration Programme

Publication Information

Journal Title: International Journal of Research and Innovation in Social Science (IJRISS)
Author(s): Adeneye Olawale Adeleke (Ph.D), Moses O. Anuolam (Ph.D) & Florence I. Ezeilo (Ph.D)
Published On: 08/03/2023
Volume: 7
Issue: 2
First Page: 566
Last Page: 577
ISSN: 2454-6186

Cite this Article

Adeneye Olawale Adeleke (Ph.D), Moses O. Anuolam (Ph.D) & Florence I. Ezeilo (Ph.D), The Effect of Monetary Policy on Economic Growth in Nigeria (2004 – 2022), Volume 7 Issue 2, International Journal of Research and Innovation in Social Science (IJRISS), 566-577, Published on 08/03/2023, Available at https://www.rsisinternational.org/journals/ijriss/articles/the-effect-of-monetary-policy-on-economic-growth-in-nigeria-2004-2022/

ABSTRACT

Arguments against and in favor of the effect monetary policy of Central Bank of Nigeria have on economic growth in Nigeria is inconclusive with mixed outcomes. Therefore, this study investigates the effect of monetary policy on the economic growth in Nigeria between 2004 and 2022. The study employed ex-post facto design with time series data covering the period of 19 years. Econometric technique of Auto-regressive distributed lag was used to analyzed the study data. Findings of the study revealed that the entire explanatory variables in the study namely; Monetary Policy Rate (MPR), Money Supply (MS), and Lending Interest Rate (LNR) at level equation and period of lag one were statistically significant. In terms of the magnitude, finding of the study revealed that the ARDL coefficients of MPR, MS and LNR are 1861.613, 5.091207 and -3778.871. This suggests that both MPR and MS have positive impact on economic growth while LNR has negative impact on economic growth. More so, one percent increase in MPR and MS leads to approximately, 186 and 509 percent increase in economic growth. In the same vein, one percent increase in LNR will effect -3778 percent decrease in economic growth. As manifested from the findings of this study, the following recommendations are suggested: that monetary policy authority should ensure that status quo should be maintained on both MPR and MS while adjustment should be made on lending rate (LNR) by reducing the rate to encourage investors to borrow for the purpose of investment and subsequently, economic growth.

Key Words: Monetary Policy, Monetary Policy Rate, Money Supply, Lending Interest rate and Economic Growth

INTRODUCTION

According to Central Bank of Nigeria (2021) monetary policy is an arrangement or a purposeful measure which is designed to regulate the value, supply and cost of money in an economy in consonance with the expected level of economic activity. However, monetary authority via central bank uses various monetary policy instruments which include; monetary policy rate, money supply, lending interest rate, cash reserve ratio, discount rate, open market operation among other instrument in targeting at controlling volume of money in circulation either directly or indirectly.

However, monetary policy instruments understudy in this study is limited to most commonly employed namely; monetary policy rate, money supply and lending interest rate. The role of monetary policy on the economic development and the changing in an aggregate economic activity depends on how monetary policy is conducted and the independence of the central bank to choose the appropriate monetary tools to formulate the monetary policy of macroeconomic objectives (Alavinasab, 2016). Conceptually, the monetary policy rate also refers to policy interest rate is an interest rate that the monetary authority (i.e. the central bank) sets in order to influence the evolution of the main monetary variables in the economy (e.g. consumer prices, exchange rate or credit expansion, among others). The policy interest rate determines the levels of the rest of the interest rates in the economy, since it is the price at which private agents-mostly private banks-obtain money from the central bank. These banks will then offer financial products to their clients at an interest rate that is normally based on the policy rate. Different countries have different policy interest rates. The most common are the overnight lending rate, discount rate and repurchase rate (of different maturities).

Normally, central banks use the policy interest rate to perform contractive or expansive monetary policy. A rise in interest rates is commonly used to curb inflation, currency depreciation, excessive credit growth or capital outflows. On the contrary, by cutting interest rates, a central bank might be seeking to boost economic activity by fostering credit expansion or currency depreciation in order to gain competitiveness. Thus, monetary policy plays a stabilizing role in influencing economic growth through a number of channels such as monetary policy rate, money supply and lending interest rate. These aforementioned variables is been measured by time series data released annually by monetary policy authority headed by Central Bank of Nigeria.

Understanding the significant impact of monetary policy on economic growth is inevitable because any monetary policy alteration in any nation is expected to change the level of stock money in circulation thereby influences the rate at which productivity take place and subsequently affects economic growth. Particularly, monetary policy aiming at controlling the level of money in economy in order to checkmate raising inflation, increase in unemployment and economic stability.

However, with current dismal economic outlook of Nigeria as a nation the extent to which monetary policy via monetary policy rate, money supply and lending interest rate impacts economic growth is debatable which called for empirical research. It is against this background that this study examines the impact of monetary policy via monetary policy rate, money supply and lending interest rate on the economic growth in Nigeria between 2004 and 2022.

Statement of the Problem

Despite, the Central Bank of Nigeria (CBN) effort through application of monetary policy measures Nigerian economy is still faced with mirage of problems which is linked to stock of money in circulation. This is because the volume of money in economy determines its economic stability and subsequently, increases or declining in economic growth. Theory and empirical evidence in the literature suggest that sustainable long term growth is associated with lower price levels. In other words, high inflation is damaging to long-run economic performance and welfare. Monetary policy has far reaching impact on financing conditions in the economy, not just the costs, but also the availability of credit, banks’ willingness to assume specific risks, etc. It also influences expectations about the future direction of economic activity and inflation, thus affecting the prices of goods, asset prices, exchange rates as well as consumption and investment.

However, the impact of monetary policy on economic growth in Nigeria and elsewhere is inconclusive with mixed outcomes in both empirical and theoretical literatures. Some studies argue that monetary policy have positive and significant impact on economic growth while others opinion were on the contrary. Studied like Ajibola and Oluwole (2018); Lacker (2014); Lashkary and Kashani (2011) were of the opinion that monetary policy through increase in money supply have adverse effect on economic growth via inflation.

While, studied like; Anowor and Okorie (2016); Chipote and Makhetha-Kosi (2014); Fasanya and Onakoya, (2013) concluded that monetary policy has positive and statistically significant impact on economic growth. These empirical literatures outcomes suggest inconclusiveness. Therefore, the need to ascertain the exact impacts monetary policy has on economic growth in Nigeria between the periods spanning from 2004 to 2022.

LITERATURE REVIEW

Conceptual Review

Conceptually, monetary policy consists of those actions designed to influence the behavior of the monetary sector (Ajibola & Oluwole, 2018). According to Thomas (2022) monetary policy is a set of tools that a nation’s central bank use to promote sustainable economic growth and controlling the overall supply of money that is available to the nation’s banks, its consumers, and its businesses. In other words, monetary policy is a policy employ by Central Bank of a nation to control the supply of money in circulation (Simon & Elias, 2021).

According to CBN (2021), monetary policy is a tool of general macroeconomic management, under the control of the monetary authorities, designed to achieve government economic objectives such as economic growth, price stability, employment generation and balance of payment equilibrium among other. Furthermore, Adigwe, Echekoba and Justus (2015) posited that monetary policy is a major economic stabilization weapon which involves measures designed to regulate and control the volume, cost, availability and direction of money and credit in an economy to achieve some specified macroeconomic policy objectives. In sum, monetary policy is the policy employed by the monetary authority of a nation to checkmate either the interest rate payable for short-term borrowing by banks from each other to meet their short-term needs or the money supply, frequently as an effort to reduce inflation or the interest rate, to ensure price stability and general trust of the value and stability of the nation’s currency. In Nigeria, according to Simon and Elias, (2021) among other several objectives, monetary policy is designed to achieve price stability, balance of payment equilibrium and high rate of economic growth.

Similarly, in macroeconomics, the money supply (or money stock) refers to the total volume of currency held by the public at a particular point in time. There are several ways to define “money”, but standard measures usually include currency in circulation (i.e. physical cash) and demand deposits (depositors’ easily accessed assets on the books of financial institutions)  According to Adeneye (2021) lending interest rate is the price a borrower pays for the use of money they borrow from a lender. It is what banks charge each other for overnight loans. Interest rate is the proportion of a loan that is charged as interest to the borrower, typically expressed as an annual percentage of the loan outstanding. Interest refers to the cost of borrowing money or the reward for saving (Banton, (2020) cited in investopedea.com, 2021). Also according to Marco and Hernandez, (2021) an interest rate is the cost of asking for a loan or saving money. It is calculated as a percentage of the amount that was delivered by a bank, financial institution, or individual. An interest rate is a percentage charged on the total amount one borrows or saves. It is the amount charged on top of the principal by a lender to a borrower for the use of the lender’s assets (Central Bank of Nigeria, 2021).

Theoretical Review

Quantity theory of money propounded by Irving Fisher (1911) and Milton Friedman (1963) as well as Keynesian theory (1936) on money and interest was adopted in this study. The quantity theory of money expresses the relationship between the quantity of money and the price in the form of an equation called “an equation of exchange. The quantity theory of money states that the quantity of money is the main determinant of the price level or the value of money. Any change in the quantity of money produces an exactly proportionate change in the price level. Fisher, stated that all things remaining unchanged, as the quantity of money in circulation increases, the price level also increases in direct proportion and the value of money decreases and vice versa. Thus, the quantity theory of money says that the level of prices varies directly with quantity of money (Ahuja, 2011). This equation of exchange is as follows

PT = MV …………………………………………………………….. (1)

Where: P =Average price level; T =Total amount of transactions; M =Quantity of money

V =Transactions velocity of circulation of money. Thus, T and V are fixed. The quantity theory of money simply indicates that the level of price is a function of the supply of money. For Walras, Marshall, Wicksell and Pigou (the Classical school) this can be expressed as:

M = KPY …………………………………………………… ………..(2)

Where: K = Fraction of income; M = Quantity of money; P = Price level; Y = Value of goods and services. The K is related to velocity of circulation of money V in Fisher’s transactions approach

In Keynesian theory (1936) monetary theory explains the effect of variation in money supply on the level of economic activity through its effect on the rate of interest which determines investment in the economy. Keynes does not agree with the older quantity theorists that there is a direct and proportional relationship between quantity of money and prices; rather the effect of a change in the quantity of money on prices is indirect and non-proportional. Keynesians propose that “money does not really matter to determine the price level, hence unable to significantly impact on economic growth. Keynes in principle believes that velocity of circulation was volatile and there often existed underemployment of resources due to recessionary conditions in the economy. Therefore, Keynesian economics believe that there was no strong automatic tendency for output and employment to move towards full employment levels (Keynes, 1936).

Empirical Review

Henry and Sabo (2020) examine the impact of monetary policy management on inflation in Nigeria between the periods of 1985- 2019. Autoregressive distributed lag analysis was employed. Finding of the study showed that while monetary policy rate and foreign exchange rate impacted negatively on inflation; broad money supply impact positively on it. Kayode, Isreal and onyuka (2020) examine the impact of money supply on savings and investment in developing countries between the period of 1999 and 2016. The study employed multiple regression technique. Finding of the study revealed that money supply have significant impact on savings and investment.

Abiodun and Ogun (2019) studied investigated the asymmetric effect of positive and negative monetary policy shocks on output and prices in Nigeria with a view of ascertaining the impact of monetary policy on sustainable output growth and price stability in Nigeria from 1986 to 2016. Non-linear Autoregressive Distributive Lag (NARDL) was employed. The study results showed that monetary policy shocks have asymmetric effects on output and prices in Nigeria both in the short and long run period.  Ajibola and Oluwole (2018) examined the impact of monetary policy on economic growth in Nigeria between period of 1981 and 2016. The study adopted Johansen Co-integration test and Vector Error Correction Mechanism (VECM). The finding of the study revealed that, two variables (money supply and exchange rate) had a positive and insignificant impact on economic growth. Furthermore, the interest rate and liquidity ratio on the other hand, have a negative and significant impact on economic growth.

Inam and Ime (2017) investigate the impact of money supply on the economic growth in Nigeria between the periods of 1970 and 2012. The study employed Ordinary Least Square (OLS) techniques and the granger causality test. Findings of the study revealed a positive and insignificant relationship between money supply and economic growth.  Khaysy and Gang (2017) examine the impact of monetary policy on the economic development in Lao People’s Democratic Republic between the period of 1989 and 2016. The study employed Johansen Cointegration and Error Correction Finding of the study reveal that money supply, interest rate and inflation rate have negative effect on the real GDP per capita in the long run while real exchange rate has a positive effect.

Alavinasab (2016) examines the impact of monetary policy on economic growth in Iran using, time series data between the period of 1971 and 2011. The study employed Multiple Regression Method and Error Correction Model (ECM). The findings of the study reveal that in the long run money supply, exchange rate and inflation rate have insignificant impact on economic growth while in the short run, money supply and exchange rate have significant impact on economic growth. Chipote and Makhetha-Kosi (2014) examine the role of monetary policy in promoting economic growth in the South African economy between the period of 2000 and 2010. The study employed Johansen co-integration and the Error Correction Mechanism. Findings of the study reveal that a long run relationship exists among the variables. Furthermore, findings of this study show that money supply, and exchange rates are insignificant monetary policy instruments that drive growth in South Africa whilst inflation is significant. Several empirical researches have been conducted to investigate the impact of monetary policy on economic growth in various countries. However, findings of these studied suggest inconclusiveness and mixed outcomes thus, suggesting that there is still a gap in literature.

Theoretical Framework

Figure 1:  Theoretical Framework of this study

Source:  The researchers concept (2022)

Figure 1 above depicts the impact of monetary policy via monetary policy rate, money supply and lending interest rate on economic growth. Each arrow pointed to economic growth simply suggests that any changes in any of these aforementioned variables will causes changes in economic growth.

RESEARCH METHODOLOGY

This study is ex-post facto research design also known as quasi-experimental study or after-the-fact research. Secondary data from Central Bank of Nigeria (2022) on variables which includes; monetary policy rate, (MPR), money supply (MS) and lending interest rate (LNR) and economic growth proxy by (GDP) in Nigeria, between 2004 and 2022 were sourced. Thereafter, econometric techniques analysis of autoregressive distributed lag (ARDL) was employed to analyze the data sourced in model specified. Eview 10 was used to generate and analyzes descriptive as well as inferential statistics for the study. However, the analysis includes both residual and coefficient diagnostics tests in order to satisfy certain econometric assumptions.

Model Specification

ARDL models are linear time series models in which both the dependent and independent variables are related not only contemporaneously, but across historical (lagged) values as well.

Although ARDL models have been used in econometrics for decades, they have gained popularity in recent years as a method of examining cointegrating relationships. ARDL models are especially advantageous in their ability to handle cointegration with inherent robustness to misspecification of integration orders of relevant variables. This study adopts the unrestricted autoregressive distributed lag model developed by Pesaran, Shinb and Smith (2001) by introduced different variables as oppose original model developed by Pesaran, Shinb and Smith (2001) as follows;

Where GDPt is a proxy for economic growth at time t;  MPRt stand for monetary policy rate at time t;  MSt represents money supply at time t; and LNRt  is lending interest rate at time t. furthermore,  Δ is a difference operator, t is time, β0 is an intercept term, β1, β2, and β3 𝛿1to 𝛿3 are the coefficients of their respective variables and ps are the lag lengths. To examine the existence of long-run relationship following Pesaran et al (2001), the study first test, based on Wald test (F-statistics), for the joint significance of the coefficients of the lagged levels of the variables, i.e. Ho: 𝛿1= 𝛿2 = 𝛿3 = 0   and   H1: 𝛿1 ≠ 𝛿2 ≠ 𝛿3 ≠0

The asymptotic critical values bounds, which are tabulated in Pesaran et al (2001), provide a test for cointegration with the lower values assuming the regressors are I(0), and upper values assuming purely I(1) regressors. If the calculated F-statistics exceeds the upper critical value, the null hypothesis is rejected, implying that there is cointegration. However, if it is below the lower critical value, the null hypothesis cannot be rejected, indicating lack of cointegration. If the calculated F-statistics falls between the lower and upper critical values, the result is inconclusive. Once cointegration is established, the conditional ARDL long-run model can be estimated as:

In the next step, we obtain the short-run dynamic parameters by estimating an error correction model associated with the long-run estimates. This is specified as follows:

Where 𝑒𝑐𝑚 is the error correction representation of equation (2) and 𝜗 is the speed of adjustment. Where 𝜗 is the speed of adjustment parameter and ECM is the residuals that are obtained from the estimated co-integration model of equation. Peseran et al., (2001) suggested applying the cumulative sum of recursive residuals (CUSUM) and the cumulative sum of squares of recursive residuals (CUSUMSQ) tests whose equation is detailed in Brown et al., (1975) to assess the parameter constancy of the model. The justification for co-integration and error correction model is to add richness, flexibility and versatility to the econometric modeling and to integrate short-run dynamics with long-run equilibrium. Hence, accurate predictions can be more confidently made on the economic relationship between the variables.

DATA ANALYSIS AND RESULTS PRESENTATION

The results of data analysis are reported in the following subsections.

Table 1 Descriptive Statistics

 GDPMPRMSLNR
 Mean 85737.05 11.31579 19635.48 16.43737
 Median 81009.96 11.50000 18743.07 16.85000
 Maximum 176075.5 16.50000 48518.73 19.33000
 Minimum 18124.06 6.000000 2131.820 11.55000
 Std. Dev. 49736.07 2.663855 13678.58 2.147109
 Skewness 0.326522-0.293590 0.483920-0.897546
 Kurtosis 1.871503 2.825350 2.230436 3.183389
 Jarque-Bera 1.345811 0.297098 1.210414 2.577655
 Probability 0.510224 0.861958 0.545961 0.275594
 Sum 1629004. 215.0000 373074.2 312.3100
 Sum Sq. Dev. 4.45E+10 127.7303 3.37E+09 82.98137
 Observations 19 19 19 19

Source: Researcher Computation using Eview 10

Table 1 presents the descriptive statistics which describes the characteristic of the data used in the study. The study observation is 19. The result shows that both GDP and MS the distribution skewed toward right while MPR and LNR are skewed toward left. In the same vein, kurtosis distribution shows that the entire exhibited relative to normal skewness and leptokurtic. If the kurtosis exceeds 3, the distribution is peaked (leptokurtic) relative to the normal; if the kurtosis is less than 3, the distribution is flat (platykurtic) relative to the normal. The Jarque-Bera test statistic which measure the difference of the skewness and kurtosis of the series with those from the normal distribution show that all the variables understudy were all significant with the probability that a Jarque-Bera statistic exceeds (in absolute value) the observed value under the null hypothesis – a small probability value leads to the rejection of the null hypothesis of no normal distribution.

Table 2 Series of Augmented Dickey-Fuller Test (ADF) Output Results

CoefficientsCritical Values at 5%ADF ValuesProbabilityComments
D(GDP)-3.081002-2.011339 0.2792I(I)
D(MPR)-3.052169-3.809911 0.0116I(0)
D(MS)-3.052169-2.059567 0.2614I(I)
D(LNR)-3.052169-4.063274 0.0071I(0)

Source: Researchers Computation Using (Eviews 10.0 Output)

Table 2 present the series of unit root tests of (ADF). The results show that all the variables are not stationary of order I(0) in first differencing, there is evidence of mixed unit root test result. GDP and MS are not stationary while, MPR and LNR are stationary.

Table 3  Autoregressive Distributed Lag Estimate.

Dependent Variable: GDP  
     
     
VariableCoefficient  Std. Errort-StatisticProb.*
     
     
GDP(-1)-1.7134350.724132-2.3661920.0422
MPR586.8843856.69600.6850550.5106
MPR(-1)1861.613784.90442.3717710.0418
MS0.2440621.1466910.2128400.8362
MS(-1)5.0912072.1767052.3389510.0441
MS(-2)4.9067941.2480843.9314600.0035
LNR-3778.8711376.144-2.7459850.0226
C89512.5126453.663.3837470.0081
     
     
R-squared       0.993565        Mean dependent var      93397.53
Adjusted R-squared0.988559    S.D. dependent var46795.03
S.E. of regression5005.223     Akaike info criterion20.17954
Sum squared resid2.25E+08 Schwarz criterion20.57164
Log likelihood-163.5261      Hannan-Quinn criter.20.21851
F-statistic198.5046    Durbin-Watson stat1.850292
Prob(F-statistic)0.000000   
     
     
*Note: p-values and any subsequent tests do not account for model selection
       

Source: Researcher Computation using Eview 10

Table 3 presents, ARDL regression estimation, the first part of the output gives a summary of the settings used during estimation. The dependent variable lag is 2 while the regressor is fixed at C including observation 17 after adjustment. However, the coefficient of Gross Domestic Product GDP(-1) at period of lag 1 is  approximately -1.71 relatively low but, statistically significant with the probability value of 0.04 at 0.05 level of significance. This implies that other independent variables remain constant a one percentage increase in GDP at period of lagged 1 translates to approximately -171% decreases in its present value. More so, the coefficients of the monetary policy rate (MPR) at current level and period of lag 1 are 586.88 and 1861.61 positively assigned with probability values of 0.51 and 0.04 respectively. MPR at current level is statistically insignificant while at period of lag 1, is statistically significant at 0.05 percent level of significance. This result suggests that monetary policy rate (MPR) period of lag 1 has positive and statistically significant impact on economic growth.  One percent increase in monetary policy rate (MPR) effect an approximately, 1861% increase in economic growth (GDP).

In the same vein, money supply [MS, MS(-1) and MS(-2)] that is, at current, period of lag 1 and 2 respectively, have coefficients of  0.24, 5.09 and 4.91 positively assigned with probabilities of 0.84, 0.04 and 0.00 the result suggests that money supply have positive and statistically significant impact on economic growth both  period of lag 1 and 2 respectively. This result indicates that both MPR and MS move in the same direction with economic growth.

On the contrary, the coefficient of the lending interest rate (LNR) at current  period is -3778.871 negatively assigned with the probability value of 0.02 statistically significant at 0.05 level of significance This suggests that one percent increase in LNR causes about -3778% decrease in economic growth. The result indicates that LNR and economic growth move in opposite direction.

Coefficient of fixed variable that is, constant (C) also known as the intercept is the value of economic growth when other independent variables have a value of zero is 89512.51 statistically significant with probability value of 0.00 at 0.05 level of significance. This result simply suggests that increase in economic growth in Nigeria is associated with other factors which are not explained by any of the explanatory variables stated in the model.

More so, the R-Square which is the coefficient of determination and also known as a measures of the goodness-of-fit, is 0.99, approximately 99%. This means that 99% of the changes in economic growth (GDP) at time t, are explained by the changes in the explanatory variables while, the remaining 1% could be explained by factors outside this model represented by error term. Similarly, adjusted R-squared, value is 99% which explained the variation in the dependent variable that is explained by only those independent variables. The overall model measured by F-statistics is 198.5046 with probability value 0.00 indicating that the model is good fit. More so, Durbin-Watson statistic (DW) is 1.8 approximately 2 shows there is no serial autocorrelation.

 Table 4 below presents ARDL Long Run Form and Bounds Test on which decision to conduct ARDL Error Correction Regression is based

Table 4a ARDL F-Bounds Test

F-Bounds TestNull Hypothesis: No levels relationship
     
     
Test StatisticValueSignificance.I(0)I(1)
     
     
   Asymptotic: n=1000 
F-statistic 9.62623110%2.373.2
K35%2.793.67
  2.5%3.154.08
  1%3.654.66
     

Source: Researcher Computation usingEview10

Table 4 present the F-bound test of null hypothesis of no cointegration regression estimation in order to confirm the no long-run cointegration status. The calculated F-statistics of 9.626231 exceeds the lower and upper critical values of 2.79 and 3.67 respectively at 5% significant level. Therefore, the null hypothesis of no cointegration is rejected, implying that there is cointegration thus the long run relationship estimate is justified.

Table 4b ARDL Long Run Form and F-Bounds Test

     
     
Conditional Error Correction Regression
     
     
VariableCoefficientStd. Errort-StatisticProb.
     
     
C89512.5126453.663.3837470.0081
GDP(-1)*-2.7134350.724132-3.7471560.0046
MPR(-1)2448.4981053.9922.3230700.0453
MS(-1)10.242062.6265333.8994620.0036
LNR**-3778.8711376.144-2.7459850.0226
D(MPR)586.8843856.69600.6850550.5106
D(MS)0.2440621.1466910.2128400.8362
D(MS(-1))-4.9067941.248084-3.9314600.0035
     
     
 * p-value incompatible with t-Bounds distribution.
** Variable interpreted as Z = Z(-1) + D(Z). 
     

Source: Researcher Computation usingEview10

Table 4b results shows that at period of lag 1 the entire variables understudy were statistically significant at 0.05 levels of significance and were positively related exception of LNR which has negative sign. However, Conditional Error Correction Regression consequently produced levels equation alongside the conditional error correction regression outcome. The result at level equation is presented in table 4c as follows.

Table 4c Levels Equation

Case 2: Restricted Constant and No Trend
     
     
VariableCoefficientStd. Errort-Statistic       Prob.
     
     
MPR902.3610321.40652.807538       0.0205
MS3.7745750.09338040.42146       0.0000
LNR-1392.652315.3940-4.415595       0.0017
C32988.645384.3756.126735       0.0002
     
     
EC = GDP – (902.3610*MPR + 3.7746*MS  -1392.6523*LNR + 32988.6377 )
     

Source: Researcher Computation using Eview10

Table 4c, levels equation shows that all the entire explanatory variables are statistically significant based on the probability values of 0.00 less than 0.05% level of significance. This result at level equation simply reveals the directions and magnitude of the relationship between dependent and independent variables.  Finally, table 5 present the error correction regression as follows;

Table 4c ARDL Error Correction Regression

     
     
ECM Regression Case 2: Restricted Constant and No Trend
     
     
VariableCoefficientStd. Errort-StatisticProb.
     
     
D(MPR)586.8843563.73451.0410650.3250
D(MS)0.2440620.5701850.4280400.6787
D(MS(-1))-4.9067940.983748-4.9878580.0008
CointEq(-1)*-2.7134350.325429-8.3380320.0000
     
     
R-squared0.782582    Mean dependent var7972.575
Adjusted R-squared0.732409    S.D. dependent var8050.764
S.E. of regression4164.598    Akaike info criterion19.70895
Sum squared resid2.25E+08    Schwarz criterion19.90500
Log likelihood-163.5261    Hannan-Quinn criter.19.72844
Durbin-Watson stat1.850292   
     

Source: Researcher Computation using Eview10

The result shows that, the CointEq(-1) coefficient of the error correction term which measures the speed of adjustment towards long-run equilibrium is negative and statistically significant at 5% level. The ECM has the expected negative sign which stands at -2.71. This implies that the rate at which changes in GDP at time t, adjusts to the single long-run co-integrating relationship is different from zero. The coefficient of the ECM revealed that the speed with which changes in GDP at time t, adjusts respond to regressors is about -27% in the short-run. This is in conformity with this study aprior expectation.

CONCLUSION AND RECOMMENDATIONS

This study examines the impact of monetary policy via monetary policy rate, money supply and lending interest rate on economic growth in Nigeria between 2004 and 2022. Autoregressive Distributed Lag Regression Estimate (ARDL) was conducted to analyze short-run and long-run impacts of these aforementioned variables on gross domestic product as a proxy for economic growth.

Findings of the study revealed that the entire explanatory variables in the study namely; Monetary Policy Rate (MPR), Money Supply (MS), and Lending interest rate (LNR) at level equation and period of lag one were statistically significant. In terms of the magnitude, finding of the study revealed that the ARDL coefficients of monetary policy rate, money supply and lending interest rate are 1861.613, 5.091207 and -3778.871. This suggests that both monetary policy rate and money supply have positive impact on economic growth. That is both monetary policy rate and money supply move in the same direction with economic growth while lending interest rate has negative impact on economic growth. Meaning that, lending interest rate is moving in the opposite direction with economic growth. More so, one percent increase in monetary policy rate and money supply leads to approximately, 186 and 509 percent increase in economic growth. In the same vein, one percent increase in lending interest rate will effect -3778 percent decrease in economic growth. As manifested from the findings of this study, the following recommendations are suggested: that monetary policy authority should ensure that status quo should be maintained on both monetary policy rate and money supply while adjustment should be made on lending interest rate by reducing the rate to encourage investors to borrow for the purpose of investment and subsequently, economic growth.

References

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