Essays on the relationship between financial sector development and economic growth

Abstract

This study investigates how financial sector development affects economic growth. The determinants of growth which include financial development have been a subject of academic investigation for the last three centuries. In all these efforts, it has been difficult for researchers to be definitive on the forces that affect growth and to explain the differences in the level of growth among nations. The neoclassical link growth to capital accumulation(CA) and total factor productivity(TFP). More recently, researchers report that financial sector development could result in capital accumulation, innovation, and total factor productivity. We investigate these claims and the various ramification of financial development and how they explain growth and the differences in the rates of growth in different contexts. For example, in chapter two of our thesis, we examine the nature of the finance-growth and finance-growth volatility functions in the context of Nigeria using time series data. To analyze the data, we use semi-parametric, Hansen sample splitting and threshold estimators. Our results are revealing. Contrary to the recent literature, we have no evidence of “to much finance.” We had evidence of U-shaped functions in both the finance – growth, and finance – growth volatility relationships. We discuss policy implications of our findings and make recommendations for reforms based on our results. In chapter three of our thesis, we follow up to examine the nature of the finance-growth relationship in the oil-producing countries and compare that with the same relationship in the non-oil producing countries. We purposely selected thirty countries based on the magnitude of the oil production from every continent, we also selected a sample of thirty non-oil producing countries and we sub-divided the samples into two based on the positive and negative indices for institutions in each country. We employ dynamic panel GMM and threshold regressors to analyze our data. We obtain very useful results. We have evidence of “too much finance” and inverted U-shaped functions in all our models. The threshold points in the two samples and the sub-samples were quite revealing. In the oil-producing countries, the thresholds were at 10.62% for the whole sample, 5.38% for the sample with negative indices for institutions, and 79.11% for the sample with positive indices for institutions. The thresholds were different and better in the non-oil producing countries: 14.81% for the whole sample, 14.71% for the countries with negative indices for institutions and 142.25% for countries with positive indices for institutions. Based on our results, we suspected the syndrome of “resource curse” in financial sector development. The implications of our findings are discussed, policy suggestions and areas of further research are articulated. In chapter four, we take up an interesting ramification of financial sector development -the structure of the financial sector (bank-based vs. market-based) and examine to see if it matters in economic growth and growth volatility. Our time series data came from the context of Nigeria from 1980 – 2015. We analyze our data using ARDL estimator. Our results were important for finance-growth literature and policymakers. Market-based financial structure distinguishes itself with a stronger effect on economic growth and growth volatility. These results agreed with the recent literature on the subject and had a huge implication for financial sector development in developing countries. We discussed these implications and suggested policy reforms for economic growth ambitions coming from the heels of financial development. In our chapter five, we examine a unique and interesting aspect of financial sector development and how it solves funding problems for the small and medium scale enterprises (SMEs). Our focus in this chapter is the increase in the physical structure of the financial sector unlike the functional - the depth, efficiency, and access which we considered in the previous chapters. We examine how the creation of the second-tier stock exchanges help SMEs to access funding when extant research believe that stock exchange services are spatial proximity bias. We use Logistic regression to analyze data from Nigeria and found evidence confirming the stock exchange spatial-proximity bias. We confirm the apparent discrimination of stock exchanges in the allocation of funds to firms located far away from the exchanges. We discuss the implication of this result including the skewness in development among regions, resources allocation efficiency and policy miscarriage in the existing practice. We recommend reforms to correct the situation.