The most established connection between finance and growth could be traced to the work of Schumpeter (1912) where he contended that investors require credit in order to enhance investment. As such, banks and capital markets are to serve as agents to facilitate the financial intermediation of mobilizing saving for investment.
The finance-led growth theory developed by Levine and Zervos (1998), postulates the
“supply-leading” relationship between financial and economic developments. It is argued that the existence of financial sector, as well-functioning financial intermediations in channeling the limited resources from surplus units to deficit units, would provide efficient allocation of resources, thereby leading the other economic sectors in their growth process.
The government-led model is adapted to the Supply-Leading theory, which holds that in the formation process of the financial industry cluster, the state or local government would launch a space layout according to the economic development strategy, and in accordance with the relevant standards to evaluate the economic and financial situation of the city, and then select a city with sound financial foundation and development potential for the financial industry cluster (Solarin & Jauhari, 2011).
The theory holds that with the development of the financial industry, savings will increase and will be transformed into investment through the various financial institutions, which improves the efficient allocation of funds and greatly promotes manufacturing sector performance and economic growth through the multiplier effect. While giving quite loose and flexible industrial policy to support and guide the location of financial institutions and the direction of financial capital investment, to drive the rapid development of the financial markets and form the financial industry cluster (Patrick, 1966). The process of the government-led financial industry cluster is a
successful case formed by the government-led model. The industry cluster is mostly generated in the emerging industrial countries after the World War II. The main reason is that the trend of the global economy integration becomes more evident after the World War II, and the industrial gradient shifted in the global scope, and the financial capital flowed around the world.
Compared to the developed capitalist countries such as the UK, USA, etc, the emerging industrial countries are still in the rising phase, and their financial system are not yet complete and lack the competitive strength. If they had kept applying the Demand-Following theory to gradually develop the financial industry, it would be hard to achieve the expected development within a short time. Therefore, these countries or regions need to rely on the state or local government‟s artificially design policy support, which can accelerate the development of the modernization and internationalization of the financial industry.
In the formation and development process of the government-led financial industry cluster, the role of government is active and positive. Through a series of policies to drive the development of the national economy and the financial sector, development strategies are carried out. Indeed, a number of studies have argued that the development of financial sector has significantly promoted economic development (Schumpeter, 1912; Levine, 1997). The theory implies that a well deepened financial system would produce enhanced manufacturing firms performance. The end result would be a consistent economic growth and development.
This study is anchored on theFinance Lead-Growth theory. There are documented evidence (Khan & Senhadji, 2000; Adjasi & Biekpe, 2005) to suggest that Levine and Zervos (1998) finance-growth linkage model has been adjudged as one of the most efficient basic models to investigate macroeconomic issues, especially macroeconomic issues with financial system component. The model is depicted as follows:
LogYit =
α
1 +α
2CMTit +α
3Xit +e
it ……… (2.1)Where:
Yit is economic growth measured as the log of: (GDPCt/GDPCt−1) in country i and at time t. As observed, the proxy for economic growth is averaged for a test of robustness in the growth model.
CMTitis the capital market indicators for country i at time t;
Xitcontains control variables and eit is the error term.
The major explanatory variables in this model are capital market based and given that the study focuses on investigating the effect of financial deepening (FDNG); which is decomposed into; money based, capital market and banking sectors indicators, on manufacturing firm performance (MFPD), there is the need to reconstruct the Levine and Zervos (1998) model. In doing this, the study used King and Levine (1993) model.
King and Levine (1993) studied 77 countries over the period from 1960-1989 to examine capital accumulation and productivity growth channels. They analyzed whether the level of financial development predicts long-run economic growth, capital accumulation, and productivity growth. In their study, they assess the strength of the empirical relationship between each of three indicators of the level of financial development average over the 1960-1989 period, and three growth indicators also average over the 1960-1989 period
Their model is depicted as follows:
G(j) = α + βF(i) + yX + Ɛ……….. (2.2)
From equation 2.2, the growth indicators are; 1. the average rate of real per capita GDP growth, 2.The average rate of growth in the capital stock per person, and 3. Total productivity growth, which is a “solow residual” defined as real per capita GDP growth minus (0.3) times the growth rate of the capital stock per person. In other words, if F(i) represents the value of the ith indicator of financial development average over the period 1960-1989, G(j) represents the value of the jth growth indicator (per capita GDP growth, per capita stock growth, or productivity growth)
average over the period 1960-1989 and X represents a matrix of conditioning information to control for other factors associated with economic growth (ie. income per capita, education , political stability, indicators of exchange rate, trade, fiscal, and monetary policy), then they estimated the following regression on a cross section of 77 conditions.
The major draw-back of this model is the use of only bank based indicators as the core variables for financial development. However, using the money based indicator as a core explanatory variable against its use as a control variable in King and Levine (1993) and the merging of the resulting equation with Levine and Zervos (1998) models, serves the purpose of this study.
The reconstructed basic model adopts Total Productivity which is one of the three explained variables in King and Levine (1993) model, and importing the capital market variable (CMT) from Levine and Zervos (1998) model into King and Levine (1993) model, the new model is as depicted in equation 2.3.
G(j) = α0 + α1CMTit + α2 F(i) + yX + µ ……… (2.3)
This modelis restructured based on the theory of financial liberalization, pioneered by McKinnon (1973) and Shaw (1973), which advocatesthat free markets should be the basis for determining credit allocation and that the markets should be liberalized completely. As a result, there will be an increase in the efficiency of savings and investments and the overall real credit supply to the manufacturing sector and to the economy in general, will increase.
Therefore, an increase in credit to the manufacturing sub-sector by financial institutions provides investible funds needed for investment. This in turn will leads to an increase in the performance of the sector.
Based on this theoretical postulation, this study hereby specify manufacturing sector performance indicators as linear function of financial deepening variables and some controlled
variables adopted from King and Levine (1993) model and others that are expected to affect manufacturing sector performance. Therefore, we substitute manufacturing firm‟s performance indicators for total productivity while retaining the money, capital market and banking sector components in deepened forms, the new model is as presented in equation 2.4.
MFPFit = α1 + α2CMTdit + α3F(i) + MBIit +α4Xdit + eit……….(2.4)
From equation 2.4, MFPFitrepresent manufacturing Sector Performance, indicators of;
average capacity utilization, contribution of manufacturing sector to Gross Domestic Product (GDP) and average capacity utilization of manufacturing sector. CMTitis the capital market deepening indicator, proxy by the ratio of market capitalization of manufacturing firms to GDP.
F(i) is the banking sector deepening indicator proxy by the ratio of credit to the private sector to GDP and MBIit, is the money based deepening indicator represented by broad money supply as a ratio of GDP. Also, Xitcontains the control variables while eitis the error term. Control variables are used to accommodate other variables that are likely to affect the outcome of the estimation aside the identified core variables.