An Empirical Re-assessment of the Finance-Growth Nexus

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An Empirical Re-assessment of the Finance-Growth Nexus

Jury

Promoteur : Lionel Artige

Lecteurs :

Joseph Tharakan Philippe Lejeune

Mémoire présenté par Karin HOBELSBERGER

En vue de l’obtention du diplôme de Master en Sciences Économiques (60 ECTS)

Année académique 2019/2020

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Declaration

I, Karin Hobelsberger, hereby declare that the work presented in this Master’s degree thesis is my own original work. Where information has been derived from other sources, I confirm that this has

been clearly and fully identified and acknowledged. No part of this dissertation contains material previously submitted to the examiners of this or any other university, or any material previously

submitted for any other assessment.

Name: Karin Hobelsberger Date: October 18, 2019

Acknowledgements

I would like to thank my supervisor, Professor Lionel Artige, for his helpful guidance and patience throughout this research process. Furthermore, I would like to thank my family and significant other

for the continuous moral support.

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Executive Summary

This paper deals with the potential positive effect of financial development on economic growth, also known as the Finance-Growth Nexus. Much uncertainty and contradiction surround the subject matter.

Based on the uncertain problem set at hand, the purpose of this study is to reduce ambiguity and provide a basis for future, more detailed research. The paper aims to add value by further refining the theoretical definition of financial development, as well as further developing empirical measurement. Furthermore, a large set of financial development variables and different estimation techniques are systematically tested against a harmonized data set, in order to increase the neutrality and comparability of results. However, results of various regression iterations were neither stable, nor always fully comparable due to changes in sample composition. Ergo, the high degree of uncertainty remains, and the author cannot reject the Null Hypothesis that there is no stable correlation between financial development and economic growth. There are many different potential explanations, but all lead to the same conclusion. Perhaps the mechanisms, interrelations and potential effects of financial development on economic growth cannot be measured from a macro perspective. Instead, focusing on a micro approach in future research could potentially add value.

Keywords: financial development, Financial Development Index, Finance-Growth Nexus, economic growth, Principal Component Analysis, growth empirics, Pooled Mean Group Estimation, Generalized Method of Moments Estimation

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List of Figures

Figure 1. Definition of Financial System and Financial Development ... 12

Figure 2. Financial Development Index ... 18

Figure 3. Evolution of composite Financial Development Index over Time by Income Group ... 28

Figure 4. Composition of composite Financial Development Index ... 65

Figure 5. Principal Component Analysis: Weights for composite Financial Development Index and Sub-Indices 77 Figure 6. Scree Plots of Eigenvalues after PCA for composite Financial Development Index and Sub-Indices including 95 Percent Confidence Interval ... 79

Figure 7. Time-Series Evolution of GDP per Capita and composite Financial Development Index for distinct Income Groups ... 83

Figure 8. Evolution of composite Financial Development Index over Time by Income Group ... 84

Figure 9. Evolution of Financial Institutions over Time (Average for all Income Groups) ... 84

Figure 10. Evolution of Credit Instruments/Markets over Time (Average for Income Groups) ... 85

Figure 11. Evolution of composite Financial Development Index, Size Sub-Index, Liquidity Sub-Index and Information and Transaction Cost Sub-Index over Time (Average for Income Groups) ... 86

Figure 12. Principal Component Analysis: Weights for Country Governance Index, Financial Liberalization Index and Legal Environment Index ... 87

Figure 13. Scree plots of Eigenvalues after PCA for Indices created for Interaction Purposes with the composite Financial Development Index including 95 Percent Confidence Interval ... 87

Figure 14. Components covered by the Financial Development Index designed by Sahay et al. (2015) ... 89

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List of Tables

Table 1. Construction of Financial Development Index - Main Dimensions ... 20

Table 2. Slope Coefficients of Financial Development Proxies in Base Model ... 32

Table 3. Slope Coefficients of Financial Development Proxies – Test on Concavity ... 34

Table 4. Sign of Slope Coefficient of Financial Development Proxies across Specifications ... 36

Table 5. Sign of Slope Coefficient of Interaction Terms across Specifications ... 37

Table 6. Slope Coefficients of Financial Development Proxies in PMG Estimation ... 45

Table 7. Data Sources underlying this Paper ... 55

Table 8. Definitions and Sources of Variables used in Regression Analysis ... 56

Table 9. Country Coverage by Region ... 61

Table 10. Country Coverage by Income Group ... 63

Table 11. List of Variables entering PCA for Construction of composite Financial Development Index ... 66

Table 12. Correlation Matrix of Variables underlying the composite Financial Development Index ... 67

Table 13. The Eigenvalue, Proportion explained, and Eigenvectors for the first Principal Component, and the KMO-Measure of the composite Financial Development Index ... 70

Table 14. The Eigenvalue, Proportion explained for the first Principal Component, and the KMO-Measure of all Financial Development Sub-Indices ... 70

Table 15. Bivariate Contemporaneous Correlations of composite Financial Development Index and Sub-Indices and Economic Growth. Annual Dataset. ... 71

Table 16. Bivariate Contemporaneous Correlations of composite Financial Development Index and Sub-Indices and Economic Growth. Five-Year Panel Dataset. ... 72

Table 17. Bivariate Lagged Correlations of composite Financial Development Index and Sub-Indices and Economic Growth. Five-Year Panel Dataset. ... 73

Table 18. Bivariate Correlations of Lagged Control Variables with Average Economic Growth. Five-Year Panel Dataset. ... 74

Table 19. Bivariate Contemporaneous Correlations of Main Regression Variables. Annual Panel Dataset. ... 74

Table 20. Summary Statistics 5-Year Interval Panel Dataset ... 75

Table 21. Summary Statistics Annual Panel Dataset ... 76

Table 22. Summary Statistics of composite Financial Development Index and Sub-Indices (Annual Data) ... 81

Table 23. Bivariate Contemporaneous Correlations of the composite Financial Development Index and Sub- indices with Real GDP per Capita for different Groups of Countries. Annual Panel Dataset. ... 82

Table 24. Sample of Countries – Comparison of GMM Estimation and PMG Estimation ... 90

Table 25. Process of choosing a Base Model - Intermediary Results (Part 1/3) ... 91

Table 28. Results of Base Regression Model (Part 1/2) ... 94

Table 29. Results of Base Regression Model (Part 2/2) ... 95

Table 30. Details on Concepts behind and specific Variables used for Interaction Terms ... 96

Table 31. Slope Coefficients and P-Values for Interaction Terms with Financial Development Proxies ... 97

Table 32. Overview on Sign of Slope Coefficient for Interaction Variable, if the Interaction Variable is statistically significant by itself ... 99

Table 33. Sub-Samples regarding Income Group ... 100

Table 34. Sub-Samples regarding OECD Membership ... 101

Table 35. Sub-Samples regarding Time-Series ... 102

Table 36. GMM Estimation based on 10-Year Intervals ... 103

Table 37. Results of Pooled Mean Group Estimation (Part 1/3) ... 104

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1 Introduction

The history of financial markets is characterized by numerous failures and crises, which shook economies to their core repeatedly. Often, such disruptions were preceded by some kind of financial innovation and a subsequent above-average expansion of the financial sector in relation to the so-called real economy. The latest incident on a global scale, the Great Financial Crisis of 2008/09, fiercely re-ignited the debate of whether or not ('too much') finance might do more harm than good. The risks and downsides seem obvious, and yet, the financial sector prevails. This begs the question as to what are the benefits and opportunities of financial development (if any), and under which circumstances do they outweigh the risks and cost.

In this context, a particular stream of research has evolved, looking specifically into this research question. This stream, referred to as the Finance-Growth Nexus, has produced a host of arguments in favor of financial development causing economic growth. The main theoretical argument is that more developed financial systems encourage the mobilization of savings and lead to a more efficient allocation of capital and risks in an economy with positive effects on the rate of capital accumulation. The argument goes as far as to posit that financial innovation and development may enable technological innovation in the real economy.

Critical voices, however, point out that many of these arguments cannot be measured empirically and are thus non-falsifiable. Moreover, even for those arguments, where empirical evidence exists, the robustness of findings is questioned.

At this stage, the research on this subject matter is still sparse, and far from having established a generally accepted consensus. Even the definition of financial development remains elusive. Based on the uncertain problem set at hand, the purpose of this study is to reduce ambiguity and provide a basis for future, more detailed research. The paper aims to add value by further refining the theoretical definition of financial development, as well as further developing the means to capture this concept for empirical measurement. Furthermore, a large set of financial development variables and different estimation techniques are tested systematically against a harmonized data set, in order to increase the neutrality and comparability of results.

This study extensively reviews existing literature with regards to theoretical concepts and propositions, definitions of financial development and related terms, as well as the variables used in empirical measurement. As there is still much uncertainty and contradiction surrounding the topic, causal research is unfeasible at this stage. Thus, the research focus will be descriptive in nature instead. The research proposal is to test, whether a stable correlation exists between financial development and economic growth. First, several indices are constructed via Principal Component Analysis to reflect the concept of financial development. The indices are the result of an extensive theoretical analysis of the definition and potential components of financial development. As such, the indices incorporate new components of financial development, which have not been investigated in previous literature. Specifically, the dimension of competition, international interconnectedness, and the degree, to which information asymmetries and transaction cost are combatted within a country’s financial system, are added. The indices are then embedded into two cross-country, cross-time regression estimations: a two-step system Generalized Method of Moments estimator and a Pooled Mean Group estimator, respectively.

The secondary data used as a basis for the analysis is obtained from reliable sources (mainly the World Bank), and carefully formatted, edited and coded. Generally, data coverage, especially of financial development variables, seems to be highly correlated with the level of development of an economy, leading

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2 to a non-random sample selection based on the focus variable¹. The final dataset underlying this study covers the period from 1990 to 2018 for 141 global countries.

Surprisingly, this study cannot find stable, statistically significant evidence for the conclusions drawn in past literature and can thus not reject the Null Hypothesis. Not only are correlations not stable in their statistical significance, they are sometimes even negative for some of the proxies for financial development.

This finding holds true despite controlling for systemic banking crises separately. This is the case for both the focus variable, in explicit, the composite Financial Development Index (and the sub-index 'Size' in particular), as well as the traditional proxies for financial development from the literature (Liquid Liabilities and Private Credit). Moreover, the statistical significance depends highly on the interaction terms, time periods and countries included, as well as on the method of data averaging (used to extract the trend relationship). Hence, correlations repeatedly failed robustness tests. However, it might be noteworthy, that while statistical significance varied widely across different specifications, most financial development proxies are stable in the algebraic sign of their correlation with economic growth, even though some of them show opposing correlations.

There could be several explanations for the contrasting findings to the literature. For instance, other researchers may have had access to non-publicly available data. Furthermore, there could have been differences in the data editing policies. Moreover, the time-series and countries underlying this paper differ from past papers. Nonetheless, if findings depend so heavily on these mentioned aspects, the robustness of empirical evidence on the Finance-Growth Nexus should be questioned. On top of that, empirical evidence in this study seems to depend severely on the selection of countries included in the sample. Hence, pooling very different economies into an estimation technique that forces homogeneity on the cross-country slope coefficients of financial development, as is standard in the Finance-Growth Nexus, might not be appropriate.

The most stable correlation of financial development with economic growth is found for two sub- indices of the composite Financial Development Index. The Liquidity Sub-Index and the Information and Transaction Cost Sub-Index are highly statistically significant and positively related to economic growth.

These sub-indices are based on several financial development variables, which have not been used in previous research. The correlation is stable across both the system Generalized Method of Moments estimator and the Pooled Mean Group estimator, as well as most interaction terms and robustness tests.

However, again, some robustness tests are failed. This would indicate that more liquid and efficient financial markets are positively linked to economic growth. Nonetheless, even this (more robust) evidence does not justify drawing conclusions beyond mere correlation, in favor of a causal effect from financial development to economic growth. This is especially the case, since the financial development proxies are highly auto- correlated and lags could thus capture a contemporaneous correlation, potentially reflecting reverse causality from economic growth to financial development.

There are many different potential explanations for why the high degree of uncertainty remains.

Nonetheless, in the end, they all lead to the same conclusion. Perhaps the mechanisms, interrelations and potential effects of financial development on economic growth cannot be measured from a macro perspective. Instead, focusing on a micro-approach in future research could potentially add value. A bottom- up research approach would allow for a much more targeted and tailored data set. For instance, this could include data on source and type of financing at different stages of development or size of the firm.

The outline of the paper is as follows. Chapter 2 gives an overview over previous findings of the literature. Chapter 3 specifies the problem definition. Chapter 4 elaborates on the research design and

1 A non-random sample selection based on an independent variable, however, still leads to unbiased and consistent estimations (Jeffrey Wooldridge, 2015).

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3 empirical framework applied. Chapter 5 outlines the sample design, the process of data collection and processing, and describes the data. Chapter 6 discusses the results of the Principal Component Analysis and some descriptive statistics on the composite Financial Development Index and its sub-indices. Thereafter, chapter 6 analyses empirical findings based on the applied estimation techniques, as well as some robustness tests. Chapter 7 draws conclusions.

2 Literature Review

Over time, there has been far from a consensus on the existence of a finance-growth causality. For instance, there have been differences of opinion with regards to the direction of potential causality. While some economists argue that finance causes economic growth, other economists take the opposing view that a growing economy will cause the financial sector to match its growth. And then there are those researchers that believe in a reciprocal causality between these two forces, in explicit, that they are mutually reinforcing.

For those that do believe that finance has an impact on economic growth, there are differing opinions on the potential effects. One view is that finance contributes positively to economic growth (also known as the Finance-Growth Nexus). The other view is that finance creates instability with negative implications on economic growth (mainly known as financial crisis literature). A third fraction believes the effect might vary over time (that is short-term versus long-term effect) or level of financial development (in explicit, a concavity of the Finance-Growth Nexus). Another point of note is that many of the arguments that have been brought forth over time, can either not be tested empirically (in explicit, they are non-falsifiable), or were based on econometric models that have since been replaced for this type of research question.² Finally, one cannot disregard the suspicion that the respective views of a particular period, as well as the evolving definition of finance, have been heavily influenced by the respective socio-economic zeitgeist of that time.

History

At the beginning of the 20th century, some economists developed the first notions that the financial sector may play an important role in an industrialized, capitalist economy. While Karl Marx defined capital as a resource (Marx, 1872), Walter Bagehot (1873) and Joseph Schumpeter (1912) saw finance together with entrepreneurship as central pillars to the economy. According to Schumpeter’s view, “[t]he banker […]

is not so much primarily a middleman, [...]. He authorizes people, in the name of society as it were, [...] [to innovate]” (Schumpeter, 1912, p.71). This points to the function of the financial system to provide promising entrepreneurs with the necessary capital in order to fuel technological progress and thereby economic growth.

Following the Great Depression, heavy and restrictive regulation on banking and the general financial sector, led to a relatively long and stable period with few financial crises until the 1970s (John Komlos, 2019). Research on the potential beneficial effects of finance on growth was sparsely existent at first. However, it appears as though this era of stability slowly led to a gradual change in mindset with regards to a potential positive finance-growth relationship. John Hicks (1969) posited that economic growth during the English Industrial Revolution was not sparked by technological innovation, but an improvement in capital market liquidity.³ In 1969, Raymond Goldsmith was the first researcher to document empirical evidence on

2 Until the end of the 1990s, literature on the Finance-Growth Nexus was mainly based on country cross-sections and estimation techniques that were not fit to deal with potential endogeneity coming from reverse causality.

3 Specifically, Hicks argues that many of the technological innovations that were spread during the Industrial Revolution had been invented decades before and that the improvement in capital market liquidity was the ultimate catalysator for the British Industrial Revolution.

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4 a correlation between finance and growth. Goldsmith, however, hesitated to draw conclusions regarding causality. By the 1970s, Ronald McKinnon (1973) and Edward Shaw (1973) argued that more developed financial systems may enhance growth by stimulating the saving rate.

When Robert King and Ross Levine published an influential study in 1993, they appear to have ignited academic curiosity on the subject. Acknowledging a potential reverse causality from growth to finance, as well as the econometric issue of endogeneity that might come with it, they investigate the impact of initial financial development on long-run economic growth for the following 10 to 30 years. They find evidence in favor of both a contemporaneous correlation of the variables, as well as the notion that finance acts as a predictor of growth in the following 10 to 30 years (King and Levine, 1993a). As a result, many researchers, which focused on a potential Finance-Growth Nexus, compared or contrasted their findings to those of King and Levine during the 1990s and early 2000s.

King and Levine’s basic ideas concur with those of Schumpeter. In 1993, they developed a model based on endogenous growth theory (King and Levine, 1993b). In this model, the role of the financial sector is to evaluate future entrepreneurs and to mobilize and pool savings in order to finance the most deserving ones. Moreover, financial services provide risk diversification for the risk linked to financing these innovative firms. The growth-enhancing mechanism from finance to growth thereby materializes two-fold, on the one hand, by increasing the investment rate to physical capital, and on the other hand, by actively enhancing productivity growth. In contrast to the traditional literature, King and Levine even identify the latter transmission channel as the main one.⁴

King and Levine (2001) and Jian-Zhou Teng and Qi Liang (2010) further argue that more developed financial systems may enhance growth by stimulating the saving rate, encouraging investment, accumulating expertise on efficient capital allocation, discouraging premature liquidations of investments, decreasing the cost of external finance, and enhancing technological progress.

Causality

The notion of the financial system having any causal impact on economic growth has continuously been drawn into question over time. Beginning in the 1950s, Joan Robinson (1952, p. 86), an often-quoted doubter of the finance-growth causality, stated that “[w]here enterprise leads, finance follows”. She thus expressed her view of a reversed Say’s theorem (in explicit, that demand creates its own supply). Robert Lucas (1988, p.33) simply considered the role of finance for growth as “badly over-stressed”. Merton Miller (2005) on the other hand claimed that “financial markets contribute to economic growth in a proportion that is almost too obvious for serious discussion”. Panicos Demetriades and Khaled Hussein (1996) employ time-series evidence for estimating the existence and the direction of a causal relationship between finance and growth individually for 16 developing countries. They find that the existence and direction of causality depends highly on the individual country specificities. They thus conclude that “[t]here can be no ‘wholesale’

acceptance of the view that ‘finance leads growth’ as there can be no ‘wholesale’ acceptance of the view that ‘finance follows growth’” (Demetriades and Hussein (1996, p.407)). Raghuram Rajan and Luigi Zingales (2001, p.469) raised another issue with the interpretation of a finance-growth causality, positing that [f]inancial development […] may predict economic growth simply because financial markets anticipate future growth. Concurrently, Mark Manning (2003, p.2) questioned conclusions regarding a positive finance-

4 Levine (1997, p.691) later added that, according to his view, the financial system has the following five functions: “[1.] facilitate the trading, hedging, diversifying, and pooling of risk, [2.] allocate resources, [3.] monitor managers and exert corporate control, [4.]

mobilize savings, and [5.] facilitate the exchange of goods and services”. Levine further claims that a well-functioning financial system can also be characterized by how well it manages to ease its market failures – information and transaction cost.

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5 growth causality by arguing that “a large stock market may simply reflect a greater wealth of investment opportunities requiring external finance”.

Some argue that the relationship may change over time, depending on the level of economic and social development. Studying under-developed countries, Hugh Patrick (1966) found evidence for a supply- driven causality from finance to growth in early stages of economic development, and for a demand-driven relationship at later developmental stages. This might imply that the direction of causality might vary over the course of the economic development of a country. An explanation delivered by Manning (2003, p.8) might provide an answer to this observation. He interprets the fact that often no empirical evidence is found for a finance-on-growth effect for developed countries as financial development “supporting the convergence process”.

This, however, does not explain the relationship of finance and growth at a time, where no modern, advanced economies, to whom other economies could converge, existed. Based on historical evidence, Valerie Bencivenga, Bruce Smith and Ross Starr (1995) argued that the financial revolution preceded the industrial one. Historical evidence from Niall Ferguson (2008) also suggests that, while iron and textile production - the primary industries of the English Industrial Revolution - did not depend considerably on bank financing, banks did play a material role for the industrialization in continental Europe. Richard Sylla (2006), on the other, hand makes an argument for initial financial development having emerged in nations exogenously, arising out of the need of governments to finance wars. According to Sylla, the associated credible commitment by governments to respect property rights and service the war debt encouraged bank and capital market development. Thus, from Sylla’s point of view, the beginnings of a financial system were (often) due to political reasons, not economic demand, but did result in economic growth subsequently. No overall conclusion can be drawn, however, as research covering this time period is subject to data limitations.

Whichever may have arrived first, finance or industry, the general research community engaged in the Finance-Growth Nexus seems to have settled on at least the notion of a mutually reinforcing effect of the development of a financial system and the growth of an economy in modern times. Researchers indeed acknowledge the existence of causality from growth to financial development but limit their research to investigating whether there also exists a causality from finance to growth (for instance, King and Levine, 1993b, Levine, 1998, Sahay et al., 2015⁵). Dong-Hyeon Kim and Shu-Chin Lin (2013, p.4385) also argue in favor of a two-way causality, by saying that “[f]inancial intermediaries and markets may arise to ameliorate information and transaction cost, thereby improving the efficient resource allocation and hence long-run economic growth. In turn, economic growth stimulates demand for financial services, leading therefore to increased competition and efficiency in financial intermediaries and financial markets.” This kind of view allows researchers to attempt to measure the potential beneficial effects of finance on growth. A reciprocal causality, however, also makes empirical research excessively challenging.

FinancialDevelopment

At the beginning of the 21st century, much research focused on the different effects that might arise from distinct kinds of financing. Traditionally, the literature on the Finance-Growth Nexus distinguishes between bank intermediation and financial market activity, investigating their impact on growth separately and in contrast to each other (mostly debt financing via banks loans, and equity financing via stock markets⁶).

Demirgüç-Kunt and Levine (2004), for instance, argue that banks do a better job at financing the growth of

5 The full reference is Ratna Sahay, Martin Čihák, Papa N’Diaye, Adolfo Barajas, Ran Bi, Diana Ayala, Yuan Gao, Annette Kyobe, Lam Nguyen, Christian Saborowski, Katsiaryna Svirydzenka, and Seyed Yousefi, 2015.

6 Bond market data is rarely used due to limited data availability.

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6 young firms, since they can provide a more credible long-term commitment. Markets, on the other hand, are more focused on enhancing competition and innovation. Rajan and Zingales (2001) argue that, since bank credit is more relationship-based, banks have a more intensive corporate governance effect on firms, whereas market finance can lead firms to “indulge […] far more in empire building” (Rajan and Zingales (2001, p.475)). However, they also posit that banks are less price sensitive, which could lead to a less efficient resource allocation.⁷ Given all these differences in delivering on their financial functions, it could hence be that distinct types of finance have varying effects on economic growth.

Jose Wynne (2002) reasons that adequate screening and monitoring activities, leading to an efficient allocation of capital by banks, need to be based on a solid history of information on firms. Since such ‘information capital’ is built slowly over time, as firms survive and flourish, this mechanism cannot work properly in times of financial liberalization, when a lot of new firms enter the market. According to Wynne, without the necessary information capital, banks necessarily miss-allocate capital to some degree with respect to new firms.

Even following the Great Financial Crisis, Teng and Liang (2010) and Felix Rioja and Neven Valev (2014) still reasoned that equity markets have a positive impact on productivity growth by facilitating the financing of innovative ideas. Due to the possibility of risk diversification, as well as liquidity in exiting the investment, if desired, (under normal market conditions, depending on the liquidity of the stock itself), investments into innovative ideas are encouraged. They further stress the channel of banks in reinforcing productivity growth via their tasks as creditors to monitor a firm’s management and positively influence corporate governance.

Another stream of research focuses on the different effects that might arise depending on the level of economic development of a country (for instance, high income versus low income). Jose De Gregorio and Pablo Guidotti (1995) suggest that some very developed economies may have attained a degree of financial depth that no longer improves investment efficiency.⁸ Peter Rousseau and Paul Wachtel (2011) find the finance on growth effect to be bigger in countries with an intermediate level of financial and economic development than for low or high income/financial development countries. Adolfo Barajas, Ralph Chami, and Seyed Yousefi (2013) have found that the growth-benefits of deeper financial systems are generally weaker for Low Income Countries, and the pay-off of the Finance-Growth Nexus increases continuously with the income level. Specifically, they find that the finance-on-growth effect is negative for the lowest income countries and turns positive at the 73rd percentile of income per capita for Low Income Countries in 2008.

Financial Innovation and Crisis Literature

There is also a sub-stream of research focusing specifically on financial innovation as a potential driver of growth. However, as pointed out by Josh Lerner (2006), and Frame and White (2004), very little empirical evidence exists, and the concept itself remains poorly defined. While Rajan (2005, p.1/2) is convinced of the “undoubted benefits” coming with the “revolutionary change” in the financial system in the past decades, he also points to the “potential source[s] of concern”. Paul Volker criticizes that the only useful financial innovation recently has been the ATM machine (Joseph Stiglitz, 2010). Ironically, in diametrical opposition to proponents of this theory, financial innovation is seen by others as the initial cause of instability and financial crisis (see Minsky-Kindleberger Model, 2002).

7 Rajan and Zingeles (2001) argue, that banks are more vulnerable to price distortions, since they, in contrast to financial markets, are not subject to a self-correcting price mechanism.

8 While this reasoning explains the disappearance of a positive finance on growth effect with increasing levels of national income and financial depth, it does not explain the negative finance on growth effect that has been found beyond a certain threshold of financial development (see Sahay et al., 2015, Arcand et al., 2012).

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7 Economists are, of course, also well aware of the risks a financial system can pose to the real economy. Just as there is research, arguing in favor of finance as a growth determinant, there is equally a host of research supporting the argument that the aggregate effect of financial development is negative due to financial instability and crisis.⁹

Concavity – A Trade-off between Growth and Instability

Norman Loayza and Romain Rancière (2004) point to the clash of these two streams of literature:

On the one hand, the empirical growth literature documents a positive impact of finance on growth. On the other hand, the banking and currency crisis literature finds that monetary aggregates, such as Private Credit, function as predictors for financial crises and their resulting recessions. Studying the short- and long-term relationship of finance and growth, Loayza and Rancière find a statistically significant, negative relationship in the short-run and a positive relation for the long-run, which could explain the contrasting findings of both streams of literature.

Rousseau and Wachtel (2011) find evidence for the disappearance of the Finance-Growth Nexus from 1990 to 2004, compared to 1960 -1989, for both a subsample of developed and developing countries.

They hypothesize that this could be explained by an application of the Lucas’ (1975) critique - that financial liberalization in the 1980s and 1990s, by trying to reap the benefits of the Finance-Growth-Nexus, might have changed the basic underlying relationship between both variables. This could be the case, since the financial system did not expand endogenously, but was sparked exogenously by liberalization policies, giving no time to financial institutions, and the legal and regulatory environment to develop accordingly. This, in turn, could also make such financial systems more prone to excessive growth and potential financial crises.

Further investigation by Rousseau and Wachtel indeed reveals a negative connection of financial development with financial crises in this later period. While they find evidence for a positive finance on growth effect using different methodologies, this effect is often reduced to (near) zero in times of financial crises (when separately controlling for the incidence of financial crises).¹⁰ Rousseau and Wachtel interpret this, in that too fast or excessive growth in financial depth, might weaken the financial system and make it more vulnerable to financial crises with their adverse effects on growth. As such, deep financial systems might increase the frequency of booms and busts, as has been documented in many advanced economies since their financial liberalization in the 1970s/80s.

Several explanations have been brought forward as to why there could be negative social consequences beyond a certain depth of the financial system. The first explanation has been fueled by the recent financial crisis, which both originated in and mostly occurred in developed economies. It points to the fact that there might be a trade-off between the growth enhancing effect of a deep financial system and the instability that might come with it. Sahay et al. (2015, p.5), claim that “[when] it proceeds too fast, deepening financial institutions can lead to economic and financial instability. It encourages greater risk-

9 Kindleberger (2002) offers a comprehensive review of how instability in financial markets can have a negative effect on the real economy. As markets become unstable and banks are losing money, the first intermediaries start becoming illiquid and then insolvent, as assets no longer match liabilities. Beyond a certain threshold of defaults, the populous loses faith in the financial system and triggers bank runs. In a feedback loop this leads to more defaults and an increasing panic. As more and more banks default, and credit and liquidity are withdrawn from the economy, the average cost of capital rises. Firms in need of financing or re-financing cannot service debt at these new levels and are themselves forced into bankruptcy.

10 Arcand et al. (2012), however, show that the disappearance of a finance on growth effect in recent years as found by Rousseau and Wachtel (2008) is consistent with a downward bias resulting from model mis-specification. They show that the finance-growth relationship is indeed concave and that previous models by typically using the logarithmized value of financial depth, thus allowing for a non-linear but not a non-monotonic relationship, result in a downward bias for financial development slope coefficients. This downward bias increases as the level of financial development increases over time, eventually growing big enough to lead to finding a near to zero and statistically insignificant finance on growth effect in recent years.

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8 taking and high leverage, if poorly regulated and supervised. In other words, when it comes to financial deepening, there are speed limits.”

Concavity (beyond Financial Crises)

Rioja and Valev (2004) were the first ones to investigate (and find empirical evidence for) the concavity of the finance-growth relationship. Augusto De la Torre, Erik Feyen, and Alain Ize (2011) hypothesize that the negative effect of ‘too much finance’ might be due to positive, but decreasing returns to scale of financial development, where after some threshold the positive return might be smaller than the cost of the resulting financial instability. Jean-Louis Arcand, Enrico Berkes, and Ugo Panizza (2012), however, find a concave relationship of finance and growth even after controlling for crisis periods, so that further explanations of the negative finance on growth effect are needed.

In this context, Martin Wolf (2009) mentions that the US financial system has increased six times more quickly than nominal GDP in the previous three decades, which leads him to the interpretation that the US financial system has come from “instead of being a servant, […] [to being] the economy’s master”.

Other researchers have argued, that growing financial sectors, with the resulting high pay to employees, diverts talent away from productive, real sectors, thereby potentially negatively influencing economic growth (Era Dabla-Norris, Si Guo, Vikram Haksar, Minsuk Kim, Kalpana Kochhar, Kevin Wiseman, and Aleksandra Zdzienicka, 2015, and James Tobin, 1984).¹¹ Another hypothesis is that a large financial sector might be especially vulnerable to moral hazard issues, which might lead to rent extraction from other sectors, ultimately resulting in a mis-allocation of resources (Sahay et al., 2015) – thus negatively affecting the primary function of the financial system.

Relativism

While many studies have found controversial evidence for an existence of a causality from finance to growth until the beginning of the 21st century, later researchers seem to rather take the finance-growth causality as given. Beginning with the 2010s, there also appears to be an acceptance of the potentially different effects, which the level of financial development or the composition of banking and stock markets in a particular country may have, depending on the level of economic development of a country. Also, the divergence between short- and long-term effects, as well as the trade-off between growth enhancing benefits and financial instability of financial development are taken into consideration. Accordingly, more nuanced research focuses on more differentiated effects based on circumstance. Kim and Lin (2013), for instance, find that banking matters more for low-income countries, and stock markets more for high-income or low inflation countries. Rioja and Valev (2014) study the impact of stock markets and banking on economic growth and its sources, physical capital accumulation and productivity growth. While they find both to be conducive to overall economic growth, they identify banks as the primary factor for enhancing capital accumulation and equity markets for productivity growth. Looking into the impact of both for high- and low- income countries, their results reveal that, in high-income countries, stock markets have a favorable effect on both capital accumulation and productivity growth¹², whereas banks seem to only influence capital accumulation. For low-income countries, in contrast, equity markets seem to not have any effect on neither source of growth, whereas banks are an important source of capital accumulation.

11 Tobin (1984) stated that "we are throwing more and more of our resources, including the cream of our youth, into financial activities remote from the production of goods and services, into activities that generate high private rewards disproportionate to their social productivity" (Arcand et al., 2012, p.3).

12 The researchers acknowledge that stock markets in low-income countries might not yet be sufficiently developed in order to find a statistically significant effect.

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9 Levine (2004, p.3) provides the closest semblance of a professional consensus by admitting that

"We are far from definite answers to the question: Does finance cause growth, and if it does, how?". At the same time, one cannot help but notice that research on the subject matter has become sparser in the last decade. Similar to the aftermath of the Great Depression, the topic seems to have lost somewhat of its popularity, at least for now.

3 Problem Definition

The following chapter discusses the problem definition. It deals with the framing of the problem set, formulates research objectives and delimitations. Then, it outlines the theoretical foundations and definitions underlying this study. Finally, it elaborates on the unit of analysis and specific research questions.

3.1 Framing

The main theoretical argument in favor of financial development is that more developed financial systems encourage the mobilization of savings and lead to a more efficient allocation of capital and risks in an economy with positive effects on the rate of capital accumulation. Arguments go as far as to posit that financial innovation and development may enable technological innovation in the real economy. Later research points to a more relativistic school of thought, where the potential beneficial effects depend on the particular circumstances of a country.

Based on the literature review, however, one can conclude that there is still much uncertainty surrounding the subject matter. To begin with, there are several overlapping streams of research related to a finance-growth relationship, such as general growth theory, Finance-Growth Nexus, financial crisis literature, and financial innovation literature. These streams not only seem unharmonized, but sometimes even appear to contradict each other. Moreover, terms such as finance, financial development, or financial innovation, as well as their functions, are inadequately defined and rarely reflect the full picture.

Furthermore, theories have rarely been integrated into the respective overarching economic growth theories of their times.

Perhaps more disconcerting is the fact that many propositions and notions cannot be measured empirically (in explicit, they are non-falsifiable) and are often implicitly assumed as given. One example of an empirically immeasurable concept is forgone profits due to not providing financing to a potentially successful economic agent (that is, the opportunity cost of capital). This type of information would, however, be necessary to measure the full effectiveness and value-added that a given financial system may be contributing to economic growth. Also, as mentioned above, the potentially crucial concept of financial innovation (set in the context of the importance of innovation for economic growth in general) remains elusive and immeasurable.

Also, past research does not account for potential variations in corporate governance mechanisms of different transmission channels of the Finance-Growth Nexus, in explicit, financial institutions and instruments. The reader is reminded that the primary aim of a debt holder (such as loans granted by banks, and corporate bonds held by institutional investors) is, in essence, the timely repayment of the notional value plus receipt of a premium. Equity investors, on the other hand, are willing to bear more risk, and expect to be rewarded with a long-term cashflow and gains in value. These two different sets of motivation and risk/return profile will lead to very different selection patterns with regards to allocation of capital. In theory, a lender does not care about any excess profit that the economic agent may generate, as the lender is not

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10 entitled to a share in those excess profits. The lender is only concerned with excess profit to the extent that it ensures the continued solvency of the borrower (in explicit, a smaller risk of defaulting on its debt). The equity owner, however, is entitled to excess profits. Depending on their individual risk/return appetite, they accept risk of loss of capital in exchange for an expected excess return (over debt) on their investment.

Hence, equity investors will in some cases be more willing to invest into riskier or more disruptive business ideas and technologies. Silicon Valley, for instance, has a reputation for having a very mutually beneficial relationship between venture capital investors and start-up ventures (in particular, IT and bio-technology firms). This also hints at the idea that different forms of finance are not only needed at different stages of economic development of an economy, but also at different developmental stages of a firm.

Furthermore, financial instability and crisis (let alone the notion of systemic risk) are not holistically integrated into theoretical frameworks, but often simply controlled for via banking crisis dummies.

Additionally, the potential sources of endogeneity, from reverse or reciprocal causality from economic growth to financial development and omitted variables, cannot yet be econometrically excluded or isolated.

Similarly, there are issues with the proxies for financial development used in empirical measurement, such as a myopic focus on banking/Private Credit as the unit of analysis, or alternatively focusing on measures of monetization (and thus including potential effects of monetary policy). Finally, critical voices question the robustness of findings, even when empirical evidence exists. Based on all these observations, it is of little surprise that opinions and findings differ so widely.

3.2 Research Objectives

Based on the uncertain problem set at hand, the purpose of this study is to reduce ambiguity and provide a basis for future, more detailed research. The paper aims to add value by further refining the theoretical definition of financial development, as well as further developing the means to capture this concept for empirical measurement. Furthermore, a large set of financial development variables and different estimation techniques will be systematically tested against a harmonized data set, in order to increase the neutrality and comparability of results.

3.3 Delimitation

In order to properly focus on the research questions at hand, this study does not aim to provide further insights or understanding in all related aspects, and will thus not focus on:

• General economic growth theory or potential growth determinants other than financial development, as well as how they are proxied empirically;

• Integrating the concept of financial development into general economic growth theory;

• Financial inclusion, in explicit, consumer finance (for example car loans) and general access to financial services (for instance, the number of Automatic Teller Machines per capita)

• Measuring the effectiveness of monetary or fiscal policy in the context of different structures of a financial system, or giving policy recommendations with regards to an optimal structure for a financial system;

• Financial crisis anticipation or prevention;

• Improving the econometric methods available for this type of research.

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3.4 Theoretical Foundations

As mentioned before, a large part of the arguments presented in past literature remain empirically immeasurable for the time being. Given the narrow research scope of this paper, certain assumptions must be accepted as given, in order to define proper research questions. At the same time, none of the assumptions may restrict or bias the empirical level of analysis. The following string of arguments provide the theoretical foundation for the study.

The main role of the financial system is the allocation of capital in an economy as a resource. The allocation does not take place randomly, as providers of capital (in explicit, investors and creditors) carry a risk of loss of invested capital and demand to be rewarded for taking that risk. As a result, providers - and by extension financial intermediaries (in explicit, poolers of capital) - must assume a stewardship/governance role, in order to maximize the return on capital invested for risk taken. This also leads to the need to value and price the expected return and risk. Financial innovation can increase the effectiveness and efficiency of the financial system in fulfilling this role. This may occur, for instance, by generating more possibilities to allocate capital (in explicit, improving access to finance¹³), by maximizing the use of capital (such as the multiplicator effect of fractional reserve banking), or by reducing the cost of capital due to reduced transaction cost in markets and/or marginal cost within intermediaries. In reality, however, a financial system might not be able to carry out its function optimally, due to obstacles such as information and transaction cost. Moreover, the economic agents within a financial system consist of humans and are thus subject to human limitations. As such, providers and allocators of capital are boundedly rational and do not have all the information necessary to act optimally. They are subject to moral hazard and conflicts of interest.

As a result, financial intermediaries can carry out their function sub-optimally for the economic system, by extracting economic rent. Furthermore, financial innovation can result in displacement¹⁴ due to behavior of individuals, which might be rational for the individual but not for the system as a whole.

3.5 Definitions

Many different terms have been used in the finance-growth literature, when alluding to finance, such as financial system, financial sector, financial infrastructure, financial depth, financial structure, financial organization, financial innovation, and financial development. Often these terms are erroneously used interchangeably. Given the research question of the finance-growth literature, researchers usually use these terms to refer to financial intermediation towards the private sector for productive purposes. Hence, financial intermediation toward households, other financial institutions, governments or government agencies, as well as credit issued by central banks is usually excluded from the variables, they use to reflect financial development. Also, researchers refer to size, access, stability, efficiency, and so forth, when further describing the characteristics of a financial system.

For the purpose of this paper, the terms financial system and financial sector will be used interchangeably. Moreover, throughout the paper, the following definitions will apply, which are illustrated in Figure 1: The form of the financial system is comprised of financial institutions, markets, and instruments.

The structure of a financial system can vary across countries across dimensions, such as size, access, competition, and international interconnectedness. A financial system fulfills the specific function of pooling and allocating capital (and risk) with the goal of maximizing risk-adjusted return on investment ('value

13 An example would be crowd-funding opportunities for economic agents that would otherwise have a hard time accessing capital.

14 Displacement is meant as in the context of the Kindleberger-Minsky Model on Manias and Panics (2002).

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12 maximization') and it does so with a certain quality. Financial development describes the structure and quality with which the financial system performs this function. Financial innovation leads to changes in the form, structure and/or quality of the financial system and its products and services. Moreover, it cannot just improve the performance of the functions of a financial system, but even alter its functions. The Finance- Growth Nexus refers to the notion of the financial system enabling additional growth in the economy by performing its functions in a manner that fosters technological progress and increases productivity in a country.

Based on the above definition, there are multiple dimensions of the financial system (form, structure, function, quality). According to contemporary school of thought, the dimensions and their potential correlations with (or effects on) economic growth can vary significantly from country to country based on idiosyncratic circumstances and interaction with other factors such as, for instance, the level of economic development, regulatory framework, or level of institutional development.

Notes: Illustration created by the author.

According to this definition, financial development consists of two dimensions, capturing the structure and quality of financial development, respectively. The structural dimension is broken down further into four sub-dimensions:

• Size refers to the volume of financial resources available to the private sector for productive purposes. Size shall thus reflect the volume of financial markets/instruments and institutions in relation to the respective economies and intends to capture the depth of financial development.

• Access highlights the accessibility of financial resources by the private sector. It reflects the ability of firms of all sizes to acquire different means of financing for productive purposes during each phase throughout the entire lifespan (for instance, start-up financing, project-finance, supply- chain finance, and long-term equity and debt investments).

• Competition in this case refers to the degree of substitutability between different credit

instruments/markets. Ideally, the measure would also capture the degree of substitutability within financial institutions/markets (banking system, stock and bond markets).

FORM

• Institutions

• Instruments

• Markets

• Pooling Savings

• Allocating Capital and Risks FUNCTION

QUALITY

• Effectiveness

• Efficiency STRUCTURE

• Size

• Access

• Competition

• Interconnectedness

FINANCIAL SECTOR / SYSTEM

FINANCIAL DEVELOPMENT

Figure 1. Definition of Financial System and Financial Development

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• Interconnectedness describes the interrelation and interdependence within and between domestic and international financial markets. This connection could exist both between different types of financial markets, as well as across different regions. On one hand, interconnectedness can lead to better risk diversification. On the other hand, a by-product of interconnectedness is the danger of systemic risk, in explicit, the risk of an isolated event of instability having a cascading effect throughout the entire system.

The quality dimension, consists of two sub-dimensions:

• Effectiveness refers to the ability of the financial system to properly fulfill its functions, specifically, pooling and allocating capital and risk. This also entails the level of stability and consistency, with which the functions are fulfilled.

• Efficiency refers to the financial system fulfilling its functions while extracting the least economic rent. Cost efficiency includes minimizing the cost of capital (such as bid/offer trading spreads, or interest rate premiums), as well as cost incurred from information asymmetry. An efficient financial system should minimize its market failures and maximize the possibility for the industry to reap the benefits of (any potential) Finance-Growth Nexus.

3.6 Unit of Analysis and Research Questions

The unit of analysis will be the level of 'Financial Development', as defined above, of a given country.

In the following, the list of research questions will be defined. The aim is to provide guidance throughout the study and provide a solid basis for empirical testing.

Base Hypothesis

𝐻₀ = Financial development does not correlate robustly with economic growth 𝐻₁ = Financial development correlates robustly with economic growth

Potential changes in correlation of financial development with economic growth will be looked at for the following variation in circumstances:

• Different levels of financial development in a country (‘concavity’)

• During a systemic banking crisis

• Distinct levels of institutional development of a country

• Different financial regulatory and supervisory environment in a country

• Distinct economic policy environment in a country

• Different stability /health of domestic financial system

• Distinct ownership structure of domestic banking system

• Correlations at different speed levels of financial development in a country

• Short versus long-run relationship

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4. Methodology and Research Design

This chapter deals with the research design and methodology applied. It will discuss the econometric models applied and variables used.

4.1 Research and Data Type

Considering the high level of uncertainty, as determined in chapter 3, the research type will be descriptive in nature. The aim is to identify potential correlations, rather than aiming to establish the existence of a causal relationship. The latter would require a much more well-defined problem set. Due to research constraints with regards to budget and time, as well as the lack of institutional backing, the analysis will be based on secondary data. This data must be obtainable from reliable, generally accepted public sources, in order to ensure the necessary minimum standards with regards to data quality (for instance, pre- screening, editing, formatting, and coding). The downside of this approach is the limited flexibility with regards to chosen variables and completeness of data across countries and time.

4.2 Econometric Models

With regards to the econometric models that will be employed in order to conduct the analysis, this study has chosen to apply both a System Generalized Method of Moments estimator ('system GMM') and a Pooled Mean Group estimator ('PMG') to identify potential correlations. The system GMM estimator is currently the standard model in the Finance-Growth Nexus, as it mitigates potential endogeneity issues resulting from omitted variables and potential reverse/reciprocal causality from economic growth. However, this model only provides information on the long-term relationship of financial development and economic growth, as data is typically averaged over five-year intervals. Moreover, the model forces homogeneity on the slope coefficients of financial development across countries. Consequently, the study additionally employs the PMG estimator, which allows to distinguish between the short- and long-run relationship, as well as allows for cross-country heterogeneity in the short-run slope coefficients of financial development.

Applying both models should give a more detailed insight into the workings of a (potential) relationship between financial development and economic growth, as well as on the robustness of findings when allowing for a higher degree of heterogeneity between countries. Both estimation techniques will be elaborated on in detail below.

4.2.1 System Generalized Method of Moments

The author chooses to apply a system Generalized Method of Moments estimator, based on the work by Arellano and Bond (1991) and Arellano and Bover (1995), and developed by Blundell and Bond (1998). GMM estimation is chosen for two reasons. First, it still represents the standard model in the Finance-Growth Nexus.¹⁵ As such, it will be interesting to compare the findings of this study with the literature. Second, GMM, and specifically the two-step system GMM estimator based on orthogonal deviations, is a good fit to several econometric issues underlying this problem set. Most importantly, the estimator was designed for samples with “small T, large N” panels, and not strictly exogenous independent

15 It might be noteworthy, that there is, however, a recent trend toward more micro-based settings in the Finance-Growth Nexus.

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15 variables (such as financial development) and a dynamic dependent variable (where the regressand depends on its own past values). Additionally, the estimator deals with fixed effects, heteroskedasticity and autocorrelation within (but not across) individuals. Moreover, it mitigates omitted variable bias. As such, this estimator addresses several of the key econometric issues underlying the Finance-Growth Nexus. A downside of this estimator is that it involves many choices, and results will differ according to the specific estimator chosen (Roodman, 2009). It is therefore imperial make all taken choices explicit.

Specifically, the two-step system GMM estimator based on forward-orthogonal deviations is chosen. This means that instead of first-differencing, the average across of all future (available) observations is subtracted from a variable (Arellano and Bover, 1995). This procedure helps to minimize data loss (Roodman, 2009), which is imperative in the small sample underlying this research paper. This procedure also helps to mitigate unbalanced panels. Additionally, the two-step system GMM estimator allows for the Windmeijer (2005) correction of the downward bias of standard errors in finite samples. Moreover, standard errors will be computed to be robust to heteroskedasticity and random patterns of autocorrelation within countries. Furthermore, the “collapse” option will be used in Stata, in order to limit instrument proliferation in the already small underlying sample. The consistency of the GMM estimator depends on the validity of the assumption that the disturbance terms do not exhibit serial correlation and that the instruments are valid. These assumptions will be tested for with the Arellano-Bond Test for second order autocorrelation¹⁶, and the Hansen-Test for overidentifying exclusion restrictions.

GMM estimation is typically applied to time-series of non-overlapping five-year (sometimes decade) intervals. Potentially endogenous variables (such as financial development) usually enter the regression equation as initial interval values as internal instruments. The reasoning for taking five-year averages is, that it is supposed to abstract from short-term business cycle fluctuations and thus reveal the long-run relationship of financial development and economic growth (Barajas et al., 2013). Loayza and Rancière (2005), however, criticize this practice, as with averaging a lot of short-term variation in variables is lost and it is not clear, whether this method effectively gets rid of business cycle movements. Moreover, they point to the possibility that it might not be sufficient to limit one’s investigation solely to the long-run relationship of financial development and growth. Additionally, business cycles differ across countries in their timing, as well as their length. As such, the National Bureau of Economic Research (NBER) for the United States and the Center for Economic Policy Research (CEPR) for Europe have found evidence for the duration of business cycles exceeding five years in these regions (Jérôme Creel, Paul Hubert, and Fabien Labondance, 2015).¹⁷ Finally, the resulting short time dimension due to averaging compared to the cross-section of countries might lead to a biased estimation or asymptotic imprecision (Giovanni Favara, 2003). Apart from the long- run focus, another potential weakness of the estimation method could be, that it forces cross-country homogeneity on the slope coefficients for financial development.¹⁸ Both issues will be addressed by using the PMG estimator as a complementary model.

16 The differenced error term probably displays first-order serial correlation by construction, even if the original disturbance term is not first-order auto-correlated (Roodman, 2009).

17 Evidence has been found that financial cycles are less frequent, and their mean duration has increased since the 1980s, to a current average of 20 years (Mathias Drehmann, Claudio Borio, and Kostas Tsatsaronis, 2012).

18 GMM only allows for country-specific intercepts.

An Empirical Re-assessment of the Finance-Growth Nexus