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Reassessing the Literature on the Relationship Between Financial Structure and Economic Growth

This paper surveys the literature, particularly the empirical literature, that examines the association between financial structure and economic growth. The studies are divided into two groups depending on their research focus and research design. Whereas both strands of literature contribute to our understanding of the relationship between financial structure and growth and may also inform each other, the fundamental difference in their research questions means that they should be treated separately rather than together. Despite this difference, the two strands of literature share a common weakness: i.e. they overlook the interactions between banks and stock markets, which may lead to biased estimations.

1 Introduction

The financial sector has been dubbed “the brain of the economy” ( Mishkin 2006 : 25) in view of its essential role in allocating capital. Without an efficient financial sector, it is hard or even impossible to transfer idle funds to more efficient uses; new ideas, innovative products, and productive investments would therefore be abandoned, and society would in turn be trapped in the status quo. It is therefore not surprising to find that historically and comparatively, economic prosperity has always been accompanied by financial development ( Rajan and Zingales 2003 ; Rousseau and Sylla 2003 ). Greenwood et al. (2013) further show that financial development can explain approximately 23% of cross-country dispersion in output. Whereas the positive effects of financial development on economic performance have been questioned since the 2008 financial crisis, the literature as a whole seems to support the beneficial role of financial development in the process of economic growth ( Arestis et al. 2015 ; Popov 2018 ; Valickova et al. 2015 ). [1]

We may be convinced by the literature and therefore agree that financial development does indeed matter for economic growth; however, there are still other unsolved questions. For example, is financial structure relevant in understanding economic progress? More specifically, does it make a difference to have a bank-based financial system versus a market-based one? If so, which system is better in terms of achieving economic prosperity? Economists have debated the comparative importance of these two systems for decades ( Allen and Gale 2000 ; Demirgüç-Kunt and Levine 2001 ; Fohlin 2012 ). However, to date, no consensus has been reached at either the theoretical or the empirical level. Allen et al. (2018 : 56) therefore admit that “the question of how financial structure characteristics affect economic development is not yet fully understood”.

It is hence necessary to survey the literature to help us understand the status quo of the research, particularly the challenges faced by researchers in terms of indicator selection, methodology employment, result robustness, etc., as well as the potential direction of future research. There are already high-quality literature reviews in the field of financial structure, such as those of Levine (2005) and Allen et al. (2018) . However, Levine’s (2005) work was published 16 years ago and therefore does not cover the more recent advances; Allen et al.’s (2018) survey, despite its recency and comprehensiveness, fails to examine certain important dimensions of the research on financial structure, such as the interactions between the banking sector and stock markets. In this study, we fill the gap left by the previous surveys.

More specifically, we identify two strands of literature and survey them separately. The first group of literature follows the tradition of Beck et al. (2001) and Levine (2002) , using certain indicators to measure the comparative weight of banks and stock markets in a financial system and then exploring whether and to what extent this comparative weight matters for understanding economic growth. The second body of literature, without referring to these relative indicators, aims to directly estimate the contributions of one financial sector to economic growth versus those of the other. Both of these bodies of literature have contributed to our understanding of the connection between financial structure and economic growth; unfortunately, the point that they contribute from different perspectives and that their research outputs therefore cannot be compared directly appears to have attracted insufficient attention from researchers in this field. Classifying these two bodies of work is the first contribution of this study.

The second contribution of this study is to highlight a missing piece of the picture, i.e. the interactions between banks and stock markets. Despite their differences, the aforementioned two strands of literature share the same weakness: i.e. they overlook these interactions. As we discuss in this study, the evidence suggests that there are indeed complicated and dynamic interactions between banks and stock markets, which in turn affect their contributions to economic growth. A failure to take such interactions into consideration in empirical research may lead to seriously biased estimation results. The real effects of certain financial sectors on the economy may be overestimated or underestimated, depending on the nature of the interactions. Future studies are therefore strongly suggested to take the interactions between different components of the financial system seriously.

The rest of the paper is organized as follows. Section 2 examines the literature that uses the relative structure indicators and therefore focuses on the role of the relative weight of different financial sectors. Section 3 surveys the literature that directly estimates the contribution of banks to the economy in comparison to that of stock markets. Section 4 discusses the interactions between banks and stock markets and the impacts of such interactions on economic growth. Section 5 concludes.

2 Studies Using the Relative Indicators [2]

Before we proceed, it is necessary to briefly discuss the meaning and measures of financial structure. In the literature, financial structure is usually defined by the relative weight (in terms of size, activities, and efficiency) of financial markets (particularly stock markets) versus financial intermediaries (particularly banks) in a country’s financial system ( Beck et al. 2001 ; Levine 2002 ). Whereas both banks and stock markets can be relied on to perform the basic function of a financial system, i.e. channeling funds from surplus units with no or little profitable investment opportunities to agents who have such opportunities but suffer from a deficit of funds, they channel funds in quite different ways. Banks typically act as an intermediary, taking deposits from savers and lending them out to borrowers in the form of loans, whereas stock (and bond) markets serve as a platform where equity (and debt) securities are issued and traded. Certainly, in most countries, the financial system combines both banks and financial markets; nevertheless, financial structure, i.e. the comparative importance of banks versus financial markets in financing the economy, varies across countries.

Based on this perspective, every country can be classified as having either a bank-based financial system or a market-based system. For example, Germany and Japan are usually cited as typical cases of the former, while the US and the UK are regarded as prototypes of the latter. In the former countries, there are “high levels of bank finance, equity holding by banks, long-term relationships, close monitoring and active corporate governance by banks”, while in the latter countries, “market-oriented financial systems support large, active securities markets, and firms use market-based financing” ( Allen et al. 2018 : 31). Certainly, it needs to be cautioned that the classification in practice is not unambiguous: “In theory, every country has one type of financial system, which falls into one of the distinct categories … in reality, there is no clear-cut distinction between financial systems, and the classifications empirically fit only roughly” ( Allen et al. 2018 : 32).

A collection of indicators that can be used to proxy for financial structure have been developed by Beck et al. (2001) and Levine (2002) . They construct four indicators. [3] The first one, structure-activity , is a measure of the activity of stock markets relative to that of banks and equals the logarithm of the total value traded ratio (the value of domestic equities traded on domestic exchanges divided by GDP) divided by the bank credit ratio (the value of deposit money bank credits to the private sector as a share of GDP). The second one, structure-size , is a measure of the size of stock markets relative to that of banks and equals the logarithm of the market capitalization ratio (the value of domestic equities listed on domestic exchanges divided by GDP) divided by the bank credit ratio. The third one, structure efficiency , is a measure of the efficiency of stock markets relative to that of banks and equals the logarithm of the total value traded ratio (or turnover ratio, which equals the value of stock transactions relative to market capitalization) times overhead costs (or interest rate margins) of the banking system relative to banking system assets. Finally, these authors develop a conglomerate indicator, structure-aggregate , which is the first principal component of the aforementioned three indicators. These indicators (Levine indicators hereafter) can therefore be relied upon to measure the relative activity, size, efficiency, and aggregate development of stock markets versus those of banks in different countries, with larger values indicating a more market-based financial system. These indicators have subsequently been used in the literature that will be the focus of this section.

By contrast, there are other studies that explore the comparative contributions of banks and stock markets to economic growth without referring to the Levine indicators. Typically, these studies add banking development indicators and stock market development indicators into the regression equation simultaneously, and the results can therefore be interpreted as the effects of banking development on economic growth after stock market development is controlled for (and vice versa), regardless of the relative weight of the banking sector (or stock markets) in the financial system. This strand of literature is surveyed in Section 3 .

As we have discussed, financial structure indicators were first introduced by  Beck et al. (2001) and Levine (2002) . These two papers use the same indicators and same methods (OLS and IV estimations), cover the same sample countries for the same period, and reach the same conclusions. They find that for 48 countries over the 1980–1995 period, when their financial structure indicators and aggregate financial development indicators (bank activity times stock market activity, bank size times stock market size, bank efficiency times stock market efficiency, and the first principal component of activity, size, and efficiency) are included in the regression equation jointly, financial development indicators are positively and significantly related to economic growth, whereas financial structure indicators never enter the growth regression significantly. Levine (2002 : 398) therefore concludes that “the results indicate that although overall financial development is robustly linked with economic growth, there is no support for either the bank-based or the market-based view”. In other words, financial structure is irrelevant in understanding economic growth.

The irrelevance argument is challenged by subsequent studies. Pinno and Serletis (2007) find that once parameter heterogeneity is allowed for, financial structure is relevant: economic growth is promoted by market-based financial systems in developed countries (but is supported by bank-based financial systems in developing countries). Luintel et al. (2008) and Arestis et al. (2010) similarly argue that estimates may be biased if cross-country parameter heterogeneity is ignored. They apply time-series and dynamic heterogeneous panel methods to overcome the problems of cross-country heterogeneity and unbalanced cross-country growth paths and find that financial structure determines output levels (not growth rates) in the majority of their sample countries.

The conclusion of Pinno and Serletis (2007) implies that the financial structure-economic growth nexus is dependent on an economy’s income level, which is supported by other studies. For example, Luintel et al. (2016) report that the relationship between financial structure and output level changes with the stage of economic development. More specifically, a market-based financial system is positively and significantly associated with per capita income only in high-income countries, whereas aggregate financial development benefits middle- and low-income countries. In addition to development stage, institutional environment is also shown to be relevant. Ergungor (2008) reports that whether and to what extent financial structure influences economic growth depend on features of the judicial system: countries that have inflexible judicial systems grow faster if they have bank-oriented financial systems. Yeh et al. (2013) find that the interactions between financial structure indicators and income level as well as rule of law are significantly related to economic growth, which implies that both income level and legal environments intervene in the financial structure-economic growth nexus. They also report that a market-based financial system promotes economic growth in the long run at the cost of inducing growth volatility.

In a more recent study, Chu (2020) demonstrates a more complicated relationship between financial structure and economic growth. She introduces the interaction between financial structure and aggregate financial development and the interaction between financial structure and an indicator of whether aggregate financial development is balanced. She also considers the potential nonlinear relationship between financial structure and economic growth. Her findings indicate that a market-based financial system promotes economic growth in the advanced stage of financial development while damaging economic growth in an unbalanced financial environment (with excessive stock market vis-à-vis banking sector development). In addition, there is an inverted U-shaped relationship between financial structure (activity indicator) and economic growth.

In summary, despite their usefulness in characterizing a financial system as bank- or market-based, the Levine indicators are actually not widely used in the economic growth literature. [4] Even in this small group of works, it is difficult to detect a consensus on the role of financial structure in economic growth. These studies use different methodologies, cover different sample countries, introduce different control variables, and even employ different dependent variables (GDP level vs. GDP growth). In addition, except for Chu (2020) , none of these studies consider the potential nonlinearity in the connection between finance and economy, although this nonlinearity has been repeatedly confirmed by the recent literature examining the connection between aggregate financial development and economic growth ( Xu and Gui 2021 ). These studies also fail to consider the interactions between the banking sector and stock markets, which will be discussed in Section 4 . When the nonlinearity and the interactions between banks and stock markets are taken into consideration, whether and to what extent the results presented by the aforementioned studies are robust remain to be seen.

The foundation of these studies, the Levine indicators, is certainly not flawless. They have certain weaknesses ( Cuadro-Sáez and Herrero 2008 ). First, these indicators are insufficient to cover the whole financial system, as financing by foreign investors and the domestic bond market is excluded. Second, being the natural logarithm of a ratio, the indicators are neither bounded nor linear. The indicators equal infinity or minus infinity when the size of one of the two financial system components is zero or approaches zero. Third, an increase in stock market development relative to the banking sector has a different impact on the indicator depending on the initial size of the markets. Cuadro-Sáez and Herrero (2008) construct a new indicator that can be used to measure whether the development of a financial system is balanced (between banks and stock markets) and find that a more balanced financial system is more favorable for economic growth. Unfortunately, this indicator has been overlooked by subsequent studies, and therefore, its usefulness has not been tested systematically. Developing better indicators that can address the problems inherent in the original Levine indicators and that therefore can be used to define, characterize and classify financial systems in different countries more effectively is of great necessity.

3 Studies Not Using the Relative Indicators

There are many more studies that explore the relative contributions of banks and stock markets in promoting economic growth without referring to the Levine indicators. Most of these studies jointly incorporate banking development indicators and stock market development indicators into the regression equation, and the results should therefore be interpreted as measuring the absolute rather than relative effects of one part of a financial system (after the influence of the other part of the financial system is controlled for). The coefficient estimates of bank development on economic growth can be further compared to those of stock market development, and their comparative merits are therefore determined.

Levine and Zervos (1998) is among the first studies [5] to systematically examine the contributions of banks versus those of stock markets to economic growth. The authors use four indicators to measure stock market development ( size , that is, the value of listed domestic shares on domestic exchanges divided by GDP; liquidity , the value of the trades of domestic shares on domestic exchanges divided by the value of listed domestic shares and the value of the trades of domestic shares on domestic exchanges divided by GDP; international integration measures , computed by the capital asset pricing model and international arbitrage pricing theory; and volatility , the 12-month rolling standard deviation estimate based on market returns) and one bank development measure (the value of loans made by commercial banks and other deposit-taking banks to the private sector divided by GDP). Based on a sample covering 47 countries for the 1976–1993 period, they find that both the initial level of bank development and that of stock market liquidity have a statistically significant relationship with future values of output growth and that the main channel linking financial development with output growth runs through productivity growth rather than capital stock growth. They also report that the economic effects of stock market liquidity are comparable with those of bank development (a one-standard-deviation increase in initial stock market liquidity (bank development) increased per capita growth by 0.8 (0.7)% points per year over the 1976–1993 period).

Levine and Zervos’s (1998) conclusion is supported by certain studies. For example, Rousseau and Wachtel (2000) find that both bank development and stock market development Granger-cause the output level, and the magnitude of their results in terms of annual output growth is similar. Beck and Levine (2004) apply a system-GMM estimation and again report that both bank development and stock market development indicators enter the growth regressions significantly. Durusu-Ciftci et al. (2017) similarly find that both bank development and stock market development have positive long-run effects on the steady-state level of GDP per capita (but the contribution of bank development is substantially greater). Shen et al. (2018) report that stock market indicators exhibit a positive effect on the real per capita GDP level regardless of outliers, whereas the influence of the banking sector on GDP changes from negative to positive when outliers are controlled for. They therefore argue that the negative relationship between banking sector development and economic growth demonstrated by the literature (see below) is caused by the existence of outliers.

The positive effects of stock markets on economic growth are further confirmed by some other studies, which, however, fail to find a beneficial role of banks or even report a negative association between bank development and economic prosperity. [6] Thumrongvit et al. (2013) find that whereas the stock market indicator is positively associated with economic growth, the banking sector measure shows no significant effect. Peia and Roszbach (2015) find that in advanced economies, stock market development generally causes the GDP level, while the causality between bank development and GDP goes in the reverse direction. Kim et al. (2012) report that whereas stock market development is favorable to growth (particularly in high-income, low-inflation, and nonagricultural countries), banking sector development is detrimental to output growth. Haiss et al. (2016) similarly demonstrate that while the stock market variable has a positive effect on economic growth (when no lags are included in the equation), all banking sector indicators (private credit, domestic credit, and liquid liabilities) and the bond market development indicator exert a negative impact on growth.

However, a larger body of literature refutes a simple linear (positive or negative) relationship between banks or stock markets and economic growth; rather, these studies demonstrate that the connection tends to be nonlinear, heterogeneous across countries, and context dependent. Shen and Lee (2006) find that an inverse U-shaped relationship exists for bank development and growth as well as stock market development and growth. Shen and Lee’s (2006) conclusion is confirmed by Gambacorta et al. (2014) and Swamy and Dharani (2019 , 2020 but challenged by Shen et al. (2011) , who identify that while there are nonlinear relationships between both components of the financial system and economic growth, the shape of nonlinearity for banks is different from that for stock markets. Moosa (2018) also reports that while a nonlinear association exists between the banking sector indicator and growth (an inverted U-shaped curve for high-income OECD countries and upper middle-income countries and a U-shaped curve for high-income non-OECD countries and low middle-income countries), no such nonlinearity is observed for the stock market indicator. Benczúr et al. (2019) find that after they control for stock market capitalization and debt market indicators, bank credit has a nonlinear, hump-shaped impact on economic growth (but they do not examine whether the stock market indicator has a nonlinear effect). By contrast, Cave et al. (2020) report that a nonlinear connection only exists between stock market development and economic growth, while there is a linearly negative relationship between bank development and economic growth.

The relationship between these two components of the financial system and economic growth is proven to be not only nonlinear but also heterogeneous across countries, regions, and time periods. Kim et al. (2010) report that while both stock market development and banking sector development damage economic growth (relative to that of the US) in low-income countries, stock market development promotes relative economic growth in high-income countries [7] (on which banks have no effects). Cheng et al. (2011) find that the effects of both banks and stock markets on the output level are contingent on the level of country risk and time horizon (long run vs. short run). The importance of a country’s income level and the time period of analysis in mediating the effects of banks and stock markets on economic growth is further confirmed by other studies, such as Cheng et al. (2014) , Barajas et al. (2016) , Seven and Yetkiner (2016) , Hou and Cheng (2017) , and Fufa and Kim (2018) . In addition to income level and time period, institutional quality and financial crises have also been shown to intervene in the relationship between financial structure and economic growth ( Asteriou and Spanos 2019 ; Compton and Giedeman 2011 ; Slesman et al. 2019 ).

It is difficult to draw a general conclusion from such a diversified literature, which applies different methodologies, covers different sample countries for different time periods, and employs different indicators. Nevertheless, despite the variety of results and the complications caused by nonlinearity and heterogeneity, it appears that the evidence as a whole indicates that stock market development is comparatively more favorable for economic growth, particularly for high-income countries. By contrast, the beneficial effects of bank development are limited to low-income countries and environments characterized by a modest level of financial development, a finding that is compatible with the recent literature showing the detrimental consequences of “too much finance (credit)” ( Arcand et al. 2015 ; Xu and Gui 2021 ).

Unfortunately, this strand of literature, despite its important contributions, deviates from the original focus of the financial structure literature, namely, to explore the comparative performance (in terms of economic growth) of a bank-based system (where banks and stock markets coexist but banks dominate the financing process and therefore are proxied by relatively larger bank development indicators) and a market-based system (where banks and stock markets coexist but stock markets play a more important role and therefore are proxied by relatively larger stock market development indicators), rather than to directly compare the economic effects of stock markets per se to those of banks per se. The results of these two strands of literature therefore cannot be compared directly. In other words, a positive association between stock market (bank) development and economic growth cannot be automatically interpreted as evidence supporting the superiority of a market- (bank-) based system. For example, if both banks and stock markets promote economic growth and the positive effects of banks dominate those of stock markets, then a bank-based system outperforms a market-based system in terms of economic growth even though stock markets per se are beneficial for economic growth. The aforementioned nonlinearity and heterogeneity issues certainly make it more difficult to bring the two strands of literature together.

The situation is even more complicated if we further consider the interactions between the banking sector and stock markets, as we will discuss in the next section. Assume that there is a complementary relationship between stock markets and banks and that stock markets and banks have opposite effects (stock markets positive and banks negative) on economic growth. In that case, stock markets affect the economy both directly and indirectly; they promote economic growth directly but damage economic growth indirectly through their effects on bank development. There would then be an overestimation of the positive effects of stock markets on economic growth if their (negative) indirect impacts (via banks) are not taken into consideration, and the results would certainly be biased.

4 Interactions Between Banks and Stock Markets

In the early theoretical literature, banks and financial markets are usually seen as substitutes, with the former only growing at the expense of the latter and vice versa ( Baliga and Polak 2004 ; Boot and Thakor 1997 ; Chakraborty and Ray 2007 ; Dewatripont and Maskin 1995 ; Greenwood and Smith 1997 ). In these theoretical frameworks, firm size, investment technologies, monitoring cost, income distribution, etc., determine which financial sector emerges and dominates. However, more recent theoretical models argue that the relationship between banks and financial markets is actually more complicated than its portrayal in earlier studies; in addition to competition (substitution), the interactions may take the form of complementarity and coevolution ( Boot and Thakor 2012 ; Song and Thakor 2010 , 2013 ).

There are two channels through which banks and markets may be linked in a codependent manner ( Song and Thakor 2010 , 2013 ). First, bank development boosts market development through securitization. Securitization means that a bank certifies a borrower’s credit quality via credit analysis and then the financial market finances the borrower. Improvements in banks’ credit analysis technology, as a result of development in the banking sector, enhance market investors’ confidence in a securitized borrower’s credit quality. This, in turn, encourages more informed trading in the market and hence leads to a more active and efficient financial market. Second, banks need to raise capital from financial markets. With the development of the financial market, the costs of information acquisition and processing are reduced, the number of informed traders increases, and pricing efficiency in the financial market is improved, all of which result in a lowering of the cost of equity capital for banks. Advances in the financial market therefore enable banks to expand their lending scope and lend to riskier borrowers who were previously excluded from credit availability.

In addition to securitization and capital raising, banks and financial markets may interact in other ways. For example, Hellmann et al. (2008) report that banks occasionally participate in the venture capital market, which is an integral part of the capital market. Boot and Thakor (2012) argue that the development of financial markets may lead to a diminished role for the central bank in providing liquidity to individual banks as a lender of last resort. Finally, as highlighted by Hardie et al. (2013) , in recent years, banks have gradually transformed from a traditional banking model to a market-based banking model that is more involved in securitization and shadow banking, more dependent on wholesale market funding, and more reliant on market-based loan pricing (mark to market).

The existence of a link between banks and stock markets is confirmed by empirical studies, but the specific feature of the link is debated. Demirgüç-Kunt and Levine (1996 : 316) find that there is a strong positive correlation between stock market development and financial intermediary development and conclude that the two “go hand in hand”. This conclusion is supported by certain subsequent studies. For example, Kim and Rousseau (2012) show that the expansion in a traditional measure of financial intermediation (the difference between broad money (M2) and narrow money (M1)) promotes stock market development (in terms of size and liquidity). Pradhan et al. (2017) present evidence showing bidirectional causality between bank development and the stock market. [8]

Other studies show that the interactions between these two financial sectors are more complicated. First, the interaction has been shown to be context-dependent. Demirgüç-Kunt and Maksimovic (1996) report that the association between stock markets and banks changes with the stage of stock market development (complementary in the developing stage but competitive in the developed state). In a time series study that covers five developed countries (France, Germany, Japan, the UK, and the US), Arestis et al. (2001) show that the direction of causality in the relationship between banks and stock markets changes from one country to another. Cheng et al. (2011) find that the relationship between the banking sector and stock markets is dependent on the time period (long run vs. short run) and country grouping (low-risk countries vs. high-risk countries). Allen et al. (2012) report that the impacts of stock market indicators on banking sector measures change between normal and crisis regimes. [9]

Second, the influence between banks and the stock market may be asymmetric. Wu et al. (2010) conduct an impulse response analysis showing that a bank development shock increases stock market development but that a stock market development shock decreases bank development. Kim and Lin (2013) similarly report that increased stock market liquidity stymies credit expansion, whereas bank credit expansion improves stock market liquidity. Ngo and Le (2019) find that banking efficiency contributes to stock market development, whereas stock market development is harmful to banking efficiency. The negative impact of stock market development on bank development is further confirmed by Lin (2020) , who reports that households’ demand for retail deposits decreases during stock market booms, which induces a contraction in bank lending and a decrease in real activity in bank-dependent sectors.

Deidda and Fattouh (2008) is the first study to examine the effects of the interaction between banks and stock markets on economic growth. They find that while both the banking sector indicator and the stock market indicator per se are positively associated with economic growth, their interaction term has a significantly negative impact on growth, which implies that the influence of banking development on growth becomes less positive as the level of stock market development increases (and vice versa). Owen and Temesvary (2014) similarly report that in countries with less developed stock markets, bank finance has a more positive effect on growth, which suggests that bank finance and stock market finance may be substitutes in promoting economic growth. By contrast, Botev et al. (2019) find an asymmetric interaction: the positive effects of bank credit on the economy are reinforced by more developed stock markets, whereas no such strengthening effects can be found to run from bank credit to stock markets.

In summary, there are intricate interactions between the banking sector and stock markets, which in turn complicate the connection between financial structure and the economy. The contributions of one financial sector to economic growth may be reinforced or weakened (or even neutralized in certain scenarios) by the other sector, depending on the nature of their interactions. Failure to take such interactions into consideration in empirical studies inevitably leads to biased estimations. Unfortunately, most of the empirical works seem to have overlooked this issue, and whether and to what extent their results remain robust after the interaction effect is controlled for is an open question.

5 Conclusion

Whether financial structure matters for understanding economic growth is a long-debated question in the literature, and so far, no consensus has been achieved. In this study, we survey the literature by first distinguishing two strands. The first one follows the tradition of Beck et al. (2001) and Levine (2002) , relying on the indicators measuring the magnitude of each financial sector in the financial system relative to the other and then exploring the contributions of the relative magnitude to economic growth. The second strand of literature, by contrast, directly examines the impacts of one financial sector on economic growth after controlling for the effects of the other sector. Both directions of research are valuable and productive; however, their research outputs cannot be compared directly, and it is therefore more appropriate to treat them separately rather than pool them together.

We further discuss an important dimension of the financial structure issue, i.e. the interactions between the banking sector and stock markets. The banking sector and stock markets not only influence the economy but also affect each other. They may compete (substitute) or cooperate (complement) with each other, and one sector’s (positive or negative) effects on the economy may therefore be weakened or strengthened, depending on the nature of the interrelationship. Unfortunately, this interrelationship appears to have been overlooked by most of the empirical studies exploring the connection between financial structure and economic growth, and it may be argued that their estimations may be biased to a certain extent by this oversight. Future studies are strongly recommended to take the interaction issue more seriously.

Studies using the Levine indicators.

Studies not using the Levine indicators.

Interactions between banks and stock markets.

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International Journal of Managerial Finance

ISSN : 1743-9132

Article publication date: 3 April 2017

The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research.

Design/methodology/approach

The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis.

Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically.

Originality/value

The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.

• Literature review
• Meta-analysis
• Capital structure
• Pecking order

Kumar, S. , Colombage, S. and Rao, P. (2017), "Research on capital structure determinants: a review and future directions", International Journal of Managerial Finance , Vol. 13 No. 2, pp. 106-132. https://doi.org/10.1108/IJMF-09-2014-0135

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THE EFFECT OF FINANCIAL STRUCTURE AND ECONOMIC GROWTH: AN EMPIRICAL APPROACH

2020, IAEME PUBLICATION

This study has been initiated with a view to understand and explore the difference between financial structure and Housing and financial market Failures are global downfall of the economic crisis. The purpose of the examination is to audit the causal relationship among financial structure and economic indicator and to understand the time effect on the economic indicator by the financial structure. The study involves economic and financial data spreads time arrangement information from 1968-2018 and the considerable number of factors. Where the required samples is allocated into two major categories of Financial structure are grouped in to four sub-industry wise as Finance Size, financial Development, formalism and growth, in order find out differences of financial structure and its variables and promote the analysis with findings. The data has been arranged in the panel set up. The years as well as the factors are cross tabulated in order to analyse the time effects in the relationships. This study has adopted the theory of financial structures and economic indicators. The relationship between the macro factors from the different time frames. The overall economic growth of financial structure mentioning. It does not considerably explain utilizing panel data observation that af fected the capital stock negatively. To explain the differences in economic performance, there was a distinction between bank vs market orienting financial system that are not taken in to consideration. On the other hand, there are also experimental literatures that displayed the consequences of financial system on economic steps forward, which have not been found as consistent across countries or time periods.

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The relationship between financial development and economic growth is among the essential issues analyzed in economy literature. This study researches the relationship between financial development and economic growth by using 1980-2014 period annual data Mexico. As the indicator of financial development, the proportion of domestic credits provided by financial sector to Gross National Product was used as the indicator of economic growth the growth rate of Gross National Product was used. Panel causality test developed by Dumitrescu – Hurlin (2012) was utilized in order to research the relationship between variables. While the obtained findings indicate the existence of a causality relationship from financial development to economic growth for the countries determined, a causality relationship from economic growth to financial development could not be identified.

The aim of this paper is to provide empirical evidence on the relationship between financial development and economic growth and to examine whether there are differences in the size of the impact of financial development on economic growth in countries with different income levels. Furthermore, the impact of additional determinants of economic growth is analyzed. Research problem is lack of empirical evidence on the relationship between financial development and economic growth when financial development is measured by proxy variables on banks and stock markets; low treatment of potential endogeneity problem as well as lack of empirical evidence on the differences in the size of the impact of financial development on economic growth in countries with different income levels. Balanced panel data for 94 countries during the period between 1992 and 2011 are used in this analysis. Five-year averaged data are used to reduce the impact of business cycles and measurement errors. Six models are estimated by using panel fixed and random effects models. However, the analysis indicates that distribution of error terms deviates from normal; the assumption of homoscedasticity is rejected and the presence of endogenous regressor is reported. Therefore, in order to overcome these issues, the dynamic one step system GMM estimator is used to estimate models. The obtained results indicate that banking sector and stock market development have statistically significant positive impact on economic growth. It has been shown that the impact of banking sector development strongly contributes to economic growth compared to stock market development. Besides, the results show that education has no statistically significant impact on economic growth while inflation, government spending and trade openness have a negative impact. The sixth model indicates that on average financial development strongly impacts economic growth in high and middle-income countries compared to low-income countries, and that the strongest impact is obtained for high income countries. The results of this paper may motivate policy makers to foster the financial development since it contributes to economic growth. Since financial development contributes to economic growth in countries with different income levels, there is a need to foster its development in low-income countries as well.

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• Investigating how different dividend policies affect shareholder value and the firm’s financial performance 

Investment Banking

The list below presents a series of research topics exploring the multifaceted dimensions of investment banking, with a particular focus on its evolution following the 2008 financial crisis.

• Analysing the evolution and impact of regulatory frameworks in investment banking post-2008 financial crisis
• Investigating the challenges and opportunities associated with cross-border M&As facilitated by investment banks.
• Evaluating the role of investment banks in facilitating mergers and acquisitions in emerging markets
• Analysing the transformation brought about by digital technologies in the delivery of investment banking services and its effects on efficiency and client satisfaction.
• Evaluating the role of investment banks in promoting sustainable finance and the integration of Environmental, Social, and Governance (ESG) criteria in investment decisions.
• Assessing the impact of technology on the efficiency and effectiveness of investment banking services
• Examining the effectiveness of investment banks in pricing and marketing IPOs, and the subsequent performance of these IPOs in the stock market.
• A comparative analysis of different risk management strategies employed by investment banks
• Examining the relationship between investment banking fees and corporate performance
• A comparative analysis of competitive strategies employed by leading investment banks and their impact on market share and profitability

Private Equity & Venture Capital (VC)

These research topic ideas are centred on venture capital and private equity investments, with a focus on their impact on technological startups, emerging technologies, and broader economic ecosystems.

• Investigating the determinants of successful venture capital investments in tech startups
• Analysing the trends and outcomes of venture capital funding in emerging technologies such as artificial intelligence, blockchain, or clean energy
• Assessing the performance and return on investment of different exit strategies employed by venture capital firms
• Assessing the impact of private equity investments on the financial performance of SMEs
• Analysing the role of venture capital in fostering innovation and entrepreneurship
• Evaluating the exit strategies of private equity firms: A comparative analysis
• Exploring the ethical considerations in private equity and venture capital financing
• Investigating how private equity ownership influences operational efficiency and overall business performance
• Evaluating the effectiveness of corporate governance structures in companies backed by private equity investments
• Examining how the regulatory environment in different regions affects the operations, investments and performance of private equity and venture capital firms

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Asset Management

This list includes a range of research topic ideas focused on asset management, probing into the effectiveness of various strategies, the integration of technology, and the alignment with ethical principles among other key dimensions.

• Analysing the effectiveness of different asset allocation strategies in diverse economic environments
• Analysing the methodologies and effectiveness of performance attribution in asset management firms
• Assessing the impact of environmental, social, and governance (ESG) criteria on fund performance
• Examining the role of robo-advisors in modern asset management
• Evaluating how advancements in technology are reshaping portfolio management strategies within asset management firms
• Evaluating the performance persistence of mutual funds and hedge funds
• Investigating the long-term performance of portfolios managed with ethical or socially responsible investing principles
• Investigating the behavioural biases in individual and institutional investment decisions
• Examining the asset allocation strategies employed by pension funds and their impact on long-term fund performance
• Assessing the operational efficiency of asset management firms and its correlation with fund performance

Hedge Funds

Here we explore research topics related to hedge fund operations and strategies, including their implications on corporate governance, financial market stability, and regulatory compliance among other critical facets.

• Assessing the impact of hedge fund activism on corporate governance and financial performance
• Analysing the effectiveness and implications of market-neutral strategies employed by hedge funds
• Investigating how different fee structures impact the performance and investor attraction to hedge funds
• Evaluating the contribution of hedge funds to financial market liquidity and the implications for market stability
• Analysing the risk-return profile of hedge fund strategies during financial crises
• Evaluating the influence of regulatory changes on hedge fund operations and performance
• Examining the level of transparency and disclosure practices in the hedge fund industry and its impact on investor trust and regulatory compliance
• Assessing the contribution of hedge funds to systemic risk in financial markets, and the effectiveness of regulatory measures in mitigating such risks
• Examining the role of hedge funds in financial market stability
• Investigating the determinants of hedge fund success: A comparative analysis

Financial Planning and Advisory

This list explores various research topic ideas related to financial planning, focusing on the effects of financial literacy, the adoption of digital tools, taxation policies, and the role of financial advisors.

• Evaluating the impact of financial literacy on individual financial planning effectiveness
• Analysing how different taxation policies influence financial planning strategies among individuals and businesses
• Evaluating the effectiveness and user adoption of digital tools in modern financial planning practices
• Investigating the adequacy of long-term financial planning strategies in ensuring retirement security
• Assessing the role of financial education in shaping financial planning behaviour among different demographic groups
• Examining the impact of psychological biases on financial planning and decision-making, and strategies to mitigate these biases
• Assessing the behavioural factors influencing financial planning decisions
• Examining the role of financial advisors in managing retirement savings
• A comparative analysis of traditional versus robo-advisory in financial planning
• Investigating the ethics of financial advisory practices

The following list delves into research topics within the insurance sector, touching on the technological transformations, regulatory shifts, and evolving consumer behaviours among other pivotal aspects.

• Analysing the impact of technology adoption on insurance pricing and risk management
• Analysing the influence of Insurtech innovations on the competitive dynamics and consumer choices in insurance markets
• Investigating the factors affecting consumer behaviour in insurance product selection and the role of digital channels in influencing decisions
• Assessing the effect of regulatory changes on insurance product offerings
• Examining the determinants of insurance penetration in emerging markets
• Evaluating the operational efficiency of claims management processes in insurance companies and its impact on customer satisfaction
• Examining the evolution and effectiveness of risk assessment models used in insurance underwriting and their impact on pricing and coverage
• Evaluating the role of insurance in financial stability and economic development
• Investigating the impact of climate change on insurance models and products
• Exploring the challenges and opportunities in underwriting cyber insurance in the face of evolving cyber threats and regulations

Quantitative Finance

These topic ideas span the development of asset pricing models, evaluation of machine learning algorithms, and the exploration of ethical implications among other pivotal areas.

• Developing and testing new quantitative models for asset pricing
• Analysing the effectiveness and limitations of machine learning algorithms in predicting financial market movements
• Assessing the effectiveness of various risk management techniques in quantitative finance
• Evaluating the advancements in portfolio optimisation techniques and their impact on risk-adjusted returns
• Evaluating the impact of high-frequency trading on market efficiency and stability
• Investigating the influence of algorithmic trading strategies on market efficiency and liquidity
• Examining the risk parity approach in asset allocation and its effectiveness in different market conditions
• Examining the application of machine learning and artificial intelligence in quantitative financial analysis
• Investigating the ethical implications of quantitative financial innovations
• Assessing the profitability and market impact of statistical arbitrage strategies considering different market microstructures

Treasury Management

The following topic ideas explore treasury management, focusing on modernisation through technological advancements, the impact on firm liquidity, and the intertwined relationship with corporate governance among other crucial areas.

• Analysing the impact of treasury management practices on firm liquidity and profitability
• Analysing the role of automation in enhancing operational efficiency and strategic decision-making in treasury management
• Evaluating the effectiveness of various cash management strategies in multinational corporations
• Investigating the potential of blockchain technology in streamlining treasury operations and enhancing transparency
• Examining the role of treasury management in mitigating financial risks
• Evaluating the accuracy and effectiveness of various cash flow forecasting techniques employed in treasury management
• Assessing the impact of technological advancements on treasury management operations
• Examining the effectiveness of different foreign exchange risk management strategies employed by treasury managers in multinational corporations
• Assessing the impact of regulatory compliance requirements on the operational and strategic aspects of treasury management
• Investigating the relationship between treasury management and corporate governance

Financial Technology (FinTech)

The following research topic ideas explore the transformative potential of blockchain, the rise of open banking, and the burgeoning landscape of peer-to-peer lending among other focal areas.

• Evaluating the impact of blockchain technology on financial services
• Investigating the implications of open banking on consumer data privacy and financial services competition
• Assessing the role of FinTech in financial inclusion in emerging markets
• Analysing the role of peer-to-peer lending platforms in promoting financial inclusion and their impact on traditional banking systems
• Examining the cybersecurity challenges faced by FinTech firms and the regulatory measures to ensure data protection and financial stability
• Examining the regulatory challenges and opportunities in the FinTech ecosystem
• Assessing the impact of artificial intelligence on the delivery of financial services, customer experience, and operational efficiency within FinTech firms
• Analysing the adoption and impact of cryptocurrencies on traditional financial systems
• Investigating the determinants of success for FinTech startups

Commercial Banking

These topic ideas span commercial banking, encompassing digital transformation, support for small and medium-sized enterprises (SMEs), and the evolving regulatory and competitive landscape among other key themes.

• Assessing the impact of digital transformation on commercial banking services and competitiveness
• Analysing the impact of digital transformation on customer experience and operational efficiency in commercial banking
• Evaluating the role of commercial banks in supporting small and medium-sized enterprises (SMEs)
• Investigating the effectiveness of credit risk management practices and their impact on bank profitability and financial stability
• Examining the relationship between commercial banking practices and financial stability
• Evaluating the implications of open banking frameworks on the competitive landscape and service innovation in commercial banking
• Assessing how regulatory changes affect lending practices and risk appetite of commercial banks
• Examining how commercial banks are adapting their strategies in response to competition from FinTech firms and changing consumer preferences
• Analysing the impact of regulatory compliance on commercial banking operations
• Investigating the determinants of customer satisfaction and loyalty in commercial banking

International Finance

The folowing research topic ideas are centred around international finance and global economic dynamics, delving into aspects like exchange rate fluctuations, international financial regulations, and the role of international financial institutions among other pivotal areas.

• Analysing the determinants of exchange rate fluctuations and their impact on international trade
• Analysing the influence of global trade agreements on international financial flows and foreign direct investments
• Evaluating the effectiveness of international portfolio diversification strategies in mitigating risks and enhancing returns
• Evaluating the role of international financial institutions in global financial stability
• Investigating the role and implications of offshore financial centres on international financial stability and regulatory harmonisation
• Examining the impact of global financial crises on emerging market economies
• Examining the challenges and regulatory frameworks associated with cross-border banking operations
• Assessing the effectiveness of international financial regulations
• Investigating the challenges and opportunities of cross-border mergers and acquisitions

Choosing A Research Topic

These finance-related research topic ideas are starting points to guide your thinking. They are intentionally very broad and open-ended. By engaging with the currently literature in your field of interest, you’ll be able to narrow down your focus to a specific research gap .

When choosing a topic , you’ll need to take into account its originality, relevance, feasibility, and the resources you have at your disposal. Make sure to align your interest and expertise in the subject with your university program’s specific requirements. Always consult your academic advisor to ensure that your chosen topic not only meets the academic criteria but also provides a valuable contribution to the field. 

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How To Choose A Research Topic: 5 Key Criteria

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Impact of Financial Structure on Firm’s Performance: A Study of Pakistan’s Chemical Sector

Society of Interdisciplinary Business Research (SIBR) 2011 Conference on Interdisciplinary Business Research

12 Pages Posted: 21 Jun 2011

Sohail Amjed

Allama Iqbal Open University - Department of Commerce

Date Written: June 20, 2011

Firms have choices to raise their capital by various means including internally generated fund, new equity issue or various types of debt. The decision to select sources of finance is referred to as financial structure decision. Financial structure decision is very critical decision with great implications for the firm's performance. Theories proposed by the researchers to explain the financing decisions have always been subject of considerable debate. This study imperially explores the impact of debt financing on the profitability of the firms in Chemical Sector of Pakistan. The rationale behind the industry specific analysis is the fact that exogenous variables appear to force firms in the same industry in similar fashion. Therefore firms within same industry construct same type of capital structure. OLS has been applied to test the hypothesized relationship. Different perspectives have evolved over the period of time to explore the critical but very complex issue of financial structure decisions. Financial structure decisions base on many psychological and situational factors especially in developing countries like Pakistan. Financial Environment has great impact on financing decisions, the role of financial institutions is critical for capital restructuring decisions. In developing countries like Pakistan Financial Markets are incomplete and are unable to meet the financing requirements of the industry. Therefore, major source of debt financing for Pakistani companies is various types of loans with different maturities. Our results are not similar to the other studies conducted on capital structure. In oppose to literature our results reveal significant negative relationship between long term Debt and firms' performance and significant positive relationship between short term debt and the profitability.

Suggested Citation: Suggested Citation

Sohail Amjed (Contact Author)

Allama iqbal open university - department of commerce ( email ).

Block # 13 H - 8 Islamabad Pakistan +923335766992 (Phone)

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Paper statistics, related ejournals, microeconomics: intertemporal firm choice & growth, investment, financing, & capacity ejournal.

Subscribe to this fee journal for more curated articles on this topic

Emerging Markets Economics: Firm Behavior & Microeconomic Issues eJournal

Global business issues ejournal, recommended papers.

What Do We Know About Capital Structure? Some Evidence from International Data

By Raghuram G. Rajan and Luigi Zingales

The Theory and Practice of Corporate Finance: Evidence from the Field

By John R. Graham and Campbell R. Harvey

Capital Structure Puzzle

By Stewart C. Myers

The Theory and Practice of Corporate Finance: The Data

Market Timing and Capital Structure

By Malcolm P. Baker and Jeffrey Wurgler

Testing Tradeoff and Pecking Order Predictions About Dividends and Debt

By Eugene F. Fama and Kenneth R. French

How Big are the Tax Benefits of Debt?

By John R. Graham

Testing Static Trade-Off Against Pecking Order Models of Capital Structure

By Lakshmi Shyam-sunder and Stewart C. Myers

Optimal Capital Structure Under Corporate and Personal Taxation

By Harry Deangelo and Ronald W. Masulis

• Publication
• Global Financial Development Report
• Global Financial Development Database (GFDD)
• Little Data Book on Financial Development
• Financial Development Barometer
• Financial Structure Database
• Appendix B Dataset
• Past Reports
• Main Messages
• Table of Contents
• Statistical Appendix
• Selected Papers
• Bibliography
• Key Terms Explained
• Abbreviations and Glossary
• Acknowledgments
• Financial Support

Financial Development and Structure Dataset (updated September 2015)

Authors: Thorsten Beck, Asli Demirguc-Kunt, Ross Eric Levine, Martin Cihak and Erik H.B. Feyen 

Web Address: Finance Research

Topics: Financial Sector

Report Number: WPS2146 , WPS4943 , WPS6175

Citation:  

Thorsten Beck, Aslı Demirgüç-Kunt and Ross Levine, 2000, "A New Database on Financial Development and Structure," World Bank Economic Review 14, 597-605. (An earlier version was issued as World Bank Policy Research Working Paper 2146.)

Thorsten Beck, Aslı Demirgüç-Kunt, and Ross Levine, " Financial Institutions and Markets across Countries and over Time: Data and Analysis ", World Bank Policy Research Working Paper 4943, May 2009.

Martin Čihák, Aslı Demirgüç-Kunt, Erik Feyen, and Ross Levine, “ Benchmarking Financial Development around the World ”, World Bank Policy Research Working Paper 6175, August 2012.

Disclaimer: These data are provided on an "as-is" basis and their accuracy is not guaranteed by the World Bank. All errors are the authors' own.

This database of indicators of financial development and structure across countries and over time includes a range of indicators (31 indicators in total), starting from 1960, that measure the size, activity, and efficiency of financial intermediaries and markets.

The compiled data permits the construction of financial structure indicators to measure whether, for example, a country's banks are larger, more active, and more efficient than its stock markets. These indicators can then be used to investigate the empirical link between the legal, regulatory, and policy environment and indicators of financial structure. They can also be used to analyze the implications of financial structure for economic growth.

Latest version:

June 2017: The Global Financial Development Database has been updated with latest information, up to 2015.

September 2015: The Financial Development and Structure dataset updated in November 2013 contains data from 1960 through 2013. Similar to its previous, November 2013 version, the revised dataset covers 203 jurisdictions and it is a subset of the broader Global Financial Development Database.

The Financial Development and Structure dataset updated in November 2013 contains data from 1960 through 2013. Similar to its previous, November 2013 version, the revised dataset covers 203 jurisdictions and it is a subset of the broader Global Financial Development Database.

All indicators have been recalculated for the entire time period to ensure higher quality and consistency over time. The file contains a sheet with definitions and sources. For more detailed definitions and descriptions of the underlying sources, please see the working papers below.

Thierry Tressel, Nan Zhou and Jeanne Verrier prepared this update of the database.

An additional compressed file contains files with macroeconomic and institutional data averaged over the period 1980-95 that have been used as dependent or controlling variables by some of the authors in recent papers. To access the compressed file please click on this self-extracting zip file : download the file, do a File, Run, and the files will be extracted.

Beck, Demirgüç-Kunt, and Levine (2000) describe the sources and construction of, and the intuition behind, different indicators and present descriptive statistics of the Financial Development and Structure dataset.

Čihák, Demirgüç-Kunt, Feyen, and Levine (2012) discuss the related Global Financial Development Database, which encompasses all the statistics from the Financial Development and Structure dataset, plus several additional series.

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What Will Technology Do to Financial Structure?

This paper looks at how advances in information and telecommunications technologies have been changing the structure of the financial system by lowering transaction costs and reducing asymmetric information. Households and smaller businesses can now raise funds in securities markets as financial institutions have become better at unbundling risks while financial products can be distributed more efficiently through electronic networks. These changes have reduced the role of traditional financial intermediaries overall efficiency by lowering the costs of financial contracting. Despite these benefits technological progress presents policymakers with some important challenges. First markets for financial products become larger and more contestable, defining geographic and product markets narrowly becomes more problematic. Second, financial consolidation and the trend towards new activities of financial intermediaries require the exploration of new methods to preserve the safety and soundness of the financial system. A combined system of vigilant supervision and constructive ambiguity to deal with failures of larger institutions should be capable of mitigating the potential for increased risk-taking and help preserve the health of the financial system.

• Acknowledgements and Disclosures

MARC RIS BibTeΧ

Download Citation Data

Published Versions

Litan, Robert and Anthony Santomero (eds.) Brookings-Wharton Papers on Financial Services. Brookings Institution Press, 1999.

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In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

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Research Methods: A Student's Comprehensive Guide: Structure

• Research Approaches
• Types of Sources
• Accessing Resources
• Evaluating Sources
• Question Crafting
• Search Strategies
• Annotated Bibliography
• Literature Reviews
• Citations This link opens in a new window

Research Paper

Welcome to the art of crafting a research paper! Think of this as your roadmap to creating a well-structured and impactful study. We’ll walk you through each crucial component—from introducing your topic with flair to wrapping up with a strong conclusion. Whether you're diving into your first research project or polishing your latest masterpiece, this guide is here to make the journey smoother and more enjoyable. Get ready to turn your research into a compelling narrative that not only showcases your findings but also captivates your readers.

• Paper Snapshot

Introduction

Methodology, research paper structure: a snapshot.

Before diving into the individual components, let's take a quick look at the full structure of a research paper. This snapshot will help you visualize how each section fits together to form a cohesive and well-organized paper.

• Introduce your topic and research question.
• Provide background and context to set up your study.
• Summarize relevant existing research.
• Highlight key studies, theories, and gaps in the literature.
• Describe your research design and methods.
• Explain your data collection and analysis processes.
• Present your findings clearly.
• Use visuals, like charts and tables, to enhance understanding.
• Analyze and interpret the results.
• Discuss the broader implications of your findings and acknowledge limitations.
• Recap your key findings.
• Suggest areas for future research and offer final reflections.

With this snapshot, you now have a high-level view of the main components of your research paper. You can explore each section in detail in the following tabs.

The introduction serves as your reader's first impression of your paper. It should draw them in with a compelling overview of your topic, clearly outline your research question or thesis, and establish the importance of your study.

Key Components

Opening Statement

• Start strong with an attention-grabbing hook: a striking fact, thought-provoking quote, or an interesting anecdote that relates to your research.

Background Information

• Provide necessary context to help readers understand the relevance and scope of your study. You can include key historical information, theoretical context, or a brief overview of previous research.

Research Question or Thesis Statement

• This is the heart of your introduction. State your research question or thesis in a clear, concise manner, so readers know exactly what you are investigating.

Scope and Objectives

• Clearly define the boundaries of your research. What will your paper cover, and what will it not address? This helps frame your work for readers.

Significance of the Study

• Explain why your research matters. Does it fill a gap in existing research? Is it practically useful? Emphasize the value and contribution your paper brings to the field.

Tips for Crafting a Strong Introduction

• Be Engaging:  Your opening should grab attention and encourage the reader to keep going.
• Be Clear:  Avoid ambiguity—clearly state your research question and purpose.
• Provide Context:  Background information is essential to help the reader understand the topic, but avoid overwhelming them with too much detail at this stage.
• Stay Focused:  Keep the introduction concise but informative, setting the tone for the rest of your paper.

Literature Review

The literature review is where you showcase the existing research that relates to your topic. It's your chance to demonstrate your understanding of the academic conversation and position your research within that context.

Summarizing Existing Research

• Review relevant studies, theories, and findings that directly relate to your research question. This provides a foundation for your paper and shows that your study is grounded in the existing body of work.

Highlighting Key Studies

• Identify the most influential or significant research in your field. These are the works that have shaped the current understanding of your topic, and they should be emphasized in your review.

Identifying Gaps or Controversies

• Point out areas where there is limited research, conflicting findings, or ongoing debates. These gaps or discrepancies provide justification for your own research.

Establishing Your Research’s Relevance

• Explain how your research contributes to the field. Whether you’re addressing a gap, building on existing studies, or proposing something new, clearly indicate how your work fits into the larger picture.

Tips for a Strong Literature Review

• Stay Focused:  Only include studies that are directly relevant to your research question. Avoid summarizing every piece of literature you've read.
• Be Critical:  Don’t just summarize—critically assess the strengths and weaknesses of the studies you include.
• Organize Effectively:  Structure your review in a logical order, grouping studies by themes, methodologies, or findings.
• Show Connections:  Discuss how different studies relate to one another and to your research. This helps build a coherent narrative.

The methodology section details how you conducted your research. This is where you explain your approach, so others can understand and potentially replicate your study.

Research Design

• Outline the overall design of your study. Are you using qualitative, quantitative, or mixed methods? Define the type of research you're conducting (e.g., case study, survey, experiment).

Data Collection

• Explain how you gathered your data. Were interviews conducted? Surveys distributed? Or perhaps you collected data through observation or archival research. Be specific about the tools, instruments, or platforms you used.

Participants and Sampling

• If applicable, describe your sample group. Who participated in your study? How were they selected? Include details like the size of your sample and any inclusion/exclusion criteria.

Data Analysis

• Discuss how you analyzed your data. Did you use statistical methods, thematic analysis, coding, or another technique? Make sure to explain why these methods were appropriate for your research question.

Ethical Considerations

• Briefly mention any ethical protocols you followed, such as obtaining consent from participants or ensuring anonymity. If your research involved sensitive topics, this is especially important to address.

Tips for Writing Your Methodology

• Be Detailed but Clear:  Provide enough detail so your methods can be understood or replicated, but avoid overloading with unnecessary jargon.
• Justify Your Choices:  Explain why you chose specific methods over others and how they align with your research objectives.
• Stay Organized:  Break your methodology into clear sections to improve readability and flow.

Results Tab

In the results section, you present the findings of your research. This is where you report what you discovered, without interpretation (that comes in the Discussion section). Clarity is key, especially if you are using visuals to support your findings.

Presentation of Data

• Clearly present your research results. This can include numerical data, text analysis, or findings from experiments, surveys, or interviews.

Use of Visuals

• Incorporate charts, tables, graphs, or other visuals to illustrate key points. Ensure that these visuals are well-labeled and easy to understand. Each visual should have a caption explaining what it represents.

Organizing Results

• Structure your results logically. You might choose to organize them by research question, themes, or hypotheses. Make sure there’s a clear flow, so readers can follow your findings easily.

Statistical or Analytical Reporting (if applicable)

• If you conducted statistical analysis, report your findings using appropriate measures (e.g., averages, standard deviations, significance levels). Be transparent about any statistical software or formulas used.

Relevant Findings Only

• Only include results that directly relate to your research question or hypothesis. Avoid tangents or irrelevant data.

Tips for a Clear Results Section

• Be Objective:  This is not the place for interpretation—just present the facts.
• Visual Clarity:  Ensure any visuals are clear, well-labeled, and directly support your results.
• Use Subheadings:  If you have multiple results or sections, use subheadings to organize them.
• Stick to the Findings:  Avoid analysis or speculation here; save that for the Discussion.

Discussion Tab

The discussion is where you interpret your findings. This is your opportunity to explain what the results mean, how they relate to your research question, and what implications they have for the field.

Interpretation of Results

• Explain what your results mean in the context of your research question. How do they answer the question or support (or refute) your hypothesis? Dive into the significance of the findings.

Connection to Existing Research

• Relate your findings back to the literature you reviewed earlier. How do your results compare with previous studies? Do they support or challenge existing theories?

Implications of the Study

• Discuss the broader implications of your research. What does it contribute to the field? Does it suggest changes in practice, policy, or further research avenues?

Limitations

• Acknowledge any limitations of your study. Were there constraints related to time, sample size, or methodology? Transparency about limitations adds credibility to your research.

Recommendations for Future Research

• Suggest areas where future researchers can explore. Perhaps there were aspects of the topic you couldn’t address fully, or new questions arose based on your findings.

Tips for a Strong Discussion Section

• Be Analytical:  Focus on interpretation, not just re-stating results.
• Relate to Literature:  Show how your findings fit within the broader research context.
• Be Honest About Limitations:  Acknowledging weaknesses shows thoroughness and integrity.
• Highlight the Importance:  Emphasize the practical or theoretical value of your work.

The conclusion ties everything together. It should succinctly summarize your key findings, emphasize their significance, and leave the reader with a clear understanding of what you’ve contributed to the field.

Summary of Key Findings

• Briefly restate your most important results. Focus on the findings that directly answer your research question and highlight their relevance.

Restating the Research Question/Thesis

• Revisit your original research question or thesis and clearly explain how your findings address it.

Implications and Impact

• Reinforce the broader significance of your work. How do your findings contribute to the academic field or practical applications? This is your chance to leave a lasting impression.

Recommendations for Future Research or Practice

• Suggest directions for future studies or practical steps that can be taken based on your findings. This ensures your conclusion looks forward rather than simply wrapping up.

Final Thought/Call to Action

• End on a strong note! Offer a thought-provoking statement, reflection, or call to action, encouraging further discussion or research.

Tips for a Strong Conclusion

• Be Concise:  Keep it focused—summarize, don’t rehash.
• Be Forward-Looking:  Emphasize the impact and potential future directions.
• End with Confidence:  Leave readers with a clear understanding of your research's importance.

How to Create a Clearly Structured Paper

Provides a step-by-step guide to organizing an effective essay or research paper outline, focusing on creating clear, logical sections that streamline the writing process.

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Condensed Matter > Strongly Correlated Electrons

Title: charge density waves and the effects of uniaxial strain on the electronic structure of 2h-nbse$_2$.

Abstract: Interplay of superconductivity and density wave orders has been at the forefront of research of correlated electronic phases for a long time. 2H-NbSe$_2$ is considered to be a prototype system for studying this interplay, where the balance between the two orders was proven to be sensitive to band filling and pressure. However, the origin of charge density wave in this material is still unresolved. Here, by using angle-resolved photoemission spectroscopy, we revisit the charge density wave order and study the effects of uniaxial strain on the electronic structure of 2H-NbSe$_2$. Our results indicate previously undetected signatures of charge density waves on the Fermi surface. The application of small amount of uniaxial strain induces substantial changes in the electronic structure and lowers its symmetry. This, and the altered lattice should affect both the charge density wave phase and superconductivity and should be observable in the macroscopic properties.

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