Does financial development matter for domestic investment? Empirical evidence from India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Niharika Sinha ◽  
Swati Shastri
Keyword(s):  
Financial Development ◽  
Principal Component ◽  
Domestic Investment ◽  
Bounds Testing ◽  
Causality Test ◽  
Content Type ◽  
Development Indicators ◽  
Indian Economy ◽  
Long Run ◽  
The Impact

PurposeThis paper empirically examines the impact of financial development on domestic investment in India for the period 1989–2017.Design/methodology/approachThis study employs the autoregressive distributed lag (ARDL) bounds testing approach to co-integration to test the long-run relationship between financial development and domestic investment. To test the direction of causality, Toda–Yamamoto causality test and vector error correction model (VECM) Granger causality/Block Exogeneity Wald test have been employed. Investment has been measured by Gross Capital Formation. To capture various aspects of financial development in India, eight alternative indicators (both bank based and market based) have been used. With the help selected indicators, a composite index (FINDEX) of financial development has been constructed using principal component analysis (PCA).FindingsThe estimated result finds evidence in favour of positive, short-run and long-run impact of financial development on investment in the Indian economy. Both bank-based and market-based indicators are found to significantly affect the level of investment. The significant effect of efficiency-based financial development indicators (both bank based and market based) upon domestic investment implies that there is a need to implement policies that ensure the efficiency of financial intermediation.Originality/valueTo the best of authors' knowledge, not much research has been done to explore the relationship between financial development and domestic investment, especially in the case of Indian economy. This study also tries to find the impact of bank-based and market-based financial development indicators upon domestic investment to explore banks vs market issue.

Do market size and financial development indicators affect human capital of select south Asian economies?

2019 ◽  
Vol 46 (7) ◽  
pp. 887-903 ◽  
Author(s):  
Narayan Sethi ◽  
Bikash Ranjan Mishra ◽  
Padmaja Bhujabal
Keyword(s):  
Growth Rate ◽  
Human Capital ◽  
Financial Development ◽  
South Asian ◽  
Market Size ◽  
Content Type ◽  
Development Indicators ◽  
Long Run ◽  
Asian Economies ◽  
The Impact

Purpose The purpose of this paper is to empirically investigate whether market size and its growth rate, along with financial development indicators, affect human capital in selected south Asian economies over the time period from 1984 to 2015. Design/methodology/approach The stationarity of the variables are checked by LLC, IPS, ADF and Phillips–Perron panel unit-root tests. Pedroni’s and Kao’s panel co-integration approaches are employed to examine the long-run relationship among the variables. To estimate the coefficients of co-integrating vectors, both PDOLS and FMOLS techniques are used. The short-term and long-run causalities are examined by panel granger causality. Findings From the empirical results, the authors found that both the market size and financial development play an important role in the development of human capital in the selected south Asian economies. It is evident that a large market size and faster degree of financial development in the selected countries result in better human capital formation. Originality/value There are a number of studies on the impact of financial development indicators on human capital and economic growth, but there is hardly any study that considers market size and its growth rate along with financial development indicators with human capital in the context of south Asian economies. The study fills this research gap.

The impact of financial development, economic growth and energy consumption on environmental degradation

2015 ◽  
Vol 26 (5) ◽  
pp. 666-682 ◽  
Author(s):  
Madhu Sehrawat ◽  
A K Giri ◽  
Geetilaxmi Mohapatra
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Financial Development ◽  
Environmental Degradation ◽  
Series Data ◽  
Development Economic ◽  
Content Type ◽  
Indian Economy ◽  
Long Run ◽  
The Impact

Purpose – The purpose of this paper is to investigate the impact of financial development, economic growth and energy consumption on environment degradation for Indian economy by using the time series data for the period 1971-2011. Design/methodology/approach – The stationary properties of the variables are checked by ADF, DF-GLS, PP and Ng-Perron unit root tests. The long-run relationship is examined by implementing the Autoregressive Distributed Lag bounds testing approach to co-integration and error correction method (ECM) is applied to examine the short-run dynamics. The direction of the causality is checked by VECM framework and variance decomposition is used to predict exogenous shocks of the variables. Findings – The empirical evidence confirms the existence of long-run relationship among the variables. Financial development appears to increase environmental degradation in India. The main contributors to environmental degradation are: economic growth, energy consumption financial development and urbanization. The results also lend support to the existence of environmental Kuznets curves for Indian economy. Research limitations/implications – The present study suggests that environmental degradation can be reduced at the cost of economic growth or energy efficient technologies should be encouraged to enhance the domestic product with the help of financial sector by improving environmental friendly technologies from advanced economies. Originality/value – This paper proposes to make a contribution to the existing literature through examining the relationship between financial development and environmental degradation in Indian economy during 1971-2011 by employing modern econometric techniques.

Exports, financial development and economic growth in Pakistan

2014 ◽  
Vol 13 (2) ◽  
pp. 155-170 ◽  
Author(s):  
Muhammad Shahbaz ◽  
Mohammad Mafizur Rahman
Keyword(s):  
Economic Growth ◽  
Error Correction ◽  
Financial Development ◽  
Error Correction Model ◽  
Causality Analysis ◽  
Bounds Testing ◽  
Causality Test ◽  
Correction Model ◽  
Content Type ◽  
Long Run

Purpose – This paper aims to explore the relationship between exports, financial development and economic growth in case of Pakistan. Design/methodology/approach – The autoregressive distributed lag bounds testing approach to cointegration and error correction model are applied to test the long-run and short-run relationships, respectively. The direction of causality between the variables is investigated by the vector error correction model Granger causality test and robustness of causality analysis is tested by applying innovative accounting approach. Findings – The analysis confirms cointegration for the long-run relation between exports, economic growth and financial development in case of Pakistan. The results indicate that economic growth and financial development spur exports growth in Pakistan. The causality analysis reveals feedback hypothesis that exists between financial development and economic growth, financial development and exports, and, exports and economic growth. Originality/value – This study provides new insights for policy makers to sustain exports growth by stimulating economic growth and developing financial sector in Pakistan.

scholarly journals Re-examining the impact of financial intermediation on economic growth: evidence from Turkey

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ibrahim Nandom Yakubu ◽  
Aziza Hashi Abokor ◽  
Iklim Gedik Balay
Keyword(s):  
Economic Growth ◽  
Financial Intermediation ◽  
Composite Index ◽  
Principal Component ◽  
Annual Data ◽  
Bounds Testing ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
The Impact

PurposeThis study seeks to investigate the impact of financial intermediation on economic growth in Turkey using annual data spanning 1970–2017.Design/methodology/approachBased on the results of the augmented Dickey–Fuller and Phillips–Perron unit root tests for stationarity, the authors employ the Autoregressive Distributed Lag (ARDL) bounds testing to cointegration to establish the long-run impact of financial intermediation alongside other control factors on economic growth. The study also examines the short-run relationship between financial intermediation and economic growth by estimating the Error Correction Model (ECM).FindingsThe authors’ findings indicate that financial intermediation significantly influences economic growth in both short and long run. However, the effect is positive only in the short run, lending support to the supply-leading hypothesis. Regarding the control variables, the authors observe that while financial openness shows a positive significant impact on economic growth in the long run, gross fixed capital formation matters only in the short run. The results further infer that regardless of the time period, inflation impedes economic growth.Originality/valueIn the empirical analysis of the relationship between financial intermediation and economic growth, financial intermediation is always measured using a single variable. The authors argue that such studies could produce bias and misleading results given that a single proxy does not adequately reflect financial intermediation activities. Likewise, such findings may delude policy implementation. To provide a more vivid and robust analysis, the authors employ the Principal Component Analysis (PCA) to construct a composite index for financial intermediation based on three broad measures. The researchers’ are unaware of any study on the financial intermediation–economic growth nexus using a composite index of financial intermediation. Thus, this paper fills this lacuna in the literature.

The relationship between financial development indicators and human development in India

2014 ◽  
Vol 41 (12) ◽  
pp. 1194-1208 ◽  
Author(s):  
Madhu Sehrawat ◽  
A.K. Giri
Keyword(s):  
Human Development ◽  
Financial Development ◽  
Decomposition Analysis ◽  
Variance Decomposition ◽  
Annual Data ◽  
Content Type ◽  
Development Indicators ◽  
Long Run ◽  
The Impact ◽  
The Relationship

Purpose – The purpose of this paper is to examine the relationship between financial development indicators and human development in India using annual data from 1980-2012. Design/methodology/approach – The Ng-Perron unit root test is used to check for the order of integration of the variables. The long run relationship and short run dynamics are examined by implementing the ARDL bounds testing approach to co-integration. Granger’s non-causality test and variance decomposition techniques are also used to examine the impact of financial development indicators on human development. Findings – The results confirm a long run relationship among the variables. The results of granger non causality indicate that unidirectional causality runs from financial development indicators to human development index (HDI). The variance decomposition analysis shows that among all the financial indicators, broad money supply (M3) has the largest contribution to changes in human development in India. Research limitations/implications – The present study recommends for appropriate reforms in financial market to attain sustainable human development in India. The findings will be useful for India’s policy makers, in order to maintain the parallel expansion of financial development and human development. Originality/value – This paper is first of its kind to empirically examine the casual relationship between financial development indicators and human capital development proxied by HDI in India by using modern econometric techniques.

scholarly journals The drivers of economic growth in China and India: globalization or financial development?

2017 ◽  
Vol 16 (1) ◽  
pp. 54-84 ◽  
Author(s):  
Magda Kandil ◽  
Muhammad Shahbaz ◽  
Mantu Kumar Mahalik ◽  
Duc Khuong Nguyen
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Emerging Market ◽  
Annual Data ◽  
Test Results ◽  
Causality Test ◽  
Content Type ◽  
China And India ◽  
Integration Test ◽  
The Impact

Purpose Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing capital and inflation and drawing comparisons between the two fastest growing emerging market economies. Design/methodology/approach In the long run, co-integration test results indicate that financial development increases economic growth in China and India. Findings The results also reveal that globalization accelerates economic growth in India but, surprisingly, impairs economic growth in China, as it increases competition for exports. The results furthermore disclose that acceleration in capitalization and inflation, as a proxy for aggregate demand, are positively linked to economic growth in China and India. Originality/value Causality test results indicate that both financial development and economic growth are interdependent. In contrast, causality runs from higher economic growth to increased globalization in India, while the results do not support long-term causality between globalization and economic growth in China.

The relationship between financial development and economic growth in Eswatini (formerly Swaziland)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siphe-okuhle Fakudze ◽  
Asrat Tsegaye ◽  
Kin Sibanda
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Financial Development ◽  
Granger Causality Test ◽  
Causality Test ◽  
Content Type ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThe paper examined the relationship between financial development and economic growth for the period 1996 to 2018 in Eswatini.Design/methodology/approachThe Autoregressive Distributed Lag bounds test (ARDL) was employed to determine the long-run and short-run dynamics of the link between the variables of interest. The Granger causality test was also performed to establish the direction of causality between financial development and economic growth.FindingsThe ARDL results revealed that there is a long-run relationship between financial development and economic growth. The Granger causality test revealed bidirectional causality between money supply and economic growth, and unidirectional causality running from economic growth to financial development. The results highlight that economic growth exerts a positive and significant influence on financial development, validating the demand following hypothesis in Eswatini.Practical implicationsPolicymakers should formulate policies that aims to engineer more economic growth. The policies should strike a balance between deploying funds necessary to stimulate investment and enhancing productivity in order to enliven economic growth in Eswatini.Originality/valueThe study investigates the finance-growth linkage using time series analysis. It determines the long-run and short-run dynamics of this relationship and examines the Granger causality outcomes.

Does Ban on Futures trading (de)stabilise spot volatility?

2019 ◽  
Vol 9 (2) ◽  
pp. 145-166 ◽  
Author(s):  
Neharika Sobti
Keyword(s):  
Granger Causality ◽  
Price Discovery ◽  
Futures Trading ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
The Impact ◽  
Spot Volatility ◽  
Non Parametric

Purpose The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility. Design/methodology/approach The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis. Findings The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility. Originality/value This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.

scholarly journals DOES FINANCIAL DEVELOPMENT HAMPER ECONOMIC GROWTH: EMPIRICAL EVIDENCE FROM BANGLADESH

2012 ◽  
Vol 14 (3) ◽  
pp. 558-582 ◽  
Author(s):  
Qazi Muhammad Adnan Hye ◽  
Faridul Islam
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Principal Component ◽  
Distributed Lag ◽  
Window Method ◽  
Long Run ◽  
Rolling Window ◽  
Augmented Dickey Fuller ◽  
The Stability ◽  
The Impact

The objective of this study is twofold. (a) Construct the first ever financial development index (FDI) for Bangladesh using the principal component method (PCM). (b) Use the FDI to explore the existence of a long run relationship between FDI and economic growth. The Augmented Dickey Fuller and the Ng-Perron unit root tests have been applied to examine the stationarity properties of the series. To explore a long run relation, the Autoregressive Distributed Lag (ARDL) approach to cointegration; and to assess the stability of the parameters, the rolling window regression approach have been used. The results show that the impact of real interest rate (RIR) and FDI on economic growth is negative. Estimates from rolling window method show that FDI and RIR are negatively related to economic growth for the years 1987–1988, 1992–1999, 2002–2006, 2008 and 2009; and 1986–1998, 2006 and 2007, respectively. The results may help policymakers formulate effective financial sector policies as a tool to promote economic growth in Bangladesh.

scholarly journals Do financial systems spur economic growth in the USA? An empirical investigation

2019 ◽  
Vol 66 (2) ◽  
pp. 165-185
Author(s):  
Sheilla Nyasha ◽  
N.M. Odhiambo
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Positive Impact ◽  
The United States ◽  
Bounds Testing ◽  
Financial Systems ◽  
Development Indicators ◽  
Distributed Lag ◽  
Long Run ◽  
The Usa

In this paper, we use the autoregressive distributed lag (ARDL) bounds testing approach to examine the dynamic impact of both bank-based financial development and market-based financial development on economic growth in the United States of America (USA) during the period 1980 to 2012. In order to adequately capture the depth and width of the USA?s financial system, we used both bank-based and marketbased financial development indices as proxies for bank-based and market-based financial systems. These indices were constructed from a number of bank- and market-based financial development indicators, using the method of means-removed average. Our empirical results reveal that both bank-based and market-based financial development have a positive impact on economic growth in the USA. These results apply irrespective of whether the regression analysis is conducted in the long run or in the short run. We, therefore, recommend that both pro-bank-based and pro-market-based financial sector development policies should be pursued in the USA - in order to bolster real sector growth and economic development.

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