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Finance growth nexus across Indian states: evidences from panel cointegration and causality tests

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Abstract

The paper deals with finance-growth relationship across Indian states over 1980–2011 in panel cointegration and causality framework. We apply Engle–Granger two-step procedure for cointegration test in panel setting which takes care of cross-sectional dependence and heterogeneity across states. For panel Granger causality analysis, we employ Dumitrescu and Hurlin (Econ Model 29:1450–1460, 2012) method and apply bootstrapping to account for cross-sectional dependence. We find robust evidence of cointegration between per capita income and credit per capita. Using panel FMOLS, we find that 1 % change in credit per capita results in 0.14 % change in per capita income. Panel Granger causality test reveals that there is bi-directional causality (feedback effects) in the absence of cross-sectional dependence. However, with cross-sectional dependence, we find evidence in favour of supply leading hypothesis. Probable policy implication calls for inclusive financial development and growth strategies in order to mitigate uneven income levels across states.

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Notes

  1. Patrick (1966) characterizes finance growth relationship as demand-following and supply-leading. While, in demand-following hypothesis, economic growth precedes financial development, in supply-leading hypothesis, financial development precedes economic growth.

  2. In 1969, fourteen large private banks were nationalised and again in 1980, six of largest private sector banks were nationalised.

  3. RBI provides data on credit as per place of sanction and credit as per place (state) of utilisation. Sometimes, credit sanctioned in one state may not be utilised in that state but in some other states. For instance, the use of credit sanctioned to big corporates may not be limited to only one state and the projects may be spread over several states. Therefore, we take data of credit as per place of utilisation in order to observe whether credit utilised in a given state exerts effect on states’ per capita income levels.

  4. In 2014, the Government of India introduces Jan Dhan Yojana Scheme for comprehensive financial inclusion in order to ensure greater access to different financial services and this scheme has been instrumental in mobilization of more banks deposits. Under this scheme, 149.9 0 million new bank accounts are opened and INR157.9 billion deposits are mobilized during August 2014 to April 2015, (Source: www.pmjdy.gov.in). Greater mobilization of deposits through this scheme indicates greater degree of financial inclusion.

  5. Our sample consists of the following states: Haryana, Himachal Pradesh, Punjab, Rajasthan, Delhi, Arunachal Pradesh, Assam, Manipur, Meghalaya, Tripura, Odisha, West Bengal, Andaman & Nikobar, Gujarat, Maharashtra, Andhra Pradesh, Karnataka, Kerala, Tamil Nadu and Puducherry.

  6. Econometric analysis of panel data (Baltagi 2014, pp.287–291).

  7. Pesaran (2004) test of cross-sectional dependence is based on the CD-statistic and CD ~ N (0, 1) under the null hypothesis of cross-sectional independence. CD statistic is defined as follows:

    $$CD = \sqrt {\frac{2T}{n(n - 1)}} \mathop \sum \limits_{i = 1}^{N - 1} \mathop \sum \limits_{j = i + 1}^{N} \hat{\rho }_{ij}$$

    where \(\widehat{\rho}_{ij}s\) are pair-wise correlation coefficients of OLS residuals from individual regressions of cross-sections and is given as:

    $$\widehat{\rho}_{ij} = \widehat{\rho}_{ji} = \frac{{\mathop \sum \nolimits_{i = 1}^{T} e_{it} e_{jt} }}{{(\mathop \sum \nolimits_{t = 1}^{T} e_{it}^{2} )^{1/2} (\mathop \sum \nolimits_{t = 1}^{T} e_{jt}^{2} )^{1/2} }}$$
    Table 2 Pesaran (2004) test of cross-sectional dependence
    Full size table
    Table 3 Pesaran (2007) panel unit root test with cross-sectional dependence
    Full size table

  8. Results based on first generation panel unit root tests in the absence of cross sectional dependence are the same as those obtained above based on Pesaran (2007) second generation panel unit root tests. These results are reported in appendix (Table 7).

  9. As suggested by one of the reviewers, we also conduct (Phillips and Ouliaris 1990) test to check co-integration in panel context. For this purpose, we constructed Fisher statistic (1932) to test cointegration in panel context as follows: \(F = - 2\mathop \sum \nolimits_{i = 1}^{n} \ln \left( {p_{i} } \right)\) where n denotes number of cross-sections and \(p_{i}\) is the p value corresponding to Philips–Ouilaris test statistic of ith cross-section. The null hypothesis of panel cointegration test is that there is no cointegration in any of the cross-sectional units against the alternate hypothesis that there is cointegration in at least one of the cross-sectional units. If the individual cross-sections are independent, then test statistic \(F\sim\chi_{2n}^{2}\). From Table 9 (in Appendix), we observe that panel statistic is significant at 1 % level of significance which indicates presence of stable long-term cointegration relationship between both measures of financial development and economic growth.

  10. For methodological details of FMOLS and DOLS, see Pedroni (2000), Stock and Watson (1993), Kao and Chiang (2000) and Nelson and Sul (2003).

  11. As the paper focuses on cointegration and causality in panel framework, we present only panel statistics for Emirmahmutoglu and Kose (2011) method. Results corresponding to individual cross-sections are available on request from authors.

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  1. Indian Institute of Technology Ropar, Rupnagar, Punjab, India

    Rajesh Sharma & Samaresh Bardhan

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  1. Rajesh Sharma
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  2. Samaresh Bardhan
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Correspondence to Samaresh Bardhan.

Appendix

Appendix

See Tables 7, 8, 9 and 10.

Table 7 First generation panel unit root tests
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Table 8 First generation panel cointegration tests
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Table 9 Philips–Ouilaris panel cointegration test
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Table 10 Results from bootstrap panel Granger causality with EK method
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Sharma, R., Bardhan, S. Finance growth nexus across Indian states: evidences from panel cointegration and causality tests. Econ Change Restruct 50, 1–20 (2017). https://doi.org/10.1007/s10644-015-9178-2

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