Central Bank Independence and Inflation in India: The Role of Financial Development

Abstract

Using a legal or de jure measure of central bank independence, the present study attempts to examine the impact of central bank independence (CBI) on the inflation in case of Indian economy over the period, 1991–1992 to 2018–2019. To ascertain the possible dependence of association on the institutional quality proxied by level of financial development, we incorporated a non-linear logistic smooth transition framework with ratio of private credit to GDP as an appropriate transition variable. We found a statistically significant regime dependency with respect to the impact of CBI on inflation. In both the short-run and long run, increase in value of CBI is found to increase inflation when the level of financial development is below threshold value, however, beyond this threshold, any increase in CBI would decrease it. The impact of other control variables like GDP growth, oil price inflation & lagged inflation is found to be positive and statistically significant. However, currency appreciation is found to lower inflation. Our findings signify an appreciable role for the degree of financial development in the transmission of central bank’s monetary policy stances to maintain low inflation.

Keywords:

• Inflation
• Central Bank Independence
• Financial Development
• LSTR
• India

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Dynamic inconsistency is a situation in which a policy maker’s preferences and decisions change over time that the decisions made became inconsistent in future.

2 For instance, the pre-requisite condition of nations to join the European Economic Community (EEC) was low inflation.

3 Seigniorage refers to the profit realized by the government authorities by printing the money. It is the difference between costs of printing the currency and its face value.

4 By credit channel transmission mechanism, the policies of central bank affect the amount and volume of credit in the economy.

5 For detailed discussion regarding each criterion see Jasmine et al. (2019).

6 The coding regarding disaggregated variables and additional details regarding the components and sub-components is not reported to save the space and can be made available on request.

7 The Tables 1(A) and 2(A) are given in the Appendix-I.

8 If $\mathrm{\gamma }\to \infty ,$ LSTR model changes to a two-regime switching regression model with an abrupt transition and if $\mathrm{\gamma }=0$ and $F\left(s_t;\gamma ,c\right)\equiv 0,$ LSTR model trims down to a linear model.

10 The values of grid search for $\mathrm{\gamma }$ were set between 0 & 100 for increments of 1 and that of $c$ was estimated for all the ranked values of transition variable $s_t.$

11 However, it may be noted that $\mathrm{\gamma }$ is not sacle-free and as such it is standardised by dividing it with the sample standard deviation of transition variable $s_t$ denoted as ${\sigma }_s^{̂}.$

12 The selection of the analysis period is purely decided according to data availability regarding various policy documents or other components and subcomponents of CBI index and other variables.

13 The less sensitiveness of final consumer goods to exchange rate changes is mainly due to the fact that the imported goods or tradable goods, have to go through a distribution chain of pricing. Like from import prices to producer prices and then finally to consumer prices. In this due course of process, significant local value addition is made and passes through different market structure of retail chains (Bhat & & Bhat, 2022).