The degree of financial inclusion has important implications for firms and households in many emerging and developing economies. Without access to formal financial institutions, and with relatively underdeveloped capital markets, firms may need to rely on retained earnings, or informal sources of funding for investment. Similarly, households may need to use their savings, or borrow from informal sources at exorbitant interest rates, to invest in human capital or start up small businesses. This underscores the importance of access to finance for economic growth and the promotion of income equality (e.g., Beck et al. 2007; Burgess and Pande 2005). Indeed, financial inclusion has been suggested to be “a tool for addressing critical issues of persistent poverty and underdevelopment” (Alliance for Financial Inclusion 2012, p. 6).
- Interest Rate
- Monetary Policy
- Central Bank
- Real Interest Rate
- Food Price
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The views expressed in this chapter are those of the authors and do not necessarily reflect those of the Bank for International Settlements or the Reserve Bank of India. Tracy Chan, Steven Kong, and Giovanni Sgro provided excellent research assistance. We are grateful to participants at seminars at the Bank for International Settlements and the Reserve Bank of India, the HKUST IEMS-CAG Workshop on “Understanding Financial Inclusion in Asia”, James Yetman, and our discussant Tomoo Kikuchi for the helpful discussions and suggestions.
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The Global Partnership for Financial Inclusion, launched by the G20 leaders to promote inclusion, has defined financial inclusion as “a state in which all working age adults, including those currently excluded by the financial system, have effective access to the following financial services provided by formal institutions: credit, savings (defined broadly to include current accounts), payments, and insurance.” See Consultative Group to Assist the Poor (CGAP 2011).
Maya Declaration is the statement of AFI network commitment to financial inclusion.
The Basel Committee on Banking Supervision; the Committee on Payments and Market Infrastructures; the International Association of Insurance Supervisors; and the International Association of Deposit Insurers.
See Di Bartolomeo and Rossi (2007) who outline this possibility in a theoretical model.
See Mehrotra and Yetman (2015) for a discussion of the implications of financial inclusion for central banks more broadly.
In some large economies, the number of persons surveyed was higher. For example, in 2014, the sample size was 3000 and more than 4000 in India and China respectively.
Both individually and jointly owned accounts are included. Account ownership numbers also include those adults who reported having a debit or an ATM card.
The sample comprises nine emerging Asian economies whose central banks are members of the BIS.
Simple averages across economies, based on data from IMF WEO.
We use 2011 instead of 2014 as the former is more relevant for the estimation sample.
We acknowledge that there are other factors beyond financial inclusion that may affect the interest rate sensitivity of output, including financial depth and financial development more broadly.
We recognise the limitations of the Hodrick-Prescott filter in estimating the output gap precisely, including the presence of end-point bias. But, since our focus is on estimating the interest rate sensitivity of output, we proceed with the HP filter as a simple and widely used methodology for estimating the output gap.
Indonesia is excluded from the second group in the panel VAR estimation due to the counterintuitive result of a persistent positive impact from an interest rate shock to inflation.
If a VAR with 1 lag is estimated instead, the impact on inflation is again larger for the economies with greater financial inclusion, while the impact on output is similar for both groups. In this case, the impact on inflation of an interest rate shock appears statistically significant for some quarters for economies with a higher degree of financial inclusion, albeit again with very large confidence intervals.
See also Prasad (2014).
See also Basu and Srivastava (2005) for the Indian case.
In the case of core inflation, the target is specified as the 20 quarter moving average of core inflation.
The sample starts in 2002Q1 for the Philippines due to the adoption of inflation targeting in 2002. Other minor differences in samples result from data availability for the different economies.
Of course, there are various reasons beyond the interaction of financial exclusion with a large share of food in the consumption basket for why central banks may prefer to target headline inflation rather than core inflation. See for example Bullard (2011).
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Mehrotra, A., Nadhanael, G.V. (2016). Financial Inclusion and Monetary Policy in Emerging Asia. In: Gopalan, S., Kikuchi, T. (eds) Financial Inclusion in Asia. Palgrave Studies in Impact Finance. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-58337-6_4
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