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Macroeconomic shocks and evolution of term structure of interest rate: A dynamic latent factor approach

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Abstract

It is imperative to assess the impact of macroeconomic shocks on the health of financial institutions under macro-prudential surveillance, which percolate through interest rate risk, because any change in the interest rate term structure would affect their profit and loss account through income from interest earning assets and expenses on interest bearing liabilities. Accordingly, this paper empirically evaluates impact of key macroeconomic variables, namely, output gap, inflation and policy rate on the term structure of the Indian G-sec using latent factor model. First, level, slope and curvature of the yield curve were modelled dynamically through dynamic latent factor model and then these factors were linked to the macroeconomic variables using vector autoregressive framework. The empirical findings show a strong evidence of the effects of macroeconomic shocks on future movements in the yield curve.

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Notes

  1. Testimony of Chairman Alan Greenspan, Before the Subcommittee on Capital Markets, Securities and Government Sponsored Enterprises of the Committee on Banking and Financial Services, U.S. House of Representatives, March 19, 1997 (https://www.federalreserve.gov/BOARDDOCS/TESTIMONY/19970319.htm).

  2. The APT is an asset-pricing model, which presume that an asset’s returns can be predicted using the relationship between that asset and many common risk factors like macroeconomic variables.

  3. A Markov process is a random process in which the future is independent of the past, given the present.

  4. Diebold and Li show that β2 corresponds to the negative of slope, which is traditionally defined as ‘long minus short yields’. However, for ease of discussion, we prefer simply to call β2 as slope which is defined as slope as ‘short minus long yields’.

  5. Authors are grateful to Sergio Salvino Guirreri for preparing and sharing R-package on ‘Yield Curve’ which facilitate estimation of the selected factor model in R.

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Acknowledgements

Views expressed in the paper are of authors’ own and not of the institutions to which they belong. Authors are thankful to the anonymous referee(s) for their valuable suggestions.

Author information

Authors and Affiliations

  1. Department of Statistics and Information Management, Reserve Bank of India, C-8, 6th Floor, BKC, Bandra East, Mumbai, 400051, India

    Sanjay Singh

  2. Mumbai School of Economics and Public Policy, University of Mumbai, Mumbai, 400098, India

    Neeraj Hatekar

Authors
  1. Sanjay Singh
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  2. Neeraj Hatekar
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Corresponding author

Correspondence to Sanjay Singh.

Appendices

Appendix 1: Yield of G-secs—Actual vis-à-vis estimate

figure a
figure b

Appendix 2: Parameter estimate of the VAR model

 

LEVEL

SLOPE

CURVATURE

OUTPUT_GAP

RR

INFLATION

LEVEL (− 1)

0.559 [1.447]

0.197 [0.411]

0.681 [0.751]

0.574 [0.657]

0.480 [2.961]

0.614 [0.889]

LEVEL (− 2)

0.208 [0.557]

− 0.177 [-0.383]

− 0.494 [− 0.565]

0.676 [0.803]

− 0.458 [− 2.930]

− 0.487 [− 0.731]

SLOPE (− 1)

0.184 [0.964]

0.360 [1.524]

− 0.266 [− 0.593]

− 0.340 [− 0.789]

0.106 [1.328]

− 0.083 [− 0.243]

SLOPE (− 2)

0.126 [0.601]

0.111 [0.427]

− 0.414 [− 0.839]

0.218 [0.458]

− 0.089 [− 1.004]

− 0.415 [− 1.105]

CURVATURE (− 1)

0.113 [0.944]

− 0.037 [− 0.250]

0.373 [1.329]

0.037 [0.135]

0.097 [1.940]

0.114 [0.534]

CURVATURE (− 2)

− 0.042 [− 0.382]

− 0.055 [− 0.407]

− 0.045 [− 0.174]

0.268 [1.090]

− 0.172 [− 3.769]

0.067 [0.344]

OUTPUT_GAP (− 1)

− 0.016 [− 0.197]

0.152 [1.490]

0.098 [0.504]

0.489 [2.630]

0.039 [1.142]

0.080 [0.542]

OUTPUT_GAP (− 2)

0.010 [0.116]

0.071 [0.704]

0.019 [0.097]

0.016 [0.085]

0.067 [1.967]

− 0.110 [− 0.755]

RR (− 1)

0.146 [0.343]

0.117 [0.220]

− 2.073 [− 2.075]

-0.712 [− 0.740]

0.916 [5.128]

0.270 [0.355]

RR (− 2)

− 0.503 [− 1.318]

0.391 [0.828]

2.099 [2.348]

− 0.113 [− 0.131]

− 0.114 [− 0.715]

0.098 [0.144]

INFLATION (− 1)

− 0.087 [− 0.996]

0.127 [1.176]

0.089 [0.433]

− 0.280 [− 1.423]

0.009 [0.257]

1.192 [7.663]

INFLATION (− 2)

0.153 [1.718]

− 0.154 [− 1.398]

− 0.263 [− 1.262]

0.097 [0.482]

0.005 [0.136]

− 0.405 [− 2.549]

C

4.156 [1.970]

− 3.926 [− 1.503]

− 0.761 [− 0.153]

− 3.342 [− 0.701]

1.214 [1.373]

− 3.149 [− 0.836]

R-squared

0.43

0.66

0.57

0.55

0.92

0.88

ADJ. R-squared

0.23

0.54

0.41

0.39

0.90

0.83

  1. The numbers given in parentheses are T-statistics

Appendix 3: Residual diagnostics of VAR(2) model

See Tables 5, 6 and Fig. 5.

Table 5 VAR lag order selection criteria
Full size table
Table 6 Tests for serial correlation and normal distribution
Full size table
Fig. 5
figure 5

Test for stability of the VAR model

Full size image

Appendix 4: Generalised impulse response function

figure c

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Singh, S., Hatekar, N. Macroeconomic shocks and evolution of term structure of interest rate: A dynamic latent factor approach. Ind. Econ. Rev. 53, 245–262 (2018). https://doi.org/10.1007/s41775-018-0019-x

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