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Empirical Economics

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07.07.2017

Regime-switching monetary and fiscal policy rules and their interaction: an Indian case study

verfasst von: Sanchit Arora

Erschienen in: Empirical Economics | Ausgabe 4/2018

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Abstract

The recession following the sub-prime crisis has rekindled international interest in the field of monetary and fiscal policy interaction. However, very little has been done to appropriately estimate these dynamic policies. This paper estimates regime- switching monetary and fiscal policy rules and lays strong emphasis on mis-specification testing. We apply a Markov regime-switching model to estimate monetary and fiscal policy rules for India to highlight the evolving stance of Indian macro-policy for the period 1951–2008 and investigate the behaviour of select macroeconomic variables under the estimated policy regimes. Our results suggest that, in India, fiscal policy was largely active for the entire period except for a few periods of restraint. Monetary policy, despite achieving greater autonomy post-1990s, has largely been accommodating fiscal policy. Whenever monetary policy became active, fiscal policy undermined monetary policy’s effectiveness by not accommodating accordingly. We argue for an aggressive monetary policy and a constrained fiscal policy in India.

Vorheriger Artikel What matters for global food price volatility?

Nächster Artikel Exploring the dark side of tax policy: an analysis of the interactions between fiscal illusion and the shadow economy

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For monetary policy: Hutchison et al. (2013), Sims and Zha (2006), Owyang and Ramey (2004) and Francis and Owyang (2004); for fiscal policy: Hoppner and Assenmacher-Wesche (2000), Ito et al. (2007), Davig (2004), Bouthevillain and Dufrénot (2011) and Deak and Lenarcic (2012).

For example, see Davig and Leeper (2011) and Favero and Monacelli (2005).

For example, see Nordhaus (1994) and Dixit and Lambertini (2003).

Breunig and Stegman (2005) find diagnostic checks to be crucial while examining regime switches in Singapore’s gross domestic product (GDP).

Monetary policy with multiple objectives of price stability, growth and financial stability.

Under Section 17(5) of RBI Act, 1934, the RBI provides ways and means advances (WMA) to the States banking with it to help them to tide over temporary mismatches in the cash flow of their receipts and payments. Such advances are under the Act ‘\(\cdot \cdot \cdot \) repayable in each case not later than three months from the date of making that advance’. Source: Reserve Bank of India, RBI

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Rajaraman (2008) argues that state expenditures and taxes are more likely to be politically driven than central government expenditure and taxes. In this paper, however, central government expenditure and tax revenues are taken as fiscal policy variables. The results could change when state government expenditures and revenues are taken into consideration.

The US Census Bureau’s software package for seasonal adjustment.

A new CPI measure is available for India since 2011.

We could have taken the interest rate as the instrument for the entire period but that rule would not have been representative for the period. The RBI, from its documents and speeches, made it clear that money supply is what they considered to design policies for the period 1950–1989.

We use the IIP as the output indicator which is not in nominal terms as required by the McCallum rule; therefore, we include inflation in the equation as well. As a result, instead of estimating the McCallum rule, we just estimate a simplified version of it.

See “Appendix C”.

See “Appendix D”.

The average call money rate at the last month of each quarter is chosen in order to avoid endogeneity. Taking the quarterly average of an interest rate in a monetary policy rule raises the issue of reverse causality between the interest rate and inflation. It can be avoided, to a certain extent, by taking the end of the period interest rate which breaks the two-way causality between the interest rate and inflation. Another alternative is to take the interest rate at the last day of the quarter; however, in such a scenario, we might end up capturing some anomaly which may not be consistent with the overall monetary policy stance.

The results are presented for the nominal exchange rate only. The inclusion of the real exchange rate instead of the nominal exchange rate gives very similar results. The results are available from the authors on request.

The Woodford (2003) version of a monetary policy rule includes a lag of the interest rate. We estimate the rule with a lagged term of the call money rate as well, but it does not change the results significantly. Therefore, to preserve parsimony, we stick to the shorter version of the rule.

Besides the theoretical arguments for government taxes as the fiscal policy instrument, we also conduct granger causality tests. The tests indicate that at high significance levels, government taxes and government expenditure do not granger- cause each other. However, as the significance limit is relaxed, government expenditure seems to granger-cause government taxes and not the other way around. We choose this specification for the following three reasons: first, to stay in line with the related literature, second, we believe that quarterly frequency of data helps in avoiding endogeneity between government taxes and the covariates to a large extent, i.e. we do not expect a change in government taxes to affect the output gap in the same quarter because of the implementation and transmission lags, and third, from a statistical point of view, the specification considered is more cogent.

See “Appendix E”.

A vigilant reader would be puzzled with the absence of the lagged tax term in the Markov switching equation. The term was dropped after the regime-switching mis-specification tests rejected it in favour of a more parsimonious model.

See “Appendix A” for a brief explanation of the Markov switching models.

See “Appendix F” for more details.

See “Appendix F” for the results of specification testing.

Alternate specifications with the lagged values of inflation and the output gap were estimated to account for endogeneity, if any. However, they do not change the economic significance of the results. Besides, instead of \(M_3\), we also ran the regression with \(M_0\) as the policy instrument. We expected the results to not change given that \(M_3\) and \(M _0\) were highly correlated with the tune of 0.96 during this period. Not surprisingly, such an exercise did not change the results and pointed towards monetary policy’s passive stance.

“Fiscal Policy and Economic Reforms” at the National Institute of Public Finance and Policy (NIPFP) on 26 May 2008, http://www.rbi.org.in/scripts/BS_SpeechesView.aspx?Id=393.

The call money rate (CMR) has been taken as the policy rate mainly because this is the rate RBI seeks to influence with its various policy instruments. Though, at present, the official RBI policy rate is the repo rate, it only captures one policy instrument but not others. The CMR is more representative of the monetary policy stance.

Since the coefficient in regime 1 is not greater than 1, as required by Leeper (1991) to term a regime active, we checked whether the coefficient can be statistically approximated to 1 . A standard t test indicated that in fact it is not statistically different from one, thus indicating towards strong monetary policy. Regime 2 satisfies the criteria proposed by Leeper (1991).

Repo rate was used as the short-term interest rate instrument by the RBI from 2003 onwards.

Our variables are HP-detrended and are not defined as a ratio of GDP. It is difficult to conduct a direct comparison based on the restrictions proposed by Leeper (1991). Therefore, to term them active/passive, we rely on the magnitude of response, which differs substantially across the regimes in our case.

An interesting observation: None of the election years matches with the fiscal policy being passive (election years: 1952, 1957, 1962, 1971, 1977, 1980, 1984–1985, 1989, 1991, 1996, 1998, 2004).

We believe that since monetary and fiscal authorities observe information only up to a point (say 1996Q1) unaware about the future outcomes, filtered probabilities are more suited to capture the endogenous nature of policy making. The results based on smoothed probabilities are similar in nature and are available from the authors on request.

I would like to thank an anonymous referee for bringing this up.

Not discounting the fact that continuous reforms and good governance are essential to achieve such outcomes.

Comptroller and Auditor General of India, www.cga.gov.in.

The BDS test is performed using “fraction of standard deviations” as a method of choosing distance between two residuals with value 0.7 and 5000 bootstrapped simulations.

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Titel: Regime-switching monetary and fiscal policy rules and their interaction: an Indian case study
verfasst von: Sanchit Arora
Publikationsdatum: 07.07.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 4/2018
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-017-1265-y

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