Asymmetric fiscal multipliers in India – Evidence from a non-linear cointegration

ABSTRACT

We attempted to scrutinize the efficacy of fiscal policy tools on key macroeconomic variables in case of India. Applying an asymmetric cointegration framework, the impact of public spending hike on output growth is significantly favourable and that of the decrease in it is insignificant. Similarly, effect of tax hikes is more pronouncing than tax cuts. Comparatively, results report more effectiveness of spending hikes than the tax cuts to avoid an economic downturn and tax hikes than spending cuts to cool down a heating economy. Private consumption mimics response of output growth, whereas response of private investment follows the substitutability hypothesis.

KEYWORDS:

• Fiscal Policy
• output growth
• private investment
• private consumption
• asymmetry
• India

Acknowledgements

We thank Greenwood Nimmo for providing estimation codes of NARDL model. We also thank the editorial staff of this journal and anonymous referees for the useful comments and meticulous evaluation of our work. Usual disclaimer applies.

Disclosure statement

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

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. A positive shock may have a larger impact in short run and a negative shock is found to be more influential in long run (or vice-versa).

2. For additional technical details refer to Shin, Yu, and Greenwood-Nimmo (2014).

3. The model resorts to reduced form data generating process for the weakly endogenous variable by appropriately expanding the lag lengths to correct for autocorrelation and endogeneity (Shin, Yu, and Greenwood-Nimmo 2014). Therefore, the possibility of feedback causality from the output growth to fiscal policy tools through the automatic stabilizers could be handled econometrically.

4. In this case the model boils down to the standard symmetric ARDL model given by Pesaran and Shin (1998).

5. ‘If the seasonally adjusted data is used to apply unit root tests, this will result in the biased test statistics for ADF, PP or other conventional test towards the non-rejection of null of unit root. Therefore in an asymptotic manner, it is preferred to study the seasonally unadjusted data for more power of unit root tests’ (Maddala and Kim 1998).

6. Results are not reported to save the space and are available on request.

7. The deseasonalization of the variables like GE, TR and GDP is mandated by the much noted ‘March Rush’ or the ‘end of season’ situations observed at the end of a financial year in case of India (Goyal and Sharma (2018).

8. The study has used the annual observations of current, capital and total expenditures in 1(a) and (b), since the data at the quarterly frequency for tax and spending components is not available consistently.

9. The short-run response of GR, LCON and LPI are not reported to save the space, however an intuitive look can be taken from the cumulative dynamic multipliers and it can be inferred that the results are largely in accordance with the existing theoretical analogies. If needed, results are available on request.

Additional information

Notes on contributors

Javed Ahmad Bhat

Javed Ahmad Bhat was a doctoral candidate at the School of Economics, University of Hyderabad, Hyderabad, India. His research interests include Empirical Macroeconomics, International Finance and Applied Time Series Analysis.

Naresh Kumar Sharma

Naresh Kumar Sharma is Professor and Dean School of Economics, University of Hyderabad, Hyderabad, India. His research areas include Economic Theory, Gandhian Economic Thought, Development, Science and Technology. He has taught courses such as Macroeconomics, Mathematical Finance, General Equilibrium, Microeconomics, Social Choice Theory and Time Series Econometrics.