Purpose: This study examined whether India’s short-run Phillips Curve was a stable, structural relationship or an episodic one over 2010–2025, extending prior Indian evidence by 14 years through the flexible inflation targeting era across four inflation channels. Design/Methodology/Approach : Using quarterly consumer price data (n = 62), the study estimated a full-sample ordinary least squares regression with a Hodrick-Prescott-filtered output gap and the real effective exchange rate as a supply-shock proxy, then tested long-run cointegration through bounds testing, structural stability through Chow tests, and time variation through rolling twelve-quarter regressions across 51 windows.

Findings: Inflation inertia dominated (β1 = 0.812, p < 0.001, R² = 0.772), and the output gap remained insignificant on average (β2 = 0.002, p = 0.949) and significant in only three of 51 rolling windows. The bounds test (F = 1.503) ruled out long-run cointegration, and policy transmission was significant only in the post-targeting period (β4 = −2.860, p < 0.05), with all Chow tests confirming stability. Practical

Implications: Rate tightening worked best when the output gap was clearly positive, and was counterproductive against food or fuel shocks. Anchoring the credibility of the inflation target remained the most reliable long-run disinflation tool. Originality/

Value: Among the first studies to apply rolling-window regression to India's quarterly Phillips Curve, the paper showed the relationship to be episodic rather than absent, with implications for central bank policy design.

1. Agrawal, S., Kaur, G., & Mittal, A. (2026). Flash sales and FOMO: Evidence from gadget impulse buying. Indian Journal of Marketing, 56(2), 44–62. https://doi.org/10.17010/ijom/2026/v56/i2/175925
2. Behera, H., Wahi, G., & Kapur, M. (2018). Phillips curve relationship in an emerging economy: Evidence from India. Economic Analysis and Policy, 59, 116–126. https://doi.org/10.1016/j.eap.2018.06.001
3. Blanchard, O., & Galí, J. (2007). Real wage rigidities and the New Keynesian model. Journal of Money, Credit and Banking, 39(s1), 35–65. https://doi.org/10.1111/j.1538-4616.2007.00015.x
4. Callen, T., & Chang, D. (1999). Modeling and forecasting inflation in India (IMF Working Paper No. WP/99/119). International Monetary Fund. https://www.imf.org/external/pubs/ft/wp/1999/wp99119.pdf
5. Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605. https://doi.org/10.2307/1910133
6. Clarida, R. H., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. SSRN Electronic Journal, 37(4). https://doi.org/10.2139/ssrn.155910
7. Dholakia, R. H., & Sapre, A. A. (2011). Speed of adjustment and inflation–unemployment tradeoff in developing countries – Case of India (W.P. No. 2011-07-01). Indian Institute of Management, Ahmedabad. https://www.iima.ac.in/sites/default/files/rnpfiles/2061814832011-07-01.pdf
8. Dua, P., & Gaur, U. (2010). Determination of inflation in an open economy Phillips curve framework: The case of developed and developing Asian countries. Macroeconomics and Finance in Emerging Market Economies, 3(1), 33–51. https://doi.org/10.1080/17520840903498107
9. Faniband, M., & Jadhav, P. (2023). Economic policy uncertainty and government bond prices. Indian Journal of Finance, 17(6), 63–73. https://doi.org/10.17010/ijf/2023/v17i6/171549
10. Friedman, M. (1968). The role of monetary policy. The American Economic Review, 58(1), 1–17. https://www.aeaweb.org/aer/top20/58.1.1-17.pdf
11. Goel, D. (2024). Managing food inflation in India. Arthshastra Indian Journal of Economics & Research, 13(1), 8–22. https://doi.org/10.17010/aijer/2024/v13i1/173411
12. Gordon, R. J. (1997). The time-varying NAIRU and its implications for economic policy. Journal of Economic Perspectives, 11(1), 11–32. https://doi.org/10.1257/jep.11.1.11
13. Guru, S., & Panda, P. (2024). Financial sustainability: The influence of internal efficiency in Indian commercial banks. Prabandhan: Indian Journal of Management, 17(10), 37–55. https://doi.org/10.17010/pijom/2024/v17i10/173995
14. Hasenzagl, T., Pellegrino, F., Reichlin, L., & Ricco, G. (2022). A model of the Fed's view on inflation. The Review of Economics and Statistics, 104(4), 686–704. https://doi.org/10.1162/rest_a_00974
15. Hodrick, R. J., & Prescott, E. C. (1997). Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1), 1–16. https://doi.org/10.2307/2953682
16. Jain, S., Mittal, A., Mittal, A., Bagga, T., & Kavita. (2025). Corporate governance and ownership structure as determinants of firm performance: A study of Indian listed companies. Indian Journal of Finance, 19(6), 8–28. https://doi.org/10.17010/ijf/2025/v19i6/175129
17. Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551–1580. https://doi.org/10.2307/2938278
18. Kapur, M. (2013). Revisiting the Phillips curve for India and inflation forecasting. Journal of Asian Economics, 25, 17–27. https://doi.org/10.1016/j.asieco.2012.12.002
19. Kotia, A. (2016). An unobserved components Phillips curve in an emerging market economy: The case of India. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2765176
20. Manhas, B., Hajam, R. A., & Shahzeb, S. M. (2025). Financial sector reforms and inflation in India: An empirical investigation. Arthshastra Indian Journal of Economics & Research, 14(4), 70–84. https://doi.org/10.17010/aijer/2025/v14i4/175047
21. Mazumder, S. (2011). The stability of the Phillips curve in India: Does the Lucas critique apply? Journal of Asian Economics, 22(6), 528–539. https://doi.org/10.1016/j.asieco.2011.05.002
22. Mittal, A., Das, H., Mittal, A., & Thukral, S. (2025). Weekend effect in the banking and financial services sector: An empirical evidence from India. Indian Journal of Finance, 19(12), 8–28. https://doi.org/10.17010/ijf/2025/v19i12/175875
23. Mohapatra, A. K., Mohanty, D., Sardana, V., & Shrivastava, A. (2024). The ripple effect: Influence of exchange rate volatility on Indian sectoral indices. Indian Journal of Finance, 18(2), 8–24. https://doi.org/10.17010/ijf/2024/v18i2/173519
24. Naveenan, R. V., & Viswanathan, T. (2025). Banking dynamics and economic growth in India: Unveiling the interplay of key performance indicators. Indian Journal of Finance, 19(11), 25–40. https://doi.org/10.17010/ijf/2025/v19i11/174492
25. Okun, A. M. (1962). Potential GNP: Its measurement and significance. Proceedings of the Business and Economics Statistics Section (pp. 98–104). American Statistical Association.
26. Pandey, A., Mittal, A., & Singh, M. (2024). Investigating seasonal anomalies and volatility patterns for Brazilian securities markets. Indian Journal of Finance, 18(5), 35–49. https://doi.org/10.17010/ijf/2024/v18i5/173841
27. Patra, M. D., Behera, H., & John, J. (2021). Is the Phillips curve in India dead, inert and stirring to life, or alive and well? RBI Bulletin, November, 63–75. https://www.rbi.org.in/Scripts/BS_ViewBulletin.aspx?Id=20629
28. Paul, B. P. (2009). In search of the Phillips curve for India. Journal of Asian Economics, 20(4), 479–488. https://doi.org/10.1016/j.asieco.2009.04.007
29. Pearl, J. B., & Rajan, M. P. (2025). Multivariate causality between GDP growth, health expenditure, unemployment, and inflation in India. Arthshastra Indian Journal of Economics & Research, 14(4), 21–39. https://doi.org/10.17010/aijer/2025/v14i4/174481
30. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616
31. Phelps, E. S. (1967). Phillips curves, expectations of inflation and optimal unemployment over time. Economica, 34(135), 254–281. https://doi.org/10.2307/2552025
32. Phillips, A. W. (1958). The relation between unemployment and the rate of change of money wage rates in the United Kingdom, 1861–1957. Economica, 25(100), 283–299. https://doi.org/10.1111/j.1468-0335.1958.tb00003.x
33. Preet, A., & Khurana, A. (2026). Efficiency–resilience analysis of Indian public sector banks. Prabandhan: Indian Journal of Management, 19(5), 56–74. https://doi.org/10.17010/pijom/2026/v19i5/174600
34. Ray, K. K., & Das, C. (2024). Nonlinear response of fuel price returns to monetary policy: A regime-switching approach. Indian Journal of Finance, 18(1), 42–56. https://doi.org/10.17010/ijf/2024/v18i1/172011
35. Reis, R. (2022). The burst of high inflation in 2021–22: How and why did we get here? London School of Economics. https://personal.lse.ac.uk/reisr/papers/22-whypi.pdf
36. Roberts, J. M. (1995). New Keynesian economics and the Phillips curve. Journal of Money, Credit and Banking, 27(4), 975–984. https://econpapers.repec.org/article/mcbjmoncb/v_3a27_3ay_3a1995_3ai_3a4_3ap_3a975-84.htm
37. Salunkhe, B., & Patnaik, A. (2019). Inflation dynamics and monetary policy in India: A new Keynesian Phillips curve perspective. South Asian Journal of Macroeconomics and Public Finance, 8(2), 144–179. https://doi.org/10.1177/2277978719861186
38. Sharma, P., & Jasuja, D. (2021). Revalidating Phillips curve in Indian context. Jaipuria International Journal of Management Research, 6(2), 58–64. https://doi.org/10.22552/jijmr/2020/v6/i2/205284
39. Singh, A., & Sahu, G. P. (2025). Enablers of multi-currency wallet adoption: A TISM-fuzzy MICMAC approach. Indian Journal of Marketing, 55(5), 66–87. https://doi.org/10.17010/ijom/2025/v55/i5/175020
40. Singh, B. K., Kanakaraj, A., & Sridevi, T. O. (2011). Revisiting the empirical existence of the Phillips curve for India. Journal of Asian Economics, 22(3), 247–258. https://doi.org/10.1016/j.asieco.2011.01.002
41. Singh, R. K., Saxena, C., Aggarwal, S., Prerna, & Singh, Y. (2025). Bibliometric insights into the 'Indian Journal of Finance': Mapping intellectual contributions. Indian Journal of Finance, 19(5), 8–36. https://doi.org/10.17010/ijf/2025/v19i5/175042
42. Stock, J. H., & Watson, M. W. (1996). Evidence on structural instability in macroeconomic time series relations. Journal of Business & Economic Statistics, 14(1), 11–30. https://doi.org/10.1080/07350015.1996.10524626
43. Stock, J. H., & Watson, M. W. (1999). Forecasting inflation. Journal of Monetary Economics, 44(2), 293–335. https://doi.org/10.1016/S0304-3932(99)00027-6
44. Stock, J. H., & Watson, M. W. (2020). Slack and cyclically sensitive inflation. Journal of Money, Credit and Banking, 52(S2), 393–428. https://doi.org/10.1111/jmcb.12757
45. Vijayakumar, S., & Karthikeyan, P. (2024). Volatility integration of world GDP and world inflation rate with crude oil prices. Indian Journal of Finance, 18(8), 67–80. https://doi.org/10.17010/ijf/2024/v18i8/174243
46. Vishnoi, S. K., Akhter, S., Bagga, T., & Mittal, A. (2023). Modeling the determinants of brand loyalty using PLS-SEM: A study of automobile customers in emerging economies. Indian Journal of Marketing, 53(12), 27–44. https://doi.org/10.17010/ijom/2023/v53/i12/173352