A new working paper from the Federal Reserve Bank of Boston finds that India's Reserve Bank has aligned its policy actions with its inflation-focused communication since adopting a formal inflation targeting framework in 2015, but only when evaluated through the right analytical lens. The study challenges conventional methods of assessing central bank credibility in emerging markets, showing that traditional backward-looking models can misrepresent policy behavior when central banks make decisions based on forecasts rather than past data. The research underscores how evaluating monetary policy credibility requires correctly modeling the information set that policymakers actually use.
Word-frequency analysis of all Reserve Bank of India monetary policy statements issued from 2000 to 2025 reveals a semantic shift from language associated with multiple economic indicators to greater emphasis on inflation and more forward-looking terms after the flexible inflation targeting framework was adopted. The framework, formally implemented in 2015, requires the central bank to target 4 percent headline consumer price index inflation with a tolerance band of plus or minus 2 percentage points. When the authors applied standard Taylor rules—which measure how policy rates respond to realized inflation and output gaps—they found no significant response of the policy rate to inflation after flexible inflation targeting adoption, suggesting a disconnect between the bank's words and actions. However, when they used a forward-looking framework incorporating the Reserve Bank's internal forecasts, they discovered that the policy rate's responsiveness to expected inflation had increased since 2015, indicating a greater role for forecast-based decision-making.
The authors write that backward-looking Taylor rules, widely used to characterize central bank behavior, can misrepresent policy when central banks base decisions on forecasts, and this mischaracterization affects the assessment of credibility, defined as alignment between a central bank's words and actions. Using the Reserve Bank's real-time inflation and output forecasts, the researchers find significant responsiveness to expected inflation in the post-flexible inflation targeting period. Hybrid reaction functions estimated by the authors show that post-2015 policy responds to both expected and realized inflation, with the corresponding evolution in communication and conduct pointing to the Reserve Bank's credibility.
The report explains that this consistency between communication and action is especially important for emerging economies, where institutional credibility and inflation expectations are still evolving and supply shocks are frequent. The Reserve Bank's monetary policy stance was previously informed by multiple economic indicators before the 2015 shift, making the transition to inflation-focused policy a significant institutional change. The authors argue that richer empirical frameworks—beyond standard Taylor rules—are needed to capture central bank behavior in emerging economies, as traditional models developed for advanced economies may fail to account for the forward-looking nature of modern monetary policymaking. The evidence suggests that when the Reserve Bank's communication and policy actions are viewed through the correct empirical lens, they exhibit alignment after the adoption of flexible inflation targeting, supporting the interpretation of central bank credibility.
The findings highlight the importance of macroeconomic forecasting in an inflation-targeting regime and demonstrate that hybrid reaction functions may better characterize emerging-market central bank behavior than purely backward- or forward-looking specifications. The report emphasizes that evaluating monetary policy credibility requires correctly modeling the information set on which policymakers act, not simply applying standard frameworks that may be inappropriate for the institutional context. For policymakers and researchers assessing central bank credibility in emerging markets, the takeaway is clear: the analytical tools matter as much as the data itself.