SUMMER INTERNSHIP REPORT

on

UNDERSTANDING THE EFFECTS OF POLICY RATE CHANGES ON THE YIELD CURVE

SUMMER INTERNSHIP SCHEME 2025

Internship Duration: April 7, 2025 - June 6, 2025

Department: Department of Economics and Policy Research

Submitted by

Siddharth Gupta

Indian Institute of Management, Rohtak

Under the guidance of

Dr. Kirti Gupta

Assistant General
Manager
Department of Economics and Policy Research
Reserve Bank of India, New Delhi

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 CERTIFICATE

This is to certify that Siddharth Gupta has completed his summer internship at the
Reserve Bank of India (RBI), New Delhi, and has submitted this project report entitled
Understanding the effects of Policy Rate Changes on the Yield Curve towards
fulfilment of the requirements for the award of Summer Internship Project 2025.

This report is the result of his work, to the best of my knowledge. This project was
carried out under my overall supervision.

Date: June 6, 2025

Place: New Delhi

Mentor

Dr Kirti Gupta

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ACKNOWLEDGEMENT

I am profoundly grateful to everyone who has supported and guided me during my

internship at the Department of Economics and Policy Research, Reserve Bank of
India, Delhi.
I extend my heartfelt thanks to the entire team at the Department of Economics and
Policy Research for their invaluable assistance and cooperation, which played a
crucial role in the successful completion of my project titled ‘Understanding the
effects of Policy Rate changes on the Yield Curve’.

I would also like to acknowledge with much appreciation the crucial role of Dr.
Rajmal Sir, whose guidance from the initial step of research enabled me to develop
an understanding of the subject. Special thanks are due to my mentor, Dr. Kirti
Gupta Ma’am, whose sincerity and encouragement have played a significant role
in the completion of my project.

I am also deeply thankful to the Reserve Bank of India for offering this summer
internship program, providing me with a significant learning experience and the
opportunity to apply my academic knowledge in a real-world setting.

Thank you all for your unwavering support and encouragement.

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 TABLE OF CONTENTS
CERTIFICATE ........................................................................................................................................ 2
ACKNOWLEDGEMENT ....................................................................................................................... 3
EXECUTIVE SUMMARY ..................................................................................................................... 6
LITERATURE REVIEW ........................................................................................................................ 7
Empirical Challenges to Traditional Theory ....................................................................................... 7
The FLANK Model: Incorporating Life-Cycle Dynamics ................................................................. 8
European Central Bank Perspectives and Unconventional Policy ...................................................... 8
Policy Implications and Yield Curve Dynamics ................................................................................. 9
Research Gaps in Emerging Market Contexts .................................................................................. 10
METHODOLOGY ............................................................................................................................... 11
1. Data Collection ........................................................................................................................ 11
2. Data Preparation and Merging .............................................................................................. 11
3. Horizon-Based Yield Change Calculation ............................................................................ 12
4. Econometric Model Specification .......................................................................................... 13
5. Regression Implementation.................................................................................................... 13
6. Visualizing Impulse Response Functions .............................................................................. 14
7. Interpretation and Inference.................................................................................................. 14
8. Tools and Environment .......................................................................................................... 15
DATA ANALYSIS AND IMPLICATIONS .......................................................................................... 16
1. REGRESSION ANALYSIS (1-Week Horizon) ................................................................... 16
Objective: ...................................................................................................................................... 16
Regression Results Summary (Week +1): .................................................................................... 16
Interpretation of Results by Maturity: ........................................................................................... 16
Thematic Interpretation: ................................................................................................................ 17
Policy & Market Implications: ...................................................................................................... 18
2. REGRESSION ANALYSIS (2-Week Horizon) ................................................................... 19
Objective: ...................................................................................................................................... 19
Regression Results Summary (Week +2): .................................................................................... 19
Interpretation of Results by Maturity: ........................................................................................... 19
Thematic Interpretation: ................................................................................................................ 20
Policy & Market Implications: ...................................................................................................... 21
3. REGRESSION ANALYSIS (4-Week Horizon) ................................................................... 22
Objective: ...................................................................................................................................... 22
Regression Results Summary (Week +4): .................................................................................... 22
Interpretation of Results by Maturity: ........................................................................................... 23

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 Thematic Interpretation: ................................................................................................................ 24
Policy & Market Implications: ...................................................................................................... 24
4. REGRESSION ANALYSIS (8-Week Horizon) ................................................................... 25
Objective: ...................................................................................................................................... 25
Regression Results Summary (Week +8): .................................................................................... 25
Interpretation of Results by Maturity: ........................................................................................... 26
Thematic Interpretation: ................................................................................................................ 27
Policy & Market Implications: ...................................................................................................... 27
5. IMPULSE RESPONSE FUNCTION ................................................................................... 28
RESULTS AND FINDINGS OF THE PROJECT ................................................................................ 30
1. Monetary Policy Significantly Influences the Yield Curve ...................................................... 30
2. Policy Effects Are Persistent Over Time .................................................................................. 30
3. Asymmetry in Yield Response to Hikes vs. Cuts ..................................................................... 30
4. The Yield Curve as a Forward-Looking Indicator .................................................................... 30
5. Contextual Sensitivity of Market Interpretation ....................................................................... 31
6. Mid- and Long-Term Bonds Are Most Sensitive to Policy ...................................................... 31
7. Policy and Market Implications ................................................................................................ 31
CONCLUSION ..................................................................................................................................... 32
REFERENCES ..................................................................................................................................... 33
APPENDIX ........................................................................................................................................... 35

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EXECUTIVE SUMMARY
This report explores how changes in the Reserve Bank of India’s (RBI) policy interest rate,
specifically the repo rate affect government bond yields across various maturities in the Indian
debt market. Drawing on data from February 2019 to April 2025 and applying a robust
econometric framework, the study evaluates the response of bond yields over multiple time
horizons (from immediate to eight weeks post-announcement), offering a comprehensive view
of the monetary policy transmission mechanism in India.

Key findings reveal that monetary policy actions have a significant and persistent effect on the
yield curve, especially at medium- and long-term maturities. Notably, the market responds
asymmetrically: rate cuts tend to induce stronger and more sustained increases in yields
compared to the declines observed following rate hikes. This behaviour is particularly
pronounced in 5-year and 10-year bonds, suggesting heightened sensitivity to perceived
inflation risk or concerns over long-term economic stability following accommodative policy
decisions.

In addition to empirical evidence, the report incorporates the FLANK model—a modern
theoretical framework emphasising household life-cycle savings behaviour—to provide a
deeper understanding of why persistent rate cuts may not always stimulate consumption, and
why long-term rates may rise in response to easing measures.

Ultimately, the study highlights the importance of policy communication, credibility, and
timing, emphasising that monetary policy decisions are not only influential at the short end of
the yield curve but are also deeply embedded in how markets forecast inflation, growth, and
risk over the long term.

The chart below shows a broad overview of the direction of different yields over different
horizons.

Yields of Different Maturities

8
7
Yield ( In percentage)

6
5
4
3
2
1
0
41

111

281
1
11
21
31

51
61
71
81
91
101

121
131
141
151
161
171
181
191
201
211
221
231
241
251
261
271

291
301
311
321

Weeks ( 2019-2025)
Yield_3M Yield_6M Yield_1Y Yield_3Y Yield_5Y Yield_10Y

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LITERATURE REVIEW
Theoretical Foundations and Traditional Understanding

The theoretical foundation for understanding yield curve dynamics rests primarily on the
expectations hypothesis, which posits that long-term interest rates represent the average of
expected future short-term rates over the corresponding maturity period (Fisher, 1907; Hicks,
1939). This framework has been central to New Keynesian models, particularly those
developed by Woodford (2003), where the term structure serves as a crucial transmission
mechanism for monetary policy.

Under this traditional view, central banks primarily influence short-term interest rates through
policy adjustments, while long-term rates remain largely autonomous, determined by market
expectations regarding future economic conditions, inflation trends, and associated risk premia
(Clarida et al., 2000). This theoretical divide has historically supported the belief that central
banks possess limited capacity to persistently influence long-term rates, with policy effects
diminishing as maturity increases.

The conventional transmission mechanism operates through intertemporal substitution, where

policy rate increases raise real interest rates, encouraging economic agents to defer current
consumption in favor of future spending. This behavioral response leads to increased savings
and reduced aggregate demand, generating contractionary effects on output and inflation. Del
Negro et al. (2013) demonstrate that the strength of this mechanism correlates positively with
the persistence of policy rate changes, suggesting that sustained rate adjustments produce more
pronounced economic effects than temporary interventions.

Empirical Challenges to Traditional Theory

Despite the theoretical coherence of the expectations hypothesis, empirical evidence

increasingly contradicts its predictions. Cochrane and Piazzesi (2002) provide early evidence
that long-term real interest rates respond significantly to short-term policy rate changes,
challenging the assumption of long-end autonomy. This finding has been corroborated by
subsequent research, with Hanson and Stein (2015) documenting substantial responsiveness of
long-term rates to monetary policy surprises.

Nakamura and Steinsson (2018) and Hansen et al. (2019) further demonstrate that long-term
interest rates react almost immediately to monetary policy surprises, including unanticipated
central bank announcements. Hillenbrand (2023) reinforces these findings by showing that a
substantial portion of the decline in U.S. long-term interest rates since 1980 occurred within
narrow windows surrounding Federal Open Market Committee (FOMC) meetings, suggesting
direct policy influence rather than gradual expectation adjustments.

One explanation for the immediate responsiveness of long-term rates centers on the
"information effect," which suggests that central bank communications convey superior
insights about future economic conditions that markets rapidly internalize (Campbell et al.,
2012). This hypothesis assumes that central banks possess informational advantages regarding

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macroeconomic developments, enabling them to influence market expectations through their
announcements and policy signals.

However, this explanation faces increasing scrutiny given the democratization of economic
data and analytical tools available to market participants. The assumption of exclusive central
bank informational advantages appears increasingly untenable in the modern information
environment, prompting researchers to seek alternative theoretical explanations for the
observed yield curve responsiveness.

The FLANK Model: Incorporating Life-Cycle Dynamics

Addressing the limitations of traditional representative agent models, Beaudry, Cavallino, and
Willems (2025) introduce the FLANK (Finitely-Lived Agent New Keynesian) model, which
incorporates overlapping generations and life-cycle behaviors into the New Keynesian
framework. This innovative approach recognizes that households face finite lifespans and must
plan for retirement, introducing heterogeneity in income streams and consumption patterns
over time.

The FLANK model identifies three distinct channels through which monetary policy affects
consumption and yield curve dynamics:

1. Intertemporal Substitution Channel: Following traditional theory, higher interest rates

incentivize saving over current consumption.
2. Asset Valuation Channel: Lower interest rates increase the present value of assets,
potentially generating wealth effects that stimulate consumption.
3. Asset Demand (Retirement Savings) Channel: This novel mechanism reveals that lower
interest rates reduce expected future income streams from retirement savings,
prompting households to increase current savings to meet future consumption needs.

The third channel proves particularly influential when households exhibit low elasticity of
intertemporal substitution (EIS < 1). Under these conditions, households that cannot easily
substitute consumption across time periods respond to lower returns by increasing rather than
decreasing savings, potentially dampening the stimulative effects of monetary easing. This
insight provides a theoretical foundation for understanding why persistent rate reductions may
not always translate into higher aggregate demand and output.

A key contribution of the FLANK model is the introduction of the function Ψ(ρ), which
measures monetary policy effectiveness as a function of interest rate change persistence (ρ).
While traditional models predict a negatively sloped Ψ(ρ), indicating increasing contractionary
effects with greater persistence, the FLANK model demonstrates non-monotonic or even
positively sloped relationships under certain conditions, particularly when EIS < 1.

Proposition 4 from Beaudry et al. (2025) formalizes this insight, suggesting that persistent rate
increases may produce weaker contractionary effects or even expansionary outcomes under
specific circumstances. This counterintuitive result occurs because long-term rates influence
savings behavior differently when agents focus on retirement planning, with persistent rate
increases potentially reducing precautionary savings needs and boosting current consumption.

European Central Bank Perspectives and Unconventional Policy

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Philip R. Lane (2019), representing the European Central Bank's Executive Board, articulates
the yield curve's dual function as both a transmission channel for monetary policy and a signal
of market expectations regarding inflation, growth, and interest rates. Lane distinguishes
between "rate surprises" (unexpected current policy rate changes) and "path surprises" (forward
guidance shifts), noting differential effects across the maturity spectrum.

Rate surprises primarily affect short-term yields, while path surprises exert more pronounced
effects on medium-term maturities. Additionally, the yield curve's shape reflects term premia—
compensation required by investors for holding longer-term securities due to uncertainty—
alongside pure expectations effects.

Research on unconventional monetary policy tools provides additional insights into yield curve
transmission mechanisms. The ECB's Asset Purchase Programme (APP) and Negative Interest
Rate Policy (NIRP) demonstrate strong influence over long-maturity yields through signaling
and portfolio rebalancing channels. Eser et al. (2019) estimate that APP reduced 10-year euro
area sovereign yields by over 100 basis points, primarily through term premium compression
rather than expectations adjustment.

These findings align with theoretical work by Vayanos and Vila (2009), which explains how
central bank asset purchases reduce the supply of duration risk in the market, leading to yield
curve flattening. The portfolio rebalancing mechanism operates as investors seek to maintain
desired duration exposures, bidding up prices (and reducing yields) on remaining long-duration
securities.

Understanding yield curve responses requires careful separation of expectations and term
premia components. Cochrane and Piazzesi (2008) and Bauer and Rudebusch (2019)
emphasize this decomposition's importance for accurate policy impact assessment. Hanson and
Stein (2015) demonstrate that monetary easing reduces long-term yields through both
expectations adjustments and term premia compression, as investors rebalance portfolios
toward longer durations in search of yield.

Policy Implications and Yield Curve Dynamics

The accumulated evidence supports the view that central banks can influence the entire yield
curve, not merely short-term rates. The FLANK model suggests that yield curve shape and
slope respond differently depending on policy intervention characteristics, particularly
regarding persistence and underlying household behavioural parameters.

Different policy actions produce distinct yield curve effects:

Policy Action Short-Term Yield Long-Term Yield Yield Curve Shape

Temporary Rate Hike Rises sharply Rises slightly Flattens
Persistent Rate Hike Rises steadily Rises more Steepens
Temporary Rate Cut Falls sharply Falls slightly Flattens
Persistent Rate Cut Falls steadily Falls more Flattens or inverts

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When the elasticity of intertemporal substitution remains below unity, persistent rate cuts may
inadvertently increase long-term savings demand, further depressing long-term yields and
potentially inverting the curve. This dynamic makes forward guidance and communication
tools essential for managing expectations and anchoring long-term yield levels.

Research Gaps in Emerging Market Contexts

While extensive research examines monetary policy yield curve transmission in advanced
economies, particularly regarding unconventional tools like quantitative easing and negative
interest rates, emerging market studies remain relatively scarce. Most existing research on
countries like India concentrates on short-term effects or daily movements around policy
announcements, without assessing persistence and asymmetry of yield responses across
multiple time horizons.

The differential responses of various maturity segments to policy tightening versus easing
cycles remain underexplored in emerging market contexts, especially using horizon-based
approaches that account for delayed market absorption of policy signals. Additionally, the
relative importance of expectations versus term premia in shaping yield reactions in emerging
markets remains empirically ambiguous, representing a significant gap in the literature.

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METHODOLOGY
This study adopts a quantitative, empirical research design with an event-study approach to
examine the impact of RBI monetary policy decisions on the Indian government bond yield
curve. The core objective is to measure how policy rate changes (repo rate hikes or cuts) affect
bond yields across different maturities (3M to 10Y) and over varying time horizons (immediate
to 8 weeks).

The study utilizes a panel regression framework with policy event-based dummy variables to
isolate the causal effects of monetary policy changes on yield dynamics. The term structure
response is analyzed for persistence (whether effects last) and asymmetry (whether hikes and
cuts have different impacts).

1. Data Collection

A. Monetary Policy Announcements Dataset (Repo Rate)

• Source: Reserve Bank of India (RBI) official releases.

• Time Period: February 2019 to April 2025.
• Fields:
o Date of announcement
o Repo rate (%)
o Calculated change in basis points (bps) from the previous meeting

This data is compiled into a structured Excel sheet, sorted chronologically. The repo rate
change is calculated as:

To prepare for analysis, this dataset is aligned with week-ending dates (typically Friday) using
Python’s pd.offsets.Week(weekday=4) method to match bond yield frequencies.

B. Weekly Bond Yield Dataset

• Source: RBI weekly yield curve data ( Taken from Investing.com)

• Time Period: February 2019 to April 2025
• Fields:
o Week Ending (Friday)
o Yield_3M, Yield_6M, Yield_1Y, Yield_3Y, Yield_5Y, Yield_10Y (in %)

Each yield corresponds to a sovereign bond maturity. This serves as the primary dependent
variable dataset.

2. Data Preparation and Merging

To establish a clean, structured, and analyzable dataset, this stage focuses on harmonizing the
temporal structure of monetary policy events with bond yield observations, ensuring alignment
and consistency for subsequent analysis.

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Step A: Match Policy Announcements to Yield Data

The first step involves converting all policy announcement dates from the RBI into a consistent
weekly format that matches the bond yield data, which is reported on a week-ending (typically
Friday) basis. This is done programmatically using Python’s pd.offsets.Week(weekday=4)
method, which shifts each date to the corresponding Friday of the same week.

Since more than one policy change can potentially occur within the same week, the dataset is
grouped by the WeekEnding column, and the latest (most recent) policy event is retained for
each week. This ensures that only one policy event per week is matched with that week's yield
data.

Next, the dataset is enhanced by adding three important variables:

• RepoChange: The numeric change in the repo rate (in basis points) from the previous
announcement.
• HikeDummy: A binary variable that takes the value 1 if RepoChange is positive (i.e., a
rate hike occurred), and 0 otherwise.
• CutDummy: A binary variable that takes the value 1 if RepoChange is negative (i.e., a
rate cut occurred), and 0 otherwise.

For all weeks where no monetary policy announcement was made, the values of RepoChange,
HikeDummy, and CutDummy are set to 0. This allows the model to distinguish between active
policy weeks and regular weeks.

Step B: Merge Bond Yield and Policy Data

Once the monetary policy data has been aligned to a week-ending format, it is merged with the
weekly bond yield dataset using WeekEnding as the common key. This join operation is
performed as a left join, where the bond yield dataset serves as the base, and the policy data is
joined onto it.

After the merge, many weeks will have missing values for the policy-related columns (i.e., no
policy event that week). These missing values are replaced with 0s for all three variables
(RepoChange, HikeDummy, and CutDummy) to maintain consistency and prepare for dummy
variable regression analysis.

The final structured dataset at this stage includes weekly data for the following columns:

• Bond yields for various maturities: Yield_3M, Yield_6M, Yield_1Y, Yield_3Y,

Yield_5Y, Yield_10Y
• Monetary policy variables: RepoChange, HikeDummy, and CutDummy

This enriched panel dataset forms the foundation for computing yield changes across horizons
and running the regression models described in the subsequent sections.

3. Horizon-Based Yield Change Calculation

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For each maturity and each forecast horizon (0W, 1W, 2W, 4W, 8W):

This represents the change in the bond yield of a specific maturity after weeks from the policy
event week.

Method:

• In Python, use .shift(-h) to compute

• Subtract current to get
• Create new columns:
o Delta_Yield_3M_1w, Delta_Yield_10Y_4w, etc.

This transformation results in a wide dataset with each column representing a particular
horizon-maturity yield response.

4. Econometric Model Specification

The regression model for each maturity and horizon is:

Where:

This model is repeated for each maturity (3M, 6M, 1Y, 3Y, 5Y, 10Y) across each horizon (1W,
2W, 4W, 8W).

5. Regression Implementation

Python is used for regression analysis via the statsmodels package:

import statsmodels.api as sm

X = df[['HikeDummy', 'CutDummy']]
X = sm.add_constant(X)
y = df['Delta_Yield_10Y_1w'] # (for example)

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model = sm.OLS(y, X).fit()
print(model.summary())

The output provides:

• Coefficients (β₁ and β₂)

• Standard errors
• t-statistics and p-values
• R², AIC, BIC values for model fit assessment

This step is looped to generate a panel of estimates across maturities and horizons.

6. Visualizing Impulse Response Functions

To better understand the concepts of persistence and asymmetry in yield responses, the study
employs visual tools—specifically, line plots that depict impulse response functions. For each
bond maturity, a separate chart is generated that plots the estimated coefficients of the hike and
cut dummies across the five forecast horizons: 0 weeks (immediate), 1 week, 2 weeks, 4 weeks,
and 8 weeks.

On these plots, the x-axis represents the forecast horizon, while the y-axis denotes the size of
the estimated coefficient (β₁ for hikes, β₂ for cuts). Two distinct lines are plotted on each
graph—one for the hike dummy and another for the cut dummy—allowing us to directly
compare how the impact of rate hikes and rate cuts evolves over time.

These visualizations help to illuminate the temporal dynamics of yield curve responses:
whether the effects dissipate quickly (indicating short-lived reactions) or persist and possibly
intensify over time (signaling strong forward-guidance effects). Additionally, the divergence
between the two lines across horizons can clearly display any asymmetry in market reaction,
enhancing the interpretability of the empirical results and contributing valuable insights into
the transmission mechanism of monetary policy.

7. Interpretation and Inference

Understanding the regression outputs requires a structured lens to assess how yields behave
over different horizons and to draw implications for monetary transmission. While our study
is empirical in nature, the theoretical expectations and interpretations guide how we think about
the dynamics of policy shocks.

A. Persistence:

We aim to assess whether monetary policy effects are persistent by examining the significance
of yield changes even several weeks after the announcement. If coefficients in the regressions
remain statistically significant at longer horizons like 4 weeks or 8 weeks, we interpret this as
evidence of persistent market reaction. This would imply that the policy signal—whether a

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hike or a cut—has not only an immediate but also a prolonged impact on investor expectations
and bond pricing.

B. Asymmetry:

Another goal is to examine whether rate cuts and hikes produce symmetric effects. We
hypothesize that if the absolute value of the coefficient on the rate cut dummy (|β₂|) is
consistently larger than that for rate hikes (|β₁|), it may suggest that the market reacts more
aggressively to monetary easing than to tightening. This would indicate that cuts are perceived
as more powerful or disruptive, potentially due to inflation expectations or perceived liquidity
expansion.

C. Term Premium Behavior:

Lastly, we explore the implication of yield changes for the term premium. If longer-tenor yields
(such as 10-year bonds) increase following a rate cut, this may indicate that markets are
adjusting their inflation expectations upward, possibly fearing future tightening or
macroeconomic instability. Such a pattern could reflect a rise in the term premium, suggesting
that accommodative policies are interpreted as risk-enhancing in the long run rather than
merely stimulative.

These interpretations provide a theoretical grounding for the empirical exercise and help in
contextualizing the findings with respect to financial market expectations and central bank
credibility.

If long-term yields rise after cuts, this indicates a possible increase in term premia due to
inflation expectations or perceived risk.

8. Tools and Environment

The primary tools used for this research include both programming-based and spreadsheet-
based environments to ensure both precision and interpretability. Python was the core
analytical platform, utilizing libraries such as Pandas for data manipulation, NumPy for
numerical operations, Statsmodels for running econometric regressions, and Matplotlib for
visualization of impulse response functions. Excel was used during the initial stages for manual
inspection, formatting, and light cleaning of the raw data collected from RBI releases and bond
yield sources.

All code and models were executed and validated in Jupyter Notebook and Python IDEs, which
allowed for modular, reproducible, and well-documented analysis pipelines.

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DATA ANALYSIS AND IMPLICATIONS

1. REGRESSION ANALYSIS (1-Week Horizon)

Objective:

This section estimates how government bond yields across various maturities (from 3-month
to 10-year) respond one week after a repo rate hike or cut by the Reserve Bank of India (RBI).
The analysis particularly focuses on two critical dimensions:

• Persistence: This measures how the the yield changes last at least a week after the policy
action.
• Asymmetry: This measures if the effects of repo rate hikes different from those of cuts?

Regression Results Summary (Week +1):

Hike Cut
Maturity Impact Impact Significant? Notes
(β1) (β2)
Both hikes and cuts reduce yields, suggesting
3M -10.39 bps -7.46 bps both the market expects a reversal or absorbs
liquidity shocks
+13.52 Cuts increase yields — counterintuitive, may
6M +1.29 bps for cut
bps reflect inflation concerns
1Y -17.22 bps +4.75 bps for hike Strong drop after hikes; cuts are not significant
Hikes have a clear contractionary impact, cuts
3Y -7.94 bps -0.78 bps for hike
are noise
+18.21 Classic asymmetric reaction — cuts drive yields
5Y -17.82 bps both
bps up, hikes pull them down
+13.80 Long-term rates show full persistence and
10Y -12.83 bps both
bps strong asymmetric response

Interpretation of Results by Maturity:

Short-Term Yields (3M, 6M, 1Y):

• 3M Yield: Both hikes and cuts result in lower yields. This suggests that market
participants may be expecting future reversals in policy or reacting to immediate
liquidity effects. The decline in yields even after a cut implies that liquidity and short-
term expectations outweigh direct policy direction.
• 6M Yield: Repo cuts lead to a substantial increase in the 6-month yield (+13.52 bps), a
result that appears counterintuitive. This could reflect rising inflation expectations or

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 fears of overheating. Interestingly, repo hikes barely affect the 6M yield, implying that
such moves are either already priced in or viewed as temporary.
• 1Y Yield: A repo hike causes a significant decline (-17.22 bps) in the 1-year yield,
showing a strong contractionary impact. The cut, however, does not have a statistically
significant impact, which may indicate that easing measures do not shift medium-term
rate expectations effectively.

Mid-Term Yields (3Y, 5Y):

• 3Y Yield: Hikes decrease 3-year yields significantly, while cuts do not have a
meaningful effect. This suggests markets interpret hikes as strong signals of monetary
tightening, whereas cuts lack the power to move expectations in the medium term.
• 5Y Yield: Here, a clear asymmetric effect is evident: hikes reduce yields by 17.82 bps,
while cuts increase them by 18.21 bps. This mid-curve maturity appears to be most
responsive to both kinds of monetary shocks, likely due to its balance between short-
term liquidity and long-term expectation anchoring.

Long-Term Yields (10Y):

• 10Y Yield: Hikes significantly reduce yields (-12.83 bps), and cuts significantly
increase them (+13.80 bps). This behavior implies that the long-term segment of the
curve is sensitive to signals about growth and inflation. A repo cut may be perceived as
a sign of future inflation, while a hike is interpreted as credible commitment to anchor
inflation

Thematic Interpretation:

1. Persistence of Policy Effects:

The yield reactions remain statistically significant even one week after the announcement,
particularly for the 1Y, 5Y, and 10Y maturities. This suggests that RBI’s policy actions are not
only impactful immediately but also have a sustained influence on market expectations and
pricing. The delayed full reaction indicates that investors may spend time digesting the policy
stance and adjusting their portfolios accordingly.

Conclusion: Monetary policy effects are persistent beyond the immediate announcement week.

2. Asymmetry in Yield Reaction:

In mid- and long-term yields (notably 5Y and 10Y), the cut effects are greater than the hike
effects. For instance, the 10Y yield rises by +13.8 bps following a cut, while it drops by -12.8
bps following a hike. This asymmetry suggests that the market is more sensitive to easing,
potentially due to expectations of inflation or excessive liquidity. In contrast, hikes may be
expected or less surprising.

Conclusion: The yield response is asymmetric, with stronger effects for repo rate cuts.

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Policy & Market Implications:

Implication Explanation
Communication Yield movement 1 week later indicates markets respond to tone and
matters guidance
Forward guidance The drop in short-term yields post-hike shows the market may have
priced in anticipated the policy direction
Cuts drive inflation Strong yield rises post-cut in 6M and 10Y suggest inflationary
fears expectations need to be managed
Market reacts more to Asymmetry implies that easing has stronger impact on expectations
cuts than tightening

In summary, this 1-week horizon analysis reveals that India's bond market is responsive to
RBI's monetary policy, with clear signs of persistence and asymmetry. Longer maturities react
more strongly to cuts, and this has significant implications for how the central bank designs
and communicates its future policy stance.

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 2. REGRESSION ANALYSIS (2-Week Horizon)
Objective:

This section builds on the earlier one-week analysis by examining how government bond yields
across maturities respond two weeks after a monetary policy decision by the Reserve Bank of
India (RBI). Specifically, the analysis aims to identify whether:

• The effects observed at the 1-week mark persist, intensify, or dissipate over a longer
horizon.
• The magnitude and direction of yield responses differ between hikes and cuts.
• Asymmetry in market behavior continues to hold, particularly at longer maturities.

By extending the time window, this analysis helps in understanding the medium-term
transmission of monetary policy in India's fixed income markets.

Regression Results Summary (Week +2):

Hike Impact Cut Impact

Maturity Significant? Notes
(β1) (β2)
Borderline Direction flips but neither is statistically
3M -8.24 bps +5.60 bps
(hike) strong
Market possibly pricing inflation risk
6M +1.68 bps +15.04 bps for cut
post cut
Clear asymmetric response with cuts
1Y -16.31 bps +21.84 bps both
driving larger impact
Greater sensitivity to cuts; hikes not
3Y -4.30 bps +11.10 bps for cut
meaningful
Highly responsive and sharply
5Y -19.27 bps +26.43 bps both
asymmetric at this horizon
Peak cut response seen; hikes remain
10Y -17.70 bps +31.10 bps both
contractionary

Interpretation of Results by Maturity:

Short-Term Yields (3M, 6M, 1Y):

• 3M Yield: The results show minimal net movement, with opposing but weak directional
responses. While a rate hike slightly lowers the 3-month yield and a rate cut increases
it, neither effect is statistically strong. This suggests that, by the second week, the short-
end of the yield curve stabilizes, and much of the market's adjustment has already taken
place. It may also reflect market participants' belief that short-term rates will revert
quickly or that repo changes are less binding at such short durations.

19 | P a g e
 • 6M Yield: In contrast to the 3-month segment, the 6-month yield shows a strong and
statistically significant rise following a rate cut. This likely reflects increased inflation
expectations or risk premia being priced into the intermediate term. The response to a
hike remains statistically insignificant, indicating the market does not fully internalize
short-term rate hikes at this tenor.
• 1Y Yield: The 1-year yield continues to display a strong, asymmetric response. While
hikes reduce the yield significantly (by 16.31 bps), cuts result in an even larger increase
(21.84 bps). This asymmetry indicates that easing actions prompt a forward-looking
repricing of growth and inflation expectations more strongly than tightening actions
constrain them. It also suggests that this maturity is a critical channel through which
policy sentiment is reflected in the yield curve.

Mid-Term Yields (3Y, 5Y):

• 3Y Yield: The 3-year segment reacts more favorably to easing than tightening, with a
statistically significant 11.1 bps increase in yield following a cut. However, the impact
of a hike is negligible. This again shows that the market interprets cuts as a more active
economic signal, likely related to expectations of accommodative liquidity or credit
conditions.
• 5Y Yield: This maturity displays the most balanced responsiveness, with both hikes
and cuts resulting in significant yield movements. A 19.27 bps drop is observed post-
hike, while a 26.43 bps increase follows a cut. The pronounced asymmetry here signals
that the 5Y yield is a sweet spot where markets absorb both the contractionary and
expansionary expectations embedded in monetary policy decisions. Persistence and
sensitivity are highest at this tenor.

Long-Term Yields (10Y):

• 10Y Yield: The 10-year yield shows the strongest reaction to cuts observed across any
maturity or horizon so far, rising by 31.10 bps following a repo rate reduction. The
response to hikes is also notable with a drop of 17.70 bps. This pattern reflects long-
term inflation expectations being revised upward following accommodative signals,
and a credible anti-inflation stance following hikes. The data suggest that the 10Y
maturity integrates macroeconomic forward guidance more fully over time.

Thematic Interpretation:

1. Persistence of Policy Effects:

Two weeks after repo rate announcements, significant changes in yields are still visible across
the curve, especially in the 1Y, 5Y, and 10Y maturities. The persistence of these effects
indicates that policy announcements have more than just a short-lived impact. Markets appear
to reassess expectations gradually over time, reflecting the delayed adjustment in expectations
for growth, inflation, and future monetary stance.

Conclusion: Yield reactions are clearly persistent at the 2-week horizon, supporting the notion
that the RBI’s actions reverberate well beyond the announcement window.

20 | P a g e
2. Asymmetry in Yield Reaction:

The asymmetry observed at the 1-week mark becomes even more pronounced at the 2-week
horizon. For almost every maturity, the effect of a rate cut is significantly larger in magnitude
than that of a hike. For example, in the 10Y segment, a repo cut increases the yield by +31.10
bps compared to a -17.70 bps drop from a hike. This signals a market bias towards interpreting
cuts as risk-enhancing (e.g., inflation, currency depreciation) while hikes are viewed as
stabilizing or already priced in.

Conclusion: Yield responses remain highly asymmetric, particularly at longer maturities,

indicating deeper structural expectations in market behavior.

Policy & Market Implications:

Implication Explanation
Yield shifts become more visible over two weeks, indicating
Market pricing evolves
staggered absorption of policy
The 10Y bond's sensitivity reflects how inflation and macro risks are
Long-tenor anchoring
priced beyond the short term
Asymmetric reaction Investors appear more responsive to easing than tightening, affecting
sharpens how RBI communication is digested

In conclusion, the 2-week analysis reinforces the idea that monetary policy shocks in India
have strong medium-term influence on the shape and slope of the yield curve. Particularly,
repo rate cuts are perceived by markets as structurally more impactful — causing greater and
more persistent shifts, especially in the longer maturities. This highlights the importance for
policymakers to consider how market participants asymmetrically interpret tightening versus
easing actions when setting and communicating future policy direction.

21 | P a g e
 3. REGRESSION ANALYSIS (4-Week Horizon)

Objective:

This section evaluates how bond yields behave four weeks after a change in the RBI’s policy
rate, extending the assessment of persistence and asymmetry in monetary transmission. A one-
month period is critical to gauge whether markets have digested the full impact of policy
surprises and whether the yield curve reflects medium-to-long term expectations about growth,
inflation, and liquidity.

By analyzing the fourth week post-announcement, we assess whether yield responses:

• Amplify due to slow-moving expectations,

• Reverse due to market recalibration, or
• Flatten as the market normalizes.

Regression Results Summary (Week +4):

Hike Impact Cut Impact

Maturity Significant? Notes
(β1) (β2)
Hike effect remains strong; cut response
3M -13.29 bps +5.19 bps Hike only
fades
Continued inflationary expectations
6M -0.72 bps +20.89 bps Cut only
from easing
Hikes continue to depress yields
1Y -29.87 bps +17.90 bps Hike only
significantly

22 | P a g e
 Mid-curve is still strongly influenced by
3Y -11.50 bps +15.06 bps Cut only
cuts
5Y -30.91 bps +35.82 bps both Peak asymmetric response observed here
Yield response continues to amplify at
10Y -28.95 bps +44.55 bps both
the long-end

Interpretation of Results by Maturity:

Short-Term Yields (3M, 6M, 1Y):

• 3M Yield: One month after a policy change, the 3-month yield reflects a significant
reduction (-13.29 bps) following a hike, while the effect of a cut becomes statistically
insignificant. This suggests that markets expect temporary easing to reverse or see cuts
as already absorbed. The strong response to hikes, however, suggests that policy
tightening anchors short-end rates more firmly, reinforcing short-run inflation control.
• 6M Yield: Here we observe a pronounced positive response to cuts, with yields
increasing by 20.89 bps, likely reflecting investor concern about overheating or long-
term inflation. The market may perceive cuts as stimulatory, raising inflation risk in the
near future. Hike effects disappear by this horizon, signaling that short-end market
expectations recalibrate faster post-tightening.
• 1Y Yield: The 1-year yield continues to fall significantly after hikes (-29.87 bps),
indicating that even after a month, the market views policy tightening as credible and
impactful. Interestingly, the response to cuts is no longer statistically significant,
pointing to a possible normalization in medium-term expectations. This maturity shows
some asymmetry in favor of hikes at this point.

Mid-Term Yields (3Y, 5Y):

• 3Y Yield: Cuts lead to a 15.06 bps increase, while hikes reduce yields by -11.5 bps
(marginally significant at 10% level). This reflects continued investor concern about
the effects of prolonged accommodative policy. The mid-segment of the curve remains
highly responsive to changes in inflation and liquidity outlook, especially under an
easing regime.
• 5Y Yield: Both cuts and hikes yield strong responses at this tenor: -30.91 bps post-hike
and +35.82 bps post-cut. These are some of the highest responses in the dataset. This
makes the 5-year yield a strong indicator of market sentiment, absorbing both policy
direction and strength. The symmetry seen earlier now transforms into clear asymmetry
in magnitude, with cuts dominating.

Long-Term Yields (10Y):

• 10Y Yield: The long bond continues to show amplified reaction. A rate cut leads to a
44.55 bps increase, and a hike reduces yields by 28.95 bps — both statistically
significant. This maturity is now a definitive indicator of policy expectations, inflation
fears, and long-term risk pricing. The growing magnitude of the yield shift one month
later confirms that the RBI’s stance is being internalized into long-term macroeconomic
forecasts.

23 | P a g e
Thematic Interpretation:

1. Persistence of Policy Effects:

Even after four weeks, the market response to monetary policy remains substantial, especially
in the mid-to-long segments. The sustained change in yields indicates that the RBI’s actions
have a lasting influence, not just through liquidity but also via the signaling channel. This
persistence reinforces the view that India's bond markets gradually digest policy decisions.

Conclusion: Effects are clearly persistent, especially for 5Y and 10Y yields, with the strongest
response observed in the 4-week horizon so far.

2. Asymmetry in Yield Reaction:

At the 4-week mark, asymmetry intensifies. Rate cuts lead to larger upward moves in yields
than the downward moves seen post-hike. For instance, in the 10Y segment, a 44.55 bps rise
follows a cut, while only a 28.95 bps fall follows a hike. This suggests that market participants
may expect inflation or fiscal loosening after easing, while hikes are seen as corrective and less
surprising.

Conclusion: Yield curve responses continue to be asymmetric, with stronger inflation

expectations embedded in the response to cuts.

Policy & Market Implications:

Implication Explanation
Amplified long-term Bond yields respond more dramatically at longer horizons, showing
expectations market's evolving inflation forecast
Credibility of policy Persistent yield drops post-hike reinforce RBI’s ability to anchor
tightening inflation
Market skeptical of rate Larger yield increases post-cut show investors may fear inflation,
cuts deficit or excessive liquidity

In conclusion, the 4-week analysis reveals a mature phase of yield adjustment. By this time,
investors have had sufficient opportunity to process and price in monetary policy actions. The
growing yield impact, especially for cuts, underscores the importance of communication and
credibility. Policymakers must be aware that easing actions are interpreted not just as growth
stimuli but also as inflation and fiscal risk signals. The data affirm that both persistence and
asymmetry continue to shape the yield curve well beyond the immediate aftermath of a policy
move.

24 | P a g e
 4. REGRESSION ANALYSIS (8-Week Horizon)

Objective:

This section presents an extended analysis of how government bond yields respond two months
after RBI's monetary policy changes. The 8-week horizon helps us understand whether the
effects of rate hikes and cuts fade out, persist, or compound over a longer duration. It also
evaluates whether expectations have normalized or if markets continue to internalize policy
direction, especially in terms of forward guidance and inflation anticipation.

The objective is to test the full duration of monetary transmission, particularly for:

• Structural market expectations

• Long-term inflation anchors
• Risk and liquidity premia

Regression Results Summary (Week +8):

Hike Impact Cut Impact

Maturity Significant? Notes
(β1) (β2)
Cut impact dominates short-end even at 2
3M -13.93 bps +20.03 bps Cut only
months
Short-term inflation concerns continue to
6M -3.83 bps +25.66 bps Cut only
be priced in
1Y -35.87 bps +45.79 bps Both Sharp, asymmetric, and persistent impact

25 | P a g e
 Mid-curve reacts only to cuts, hikes fade
3Y -8.16 bps +26.56 bps Cut only
out
Peak reaction at this horizon, highly
5Y -49.28 bps +58.12 bps Both
asymmetric
Long-term segment reflects massive
10Y -51.58 bps +61.99 bps Both
expectations shift

Interpretation of Results by Maturity:

Short-Term Yields (3M, 6M, 1Y):

• 3M Yield: Two months after the monetary policy event, the 3-month yield shows a
significant rise (+20.03 bps) following a cut and a continued, although not significant,
decline post-hike. This behavior reflects a delayed inflation signal or a perception of
excess liquidity. It also indicates that markets do not quickly neutralize short-end yield
changes in response to accommodative policy.
• 6M Yield: The 6-month maturity reflects similar dynamics, with a robust 25.66 bps
increase in yields after a cut. Although hikes do not elicit a significant response, the
persistence of elevated yields highlights structural inflation fears or uncertainty. This
may point to RBI's dovish stance being seen as misaligned with underlying macro
conditions.
• 1Y Yield: Both hikes (-35.87 bps) and cuts (+45.79 bps) lead to statistically strong yield
movements. The magnitude of the response is amplified compared to earlier horizons.
This suggests that the market has now fully incorporated forward guidance and that
yield reactions are shaped by expectations of future policy actions. This also confirms
the presence of a strong asymmetric bias.

Mid-Term Yields (3Y, 5Y):

• 3Y Yield: The 3-year yield remains sensitive to cuts (+26.56 bps), while hike responses
diminish, implying that accommodative policies shape the mid-curve more forcefully
over time. As this segment usually reflects both short- and medium-term inflation
expectations, the result points toward a credibility gap in easing actions.
• 5Y Yield: The 5-year maturity shows a major turning point in yield behavior. Yields
fall steeply (-49.28 bps) post-hike and rise significantly (+58.12 bps) post-cut, both with
high statistical confidence. These results suggest that this maturity embodies the
intersection of liquidity outlook and growth perception. The high sensitivity here also
underlines the market’s evolving understanding of the monetary regime.

Long-Term Yields (10Y):

10Y Yield: The 10-year bond yield marks the strongest observed effect across all horizons and
maturities. Following a cut, yields rise by 61.99 bps, while they fall by 51.58 bps after a hike.
These results are not only statistically significant but also economically substantial. The steep
responses show that the 10Y segment captures market expectations regarding inflation, fiscal
stability, and macroeconomic guidance. The 8-week data signals that the yield curve’s long-
end is shaped by deep shifts in policy credibility and risk sentiment.

26 | P a g e
Thematic Interpretation:

1. Persistence of Policy Effects:

Yield shifts persist, and in some cases amplify, even two months after a policy change.
Especially in the 5Y and 10Y maturities, the transmission mechanism seems to reach its full
impact at this horizon. This persistence validates the view that monetary policy is gradually
internalized and diffused through the term structure.

Conclusion: The 8-week horizon shows maximum persistence in yield responses across the
curve.

2. Asymmetry in Yield Reaction:

Rate cuts generate sharper and larger responses in yields across all maturities than hikes do.
This holds particularly true for the 5Y and 10Y maturities, where the cut-induced yield increase
is over 60 bps. Asymmetry implies that while tightening is seen as stabilizing, easing creates
uncertainty about inflation, fiscal response, or future tightening.

Conclusion: The asymmetry observed earlier now peaks at 8 weeks, reflecting long-run
expectations and policy skepticism.

Policy & Market Implications:

Implication Explanation
Long-term expectations 10Y yield changes show that markets internalize macro guidance
priced in with a lag but lasting effect
Easing triggers risk Yield surge post-cut reflects potential fears over inflation, fiscal
sentiment burden, or growth overreach
Tightening perceived as Persistent drop post-hike across maturities confirms RBI's anti-
credible inflation credibility

In conclusion, the 8-week horizon uncovers the deepest and most asymmetric reaction in India's
fixed income market to monetary policy surprises. Both the magnitude and persistence of
responses reinforce the significance of effective policy communication and macroeconomic
alignment. For central bankers, the takeaway is clear: markets may accept hikes with calm, but
react to cuts with heightened scrutiny. The data provide compelling evidence of long-term
transmission, confirming that policy effects culminate and peak at this extended horizon.

27 | P a g e
5. IMPULSE RESPONSE FUNCTION

28 | P a g e
The impulse response analysis shows that bond yields across different maturities in India
respond significantly and consistently to changes in the policy rate announced by the RBI. The
strength and direction of these responses vary depending on the maturity of the bond and
whether the policy action was a hike or a cut.

For short-term maturities such as 3-month and 6-month yields, the impact of repo rate cuts is
stronger and more persistent compared to hikes. In the case of the 3-month yield, rate cuts lead
to a consistent upward movement in yields, while hikes only slightly reduce yields. The 6-
month yields behave similarly, where cuts result in a strong upward shift while the effect of
hikes is relatively muted.

Medium-term yields, such as the 1-year and 3-year tenors, also show clear responses. The 1-
year yield responds to both hikes and cuts, but with stronger effects for cuts, indicating the
market adjusts its expectations meaningfully in both scenarios. The 3-year yield also responds
positively to cuts and shows a less pronounced reaction to hikes.

For long-term maturities like the 5-year and 10-year yields, the responses are the most
significant. Both cuts and hikes generate strong and persistent changes in yields over the 8-
week horizon. However, the impact of cuts is particularly notable, with yields increasing
steadily over time, suggesting that rate cuts are associated with upward revisions in long-term
inflation expectations or risk premiums.

These findings suggest two important dynamics in the transmission of monetary policy: (1)
persistence — the impact of policy changes remains visible even after several weeks; and (2)
asymmetry — the market tends to react more strongly to rate cuts than to rate hikes.

Maturity Persistence Asymmetry

3M Moderate Yes
6M Strong Yes
1Y Strong No
3Y Strong Yes
5Y Very Strong No
10Y Very Strong Yes

29 | P a g e
RESULTS AND FINDINGS OF THE PROJECT

1. Monetary Policy Significantly Influences the Yield Curve

The empirical results confirm that repo rate changes announced by the Reserve Bank of India
(RBI) exert a statistically significant and economically meaningful influence on government
bond yields across the maturity spectrum. This reinforces the fundamental theoretical premise
of monetary transmission—that interest rate decisions impact not only short-term funding rates
but also broader market yields through liquidity conditions, investor expectations, and
perceived policy credibility.

2. Policy Effects Are Persistent Over Time

A key finding of the study is the persistent nature of yield responses to monetary policy actions.
Yield changes do not dissipate rapidly; rather, they continue to evolve over extended horizons.
For example, the 10-year yield rises by over 60 basis points within eight weeks of a repo rate
cut, and the 1-year yield continues to decline progressively after a hike. This persistence
suggests that market expectations adjust gradually, and that monetary policy announcements
initiate a dynamic process of repricing across the yield curve rather than triggering
instantaneous adjustments.

3. Asymmetry in Yield Response to Hikes vs. Cuts

Another notable conclusion is the asymmetric response of bond yields to the direction of policy
actions. Across most maturities, the magnitude of the yield increase following a cut exceeds
the magnitude of the decline following a hike. This asymmetry is particularly pronounced at
longer maturities, such as the 5-year and 10-year segments. For instance, the 5-year yield rises
by approximately 58 basis points after a cut but falls by only 49 basis points following a hike.
This indicates that markets respond more forcefully to monetary easing, potentially due to
inflation concerns, fiscal pressures, or shifts in future policy expectations.

4. The Yield Curve as a Forward-Looking Indicator

The results affirm the yield curve’s role as a forward-looking instrument that reflects investor
expectations about macroeconomic conditions. Short-term yields (3M, 6M) are primarily
influenced by immediate liquidity and interest rate expectations. In contrast, medium- and
long-term yields (1Y to 10Y) respond to forward-looking variables such as inflation, fiscal
sustainability, and overall macroeconomic outlook. The significant and sustained upward

30 | P a g e
movement of long-term yields in response to rate cuts underscores how policy decisions shape
the trajectory of inflation expectations and risk premia.

5. Contextual Sensitivity of Market Interpretation

The bond market's interpretation of monetary policy actions is sensitive to the broader
macroeconomic context. While rate hikes are generally perceived as stabilizing and
deflationary, rate cuts—especially during uncertain periods—are sometimes interpreted as
signals of future macroeconomic instability. This context-dependent interpretation adds a
behavioral and psychological layer to monetary transmission, emphasizing the importance of
central bank communication and credibility.

6. Mid- and Long-Term Bonds Are Most Sensitive to Policy

The analysis reveals that the 5-year and 10-year bonds exhibit the strongest and most persistent
responses to monetary policy shocks. These maturities consistently show the highest
coefficients and statistical significance across all forecast horizons. This underscores the
importance of the mid- and long-end of the yield curve as indicators of market sentiment and
confidence in the RBI’s monetary stance.

7. Policy and Market Implications

The findings have important implications for both policy design and financial market
operations:

• Communication Strategy: Since yield responses evolve over multiple weeks, the RBI's
forward guidance and clarity of communication play a critical role in shaping
expectations.
• Easing Trade-Offs: While rate cuts aim to stimulate the economy, they may also raise
long-term yields, thereby tightening financial conditions at the long end of the curve.
• Credibility Anchor: The symmetric and persistent downward response of yields to rate
hikes reflects confidence in the RBI's inflation-targeting framework.

31 | P a g e
CONCLUSION
This study reaffirms the central role of monetary policy in shaping financial market outcomes,
particularly through its influence on the yield curve. The evidence shows that RBI's policy rate
changes are neither short-lived nor uniform in effect—they persist over time and vary
significantly across different maturities.

More importantly, the findings underscore a clear asymmetry in market response: bond yields
tend to rise more sharply and remain elevated longer following a repo rate cut than they fall
after a hike. This indicates that markets often interpret easing measures as signals of future
inflationary pressure or macroeconomic uncertainty, rather than simply as stimulative actions.

These insights carry important implications for policymakers. Traditional interest rate tools,
while still effective, must be complemented by clear forward guidance and consistent
communication strategies, especially in an environment where financial markets are
increasingly forward-looking and sensitive to perceived shifts in credibility.

In sum, this report not only enriches our understanding of monetary transmission in India but
also offers valuable perspectives for future policy design—reminding us that the effectiveness
of monetary policy lies as much in perception and communication as it does in the actual policy
move.

32 | P a g e
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Clarida, R., Galí, J., & Gertler, M. (2000). Monetary policy rules and macroeconomic stability:
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Annual, 23, 103–148.

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https://doi.org/10.1257/mac.5.1.183

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ECB’s asset purchase programme on the yield curve. International Journal of Central Banking,
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McKay, A., Nakamura, E., & Steinsson, J. (2016). The power of forward guidance revisited.
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APPENDIX
Regression Results

=== Horizon: 1 weeks ===

Maturity: Yield_3M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0056 0.004 1.306 0.193 -0.003 0.014

HikeDummy -0.1039 0.030 -3.425 0.001 -0.164 -0.044

CutDummy -0.0746 0.033 -2.248 0.025 -0.140 -0.009

==============================================================================

Maturity: Yield_6M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -4.778e-05 0.004 -0.011 0.992 -0.009 0.009

HikeDummy 0.0129 0.032 0.406 0.685 -0.049 0.075

CutDummy 0.1352 0.035 3.902 0.000 0.067 0.203

==============================================================================

Maturity: Yield_1Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0039 0.007 0.575 0.566 -0.009 0.017

HikeDummy -0.1722 0.048 -3.600 0.000 -0.266 -0.078

CutDummy 0.0475 0.052 0.908 0.365 -0.055 0.150

35 | P a g e
==============================================================================

Maturity: Yield_3Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0044 0.004 1.026 0.306 -0.004 0.013

HikeDummy -0.0794 0.030 -2.649 0.008 -0.138 -0.020

CutDummy -0.0078 0.033 -0.237 0.813 -0.072 0.057

==============================================================================

Maturity: Yield_5Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0001 0.005 -0.021 0.983 -0.010 0.010

HikeDummy -0.1782 0.035 -5.147 0.000 -0.246 -0.110

CutDummy 0.1821 0.038 4.809 0.000 0.108 0.257

==============================================================================

Maturity: Yield_10Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -3.413e-05 0.006 -0.005 0.996 -0.012 0.012

HikeDummy -0.1283 0.044 -2.908 0.004 -0.215 -0.041

CutDummy 0.1380 0.048 2.860 0.005 0.043 0.233

==============================================================================

36 | P a g e
=== Horizon: 2 weeks ===

Maturity: Yield_3M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0052 0.006 0.856 0.393 -0.007 0.017

HikeDummy -0.0824 0.043 -1.918 0.056 -0.167 0.002

CutDummy 0.0560 0.047 1.192 0.234 -0.036 0.148

==============================================================================

Maturity: Yield_6M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0020 0.006 0.334 0.739 -0.010 0.014

HikeDummy 0.0168 0.043 0.391 0.696 -0.068 0.101

CutDummy 0.1504 0.047 3.199 0.002 0.058 0.243

==============================================================================

Maturity: Yield_1Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0018 0.009 0.198 0.843 -0.016 0.019

HikeDummy -0.1631 0.063 -2.570 0.011 -0.288 -0.038

CutDummy 0.2184 0.069 3.147 0.002 0.082 0.355

==============================================================================

Maturity: Yield_3Y

==============================================================================

37 | P a g e
 coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0038 0.006 0.650 0.516 -0.008 0.015

HikeDummy -0.0430 0.042 -1.031 0.303 -0.125 0.039

CutDummy 0.1110 0.046 2.432 0.016 0.021 0.201

==============================================================================

Maturity: Yield_5Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0023 0.008 -0.294 0.769 -0.018 0.013

HikeDummy -0.1927 0.056 -3.462 0.001 -0.302 -0.083

CutDummy 0.2643 0.061 4.343 0.000 0.145 0.384

==============================================================================

Maturity: Yield_10Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0030 0.009 -0.342 0.733 -0.020 0.014

HikeDummy -0.1770 0.062 -2.853 0.005 -0.299 -0.055

CutDummy 0.3110 0.068 4.584 0.000 0.177 0.445

==============================================================================

=== Horizon: 4 weeks ===

Maturity: Yield_3M

==============================================================================

coef std err t P>|t| [0.025 0.975]

38 | P a g e
------------------------------------------------------------------------------

const 0.0107 0.008 1.270 0.205 -0.006 0.027

HikeDummy -0.1329 0.060 -2.228 0.027 -0.250 -0.016

CutDummy 0.0519 0.065 0.795 0.427 -0.077 0.180

==============================================================================

Maturity: Yield_6M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0067 0.008 0.794 0.428 -0.010 0.023

HikeDummy -0.0072 0.060 -0.121 0.904 -0.125 0.111

CutDummy 0.2089 0.065 3.190 0.002 0.080 0.338

==============================================================================

Maturity: Yield_1Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0050 0.013 0.382 0.703 -0.021 0.031

HikeDummy -0.2987 0.093 -3.224 0.001 -0.481 -0.116

CutDummy 0.1790 0.101 1.767 0.078 -0.020 0.378

==============================================================================

Maturity: Yield_3Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0096 0.008 1.140 0.255 -0.007 0.026

HikeDummy -0.1150 0.060 -1.928 0.055 -0.232 0.002

CutDummy 0.1506 0.065 2.309 0.022 0.022 0.279

==============================================================================

39 | P a g e
Maturity: Yield_5Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0042 0.013 -0.331 0.741 -0.029 0.021

HikeDummy -0.3091 0.090 -3.450 0.001 -0.485 -0.133

CutDummy 0.3582 0.098 3.655 0.000 0.165 0.551

==============================================================================

Maturity: Yield_10Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0055 0.013 -0.426 0.670 -0.031 0.020

HikeDummy -0.2895 0.091 -3.179 0.002 -0.469 -0.110

CutDummy 0.4455 0.100 4.474 0.000 0.250 0.641

==============================================================================

=== Horizon: 8 weeks ===

Maturity: Yield_3M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0185 0.013 1.437 0.152 -0.007 0.044

HikeDummy -0.1393 0.091 -1.532 0.127 -0.318 0.040

CutDummy 0.2003 0.099 2.013 0.045 0.005 0.396

==============================================================================

40 | P a g e
Maturity: Yield_6M

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0176 0.013 1.353 0.177 -0.008 0.043

HikeDummy -0.0383 0.092 -0.416 0.677 -0.219 0.143

CutDummy 0.2566 0.101 2.550 0.011 0.059 0.455

==============================================================================

Maturity: Yield_1Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0017 0.021 0.084 0.933 -0.039 0.042

HikeDummy -0.3587 0.146 -2.463 0.014 -0.645 -0.072

CutDummy 0.4579 0.159 2.875 0.004 0.144 0.771

==============================================================================

Maturity: Yield_3Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const 0.0180 0.013 1.393 0.164 -0.007 0.043

HikeDummy -0.0816 0.091 -0.897 0.371 -0.261 0.097

CutDummy 0.2656 0.100 2.668 0.008 0.070 0.462

==============================================================================

Maturity: Yield_5Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

41 | P a g e
------------------------------------------------------------------------------

const -0.0072 0.021 -0.342 0.733 -0.048 0.034

HikeDummy -0.4928 0.148 -3.329 0.001 -0.784 -0.201

CutDummy 0.5812 0.162 3.589 0.000 0.263 0.900

==============================================================================

Maturity: Yield_10Y

==============================================================================

coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

const -0.0059 0.021 -0.276 0.783 -0.048 0.036

HikeDummy -0.5158 0.151 -3.412 0.001 -0.813 -0.218

CutDummy 0.6199 0.165 3.750 0.000 0.295 0.945

42 | P a g e