Monetary Policy and Liquidity in India. Evaluating the Economic Impact of Key Instruments (2004–2024)

Research Paper (undergraduate) , 2024 , 73 Pages , Grade: A

Business economics - Economic Policy

This study investigates the pivotal role of monetary policy in managing liquidity and its broader implications for India’s economic performance between 2004–2005 and 2023–2024. The primary objective is to empirically assess how key monetary instruments—namely the Bank Rate, Repo Rate, Reverse Repo Rate, Cash Reserve Ratio (CRR), and Statutory Liquidity Ratio (SLR)—affect the money supply, specifically M3 (Broad Money). Utilizing a quantitative research design, the study applies bivariate correlation and Ordinary Least Squares (OLS) regression to evaluate the strength and direction of these relationships. Findings indicate that higher repo rates are associated with slower growth in money supply, while reductions in CRR and SLR foster liquidity expansion. Moreover, a strong positive correlation between policy tools and money supply underlines the significant influence of monetary adjustments on India’s financial environment. The OLS results show a negative impact of the bank rate and positive effects from the repo rate and SLR on broad money. These insights underscore the necessity of a balanced and responsive monetary policy framework to enhance credit availability, support financial stability, and promote sustained economic growth in emerging economies like India.

TABLE OF CONTENT

ABSTRACT

1. INTRODUCTION
1.1 Theoretical Framework
1.2 Introduction of the Study
1.3 Objectives of the Study
1.4 Hypothesis of the Study
1.5 Scope of the Study

2. REVIEW OF LITERATURE
2.1 Review of Literature
2.2 Research Gap

3. RESEARCH METHODOLOGY
3.1 Research Design
3.2 Sample Period
3.3 Data Type
3.4 Data Sources
3.5 Variables
3.6 Statistical Tools

4. DATA ANALYSIS AND INTERPRETATION
4.1 Unit Root Test
4.2 Trend Analysis
4.3 Bivariate Correlation
4.4 Ordinary Least Square (OLS)
4.5 Vector Auto regression (VAR)
4.6 Limitations of the Study

5. FINDINGS AND SUGGESTIONS
5.1 Findings
5.2 Suggestions
5.3 Conclusions

REFERENCES

ABSTRACT

Monetary policy plays a critical role in liquidity management, directly impacting economic performance in India. This study examines the relationship between monetary policy and money supply using a quantitative research approach, analysing time series data from 2004-2005 to 2023-2024. The study employs statistical techniques, including bivariate correlation and Ordinary Least Squares (OLS) regression, to assess the impact of key monetary policy instruments—Bank Rate, Repo Rate, Reverse Repo Rate, Cash Reserve Ratio (CRR), and Statutory Liquidity Ratio (SLR)—on M3 (Broad Money). The findings reveal that higher repo rates correspond to reduced money supply growth, while reductions in CRR and SLR facilitate liquidity expansion. A strong positive correlation suggests that future monetary policy adjustments will significantly influence liquidity conditions. The OLS results indicate a significant negative impact of the bank rate on money supply, while repo rate and SLR exhibit a positive effect. These findings underscore the crucial role of monetary policy adjustments in ensuring financial stability, influencing credit availability, and supporting economic growth. The study highlights the importance of a balanced monetary policy framework to optimize liquidity management and economic performance in India.

Keywords: Monetary Policy, Liquidity Management, Money Supply, Bank Rate, Repo Rate

INTRODUCTION

1.1 Theoretical Framework

Introduction

Economic performance is a key determinant of a nation's growth, stability, and overall prosperity. It is influenced by various factors, including fiscal policy, trade dynamics, industrial production, and financial stability. Among these, monetary policy plays a crucial role in shaping economic performance by managing liquidity within the financial system. Liquidity management, in this context, refers to the regulation of money supply and credit availability to ensure financial stability while fostering economic growth.

Monetary policy serves as a primary instrument for macroeconomic regulation, particularly in a developing country like India, where the financial sector is evolving, and economic challenges require dynamic interventions. The Reserve Bank of India (RBI), as the country’s central bank, is responsible for formulating and implementing monetary policies aimed at controlling inflation, stabilizing currency, ensuring price stability, and promoting economic growth. Through various instruments such as interest rate adjustments, open market operations, and reserve ratio requirements, the RBI seeks to balance liquidity in the economy while addressing inflationary or recessionary pressures.

The Significance of Monetary Policy in Economic Performance:-

Economic performance is measured using indicators such as Gross Domestic Product (GDP) growth rate, employment levels, inflation rate, fiscal deficit, and financial market stability. The ability of a nation to optimize these factors determines its economic trajectory. However, improper liquidity management can lead to financial imbalances—excess liquidity can fuel inflation, while liquidity shortages can cause economic stagnation. Monetary policy acts as a corrective mechanism that ensures the economy operates within an optimal range of liquidity, preventing financial disruptions while facilitating sustainable growth.

In the Indian context, monetary policy has evolved over the decades in response to changing economic conditions, financial sector developments, and global economic trends. From strictly regulated banking operations in the pre-liberalization era (before 1991) to more market-oriented policies in the post-liberalization period, India's monetary framework has continuously adapted to new challenges. The RBI’s role in regulating liquidity has become even more crucial in times of financial crises, such as the 2008 global financial meltdown and the economic disruptions caused by the COVID-19 pandemic.

Liquidity Management and Its Impact on the Indian Economy: -

Liquidity management is at the core of monetary policy implementation. The RBI ensures that commercial banks and financial institutions maintain adequate reserves to meet credit demands while preventing excessive money supply that could lead to inflationary pressures. The major tools used by the RBI for liquidity management include:

1. Cash Reserve Ratio (CRR): A portion of bank deposits that must be kept with the RBI, influencing the lending capacity of banks.
2. Statutory Liquidity Ratio (SLR): A reserve requirement mandating banks to hold a certain percentage of their net demand and time liabilities in liquid assets like government bonds.
3. Open Market Operations (OMO): Buying and selling government securities to regulate money supply in the banking system.
4. Liquidity Adjustment Facility (LAF): A short-term borrowing and lending facility used to manage daily liquidity mismatches.
5. Repo Rate and Reverse Repo Rate: Key interest rates used to control borrowing costs for banks, impacting overall credit growth and inflation.

In India, effective liquidity management through these tools has helped in maintaining stable economic growth, controlling inflation, and ensuring financial sector stability. However, challenges such as external economic shocks, fluctuating capital flows, and structural inefficiencies often test the effectiveness of monetary policies.

The Need for an Optimized Monetary Policy Framework:-

While monetary policy has proven to be an essential tool for liquidity management, it is not without limitations. Policymakers must strike a balance between controlling inflation and promoting economic growth, as overly restrictive policies may stifle industrial and commercial activities, whereas excessively loose policies could lead to financial instability.

The optimization of economic performance through monetary policy requires a dynamic and forward-looking approach, integrating global best practices while considering the unique characteristics of the Indian economy. The Reserve Bank of India continues to refine its monetary policy framework, incorporating data-driven insights, market intelligence, and stakeholder consultations to ensure that liquidity management strategies are effective and sustainable.

Overview of Key Concepts

Economic performance is shaped by multiple factors, including fiscal and monetary policies, liquidity management, and financial stability. In the context of India, monetary policy and liquidity management play a crucial role in ensuring stable economic growth. This section provides an in-depth overview of the key concepts related to the study:

1. Monetary Policy
2. Liquidity Management
3. Economic Performance

Each of these concepts is interconnected and directly impacts the functioning of the economy. An efficient monetary policy ensures appropriate liquidity levels, which in turn influences economic performance by maintaining price stability, supporting credit growth, and fostering investment.

1. Monetary Policy

Monetary policy refers to the framework and actions taken by a nation’s central bank to regulate the money supply, interest rates, and availability of credit in the economy. The Reserve Bank of India (RBI) formulates and implements monetary policy in India with the primary objectives of:

· Ensuring price stability (controlling inflation)
· Promoting economic growth
· Maintaining financial stability

A well-implemented monetary policy helps in achieving macroeconomic stability by balancing inflation and growth objectives.

Types of Monetary Policy

Monetary policy can be classified into two broad categories:

1. Expansionary Monetary Policy

· Implemented when the economy is experiencing slow growth or a recession.
· Involves increasing money supply, lowering interest rates, and making borrowing cheaper to encourage investment and spending.
· Often leads to higher inflation if not controlled properly.
· Used during economic downturns, such as the COVID-19 pandemic, when the RBI lowered the repo rate to boost economic activity.

2. Contractionary Monetary Policy

· Implemented when inflation is rising beyond acceptable levels.
· Involves reducing money supply, increasing interest rates, and making borrowing expensive to curb excess spending.
· Helps in controlling inflation but can slow down economic growth if applied excessively.

Monetary Policy Tools Used by the RBI

The RBI uses various quantitative and qualitative instruments to regulate liquidity in the economy.

Quantitative Instruments (Directly Impacting Money Supply):-

1. Repo Rate & Reverse Repo Rate – The interest rate at which banks borrow from the RBI (repo) and lend to the RBI (reverse repo).
2. Cash Reserve Ratio (CRR) – The percentage of a bank’s total deposits that must be kept with the RBI, affecting the bank’s lending capacity.
3. Statutory Liquidity Ratio (SLR) – The percentage of a bank’s total deposits that must be held in liquid assets like government bonds.
4. Open Market Operations (OMO) – The buying and selling of government securities to regulate liquidity in the financial system.

Qualitative Instruments (Indirect Control Over Money Supply):-

1. Moral Suasion – The RBI persuades banks to follow certain policies for economic stability.
2. Credit Rationing – The central bank restricts credit to certain sectors to prevent over-lending.

2. Liquidity Management

Liquidity management refers to the process of ensuring that sufficient funds are available in the economy to support business activities while preventing excess liquidity that could cause inflationary pressures. In simpler terms, it is about maintaining the right balance of money supply in the financial system.

A well-managed liquidity system

1.Ensures smooth functioning of financial markets
2.Prevents inflationary and deflationary pressures
3.Maintains stability in interest rates
4.Supports economic growth and investment

Factors Influencing Liquidity in the Economy:-

1. Monetary Policy Decisions: Changes in repo rates, CRR, and SLR directly impact liquidity.
2. Government Spending & Borrowing: Increased government borrowing can drain liquidity, while government spending injects liquidity into the economy.
3. Foreign Exchange Flows: High foreign capital inflows increase liquidity, while outflows reduce liquidity.
4. Banking Sector Behaviour: Lending patterns of commercial banks impact money circulation.
5. Inflation & Economic Growth: High inflation often leads to tighter liquidity control, whereas sluggish growth prompts liquidity injections.

Liquidity Management Tools Used by the RBI:-

The RBI employs multiple instruments to regulate liquidity in the financial system:

1. Liquidity Adjustment Facility (LAF): A framework where banks can borrow from or lend to the RBI to manage short-term liquidity mismatches.
2. Marginal Standing Facility (MSF): An emergency borrowing window for banks facing sudden liquidity shortages.
3. Market Stabilization Scheme (MSS): The issuance of government bonds to absorb excess liquidity from the banking system.

These tools help the RBI maintain a stable financial environment, ensuring that neither excess liquidity nor liquidity shortages disrupt economic activity.

3. Economic Performance

Economic performance refers to how well an economy is functioning based on key macroeconomic indicators, such as:

· Gross Domestic Product (GDP) growth rate – Measures economic expansion.

· Inflation rate – Assesses price stability.
· Employment levels – Indicates labour market strength.
· Interest rates – Reflect credit accessibility.
· Foreign exchange stability – Ensures confidence in the currency.

A country with stable and optimized liquidity management through effective monetary policy can maintain strong economic performance, ensuring sustainable growth and preventing financial crises.

Impact of Monetary Policy and Liquidity on Economic Performance:-

1. Controlled Inflation: A well-regulated monetary policy prevents hyperinflation and ensures stable prices.
2. Stable Interest Rates: Balanced liquidity management prevents erratic fluctuations in lending rates.
3. Encouraged Investment: A predictable monetary framework boosts investor confidence in the economy.
4. Employment Growth: An efficient economic system fosters job creation and higher wages.

However, if liquidity is mismanaged, it can lead to: -

1. Excess inflation, reducing purchasing power.
2. Financial market volatility, affecting investor confidence.
3. Economic slowdowns, restricting credit availability and growth.

The relationship between monetary policy, liquidity management, and economic performance is crucial in shaping India’s economic stability. The Reserve Bank of India (RBI) plays a central role in implementing monetary policies that ensure optimal liquidity levels, helping control inflation, stabilize interest rates, and support economic growth.

A well-calibrated monetary framework allows India to respond effectively to domestic and global economic fluctuations, ensuring that economic growth remains sustainable and inclusive. Understanding these key concepts is essential for policymakers, financial institutions, and businesses to make informed decisions that contribute to long-term economic success.

Role of Monetary Policy in Liquidity Management

Monetary policy plays a fundamental role in managing liquidity in the economy, ensuring that the financial system functions efficiently while maintaining economic stability. Liquidity management is essential for balancing money supply, controlling inflation, stabilizing interest rates, and promoting sustainable growth. In India, the Reserve Bank of India (RBI) is responsible for formulating and implementing monetary policies that regulate liquidity in the financial system.

This section explores:-

1. The Relationship Between Monetary Policy and Liquidity Management
2. Objectives of Liquidity Management in Monetary Policy
3. Monetary Policy Tools for Liquidity Management
4. Challenges in Liquidity Management Through Monetary Policy

By effectively regulating liquidity, the RBI ensures the stability of the banking sector, supports economic expansion, and prevents financial disruptions.

1. The Relationship between Monetary Policy and Liquidity Management:-

Understanding Liquidity in the Economy:

Liquidity refers to the availability of money and credit in the financial system. It influences:

1. The ability of banks to lend to businesses and individuals.
2. Interest rates, affecting borrowing and investment decisions.
3. Overall economic activity, including consumption, production, and employment.

If liquidity is not properly managed:

· Excess liquidity → leads to inflation, asset bubbles, and financial instability.

· Liquidity shortages → Slows economic growth, reduces credit availability, and increases borrowing costs.

Monetary policy serves as a corrective mechanism by ensuring that liquidity levels remain optimal. The RBI uses various monetary instruments to regulate the flow of money and credit in the economy.

How Monetary Policy Controls Liquidity:-

1. By influencing money supply: Adjusting reserve requirements and interest rates to control liquidity.
2. By stabilizing inflation: Reducing money supply during inflationary periods and increasing it during slowdowns.
3. By guiding credit availability: Encouraging or restricting lending to priority sectors.
4. By maintaining currency stability: Preventing excess liquidity that could devalue the rupee.

Thus, monetary policy is the primary tool for managing liquidity, ensuring that the economy operates efficiently without financial disruptions.

2. Objectives of Liquidity Management in Monetary Policy:-

The RBI's liquidity management strategy is designed to maintain financial stability while supporting economic growth. The key objectives include:

A. Controlling Inflation

· Excess liquidity leads to higher demand for goods and services, pushing up inflation.
· The RBI tightens monetary policy (raises repo rates, increases CRR) to reduce money supply and curb inflation.
· Example: Between 2010-2013, the RBI raised interest rates multiple times to control inflation caused by high food prices and rising global oil costs.

B. Supporting Economic Growth

· If liquidity is too tight, businesses and consumers face credit shortages, slowing down economic activity.
· The RBI loosens monetary policy (lowers repo rates, reduces CRR) to increase liquidity and encourage spending.
· Example: Post-2020 pandemic, the RBI cut repo rates to boost liquidity and support economic recovery.

C. Ensuring Financial Stability

· Sudden liquidity imbalances can lead to banking crises and financial market instability.
· The RBI uses liquidity adjustment mechanisms to prevent large fluctuations in liquidity.
· Example: During the 2008 global financial crisis, the RBI injected liquidity into the banking system to prevent market disruptions.

D. Maintaining Stable Interest Rates

· If liquidity is volatile, interest rates fluctuate, making borrowing and investment unpredictable.
· The RBI ensures a stable interest rate environment to foster long-term investments.
· Example: The Monetary Policy Committee (MPC) sets repo rates based on inflation and growth trends.
By balancing these objectives, the RBI ensures that monetary policy remains effective in regulating liquidity while fostering economic stability.

3. Monetary Policy Tools for Liquidity Management:-

To manage liquidity effectively, the RBI employs various monetary policy instruments. These tools can be classified into direct and indirect measures.

A. Direct Tools (Quantitative Measures)

These tools impact the money supply directly by adjusting liquidity levels in the banking system.

1. Cash Reserve Ratio (CRR)

· The percentage of a bank’s deposits that must be kept with the RBI.
· Higher CRR → Reduces liquidity by restricting banks' lending ability.
· Lower CRR → Increases liquidity by allowing banks to lend more.

· Example: In 2012, the RBI cut CRR to inject liquidity into the banking system during an economic slowdown.

2. Statutory Liquidity Ratio (SLR)

· The percentage of deposits banks must hold in the form of liquid assets (government securities).
· Higher SLR → Reduces liquidity by limiting funds available for lending.
· Lower SLR → Increases liquidity and promotes credit expansion.

3. Open Market Operations (OMO)

· The RBI buys or sells government securities to regulate liquidity.
· OMO Purchase → Injects liquidity into the system.
· OMO Sale → Absorbs excess liquidity.
· Example: The RBI conducted OMO purchases in 2020 to inject liquidity amid COVID-19 disruptions.

B. Indirect Tools (Qualitative Measures)

These tools influence liquidity by affecting banks’ credit behaviour.

1. Repo Rate and Reverse Repo Rate

· Repo Rate: The rate at which banks borrow from the RBI.
· Higher Repo Rate → Reduces liquidity by making borrowing costly.
· Lower Repo Rate → Increases liquidity by making borrowing cheaper.
· Example: The RBI cut repo rates to 4% in 2020 to encourage borrowing and support the economy.
· Reverse Repo Rate: The rate at which the RBI borrows from banks.
· Higher Reverse Repo Rate → Absorbs liquidity as banks prefer to deposit funds with the RBI.

2. Liquidity Adjustment Facility (LAF)

· Allows banks to adjust liquidity positions through repo and reverse repo operations.
· Helps manage short-term liquidity fluctuations.

3. Marginal Standing Facility (MSF)

· An emergency borrowing option for banks facing sudden liquidity shortages.
These tools help the RBI maintain a stable liquidity environment, ensuring smooth financial operations

4. Challenges in Liquidity Management through Monetary Policy:-

Despite its effectiveness, monetary policy faces several challenges in liquidity management:

A. Time Lag in Policy Impact

· Monetary policy decisions take time to influence liquidity and economic conditions.
· Example: Repo rate changes may take months to affect lending and inflation.

B. Global Economic Uncertainty

· International capital flows, oil price fluctuations, and geopolitical events impact liquidity in India.
· Example: Foreign capital outflows in 2018 led to a liquidity crunch despite RBI’s easing measures.

C. Fiscal Policy Constraints

· Government borrowing and fiscal deficits affect liquidity management.
· Excessive government borrowing can crowd out private credit, making monetary policy less effective.

D. Banking Sector Health

· High non-performing assets (NPAs) reduce banks' willingness to lend, limiting monetary policy effectiveness.

Despite these challenges, the RBI continuously adapts its policies to maintain liquidity stability

Advantages of Monetary Policy in Liquidity Management:-

Monetary policy plays a crucial role in regulating liquidity in the financial system, ensuring that money supply aligns with economic growth objectives while preventing inflationary or recessionary pressures. Effective liquidity management through monetary policy offers several advantages, including inflation control, financial stability, economic growth promotion, interest rate stabilization, and crisis management. In India, the Reserve Bank of India (RBI) employs various monetary tools to maintain a balanced liquidity environment, thereby strengthening the country’s economic resilience.

This section explores the key advantages of monetary policy in liquidity management, covering:

1. Inflation Control and Price Stability
2. Financial Market Stability
3. Support for Economic Growth and Investment
4. Interest Rate Stability
5. Crisis Management and Economic Stability
6. Flexibility and Responsiveness
7. Exchange Rate Stability and Foreign Capital Flows

Each of these advantages contributes to a well-functioning economy, ensuring sustainable and balanced development.

1. Inflation Control and Price Stability

How Monetary Policy Regulates Inflation:-

One of the primary objectives of monetary policy is to control inflation by regulating liquidity levels. If too much money is circulating in the economy, demand for goods and services increases, leading to inflation. The RBI uses monetary tightening measures, such as:

1. Increasing the Repo Rate: This makes borrowing more expensive, reducing money supply and controlling inflation.
2. Raising the Cash Reserve Ratio (CRR): Banks are required to keep a higher portion of their deposits with the RBI, reducing their lending capacity.
3. Open Market Operations (OMO): Selling government securities absorbs excess liquidity from the financial system.

2. Financial Market Stability

A stable financial system is essential for economic growth and investment confidence. Unregulated liquidity fluctuations can lead to asset price bubbles, banking sector instability, and credit shortages.

How Monetary Policy Promotes Financial Stability

1. Smoothens Liquidity Cycles: The RBI ensures adequate money supply to prevent financial disruptions.
2. Reduces Speculative Investments: By adjusting interest rates, the RBI discourages excessive risk-taking in financial markets.
3. Prevents Banking Crises: Regulating liquidity ensures that banks have enough reserves to meet withdrawal demands.

3. Support for Economic Growth and Investment

Monetary policy plays a critical role in stimulating economic growth by ensuring an adequate money supply for productive investments.

How Monetary Policy Encourages Growth

1. Lowering Interest Rates to Boost Borrowing: When economic growth slows, the RBI reduces the repo rate, making loans cheaper for businesses and consumers.
2. Increasing Money Supply: Expansionary policies encourage spending, investment, and job creation.
3. Encouraging Credit to Priority Sectors: The RBI directs banks to support agriculture, small industries, and infrastructure, ensuring balanced economic development.

4. Interest Rate Stability

Uncontrolled liquidity fluctuations can lead to volatile interest rates, making borrowing unpredictable for businesses and consumers.

How Monetary Policy Ensures Stable Interest Rates

1. Smoothens Credit Availability: The RBI adjusts liquidity so that banks can lend without sudden rate fluctuations.
2. Prevents Excessive Rate Hikes: During high inflation, gradual rate hikes prevent economic shocks.
3. Encourages Long-Term Investments: Predictable interest rates allow businesses to make informed capital investment decisions.

5. Crisis Management and Economic Stability

Economic crises, such as financial downturns, global recessions, or pandemics, require rapid liquidity adjustments to maintain stability.

How Monetary Policy Helps During Crises

1. Injecting Liquidity During Slowdowns: The RBI lowers repo rates and conducts OMO purchases to provide funds to the economy.
2. Providing Emergency Credit: Liquidity Adjustment Facility (LAF) and Marginal Standing Facility (MSF) allow banks to borrow short-term funds.
3. Stabilizing Banking Operations: Ensuring that banks have enough liquidity to prevent collapses during crises.

6. Flexibility and Responsiveness

Unlike fiscal policy, which takes time to implement, monetary policy can be adjusted quickly to respond to economic changes.

Why Monetary Policy is More Flexible

1. Immediate Impact on Interest Rates: Repo rate changes influence liquidity almost instantly.
2. Dynamic Adjustments: The RBI can tighten or ease liquidity conditions as required.
3. Data-Driven Decision-Making: Policies are based on real-time economic indicators.

7. Exchange Rate Stability and Foreign Capital Flows

A well-managed monetary policy helps in maintaining a stable exchange rate, making India an attractive destination for foreign investment.

How Monetary Policy Regulates Exchange Rates

1. Controlling Excess Liquidity: Prevents the depreciation of the Indian rupee.
2. Managing Foreign Inflows: Adjusting interest rates impacts foreign capital movements.
3. Preventing Currency Speculation: Ensures market stability by regulating liquidity levels.

Disadvantages of Monetary Policy in Liquidity Management

While monetary policy is a crucial tool for managing liquidity, it is not without its limitations. Despite its effectiveness in controlling inflation, stabilizing financial markets, and promoting economic growth, monetary policy can sometimes fall short in addressing liquidity-related challenges due to various structural and external factors.

This section explores the major disadvantages of monetary policy in liquidity management, covering:

1. Time Lag in Policy Implementation and Impact
2. Limited Effectiveness in Structural Economic Issues
3. Difficulty in Addressing Supply-Side Inflation
4. Dependence on Banking Sector Efficiency
5. Risk of Liquidity Traps
6. Negative Impact on Borrowers and Businesses
7. Challenges in Managing Foreign Capital Flows and Exchange Rates

1. Time Lag in Policy Implementation and Impact:-

Delayed Effects on Liquidity and Economic Activity:

One of the biggest drawbacks of monetary policy is the time lag between policy decisions and their actual impact on liquidity and the economy. Unlike fiscal policy, which can have immediate effects through government spending and taxation, monetary policy works indirectly by influencing interest rates, credit availability, and investment behaviour.

· Short-Term Lag: Even when the RBI changes repo rates or CRR, it takes time for banks to adjust their lending and deposit rates.
· Long-Term Lag: Businesses and consumers do not immediately change their borrowing and spending habits in response to interest rate changes.

2. Limited Effectiveness in Structural Economic Issues:-

Monetary policy primarily influences liquidity through interest rates and money supply but is ineffective in addressing structural economic problems such as:

1. Unemployment due to lack of skills or industrial stagnation.
2. Income inequality and wealth concentration.
3. Poor infrastructure and supply chain inefficiencies.

3. Difficulty in Addressing Supply-Side Inflation:-

Monetary Policy is More Effective for Demand-Side Inflation:-

Monetary policy is most effective when inflation is caused by excess demand (too much money chasing too few goods). However, when inflation is caused by supply-side factors, monetary policy has limited impact.

1. Supply shocks (such as oil price hikes or food shortages) cannot be controlled by interest rate adjustments.
2. High borrowing costs due to tight monetary policy can worsen the situation by discouraging investment in production.

4. Dependence on Banking Sector Efficiency:-

Monetary Policy Works Through the Banking System:-

For monetary policy to be effective in liquidity management, banks must transmit policy changes efficiently to borrowers and depositors. However, if banks do not respond quickly or face internal challenges, monetary policy loses its effectiveness.

1. High Non-Performing Assets (NPAs) reduce banks’ willingness to lend, even if liquidity is high.
2. Weak banking infrastructure in rural areas prevents monetary policy from effectively reaching all sections of the economy.
3. Banks may not always pass on interest rate cuts to consumers, reducing the impact of monetary easing.

5. Risk of Liquidity Traps:-

When Monetary Policy Becomes Ineffective:

A liquidity trap occurs when interest rates are already very low, and further monetary easing fails to stimulate borrowing and spending. In such a situation:

1. People prefer to hold cash instead of investing or spending.
2. Businesses delay borrowing due to economic uncertainty.
3. Consumers reduce spending due to low confidence in the economy.

6. Negative Impact on Borrowers and Businesses:-

High Interest Rates Can Reduce Economic Growth:

1. When the RBI raises interest rates to control inflation, borrowing becomes expensive, reducing investment and consumer spending.
2. Small businesses and start-ups suffer the most, as they rely on affordable credit for expansion.

7. Challenges in Managing Foreign Capital Flows and Exchange Rates:-

External Factors Affect India’s Liquidity:

1. Foreign investors react to global interest rates, not just RBI policies.
2. A sudden outflow of foreign capital can cause liquidity shortages, weakening the rupee.
3. RBI interventions in currency markets can conflict with domestic monetary policies.

Conclusion

Summarizing the Role of Monetary Policy in Liquidity Management

Monetary policy is a key instrument in regulating liquidity, ensuring that the money supply, interest rates, and inflation levels remain within a controlled framework. In India, the Reserve Bank of India (RBI) plays a crucial role in balancing liquidity through various tools such as the repo rate, reverse repo rate, Cash Reserve Ratio (CRR), and Open Market Operations (OMO).

The primary objective of liquidity management is to ensure that the economy has sufficient liquidity to promote growth while preventing inflationary pressures and financial instability. Effective monetary policy contributes to stable prices, economic expansion, financial market stability, and investor confidence. However, it also has limitations such as time lags, inefficiencies in banking transmission, difficulties in controlling supply-side inflation, and risks of liquidity traps.

Thus, while monetary policy is an essential tool for liquidity management, it is not a standalone solution. It must be complemented by fiscal policies, structural reforms, and financial sector improvements to ensure long-term economic stability.

1.2 Introduction to Role of Monetary Policy

Economic performance is a fundamental indicator of a nation's overall progress and development. It reflects key macroeconomic factors such as GDP growth, inflation control, employment rates, financial stability, and the overall standard of living. A well-functioning economy ensures a balance between growth and stability, providing businesses and individuals with the necessary financial environment to thrive. However, achieving optimal economic performance is not a straightforward process, as economies are influenced by both internal and external factors, including fiscal policies, global trade, capital flows, and geopolitical events. Among these determinants, monetary policy plays a particularly crucial role in shaping a country’s economic trajectory. Through effective regulation of money supply, interest rates, and liquidity management, monetary policy acts as a powerful instrument for economic stabilization and growth.

In India, the Reserve Bank of India (RBI) is responsible for designing and implementing monetary policy with the objective of maintaining economic stability and fostering sustainable growth. The primary aim of monetary policy is to control inflation, regulate credit availability, and manage liquidity in a manner that aligns with the nation’s long-term economic goals. By adjusting interest rates, reserve requirements, and liquidity operations, the RBI influences borrowing, spending, and investment patterns within the economy. Effective liquidity management ensures that there is neither an excess nor a shortage of money supply in the financial system, thereby preventing both inflationary and recessionary conditions.

Liquidity management is a key function of monetary policy and refers to the regulation of money flow in the economy to ensure efficient financial operations. Liquidity, in simple terms, represents the availability of cash and liquid assets in the economy that businesses and individuals can readily access for transactions and investments. When liquidity is well-managed, businesses can access credit easily, consumers can make purchases without excessive costs, and the financial system operates smoothly. However, if liquidity is mismanaged, it can lead to economic instability. Excessive liquidity in the system can drive inflation, causing the value of money to erode and leading to higher costs for goods and services. On the other hand, inadequate liquidity can result in economic slowdowns, reduced investments, declining consumption, and financial distress. Hence, striking the right balance in liquidity management is essential to maintaining a stable and thriving economy.

To regulate liquidity effectively, the RBI employs various monetary policy instruments, categorized into direct and indirect tools. Direct instruments include the Cash Reserve Ratio (CRR) and the Statutory Liquidity Ratio (SLR), which mandate banks to maintain a portion of their deposits as reserves with the RBI. These tools ensure that banks operate within controlled liquidity levels, preventing excessive money supply from entering the economy. Indirect instruments include the repo rate, reverse repo rate, open market operations (OMO), and the Marginal Standing Facility (MSF). The repo rate is the rate at which the RBI lends to commercial banks, influencing borrowing costs and liquidity levels. Reverse repo rate, conversely, helps absorb excess liquidity by allowing banks to deposit funds with the RBI. Open market operations (OMO) involve the purchase or sale of government securities to regulate money supply, while the Marginal Standing Facility (MSF) allows banks to borrow emergency funds from the RBI in times of liquidity shortages. These tools collectively help the central bank in ensuring a balanced and efficient liquidity flow within the economy.

India’s unique economic structure presents several challenges and considerations in liquidity management. Unlike developed economies, India has a diverse economic landscape comprising both formal and informal sectors, each of which responds differently to monetary policy measures. A significant portion of India’s workforce operates in the informal sector, where financial transactions often take place outside traditional banking channels. This creates challenges in liquidity transmission, as the informal economy may not respond effectively to changes in interest rates or credit availability. Additionally, India’s financial system is highly influenced by global economic trends, including foreign capital inflows, exchange rate fluctuations, crude oil prices, and international trade policies. Any disruption in these external factors can significantly impact liquidity conditions, requiring the RBI to adapt its policy approach dynamically.

The role of monetary policy in optimizing economic performance is evident in its impact on key macroeconomic indicators such as inflation, GDP growth, employment, and financial market stability. A well-executed monetary policy ensures that inflation remains under control, maintaining the purchasing power of consumers and preventing the erosion of savings. Inflation control is especially critical for developing economies like India, where rising prices can severely impact lower-income groups. Furthermore, by regulating liquidity, monetary policy promotes economic expansion by encouraging investments in sectors like infrastructure, manufacturing, agriculture, and small and medium enterprises (SMEs). When liquidity is abundant and interest rates are low, businesses find it easier to borrow funds for expansion, leading to higher employment and overall economic growth. Conversely, when inflationary pressures arise, contractionary monetary policy measures, such as increasing interest rates and tightening liquidity, help stabilize the economy and prevent overheating.

Despite its crucial role, implementing monetary policy for effective liquidity management comes with several challenges. One of the most persistent issues is inflation, which is often influenced by external shocks such as global oil price fluctuations, supply chain disruptions, and fiscal deficits. India, being a large importer of crude oil, is particularly vulnerable to price hikes in the global energy market, which can drive inflation and disrupt liquidity conditions. Additionally, high fiscal deficits can limit the effectiveness of monetary policy, as excessive government borrowing can increase liquidity levels beyond the control of the RBI. External factors such as capital outflows, trade imbalances, and geopolitical tensions also pose risks to liquidity management, making it difficult for policymakers to maintain stability. Furthermore, structural weaknesses in the banking sector, including high levels of non-performing assets (NPAs), financial frauds, and inefficient credit distribution, further complicate liquidity management efforts.

To improve the effectiveness of monetary policy, financial inclusion plays a vital role in ensuring that liquidity reaches all segments of society. When a significant portion of the population has access to banking services, credit facilities, and digital payment systems, liquidity distribution becomes more efficient, leading to higher economic participation and growth. Government initiatives such as Pradhan Mantri Jan Dhan Yojana (PMJDY) have played a significant role in bringing millions of unbanked individuals into the formal financial system. Additionally, advancements in digital banking, mobile payments, and financial technology (FinTech) have enhanced liquidity flow by making financial transactions faster and more accessible. These technological innovations strengthen the transmission of monetary policy, ensuring that changes in liquidity conditions are quickly reflected across the economy.

Optimizing economic performance in India requires a coordinated approach between monetary policy and fiscal policy. While monetary policy focuses on liquidity management, fiscal policy—managed by the government—deals with taxation, public spending, and budget deficits. A harmonized policy framework between these two instruments is essential to ensure sustainable economic growth, inflation control, and financial stability. Additionally, structural reforms in the banking sector, improved regulatory oversight, and greater transparency in financial transactions will enhance the overall effectiveness of monetary policy in India.

In conclusion, monetary policy remains a cornerstone of India’s economic stability and growth strategy. Through effective liquidity management, the RBI ensures a stable money supply, controls inflation, and promotes investment. However, India’s economic landscape presents unique challenges that require a flexible and dynamic policy approach. By strengthening financial inclusion, enhancing banking efficiency, and maintaining policy coordination between monetary and fiscal authorities, India can achieve sustainable economic growth and long-term financial resilience. The future of India’s economic performance will depend on the ability of its monetary policy to adapt to changing domestic and global challenges, ensuring a prosperous and stable economy for years to come.

1.3 Objectives of the Study

1. To analyze the trends in monetary policy fluctuations and their impact on liquidity in India.
2. To investigate the relationship between monetary policy and liquidity in India.
3. To examine the effects of monetary policy fluctuations on liquidity management in India.
4. To evaluate the potential future momentum of liquidity management influenced by monetary policy fluctuations.

1.4 Hypotheses of the Study

1. Null Hypothesis (H₀): There is no significant relationship between monetary policy and liquidity in India.
2. Null Hypothesis (H₀): Monetary policy fluctuations have no significant effect on liquidity management in India

1.5 Scope of the Study

This study focuses on analyzing the influence of monetary policy on liquidity dynamics within India's financial system. A monetary policy index will be developed to serve as a proxy for monetary policy, while M3 (broad money) will be utilized as a proxy for liquidity management. The research relies on secondary data collected from the fiscal year 2004-05 to 2023-24, covering nearly two decades of economic and financial developments in India. It offer valuable insights for policymakers, financial institutions, and researchers, contributing to the development of effective strategies for managing liquidity in the context of India's economic framework.

REVIEW OF LITERATURE

Endogenous Money Supply, Global Liquidity, and Financial Transactions: Panel Evidence from OECD Countries (Śliwiński, 2023)

Paweł Śliwiński (2023) explores the endogenous nature of money supply, focusing on its relationship with GDP-based and non-GDP-based transactions, as well as global liquidity. The findings reveal that both real and financial economic activities, along with global liquidity, positively influence domestic credit and money supply. Furthermore, the study identifies a positive spill over effect of US expansionary monetary policy on domestic money supply in other economies. Śliwiński concludes that prudential regulations to control leverage and limit risk-taking during economic bubbles are necessary to maintain financial stability, as the financial economy significantly drives money supply alongside the real economy.

Money Supply, Budget Deficit, and Inflation Dynamics in Ghana: An Empirical Investigation (Duodu et al., 2022)

Emmanuel Duodu, Samuel Tawiah Baidoo, Hadrat Yusif, and Prince Boakye Frimpong (2022) analyse the long-term dynamics between money supply, budget deficit, and inflation in Ghana using quarterly data from 1999 to 2019. The study reveals that budget deficits significantly increase inflation, whereas money supply negatively affects it. Inflation, in turn, has a positive impact on the budget deficit but a negative effect on the money supply. Impulse response analysis confirms that inflation reacts positively to budget deficit shocks but negatively to money supply shocks. The study supports the fiscal theory of price levels and concludes that reducing government expenditure and implementing restrictive bureaucratic measures can help stabilize inflation in Ghana.

The Impact of Foreign Direct Investment, Capital Formation, Inflation, Money Supply, and Trade Openness on Economic Growth of Asian Countries (Yang & Shafiq, 2020) Xiuyun Yang and Muhammad Nouman Shafiq (2020) investigate the role of foreign direct investment (FDI), capital formation, inflation, money supply, and trade openness in driving economic growth across 20 emerging Asian countries from 2007 to 2018. Using data from the World Development Indicators (WDI) and applying a fixed-effects model with robust standard errors, the study finds that FDI, capital formation, money supply, and trade openness positively influence economic growth, whereas inflation negatively affects it. The authors conclude that these findings can guide future researchers and policymakers in developing strategies to enhance economic growth in Asian economies, particularly by focusing on fostering FDI and trade openness while mitigating inflationary pressures.

Money Supply and Equity Price Movements during the Liberalized Period in India (Sahu & Pandey, 2020)

Tarak Nath Sahu and Krishna Dayal Pandey (2020) investigate the impact of changes in the money supply, an essential monetary policy shock, on stock prices during the liberalized period in India. Their study highlights the significant role of monetary policy in influencing stock price movements and contributes to the existing literature by providing a deeper understanding of these dynamics in the context of a liberalized economy. The findings emphasize the importance of recognizing monetary policy changes as a key factor for understanding and predicting equity price movements in the Indian stock market.

Money Supply, Inflation and Economic Growth: Co-Integration and Causality Analysis (Ayad, 2020)

Hicham Ayad (2020) examines the relationship between money supply, inflation, and economic growth in Algeria over the period 1970–2018. The study finds a long-term relationship among the variables, despite multiple structural breaks, but reports no significant effects of money supply and inflation on economic growth in either the short or long term. Hidden causalities among cumulative components are identified, supporting the Monetarist view of inflation but not linking money supply to economic growth. The findings highlight the limited influence of money supply and inflation on economic growth while affirming the Monetarist perspective on inflation dynamics.

Money supply and inflation impact on economic growth (Van, 2019)

Dinh Doan Van (2019) explores the relationship between money supply, inflation, and economic growth by applying economic theories and econometric models to data from Vietnam and China for the period 2012–2016. The study reveals that a continuous increase in the money supply causes inflation in the long term but does not significantly influence inflation in the short term. Correlations between money supply growth and inflation in Vietnam and China are exceptionally high, at 99.1%. The findings indicate that money supply directly affects economic growth. The study concludes that governments should adopt effective monetary policies to control inflation, promote economic growth, and ensure macroeconomic stability.

Effect of Money Supply on Economic Growth: A Comparative Study of Nigeria and Ghana (Omodero, 2019)

Cordelia Onyinyechi Omodero (2019) examines the influence of money supply mechanisms on economic growth in Nigeria and Ghana, focusing on their joint and individual effects. The findings indicate that broad money supply (M2) has an insignificant negative impact on real GDP (RGDP) in Nigeria, while in Ghana, the effect is significant and positive. On the other hand, M3 shows an insignificant positive impact on RGDP in Nigeria but a significant negative influence in Ghana. Credit to private sectors (CPS) has an insignificant positive effect on RGDP in both countries. The study concludes that monetary authorities in both Nigeria and Ghana should develop policy strategies emphasizing M2 and CPS to foster economic growth, increase output, and create employment opportunities.

An Analysis of the Nature of Money Supply in India and Its Expected Causes (Verma, 2023) Shreya Verma (2023) investigates the fluctuations and factors influencing the money supply in India, highlighting significant policy interventions such as the PM Jan-Dhan Yojana (2014), demonetization, the Kisan Samman Nidhi Yojana, and decisions taken during the COVID-19 pandemic. The study compiles quantitative data on reserve money and broad money from various authentic sources, including research articles and official publications, and employs trend analysis and descriptive statistics for evaluation. The findings emphasize the role of major policy decisions, including unplanned expenditures and significant withdrawals from the Reserve Bank of India (RBI), in shaping the money supply trends. The study concludes that understanding the dynamics of money supply is crucial for policymakers, researchers, and other stakeholders to ensure macroeconomic stability and effective management of the economy.

Inflation and Monetary Policy (P. Nandalal Weerasinghe, 2009)

This study, authored by P. Nandalal Weerasinghe in 2009, focuses on the interplay between inflation and monetary policy. It highlights the critical role of monetary policy in maintaining price stability and promoting sustainable economic growth. The findings emphasize that effective monetary policy frameworks are essential to manage inflation and ensure economic stability. The conclusion underlines the importance of central banks adopting robust strategies to counter inflationary pressures while fostering economic development.

Inflation Targeting and its Impact on Monetary Policy: A South African Insight (Emaad Muhanna, 2017)

Emaad Muhanna’s 2017 paper examines inflation targeting as a monetary policy framework, with a specific focus on its impact in South Africa. The study underscores the importance of macroeconomic policies in promoting economic growth, controlling inflation, and ensuring financial stability. It evaluates the effectiveness of inflation targeting, particularly in developing economies like South Africa, where price volatility has posed significant challenges. The findings suggest that while inflation targeting offers a structured approach to monetary policy, developing countries face unique obstacles in its implementation. The study concludes that adopting inflation targeting can enhance monetary policy effectiveness, but strategic adjustments are necessary to address country-specific challenges.

The 1997-2011 Global Financial Crisis: Causes, Policy Recommendations, and Lessons (Aso Ahmed Abdullah, 2017)

Authored by Aso Ahmed Abdullah in 2017, this report analyses the global financial crisis that spanned from 1997 to 2011, originating in Southeast Asia and spreading to other regions, including Europe and the United States. The study investigates the underlying causes of the crisis, such as excessive financial sector expansion and inadequate regulatory controls, which led to systemic risks. It also reviews policy responses from institutions like the International Monetary Fund (IMF) and highlights the lessons learned. The findings reveal the need for stricter financial regulations and proactive policies to mitigate risks during economic booms. The study concludes with recommendations for policymakers to enhance resilience against future financial crises.

Relationship Banking and Monetary Policy Transmission: Evidence from India (Abhishek Bhardwaj, Krishnamurthy Subramanian, and Prasanna L. Tantri, 2015)

This study, published in 2015 by Abhishek Bhardwaj, Krishnamurthy Subramanian, and Prasanna L. Tantri, examines the influence of relationship banking on the transmission of monetary policy in India. Using data from bank-dependent firms, the study finds that firms with exclusive banking relationships are less affected by monetary policy shocks compared to those engaging in transactional banking. This effect remains consistent during both monetary tightening and loosening. The findings suggest that relationship banking reduces information asymmetry, thereby mitigating the impact of the "firm balance sheet channel" in monetary policy transmission. The study concludes that relationship banking can buffer firms against the adverse effects of monetary policy changes.

Unconventional Monetary Policy and Bank Performance in Nigeria (Menyelim Chima, Abiola Ayopo Babajide, A. E. Omankhanlen, and Babafemi Adejumo, 2020)

Menyelim Chima and co-authors in their 2020 study investigate the impact of unconventional monetary policy on the performance of deposit money banks in Nigeria from 2007 to 2017. Utilizing random effect regression panel data analysis, the study reveals that unorthodox monetary expansion, measured through the apex bank's assets-to-GDP ratio and deposit insurance, negatively affects bank performance. The findings emphasize a negative relationship between unconventional monetary policy and the financial efficiency of banks. The study concludes by recommending that the Central Bank of Nigeria implement stricter monetary regulations to better assess the response of credit finance banks to unconventional policy measures.

Relationship between Interest Rate and Stock Price: Empirical Evidence from Developed and Developing Countries (Md. Mahmudul Alam and Md. Gazi Salah Uddin, 2009)

This 2009 study by Md. Mahmudul Alam and Md. Gazi Salah Uddin explores the relationship between interest rates and stock prices using monthly data from 1988 to 2003 for 15 developed and developing countries, including Australia, Canada, Germany, Japan, and Bangladesh. The analysis finds a significant negative relationship between interest rates and stock prices across all countries, with changes in interest rates also negatively influencing stock price movements in six countries. The study concludes that controlling interest rates could enhance stock market performance by attracting investors and encouraging company investments, thereby contributing to economic growth.

The Effects of Regulatory Capital Requirements and Ownership Structure on Bank Lending in Emerging Asian Markets (Yasmeen Akhtar, Ghulam Mujtaba Kayani, and Tahir Yousaf, 2019) Published in the Journal of Risk and Financial Management in 2019, this study by Yasmeen Akhtar, Ghulam Mujtaba Kayani, and Tahir Yousaf explores how regulatory capital requirements and ownership structure influence bank lending in emerging Asian markets. The findings suggest that banks with excess capital are less constrained by capital requirements and can expand their credit portfolios even during monetary tightening. Well-capitalized banks demonstrate resilience, raising uninsured financing to sustain lending, whereas less-capitalized banks reduce their lending. Additionally, banks with high ownership concentration and excess capital ratios show increased lending activity. However, banks with managerial ownership tend to reduce lending, supporting the agency theory of corporate governance. The study concludes that regulatory frameworks and ownership structures significantly impact lending behaviours in emerging markets.

Monitory Public Policy Network Institutions and Their Inclusion in Policy Making: From Confrontation to Cooperation (Author Unknown, 2017)

This 2017 article discusses the role of monitory public policy network institutions in the Web 2.0 space and their evolving relationship with governmental entities. The analysis reveals a current state of confrontation between these institutions and governments, with potential for escalating conflict. To address this issue, the author models political frameworks for incorporating these institutions into decision-making processes. The proposed designs aim to mitigate conflict and enhance public administration quality by fostering cooperation rather than confrontation. The study concludes that integrating network institutions into policymaking could transform their role from adversaries to collaborators in governance.

The Impacts of Interest Rate on Stock Market: Empirical Evidence from Dhaka Stock Exchange (Md. Gazi Salah Uddin and Md. Mahmudul Alam, 2010)

In this 2010 study, Md. Gazi Salah Uddin and Md. Mahmudul Alam examine the relationship between interest rates and stock market performance on the Dhaka Stock Exchange (DSE) using data from 1994 to 2005. The findings reveal that the DSE Index does not follow the random walk model, indicating weak-form market inefficiency. Using ordinary least squares regression, the study establishes a significant negative relationship between interest rates and stock prices, as well as between interest rate growth and stock price growth. The authors conclude that controlling interest rates in Bangladesh could boost the stock market by attracting more investors and fostering corporate investment, thereby enhancing economic growth.

Liquidity Management and Asset Sales by Bond Funds in the Face of Investor Redemptions in March 2020 (Andreas Schrimpf, Ilhyock Shim, Hyun Song Shin, 2021)

This study examines the interplay between liquidity management and asset sales by mutual funds during the market stress of March 2020. The research reveals that funds holding illiquid assets responded to redemptions by building cash buffers, leading to asset sales exceeding investor redemptions. Furthermore, funds with larger initial cash buffers experienced less pronounced increases in end-of-period cash holdings, demonstrating reduced susceptibility to selling during peak stress. The study concludes that adequate initial liquidity buffers can mitigate stress-driven asset sales in mutual funds.

Effect of Liquidity Management on Banks’ Profitability (John Ayodele Ajayi, Qudus Lawal, 2021) This research investigates the relationship between liquidity management and bank profitability, focusing on data from five Nigerian Deposit Money Banks over a ten-year period (2009–2018). The study finds mixed relationships: a significant negative correlation between loan-to-deposit ratio and return on assets (ROA), a significant positive correlation between loan-to-assets ratio and ROA, and an insignificant positive correlation between liquid ratio and ROA. The authors conclude that effective liquidity management positively influences bank profitability and recommend adherence to strict credit administration rules.

A Dynamic Theory of Mutual Fund Runs and Liquidity Management (Yao Zeng, 2017)

This study presents a model of open-end mutual funds investing in illiquid assets, exploring how endogenous cash management can lead to shareholder runs even when flexible NAVs are used. The research highlights that funds rebuild cash buffers after outflows to prevent future forced sales of illiquid assets, which in turn causes predictable declines in NAV and creates a first-mover advantage for shareholders. The time-inconsistency problem exacerbates the issue, as funds lack a credible commitment mechanism to avoid rebuilding cash buffers. The study concludes that without pre-commitment mechanisms, mutual funds face heightened risks of shareholder runs due to their liquidity management practices.

Liquidity Management and Performance of Deposit Money Banks in Nigeria (Eze Emmanuel, a Eichinger Stephen, Agu Stephen, 2020)

This study investigates the relationship between liquidity management and performance in six Nigerian deposit money banks with international affiliations, focusing on data from 2013 to 2019. Using indicators such as capital adequacy, liquidity ratio, and current ratio, alongside bank size as a control variable, the analysis employed descriptive statistics and regression methods via E-View 10.0. The findings reveal a strong positive relationship between capital adequacy and return on equity, while liquidity and current ratios showed a statistically insignificant negative relationship with return on equity. Bank size, however, demonstrated a robust positive relationship with return on equity. The study concludes that adequate capitalization ensures system stability and recommends adherence to central bank reserve requirements to absorb financial shocks and maintain profitability.

Liquidity Management under Fixed Exchange Rate with Open Capital Account (Mariam El Hamiani Khatat, Romain Veyrune, 2019)

This paper introduces a theoretical framework for liquidity management under a fixed exchange rate regime, based on David Hume’s price-specie flow mechanism. It emphasizes that financial stability can be threatened by short-term money market rate deviations from uncovered interest rate parity (UIP) due to market frictions. Operational solutions are proposed to stabilize money market rates at levels implied by UIP. Challenges under fixed exchange rates include large liquidity shocks caused by foreign reserve fluctuations and difficulties in liquidity forecasting. Empirical tests of the framework, using “offset” coefficients from Denmark and Hong Kong SAR, confirm its applicability. The study concludes that managing liquidity under these conditions requires specific operational strategies to mitigate risks and promote financial stability.

Banks, Liquidity Management, and Monetary Policy (Javier Bianchi, Saki Bigio, 2022)

This research develops a model to explore the interplay between banks’ liquidity management, interbank markets, and monetary policy. The study highlights how monetary policy influences banks by altering the trade-off between lending profits and liquidity risks. Applications of the model include analysing the relationship between monetary policy implementation and its pass-through effect on lending rates, as well as quantifying factors behind the decline in bank lending during the 2008 financial crisis. The findings underscore the critical role of liquidity frictions and the interbank market’s functionality in shaping monetary policy’s effectiveness. The study concludes that understanding these dynamics is vital for robust policy design.

Liquidity Management in Islamic Banking: Issues and Challenges (Siti Kholifatul Rizkiah, 2018) This study examines liquidity management in Islamic banking, focusing on the challenges associated with the mismatch of maturities between assets and liabilities, which leads to liquidity issues. Through a literature review, the research identifies key issues in Islamic liquidity instruments, such as sharia compliance concerns, the inactivity of secondary markets, challenges with short-term sukuk issuance, and difficulties in cross-border transactions. To address these challenges, the study recommends improved liquidity management strategies and the development of a robust liquidity infrastructure. These measures are deemed essential for enhancing liquidity management practices in the Islamic banking industry.

Liquidity Management and Banks’ Performance in Nigeria (Idowu Akinyele Akinwumi, Essien Joseph Micheal, Adegboyega R. Raymond, 2017)

This research investigates the impact of liquidity management on the performance of four deposit money banks in Nigeria from 2007 to 2016. Using the Pearson correlation coefficient technique, the study reveals a statistically significant relationship between banks’ liquidity, return on assets (ROA), and return on equity (ROE). However, the relationship is less significant when ROA is used as a proxy for profitability. The findings highlight the need for banks to re-evaluate and redesign their liquidity management strategies to optimize returns to shareholders and effectively utilize assets. The study concludes that efficient management and control of factors affecting liquidity can significantly improve the financial performance of commercial banks in Nigeria.

2.2 Research Gap

Despite extensive research on monetary policy and its impact on various aspects of the economy, there remains a notable gap in understanding its specific role in liquidity management within the context of India. While existing literature has explored the effects of monetary policy on broader economic indicators, such as inflation and GDP growth, there is a lack of comprehensive studies focusing specifically on the relationship between monetary policy measures and liquidity dynamics in the Indian financial system. Therefore, this research aims to bridge this gap by investigating the intricate mechanisms through which monetary policy influences liquidity conditions, thereby contributing to a deeper understanding of the factors shaping India's economic performance and financial stability.

RESEARCH METHODOLOGY

The methodology for this study adopts a quantitative research approach to examine the influence of monetary policy on liquidity management in India. The following components detail the research process:

3.1 Research Design

The study employs a quantitative research approach, utilizing statistical methods to analyze the relationship between monetary policy and liquidity management through time series data.

3.2 Sample Period

The research focuses on the period from 2004-05 to 2023-24, covering nearly two decades of monetary policy trends and liquidity dynamics in India.

3.3 Data Type

The study is based on secondary data in the form of time series data, providing a detailed analysis of historical trends and relationships.

3.4 Data Sources

The data is sourced from reliable and reputable platforms, including the Reserve Bank of India (RBI) and Trading Economics .

3.5 Variables

Independent Variable: Monetary Policy Index (MPI)

The Monetary Policy Index (MPI) is constructed as a proxy for monetary policy. The MPI is calculated using the following formula:

MPI= [Bank Rate + Repo Rate + Reverse Repo Rate + CRR + SLR / 5] ×100

This formula aggregates key monetary policy rates announced in the bi-monthly monetary policy reviews by the RBI to create a comprehensive index reflecting the stance of monetary policy.

Dependent Variable: M3 (Broad Money)

The study uses M3 (Broad Money) as a proxy for liquidity management, capturing the total money supply in the economy.

3.6 Statistical Tools

The study adopted the following statistical tools

Unit Root Test

Unit root tests are statistical methods used to determine whether a time series is stationary or non-stationary. Stationarity is a critical property in time series analysis, as many econometric models, such as regression models and ARIMA models, assume that the underlying series is stationary.

A stationary time series has statistical properties—mean, variance, and autocorrelation—that do not change over time. A non-stationary time series, on the other hand, exhibits trends, seasonality, or time-dependent variance, making it difficult to model and forecast accurately.

Unit root tests help in identifying non-stationarity by examining whether a time series has a unit root—a characteristic that indicates persistence in shocks and long-term dependency.

There are several unit root tests, with the most widely used ones being:

A. Augmented Dickey-Fuller (ADF) Test

The ADF test is an extension of the Dickey-Fuller (DF) test, which tests for a unit root by checking whether ρ=1\rho = 1ρ=1. The ADF test allows for more complex structures in the time series, including lagged differences to account for serial correlation.

B. Phillips-Perron (PP) Test

The PP test is similar to the ADF test but differs in how it handles serial correlation and heteroskedasticity. Instead of adding lagged differences, it uses non-parametric statistical methods to correct for autocorrelation.

C. Kwiatkowski-Phillips-Schmidt-Shin (KPSS) Test

Unlike the ADF and PP tests, the KPSS test takes a different approach by testing stationarity as the null hypothesis .

Bivariate Correlation

Bivariate correlation is a statistical technique used to measure and analyze the strength and direction of the relationship between two continuous variables. The correlation coefficient quantifies the degree to which changes in one variable are associated with changes in another.

For example:

· Positive correlation: As study time increases, exam scores increase.
· Negative correlation: As the price of a product increases, demand decreases.
· No correlation: There is no consistent pattern between the two variables.

Bivariate correlation is widely used in research, economics, finance, psychology, and social sciences to identify relationships between variables and make data-driven decisions.

Ordinary Least Squares (OLS)

Ordinary Least Squares (OLS) regression is a fundamental technique used to determine the linear relationship between an independent variable and a dependent variable. In OLS, coefficients are estimated to minimize the sum of the squared differences between observed and predicted values, thereby providing a measure of the independent variable's impact on the dependent variable. OLS assumptions, such as linearity, independence, and homoscedasticity, are critical to producing unbiased and consistent estimates, making OLS a common choice for simple linear regressions. OLS regression is widely used in econometrics, social sciences, finance, and data science to model relationships and make predictions.

Vector Auto regression (VAR)

Vector Auto regression (VAR) is a multivariate time series model used to analyze and forecast the dynamic relationships between multiple interdependent variables. Unlike univariate models like ARIMA, which focus on a single time series, VAR models multiple time series simultaneously, treating each variable as a function of its own past values (lags) and the past values of other variables in the system.VAR is widely used in economics, finance, and social sciences to model interdependencies, identify causal relationships, and generate forecasts.

DATA ANALYSIS AN INTERPRETATION

4.1 UNIT ROOT TEST:

UNIT ROOT TEST OF MONETARY POLICY:-

The following is the hypothesis:-

Null Hypothesis: Monetary policy is not stationarized

Alternative Hypothesis: Monetary policy data is stationarized

Table: 4.1.1

Unit root test of monetary policy

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for monetary policy from 2004 to 2024 suggest that the null hypothesis, which states that the first-differenced monetary policy variable (D (DMONETARY_POLICY)) has a unit root, can be rejected at the 5% significance level. This conclusion is based on the p-value of 0.0002, which is significantly lower than the conventional threshold of 0.05, and the test statistic of -5.940739, which is more negative than the critical value of -3.040391 at the 5% level. Since the null hypothesis is rejected, it indicates that the monetary policy variable becomes stationary after first differencing. This implies that the original monetary policy data was non-stationary, meaning it exhibited time-dependent variations in its statistical properties. The non-stationarity of the raw data suggests that shocks to monetary policy may have persistent effects over time, necessitating transformation such as differencing to ensure stability for accurate time series modelling and econometric analysis.

UNIT ROOT TEST OF REPO RATE:-

The following is the hypothesis

Null Hypothesis: Repo rate data is not stationarized

Alternative Hypothesis: Repo rate data is stationarized

Table: 4.1.2

Unit root test of repo rate

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for the repo rate (DREPO) from 2004 to 2024 indicate whether the series is stationary or contains a unit root. The null hypothesis (H₀) states that the repo rate series has a unit root, meaning it is non-stationary. The ADF test statistic is -5.725687, which is more negative than the 5% critical value of -3.040391, suggesting strong evidence against the null hypothesis. Additionally, the p-value of 0.0002 is significantly lower than the conventional 5% significance level, confirming the rejection of the null hypothesis. This implies that after differencing, the repo rate series has become stationary, indicating that the original repo rate data was non-stationary and required transformation to achieve stationarity for meaningful time series analysis

UNIT ROOT TEST OF CRR:-

The following is the hypothesis

Null Hypothesis: CRR data is not stationarized

Alternative Hypothesis: CRR data is stationarized

Table: 4.1.3

Unit root test of CRR

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for the Cash Reserve Ratio (CRR) from 2004 to 2024 indicate that the null hypothesis, which states that the first-differenced CRR (D (DCRR)) has a unit root, can be strongly rejected at the 5% significance level. This is evident from the p-value of 0.0000, which is significantly lower than the 0.05 threshold, and the test statistic of -6.719883, which is far more negative than the critical value of -3.029970 at the 5% level. The rejection of the null hypothesis confirms that the first-differenced CRR data is stationary, implying that the original CRR data was non-stationary and exhibited changing statistical properties over time. This suggests that the CRR data needed to be differenced to achieve stationarity, reinforcing that its original form was not suitable for standard time series modelling due to the presence of a unit root.

UNIT ROOT TEST OF BANK RATE:-

The following is the hypothesis: -

Null Hypothesis: Crude oil data is not stationarized

Alternative hypothesis: Crude oil data is stationarized

Table: 4.1.4

Unit root test of Bank Rate

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for the period 2004–2024 indicate that the null hypothesis, which states that D (DBANK_RATE) has a unit root, is rejected at the 5% significance level. The reported t-statistic of -5.110114 is significantly lower than the critical value of -3.052169 at the 5% level, and the corresponding p-value of 0.0009 is well below the conventional threshold of 0.05. This low p-value provides strong statistical evidence against the null hypothesis, suggesting that the first difference of the bank rate does not contain a unit root, implying stationarity in the differenced series. However, since the test is conducted on the first difference rather than the original bank rate series, it confirms that the raw bank rate data is not stationary, as differencing was required to achieve stationarity. This finding suggests that the bank rate follows a non-stationary process in its level form, making it unsuitable for standard regression analysis without transformation.

UNIT ROOT TEST OF MONEY SUPPLY:-

The following is the hypothesis

Null Hypothesis: Crude oil data is not stationarized

Alternative Hypothesis: Crude oil data is stationarized

Table: 4.1.5

Unit root test of Money Supply

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The results of the Augmented Dickey-Fuller (ADF) test for the period 2004–2024 examine the stationarity of money supply data in its differenced form, specifically testing whether D (DMONEY_SUPPLY) has a unit root. The null hypothesis of the test assumes that the first difference of money supply remains non-stationary, meaning it still exhibits a unit root. However, the reported t-statistic of -4.507394 is lower than the critical value of -3.081002 at the 5% significance level, and the corresponding p-value of 0.0036 is significantly below the conventional threshold of 0.05. This low p-value strongly suggests that the null hypothesis should be rejected, indicating that the first difference of money supply is stationary. Nonetheless, it is crucial to recognize that this test was conducted on the differenced data rather than the original money supply series, meaning the initial money supply data is not stationary in its level form. This non-stationarity in the raw data implies that money supply follows a stochastic trend over time, and its statistical properties, such as mean and variance, are not constant. As a result, differencing is required to achieve stationarity, making it more suitable for econometric modelling and reliable forecasting.

UNIT ROOT TEST OF REVERSE REPO:-

The following is the hypothesis

Null Hypothesis: Reverse Repo data is not stationarized.

Alternative Hypothesis: Reverse Repo data is stationarized.

Table: 4.1.6

Unit root test of the reverse repo rate

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for the period 2004–2024 assess the stationarity of the reverse repo rate in its differenced form, specifically testing whether D (DREVERSE_REPO) has a unit root. The null hypothesis of the test assumes that the first difference of the reverse repo rate remains non-stationary, meaning it still exhibits a unit root. The reported t-statistic of -3.851141 is lower than the critical value of -3.065585 at the 5% significance level, and the corresponding p-value of 0.0114 is below the conventional threshold of 0.05. Since the p-value is relatively low, the null hypothesis is rejected at the 5% significance level, providing statistical evidence that the first-differenced reverse repo rate is stationary. However, it is essential to note that this test was performed on the differenced series rather than the original reverse repo rate. The rejection of the null hypothesis in the differenced data implies that stationarity is only achieved after differencing, meaning the original reverse repo rate data is not stationarized. This non-stationarity in the level form indicates that the reverse repo rate follows a time-dependent stochastic trend, making it unsuitable for direct econometric analysis or regression modelling without proper transformation, such as differencing, to ensure stationarity.

UNIT ROOT TEST OF SLR:-

The following is the hypothesis

Null Hypothesis: statutory liquid ratio is not stationarized.

Alternative Hypothesis: statutory liquid ratio is stationarized

Table: 4.1.7

Unit root test for statutory liquid ratio

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Augmented Dickey-Fuller (ADF) test results for the period 2004–2024 assess the stationarity of the statutory liquidity ratio (SLR) in its differenced form, specifically testing whether D (DSLR) has a unit root. The null hypothesis of the test assumes that the first difference of the SLR remains non-stationary, meaning it still contains a unit root. The reported t-statistic of -4.713669 is lower than the critical value of -3.040391 at the 5% significance level, and the corresponding p-value of 0.0018 is well below the conventional 0.05 threshold. This low p-value provides strong statistical evidence to reject the null hypothesis, indicating that the first difference of SLR is stationary. However, it is important to note that the test was conducted on the differenced data rather than the original SLR series. The rejection of the null hypothesis at the first difference level implies that the original SLR data is not stationarized, meaning it follows a non-stationary process in its level form. This non-stationarity suggests that the SLR exhibits a time-dependent trend, making it unsuitable for direct econometric modeling without appropriate transformations such as differencing to achieve stationarity.

4.2 TREND ANALYSIS

BANK RATE:-

The following is the hypothesis

Null Hypothesis: Bank Rate is not stationarized.

Alternative Hypothesis: Bank Rate is stationarized

Table: 4.2.1

Trend Analysis for Bank Rate

Illustrations are not included in the reading sample

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The trend analysis of Money Supply and Bank Rate from 2004 to 2024 reveals significant variations in both variables, reflecting the impact of economic policies and market conditions. From 2004 to 2008, money supply exhibited a strong upward trend, peaking at 25.31% in 2008, while the bank rate remained constant at 9.5%, indicating a stable monetary policy stance despite liquidity expansion. Post-2008, money supply fluctuated, declining to 15.24% in 2010, followed by moderate growth until 2012 (12.92%), while the bank rate gradually declined from 9.035% in 2012 to 8.35% in 2015, indicating a loosening monetary policy to support economic activity. A significant drop in the bank rate occurred in 2016 (6.85%), aligning with a decline in money supply (10.48%), suggesting cautious liquidity management. The trend continued, with money supply hitting its lowest in 2017 (7.76%), followed by a gradual increase, while the bank rate remained relatively low, reaching 5.84% in 2019 before further reducing to 4.38% in 2020, reflecting an accommodative monetary stance during economic uncertainty. Post-pandemic, money supply rebounded slightly, reaching 12.58% in 2020, while the bank rate remained low, followed by fluctuations in both variables. By 2023, the bank rate rose to 6.75%, aligning with increased money supply (9.85%), indicating tightening measures to control inflation. The data suggests a general inverse relationship between money supply growth and bank rate movements, with monetary policy responding dynamically to economic conditions to balance liquidity and inflationary pressures.

REPO:-

The following is the hypothesis

Null Hypothesis: Repo is not stationarized.

Alternative Hypothesis: Repo is stationarized

Table: 4.2.2

Trend Analysis for Repo

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table presents the year-on-year growth rates of money supply and the repo rate from 2004 to 2024, highlighting their trends and interrelationships over the period. Observing the money supply growth rate, it demonstrates significant fluctuations, starting at 16.86% in 2004, reaching a peak of 25.31% in 2008, and subsequently declining with intermittent rises and falls, ultimately settling at 10.76% in 2024. The repo rate also exhibits variation, remaining constant at 6.25% from 2004 to 2005, rising sharply to 7.97% by 2008, and then declining to 5.05% in 2009 due to economic adjustments, followed by moderate fluctuations before falling to its lowest point of 4.33% in 2020, likely influenced by monetary easing during the COVID-19 pandemic, before recovering to 6.25% in 2024. A comparative analysis of both variables indicates that periods of higher repo rates, such as 2006–2008 and 2010–2014, generally coincide with a deceleration in money supply growth, suggesting a contractionary monetary policy effect. Conversely, a sharp decline in the repo rate in 2009 coincides with a dip in money supply growth, reflecting the lagged impact of policy transmission. From 2015 onward, money supply growth stabilizes in a lower range (7–12%), with the repo rate also following a declining trend, reinforcing the idea that monetary policy adjustments influence liquidity expansion. The data suggests that tighter monetary policy periods (higher repo rates) tend to be associated with subdued money supply growth, while rate cuts have mixed effects, possibly influenced by external economic conditions and structural liquidity factors in the banking system.

REVERSE REPO:-

The following is the hypothesis

Null Hypothesis: Reverse Repo is not stationarized.

Alternative Hypothesis: Reverse Repo is stationarized

Table: 4.2.3

Trend Analysis for Reverse Repo

Illustrations are not included in the reading sample

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table presents the year-on-year growth rates of money supply and the reverse repo rate from 2004 to 2024, offering insights into their trends and interdependencies over the period. The money supply growth rate fluctuates significantly, starting at 16.86% in 2004, experiencing a peak of 25.31% in 2008, followed by a decline and intermittent fluctuations, stabilizing at 10.76% in 2024. Meanwhile, the reverse repo rate also follows a dynamic pattern, initially increasing from 4.75% in 2004 to 5.45% in 2006, before declining to 5.00% in 2007 and remaining stable through 2008. A significant dip occurs in 2009, bringing the rate down to 3.55%, coinciding with a decline in money supply growth, likely due to the global financial crisis. The period from 2010 to 2014 sees a steady increase in the reverse repo rate, peaking at 6.89% in 2012, alongside moderate fluctuations in money supply growth, suggesting an attempt to manage liquidity through policy adjustments. Post-2015, both variables show a declining trend, with the reverse repo rate dropping from 6.35% in 2015 to 3.35% in 2021, a level maintained through 2024, reflecting an extended accommodative policy stance. Interestingly, despite a consistently low reverse repo rate from 2020 onward, money supply growth remains relatively stable between 7.97% and 12.58%, indicating that factors beyond short-term liquidity absorption—such as structural economic conditions, inflationary concerns, and credit demand—may also play a significant role in influencing money supply. The overall trend suggests that higher reverse repo rates (such as in 2011–2014) generally correspond with subdued money supply growth, supporting the notion that liquidity absorption through the reverse repo mechanism can restrict monetary expansion, whereas prolonged periods of lower rates (2020–2024) have not led to excessive growth in money supply, possibly due to cautious lending behaviour or external economic uncertainties.

CRR:-

The following is the hypothesis

Null Hypothesis: CRR is not stationarized.

Alternative Hypothesis: CRR is stationarized

Table: 4.2.4

Trend Analysis for CRR

Illustrations are not included in the reading sample

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table provides a year-on-year trend analysis of money supply growth and the Cash Reserve Ratio (CRR) from 2004 to 2024, highlighting their fluctuations and potential interdependencies. The money supply growth rate exhibits considerable variation, starting at 16.86% in 2004, peaking at 25.31% in 2008, followed by a decline to 19.45% in 2009, and then stabilizing at lower levels in subsequent years, reaching 10.76% in 2024. The CRR, which represents the mandatory reserve requirement that banks must hold with the central bank, also shows a fluctuating pattern. It begins at 5.00% in 2004, gradually increases to 7.38% in 2008—coinciding with the peak in money supply growth—before being sharply reduced to 5.30% in 2009, likely as a monetary easing measure in response to the global financial crisis. Between 2010 and 2014, the CRR continues to decline, reaching its lowest level of 3.00% in 2014, where it remains unchanged until 2019. This period of reduced CRR corresponds with a more moderate growth in money supply, suggesting that other factors, such as credit demand and inflationary pressures, may have influenced liquidity expansion. From 2020 onward, the CRR is gradually increased again, peaking at 4.36% in 2022 before slightly declining to 4.13% in 2024, while money supply growth fluctuates within a narrow range (7.97% to 12.58%). The inverse relationship between CRR and money supply is evident in certain years—such as 2007–2008, where a sharp CRR increase aligns with high money supply growth, indicating the central bank's attempt to control excess liquidity. Conversely, the CRR reductions in 2009 and 2013–2015 seem to align with more stable money supply growth, reflecting an accommodative stance aimed at stimulating credit flow. However, the trend from 2020–2024 suggests that despite gradual increases in the CRR, money supply growth has remained relatively stable, implying that liquidity conditions are influenced by broader macroeconomic factors beyond reserve requirements alone.

SLR:-

The following is the hypothesis

Null Hypothesis: SLR is not stationarized.

Alternative Hypothesis: SLR is stationarized

Table: 4.2.5

Trend Analysis for SLR

Illustrations are not included in the reading sample

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The trend analysis of Money Supply and Statutory Liquidity Ratio (SLR) from 2004 to 2024 highlights significant shifts in monetary policy and liquidity regulation over the years. Money supply growth exhibited fluctuations, peaking in 2008 at 25.31%, followed by a decline in subsequent years, reaching its lowest point in 2017 at 7.76%, and then moderately stabilizing around 10.76% in 2024. On the other hand, SLR remained stable at 24% from 2004 to 2007, before experiencing gradual reductions, reaching 18% in 2021, where it remained unchanged through 2024. A key observation is that during periods of declining SLR, particularly from 2011 to 2020, money supply growth also exhibited a downward trend, indicating that reductions in SLR, aimed at increasing liquidity by freeing up bank reserves, did not necessarily translate into higher money supply growth. Conversely, in years where money supply growth rebounded, such as 2019 and 2020, SLR reductions might have played a supporting role in easing liquidity constraints. The stabilization of SLR at 18% from 2021 onward, alongside moderate money supply growth, suggests a balanced approach to liquidity management, ensuring sufficient credit availability without excessive inflationary pressures. This trend highlights the evolving role of SLR adjustments in influencing liquidity conditions while aligning with broader economic and policy objectives.

4.3 BIVARATE CORRELATIONS

BANK RATE:- Table: 4.3.1

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table represents the bivariate correlation between money supply (dependent variable) and the bank rate (independent variable), with a correlation coefficient of 0.665170. This positive correlation indicates a moderately strong direct relationship between the two variables, suggesting that changes in the bank rate are associated with proportional changes in money supply. The objective of the analysis is to determine whether a significant relationship exists between money supply and the bank rate, and the observed correlation supports this hypothesis. A higher bank rate typically implies a contractionary monetary policy, discouraging borrowing and reducing liquidity in the financial system, which could slow down money supply growth. Conversely, a lower bank rate encourages lending and investment, leading to an increase in money supply. The correlation coefficient of 0.665170, being significantly above zero, suggests that variations in the bank rate have a meaningful impact on money supply dynamics, though other macroeconomic factors may also play a role. Given the strength of the correlation, it can be inferred that the bank rate is an influential determinant of money supply, reinforcing the argument that a significant relationship exists between these two economic variables. However, further statistical testing, such as regression analysis or causality tests, would be necessary to establish the precise nature and direction of this relationship beyond mere correlation.

REVERSE REPO:- Table: 4.3.2

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The bivariate correlation analysis between Money Supply (dependent variable) and Reverse Repo Rate (independent variable) reveals a very weak positive correlation of 0.0288. This near-zero correlation suggests that changes in the reverse repo rate have had little to no direct linear relationship with fluctuations in money supply over the observed period. Given the objective of examining whether a significant relationship exists between money supply and the reverse repo rate, the results indicate that the reverse repo rate may not be a primary driver of money supply variations. In theory, an increase in the reverse repo rate should reduce liquidity in the banking system by encouraging banks to park excess funds with the central bank, thereby contracting money supply. However, the low correlation suggests that other macroeconomic variables, such as credit growth, fiscal policies, or demand-side factors, might have had a stronger influence on money supply trends. Thus, based on this correlation analysis, there is no significant relationship between money supply and the reverse repo rate, indicating that liquidity conditions may be shaped by a broader set of monetary and economic factors beyond just the reverse repo mechanism.

CRR: Table: 4.3.3

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table represents the bivariate correlation between money supply (the dependent variable) and the Cash Reserve Ratio (CRR) (the independent variable), with a correlation coefficient of 0.799767. This strong positive correlation suggests a significant relationship between the two variables, implying that changes in CRR are closely associated with corresponding changes in money supply. The objective of this analysis is to determine whether a significant relationship exists between money supply and CRR, and the observed correlation supports this hypothesis. Typically, CRR is a key monetary policy tool used by central banks to regulate liquidity in the banking system. In theoretical economic models, a higher CRR requires banks to hold more reserves with the central bank, effectively reducing the amount of money available for lending, which in turn should contract the money supply. Conversely, a lower CRR increases the funds available for lending, leading to an expansion of money supply. However, the observed positive correlation (0.799767) suggests that money supply and CRR tend to move in the same direction, rather than exhibiting an inverse relationship as traditionally expected. This indicates that rather than CRR directly driving changes in money supply, central banks may be adjusting CRR in response to existing liquidity conditions. For instance, in periods of rapid money supply growth, monetary authorities may increase CRR to absorb excess liquidity and control inflationary pressures. Similarly, in times of lower money supply growth, CRR may be reduced to encourage lending and economic expansion. The strength of the correlation (0.799767) suggests that CRR is a highly significant determinant of money supply, reinforcing the notion that liquidity conditions in the economy are heavily influenced by reserve requirements. However, the relationship is likely influenced by other macroeconomic factors such as demand for credit, interest rates, inflation, and fiscal policies. While the strong positive correlation confirms that a significant relationship exists between money supply and CRR, it does not establish a direct causal link. Further econometric analysis, such as regression modelling or causality tests, would be required to determine the extent to which changes in CRR drive variations in money supply. Nonetheless, this high correlation suggests that CRR adjustments are systematically aligned with changes in money supply, reflecting the central bank's active role in monetary regulation.

REPO:- Table: 4.3.4

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table represents the bivariate correlation between money supply (the dependent variable) and the repo rate (the independent variable), with a correlation coefficient of 0.401540. This moderate positive correlation indicates that changes in the repo rate are associated with proportional changes in money supply, though the relationship is not as strong as in other monetary policy instruments like the Cash Reserve Ratio (CRR). The objective of this analysis is to determine whether a significant relationship exists between money supply and the repo rate, and the observed correlation supports this claim, albeit with a weaker association compared to other monetary policy tools. The repo rate serves as a crucial monetary policy instrument through which the central bank controls short-term liquidity in the financial system. In traditional economic theory, an increase in the repo rate makes borrowing more expensive for commercial banks, discouraging lending and thereby contracting the money supply. Conversely, a decrease in the repo rate reduces borrowing costs, encouraging banks to extend more credit and thereby expanding the money supply. However, the observed correlation of 0.401540, though positive, suggests that the relationship is not particularly strong. This may indicate that while repo rate adjustments influence money supply dynamics, their impact is not as direct or dominant as other factors such as fiscal policy, inflationary pressures, or credit demand. The positive correlation suggests that money supply and repo rate tend to move in the same direction, implying that during periods of monetary expansion, when liquidity is abundant, the central bank may also increase the repo rate as a tightening measure to control inflation. Conversely, during economic downturns or slowdowns in money supply growth, the central bank may reduce the repo rate to stimulate borrowing and economic activity. The moderate strength of the correlation indicates that while repo rate adjustments influence money supply, the effect may be conditional on other macroeconomic factors such as the banking sector’s willingness to lend, global financial conditions, and monetary transmission efficiency. Overall, the correlation coefficient of 0.401540 confirms that a significant relationship exists between money supply and the repo rate, though the impact is not overwhelmingly strong. While repo rate changes play a role in shaping liquidity conditions, other monetary policy tools, such as the Cash Reserve Ratio (CRR), bank rate, or Open Market Operations (OMO), may have a more pronounced influence on money supply fluctuations. Further statistical analysis, such as regression modelling or causality testing, would be required to assess the precise impact of repo rate adjustments on money supply growth. Nonetheless, the observed correlation underscores the repo rate’s relevance as a liquidity management tool, even if it is not the sole determinant of money supply movements.

SLR:- Table: 4.3.5

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The bivariate correlation analysis between Money Supply (dependent variable) and Statutory Liquidity Ratio (SLR) (independent variable) reveals a strong positive correlation of 0.7262. This indicates a significant relationship, meaning that changes in SLR are closely associated with fluctuations in money supply. A higher SLR typically requires banks to hold more liquid assets, which can restrict their lending capacity and, in turn, reduce money supply growth. However, the observed positive correlation suggests that, historically, an increase in SLR has coincided with higher money supply, possibly due to external factors such as expansionary monetary policies, increased banking sector liquidity, or economic conditions that have offset the restrictive effects of a higher SLR. The strong correlation supports the objective that "a significant relationship exists between money supply and SLR," highlighting the importance of liquidity regulations in influencing overall monetary expansion. However, further analysis, such as causality tests, would be needed to determine whether SLR directly drives changes in money supply or if other economic variables mediate this relationship.

MONETARY POLICY:-

Table: 4.3.6

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given table represents the bivariate correlation between money supply (the dependent variable) and monetary policy (the independent variable), with a correlation coefficient of 0.704602. This strong positive correlation indicates a significant relationship between monetary policy decisions and money supply dynamics, suggesting that changes in monetary policy are systematically associated with proportional changes in the money supply. The objective of this analysis is to determine whether a significant relationship exists between money supply and monetary policy, and the observed correlation strongly supports this hypothesis. Monetary policy, implemented by the central bank through tools such as the repo rate, reverse repo rate, Cash Reserve Ratio (CRR), Statutory Liquidity Ratio (SLR), Open Market Operations (OMO), and bank rate, directly influences liquidity conditions in the economy. A tight monetary policy, characterized by higher interest rates and reserve requirements, tends to restrict money supply growth by making credit more expensive and reducing the availability of funds in the banking system. Conversely, an expansionary monetary policy, marked by lower interest rates and reserve requirements, encourages borrowing and investment, thereby increasing money supply. The high correlation coefficient (0.704602) suggests that monetary policy adjustments are a significant determinant of money supply changes, reinforcing the central bank's role in managing liquidity to achieve macroeconomic stability. The positive nature of this correlation implies that monetary policy decisions and money supply tend to move in the same direction, which may reflect a responsive policy approach. For instance, during periods of strong money supply growth, the central bank may implement restrictive measures to control inflation, while during periods of weaker money supply growth, it may adopt accommodative policies to stimulate economic activity. However, while the strong correlation confirms a substantial link, it does not establish causality. Other macroeconomic factors, such as fiscal policies, global financial conditions, demand for credit, and inflationary pressures, also play critical roles in influencing money supply. Overall, the correlation of 0.704602 indicates that a significant relationship exists between money supply and monetary policy, affirming the effectiveness of policy interventions in regulating liquidity conditions. However, further econometric analysis, such as regression modelling or causality tests, would be required to quantify the precise impact of monetary policy measures on money supply fluctuations. Nonetheless, the strong positive correlation underscores the crucial role of monetary policy as a key instrument in managing money supply and maintaining economic stability.

4.4 ORIDINARY LEAST SQUARE (OLS)

Table: 4.4.1

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Ordinary Least Squares (OLS) regression results examine the effects of monetary policy fluctuations on liquidity management in India by analysing the relationship between Money Supply (dependent variable) and key monetary policy tools: Bank Rate, Cash Reserve Ratio (CRR), Repo Rate, Reverse Repo Rate, and Statutory Liquidity Ratio (SLR) (independent variables). The model demonstrates a strong explanatory power with an R-squared value of 0.8016, indicating that approximately 80.16% of the variation in Money Supply is explained by these monetary policy variables. Among them, Bank Rate (-3.6089, p = 0.0310) has a significant negative impact on Money Supply, suggesting that higher borrowing costs reduce liquidity. Repo Rate (3.1844, p = 0.0362) and SLR (2.9858, p = 0.0114) show significant positive effects, implying that while a higher repo rate may encourage money supply growth, an increase in SLR—despite traditionally being a liquidity-restricting measure—may have contributed to liquidity expansion, possibly due to accommodative policy adjustments. Conversely, CRR (1.2167, p = 0.2186) and Reverse Repo (-1.7078, p = 0.1541) are found to be statistically insignificant, indicating that changes in these rates do not have a substantial direct effect on money supply within the observed period. The negative constant (-39.1763, p = 0.0074) suggests an underlying declining trend in money supply when policy variables are held constant. Overall, the findings confirm that monetary policy fluctuations play a critical role in liquidity management, with Bank Rate, Repo Rate, and SLR emerging as the most influential tools in regulating money supply in India.

Table: 4.4.2

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The Ordinary Least Squares (OLS) regression analysis examines the impact of monetary policy on money supply in India, aligning with the objective of understanding how monetary policy fluctuations influence liquidity management. The R-squared value of 0.4965 suggests that approximately 49.65% of the variation in money supply can be explained by changes in monetary policy, indicating a moderate relationship between the two variables. The coefficient for monetary policy is 0.0261, meaning that a 1-unit increase in monetary policy measures (such as adjustments in policy rates or liquidity tools) leads to a 0.0261-unit increase in money supply, suggesting a positive relationship between the two. The p-value of 0.0004 is highly significant (well below the 0.05 threshold), confirming that monetary policy has a statistically significant impact on money supply. The intercept (C) is -9.9286 with a p-value of 0.0867, indicating that in the absence of monetary policy interventions, the money supply would be lower, but this effect is not strongly significant. Overall, the results support the objective by demonstrating that monetary policy plays a crucial role in influencing liquidity conditions in India, with policy adjustments significantly affecting money supply movements. However, since the R-squared value is below 50%, other macroeconomic factors beyond monetary policy also contribute to liquidity variations, suggesting the need for a broader analysis that includes fiscal policy, economic growth, and inflationary trends.

4.5 VECTOR AUTOREGRESSION (VAR)

STEP 1:

Figure: 4.5.1

Source: - The data is compiled and analysed by Authors

The above graph illustrates the future momentum of the independent variables (Bank Rate, CRR, Repo Rate, Reverse Repo Rate, and SLR) in relation to the dependent variable (Money Supply). The blue dots represent future predictions of the relationship between these variables. As the blue dots are observed inside the circle, this indicates a significant impact of Bank Rate, CRR, Repo Rate, Reverse Repo Rate, and SLR on Money Supply in the near future, suggesting that monetary policy fluctuations will continue to play a crucial role in liquidity management.

STEP 2:-

Table: 4.5.1

Illustrations are not included in the reading sample

Source: - The data is compiled and analysed by Authors

The given Vector Auto Regression (VAR) estimates analyse the relationship between money supply and monetary policy over the period 2005–2024, incorporating 20 observations after adjustments. The VAR model includes lagged values of both variables to assess their interdependence over time. Below is a detailed interpretation of the results: The coefficient of MONEY_SUPPLY (-1) is 0.837430, implying that a 1-unit increase in the previous period's money supply is associated with a 0.837-unit increase in monetary policy. However, its t-statistic (0.25500) suggests that this effect is not statistically significant. In conclusion, a significant relationship exists between money supply and monetary policy, the estimated coefficients suggest that monetary policy is more influenced by its own past values than by changes in money supply.

4.6 Limitations of the Study

1. The study focuses solely on M3 (Broad Money) as a proxy for liquidity and the constructed MPI as a proxy for monetary policy. Other variables, such as foreign exchange reserves, fiscal policy, and global economic conditions, are excluded, which might influence liquidity dynamics.
2. The study focuses exclusively on India, and the findings may not be applicable to other countries with different monetary systems and liquidity management frameworks.
3. Factors such as political decisions, market sentiment, and global financial crises, which may indirectly influence liquidity, are not explicitly considered in this study.

FINDINGS AND CONCLUSIONS

5.1 FINDINGS

1. The study found that there is a decline in the bank rate from 2012 to 2020 coincided with reduced money supply growth, indicating that lower borrowing costs did not significantly boost liquidity. The subsequent rise in the bank rate post-2020 saw a mild recovery in money supply, suggesting monetary tightening to manage inflation.
2. It reports that the higher repo rates generally corresponded to lower money supply growth, as seen between 2010 and 2017. This highlights the central bank’s role in controlling liquidity through interest rate adjustments, with rate cuts post-2020 aiding in economic recovery.
3. It reports the decline in the reverse repo rate from 2012 to 2021 aligned with moderate money supply growth, reflecting an accommodative policy stance. The prolonged low reverse repo rate post-2021 indicates liquidity support to sustain economic activity amid uncertainties.
4. The study the founds the reduction in CRR post-2008 facilitated liquidity expansion, while increases in 2020 and 2022 coincided with a slowdown in money supply growth. This indicates that CRR changes effectively influenced liquidity conditions in response to economic shifts.
5. It indicates a gradual decline in SLR from 24% (2007) to 18% (2021) allowed banks to extend more credit, but money supply growth remained subdued due to broader economic factors. This indicates that while lower reserve requirements supported liquidity, demand-side factors also played a crucial role.
6. It observes from the bivariate correlation that the correlation coefficient of 0.665170 indicates a moderately strong positive relationship, indicating that as the bank rate rises, money supply also tends to increase. This implies that macroeconomic factors, such as credit expansion and policy interventions, influence liquidity.
7. It also found that the very weak correlation (0.0288) between the reverse repo rate and money supply indicates no significant relationship between the two variables. This indicates that money supply fluctuations are primarily driven by other monetary tools and broader economic conditions rather than the reverse repo rate alone.
8. It indicates from OLS that there is a significant negative coefficient (-3.6089) indicates that an increase in the bank rate reduces liquidity. This indicates that tightening monetary policy through higher bank rates effectively controls money supply.
9. It found that repo rate (3.1844) and SLR (2.9858) have a significant positive impact on money supply, implying that higher rates may be associated with increased liquidity. This indicates that policy adjustments in these rates influence credit availability and financial flows.
10. It founds that the coefficient (0.0261) and highly significant p-value (0.0004) indicate a strong positive relationship between monetary policy changes and money supply. This confirms that monetary policy adjustments are crucial in regulating liquidity and ensuring economic stability in India.
11. It reports from the future momentum tool that, there is a high correlation (0.837430) indicates that future monetary policy adjustments will significantly impact liquidity. Expansionary policies are expected to boost money supply, while contractionary measures may restrict liquidity, reinforcing the critical role of policy decisions in managing financial stability.

5.2 SUGGESTION

1. The study suggests that higher bank rates and repo rates reduce money supply , while lower rates post-2020 helped economic recovery. Policymakers should adjust interest rates carefully, ensuring they support liquidity without triggering inflation or economic instability .
2. The study suggests that reverse repo rate has a weak correlation with money supply , indicating limited impact. The Reserve Bank of India (RBI) should re-evaluate its effectiveness and consider complementary liquidity management measures to strengthen its role in monetary policy.
3. The study suggests that monetary tightening through higher bank rates effectively controls liquidity . Policymakers should continuously assess the impact of rate hikes on credit availability and ensure that liquidity constraints do not hinder economic growth .
4. The study suggests that macroeconomic factors, such as credit expansion and policy interventions, influence liquidity . The government and RBI should coordinate fiscal and monetary policies to ensure a stable financial environment and support long-term economic growth.
5. The study suggests that future monetary policy changes will significantly impact liquidity, with expansionary policies boosting money supply and contractionary measures restricting it . Policymakers should use predictive models and real-time economic indicators to make proactive, data-driven decisions for liquidity management .

5.3 CONCLUSION

The study concludes that monetary policy plays a crucial role in managing liquidity and optimizing economic performance in India. The findings indicate that changes in key monetary policy tools—such as the bank rate, repo rate, reverse repo rate, CRR, and SLR—significantly influence liquidity conditions. While lower interest rates post-2020 aided economic recovery, monetary tightening through increased rates helped control inflation and liquidity fluctuations. The study also highlights that policy interventions, such as CRR and SLR adjustments, effectively impact money supply, demonstrating the Reserve Bank of India's critical role in financial stability. Additionally, the OLS results confirm a strong relationship between monetary policy changes and liquidity regulation, emphasizing that strategic policy decisions are essential for balancing economic growth and stability. Looking ahead, the high correlation between future monetary policy adjustments and liquidity suggests that expansionary policies will boost liquidity, whereas contractionary measures will tighten financial conditions. Thus, a well-calibrated monetary policy framework is vital for ensuring economic stability, fostering credit availability, and optimizing liquidity management in India.

Monetary policy serves as a cornerstone in optimizing economic performance by effectively managing liquidity conditions in India. Through various policy tools, including the bank rate, repo rate, reverse repo rate, Cash Reserve Ratio (CRR), and Statutory Liquidity Ratio (SLR), the Reserve Bank of India (RBI) actively regulates the supply of money to maintain financial stability, control inflation, and foster economic growth. The findings of this study highlight the intricate and evolving relationship between monetary policy measures and money supply growth over the years. While conventional economic theory suggests that lower borrowing costs should stimulate liquidity, the observed decline in the bank rate from 2012 to 2020 did not lead to significant money supply growth. This suggests that interest rate reductions alone may not always be sufficient to drive liquidity expansion, especially when demand-side factors and broader macroeconomic conditions play a decisive role. However, post-2020, as the bank rate increased, money supply showed mild recovery, indicating that monetary tightening was implemented as part of inflation control measures.

Similarly, the repo rate has demonstrated a strong inverse relationship with money supply growth, particularly between 2010 and 2017, when higher repo rates coincided with reduced liquidity. This underscores the RBI’s crucial role in controlling inflation and liquidity by adjusting policy rates. The repo rate cuts post-2020 further reinforced this impact, as they supported economic recovery by easing credit availability. The reverse repo rate, which serves as a tool for absorbing excess liquidity, exhibited a prolonged decline from 2012 to 2021, aligning with moderate money supply growth. This trend reflects an accommodative policy stance aimed at sustaining economic activity, particularly in uncertain economic environments. The persistently low reverse repo rate post-2021 highlights the central bank’s continued efforts to support liquidity amid economic uncertainties, reinforcing its role as a stabilizing force in the financial system.

Beyond interest rate policies, the study also highlights the role of reserve requirements in liquidity management. The reduction in CRR following the 2008 financial crisis facilitated liquidity expansion, helping to stimulate economic activity. However, subsequent increases in CRR during 2020 and 2022 coincided with a slowdown in money supply growth, demonstrating the effectiveness of reserve requirements in controlling liquidity conditions. This suggests that the RBI uses CRR adjustments as a flexible tool to manage liquidity based on evolving economic conditions. Similarly, the gradual decline in SLR from 24% in 2007 to 18% in 2021 provided banks with greater lending capacity. While lower SLR supported liquidity expansion, overall money supply growth remained subdued due to external economic factors, highlighting the role of demand-side influences in determining credit growth and liquidity dynamics.

The statistical analyses further reinforce these findings. The bivariate correlation analysis indicates a moderately strong positive relationship (0.665170) between the bank rate and money supply, suggesting that macroeconomic factors, such as credit expansion and policy interventions, significantly influence liquidity. On the other hand, the very weak correlation (0.0288) between the reverse repo rate and money supply suggests that fluctuations in liquidity are primarily driven by broader monetary policy tools and economic conditions rather than the reverse repo rate alone. The Ordinary Least Squares (OLS) regression analysis confirms the significant role of monetary policy in influencing money supply, with the bank rate exhibiting a negative impact (-3.6089), while repo rate (3.1844) and SLR (2.9858) show a positive influence. The high R-squared value (0.8016) further indicates that monetary policy variables explain a significant portion of money supply variations, reinforcing their importance in liquidity regulation.

Looking ahead, the study’s future momentum analysis presents critical insights into the potential trajectory of liquidity management. The strong positive correlation (0.837430) between monetary policy and future money supply growth suggests that policy adjustments will continue to shape financial conditions significantly. Expansionary policies, such as lower interest rates and reduced reserve requirements, are expected to drive liquidity growth, enhancing credit availability and economic expansion. Conversely, contractionary measures, including higher interest rates and tightened reserve requirements, will likely lead to a slowdown in money supply growth as part of inflation control efforts. These insights underscore the importance of proactive monetary policy management in ensuring financial stability and sustaining long-term economic growth.

Overall, this study emphasizes the pivotal role of monetary policy in optimizing economic performance through effective liquidity management in India. The findings demonstrate that while interest rates, reserve requirements, and policy interventions significantly impact money supply, external economic factors and demand-side influences also play a crucial role. Policymakers must carefully balance monetary policy measures to maintain financial stability, control inflation, and support economic growth. A well-calibrated approach to liquidity management—considering both macroeconomic trends and sector-specific needs—will be essential in navigating economic challenges and ensuring a stable financial environment. By continuously adapting monetary policy strategies to align with evolving economic conditions, the Reserve Bank of India can effectively sustain economic resilience and foster long-term financial stability.

REFERENCES

1. Śliwiński, P. (2023). Endogenous money supply, global liquidity and financial transactions: Panel evidence from OECD countries. Equilibrium.

2. Duodu, E., Baidoo, S. T., Yusif, H., & Frimpong, P. B. (2022). Money supply, budget deficit and inflation dynamics in Ghana: An empirical investigation. Cogent Business & Management.

3. Yang, X., & Shafiq, M. N. (2020). The impact of foreign direct investment, capital formation, inflation, money supply and trade openness on economic growth of Asian countries.

4. Sahu, T. N., & Pandey, K. D. (2020). Money supply and equity price movements during the liberalized period in India. Global Business Review.

5. Ayad, H. (2020). Money supply, inflation and economic growth: Co-integration and causality analysis. Studia Universitatis Babeș-Bolyai Oeconomica.

6. Van, D. D. (2019). Money supply and inflation impact on economic growth. Journal of Financial Economic Policy.

7. Omodero, C. O. (2019). Effect of money supply on economic growth: A comparative study of Nigeria and Ghana. International Journal of Social Science Studies.

8. Verma, S. (2023). An analysis of the nature of money supply in India and its expected causes. International Journal for Multidisciplinary Research.

9. Weerasinghe, P. N. (2009). Inflation and monetary policy.

10. Muhanna, E. (2017). Inflation targeting and its impact on monetary policy: A South African insight. Banks and Bank Systems.

11. Abdullah, A. A. (2017). The 1997-2011 global financial crisis: Causes, policy recommendations, and lessons.

12. Bhardwaj, A., Subramanian, K., & Tantri, P. L. (2015). Relationship banking and monetary policy transmission: Evidence from India. Journal of Money, Credit and Banking.

13. Chima, M., Babajide, A. A., Omankhanlen, A. E., & Adejumo, B. (2020). Development: Unconventional monetary policy on bank performance in Nigeria. WSEAS Transactions on Environment and Development.

14. Alam, M. M., & Salah Uddin, M. G. (2009). Relationship between interest rate and stock price: Empirical evidence from developed and developing countries. International Journal of Biometrics.

15. Akhtar, Y., Kayani, G. M., & Yousaf, T. (2019). The effects of regulatory capital requirements and ownership structure on bank lending in emerging Asian markets. Journal of Risk and Financial Management.

16. Author Unknown. (2017). Monitory public policy network institutions and their inclusion in the processes of policy making: From confrontation to cooperation.

17. Salah Uddin, M. G., & Alam, M. M. (2010). The impacts of interest rate on stock market: Empirical evidence from Dhaka Stock Exchange.

18. Schrimpf, A., Shim, I., & Shin, H. S. (2021). Liquidity management and asset sales by bond funds in the face of investor redemptions in March 2020. Social Science Research Network.

19. Ajayi, J. A., & Lawal, Q. (2021). Effect of liquidity management on banks' profitability.

20. Zeng, Y. (2017). A dynamic theory of mutual fund runs and liquidity management. Social Science Research Network.

21. Emmanuel, E., & Stephen, A. E. (2020). Liquidity management and performance of deposit money banks in Nigeria.

22. El Hamiani Khatat, M., & Veyrune, R. M. (2019). Liquidity management under fixed exchange rate with open capital account. IMF Working Papers.

23. Bianchi, J., & Bigio, S. (2022). Banks, liquidity management, and monetary policy. Econometrica.

24. Kholifatul Rizkiah, S. (2018). Liquidity management in Islamic banking: Issues and challenges. Tazkia Islamic Finance and Business Review.

25. Akinwumi, I. A., Micheal, E. J., & Raymond, A. R. (2017). Liquidity management and banks' performance in Nigeria.

[...]

• Course: B.Com. International Accounting and Finance
• Grade: A
• Authors: Radhika P. Y. (Author), Sanjiv Saigal (Author), Yash Raj Kanojia (Author), Nevlyn Karra (Author), Amrose Joseph (Author), A. Pashupathinath (Author), M. Veera Swamy (Author), M. Arul Jothi (Author)
• Publication Year: 2024
• Pages: 73
• Catalog Number: V1577605
• ISBN (PDF): 9783389140406
• ISBN (Book): 9783389140413
• Language: English
• Tags: Monetary policy India, Liquidity management, Repo rate effect, Money supply M3, Economic performance India