INTRODUCTION
Problem statement
Banking system plays a significant role in economic development process in Vietnam
Banks serve as essential financial intermediaries in the economy, facilitating the flow of capital between savers and borrowers while supporting various economic and social activities By connecting companies to the market, banks play a crucial role in economic regulation, making them vital tools for government intervention The government oversees the macro-economy through various strategies, including monetary policy, fiscal policy, foreign capital control, and trade policy This article specifically examines the impact of monetary policy on the banking system.
The banking system plays a crucial role in the economy by facilitating credit operations and payment transactions among commercial banks, all while adhering to government regulations This system not only expands the money supply by providing credit to various economic sectors but also acts as a vital financial intermediary that supports economic growth by meeting capital needs and fostering business development The volume of bank loans reflects this intermediary function and indicates the flow of money within the economy Several factors influence bank loan supply, including capital input costs, monetary policies, economic conditions, and loan demand This article focuses specifically on the impact of monetary policy on loan supply, highlighting its significance for understanding the strength and distributional effects of such policies Additionally, comprehending how monetary policy affects loan supply reinforces the connection between government stabilization efforts, regulatory policies, and the decision-making processes of bankers in Vietnam.
B S Bernanke and Blinder (1989)suggested bank intermediation is seen to be especially crucial in a situation of asymmetric information and moral hazard since only bank specializes in monitoring their borrowers Moreover, bonds and bank loans are assumed not perfectly substitute so then many firms would turn into bank dependent
The bank lending channel plays a crucial role in the monetary transmission mechanism, influencing both bank assets and liabilities Monetary policy impacts not only the supply of deposits but also the availability of bank loans As banks primarily rely on deposit financing, they adjust their loan supply in response to changes in bank reserves triggered by monetary policy shocks Consequently, when monetary policy tightens, banks reduce their loan supply, with weaker, undercapitalized banks responding more significantly than their larger, well-capitalized counterparts Numerous empirical studies, including those by Kashyap and Stein (1995), further explore this phenomenon.
Kashyap and Stein (1997, 2000) found that large banks are more effective at mitigating monetary shocks compared to smaller banks, based on their analysis of disaggregated bank data Additionally, research by Kishan and Opiela (2000) along with Alcoforado Farinha and Robalo Marques further supports these findings.
Research indicates that small and undercapitalized banks are significantly influenced by monetary policy (2001), while illiquid banks experience greater effects from monetary shocks compared to their liquid counterparts (Loupias et al., 2002) This suggests that the composition of a bank's balance sheet plays a crucial role in determining the impact of monetary policy on loan supply To explore this further in the context of Vietnam, this study aims to analyze the response of the Vietnamese banking system to changes in monetary policy shocks, utilizing the Generalized Methods of Moments (GMM) approach for a dynamic panel data model The premise is that the adjustment of banks' credit supply may vary based on their distinct characteristics.
Research objective
This study aims to analyze how the supply of bank loans in Vietnam responds to changes in monetary policy, focusing on a sample of 20 commercial banks from 2008 to 2012 It investigates whether significant differences exist in the responses of these banks, based on varying characteristics such as asset size, capitalization, and liquidity, to shifts in monetary policy, particularly regarding changes in short-term interbank deposit offer rates.
This study aims to assess the influence of interbank deposit offer rates on the availability of bank loans, while also examining the effects of bank asset size, capitalization, and liquidity on loan supply.
Finally, the study examines whether bank asset size, capitalization, and liquidity affect the impact of monetary shocks on the supply of bank loan.
Research questions
In order to obtain the above objectives, the study attempts to answer the following questions:
(i) Does change in the three-month interbank offered rate affectthe supply of bank loan?
(ii) Do bank asset size, liquidity, and capitalization affect the supply of bank loan?
(iii) Do bank asset size, liquidity, and capitalization affect the impact of monetary shocks on the supply of bank loan?
Research methodology
The paper bases on the credit channel approach of B S Bernanke and Blinder (1989);
B Bernanke (1990); B S Bernanke (1993); Kashyap and Stein (1994); Kashyap and Stein (1995); B S Bernanke and Gertler (1995);Kashyap and Stein (2000) and empirical studies about bank lending and the impact of bank characteristics and monetary policy change on the supply of bank loan
This study employs a dynamic panel data model, drawing on methodologies similar to those of Hernando and Martínez Pagés (2001), Golodniuk (2006), and Gambacorta and Marques-Ibanez (2011) Data is sourced from balance sheet statements to analyze financial trends effectively.
This article examines 20 Vietnamese commercial banks from 2008 to 2012, highlighting the advantages of using panel data in the banking and finance sector Panel data enhances variability, reduces collinearity among variables, increases degrees of freedom, and provides improved statistical fits due to the high correlation of balance sheet data Additionally, it controls for individual heterogeneity, minimizing bias and better explaining dynamic changes compared to purely time-series or cross-sectional analyses Following the recommendations of Anderson and Hsiao (1982), this study employs the Generalized Method of Moments (GMM) with a lag of two for the dependent variable as an instrument, with a detailed discussion of the econometric approach and variables presented in chapter four.
Structure of thesis
This paper is structured to cover several key areas: Chapter two explores foundational theoretical studies and connects them with current empirical literature on the bank lending channel Chapter three presents important insights into the Vietnamese monetary policy and banking system Chapter four outlines the study's methodology, including model specifications and data sources Chapter five analyzes the results from dynamic panel regressions, while Chapter six concludes with findings and their policy implications.
LITERATURE REVIEW
Theoretical literature
This section explores the theoretical literature on the bank-lending channel, focusing on how changes in monetary policy impact the supply of bank loans It outlines the mechanisms through which a representative bank generates loans and responds to monetary policy shifts Additionally, the theory highlights the fundamental components of banking activities and their interactions The relationship between monetary policy and bank loan supply, along with the influence of bank characteristics on their responses to policy changes, will be discussed.
The traditional interest rate channel views banks as passive intermediaries between the central bank and the economy, where changes in monetary policy primarily lead to lower deposit rates and a general decrease in money supply This tightening of monetary policy, characterized by reduced money supply and higher interest rates, directly dampens economic activity Consequently, a decline in bank loan demand often stems from a sluggish economy.
Among other proponents of the credit view, B S Bernanke and Blinder (1989) and B
S Bernanke and Gertler (1995) suggested that the change of aggregate demand of the economy cannot be entirely explained by the movement of interest rate They underline the role of financial intermediaries and agent costs in monetary policy transmission
The article explores the integration of the balance sheet channel and bank lending channel into the theoretical framework of the credit view regarding monetary policy transmission For a more detailed understanding of this monetary transmission process, readers are encouraged to refer to Figure A.1 in the appendix.
Monetary shocks, resulting from policy changes by the state bank, significantly impact the real economy in two key ways Firstly, these shocks influence the financial position of borrower firms; a stronger balance sheet enhances a firm's ability to secure financing from capital markets Secondly, monetary shocks can restrict access to external funding for firms by decreasing the availability of bank loans, particularly affecting bank-dependent companies.
B S Bernanke and Blinder (1989) and Kashyap and Stein (1994)indicatedthe asymmetric information problem and adverse selection problem in the balance sheet channel In this channel, firms have few substitute sources of fund beyond bank borrowing so that tightening monetary policy indirectly deteriorate borrower’s balance sheet through the rise in interest rate This deterioration raises the cost of credit intermediation and the requirement of additional collateral.Moreover, asymmetric information problem between bank and borrower also causes a wedge between internal and external cost for firm A reduction of the supply of bank loan directly raises the external finance premium of bank-dependent firms
B S Bernanke and Gertler (1995)describedbank-lending channel as a set of factors that amplify and propagate conventional interest rate.In the bank-lending channel, monetary shock transmits into the economy through adjustment to the asset side of bank’s balance sheet This channel suggests that monetary policy can affect the channel are that bank borrowers must not be able perfectly substitute bank loan with other alternative financial methods and it is costly for bank to use non-reservable financial source of fund like bond and securities to rebalance its asset portfolio after the change in reserve.Moreover, the bank-lending channel also bases on the asymmetric information and agency cost problem between banks and their borrowers, which associated with financial transaction Bank do not have perfect substitute for deposit A tightening monetary policy limits bank access to other form of financial source that do not subject to reserve requirement without cost and theycannot obtain sufficient liquidity through the sale of bond Therefore, a tightening monetary policy draws down the bank money reserve that limit bank to access to loanable fund, which means bank have less money to make loan As the result, the supply of credit falls
The assumptions and mechanism of bank lending channel are presented by B S
Bernanke and Blinder (1989) introduced a foundational model for the bank lending channel by enhancing the traditional IS-LM framework to incorporate the loan market and eliminating the assumption of perfect substitutability between bank loans and bonds This model has since served as a benchmark for subsequent research on monetary transmission from a credit perspective.
According to Van Ees et al (1999), banks typically respond to monetary shocks by either selling securities in the domestic capital market or issuing long-term liabilities, such as bonds, or by adjusting the domestic loan supply Bernanke and Blinder (1989) and Bernanke and Gertler (1995) highlight that there is an imperfect substitution between bank loans and bonds, particularly when tightening monetary policy leads to a decrease in aggregate demand and a depletion of bank reserves As deposits decline, banks face the necessity to find alternative funding sources to maintain their loan levels However, if these alternative financial sources are scarce or limited, banks are compelled to reduce their loan supply.
Moreover, there are two main conditions for the bank-lending channel to operate The first condition is that some firms must be dependent on bank loan Van den Heuvel
Small firms are often reliant on banks for financing due to their limited access to capital markets, as highlighted by Christiano (2005) and earlier research in 2002 Banks possess a comparative advantage in gathering customer information at a lower cost than investors, making them a crucial source of funding for these businesses Additionally, small firms typically do not meet the regulatory requirements necessary to issue securities on the stock market, further restricting their capital-raising options.
In countries with underdeveloped capital markets, the central bank's ability to adjust banks' loan supply is crucial Bernanke and Gertler (1995) highlighted the impact of financial market imperfections on banks' responses to monetary shocks, emphasizing that asymmetric information increases the costs for banks to raise funds through means other than deposits When the central bank tightens monetary policy and withdraws money reserves, it raises the opportunity cost of holding deposits, prompting banks to seek alternative, often more expensive and riskier financial instruments This shift leads to higher loanable fund costs and compels banks to reduce their loan supply Furthermore, Bernanke and Gertler noted that during periods of tightened monetary policy, banks are forced to decrease deposits on their balance sheets and liquidate securities in the short term Over time, banks may gradually rebuild their securities portfolios while simultaneously reducing loans, reflecting a decline in real economic activity Thus, the reduction in bank loan supply is primarily driven by decreased demand resulting from a weakened economy.
Bank specific characteristics accentuate the asymmetric information and agency cost
Kashyap and Stein (1995); Kashyap and Stein (2000); Kishan and Opiela (2000);
Research by Westerlund (2003), Alfaro et al (2003), Gambacorta and Mistrulli (2004), Bichsel and Perrez (2005), and Ezema (2009) indicates that small banks struggle more than large banks to raise funds and consequently reduce their loan supply during periods of tightening monetary policy Additionally, studies by Kashyap and Stein (2000), Alfaro et al (2003), Gambacorta and Mistrulli (2004), Gómez-Gonzalez and Grosz (2007), and Ezema (2009) highlight that banks with strong liquidity can utilize their liquid assets to protect their loan portfolios in such challenging economic conditions.
Another aspect is bank’s capitalization level B S Bernanke and Gertler (1995);
Research by Kishan and Opiela (2000), Altunbaş et al (2002), Van den Heuvel (2002), Westerlund (2003), Alfaro et al (2003), Gambacorta and Mistrulli (2004), Bichsel and Perrez (2005), Golodniuk (2006), Gómez-Gonzalez and Grosz (2007), and Gambacorta and Marques-Ibanez (2011) indicates that banks with a higher capital-to-asset ratio are perceived as less risky In contrast, banks with lower capital levels face greater challenges in securing external financing compared to their better-capitalized counterparts.
The credit approach faces the identification problem, often referred to as the simultaneity problem, where tightening monetary policy leads to reduced bank deposits and loan supply due to high interest rates impacting aggregate demand Distinguishing shifts in loan supply between the demand and supply sides is challenging; on the supply side, tighter monetary policy results in decreased bank deposits, forcing banks to limit loan availability Conversely, on the demand side, higher interest rates diminish investment, leading to a reduced demand for loans from firms in a low-growth economic environment To address this issue, researchers utilize cross-sectional or bank-level data to analyze the asymmetric behavior of loan supply in relation to monetary policy measures, as demonstrated in studies by Kishan and Opiela (2000), Altunbaş et al (2002), Westerlund (2003), and Alfaro et al.
Several studies, including those by Golodniuk (2006), Kashyap and Stein (2000), and Gambacorta and Mistrulli (2004), utilized disaggregated data on bank balance sheets to analyze the supply of bank loans This approach aimed to separate demand from supply-side effects, ensuring a clearer identification of the bank lending channel.
Bank lending channel emphasizes the role of changes in banks’ balance sheet items, i.e., in deposits and loans as conduits for monetary policy transmission B S Bernanke
(1983) denoted that when federal funds rate increase, tightening monetary policy downsize the bank activities and decrease the level of loan supply
Empirical studies
This section reviews previous empirical studies examining how changes in monetary policy affect the supply of bank loans It includes a summary of research conducted across various countries and periods, detailing methodologies and key findings While numerous studies exist in this field, this section focuses on the most significant and relevant ones To provide readers with an overview of the credit channel approach discussed in the theoretical literature, a table summarizing the interaction between bank loan supply and bank characteristics is included.
Empirical studies have examined the impact of monetary policy changes on bank loan supply, notably a study by Kishan and Opiela (2000) that analyzed quarterly data from 13,042 US commercial banks between 1980 and 1995 The researchers categorized banks based on asset size and capital leverage, employing OLS regression to assess loan growth in relation to lagged values of loans, changes in the federal funds rate, current growth in term deposits, securities, GDP, and seasonal factors Their findings revealed that monetary policy changes significantly affect the loan growth of small and undercapitalized banks, highlighting that these smaller institutions struggle to secure funding for loans during periods of tightening monetary policy.
Altunbaş et al (2002) applied the same methodology approach as Kashyap and Stein
From 1991 to 1999, a study by De Bondt (1998) and Kishan and Opiela (2000) examined the bank lending channel in 11 European Monetary Union countries, focusing on the banking systems of Germany, France, Italy, and Spain Utilizing a random effect panel data estimator, the research analyzed the growth of bank loan supply in relation to its lagged values, short-term money market values, lagged bank securities values, interbank deposit growth rates, and GDP growth rates.
The author also estimate the same model for deposit, securities and interbank borrowing to find out which balance sheet items will be affected by monetary policy
Research indicates that in the context of the European Monetary Union, undercapitalized banks, regardless of their size, are more responsive to policy changes Additionally, the banking channel effect is observed specifically in Italy and Spain among the four countries analyzed.
Westerlund (2003) applied a similar methodology to examine the hypothesis that monetary policy influences the supply of bank loans, focusing on 12 Swedish banks from January 1998 to June 2003 Utilizing the Autoregressive Distributed Lag model, the study regressed the growth rate of loans against its lagged values, changes in monetary policy instruments, bank balance sheet variables, certificates of deposit, and securities to gauge loan demand fluctuations The findings aligned with previous studies, reinforcing the connection between monetary policy and bank loan supply.
Small and undercapitalized banks exhibit a heightened sensitivity and strong reactions to changes in monetary policy Alfaro et al (2003) conducted an empirical study employing a similar methodology to Westerlund (2003) to analyze the response of bank loan supply to shifts in monetary policy While both studies utilize comparable approaches, Westerlund's research presents distinct findings that contribute to the understanding of this dynamic.
In their 2003 study, researchers utilized certificates of deposit and securities holdings to analyze loan demand fluctuations, while Alfaro et al incorporated annual GDP growth and real exchange rate depreciation as control variables for loan demand The findings revealed that smaller, less liquid, and less capitalized banks are compelled to reduce their loan supply in response to monetary policy shocks.
Golodniuk (2006) using Generalized Methods of Moments procedure to estimate a model likely the same with Westerlund (2003) for 149 Ukrainian banks from 1998 to
A 2003 study analyzes banks based on asset size, capitalization, and liquidity to determine how these factors influence lending responses during periods of tightening monetary policy The findings indicate that undercapitalized banks struggle significantly to maintain loan supply in such conditions Furthermore, the study suggests that liquidity levels are not a critical factor in explaining the changes in bank loan supply in response to policy shifts.
This literature chapter highlights that banks respond differently to changes in monetary policy via the bank lending channel, influenced by their unique characteristics, including asset size, liquidity position, and capitalization Additionally, it notes that monetary policy changes can adversely affect the supply of bank loans.
Banks with greater assets, high liquidity ratios, and strong capitalization are less impacted by monetary policy changes These characteristics play a crucial role in distinguishing the effects on bank loan supply through the lending channel and the interest rate channel For more detailed empirical reviews, please refer to table A.14 in the Appendix section.
STYLIZED FACT ON VIETNAMESE MONETARY POLICY AND
Monetary policy system
In the late 1980s, Vietnam underwent significant financial sector reform, transitioning from a mono-bank system to a two-tier banking system This reform established the State Bank of Vietnam as the central bank and introduced four large state-owned commercial banks, one small state-owned commercial bank, thirty-six joint stock banks, and a comprehensive network of people’s credit funds.
In 2004, Vietnam's banking system was primarily dominated by four major state-owned commercial banks, which represented 74% of the total credit market These banks allocated approximately 23-26% of their loan portfolios to the agriculture and aqua-cultural sectors, while 16-22% was directed towards trade and services, with 60% of loans being short-term The regulatory framework has been structured to favor these state-owned banks, which the government views as essential for financing state-owned enterprises, deemed crucial for the country's economic growth Notably, state-owned enterprises constituted 32% of the loan portfolios of these banks In contrast, joint stock banks and smaller banks focused on supporting the domestic private sector, with joint stock banks accounting for 27% of total credit, providing only 4% to state-owned enterprises and 23% to non-state sectors.
The “Law on the State Bank of Vietnam”, which enacted in 1996 and amended in
In 2003, the legal framework for the State Bank of Vietnam was established, defining it as a government agency and the central bank of the Socialist Republic of Vietnam The State Bank is responsible for managing monetary and banking activities, focusing on stabilizing currency value and safeguarding the banking system in alignment with the country’s social objectives However, its independence in monetary policy is limited, as the law designates monetary policy as the responsibility of the National Assembly and the government, positioning the State Bank more as a government department than an independent central bank.
The State Bank of Vietnam faces challenges in controlling monetary policy due to its limited operational independence from other state bodies, leading to confusion in accountability for banking sector management and supervision The National Assembly not only establishes monetary policy, including annual inflation rates, credit, and money growth, but also oversees its implementation In the context of Vietnam's financial system and ongoing financial sector reforms, an underdeveloped financial market hampers the effectiveness of monetary transmission through interest rates, making bank lending the primary and more effective channel for monetary transitions.
The Vietnamese monetary policy follows the five-year plan on the Social and
The State Bank of Vietnam is responsible for developing the banking sector's action plan, focusing on two key components of its monetary policy strategy: setting an annual target for the depreciation of the dong and establishing targets for total liquidity (M2) and credit to the economy Countries can typically pursue only two of the following options: fixed exchange rates, domestic monetary autonomy, and capital mobility Furthermore, the prevalence of dollarization restricts the ability to implement an independent monetary policy within a fixed exchange rate framework.
Since the financial sector reform, Vietnam has utilized indirect monetary policy instruments such as reserve requirements, refinancing and discount lending facilities, open market operations, and foreign exchange interventions Reserve requirements vary based on deposit maturity, the favored economic sector, and the dominant currency, with lower requirements for longer deposit periods and banks serving agriculture and people's credit funds Refinancing and discount lending facilities involve outright purchases of securities and repurchase agreements, with the discount rate being lower than the refinancing rate Open market operations control liquidity through the buying and selling of government securities and state bank bills However, due to the thin and segmented nature of Vietnam's financial market, the government and the State Bank of Vietnam believe that these indirect instruments alone are insufficient to control inflation, which is primarily driven by supply shocks Consequently, the State Bank uses the base interest rate as a reference for influencing lending rates and employs administrative measures to regulate prices The base rate serves as a fundamental determinant for credit institutions in setting lending rates in Vietnamese dong, with market participants adjusting to changes in the base rate as indicators of shifts in commercial bank lending rates.
Monetary policy and the supply of bank loan change in the period 2008 – 2012
From January 2007 to August 2008, Vietnam experienced a significant rise in inflation, peaking at 28.3% in August 2008 This surge was influenced not only by international economic integration but also by inflationary pressures from the previous year, as Vietnam prioritized economic growth and adopted expansionary macroeconomic policies In the first half of 2008, curbing inflation became the primary economic objective In February 2008, the State Bank of Vietnam raised the reserve requirement ratio by 1 percentage point for all terms and currencies, while also extending reserve requirements for deposits with terms of 24 months or more In March 2008, the bank issued VND 20.3 trillion in compulsory bills with a 364-day maturity at an 8% interest rate To tighten monetary policy, the State Bank increased the base rate from 8.25% to between 12-14%, the discount rate from 4.5% to between 11-13%, and the interbank overnight rate from 10.8% to 15% Early in 2008, the VND mobilizing rate surged to a peak of 13.8% per annum, while interbank rates also climbed due to liquidity shortages among credit institutions.
On May 16, 2008, the State Bank of Vietnam issued Decision No 16/2008/QĐ - NHNN, which established a regulatory mechanism for the VND deposit base interest rate, alongside Decision No 1098/QĐ - NHNN, setting the applicable interest rate This regulatory change increased the relative cost of bank funds and led to a reduction in loan supply following a decline in reserves due to monetary shocks As a result of the tightened monetary policy, the total loan outstanding in the banking sector rose by only 25.43% in 2008, a significant drop from the 53.89% growth rate observed in 2007, highlighting a notable decrease in credit growth compared to the previous year.
In 2009, inflation rate declines The average consumer price index in 2009 compared to
In 2008, inflation increased by 6.88%, significantly lower than previous years However, from September to December 2009, driven by government stimulus measures, rising global prices, and an appreciating VND/USD exchange rate, inflation surged again The banking system's fund mobilization rose by 29.88%, surpassing the 2008 rate, while total outstanding loans increased by 37.53% due to these stimulus policies Initially, credit growth was sluggish in the first two months of the year, mirroring trends from 2008 However, from March to September 2009, credit growth accelerated as a result of government support and lower interest rates This response aligns with the bank lending channel mechanism proposed by B S Bernanke and Gertler (1995).
Between September 2010 and December 2011, inflation surged to 11.8% compared to December 2009, peaking at 18.1% in December 2011 In the early months of 2010, interest rate volatility was high due to the State Bank of Vietnam's upward adjustments to the base rate and restrictions on money supply However, interest rates in 2010 significantly decreased, with VND mobilizing and lending rates dropping by approximately 1% and 1.3% per annum, respectively, compared to 2009 By the end of 2010, rising capital demand for consumption and investment led to increased lending and deposit rates In 2011, the State Bank's tightening monetary policy caused mobilizing and lending rates to rise, with the average VND mobilizing interest rate reaching 15.6% per annum by June 2011, up from 12.44% at the end of 2010 Following the implementation of interest rate ceilings by commercial banks in September 2011, market interest rates slowed bank loan growth Although total credit growth was sluggish in early 2010, it began to rise in May 2010 due to a decrease in interest rates from the Governor’s Resolution No 18/NQ-CP By September 2010, total credits in the banking system reached 31.19%, down from 37.53% in 2009.
In 2010 and 2011, the State Bank of Vietnam implemented a tightening monetary policy to combat inflation, leading to a slowdown in investment activities across all credit institutions, including commercial banks The total mobilized funds increased by only 12.4%, significantly lower than the previous year's rate Notably, the share of state-owned commercial banks declined, while the share of other credit institutions saw a sharp increase.
In early 2012, amid slow economic growth and low inflation, the State Bank of Vietnam reduced deposit and lending interest rates, with key rates operating under a "ceiling" for the refinancing rate and a "floor" for the discount rate, allowing for a +/- 2% market regulation By the end of 2011, deposit rates for maturities under 12 months ranged from 11-12% for small and medium enterprises and 14-17% for others Although total mobilizing funds increased by 12.4%, this was significantly lower than in 2010, with a notable shift in market share away from state-owned banks towards other credit institutions Despite the overall low interest rates in 2012, banks experienced only a slight loan growth of 1.51% compared to 2011, with sixty-nine banks reporting negative credit growth.
The changing of the supply of bank loan from 2008 to 2012 as discuss above is significantly related to the mechanism of B S Bernanke and Gertler (1995)
Tightening monetary policy, characterized by increased interest rates and reserve requirements, elevates the relative cost of bank funds, leading to a reduction in loan supply as banks respond to decreased reserves from monetary shocks Conversely, loose monetary policy tends to increase loan supply Adjustments in monetary policy significantly impact the banking system's loan supply; for instance, higher market interest rates, such as the base or interbank rate, typically result in decreased loan availability This relationship between market rate changes and bank balance sheet items is consistent with the mechanisms discussed in Chapter 2, Figure 2.1.
Table 3.1 outlines the annual changes in monetary policy and the corresponding fluctuations in the three-month interbank rate (Vnibor) This rate serves as a key instrument for monetary policy adjustments, as highlighted by B Bernanke in 1990.
Table 3.1: The short-term three months interbank deposit offer rate from 2008 to 2012
Monetary policy Tightening Loosening Tightening Tightening Loosening Vnibor
Source: Global financial data, Ho Chi Minh City securities company (HSC)
This article analyzes the Vietnamese monetary policy and its significant negative impact on the banking system's loan supply, highlighting the interplay between market interest rates and bank loans The subsequent chapter delves into the changes in loan supply within the Vietnamese banking sector, utilizing an econometric model based on data from 20 commercial banks between 2008 and 2012.
METHODOLOGY, MODEL SPECIFICATION AND DATA RESOURCES 36
Data and econometric model
This study analyzes the bank balance sheet data from 20 Vietnamese commercial banks covering the period from 2008 to 2012 The data was meticulously gathered and computed from the individual balance sheet statements of each bank, with a complete list of the commercial banks included in Table A.8 of the appendix.
Table 4.1: Variables definition and sources
ln𝐿𝑂𝐴𝑁 𝑖𝑡 Total loan of bank i in year t Bank’s balance sheet statement
ln𝐿𝑂𝐴𝑁 𝑖𝑡 (-1) One period lag of total loan of bank i in year t
Ln 𝐴𝑆𝑆𝐸𝑇 𝑖𝑡 Total asset size of bank i in year t
Ln 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌 𝑖𝑡 The liquidity ratio of bank i in year t
Ln 𝐾𝐴 𝑖𝑡 Capitalization ratio of bank i in year t
ln𝑇𝐸𝑅𝑀 𝐷𝐸𝑃𝑂𝑆𝐼𝑇 𝑖𝑡 Total term deposit of bank i in year t
To accurately model the economic significance of bank balance sheets, original figures cannot be directly imported Instead, total loans are calculated by excluding provisions for credit losses, reflecting the actual volume of loans banks extend to customers within a specific year This approach does not factor in potential future credit losses, as banks define risk differently, influenced by both their internal assessments and regulations from the State Bank of Vietnam Consequently, the total loan variable effectively represents the true supply of bank loans.
The liquidity ratio of a bank is determined by its liquid assets, which include cash on hand, balances with the State Bank of Vietnam, and loans to other credit institutions Liquid assets are those that can be quickly converted into cash and have an established market, allowing for relative ease in transfer.
The interbank borrowing amount of bank i in year t
ln𝑖 𝑡 Annualized, average weighted, short-term
(three month) SBV interbank deposit offered rate as measure of monetary policy shock – B
Ho Chi Minh City Securities Company (HSC) highlights the importance of liquidity ratios in assessing a bank's ability to meet short-term debt obligations A higher liquidity ratio indicates better management of these obligations, though it often results in lower profit due to increased liquid assets In practice, banks typically maintain this ratio at regulatory levels to ensure a margin of safety for covering short-term debts during emergencies.
The interbank borrowing variable in the equation represents the total borrowing amount from the government, the State Bank of Vietnam, and other credit institutions Banks utilize interbank loans to meet their short-term liquidity needs, borrowing funds from either the State Bank or other banks within the banking system.
The asset size variable represents a bank's total assets, which encompass liquid assets, trading and investment securities, loans, long-term investments, fixed assets, and other assets.
Capitalization ratio is calculated as the ratio of bank total capital to bank total asset
Bank capital, essential for determining a bank's capitalization, is defined as total shareholders' equity, which is calculated by subtracting total liabilities from total assets If a bank's balance sheet does not explicitly list shareholders' equity, it can be derived by subtracting total liabilities and minority interest from the sum of total liabilities and shareholders' equity Shareholders' equity reflects the financing a company receives through common and preferred stocks, encompassing capital, reserves, and retained earnings, often referred to as tier one or core capital The primary source of shareholders' equity is the initial capital invested, while retained earnings accumulate over time through the bank's operations Minority interest is excluded in this calculation because banks often invest in other institutions, and minority interest represents ownership stakes in those entities The benefits derived from these investments include dividends and net assets attributable to shareholders' equity.
Capitalization refers to the total market value of a bank's shares on the stock exchange, known as market capitalization The capitalization ratio assesses the debt component within the bank's capital structure, providing crucial insights into the bank's leverage usage.
This study examines the tier one capital ratio, which measures the relationship between a bank's core capital and its total risk-weighted assets, categorizing banks into five levels of capital adequacy: well-capitalized, adequately capitalized, undercapitalized, significantly undercapitalized, and critically undercapitalized Kishan and Opiela (2000) highlight the significance of bank core capital, noting its impact on external ratings and investor perceptions of creditworthiness Additionally, low-capitalized banks face higher costs when raising funds through non-reservable sources, such as bonds or certificates of deposit, and are viewed as riskier by the market Van den Heuvel (2001) points out that these banks may forgo lending opportunities to mitigate the risk of capital inadequacy, even when their capital exceeds regulatory requirements, suggesting that bank capitalization significantly influences the responsiveness of loan supply to economic fluctuations.
The term deposit variable encompasses all types of term deposits and savings accounts, characterized by a fixed duration at the bank These deposits are regarded as highly secure for investors and provide stability for banks Investors typically receive higher interest rates compared to demand deposits However, due to insufficient data, the term deposit variable does not differentiate between various terms of deposits, which may limit its ability to reflect the specific impacts of each term on the bank loan supply.
The Vietnamese interbank deposit offer rate represents the interest charged on short-term loans between banks within the country's wholesale money market Essentially, this rate reflects the cost of interbank borrowing for financial institutions in Vietnam.
The data for the variables in equation (21) is derived from the balance sheet statements of 20 selected banks, all of which are public and audited However, there are gaps in the three-month interbank deposit offer rate data: for 2008, information is missing from the start of the year until July 1, and for 2009, from the beginning of the year until May 18 Additionally, data is absent from April 4, 2010, until the end of that year Despite these missing data points, the fluctuations in the interbank rate during these years are minimal and do not significantly impact the average figures calculated for the year.
This section outlines the empirical model used to address the research questions from the first chapter, focusing on the differing responses of strong and weak banks to changes in monetary policy The study tests hypotheses based on the representative bank model established by J Peek and E S Rosengren (1995), further explored by Kashyap and Stein (1995), and adapted by Kishan and Opiela (2000) The theory posits that well-capitalized and liquid banks exhibit less sensitivity to monetary policy changes; however, the overall impact of bank asset size on loan supply remains uncertain It is important to recognize that banks vary significantly in their characteristics, which in turn influence their business operations.
The study utilizes a dynamic panel data model to analyze the time-varying effects of explanatory variables on bank loan supply This model includes a lagged dependent variable alongside a single regressor, X, to capture the dynamic relationships at play.
In dynamic panel models, the fixed effect 𝜇 𝑖 is combined with a vector of exogenous regressors 𝑋 𝑖𝑡, while the random disturbance 𝜀 𝑖𝑡 follows a normal distribution, N(0, 𝜎 𝜀 2) Key assumptions for these models include stationarity, absence of serial correlation, and homoskedasticity Anderson and Hsiao (1982) emphasized that random effects estimation is inappropriate for dynamic panel data due to the condition E[𝑌 𝑖,𝑡−1 𝜇 𝑖 ] ≠ 0.
Moreover, the fixed effects estimation is also biased in dynamic panel model.Nickell
Analytical framework
Rely on theory and empirical studies, analytical framework are conducted below:
This study develops a framework based on theoretical and empirical literature to analyze the interactions among key variables in banking In the context of banking, assets and liabilities are the two primary components, with term deposits and interbank borrowing reflecting loan demand dynamics, as noted by Kashyap and Stein (1995) and Kishan and Opiela (2000) The asset size, liquidity, and capitalization of banks signify their strength and ability to adapt to changing business environments Furthermore, the study examines how shifts in monetary policy influence the supply of bank loans, highlighting the varying states of bank liabilities and assets.
Therefore, they eventually react in different level to the change in monetary policy
Changes in monetary policy trigger chain reactions that impact the supply of bank loans While the alteration in policy does not directly influence lending, it sets off a series of events that ultimately affect the availability of credit in the economy.
The changes in bank supply across different banks will vary based on their unique characteristics, leading to distinct reactions in their balance sheets This topic will be explored further with empirical results in the following chapter.
FINDINGS
Data analysis discussion
Data analytics involves examining raw data to draw meaningful conclusions This section discusses key aspects of empirical studies, including data distribution, sources, and the relationships among independent variables in the empirical model It highlights the presence of collinearity among independent variables and their cross-term variables, such as Ln ASSET, Ln LIQUIDITY, and Ln KA This collinearity occurs because the independent variables include themselves in the cross-terms, leading to correlation due to model specification Additionally, the analysis utilizes the cross-term of interbank interest rates and bank characteristics to assess how these characteristics influence the effects of monetary policy changes on bank loan supply.
Econometric results
In scientific research, regression models are utilized to analyze the relationship between a dependent variable and various explanatory variables, with the dependent variable being associated with the effects of these variables Each explanatory variable contributes additional insights into the dependent variable (lnLOANit) The inclusion of interaction terms enhances the understanding of relationships among the variables and facilitates the testing of multiple hypotheses Specifically, these interaction terms allow for the examination of how changes in the interbank rate impact loan supply differently based on distinct bank characteristics A significant interaction suggests that the influence of one predictor variable on the response variable varies at different levels of another predictor variable The empirical regression results from the GMM estimation process are detailed in Table 5.2.
Table 5.2: The empirical regression results of GMM estimation
Prob> chi2 = 0.0000 Source: Author’s calculation
The analysis identifies six key single variables and four cross-terms that account for the variation in bank loan supply during the observed periods The theoretical and empirical literature indicates that the average banks' response to monetary shocks is represented by the coefficient β j of the sum of changes in interest rates (∆ln it−j) Additionally, the cross-terms involving lagged assets, liquidity, and capital adequacy highlight differing responses to monetary policy between weak and strong banks Consistent with theoretical expectations, the results show a negative coefficient for the sum of changes in interest rates, while the cross-terms exhibit positive coefficients.
Incorporating an interaction term into a model significantly alters the interpretation of the coefficients Without interaction terms, the coefficient β j of ∑ 1 j=0 ∆ln i t−j reflects the distinct impact of changes in the interbank offered rate on the supply of bank loans Specifically, the coefficient β 0 = -1.5681 indicates that a 1% increase in the growth rate of the interbank rate leads to a -1.5681% decrease in the growth rate of bank loan supply Similarly, the coefficient β 1 = -2.3899 signifies that a 1% change in the growth rate of the interbank rate from the previous period (t-1) results in a -2.3899% change in the growth rate of bank loan supply.
The impact of changes in the interbank offered rate on bank loan supply varies based on factors such as asset values, capitalization, and liquidity levels of banks Consequently, the effect of the interbank offered rate is influenced not only by the coefficient β j but
A 1% change in the interbank growth rate results in a -1.067% change in the growth rate of loans, indicating a negative relationship Specifically, the growth rate of the interbank rate impacts loan growth at -1.5681 However, the interaction terms involving bank characteristics, such as the lagged asset and capital growth rates, demonstrate a positive influence on loan supply growth when combined with monetary policy These interaction terms mitigate the adverse effects of interbank rate changes on loan supply growth The study highlights the concept of net effect, showing that the negative impact of interbank rate fluctuations on loan supply growth is lessened through the interaction with monetary policy This interpretation also applies to the lagged growth rate of the interbank rate.
The analysis reveals that a 1% change in the growth rate of the interbank rate from the previous period leads to a net decrease of 2.0877% in the growth rate of bank loan supply This response to monetary shocks varies among banks, with stronger institutions—characterized by larger asset sizes, better capitalization, and superior liquidity—experiencing a reduced negative impact due to supplementary cross-term effects For instance, when a central bank tightens monetary policy by raising interest rates to control money supply, bank loans inevitably decline due to increased loan interest rates and funding costs Although loan demand decreases, it does not vanish entirely, creating a competitive landscape where banks that can effectively mobilize funds to meet remaining loan demand will prevail In this scenario, larger, reputable banks are better positioned to attract high-cost funds and satisfy loan demand, highlighting that while both large and small banks are influenced by interest rate changes, the extent of the impact differs based on their individual characteristics.
The stronger the banks are, the less the magnitude the effect
The study reveals that bank asset size and capitalization significantly influence loan supply, with a 1% change in asset size resulting in a 0.0551% increase in loan supply, and a 1% change in capitalization leading to a 0.1574% increase Larger banks with substantial assets and higher capitalization are better positioned to offer more loans, as they typically possess extensive fixed assets, long-term investments, and diversified loan portfolios Strong banks experience lower costs and risks, enabling them to meet obligations and manage credit and operational risks more effectively than smaller banks Consequently, these banks are more capable of mobilizing capital and fulfilling loan demands, particularly during challenging economic periods.
The impact of term deposits on bank loan supply is significant Specifically, a 1% increase in current term deposits (π0) leads to a 0.5711% rise in loans, while a 1% increase in previous term deposits (π1) results in a 0.3573% increase in loans This highlights that term deposits are a crucial source of funding for banks.
The more the input source the more the loan that bank can generate and yeild profit
The intercept 𝛼 𝑖 = -0.5701 indicates that when all predictors in the regression model are zero, the response value is -0.5701 While the intercept is often seen as insignificant, it is essential to include it in the regression analysis This constant term accounts for any bias not captured by the predictors and ensures that the model's residuals average to zero.
The regression result of variables 𝑙𝑛 𝑖 𝑖𝑡 ; 𝑙𝑛 𝑖 𝑖𝑡−1 ; 𝑙𝑛 𝑖 𝑖𝑡 *𝐿𝑛 𝐴𝑆𝑆𝐸𝑇 𝑖𝑡−1 ;
𝐿𝑛 𝐴𝑆𝑆𝐸𝑇 𝑖𝑡−1 ; 𝐿𝑛 𝐾𝐴 𝑖𝑡−1 ; 𝑙𝑛 𝑇𝐸𝑅𝑀 𝐷𝐸𝑃𝑂𝑆𝐼𝑇 𝑖𝑡 ; and 𝑙𝑛 𝑇𝐸𝑅𝑀 𝐷𝐸𝑃𝑂𝑆𝐼𝑇 𝑖𝑡−1 are consistently link to the theoretical and empirical literature review in chapter two
Beside the significant variables which discus above, there are six others insignificant variables They are 𝑙𝑛 𝐿𝑂𝐴𝑁 𝑖𝑡−1 ; 𝑙𝑛 𝑖 𝑖𝑡 *𝑙𝑛 𝐿𝐼𝑄𝑈𝐼𝐷𝐼𝑇𝑌 𝑖𝑡−1 ; 𝑙𝑛 𝑖 𝑖𝑡−1 *𝑙𝑛 𝐾𝐴 𝑖𝑡−1 ;
In the model, the change in the lagged loan variable (𝑙𝑛 𝐿𝑂𝐴𝑁 𝑖𝑡−1) does not influence the current loan supply (𝑙𝑛 𝐿𝑂𝐴𝑁 𝑖𝑡), indicating a lack of relationship between the current loan levels and their previous values This suggests that the lagged loan variable operates independently and does not affect the present loan supply dynamics These findings contrast sharply with real-world expectations, highlighting the need for further empirical research to better understand and explain this unexpected result.
The insignificance of the variable \( \ln \text{LIQUIDITY}_{it-1} \) suggests that changes in a bank's liquidity ratio do not influence its loan supply Additionally, the lack of significance in the cross-term \( \rho \ln i_{it} * \ln \text{LIQUIDITY}_{it-1} \) indicates that liquidity does not affect how monetary shocks impact bank loan supply A similar interpretation applies to the cross-term \( \rho \ln i_{it-1} * \ln K_{it-1} \) Furthermore, the insignificance of the variable
Interbank borrowing is primarily utilized by banks to address short-term liquidity shortages rather than to finance loans Typically, these borrowing periods range from overnight to several weeks or up to three months Banks do not rely on interbank borrowing as a means to increase their overall loan levels.
In summary, empirical findings indicate that fluctuations in the interbank offered rate negatively impact the supply of bank loans across all banks However, this effect is less pronounced for larger banks with substantial assets and strong capitalization compared to smaller, undercapitalized banks.
The findings highlight the crucial role of term deposits as a key source of capital for banks, enabling them to gather funds from the economy and generate profits by lending these resources back to the market.
CONCLUSION
Summarize of methodology
This study utilizes the Generalized Methods of Moments (GMM) approach for dynamic panel data analysis, originally proposed by Anderson and Hsiao in 1982 and later refined by Arellano and Bond in 1991, as well as Blundell and Bond in 1998, employing twice lagged levels of loans as instruments The regression analysis is conducted using bank balance sheet data from 20 Vietnamese commercial banks over the period from 2008 to 2012.
Summarize of major findings
This study examines the influence of changes in the interbank offered rate on bank loan supply The research aims to achieve three key objectives: first, to analyze how variations in the interbank deposit offer rate affect the availability of bank loans; second, to investigate the effects of bank asset size, capitalization, and liquidity on loan supply; and third, to evaluate how these factors modulate the impact of monetary shocks on the provision of bank loans.
The impact of changing market interest rates on bank loan supply is generally negative for all banks, but the extent of this impact varies based on individual bank characteristics Empirical studies indicate that small and undercapitalized banks are more sensitive to shifts in monetary policy compared to stronger, well-established banks These smaller institutions face greater challenges in raising funds within the economy, making their loan supply more vulnerable during periods of tightening monetary policy.
Liquid banks can utilize their liquid assets to protect their loan portfolios and sustain loan levels, resulting in reduced sensitivity of loan supply to fluctuations in market rates Studies by Kashyap and Stein (2000), Alfaro et al (2003), Gambacorta and Mistrulli (2004), Gómez-Gonzalez and Grosz (2007), and Ezema (2009) support this notion Additionally, banks with a higher capital-to-asset ratio are perceived as less risky, while banks with lower capitalization face higher costs in accessing external financing compared to their well-capitalized counterparts, as highlighted by Bernanke and Gertler (1995), Kishan and Opiela (2000), Altunbaş et al (2002), and Van den Heuvel (2002).
Westerlund (2003); Alfaro et al (2003); Gambacorta and Mistrulli (2004); Bichsel and Perrez (2005); Golodniuk (2006); Gómez-Gonzalez and Grosz (2007) and Gambacorta and Marques‐Ibanez (2011))
After running the regression, for the case of Vietnam, this study finds out:
(i) Change in Vietnam interbank offered rate has negative effect on the supply of bank loan
The asset size and capitalization of a bank have a significantly positive impact on the availability of bank loans, while the bank's liquidity position does not influence loan supply.
The supply of bank loans is influenced not only by interbank rates but also by the interplay between these rates and specific bank characteristics Notably, the capitalization state of the bank mitigates the negative effects of market rates on loan supply.
The study reveals that term deposits have a significantly positive impact on bank loan supply, indicating that a one percentage point increase in term deposits can lead to an almost sixty percentage point increase in loan supply This highlights that term deposits are the most crucial source of financing for bank loans.
Policy implications
Research indicates that bank characteristics mitigate the effect of market rate changes on bank loan supply during periods of tightening monetary policy Larger, more liquid, and well-capitalized banks demonstrate greater resilience to monetary shocks, in contrast to their smaller counterparts.
The research highlights the relationship between bank characteristics and their responses to monetary policy changes implemented by the State Bank of Vietnam Overall, the banking system experiences a contraction in loan supply when the State Bank enacts a tightening monetary policy However, the impact varies significantly among banks, with smaller, illiquid, and under-capitalized institutions being the most severely affected.
Policymakers must recognize the effectiveness and objectives of financial policies, as strict tightening measures could threaten the survival of smaller banks, potentially leading to an interest rate war The State Bank of Vietnam and the government need to be acutely aware of market imperfections and the necessity of establishing sustainable financial intermediaries Recent bank bankruptcies and mergers highlight the need for stricter regulations and better management within the financial market Weak financial intermediaries not only undermine market conditions but also disrupt the central bank's monetary policy mechanisms.
Shortcomings of the study
This study has several limitations, primarily stemming from a restricted dataset comprising only 20 commercial banks over a five-year period It evaluates the overall impact of bank characteristics on loan supply without breaking down the data into specific subsections, which would provide a more detailed understanding of each sector's relationship with banks Additionally, the limited data constrains the model's ability to analyze the relationship between loan supply and other variables across multiple lagged periods Consequently, these factors may lead to an underestimation of the overall effects of monetary policy on bank loan supply due to the inherent lag in monetary policy's impact on the economy.
Suggestions for further study
The identified limitations present opportunities for future research It is recommended that subsequent studies categorize the bank loan portfolio into sub-sections, such as consumer loans and enterprise loans, while also classifying banks based on their asset size, liquidity, and capitalization status This approach, as suggested by Kashyap and Stein (1995), Kishan and Opiela (2000), Altunbaş et al (2002), and Golodniuk (2006), will facilitate a deeper investigation into how monetary shocks affect the responses of various banks within the financial system.
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Table A.1: The base rate of VND in the year 2008
Base rate (VND) per annual Decision No Effective date
Source: State bank of Vietnam, 2013
Table A.2: The base rate of VND in the year 2009
Base rate (VND) per annual Decision No Effective date
Source: State bank of Vietnam,2013
Table A.3: The base rate of VND in the year 2010
Base rate (VND) per annual Decision No Effective date
Source: State bank of Vietnam,2013
Table A.4: The required reserve rate of VND in the year 2008
(VND) Decision No Effective date
11% 1 - 5% 2 187/QĐ-NHNN dated16/01/2008 02/01/2008 8% 1 - 3% 2 2811/QĐ-NHNN dated 20/11/2008 12/01/2008 6% 1 - 3% 2 2951/QĐ -NHNN dated 03/12/2008 12/05/2008 10% 1 - 3% 2 2560/QĐ-NHNN dated 3/11/2008 05/11/2008
(1) for term under 12 months (2) for term over 12 months Source: State bank of Vietnam,2013
Table A.5: The required reserve rate of VND in the year 2009
Required reserve (VND) Decision No Effective date
(1) for term under 12 months (2) for term over 12 months Source: State bank of Vietnam,2013
Table A.6: The required reserve rate of VND in the year 2010
Required reserve (VND) Decision No Effective date 4% 1 - 3% 2 74/QĐ-NHNN dated 18/01/2010 01/02/2010
(1) for term under 12 months (2) for term over 12 months Source: State bank of Vietnam, 2013
Table A.7: The required reserve rate of VND in the year 2011
Required reserve (VND) Decision No Effective date 3% 1 - 4% 2 750/QĐ-NHNN dated 9/04/2011 01/05/2011 3% 1 - 5% 2 1209/QĐ-NHNN dated 1/06/2011 01/06/2011
(1) for term under 12 months (2) for term over 12 months Source: State bank of Vietnam,2013
Table A.8: List of commercial banks
No Local Name English Name
2 Agribank Vietnam Bank For Agriculture And Rural Development
3 An Binh Bank An Binh Commercial Joint Stock Bank
4 BIDV Bank For Investment And Development Of Vietnam
5 Dai A Bank Great Asia Commercial Joint Stock Bank
6 EAB Eastern Asia Commercial Joint Stock Bank
7 Eximbank Viet Nam Export – Import Commercial Joint Stock Bank
8 HD Bank Housing Development Commercial Joint Stock Bank
9 Maritime Bank Maritime Commercial Joint Stock Bank
10 MB Bank Military Commercial Joint Stock Bank
11 MHB Housing Bank Of Mekong Delta
12 Nam A Bank Southeast Asia Commercial Joint Stock Bank
13 Sacombank SaiGonThuong Tin Commercial Joint-Stock Bank
14 SHB Saigon-Hanoi Commercial Joint Stock Bank
15 Southern Bank Southern Commercial Joint Stock Bank
16 Techcombank Viet Nam Technological And Commercial Joint Stock Bank
17 VIB Vietnam International Commercial Joint Stock Bank
18 Vietcombank Joint Stock Commercial Bank For Foreign Trade Of Vietnam
19 Vietinbank Vietnam Bank For Industry And Trade
20 VP Bank Vietnam Prosperity Commercial Joint-Stock Bank
Note:All variable is in logarithm form and dis denoted for first-difference
Table A.10: The empirical regression results of GMM estimation
Number of obs = 48 Wald chi2 (16) = 237.55 Prob> chi2 = 0.0000 R-squared = 0.7863
GMM weight matrix: Robust Root MSE = 0.0826
Table A.10: The empirical regression results of GMM estimation (continued)
Table A 11: Wooldridge test for autocorrelation in panel data
Table A 12 : White’s test for Heteroskedasticity in panel data
Table A 13 : Test the relevance of instrumentvarible
Prob > F = 0.3580 F( 1, 11) = 0.920 H0: no first-order autocorrelation Wooldridge test for autocorrelation in panel data
Total 60.76 64 0.5917 Kurtosis 1.69 1 0.1940 Skewness 11.07 16 0.8049 Heteroskedasticity 48.00 47 0.4321 Source chi2 df p
Cameron & Trivedi's decomposition of IM-test
Prob > chi2 = 0.4321 chi2(47) = 48.00 against Ha: unrestricted heteroskedasticity White's test for Ho: homoskedasticity
Ho: variables are exogenous Test of endogeneity (orthogonality conditions)
USA, disaggregate quarterly data on bank balance sheet from 1976Q1 to 1992Q2
The six-variable prediction equation in
Classifying banks by asset size and using the Federal reserve funds rate as the monetary policy instrument
Tightening monetary policy declines deposit for all size categories
An increase in the Federal reserve funds rate has a negative and statistically significant effect on the growth rate of total loans
Small banks are more sensitive to change in monetary policy
USA, disaggregate quarterly data on bank balance sheet from 1976Q1 to 1993Q2
The Two-Step regression approach
The impact of tightening monetary policy on a bank’s lending activity is stronger for less liquid banks
USA, disaggregate quarterly data on bank balance sheet from 1980Q1 to 1995Q4
The OLS regression approach Segregating banks by asset size and capital leverage ratio
Loans of small and undercapitalized banks are the most responsive to monetary policy
Euro, disaggregate yearly data on bank balance sheet from
The six-variable prediction equation in
Classifying banks by asset size and capital
Undercapitalized banks no matter what size they are tend to react more to policy change
Sweden, disaggregate monthly data on bank balance sheet from 1998:M1 to 2003:M6
Autoregressive distributed lag (ARDL) approach
Small, undercapitalized bank are sensitive and strongly react to monetary policy change
Chile, disaggregate yearly data on bank balance sheet during the period
Autoregressive distributed lag (ARDL) approach
Small, illiquid, and less capitalized banks have to compress their loan supply during the period of monetary policy shock
Italy, disaggregate quarterly data on bank balance sheet during the period1992Q3 to 2001Q3
The GMM approach Well-capitalized banks can better shield their lending from monetary policy shocks Small and illiquid banks tend to react more toward monetary shock
Switzerland, disaggregate quarterly data on bank balance sheet from the period 1996Q1 to 2003Q1
The Two-Step Regression Approach
Better-capitalized banks are relatively immune to changes in the monetary policy stance
Ukraine, disaggregate yearly data on bank balance sheet during the period of 1998 to 2003
Segregating banks by theirs asset size, capitalization, and liquidity
Undercapitalized bank face serious problem to maintain the loan supply level in tightening monetary policy period
Disaggregate monthly data on bank balance sheet during the period of 2003M8 to 2005M11 for Argentina and 1995M1 to 2005M9 for Colombia
The six-variable prediction equation in
For both case of Argentina and Columbia:
Better-capitalized and liquid banks reduce the effect of tightening monetary policy on the supply of bank loan
France, Germany, Greece, Japan, UK and USA
Disaggregate yearly data on bank balance sheet during the period of 1996 to 2003
The six-variable prediction equation in
Only japan and Greece present the existence of bank lending channel
There is weak bank lending channel in France
Germany, US and UK do not have ban k lending channel
Disaggregate quarterly data on bank balance sheet during the period of 1999Q1 to 2008Q4
The GMM approach The tightening monetary policy affects more on small and illiquid banks.