INTRODUCTION
RELEVANCE AND BACKGROUND OF STUDY
Since the financial reforms in Vietnam during the early 1990s, the restructuring of state-owned commercial banks (SOCBs) and the establishment of joint-stock banks (JSBs) have significantly transformed the financial system By 2004, the monetization of the economy had surged, with the M2 to GDP ratio exceeding 70%, compared to just 25% in the mid-1990s SOCBs accounted for 73% of total credit in 2004, highlighting their dominant role in the credit market The financial system has become increasingly segmented, with JSBs and smaller banks primarily serving the private sector, while SOCBs have continued to provide loans to both the private and public sectors equally (Camen, 2006).
Vietnam's entry into the World Trade Organization (WTO) has led to a significant increase in foreign direct investment and portfolio inflows, marking a crucial step in its globalization journey However, this rapid economic growth has brought challenges, particularly an unfavorable balance of payments Since 2000, Vietnam's financial sector has experienced explosive growth, especially during the 2007-2008 period, with credit market expansion reaching approximately 50% in January 2008, contributing to a rise in inflation that peaked at 14% By March 2011, inflation had accelerated to 13.89%, the highest in 25 months, while the trade deficit widened to $1.15 billion, up from $1.11 billion in February.
PROBLEM STATEMENT
Economic models often simplify the relationship between financial conditions and economic changes by focusing on a limited set of financial variables, such as short-term risk-free interest rates and long-term government bond rates (Hall, 2001).
As financial systems have advanced significantly in recent years, their influence on the economy has become more extensive and profound This complexity makes it challenging to identify the underlying issues in a developed economy, as certain variables may not be readily apparent A notable example is the 2008 global financial crisis, which originated from the credit sector, specifically the mortgage asset crisis in the U.S., and was exacerbated by the influx of capital into the Vietnamese securities market due to prior years of loose monetary policy.
Historically, economists like Pintinkin, Gurley, and Shaw highlighted the crucial role of financial intermediaries and credit markets in the economy Modigliani and Papademos (1977) acknowledged that traditional monetary theory overlooked the significant functions of these intermediaries and bank credit Research by Gurley and Shaw (1956) indicated that financial intermediaries have a greater impact on credit supply than on money supply Consequently, the credit channel emerges as a vital factor that directly influences policymakers' decisions.
Understanding the role of the credit channel in the financial market is vital for policymakers, as it plays a key role in the transmission of monetary policy Identifying how the credit channel operates within this framework is essential for improving current policies, ultimately contributing to the achievement of national economic objectives.
This study aims to identify the role of credit channel in Vietnam’s monetary transmission mechanism, specify 1996-2010 period Following the main objective, the thesis:
- To analyze whether past value of credit helps predict the money supply;
- To examine the impact of credit shocks on money supply, also other macro economies;
- To test whether credit shock plays important role in forecasting the error of money supply.
RESEARCH QUESTION
To obtain the above objectives, this thesis will attempt to answer the following questions:
What is the role of credit channel in the monetary policy transmission in Vietnam case over the period 1996-2010?
- Does the past value of credit help predict money supply?
- How does money supply reaction to credit shock?
- Whether credit shocks plays important role in forecasting money supply’s error?
To carry out above objectives, this study uses quarterly data from 1996:Q1 to 2010: Q3 Econometric techniques and descriptive statistic will be employed as primary quantitative in this research
This article presents a descriptive statistical analysis of the variables utilized in the thesis, including their distribution, variation, and central tendency, allowing for an initial evaluation of data quality To address key questions using econometric techniques for time series data, vector autoregression (VAR) will be employed A unit root test will first assess the stationarity of all variables, ensuring the validity of subsequent t-tests and F-tests Optimal lag lengths for the VAR model will be determined using various criteria to establish the most effective model The Granger causality test will investigate whether past credit values can predict money supply, while impulse responses and variance decompositions will provide insights into the remaining sub-questions Ultimately, these empirical findings will elucidate the role of the credit channel in monetary transmission within the context of Vietnam.
STRUCTURE OF THESIS
The study is organized as following:
Chapter 1 introduces the importance of thesis, relevance and back ground of study, the objectives and research questions And the methodology is presented as briefly in this part
Chapter 2 demonstrates the literature review Firstly, credit channel theory is mentioned as a core of study Secondly, empirical studies about the role of credit channel in monetary policy transmission are presented In addition, the chapter gives overview the Vietnam’s monetary policy framework, in which focuses on the credit market
Chapter 3 presents analytical framework, then develop the model which helps us answer key question Finally, data description as well as steps of economic techniques will be mentioned in this chapter
Chapter 4 shows the empirical results and discussion Finally, results comparison is also presented in this part
Chapter 5 give conclusion, suggests some practical policy implications, and discusses the limitations and direction for further studies.
LITERATURE REVIEW
CREDIT CHANNEL THEORY
Credit channel theory revolves around the concept of an external finance premium, which often arises from the principal-agent problem between lenders and borrowers Bernanke and Gertler (1995) explored this theory in depth, identifying two key linkages: the bank lending channel and the balance-sheet channel This thesis will focus on these two linkages that are pertinent to the credit channel theory.
The bank lending channel: concentrates the variability of loan supply through deposit institutions caused by the effect of monetary policy actions
Banks play a crucial role as primary information sources in the economy, effectively addressing issues of asymmetric information and other distortions in credit markets This is particularly significant for borrowers, especially small and medium-sized enterprises, who heavily rely on bank credit As long as this function persists, the impact of bank lending on the transmission of monetary policy remains vital.
When the government implements expansionary monetary policy, it increases bank deposits and reserves, which in turn boosts the availability of bank loans This increase in loans fosters higher investment levels, ultimately resulting in greater output.
Tightening monetary policy results in a reduction of bank reserves and customer deposits, which in turn decreases the availability of bank loans This leads to a decline in investment spending and a subsequent decrease in overall output.
Another side of credit view, when we mention to the impact of monetary policy to enterprises, small firms suffer bad effects on expenditure than large firms (Mishkin,
Small companies often rely heavily on bank loans for their financing needs, while larger corporations have the advantage of accessing significant capital through stock and bond markets, reducing their dependence on traditional bank channels.
Balance sheet channels: focuses influence of monetary policy changing on borrower’s balance sheets and income statement
Changes in a company's worth due to fluctuations in monetary policy can exacerbate adverse selection and moral hazard issues when lending to businesses Borrowers with lower collateral face a higher risk of moral hazard, especially if they seek loans Companies with declining equity are more likely to pursue risky projects, increasing the likelihood of loan defaults, which can lead to bank failures and a reduction in lending and investment In response to declining net worth, banks often require borrowers to provide more collateral, further intensifying adverse selection problems and constraining available funds for investment.
Here is several ways which monetary policy acts upon on firm’s balance sheet:
Expansionary monetary policy has led to an increase in equity stakes, while also mitigating issues related to adverse selection and moral hazard Consequently, this results in a higher firm valuation and greater access to capital for investments, ultimately boosting aggregate demand.
Lower interest rates resulting from expansionary monetary policy can lead to a reformation of a firm's balance sheet due to improved cash flow This can mitigate issues of adverse selection and moral hazard, ultimately increasing the availability of capital for loans, fostering growth in investment spending, and contributing to an overall rise in aggregate output.
Monetary expansion leads to an unexpected increase in price levels, enhancing companies' net worth while reducing issues related to adverse selection and moral hazard This process stimulates higher investment spending and boosts overall aggregate output.
Contractionary monetary policy leads to a decrease in equity prices and cash flow, resulting in a lower net worth for businesses This decline exacerbates issues related to adverse selection and moral hazard, ultimately reducing financing for both investment and consumption.
MONETARY POLICY FRAMEWORK OF VIETNAM
The State Bank of Vietnam (SBV), as established by the "Law on the State Bank of Vietnam," serves as the central bank of the Socialist Republic of Vietnam and operates under the supervision of the National Assembly and government The government is tasked with formulating plans that include annual inflation projections and determining liquidity levels to be injected into the economy Furthermore, the government must report on the implementation of monetary policy to the National Assembly The SBV's responsibilities encompass executing the government's monetary policy, managing state monetary and banking activities, and functioning as the currency issuer, the bank for credit institutions, and the government's bank These activities aim to stabilize currency value, preserve banking operations, and align with the country's socialist economic growth objectives.
According to SBV Law, the State Bank of Vietnam (SBV) functions as a governmental entity, with the National Assembly significantly influencing monetary policy decisions The strong intervention by both the government and the National Assembly in monetary policy implementation highlights the limited independence of the SBV's operational instruments (Camen, 2006).
2.2.2 MONETARY POLICY STRATEGY AND INSTRUMENTS
Vietnam's monetary policy strategy is derived from its five-year Social and Economic Development Plan, with the government responsible for creating an actionable implementation plan This plan includes specific targets for liquidity injection into the economy, as well as key metrics such as M2, credit, and deposit levels, which are essential components of the government's strategy (Camen, 2006).
The State Bank of Vietnam (SBV) sets annual targets for total liquidity and credit in the economy based on macroeconomic and monetary objectives Each year, the SBV prepares a report detailing the implementation of monetary policy and the outlook for the following year, which is then submitted to the government for consideration and approval After review, the government presents this report to the National Assembly for final approval, following consultations with the National Monetary Policy Advisory Board.
Regarding to monetary instruments, a number of indirect tools have been introduced include reserve requirement, refinancing, discount financing facilities, open market operation and foreign exchange interventions
SBV has applied reserve requirement in various forms since 1990s This instrument proves its important role on money market regulating in past Currently, required
The National Monetary Policy Advisory Board (NMPAD) comprises key figures such as the Governor of the State Bank and the Minister of Finance, along with various experts Bank reserves are categorized based on deposit maturity, sectoral focus, and the currency type (domestic or foreign) Short-term deposits, typically under one year, attract higher rates compared to long-term deposits, and banks receive interest subsidies when extending credit to the agricultural sector or the People Credit’s Fund (Camen, 2006).
In 2008, the reserve requirement served as a crucial tool to manage inflation amid significant domestic and international economic fluctuations, with the State Bank of Vietnam (SBV) increasing the reserve requirement ratio by 1 percentage point for both local and foreign currency deposits in February To combat potential economic downturns, the SBV subsequently lowered the required reserve for VND deposits under 12 months twice in 2009, reducing it from 6% to 5% and then to 3%, while the Vietnam Bank for Agriculture and Development further decreased its rate from 3% to 2% and then to 1%.
In 2010, the State Bank of Vietnam (SBV) maintained a low reserve requirement ratio of 3% for VND deposits under 12 months and 1% for those exceeding 12 months Additionally, the SBV reduced the reserve ratio for foreign currency to support credit institutions in boosting their foreign currency funding.
Since July 2000, the State Bank has utilized Open Market Operations (OMOs) as a crucial monetary tool for controlling liquidity, proving its significance over the years These operations have been managed flexibly alongside other monetary policy instruments, contributing to the stabilization of the money market In 2008, the State Bank issued compulsory bills with higher base interest rates, notably increasing the 182-day and 364-day bills to 7.5% and 7.75% respectively to combat inflation during the first seven months In the first half of 2009, the State Bank also offered to purchase short-term securities with a 14-day maturity, providing essential capital to credit institutions and supporting economic stimulus programs.
In 2009, the State Bank of Vietnam (SBV) attempted to take action but faced challenges due to low demand for funds and an abundance of financial resources at that time To support credit institutions during the first nine months of 2010, the SBV conducted open market operations (OMOs) by purchasing valuable papers However, by the end of the third month of 2010, rising inflation pressures led to increased interest rates for these papers.
The State Bank of Vietnam (SBV) employs refinancing and rediscount facilities as part of its discount policy, with both rates serving distinct purposes The rediscount rate, determined by the SBV, is based on collateralized valuable papers like drafts and bonds, while the refinancing rate is linked to loans from commercial banks that use these loans as collateral Typically, the refinancing rate is higher than the rediscount rate In 2010, the SBV utilized the refinancing rate to enhance short-term lending and liquidity for credit institutions, primarily offering 1 to 2-month refinancing to support economic liquidity Additionally, towards the end of 2010, the SBV implemented refinancing measures to address the increased demand for deposit withdrawals from businesses and individuals during the Lunar New Year.
Historically, Vietnam's financial system was primarily served by the State Bank of Vietnam (SBV) and two state-owned commercial banks (SOCBs) In 1988, following the Doi Moi reforms, the SBV was established as an independent central bank focused on monetary policy and financial supervision The next phase of financial reform saw the introduction of joint-stock commercial banks and foreign banks in 1991 and 1992, respectively In 2000, the Development Assistance Fund was created to support financial policy objectives Historically, Vietnam's financial market has been closely linked to non-commercial lending, with a significant emphasis on the agriculture sector, as highlighted in a World Bank report from 2006.
According to a 2006 World Bank report, Vietnam's banking sector experienced rapid growth primarily through lending to the private sector, with State-Owned Commercial Banks (SOCBs) maintaining a dominant role in providing credit to the economy However, despite ongoing sector reforms, the banking industry continues to face financial weaknesses, necessitating further reinforcement to improve stability and enhance lending capacity.
Table 2.1: One decade and Vietnam’s credit
Credit to Economy (growth rate) 23% 25% 32% 39% 35% 23% 50% 28% 45% 32%
Source: Calculated from IMF-IFS and GSO data
In the banking sector credit, credit to the economy rose from VND 155 trillion in 2000
Vietnam's credit growth surged dramatically, escalating from 35 percent of GDP to VND 2,690 trillion, or 136 percent of GDP, by 2010, reflecting a seventeen-fold increase in just a decade Notably, this rapid credit expansion, particularly a staggering 50 percent growth since late 2007, can be attributed to significant capital inflows and the emergence of real estate price bubbles serving as collateral for loans (Vietnam Plus News, 2009).
Vietnam’s credit growth 2011 and orientation in 2012
In 2022, Vietnam's banking system experienced a modest loan growth of 10.9 percent, marking the lowest credit growth rate in a decade, significantly below the targeted range of 15-17 percent set for the year Additionally, deposit growth reached 8.89 percent, while the money supply expanded by an estimated 9.27 percent, according to the latest monthly report from the State Bank of Vietnam (SBV).
Vietnam aims for a credit growth of 15-17 percent and a 14-16 percent increase in the money supply this year, with the Central Bank implementing monetary policy to achieve these targets Governor Nguyen Van Binh indicated that lending growth might remain below 15 percent The State Bank of Vietnam (SBV) is prioritizing the development of agriculture, rural sectors, export goods production, auxiliary industries, and support for small and medium-sized enterprises Agribank, the country's largest lender by assets, continues to dominate fund disbursement, allocating 75-89 percent of its loans to agriculture and rural development Additionally, the SBV has set annual credit growth targets for domestic banks, categorizing them into four groups with maximum loan growth rates of 17 percent, 15 percent, 8 percent, and zero percent.
EMPIRICAL LITERATURE
Recent empirical studies have increasingly focused on the role of credit in monetary policy transmission, beginning with Bernanke and Blinder's influential 1988 paper, “Credit, Money and Aggregate Demand.” They utilized the IS/LM model to analyze the variance of money demand shocks and introduced the CC (commodities and credit) curve, resembling the IS/LM curve, to examine the credit channel's impact via bank lending during economic shocks Their analysis of two sub-samples (1974:1-1979:3 and 1979:4-1985:4) revealed that the variance of money-demand shocks was significantly smaller than that of credit-demand shocks in the first period, while credit demand became more crucial in the 1980s.
The role of the credit channel in monetary transmission has been a topic of discussion since Ramey's (1993) study, which analyzed data from 1954 to 1991 to assess the relative importance of money versus credit channels Utilizing a dynamic stochastic general equilibrium model and eight key variables, Ramey concluded that the money channel plays a more significant role than the credit channel in the direct transmission of policy shocks In contrast, Bernanke and Gertler (1995) argued that the credit channel is a crucial component of the monetary transmission mechanism, detailing its two linkages: bank lending and the balance sheet channel Subsequent studies have adopted this framework to examine the credit channel's impact, employing vector autoregression methods to analyze responses to policy shocks and identifying significant costs associated with capital effects in a neoclassical context.
In his 1999 investigation of Korea's financial crisis, Kim examined the significance of the credit channel in the transmission of monetary policy Utilizing monthly data from January 1993 to May 1998, he integrated three methodologies, including a narrative approach and disaggregated bank analysis.
Bernanke and Blinder described the monetary transmission mechanism as a "black box" in their journal, utilizing a disequilibrium model to examine the bank lending channel They employed standard vector autoregression for econometric specification to determine the significance of loan supply Their findings offered compelling evidence of the critical role played by the credit channel following the financial crisis.
Numerous researchers have explored similar topics over the years, yielding diverse results due to varying characteristics among countries Warner and Georges (2001) introduced a novel approach to testing the credit view of monetary transmission by analyzing stock market returns, specifically focusing on abnormal returns of U.S manufacturing firms' common shares Their findings revealed no consistent relationship between abnormal stock returns and credit constraints during both recessionary (1990-1991) and expansionary (1993-1994) periods Similarly, Suzuki (2004) examined the lending view in Australia from 1985:Q1 to 2000:Q2, concluding that the lending channel was less significant due to specific behaviors of Australian banks Additionally, Lown and Morgan (2002) and Disyatat and Vongsinsirikul (2003) investigated credit effects in the U.S and Thailand, respectively Lown and Morgan utilized bank commercial credit standards as a proxy for credit availability, employing a vector autoregression (VAR) model to analyze the data.
This study categorizes the loan market into two forms: the classical market and the augmented market Through market discrimination, the author identifies the significant role of credit standards in the U.S economy The empirical findings reveal that the dynamics of commercial credit standards greatly influence both loans and economic output Utilizing a typical econometric methodology, specifically the VAR model, Disyatat and Vongsinsirikul present their results.
3 The economists who supported the view: bank loans play important role in monetary policy transmission mechanism.
Lown and Morgan (2002) explored the enigmatic nature of credit effects in the Thai economy, focusing on three key variables: real output, the Consumer Price Index (CPI), and the 14-day repurchase rate from Q1 1993 to Q4 2001 Their study revealed that investments were significantly influenced by monetary shocks, highlighting the crucial role of banks as vital facilitators in the effective implementation of monetary policy.
Charoenseang and Manakit (2006) found that in Thailand, following the implementation of inflation targeting, the transmission of monetary policy was primarily facilitated through the credit channel rather than the interest rate channel.
From 2000 to July 2006, the Thai financial market heavily relied on bank lending as a key source of capital for economic activities This period reaffirmed the significant role that commercial bank lending plays in supporting the Thai economy.
In the same year, Podpiera (2007) had employed commercial banks data to study the impact of monetary policy shocks on loan market in Czech case; meanwhile Kubo.A
In 2007, a study focused on the credit channel as a key aspect of the monetary transmission mechanism in Thailand, emphasizing its significant role during the research period Empirical evidence supported this, with Podpiera utilizing the Kashyap and Stein model on balance sheet data from Czech banks covering 1996:Q1 to 2001:Q4, revealing that monetary policy changes influenced loan growth rates, particularly between 1999 and 2001 Kubo applied a structural vector autoregression (SVAR) approach to analyze the effects of exogenous monetary policy shocks on domestic macroeconomic variables from May 2000 to December 2006, incorporating five key indicators: the consumer price index, industrial production, producer price index, inter-bank overnight lending rate, and private credit aggregates The findings highlighted the Bank of Thailand's (BOT) success, attributing it significantly to the credit channel, while also noting a negative impact on import demand when assessing the effects of monetary policy shocks on international variables within the SVAR framework.
Balazs Egert (2009) investigated the effectiveness of research on the monetary transmission mechanism in Central and Eastern Europe, revealing that a decrease in inflation rates significantly enhances exchange rate transmission over time The study identified the credit channel as a crucial component of monetary policy transmission, while the asset price channel lacked efficacy in stagnant stock and bond markets Similarly, Fiorentini and Tamborini (2001) emphasized the critical role of credit supply in Italy's monetary policy, highlighting its importance in research conducted over the past decade.
This article examines the monetary policy transmission in India, highlighting the work of Abdul (2009), who utilized a VAR model with macroeconomic variables such as bank rate, repo rate, and reserve repo rate The study emphasized the significance of the bank lending channel in transmitting monetary policy to India's economic activities Additionally, it suggested including the Federal Reserve's rate in the analysis of monetary shocks due to its substantial impact on emerging economies like India Furthermore, Catão and Pagan (2010) employed an expectation-augmented SVAR model to investigate monetary transmission in Brazil and Chile, using data from the IMF's International Financial Statistics and other local sources Their findings underscored the critical role of the bank-credit channel in emerging markets, revealing that typical credit shocks could have significant effects on output and inflation, particularly in Chile, where bank system penetration is higher.
Research on the role of credit in monetary policy transmission in Vietnam is limited, with significant contributions only emerging in 2008 Hung and Pfau analyzed Vietnam's monetary transmission mechanism using a vector autoregression (VAR) approach, focusing on the relationships among money supply, real output, price levels, real interest rates, real exchange rates, and credit Their findings highlighted a weak connection between monetary policy and its channels in Vietnam, emphasizing that the credit and exchange rate channels are more influential than the interest rate channel.
This chapter delves into the core thesis by examining the credit channel, highlighting that credit theory is driven by the external finance premium It discusses how monetary policy shocks can affect the loan market through both the bank lending channel and the balance-sheet channel In the context of Vietnam's monetary policy framework, the National Assembly oversees sovereign monetary activities, while the State Bank of Vietnam (SBV) implements these policies Key monetary instruments in Vietnam include reserve requirements, open market operations (OMOs), and discount policies The empirical literature largely acknowledges the significant role of the credit channel, although some studies present findings that challenge this perspective.
CHAPTER 3: MODEL SPECIFICATION AND DATA
This section presents the analytical framework that outlines the methodology used in this thesis It introduces the VAR model as the primary method for examining the impact of the credit channel on monetary policy transmission in Vietnam Additionally, it provides a brief overview of the estimation steps employed throughout the research.
ANALYTICAL FRAMEWORK
Rely on theory and empirical studies, an analytical framework is conducted below
Vietnam's government implements new monetary policy adjustments through four main channels: interest rate, exchange rate, asset rate, and credit channels, which influence macroeconomic variables like output and inflation However, the asset channel is not analyzed due to the inexperience of Vietnam's stock market, and the exchange rate channel is excluded because of the country's strict capital mobility, which is primarily driven by interest rates This study focuses on the interest rate and credit channels, emphasizing the significance of the credit channel in monetary policy transmission in Vietnam To explore the role of credit, two markets are introduced: a classical market without credit and an augmented market with credit A VAR model will be applied to both markets through Granger causality, impulse response, and variance decomposition tests, revealing the differences between them and identifying the critical role of the credit channel in the monetary policy transmission mechanism.
MODEL SPECIFICATION
To achieve the thesis objective, a Vector Autoregression (VAR) model will be developed to investigate the significance of the credit channel in the transmission of monetary policy in Vietnam.
According to Stock and Watson (2001), Vector Autoregressions (VARs) can be categorized into three types: reduced form, recursive, and structural This thesis employs the VAR approach, specifically focusing on the reduced form as an effective method to achieve its objectives.
A reduced form represents each variable as a linear function of its own previous values and the past values of all other variables This approach allows for the derivation of a reduced form of the VAR model.
Yt is an m-dimensional vector of endogenous variables
(L) denotes vector polynomial of lag operator with optimal lag order;
t is assumed to be vector white noise residual
In regression analysis, the error term (εt) represents the unexpected fluctuations in the variables after considering their past values Each equation is individually estimated using ordinary least squares, and the optimal number of lagged values is determined through various methods.
This thesis utilizes quarterly data from 1996:Q1 to 2010:Q3, focusing on Vietnam's unique data accessibility challenges for longer periods The selected macroeconomic variables include M2, consumer price index, domestic credit, real industrial output, refinancing rate, and lending rate, as detailed in Table 3.1 These variables provide a concise yet comprehensive overview of Vietnam's macroeconomy The choice of these variables is motivated by findings from Romer and Romer (1990), which highlight that a decrease in reserves leads to reduced loan availability, often due to contractionary monetary policy M2 is particularly relevant as it serves as a key measure of money and policy shocks in Vietnam, while the refinancing rate is an essential tool used by the State Bank of Vietnam to implement tighter monetary policy (Hung and Pfau).
The customer price index plays a crucial role in assessing inflation, which is a key predictor of economic output To accurately measure domestic loan supply, it is essential to include domestic credit variables in the model Additionally, the lending rate is a vital element in the policy transmission mechanism discussed in the theoretical section While GDP typically serves as a standard measure of economic growth, Vietnam's GDP data is only available from 2000; thus, real industrial output is utilized as a proxy This approach was also adopted in the empirical study by Hung and Pfau (2008) using a VAR model to analyze monetary transmission in Vietnam It is important to control for spurious regression among all variables, as Asteriou and Hall (2007) noted that most macroeconomic time series are trended and non-stationary.
Based on the empirical study by Lown and Morgan (2002), which investigated the role of the credit channel in the U.S., the loan market was classified into two scenarios: a classical market characterized by quantity and price, and an augmented market that includes credit This framework will be applied to the Vietnamese context, distinguishing between a classical market—comprising the customer price index, money-quasi, industrial output, refinancing rate, and lending rate—and an augmented market that incorporates credit as a proxy for loan supply or domestic credit to the economy.
DATA SOURCES
M2denoted broad of money stock and are defined by formula:
In 2009, IFS defined M2 as encompassing money (M1) along with savings and time deposits in national currency, as well as demand deposits in foreign currency held by other depository corporations, excluding those of the central government.
The Consumer Price Index (CPI) is calculated based on data from the 37 largest provinces in Vietnam, representing eight economic regions The weights used in this calculation are derived from the 2004 Vietnam Household Living Standard Survey, as noted by the IMF in 2009.
CREDIT denoted domestic credit It is the sum of credit to the nonfinancial public sector, credit to private sector and other account
OUTPUT denoted real industrial output As already represented, Vietnam’s industrial output is used as proxy for GDP, due to data limited
REFIN symbolized refinancing rate That is the rate charged by the State Bank of
Vietnam on its lending to facilities to all credit institution (IMF world and country noted, 2009)
M2 Broad money stock IFS-IMF
CPI Customer price index IFS-IMF
CREDIT Domestic credit to economy IFS-IMF
OUTPUT Real industrial output Vietnam GSO
REFIN Refinancing rate IFS-IMF
LR Lending Rate IFS-IMF
The LR, or lending rate, represents the average rates on short-term working capital loans provided by four major state-owned commercial banks, as noted by the IMF in 2009.
Excepting for output that is extracted from Vietnam General Statistic Office, these variables are taken from the International Monetary Fund’s (IMF) International Financial Statistic (IFS).
STEPS OF ESTIMATION
Stock and Watson (2001) stated that due to the complicated dynamics in the VAR, below statistics are more informative than estimated VAR regression coefficients or R 2 statistics
Stationary time series are crucial for accurate analysis, as non-stationary series only reflect behavior within a specific time frame and can lead to misleading results, known as "spurious" regression Therefore, it is essential to conduct stationarity tests on all variables before applying the VAR model, as emphasized by Gujarati (2003).
Several formal statistical tests address the unit-root problem, with the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests being the most favored These tests incorporate additional lagged terms of the dependent variable to effectively eliminate autocorrelation.
The Granger causality test is a crucial step in the regression of VAR models and is widely utilized in economic policy analysis This test serves as an effective tool for assessing the significance of coefficients, allowing for accurate predictions of Xt based on its past values.
Yt variable rather than not using such past value, or causality represents the ability of one variable to predict another variable
Impulse response analysis reveals how current and future values of variables react to a one-unit increase in the current value of a VAR error, while keeping other errors constant This method includes ± 1 standard error bands, providing an approximate 66% confidence interval for each impulse response Additionally, the forecast error decomposition tool allows us to determine the percentage of variance in forecasting errors attributed to specific shocks over a given horizon (Stock and Watson, 2001).
FINDING AND DISCUSSION
DESCRIPTIVE STATISTIC
This part reports the descriptive statistic of all variables of original data, also changed
It summarizes the mean, median, max, min, standard deviation and count of each variable
Table 4.1: Description statistic of variables Variables Mean Median Maximum Minimum Std Dev Obs
Source: Calculated from IMF-IFS and GSO data
The high standard deviation of CPI, CREDIT, M2, and OUTPUT, along with the significant spread between maximum and minimum values, indicates considerable volatility during this period As a result, the estimation outcomes based on their original values may be unreliable However, transforming these variables into logarithmic form and multiplying by 100, or estimating them in percentage changes, significantly reduces their standard deviation.
Figure 1a and 1b in the appendix provide an overview of the original data presented in this thesis Both domestic credit supply and quasi-money exhibit a similar upward trend, particularly after 2007, while incremental output remains relatively stable As discussed in Chapter 2, the significant increase in credit can be attributed to substantial capital inflows and real estate price bubbles.
UNIT ROOT TESTS
Asteriou and Hall (2007) assert that macroeconomic variables typically exhibit trends, and both the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests confirm that all variables analyzed are non-stationary, as demonstrated in Tables 4.2 and 4.3.
Table 4.2: Augment Dickey-Fuller test
Variables Exogenous t-statistic p-value Data in Level
Source: Calculated from IMF-IFS and GSO data
The analysis indicates that the changed data are stationary, but the CL_CPI variable did not meet the criteria for stationarity in the ADF test, although it did pass the PP test Consequently, these data can be utilized to uncover the key answers for the thesis.
Variables Exogenous t-statistic p-value Data in Level
Source: Calculated from IMF-IFS and GSO data
Concern to the optimal lag problem for VAR model, different criteria are used to determine
Table 4.4: Optimal lap-Classical market
Lag LogL LR FPE AIC SC HQ
Source: Self calculation by using Eviews
Table 4.5: Optimal lap-Augmented market
Lag LogL LR FPE AIC SC HQ
* indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error
AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion
Table 4.4 and 4.5 illustrate that several statistical methods can determine the optimal lag length for our model, with the Akaike Information Criterion (AIC) and Schwarz Criterion (SC) being the most significant To minimize the information criteria, the optimal lag length is identified as five for both markets based on the minimum AIC Therefore, I will select five lags for both cases when applying the VAR model.
VAR REGRESSION STATISTICS FOR CLASSICAL AND AUGMENTED
Table 4.6 presents regression statistics for VAR in a classical market, showing p-values from the VAR Granger Causality test with 5 lags The null hypothesis indicates that the independent variable does not cause the dependent variable Significant relationships were found, as lagged values of most variables predict output at a 5 percent level, except for the lending rate at 10 percent While the lending rate does not predict money-quasi, it is useful for forecasting the consumer price index, output, and refinancing rate at the 10 percent level The refinancing rate, however, provides limited predictive power for other macro variables, except for output Money supply does not Granger cause the lending rate but is useful for predicting output, price level, and refinancing rate at the 10 percent level Historically, from the late 1980s to 2000, Vietnam maintained a positive real interest rate to control inflation The State Bank of Vietnam transitioned from a ceiling mechanism to a base interest rate mechanism in August 2000, allowing banks to limit lending rates Currently, lending rates in Vietnam remain non-liberalized, failing to reflect market demand and supply Notably, in a credit-free market, no independent variable in a classical market Granger causes money supply, highlighting a potential gap in the classical market framework.
Table 4.6: VAR Regression Statistic- Classical market
Dependent Variable Independent vars CL_CPI CL_LR CL_M2 CL_OUTPUT CL_REFIN
Source: Calculated from IMF-IFS and GSO data
Table 4.7: VAR Regression Statistic- Augmented market Augmented
CL_CPI CL_CREDIT CL_LR CL_M2 CL_OUTPUT CL_REFIN
Source: Calculated from IMF-IFS and GSO data
Note: The reported are p-value
The augmented credit market analysis reveals that lagged credit values are highly significant in predicting money supply, with a p-value of zero However, credit does not Granger cause output or price levels, as indicated by p-values of 0.67 and 0.19, respectively This suggests that the State Bank of Vietnam primarily utilizes credit to inject liquidity into the money market Additionally, price levels serve as a useful predictor for money supply at a 5 percent significance level In this context, the lending rate does not effectively predict output or significantly Granger cause monetary policy shocks or credit, although it shows a slight improvement with a p-value of 0.1 Notably, the combination of price level and refinancing rate Granger causes output, while output and lending rate can predict credit at a 10 percent significance level In contrast, M2 fails to forecast either credit or output.
Regression statistics reveal key insights into monetary transmission and the lending channel Firstly, traditional VAR results may inadequately explain these dynamics, while an augmented model that includes credit significantly enhances money supply forecasting Secondly, in models excluding credit, the lending rate's influence appears diminished compared to money market regulation; however, its importance increases when credit is considered Lastly, the price level and lending rate emerge as the second and third most valuable predictors of money supply, surpassing the role of credit.
IMPULSE RESPONES AND VARIANCE DECOMPOSITIONS
This article examines the impact of monetary policy and credit variable shocks on the macroeconomy, specifically in Vietnam By analyzing regression estimates, we identify changes in monetary policy through fluctuations in the money supply, or M2.
Figure 4.1: The impulse response functions for classical market
Response of CL_CPI to CL_CPI
Response of CL_CPI to CL_LR
Response of CL_CPI to CL_M2
Response of CL_CPI to CL_OUT PUT
Response of CL_CPI to CL_REFIN
Response of CL_LR to CL_CPI
Response of CL_LR to CL_LR
Response of CL_LR to CL_M2
Response of CL_LR to CL_OUT PUT
Response of CL_LR to CL_REFIN
Response of CL_M2 to CL_CPI
Response of CL_M2 to CL_LR
Response of CL_M2 to CL_M2
Response of CL_M2 to CL_OUT PUT
Response of CL_M2 to CL_REFIN
Response of CL_OUT PUT to CL_CPI
Response of CL_OUT PUT to CL_LR
Response of CL_OUT PUT to CL_M2
Response of CL_OUT PUT to CL_OUT PUT
Response of CL_OUT PUT to CL_REFIN
Response of CL_REFIN to CL_CPI
Response of CL_REFIN to CL_LR
Response of CL_REFIN to CL_M2
Response of CL_REFIN to CL_OUT PUT
Response of CL_REFIN to CL_REFIN Response to Cholesky One S.D Innov ations ± 2 S.E.
Source: Calculated from IMF-IFS and GSO data
The monetary policy shock demonstrates a significant decline, dropping sharply from 4.46 in the first quarter to 0.006 in the third quarter, indicating a substantial tightening in current conditions Output adjusts with a lag of one quarter, showing greater fluctuations compared to M2 This sensitivity reveals that output reacts to monetary shocks, though not in a one-to-one manner, with a response lasting for two quarters before recovering growth in the fourth quarter The lowest output level is 1.32 percent below the pre-shock level The lending rate positively responds to the monetary shock after one quarter, peaking at 2.2 percent in the sixth quarter, but subsequently decreases over the next three quarters while M2 continues to tighten Additionally, the price level reacts slowly to M2 shocks, with noticeable effects emerging after the fifth quarter, while the refinancing rate responds to the monetary shock after one quarter, reaching a peak of 3.8 percent.
A decrease in lending rates positively impacts the money supply after one quarter, although this effect is short-lived Theoretically, contractionary monetary policy leads to higher lending rates, which restrains investment and subsequently reduces aggregate demand and output However, this expected response does not always occur consistently.
Historical data reveals an abnormal relationship between M2 growth and lending rates Despite a continuous increase in M2, lending rates remained constrained at 14.4 percent in 1998, contradicting existing literature This pattern reemerged from Q3 2002 to Q3 2008, attributed to poor credit conditions in real estate and financial investments (Dung, 2010) Notably, lending rate shocks impact output responses starting in the second quarter, but only persist for one quarter Conversely, output shocks lead to a strong reaction in money supply after just one quarter.
These reactions are consistent with the regression statistic; output is highly sensitive to monetary shock; the impact of lending rate shock on money supply is somewhat weak
5 Response of all variables represent the cumulative percentage change following the shock
Figure 4.2: The impulse response functions for augmented market
Response of CL_CPI to CL_CPI
Response of CL_CPI to CL_CREDIT
Response of CL_CPI to CL_LR
Response of CL_CPI to CL_M2
Response of CL_CPI to CL_OUTPUT
Response of CL_CPI to CL_REFIN
Response of CL_CREDIT to CL_CPI
Res ponse of CL_CREDIT to CL_CREDIT
Response of CL_CREDIT to CL_LR
Response of CL_CREDIT to CL_M2
Res ponse of CL_CREDIT to CL_OUTPUT
Respons e of CL_CREDIT to CL_REFIN
Response of CL_LR to CL_CPI
Response of CL_LR to CL_CREDIT
Response of CL_LR to CL_LR
Response of CL_LR to CL_M2
Respons e of CL_LR to CL_OUTPUT
Response of CL_LR to CL_REFIN
Response of CL_M2 to CL_CPI
Response of CL_M2 to CL_CREDIT
Response of CL_M2 to CL_LR
Response of CL_M2 to CL_M2
Respons e of CL_M2 to CL_OUTPUT
Response of CL_M2 to CL_REFIN
Response of CL_OUTPUT to CL_CPI
Res ponse of CL_OUTPUT to CL_CREDIT
Respons e of CL_OUTPUT to CL_LR
Respons e of CL_OUTPUT to CL_M2
Res pons e of CL_OUTPUT to CL_OUTPUT
Res ponse of CL_OUTPUT to CL_REFIN
Response of CL_REFIN to CL_CPI
Respons e of CL_REFIN to CL_CREDIT
Response of CL_REFIN to CL_LR
Response of CL_REFIN to CL_M2
Res ponse of CL_REFIN to CL_OUTPUT
Respons e of CL_REFIN to CL_REFIN Response to Cholesky One S.D Innovations ± 2 S.E.
Source: Calculated from IMF-IFS and GSO data
In the augmented market, credit shocks initially lead to a 4.9% expansion, but this is short-lived as it plummets to -1.39% by the second quarter, with tightened credit persisting for twelve quarters Output reacts strongly, dropping from 1.1% to -1.9% by the fourth quarter following the credit shock, before gradually recovering and fluctuating within a narrow range by year-end Additionally, M2 responds sharply to these credit shocks, decreasing from 3% to 0.5% within just one quarter, with this decline also lasting for twelve quarters.
Lending rate is slow reactions to credit shocks, because of specific characteristic of Vietnam’s credit market as mentioned above
The analysis reveals that credit's response to money shocks is minimal and enduring when M2 shifts from easing to tightening in the initial two quarters Output begins to react to M2 shocks starting in the second quarter, reaching a low of 0.7 percent by the fourth quarter Additionally, the refinancing rate responds to tightening monetary policy after two quarters, while the price level reacts more gradually, taking five quarters to show a significant response.
Credit responses to lending rate shocks are slow, as evidenced by the data in the second row and third column This indicates that credit reacts after four quarters, followed by a decline when lending rates rise Additionally, the output takes one quarter to respond to lending rate changes and experiences continuous fluctuations over the next eight quarters.
In summary, shocks to credit significantly impact monetary policy, leading to a decline in output and prolonged effects on lending rates Additionally, monetary policy shocks result in reduced output, an increase in refinancing rates, and a slight decrease in price levels.
In the analysis of variance decomposition of M2 across two markets, significant differences in shock magnitudes are observed, with M2 accounting for over 50% of its error variance in the classical market, unlike in the augmented market This trend persists across different horizons but diminishes over time Notably, at the 13-quarter horizon, credit accounts for 21.5% of the variance in M2’s forecast error, compared to 15.7% from its own variance decomposition, with credit shocks dominating the first quarter prediction of money-quasi Additionally, price level shocks enhance M2 forecasting in the credit-inclusive market Refinancing rate shocks contribute 20% to variance after nine quarters in the augmented market, while their impact is negligible in the classical model Although lending rate shocks have gained importance in the augmented market, they remain weaker than other factors, and the output response is modestly lower in the credit market, at 8.4% compared to 9.2% in the classical market after nine quarters.
The variance decomposition results indicate that M2 shocks have a smaller impact on the market with credit, accounting for 19.9 percent initially but dropping to 5.1 percent after nine quarters, with this difference widening over longer horizons In an augmented market that includes credit variables, the contribution of lending rates to output variance decreases from 20 percent to 14 percent after five quarters Notably, credit shocks represent 18.9 percent of the forecast error in output at thirteen quarters, highlighting the significant and continuous role of credit shocks in predicting output errors.
The findings indicate that output and price levels play a crucial yet fragile role in forecasting credit error, contributing 15.2% and 14.8% respectively over a 13-quarter horizon Similar to impulse response results, M2 shocks contribute minimally to predicting credit error, accounting for only 3.5% after thirteen quarters Notably, credit shocks consistently represent nearly half of the forecast error for credit itself during this period Additionally, the introduction of credit variables significantly alters the decomposition of lending rate shocks, with credit shocks responsible for approximately 30% of the prediction error in lending rates, although this percentage diminishes over longer horizons.
Table 4.8: Variance Decompositions for vector autoregression for Classical and Augmented Market
Sources: Calculated form IMF-IFS and GSO data
Empirical results indicate that in VAR regression, neither the lagged lending rate nor the refinancing rate effectively predicts money supply, suggesting a gap in classical market models Conversely, credit emerges as a significant predictor of money supply in augmented markets Analysis of impulse response and variance decomposition reveals that the relationship between money supply and lending rate shocks can be irregular in markets lacking credit, while M2 shows immediate and strong responses to credit shocks Credit shocks are crucial for forecasting errors in money supply, with variations in magnitude and order among macroeconomic variables when credit is present in augmented markets, highlighting the influential role of credit and price levels on output and M2.
RESULTS COMPARISON
This thesis will compare its estimation findings with relevant research conducted in Vietnam and other countries, highlighting both similarities and differences to identify the unique contributions of the thesis.
Our findings affirm the existence of the credit channel and its significance in the Vietnamese context, aligning with the research of Bernanke and Gertler (1995) The empirical results of this study are consistent with the majority of prior research that employs the VAR model as a primary analytical approach, including the work of Kim.
(1999), Lown and Morgan (2002), Disyatat and Vongsinsirikul (2003), Abdul (2009); and structure vector autoregression model such as Kubo.A (2007), Catão and Pagan
(2010) that credit channel plays important role in monetary transmission mechanism Once again, this study is in line with Podpiera (2007), Charoenseang J and Manakit P
A study reaffirmed the significance of the credit channel in Thailand and Chile, despite variations in countries and econometric methods Similarly, research on Vietnam aligns with Hung and Pfau (2008), concluding that the credit channel is more crucial than the interest rate channel, making it the most significant channel in the Vietnamese context.
However, the study’s finding conflicts with several researches, such as Ramey (1993), Suzuki (2004) when their empirical provides evidence the insignificant role of credit in transmission of monetary policy
In general, despite of different market conditions and Vietnam’s specific characteristic, the empirical finding still has same results to majority relevant studies.
CONCLUSION AND POLICY IMPLICATION
CONCLUSIONS
This thesis examines the role of credit in the monetary transmission mechanism in Vietnam from Q1 1996 to Q3 2010, utilizing data primarily sourced from IFS-IMF, with the exception of industrial output Employing a VAR model with a reduced form as the optimal economic technique, the study differentiates between classical and augmented markets to investigate the credit channel's impact Initial stationary and unit-root tests determine the suitability of data for model application, while the minimum AIC criteria guide the selection of optimal lags for VAR estimation The VAR Granger-causality test assesses the causal relationships between money supply, credit variables, and other relevant factors Impulse response analysis reveals the reactions of each variable to shocks, and variance decomposition evaluates the contribution of each variable to the forecast error of monetary shocks over a specified horizon The estimated results provide valuable insights into the dynamics of credit and monetary policy in Vietnam.
In classical markets, there are no independent variables exhibiting Granger causality with money supply, which primarily aids in predicting various dependent variables except for the lending rate This suggests that VAR regression statistics may inadequately explain the monetary transmission mechanism In contrast, the augmented market shows that domestic credit significantly predicts money supply, with price levels and lending rates also playing predictive roles that are absent in classical markets However, the lagged value of money supply does not forecast credit, output, or lending rates Thus, incorporating credit variables in the augmented market underscores the critical importance of the credit channel in the transmission of monetary policy.
In a classical market, the output and refinancing rates respond to monetary policy shocks, such as tightening, after a lag of one period The output shows a strong sensitivity to monetary shocks, while the lending channel's reaction can be short-lived and inconsistent In credit markets, however, the output reacts robustly to credit shocks after a similar lag, with M2 responding immediately and in alignment with Bernanke and Gertler's findings Additionally, the correlation between the lending channel and the credit channel remains relatively weak.
In the variance decomposition of M2, a clear distinction emerges between two markets, with over fifty percent of forecast errors attributed to credit shocks in the first quarter of the augmented market Both credit and price level shocks significantly influence the variance decomposition of M2, although their impact diminishes over longer horizons Notably, there is a substantial difference in both magnitude and the sequence of variance decomposition of M2 in markets characterized by credit.
Since those findings, the study agrees with Bernanke and Gertler view that credit channel played as important channel in monetary transmission mechanism in Vietnam case.
POLICY IMPLICATION
The study highlights significant implications for policymakers regarding the credit channel and the monetary transmission mechanism The findings demonstrate the crucial role that the credit channel plays in the effectiveness of monetary policy transmission.
Vietnam; hence; in order to regulate the economy development through reasonable monetary policy at each period, some recommendations are given below:
The credit channel is vital for the monetary transmission mechanism in Vietnam, necessitating careful regulation of the credit sector when implementing new monetary policies Changes in government policy from loose to tight monetary measures significantly impact this channel The State Bank of Vietnam (SBV) plays a crucial role in regulating credit flow in the economy through its instruments As the central bank overseeing commercial banks, the SBV must provide appropriate recommendations and practical policies to the government, and to enhance effectiveness, it should be granted greater autonomy in decision-making.
Tightening monetary policy leads to immediate and significant credit shocks, causing a sharp decline in output, particularly affecting manufacturing enterprises due to reduced credit supply To mitigate the adverse effects on production, especially in agriculture-dependent countries like Vietnam, it is crucial to implement support programs for these enterprises While the Vietnamese government has introduced various subsidized initiatives for the sector, challenges remain in their execution Therefore, effective control and supervision by the government are essential to ensure the success of these policies.
The relationship between lending channels and monetary policy in Vietnam often deviates from theoretical expectations, primarily due to the underdevelopment of the country's financial market Despite having some autonomy in credit operations and interest negotiations, commercial banks still rely heavily on the State Bank of Vietnam's guidance for lending decisions Therefore, it is crucial to implement alternative solutions for lending rates, moving towards a more market-driven lending mechanism.
Variance decomposition results indicate that credit and price levels significantly influence the short-run dynamics of money quasi, with their impact diminishing over longer horizons Therefore, it is crucial to manage credit growth carefully, prioritizing financing for development projects over speculative activities to mitigate the risks of bubbles and bad debts.
Monetary policy must be applied with caution and flexibility to improve the effectiveness of money stock control To fulfill this responsibility, the SBV should closely monitor and anticipate shifts in both domestic and global financial markets to implement timely and appropriate policies.
Understanding the importance of the credit channel in the monetary transmission mechanism is crucial for mitigating negative impacts from newly implemented policies Successfully executing these measures can lead to a substantial improvement in the health of Vietnam's financial market.
LIMITATION AND FURTHER STUDIES
Although, this study has answered all the key questions about the role of credit in monetary transmission mechanism in Vietnam case, it also contains some limitations
Data resources in Vietnam are notably limited, restricting the study's ability to access longer time periods Since Vietnam's GDP data has only been available since 2000, the research utilizes industrial output value as a proxy for GDP Additionally, following Lown and Morgan's methodology, domestic credit value is employed as a standard variable proxy for net percentage tightening.
Vector Autoregression (VAR) models are essential for understanding the impact of credit on monetary transmission They have significantly enhanced the toolkit for macroeconometricians, enabling them to effectively analyze data and produce reliable multivariable benchmark forecasts (Stock and Watson, 2001).
This study utilizes impulse response and variance decomposition of the VAR model to analyze the impact of credit and monetary transmission using quarterly data from 1996:Q1 to 2010:Q3 Future research could enhance this analysis by incorporating monthly data over an extended period to better understand the correlation and interactions between these variables Additionally, employing alternative models like the vector error correction (VECM) could provide insights into the validity of these findings in the context of Vietnam.
Besides that, the study could add several variables such as Federal Funds rate, exchange rate to exploit how the changes of estimated result with joined new variables
6 The number of banks tightening less the number easing, divided by the number reporting (Lown and Morgan,
The credit plays important role in monetary transmission Hence, potential study may expand by consider the determinants of domestic credit in Vietnam case.
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