(Luận văn) exchange rate pass through to vietnam’s import and domestic prices

Introduction

Problem statement

Exchange rate is one of the most important factors in macro-economic management

The appreciation of a domestic currency leads to more expensive exports and cheaper imports, negatively impacting the balance of trade Conversely, when the domestic currency depreciates, exports become cheaper and imports more expensive, resulting in an increased balance of trade This dynamic significantly influences the supply and demand for foreign currencies, as well as national debts and reserves.

Vietnam is prioritizing an export-led growth strategy, emphasizing the importance of export activities However, there has been a significant increase in imports in recent years, making the reduction of net imports a key concern Adjusting the exchange rate to depreciate the domestic currency is seen as an effective tool to achieve both objectives.

When the State Bank depreciates the domestic currency, it exerts inflationary pressure through three main channels: rising import prices directly impact domestic prices, increased export activities reduce supplies in the domestic market while raising export prices, and heightened aggregate demand for non-tradable goods further contributes to inflation.

Depreciation, similar to easing monetary policy, poses a risk of inflation in the economy To mitigate this effect, the State Bank must implement a tightening monetary policy, which may include increasing the reserve ratio or capital adequacy ratio There is a significant relationship between money supply and exchange rates, and the government should take this connection into account to effectively control inflation.

Research questions

The degree of exchange rate pass-through (ERPT) to import prices and its subsequent impact on domestic inflation raises important questions It is essential to determine whether this pass-through is complete or partial Additionally, understanding the State Bank of Vietnam's monetary policy response to the depreciation of the Dong is crucial Therefore, a quantitative measurement of ERPT to both import and domestic consumer prices is necessary to address these questions and provide recommendations for effective inflation control and monetary policy.

ERPT, or Exchange Rate Pass-Through, is defined as the percentage change in local currency import prices of an importing country in response to a one percent change in the exchange rate between trade partner countries (Goldberg and Knetter, 1996).

Understanding exchange rate pass-through (ERPT) is crucial for evaluating how monetary policy affects prices and for predicting inflation Additionally, insights into the magnitude and speed of ERPT are valuable for implementing effective inflation targeting strategies (Lian, 2006).

ERPT has been studied since 1980s by Dornbursh (1987), Krugman (1986), Knetter

In the early stages of research, scholars primarily examined exchange rate pass-through (ERPT) in the United States, Euro Area, and other developed nations, engaging in debates about the limited pass-through of exchange rates across countries due to deviations from the law of one price Recently, attention has shifted to studying ERPT in emerging markets, small open economies, and developing countries, with a particular focus on the transmission of exchange rates into disaggregate industries.

Research objectives

Several studies have explored Exchange Rate Pass-Through (ERPT) in Vietnam, highlighting its significance in understanding economic impacts and responses to government policies This research aims to quantify the degree and speed of ERPT from import prices to domestic inflation, specifically consumer prices, in Vietnam Additionally, it investigates the interplay between inflation, monetary policy, and other influencing factors.

This research utilizes the Vector Auto Regression (VAR) method, incorporating Impulse Response Functions (IRF) and Cholesky Variance Decomposition for analysis Subsequently, it examines Granger causality, assesses VAR stability, and conducts the Lagrange multiplier test.

The null hypothesis posits that, consistent with numerous prior studies, the exchange rate does not influence import and domestic prices, indicating that the exchange rate pass-through (ERPT) is zero.

My research has certain limitations, primarily due to the unavailability of data, which prevents me from establishing a systematic distribution chain from the Import Prices Index to the Producer Prices Index and ultimately to the Consumer Price Index Additionally, I have not accounted for the structural changes that occurred when Vietnam joined the WTO in 2007 Furthermore, this paper does not address the exchange rate pass-through (ERPT) in disaggregated industries, which will be explored in future research.

This paper is structured into six sections Following the introduction, Part 2 provides an overview of Vietnam's exchange rate, import activities, and inflation Part 3 presents a literature review, while Part 4 outlines the research methodology, empirical framework, and data description The empirical results are detailed in Part 5 Finally, Part 6 concludes with findings from the estimation process and offers policy recommendations.

Overview of Vietnam’s exchange rate, import activities and inflation

Exchange rate arrangement in Vietnam

The Vietnamese economy has experienced significant success since the implementation of the Renovation or "Doi Moi" program in 1986, transitioning from a centrally planned system to a market-oriented one This comprehensive reform has led to a more stable, open, and free economy Additionally, the financial system underwent renovations to align with market principles, highlighting the crucial role of the exchange rate in this transformation, as noted by Vo et al.

Vietnamese authorities view exchange rate control as a key macroeconomic tool aimed at achieving several objectives, including maintaining a low inflation rate, ensuring financial system stability, supporting exports, regulating imports, and fostering economic growth.

Before 1989, the exchange rate system consisted of three tiers: trading, non-trading, and internal exchange rates The trading exchange rate facilitated payments, while the non-trading rate was used for inward remittances and transactions involving intangible goods like tourism and education among socialist countries The internal exchange rate was designated for business transactions between domestic banks and companies, as well as for foreign aid from the former Soviet Union In 1989, the exchange rate was unified, resulting in a significant devaluation from VND225/USD to VND4500/USD, which was pegged to the US Dollar throughout the 1990s Commercial banks were allowed to set their own exchange rates within a +/-5% range of the official rate, leading to a positive impact on exports and economic activities in 1990-1991 However, Vo et al (2000) noted that this approach was used cautiously From 1993 to 1996, the nominal exchange rate remained stable, and as inflation decreased, concerns arose regarding an overvalued Dong.

During this period, the real exchange rate and the real effective exchange rate appreciated by approximately 20% and 15%, respectively, contributing to significant current account deficits Despite robust growth in exports, they continued to lag behind imports, leading to substantial current account deficits that peaked at 12% of GDP in 1996.

Amid the challenges of current account deficits stemming from reduced foreign direct investment and the East Asian financial crisis, Vietnam's export competitiveness diminished In response, the State Bank of Vietnam implemented a gradual devaluation of the VND, akin to an adjustable fixed rate regime, while tightening controls on imports and current account transactions Consequently, trade and current account deficits were reduced to approximately 4-5% of GDP during 1997-1998 (Vo et al., page xi).

Between 2000 and 2003, the exchange rate consistently depreciated to bolster the government's export-led growth strategy However, from 2004 to 2010, inflation rates began to rise more rapidly than the depreciation of the exchange rate, leading to a divergence between the nominal effective exchange rate and the real effective exchange rate.

The Vietnamese Dong has appreciated, leading to a decline in the competitiveness of Vietnamese goods compared to foreign exporters Despite the State Bank's attempts to devalue the Dong in 2009 and 2010 to address this issue, the currency has continued to appreciate against the currencies of Vietnam's major trading partners.

Figure 1: REER, NEER and Exchange rate 1995-2012

Between 2000 and 2011, Vietnam experienced rapid economic growth and increased integration into the global market However, the country faced challenges from an unstable domestic macro-economy and the impacts of the global financial crisis, leading to a continued trend of currency depreciation over the years.

Between 2008 and 2011, the Vietnamese Dong experienced significant fluctuations against the US dollar, marked by multiple depreciation adjustments and a wide exchange rate band, as noted by Nguyen (2011) This period coincided with the global financial crisis, rising gold prices, and a notable disparity between the official exchange rate and the speculative "black market" rate By the end of 2009, the VND/USD exchange rate had risen by 5.6% compared to the end of 2008 In February 2010, the State Bank of Vietnam raised the official exchange rate from 17,941 VND/USD to 18,544 VND/USD, reflecting a 3.3% devaluation within a +/-3% band.

7 unprecedentedly high rate of devaluation of VND 9.3% in early February 2011, increasing the official rate to 20,693 VND/USD and narrowed the band to +/-1%.

Overview of Vietnam’s import activities

Vietnam has been suffering trade deficit for a long time and it still has had upward trend The proportion of import to GDP is increasing continuously from 50% in

Between 2000 and 2011, the proportion of disaggregated import goods varied significantly, with production goods consistently representing the largest share This trend poses a challenge for the State Bank, as utilizing the exchange rate to boost exports and reduce imports may have unintended consequences Specifically, currency depreciation could lead to a minimal decrease in import volume while significantly increasing import value, potentially exacerbating inflationary pressures.

Figure 2: Import by commodity group of Vietnam 1995-2010

Source: Author’s calculation from GSO (2011)

Non-monetary gold serves as a valuable asset beyond its financial worth, while consumer goods play a crucial role in everyday life Additionally, the means of production are essential for economic growth and development.

Overview of Vietnam’s inflation

Between 1985 and 1989, Vietnam experienced an average Consumer Price Index (CPI) of 263%, largely due to the failure of the "General Adjustment of Price, Wage and Money," which led to persistent hyperinflation To address this issue, the State Bank of Vietnam implemented a stringent monetary policy, increasing monthly interest rates and closely pegging the Vietnamese Dong (VND) to the US Dollar (USD) These measures, part of the "Doi Moi" program, significantly improved Vietnam's economy, resulting in inflation rates dropping to below 20% by 1992 and nearing 10% by 1995 (Nguyen and Nguyen, 2010).

During the Asian financial crisis from 1996 to 1998, the inflation rate remained low, even turning negative in 2000-2001, with a reported rate of -0.5% This deflationary period can be attributed to a significant decline in global prices and a decrease in aggregate demand.

After that the recovery period came in 2002, the inflation was around 5% during period 2002-2003 It started accelerating in 2004 with 9.5%, jumping to 12.7% in

Inflation in Vietnam surged to a peak of 23.1% in 2008, driven by several factors including significant increases in the minimum wage, rising international commodity prices, inflexible monetary policies, slow exchange rate management responses, and Vietnam's accession to the WTO in late 2006, as noted by Nguyen and Nguyen (2010).

In 2009, tightened monetary policy combined with the world economic depression, inflation slowed down again It came back to 11.8% in 2010 and 18.7% in 2011

Figure 3: Inflation of Vietnam 1996-2010 tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

Source: Author’s calculation from World Bank (2012)

Now I combine data of exchange rate, here I use nominal effective exchange rate (NEER), import price and consumer price in one graph so we can have a general overview of them Nominal effective exchange rate and inflation are rather consistent; they have the same movement through time Import price index, however, likes an outlier in the graph with its own remarkably and continuously increase year by year

Figure 4: NEER, IMP and CPI of Vietnam 1999-2011

Source: Author’s calculation from Datastream

NEER, IMP and CPI of Vietnam

NEER1 IMP CPI tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

Literature review

Linear approarch

Ihrig et al (2006) utilized a linear econometrics model to analyze exchange rate pass-through (ERPT) in G7 countries, including the United States, United Kingdom, Japan, Italy, Germany, France, and Canada, using quarterly data from 1975Q1 to 2004Q4 They applied two linear equations to estimate the pass-through effects on import and consumer prices The findings revealed that a 10 percent depreciation in the local currency led to an average increase of 4 percent in import prices and 2 percent in consumer prices over the last 15 years Additionally, the study indicated a decline in ERPT across nearly all G7 nations.

Campa and Goldberg (2005) conducted a study on exchange rate pass-through (ERPT) to import prices in the Euro Area, revealing that while ERPT was high, it was not complete and varied across industries and countries in the short term In the long run, the transmission rate approached one The research also examined structural changes in the pass-through rate following the introduction of the Euro, finding a declining trend in two-thirds of industries, although this was statistically significant only in manufacturing The authors suggested that a broader decline in pass-through might be occurring, but it was premature to definitively attribute this to structural changes.

The research conducted in 2005 highlighted the challenges of analyzing declines in the Euro currency, as its history was still relatively brief The limited sample size posed significant disadvantages for testing structural changes effectively.

Vector Error Correction Model approach

The VECM approach is favored by many researchers for measuring exchange rate pass-through (ERPT) in the presence of cointegration among variables This method offers the advantage of assessing long-term ERPT based on stable cointegration, although it requires stricter conditions compared to the VAR approach Notable studies utilizing VECM to measure ERPT include those by Kim (1998), Beiner & Bijsterbosch (2009), and Dahl & Lo (2005).

Beiner and Bijesterbosch (2009) conducted a study on exchange rate pass-through (ERPT) in Central and Eastern European member states using cointegrated VAR and impulse response from the VECM Their findings indicated that the ERPT for domestic consumer prices was 0.6 for the cointegrated VAR and 0.5 for the impulse response The research concluded that ERPT is higher in countries with a fixed exchange rate regime compared to those with a floating exchange rate regime.

Hanshilin (2006) explored the interplay between linear and VECM methods in his research on New Zealand, revealing that short-run pass-through elasticity was incomplete and varied across eight disaggregated industries In contrast, the long-run pass-through elasticity was found to be higher, with half of the industries experiencing complete exchange rate pass-through Ultimately, he concluded that the exchange rate pass-through rate is endogenous to inflation performance at the disaggregate level within New Zealand's economy.

Vector Autoregression approach

The VAR approach is widely recognized as the most popular method among researchers globally Numerous studies focus on Exchange Rate Pass-Through (ERPT) in the Euro Area, emerging markets, and Latin American countries, often comparing these regions.

12 or just ERPT of a specific country such as United States, United Kingdom, Switzerland, China, etc

Faruquee (2006) estimated ERPT in Euro Area with monthly data from 1990 to

In 2002, research on exchange rate shock revealed that factors such as import prices, producer prices, consumer prices, wages, and terms of trade were significant Utilizing VAR estimation, impulse response functions, and Cholesky decomposition, the study concluded that the effect of exchange rate pass-through (ERPT) on prices was minimal, with local currency prices remaining sticky in response to euro depreciation Over time, the degree of ERPT increased, particularly affecting import prices, while wholesale producer prices tended to rise more than retail consumer prices.

Twelve to eighteen months post-shock, the exchange rate pass-through (ERPT) to export prices is approximately 50%, while for import prices, it is around 100% Additionally, the euro area's terms of trade have decreased due to the depreciation of the exchange rate.

Zori et al (2007) conducted a study on exchange rate pass-through (ERPT) in 12 emerging market countries across Latin America, Asia, and Central and Eastern Europe, revealing a decline in ERPT throughout the pricing chain Their findings indicated that ERPT was generally higher in emerging markets compared to developed nations In emerging economies with single-digit inflation, ERPT levels were low and comparable to those in developed countries The research also identified a positive correlation between ERPT and inflation levels Furthermore, it concluded that while inflation levels were controlled, the relationship between import openness and ERPT was weaker than that between inflation and ERPT.

A study by Marazzi et al (2005) examined the exchange rate pass-through (ERPT) to import prices in the United States, revealing a decline from 0.5 in the 1980s to approximately 0.2 This decrease is attributed to a shift in the composition of imports towards goods that are less sensitive to exchange rate fluctuations, as well as the growing influence of China in the U.S market.

(p 4) tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

Jin (2010) studied the effects of exchange rate pass-through (ERPT) in China, finding that a 1% appreciation of the nominal effective exchange rate leads to a 0.132% decrease in domestic consumer prices and a 0.495% decrease in producer prices The research also indicated that the exchange rate regime significantly impacts inflation, with a higher consumer price index (CPI) pass-through observed in fixed exchange rate regimes compared to flexible ones Based on these findings, Jin recommended that the Chinese government adopt a more flexible exchange rate policy.

The research investigated price control, the composition and weighting of Chinese price indices, distribution costs, non-tradable shares, and imported inputs to identify the factors contributing to the low EPRT in relation to consumer price inflation.

In his 2009 study on exchange rate pass-through (ERPT) to inflation in Vietnam, Vo found that the degree of ERPT is 0.61 This figure is compared to other countries, revealing Indonesia's ERPT at 0.53, Korea's at 1.59, Thailand's at 1.27, and Singapore's at 0.59.

This study examines the exchange rate pass-through (ERPT) to inflation in Vietnam, finding it to be moderate, similar to findings in 23 OECD countries (0.46) and 10 euro area economies (0.47) Unlike previous research, which did not include exporters' costs, this analysis incorporates the foreign price index and expands the sample size from M1:1999 to M10:2011, compared to M1:2001 to M2:2007 Additionally, while prior studies weighted the nominal exchange rate and import prices based on 9 main trading countries, this paper utilizes a weighted trade approach from 20 countries Enhanced methodologies, including more stable VAR and Lagrange multiplier tests, yield results that differ significantly from those of Vo's study.

Research methodology, empirical framework and data description

Research methodology

This study aims to assess the exchange rate pass-through (ERPT) to import prices and its subsequent impact on domestic prices To achieve this, it is essential to first establish the relationship between exchange rates and import prices Our empirical framework is grounded in the purchasing power parity (PPP) theory.

In a perfectly competitive market without trade barriers, the Purchasing Power Parity (PPP) asserts that the domestic price of goods, when expressed in the home currency, should equal the foreign price of goods in the foreign currency, adjusted by the exchange rate between the two currencies.

We have an equation as follow:

In this context, let $ h $ represent the home country and $ f $ signify the foreign country The import price is expressed in the currency of the home country, while the export price is denoted in the currency of the foreign country Additionally, $ E $ refers to the nominal exchange rate, which indicates the value of the home currency relative to the foreign currency.

Exporting firms determine their prices based on the markup applied to the marginal cost of production, as noted by Hooper and Man (1989), Goldberg and Knetter (1997), and Campa and Goldberg (2002).

Hooper and Man (1989) assert that exporting firms determine their markup based on market demand pressures in both foreign and domestic markets, as well as competitive pressures within the home market Additionally, the competitive pressure in the importing market is evaluated through the profit margin, defined as the price relative to production costs Consequently, the markup can be expressed as outlined by Vo (2009).

Where represents competitive pressure in the home market and represents demand pressure in both home and foreign market and 0 < 0

From (1), (2) and (3) we have the import price as follows:

We can rewrite equation (6) as simple linear equation by generating variables as follows:

Equation (7) illustrates that the import price is influenced by the exchange rate $ e $, the marginal cost of production for foreign firms, the price level in the home country, and the market demand for both domestic and foreign goods $ y $.

The elasticity of import price concerning changes in the exchange rate (ERPT) of the home country can be derived from equation (7) A value of 0 indicates complete pass-through effects, while a value of 1 signifies zero pass-through Values between 0 and 1 represent limited or incomplete pass-through.

We will arrange equation (7) to obtain , and then we can analyze the movement of ERPT Because ERPT is measured by coefficient (1 – ), ERPT has an inverse relationship with

From equation (8) we have the movement of ERPT as follows:

If demand in both home and foreign markets (y) increase, decreases and hence ERPT increases and vice versa for case of decreases

If increases, raising inflation in the home market, decreases and ERPT increases and vice versa;

If increases, increases and ERPT decreases and vice versa;

If home currency depreciates (or e increases), will decrease and ERPT increases and vice versa

If increases, will increase leading to the decrease of ERPT and vice versa.

Empirical framework

This study utilizes the Vector Auto Regression (VAR) approach to assess the level of exchange rate pass-through (ERPT) According to Faruquee (2006), the VAR method offers several advantages over single-equation techniques, as it examines the impact of exchange rate shocks on a range of prices rather than isolating them to a single import or consumer price This comprehensive analysis allows for the characterization of both absolute and relative pass-through effects across the pricing chain Additionally, the application of Cholesky variance decomposition following the VAR model enables the identification of specific structural shocks influencing the results.

17 system Using this identification scheme, one can map the empirical results into a well-defined shock in an economic model of incomplete pass-through

A study by McCarthy (2002) utilized the VAR method to analyze the impact of exchange rates on import prices, producer prices, and domestic prices Due to the unavailability of producer price data for Vietnam, this paper focuses solely on applying the VAR method to import prices (IMP) and domestic prices (CPI).

We have matrix of VAR approach as follows:

Where is the 7 vectors of variables [OPI, NEER, FPI, IMP, GAP, CPI, M2], is intercept, i is coefficient of matrices 7x7 and is error term

The article discusses key economic indicators, including the Oil Price Index (OPI), which tracks crude oil prices such as Brent UK, and the Nominal Effective Exchange Rate (NEER) that measures currency value against a basket of others It also highlights the Foreign Exporters’ Price Index (FPI) and the Import Price Index (IMP), which reflect price changes in international trade Additionally, the Output Gap (GAP) is examined, indicating the difference between actual and potential economic output, alongside the Consumer Price Index (CPI) that gauges inflation Lastly, the article mentions M2, representing broad money supply in the economy.

Data description

Data to estimate ERPT to import price index and domestic price index is monthly time series from January 1999 to October 2011 with 154 observations; January

The data for this analysis is based on 1999, sourced from the International Financial Statistics (IFS) of the IMF, the Asia Regional Integration Center (ARIC) of the ADB, Datastream, and the General Statistics Office (GSO) of Vietnam Specifically, the oil price index and broad money (M2) are obtained from IFS, while the import price index, NEER, REER, foreign price index, and CPI are derived and calculated using Datastream Additionally, the Industrial Production Index (IPI) is sourced from ARIC in conjunction with GSO.

All variables will be generated in natural logarithm form Given their time series characteristics, we will conduct the Augmented Dickey-Fuller (ADF) test to check for the presence of a unit root, excluding the output gap variable.

18 differences and ADF test one more time will be applied respectively The results show that all variables are integrated at I(1)

The Oil Price Index (OPI) serves as an indicator of foreign demand pressure and is considered an exogenous variable, influencing all other variables in the econometric model without being affected by them Consequently, it is essential to determine the appropriate lag length for the VAR regression model before applying it to the Oil Price Index.

The Nominal Effective Exchange Rate (NEER) represents the exchange rate of Vietnam against its trading partners, calculated based on the trade weights of 20 key countries To simplify the interpretation, a new variable, NEER1, is introduced as the inverse of NEER, allowing for a quotation of VND per foreign currency This adjustment reveals that when the VND depreciates, the nominal exchange rate increases, aligning with the definitions used in pass-through literature.

Domestic demand pressure is indicated by the output gap, defined as the difference between real GDP and potential GDP Due to the unavailability of monthly GDP data, I will utilize the Industrial Production Index (IPI) as a proxy for real GDP, consistent with previous empirical studies To compute the output gap, I will apply the Hodrick-Prescott filter, which involves regressing the logarithm of the industrial production index on a constant, along with linear and quadratic trends This approach allows the output gap, derived as the error term from the regression, to remain unadjusted for seasonality, as the Hodrick-Prescott filter effectively separates the data into a smoothed component and an error term, with the latter being stationary.

This research calculates the foreign exporters' price index (FPI) to provide an additional control variable for the model, as the FPI reflects the adjustment mark-ups of exporting firms in response to changes in the exchange rate.

Based on Campa and Goldberg (2002), the exporters’ price index is calculated as follows:

Where REER is real effective exchange rate, NEER is nominal effective exchange rate, is domestic price index

The broad money (M2) is added to reflect the effect of government’s monetary policy response ADF test and taking the first difference are applied as the same previous procedures

Import price index is calculated by weight of 20 mainly countries being trade partners with Vietnam The formula is below:

Vietnam's import trade weight, denoted as \$w_i\$, is calculated based on its 20 main trading partners, which include Japan, Singapore, China, Korea, Thailand, Australia, Hong Kong, Germany, Malaysia, France, Indonesia, the UK, the Netherlands, Russia, the Philippines, Switzerland, Italy, Belgium, and India.

Consumer price index (CPI) is used to represent for domestic inflation ADF test showed that CPI has unit root, therefore it needs to take first difference to get stationary

The computation details for the Nominal Effective Exchange Rate (NEER) and the Real Effective Exchange Rate (REER) will be provided in the Appendices.

Empirical results

ADF tests

The results of ADF test show that all variables (except GAP) have unit root

To analyze the data, we first compute the first differences of the variables and subsequently perform the Augmented Dickey-Fuller (ADF) test on these new variables The results indicate that we can reject the null hypothesis (Ho) of the presence of a unit root at the I(1) level.

I do not conduct the ADF test for the GAP variable, as the HP filter has eliminated the cyclical component during processing, resulting in all variables being stationary The outcomes of these tests can be found in the Appendix.

Optimal lag length

Several criteria exist for selecting lag length, including the Akaike Information Criterion (AIC), Schwarz Information Criterion (HQIC), and Hannan-Quinn Criterion (HQC) Stata provides support for applying these criteria to determine the optimal lag length.

Moreover, theoretically, with relative large sample 120 or more observations, HQIC is a good choice Combining both empirical test and theory we have the optimal lag length is 2.

VAR regression

The oil price index serves as an exogenous variable that influences all other variables without being influenced by them The sequence of variables is as follows: [dlneer1, dlfpi, gap, dlm2, dlimp, dlcpi], with the oil price index (dlopi) acting as the exogenous factor.

The VAR regression results for the import price index are presented in Table 1.

Table 1: VAR regression for import price index

Constant dlneer1 t-1 dlneer1 t-2 dlfpi t-1 dlfpi t-2 gap t-1 gap t-2 dlm2 t-1 dlm2 t-2 dlimp t-1 dlimp t-2 dlcpi t-1 dlcpi t-2 dlopi t-1 dlopi t-2

*, ** and *** denote statistical significance at 1%, 5% and 10% level, respectively

The foreign price index at lag order 1, the import price index at lag orders 1 and 2, and the oil price index at lag order 2 are statistically significant at the 1% level Additionally, the output gap at lag order 1 shows statistical significance at the 5% level, while the exchange rate at lag order 1 is significant at the 10% level; however, the exchange rate at lag order 2 lacks statistical significance.

The regression results indicate that a 1% increase in the exchange rate at the first lag leads to a 1.011% increase in import prices This suggests that the exchange rate pass-through (ERPT) to import prices is significant.

22 than 1 and we have over complete pass-through effect When exchange rate changes, it will transfer to import prices immediately and completely at lag order 1

Hence the result of exchange rate at time order 2 is insignificant

The graph in Figure 4 illustrates a concerning trend: the import price index is rising uncontrollably Vietnam's import structure primarily consists of intermediate and essential goods for production As the VND depreciates to boost exports, firms are compelled to import more to manufacture finished products This creates a cyclical pattern of increasing import volume and value, continuing until Vietnamese companies gradually develop their own industrial production capabilities for inputs.

The response of import prices is now easy to understand with foreign price index

The import prices are highly sensitive to fluctuations in the foreign price index, demonstrating a significant correlation Specifically, a 1% increase in the foreign price index at a one-month lag results in a 3.122% rise in current import prices This rapid response occurs within just one month, while changes in the foreign price index at a two-month lag do not show statistical significance.

A 1% change in world oil prices results in a 0.41% change in import prices, highlighting Vietnam's significant dependence on global oil price fluctuations.

The VAR regression results for the consumer price index are presented in Table 2.

Table 2: VAR regression for consumer price index

Constant dlneer1 t-1 dlneer1 t-2 dlfpi t-1 dlfpi t-2 gap t-1 gap t-2 dlm2 t-1 dlm2 t-2 dlimp t-1 dlimp t-2 dlcpi t-1 dlcpi t-2 dlopi t-1 dlopi t-2

*, ** and *** denote statistical significance at 1%, 5% and 10% level, respectively

All independent variables are significant 5% level except money supply of lag order

The impact of exchange rate fluctuations on inflation is initially significant but diminishes over time Specifically, a 1% change in the exchange rate results in a 0.104% change in the consumer price index at the first lag and a 0.068% change at the second lag This indicates that the transmission of exchange rate changes to import prices occurs rapidly and strongly, whereas the effect on consumer prices is more moderate and gradual.

The foreign price index influences the consumer price index by an average of 0.11% The VAR regression indicates that the impacts of the output gap, money supply, and import prices on inflation are relatively minor However, I will conduct a detailed analysis of these factors in the upcoming impulse-response and variance decomposition processes to assess their significance and effects over time.

The oil price does not have statistical meaning, this can be understood that oil prices transferred to import prices but not to consumer prices

All results of VAR regression will be presented in Appendices; I just extract two results of import prices and consumer prices in here.

Impulse response function

With impulse response outcome we can trace out how typical shocks will affect a variable through time In this paper, I apply impulse response function for 24 months

5.4.1 Response to exchange rate of foreign price index

The foreign price index reflects how foreign exporters respond to changes in the exchange rate An impulse response function indicates that a 1% increase in the exchange rate leads to a 0.0198% rise in the foreign price index in the first month, suggesting that currency depreciation makes foreign goods more expensive However, in the second month, foreign exporters adjust their markups to maintain market share, resulting in a negative response of -0.394% in the foreign price index This decrease is temporary, as exporters eventually raise the foreign price index by 0.394% after regaining market share, followed by slight price reductions in subsequent months The overall response stabilizes within six months, with decreases approaching zero, indicating that exchange rate shocks have minimal long-term effects on foreign exporters' prices This outcome aligns with the understanding that foreign exporters wield more power in the global market compared to their Vietnamese counterparts.

25 importers Foreign exporters are price leaders and Vietnamese importers are price takers

Figure 5: Response to exchange rate of foreign price index

5.4.2 Response to exchange rate of import price index

A one percent change in the exchange rate results in a 0.970 percent increase in the import price index in the first month, followed by a slight decrease of -0.008 percent in the second month, and a more significant decline of -0.395 percent in the third month.

In the fourth and fifth months, the import price index shows a positive change, which gradually decreases to zero starting from the tenth month This response indicates that when an exchange rate shock occurs, its impact on import prices is almost fully realized within the first month, continues to affect prices in the second month, and diminishes by the third month.

The impulse response function (IRF) results indicate a significant relationship between the variables, with a 95% confidence interval The analysis focuses on the impact of changes in the exchange rate on total employment, highlighting the latest findings For further details, please contact via email at vbhtj mk gmail.com.

26 being familiar with new status of exchange rate, the import starts going back to its increase trending in fifth and sixth months and ending from tenth month

Figure 6: Response to exchange rate of import price index

5.4.3 Response to exchange rate of consumer price index

The impact of exchange rate fluctuations on consumer prices is relatively minimal, with a 1% increase in the exchange rate resulting in a consumer price index rise of only 0.109% in the first month, 0.118% in the second month, and 0.061% in the third month, gradually diminishing to zero by the twelfth month While the transmission of exchange rate changes to inflation is less significant than to import prices, the effect of exchange rate changes on inflation persists longer than their impact on imports.

The impulse response function (IRF) analysis indicates a significant relationship between the variables, with a 95% confidence interval The results suggest that changes in the exchange rate (dlneer1) have a notable impact on the total employment (dlimp) For further details, please refer to the latest research findings.

Figure 7: Response to exchange rate of consumer price index

5.4.4 Response to foreign price index of import price index

A 1% increase in foreign prices leads to an immediate 3.06% rise in import prices within the first month, indicating a rapid and complete response of imports to foreign market fluctuations This highlights the deep dependence of Vietnam's import activities on international market dynamics In the following two months, the import price index decreases significantly by -1.95% and -1.02%, respectively However, by the fourth and fifth months, the index begins to trend upward again, with the effects of these changes diminishing by the eleventh month.

The impulse response function (IRF) analysis indicates a significant relationship between the changes in the exchange rate (dlneer1) and the total consumer price index (dlcpi) The results are presented with a 95% confidence interval, highlighting the impact of exchange rate fluctuations on inflation dynamics For further details, please refer to the latest research findings.

Figure 8: Response to foreign price index of import price index

5.4.5 Response to foreign price index of consumer price index

The shock in the foreign price index results in a positive response in the consumer price index over a span of 24 months Initially, inflation rises by 0.121% in the first month, followed by increases of 0.185% in the second month, and 0.098% and 0.081% in the third and fourth months, respectively This trend continues until it diminishes by the eleventh month The transfer of shocks from the foreign price index to inflation is more stable and gradual compared to its effect on imports This is logical, as the import price index acts as a buffer, absorbing the shock before it impacts the consumer price index.

The impulse response function (IRF) results indicate a significant relationship between the variables, with a 95% confidence interval The analysis suggests that changes in the labor force participation index (dlfpi) have a notable impact on the total employment index (dlimp) For further details, please refer to the latest research findings.

Figure 9: Response to foreign price index of consumer price index

5.4.6 Response to output gap of money supply

In Figure 10, a positive output gap correlates with a decrease in money supply, indicating that the response of money supply to this positive shock is diminishing over time This trend reflects the State Bank of Vietnam's tightening monetary policy in response to rising inflation linked to an increasing output gap When real GDP exceeds potential GDP, the economy faces inflationary pressures, prompting the need to contract the money supply to mitigate inflation effectively.

The impulse response function (IRF) results indicate a significant relationship between the variables, specifically showing a 95% confidence interval for the response of the dependent variable to changes in the independent variable This analysis is crucial for understanding the dynamics of the economic model being studied.

Figure 10: Response to output gap of money supply

5.4.7 Response to output gap of consumer price index

The findings indicate that a 1% increase in the output gap leads to a 0.039% rise in the consumer price index in the first month and a 0.013% increase in the second month Although the response becomes negative in the third month, it turns positive again in the fourth month with a slight increase of -0.0046% and remains positive in subsequent months While the impact of the output gap on inflation is relatively small, the results from variance decomposition confirm that it is the second most significant factor influencing inflation movements.

The impulse response function (IRF) results indicate a 95% confidence interval, highlighting the relationship between the gap and the total employment dynamics For the latest updates, please refer to the provided email for further inquiries.

Figure 11: Response to output gap of consumer price index

5.4.8 Response to money supply of consumer price index

An increase of 1% in the money supply by the State Bank leads to a 0.039% rise in the consumer price index (CPI) in the first month and 0.067% in the second month, with subsequent months showing negative CPI responses in the third and fourth months, followed by positive responses in later months This indicates that the impact of money supply expansion on inflation is minimal, allowing the State Bank to implement monetary policies with greater flexibility The State Bank of Vietnam adjusts its monetary policy based on changes in the economic gap to mitigate inflation, as discussed in section 5.4.6.

This helped minimizing the effect of money supply to inflation and the State Bank is doing well with monetary policy

Variance decomposition

Variance decomposition identifies the key shocks that significantly influence the variance or fluctuations of a variable over time Similar to the impulse response function, the analysis period for variance decomposition is set at 24 months.

The forecast error variance decomposition indicates that the output gap is the primary factor influencing the import price index over time, accounting for 32% of the variance Following this, the foreign price index contributes 7.5%, and the money supply accounts for 7% In contrast, the exchange rate only explains 3.6% of the variance These findings suggest that domestic demand pressure is the dominant driver of import price fluctuations, while the exchange rate is less significant than anticipated.

Regarding the movement of consumer price index, the cause of foreign price index and gap take account for 18.7% and 14.5% respectively Factors money supply and

The impulse response function (IRF) analysis indicates a significant relationship between changes in consumer price index (CPI) and money supply (M2) The results, presented with a 95% confidence interval, highlight the dynamic interactions within the economic model For further details, please refer to the latest research findings available at the provided email address.

The exchange rate contributes a small percentage to the consumer price index, accounting for 2.48% and 5.4%, respectively Additionally, the impact of imports on inflation is minimal, at around 2% Notably, self-explanatory factors of inflation represent a significant average of 56.7% This suggests that current inflation is influenced by past indices; higher inflation shocks in previous periods lead to greater expected inflation in the present.

The output gap accounts for approximately 9.1% of the fluctuations in the money supply, whereas the exchange rate contributes only 4.9% This indicates that monetary policy is primarily guided by the output gap rather than the exchange rate Additionally, the money supply explains about 8.5% of the variations in the output gap.

Technically, there is a close relationship between output gap and money supply.

Granger causality test

Null hypothesis of Granger causality test is “X does not Granger cause Y”; the test results will tell us whether variable X be useful predicting variable Y

Granger causality indicates a statistical correlation between the current value of one variable and the historical values of others, suggesting that information from variables up to lag $ p $ holds statistical significance However, it is important to note that this does not imply that changes in one variable directly cause changes in another, as the relationship relies on the underlying statistical properties of the data.

The result shows that no variable Granger-causes exchange rate This means no information of all variables is useful to explain for the change of exchange rate

Oppositely, to consumer price index, all variables Granger-cause domestic inflation, this means all variables in the model can be used to predict the change of domestic price index

The foreign price index is primarily influenced by the output gap, which Granger-causes changes in it This relationship is logical, as domestic demand pressure serves as the fundamental factor affecting the foreign price index.

The output gap is influenced by the money supply and the consumer price index, both of which Granger-cause it Similarly, the money supply is affected by the output gap and the consumer price index, indicating a reciprocal relationship among these economic indicators.

Foreign price index and output gap Granger-cause import price index.

VAR stable

After conducting VAR regression, Impulse-Response Function analysis, Variance Decomposition, and the Granger causality test, I will assess the stability of the VAR model by checking the eigenvalue stability condition The results, illustrated in Figure 16, indicate that all eigenvalues are located within the unit circle, confirming that the VAR model meets the stability condition.

The real roots of the companion matrix are essential for understanding the properties of polynomials This analysis is crucial for academic research and can be beneficial for graduate theses For the latest updates and resources, please refer to the provided email for further assistance.

Lagrange multiplier test

Based on result of Lagrange multiplier test, we cannot reject Ho (no auto correlation at lag order) at 5% level It means there is no residual autocorrelation at lag order 2

However there is residual autocorrelation at lag order 1

Table 3: Larange multiplier test Lagrange-multiplier test

| lag | chi2 df Prob > chi2 | | -+ -|

| 1 | 54.5042 36 0.02465 | | 2 | 32.2289 36 0.64862 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

Conclusion, Policy Recommendation and Future Work

Conclusion

This study investigates the exchange rate pass-through (ERPT) to Vietnam's import and domestic prices through a VAR approach, utilizing impulse-response functions and variance decomposition to assess the magnitude and speed of the pass-through effect Additionally, Granger causality and VAR stability tests were conducted, yielding results consistent with the VAR regression analysis.

My research indicates that import prices respond immediately and significantly to fluctuations in exchange rates, with this response diminishing over approximately ten months In contrast, consumer prices exhibit a slower and weaker reaction to exchange rate changes, which is expected as the exchange rate pass-through (ERPT) operates through the channel of import prices Notably, the impact on consumer prices persists for a longer duration compared to that on import prices.

The relationship between money supply, output gap, import prices, and consumer prices indicates that the State Bank of Vietnam is effectively managing its monetary policy The adjustments in money supply are timely and appropriately respond to fluctuations in the output gap, import prices, and consumer prices.

Thanks to the effective monetary policy management by the State Bank, the expansion of the money supply has minimal impact on inflation This allows the government to focus on economic development policies without significant concern over inflationary pressures.

Variance decomposition analysis indicates that the output gap significantly influences the fluctuations in the import price index Domestic demand pressures have severely impacted Vietnam's imports, highlighting a critical shortage of material resources for manufacturing Consequently, the economy remains heavily reliant on foreign goods for production.

The output gap significantly influences inflation trends, indicating that Vietnam's economy is experiencing demand-pull inflation As the economy expands rapidly, its capacity struggles to keep pace with this growth, leading to inflation as a direct result of this imbalance.

The exchange rate has a minimal effect on the consumer price index (CPI), whereas foreign price indices and the output gap significantly influence the CPI Consequently, inflation from other countries is imported into Vietnam.

Domestic demand and foreign price indices equally contribute to inflationary pressures in Vietnam, resulting in the country facing inflationary challenges from both internal and external factors.

The variance decomposition analysis reveals that the exchange rate accounts for over 90% of its own fluctuations, indicating a strong self-explanatory nature Vietnam operates under a fixed exchange rate regime, placing the responsibility on the State Bank to manage the exchange rate in response to economic policy changes and economic fluctuations However, the findings suggest that the State Bank has not adequately adjusted to these changes in a timely manner Additionally, Granger causality results further support this issue, showing that no variable can effectively predict changes in the exchange rate.

It is common practice to use the industrial production index as a proxy for the gap variable; however, this may not be an effective measure for Vietnam's economy.

Because Vietnam has not yet become an industrial country, industrial production index will not well reflect all activities of Vietnam’s economy.

Policy Recommendation

The government should focus on the output gap, as it significantly impacts both the import price index and the consumer price index Inflation primarily stems from demand-pull factors linked to the excessive rise in real GDP The aggregate demand can be expressed with the formula \$AD = C + I + G + NX\$ One effective strategy to mitigate inflation is to reduce government spending on inefficient investments.

Expanding the economy's capacity is essential for reducing inflation and enhancing potential output When demand exceeds supply, it indicates inefficient use of production factors Therefore, the government should promote resource utilization, particularly in the private sector, where companies are driven by strong economic incentives to optimize efficiency and ensure their survival in the market.

The government should focus on restructuring the economy to foster the development of intermediate goods industries This initiative will create a robust industrial production chain in Vietnam, reducing reliance on foreign imports and promoting stable, independent production By enhancing the production of intermediate goods, domestic demand issues can be addressed, which in turn helps mitigate inflation concerns.

Despite empirical evidence indicating that the exchange rate is not the primary driver of import and inflation challenges, the State Bank of Vietnam must exercise caution when considering the depreciation of the VND Currently, dollarization is significant in Vietnam, accounting for 30% of total broad money, according to the ADB A depreciation of the VND could exacerbate this situation, leading to a loss of confidence in the currency and prompting individuals to seek refuge in more stable currencies like the US dollar, Euro, or Japanese Yen.

Future Work

Examining the Exchange Rate Pass-Through (ERPT) at a disaggregated level allows us to identify which industries and types of goods are most and least affected by currency depreciation Understanding this internal structure provides a clearer picture of how ERPT influences import prices and inflation in Vietnam.

Beirne, J., Bijsterbosch, M (2009) Exchange rate pass-through in central and eastern

European member states Working Paper 1120 European Central Bank, Euro System

Campa, M., J., Goldberg, L., S., & Koujianou, P (2002) Exchange rate pass- through into import prices: A macro or micro phenomenon NBER Working Paper

Campa, J., M., Goldberg, L., S (2005) Exchange rate pass-through into import prices Review of Economics and Statistics, Vol 87, pages 679.90

Campa, J., M., Goldberg, L., S., & Gonzalez, J., M (2005) Exchange rate pass- through to import prices in the euro area NBER Working Paper 11632

Faruquee, H (2006) Exchange rate pass-through in euro area IMF Staff Papers, Vol.53, No.1

Ihrig, J., Marazzi,M., & Rothenberg, A.(2006) Exchange-rate pass-through in the G-7 countries International Finance Discussion Papers 851

Jin, X (2010) An empirical study of exchange rate pass through in china Ludwig Maximilians University Munich, Munich Graduate School of Economics

Lin, H (2006) Exchange rate pass-through into import prices across industries in New Zealand Massey University, Albany

Marazzi et al (2005) provide new evidence on the exchange rate pass-through to U.S import prices, highlighting the significant impact of exchange rate fluctuations on import costs Their findings contribute to the understanding of how currency movements influence pricing in the U.S market, which is crucial for policymakers and economists The study emphasizes the importance of considering exchange rate dynamics when analyzing import price trends.

McCarthy, J (2000) Pass-through of exchange rates and import prices to domestic inflation in some industrialized economies Working Paper 79, Bank for

Mumtaz, H., OOmen,ệ., & Wang, J Exchange rate pass-through into UK import prices Working paper 312, Bank of England

Nguyen, H., T., T (2011) Exchange rate in Vietnam: trend and management

Vietnam’s Socio-Economic Development Working paper 67

Nguyen, H., T., T., & Nguyen, T., D (2010) Macroeconomic determinants of Vietnam’s inflation 2000-2010: evidence and analysis Vietnam Centre for Economic and Policy Research University of Economics and Business, Vietnam National University Hanoi

Rowland, P Exchange rate pass- through to domestic prices: The case of Colombia

Sarno, L., Taylor, M., P (2003) The economics of exchange rates New York:

Stulz, J (2006) Exchange rate pass-through in Switzerland: Evidence from vector autoregressions Mimeo, February

Vo,V M (2009) Exchange rate pass-through into import prices and its implication for inflation in Vietnam Vietnam Development Forum Working Paper 0902

Vo, T.T., Dinh, H.M., Do, X.T., Hoang, V T., & Pham, C Q (2000) Exchange rate arrangement in vietnam: Information contain and policy option Individual research project, East Asian Development Network

Yang (1997) investigates the phenomenon of exchange rate pass-through in U.S manufacturing industries, highlighting its implications for pricing strategies and economic policy The study, published in The Review of Economics and Statistics, provides valuable insights into how fluctuations in exchange rates affect domestic prices across various sectors This research is essential for understanding the broader economic impacts of currency movements on manufacturing performance.

Zorzi, M., C., Hahn, E., Sanchez, M (2007) Exchange rate pass-through in emerging markets Working Paper 739 European Central Bank, Euro System

International Monetary Fund (2011) International Financial Statistics Available from www.imfstatistics.org

Vietnam General Statistics Office (2011) Import goods by SITC [Data file]

The article discusses the latest updates on graduate thesis downloads from the official GSO website It emphasizes the importance of accessing full versions of academic papers and provides guidance on how to retrieve these documents effectively For further information, users are encouraged to visit the GSO website directly.

Import price index is calculated basing on the import trade weight between Vietnam with partners following with the formula:

Vietnam's import trade weight, denoted as \$w_i\$, is influenced by its 20 main trading partners, which include Japan, Singapore, China, South Korea, Thailand, Australia, Hong Kong, Germany, Malaysia, France, Indonesia, the United Kingdom, the Netherlands, Russia, the Philippines, Switzerland, Italy, Belgium, and India.

Measuring NEER and Real Effective Exchange Rate (REER): where:

Vietnam has numerous trading partners, denoted as N The exchange rate between the Vietnamese Dong (VND) and the currency of each trading partner is calculated using the indirect method, as direct exchange rates are unavailable This involves converting the VND to USD and the respective currency to USD Exchange rate data is sourced from the International Financial Statistics (IFS).

The results are calculated using a specific formula For the latest updates, please download the full document For further inquiries, you can reach out via email at vbhtj mk gmail.com.

46 where is the exchange rate between respective currency v.s USD is the trade weight of economy i with Vietnam; and are CPI of Vietnam and trading partner i, respectively

Based on Campa and Goldberg (2002), the exporters’ cost is calculated as follows:

Where REER is real effective exchange rate, NEER is nominal effective exchange rate, is domestic price index

Table 4: ADF test of dlneer1

Dickey-Fuller test for unit root Number of obs = 152 - Interpolated Dickey-Fuller - Test 1% Critical 5% Critical 10% Critical Statistic Value Value Value - Z(t) -15.102 -3.493 -2.887 -2.577 - MacKinnon approximate p-value for Z(t) = 0.0000

Table 5: ADF test of dlimp

The Dickey-Fuller test for unit root was conducted with 152 observations The interpolated Dickey-Fuller statistic, Z(t), yielded a value of -15.923, which is significantly lower than the critical values at the 1% (-3.493), 5% (-2.887), and 10% (-2.577) levels The MacKinnon approximate p-value for Z(t) is 0.0000, indicating strong evidence against the null hypothesis of a unit root.

Table 6: ADF test of dlcpi

Table 7: ADF test of dlm2

Table 8: ADF test of dlopi

Table 9: ADF test of dlpi

The Dickey-Fuller test for unit root was conducted with 152 observations The interpolated results show a test statistic value of Z(t) = -18.234, which is significantly lower than the critical values at the 1% (-3.493), 5% (-2.887), and 10% (-2.577) levels The MacKinnon approximate p-value for Z(t) is 0.0000, indicating strong evidence against the presence of a unit root in the data.

Selection-order criteria Sample: 1999m6 - 2011m10, but with a gap Number of obs = 127 + -+

|lag | LL LR df p FPE AIC HQIC SBIC | | + -|

Endogenous: dlneer1 dlimp dlcpi dlfpi dlm2 gap Exogenous: dlopi _cons

| dlneer1 dlfpi | 5.0071 2 0.082 | | dlneer1 gap | 2.9406 2 0.230 | | dlneer1 dlm2 | 1.754 2 0.416 | | dlneer1 dlimp | 1.1475 2 0.563 | | dlneer1 dlcpi | 1.4137 2 0.493 | | dlneer1 ALL | 13.415 10 0.201 | | -+ -|

| dlfpi dlneer1 | 41083 2 0.814 | | dlfpi gap | 7.668 2 0.022 | | dlfpi dlm2 | 5.7014 2 0.058 | | dlfpi dlimp | 4.5089 2 0.105 | | dlfpi dlcpi | 13646 2 0.934 | | dlfpi ALL | 18.276 10 0.050 | | -+ -|

| gap dlneer1 | 49956 2 0.779 | | gap dlfpi | 2.8598 2 0.239 | | gap dlm2 | 13.084 2 0.001 | | gap dlimp | 3.0135 2 0.222 | | gap dlcpi | 10.111 2 0.006 | | gap ALL | 32.222 10 0.000 | | -+ -|

| dlm2 gap | 7.6289 2 0.022 | | dlm2 dlimp | 1.3334 2 0.513 | | dlm2 dlcpi | 6.4592 2 0.040 | | dlm2 ALL | 28.136 10 0.002 | | -+ -|

| dlimp dlneer1 | 3.0772 2 0.215 | | dlimp dlfpi | 13.353 2 0.001 | | dlimp gap | 37.57 2 0.000 | | dlimp dlm2 | 3.0471 2 0.218 | | dlimp dlcpi | 3.9075 2 0.142 | | dlimp ALL | 65.465 10 0.000 | | -+ -|

The analysis reveals significant relationships among various variables, with the highest correlation observed between "dlcpi" and "gap" at a value of 31.125, indicating a strong association (p < 0.000) Additionally, "dlcpi" shows a notable connection with "dlfpi" (15.046, p < 0.001) and "dlimp" (9.9132, p < 0.007) The overall model, represented by "dlcpi ALL," demonstrates a robust fit with a total value of 106.71 (p < 0.000), while "dlcpi" and "dlm2" present a marginally significant relationship (5.7998, p = 0.055).

Sample: 1999m4 - 2011m10, but with a gap No of obs = 131 Log likelihood = 1840.494 AIC = -26.72509 FPE = 1.00e-19 HQIC = -25.92243 Det(Sigma_ml) = 2.52e-20 SBIC = -24.74977

Equation Parms RMSE R-sq chi2 P>chi2 - dlneer1 15 025318 0.1526 23.59149 0.0513 dlfpi 15 017008 0.2992 55.91954 0.0000 gap 15 077665 0.3061 57.77827 0.0000 dlm2 15 015675 0.2394 41.23188 0.0002 dlimp 15 123984 0.5277 146.3719 0.0000 dlcpi 15 005916 0.6409 233.8129 0.0000 -

- | Coef Std Err z P>|z| [95% Conf Interval]

-+ - dlneer1 | dlneer1 | L1 | -.0681238 1253736 -0.54 0.587 -.3138515 1776038 L2 | -.0823673 1275991 -0.65 0.519 -.3324569 1677222 | dlfpi | L1 | 3366186 1755472 1.92 0.055 -.0074477 6806849 L2 | 0368577 1800849 0.20 0.838 -.3161022 3898176 | tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

The analysis reveals various coefficients across different models, indicating the relationships between variables For instance, the gap shows a coefficient of 0.51 in L1, with a p-value of 0.609, suggesting a lack of statistical significance In contrast, the dlfpi variable demonstrates a significant negative impact in L1, with a coefficient of -0.4906391 and a p-value of 0.000, indicating strong evidence against the null hypothesis Additionally, the dlcpi variable presents a coefficient of -0.3843468 in L1, but lacks significance with a p-value of 0.206 Overall, the results highlight the varying degrees of influence among the examined variables, with some showing potential significance while others do not.

The analysis reveals significant findings across various variables For instance, the coefficient for L2 in the model shows a negative impact of -0.0533727 with a p-value of 0.009, indicating statistical significance In contrast, L1 for the same variable presents a non-significant result with a coefficient of -0.1057085 and a p-value of 0.273 Notably, L2 for dlimp demonstrates a positive effect of 0.2071339 with a p-value of 0.031, suggesting a significant relationship Additionally, dlcpi's L2 coefficient of 0.0200781 is significant at a p-value of 0.033 However, L1 for dlopi shows no significant effect, while the overall gap analysis indicates a significant negative coefficient of -0.3185222 for L2 with a p-value of 0.001, highlighting critical insights into the data trends.

The analysis of the model reveals significant findings, particularly with the variable "gap," which shows a positive relationship with a coefficient of \$0.0472105\$ and a p-value of \$0.012\$, indicating statistical significance Conversely, the variable "dlm2" presents mixed results, with L1 showing a coefficient of \$-1.098802\$ and a p-value of \$0.013\$, while L2 has a coefficient of \$-0.9087833\$ and a p-value of \$0.038\$ Other variables, such as "dlimp" and "dlcpi," exhibit coefficients that suggest no strong significance, with p-values above \$0.05\$ Overall, the findings highlight the importance of the "gap" variable in the model while indicating that further investigation is needed for other variables.

The analysis reveals significant findings regarding various economic indicators The variable "dlimp" shows a positive coefficient in L1, indicating a potential influence, although it is not statistically significant (p = 0.294) In contrast, "dlopi" demonstrates a noteworthy negative impact in L2 with a p-value of 0.031, suggesting a significant relationship The "dlfpi" variable exhibits a strong positive correlation in L1 (p < 0.001), while "gap" indicates a significant negative effect in both L1 and L2, with p-values of 0.044 and 0.000, respectively Overall, these results highlight the importance of understanding the dynamics between these economic factors.

The analysis reveals significant findings regarding the impact of various economic indicators The variable dlimp shows a strong negative correlation in both L1 and L2, with coefficients of -0.4459639 and -0.2724077, respectively, both statistically significant at p < 0.001 In contrast, the variable dlcpi exhibits a negative relationship, with L1 and L2 coefficients of -1.210869 and -1.426147, but lacks statistical significance The variable dlopi shows no significant effect, while dlopi_2 demonstrates a positive and significant impact with a coefficient of 0.4063403 at p < 0.001 Additionally, the variable dlneer1 shows a positive correlation in both L1 and L2, with significant coefficients of 0.1036844 and 0.0683652, respectively The dlfpi variable also indicates a positive and significant relationship, with coefficients of 0.1136289 and 0.1266206 The gap variable presents mixed results, with L1 being insignificant and L2 showing a significant positive effect Lastly, the variable dlm2 shows no significant impact in L1, while L2 approaches significance Overall, these findings highlight the complex interactions between economic indicators and their implications for further research.

L2 | 0090365 0032814 2.75 0.006 002605 015468 | dlcpi | L1 | 4202509 0709991 5.92 0.000 2810953 5594065 L2 | 3560058 0717675 4.96 0.000 215344 4966676 | dlopi | 004773 0060364 0.79 0.429 -.0070581 016604 dlopi_2 | -.0066267 0059361 -1.12 0.264 -.0182613 0050078 _cons | -.0019207 0012385 -1.55 0.121 -.0043481 0005067 - tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

Table 13: Impulse - Response Function impulse = dlneer1, response = dlneer1 impulse = dlneer1, response = dlfpi impulse = dlneer1, response = gap + -+

|24 | 000031 -.000149 000212 | -9.9e-06 -.000072 000052 | -.000115 -.000926 000695 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

58 impulse = dlneer1, response = dlm2 impulse = dlneer1, response = dlimp impulse = dlneer1, response = dlcpi + -+

|24 | -.000177 -.00095 000597 | -.000056 -.000488 000376 | 000171 -.000705 001047 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

59 impulse = dlfpi, response = dlneer1 impulse = dlfpi, response = dlfpi impulse = dlfpi, response = gap + -+

|24 | 000051 -.000216 000317 | -.00002 -.000116 000075 | -.000174 -.001402 001054 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

60 impulse = dlfpi, response = dlm2 impulse = dlfpi, response = dlimp impulse = dlfpi, response = dlcpi + -+

61 impulse = gap, response = dlneer1 impulse = gap, response = dlfpi impulse = gap, response = gap + -+

|24 | 3.1e-06 -.000021 000027 | -1.9e-06 -.000016 000012 | -.000041 -.000199 000117 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

62 impulse = gap, response = dlm2 impulse = gap, response = dlimp impulse = gap, response = dlcpi + -+

63 impulse = dlm2, response = dlneer1 impulse = dlm2, response = dlfpi impulse = dlm2, response = gap + -+

|24 | 6.2e-06 -.000078 00009 | 2.7e-06 -.000044 000049 | -.000107 -.000537 000324 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

64 impulse = dlm2, response = dlm2 impulse = dlm2, response = dlimp impulse = dlm2, response = dlcpi + -+

|24 | -.000079 -.000406 000247 | 000012 -.000696 000719 | 000073 -.000266 000412 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

65 impulse = dlimp, response = dlneer1 impulse = dlimp, response = dlfpi impulse = dlimp, response = gap + -+

|24 | 2.5e-06 -.000011 000016 | -7.9e-07 -7.7e-06 6.2e-06 | -4.3e-06 -.000063 000055 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

66 impulse = dlimp, response = dlm2 impulse = dlimp, response = dlimp impulse = dlimp, response = dlcpi + -+

|24 | -.000012 -.000063 000039 | -1.3e-06 -.000077 000074 | 000011 -.000047 00007 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

67 impulse = dlcpi, response = dlneer1 impulse = dlcpi, response = dlfpi impulse = dlcpi, response = gap + -+

|24 | 000149 -.000722 001021 | -.000048 -.000343 000248 | -.000644 -.004571 003283 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

68 impulse = dlcpi, response = dlm2 impulse = dlcpi, response = dlimp impulse = dlcpi, response = dlcpi + -+

Table 14: Variance decomposition impulse = dlneer1, response = dlneer1 impulse = dlneer1, response = dlfpi impulse = dlneer1, response = gap + -+

|24 | 907184 810101 1.00427 | 423322 281412 565233 | 065678 -.017903 149259 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

70 impulse = dlneer1, response = dlm2 impulse = dlneer1, response = dlimp impulse = dlneer1, response = dlcpi + -+

|24 | 049216 -.013596 112029 | 036338 -.026206 098882 | 05439 -.030321 139101 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

71 impulse = dlfpi, response = dlneer1 impulse = dlfpi, response = dlfpi impulse = dlfpi, response = gap + -+

|24 | 038587 -.024928 102101 | 47058 336026 605133 | 009933 -.020106 039972 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

72 impulse = dlfpi, response = dlm2 impulse = dlfpi, response = dlimp impulse = dlfpi, response = dlcpi + -+

|24 | 028849 -.011576 069274 | 075676 -.011699 16305 | 187251 044065 330437 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

73 impulse = gap, response = dlneer1 impulse = gap, response = dlfpi impulse = gap, response = gap + -+

74 impulse = gap, response = dlm2 impulse = gap, response = dlimp impulse = gap, response = dlcpi + -+

|24 | 091778 007686 17587 | 327661 195239 460084 | 145003 037125 252881 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

75 impulse = dlm2, response = dlneer1 impulse = dlm2, response = dlfpi impulse = dlm2, response = gap + -+

76 impulse = dlm2, response = dlm2 impulse = dlm2, response = dlimp impulse = dlm2, response = dlcpi + -+

|24 | 782699 656428 908969 | 070525 002768 138282 | 024886 -.024739 074512 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

77 impulse = dlimp, response = dlneer1 impulse = dlimp, response = dlfpi impulse = dlimp, response = gap + -+

78 impulse = dlimp, response = dlm2 impulse = dlimp, response = dlimp impulse = dlimp, response = dlcpi + -+

|24 | 008235 -.012376 028847 | 482597 351004 614189 | 020847 -.013095 054789 | + -+ tot nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg

79 impulse = dlcpi, response = dlneer1 impulse = dlcpi, response = dlfpi impulse = dlcpi, response = gap + -+

Tiêu đề	Exchange Rate Pass-Through to Vietnam’s Import and Domestic Prices
Tác giả	Cai Bao Hieu
Người hướng dẫn	Dr. Dinh Cong Khai
Trường học	University of Economics
Chuyên ngành	Development Economics
Thể loại	Thesis
Năm xuất bản	2012
Thành phố	Ho Chi Minh City

Định dạng
Số trang	89
Dung lượng	1,24 MB