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Introduction

Introduction

           I.  Background and relevance of the topic

         Inflation re-emerged in 1990 and 1991, up to 67.5% and 67.6%, respectively. In 1992, it was at 17.5% and fell to 5.2% in 1993. Then, it rose to 14.4% in 1994 and to 12.7% in 1995. It fell fast to 4.5% in 1996, to 3.6% in 1997, up to 9.2% in 1998.

         It is evident that higher inflation rate tends to be associated with lower growth rate. However, In 1999 Vietnam faced a new and great challenge: a sharp fall in inflation rate (to 0.1%), accompanied by a low economic growth rate (4.8%). The issue of too low inflation is now at the center of much debate among economists.

         The debate about appropriate macro policy responses has raised questions about main factors involved in inflation and whether the magnitude of these factors determining inflation has been stable or not in Vietnam during 1991-1999.

        II.  Focus and scope of the thesis

          To  investigate the fundamental determinants of inflation in Vietnam by the model.

          To  recommend macroeconomic policy implications within the new circumstances.

          To  examine determinants of inflation in Vietnam from January 1991 to May 1999.

           III.  Research questions

         1. What are fundamental determinants of inflation in Vietnam during 1991 - 1999 ?

         2. Has the magnitude of the determinants of inflation stabilised during 1991-1999?      

         3. What are macroeconomic policy implications concerning Vietnam determinants of inflation in the context of the goal of achieving high economic growth?

           IV.  Methodology of the thesis

          The main method of analysis used to study the inflation is the quantitative method.

         Monthly secondary data in the thesis is provided by the CIEM, SBV, GSO and IMF

           V.  Structure of the thesis

         Chapter 1 presents theoretical foundation of inflation and two empirical evidences.

         Chapter 2 presents the financial reform  & the evolution of the inflation in Vietnam.

         Chapter 3 quantitatively analyzes the determinants of inflation during 1991 - 1999.

         Chapter 4 summarizes the primary findings  & macroeconomic policy implications.

Chapter 1:   Theoretical  framework

                 1.1.  Definition, Measurement and Classification of Inflation

         Inflation is a process of continuously rising prices, which are measured by CPI.

         Inflation rate measurement is also calculated as follows: pt = (Pt -Pt-1)*100/ Pt-1.

         Three main types: demand-pull inflation, cost-push inflation, structural inflation.

                 1.2.  Structuralist Approach to Inflation

                Causes: inelastic supply of foodstuffs, foreign exchange and budget constraint.

                Inflation is seen to be unavoidable in an economy attempting to grow very fast.

                 1.3. Monetarist Approach to Inflation

                Causes: a rise in money supply in classical money quantity theory: M´V = P´ Y                   

         and based mainly on the quantity function of Monetarist theory: P´Y = (1/k) ´ M.

         Inflation is regarded as the fundamental monetary phenomenon in an economy

                 1.4. Consequences of inflation

                Monetarist view: Price stability is a prerequisite for sustained economic growth.

                Structuralist view: Inflation is seen as a mean of accelerating economic growth.

                      Both schools' view: Inverted U_shaped relationship between inflation & growth.

                 1.5.  methods to fight inflation

                The Orthodox ( mainly according to the Monetarists) Approach to fight inflation.

                The Heterodox ( mainly based on the Structuralists ) Approach to fight inflation.

                1.6.  Theory-based foundation for determinants of inflation

           Equilibrium condition in money market  -Definitional equation for money velocity

                                 and                                                       

                1.7.  Empirical investigation of determinants of inflation

           Lag technique illustrated by Malaysia's instance of the determinants of inflation.

           Cointegration technique through Negeria's example of determinants of inflation.

                 1.8.  Chapter remarks

                Applying the broad monetarist model taking into account structuralist variables.

           Lag technique used to estimate Vietnam's distributed-lagged model of inflation.

        CHAPTER 2:  Vietnam's Financial REFORM AND INFLATION

            2.1.    Financial reform in Vietnam

            2.1.1. INSTITUTIONAL REFORM

           The reform of financial system in Vietnam is regarded as banking system reform.

            First basic steps in reforming the banking system made in mid - 1988 in Vietnam.

   Nevertheless, the two - tier banking system really was established in May , 1990.

   Moreover, the second steps in the banking system reform have done since 1992.

            2.1.2. MONETARY POLICY INSTRUMENT REFORM 

                  State Bank of Vietnam still relies heavily on direct instruments of monetary policy

       Some principal "price-based" instruments are still very underdeveloped presently.

      Five main instruments of monetary policy are the interest rate, the credit ceilings, the required reserve ratios, the refinancing facilities and the treasury bill auctions.

       Financial reform in Vietnam has several positive effects on the control of inflation.


Source: ADB (1999); IMF(1999); CIEM (2000).

Source: Thanh (1996); IMF(1999); CIEM (2000); (Note that: index 1989 = 100).

                  Chapter 3:  Econometric evidence of model specification

                3.1.   Description of data

                  3.2.    Empirical model specification and validity

              3.2.1.Model Specification

                   The distributed-lag model of determinants of inflation during 1991:1-1999:5.

                

              Where: p and gM are the inflation rate & nominal money supply growth rate;  gY is the real output growth rate and v  is minus of the rate of return on US dollars circulating in the domestic economy (percentage) and pe is the expected inflation rate.

               Cumulative coefficients of determinants of inflation have its signs as follows:

              åaiM > 0,     åaiY < 0,      åaiv > 0,      åaipe > 0.                              

                   3.2.2.Unit Root Test for Stationary

              Augmented Dickey-Fuller (ADF) tests show that all series: p, gM1, gM2, gY, v are integrated of order zero or stationary at five percent significance level.

Table 8: Unit Root Tests for Stationary.

        Variable

            ADF  Statistic for b1

        ADF Critical Value (at 5%)

     1991:1-1998:12

1991:1-1999:5

1991:1-1998:12

 1991:1-1999:5

        p

-2.904

-3.118 & -4.915

-2.890

    -2.890 & -2.890

 

        gM1

-3.801

-3.963

-3.463

     -3.458

 

        gM2

-3.417

-3.936

-2.890

     -3.463

 

        v=e(Market)-id

 

-3.968 & -3.695

 

    -3.459 & -3.465

 

        v=e(Office)-id

-8.816

 

-3.538

 

 

        gY

-7.940

-6.719 & -8.706

-3.459

    -3.459 & -3.457

 

           Note:  ADF critical value at 5 %  in the sample size of 100 is about -2.89  (Maddala, 1992).

                        Source:  Author's calculations based on data during 1991:1 - 1999:5  in the model specification  (1).

          3.2.3. Lag Lengths of Each Determinant

                 The lags of the determinants of inflation in the model (1) are chosen in line with a sequential procedure by Hsiao (1981) on the basis of Akaike’s FPE.

          Table 9: The specifications of the model (1) for the cases of M1 and M2.

           1991:1-1998:12  and  e(Office)

                    1991:1 - 1999:5    and    e(Market)

           Case of M1

     Case of M2

 Case of M1

       Case of M2

         gM1 (nM1 = 5)

  gM2 (nM2 = 6)

 gM1 (nM1 = 3)

   gM2 (nM2 = 6)

         gY    (nY  = 1)

  gY   (nY  = 1)

gY    (nY =  4)

   gY    (nY  = 1)

         pe     (npe = 8)

  pe    (npe  = 8)

pe     (npe =11)

   pe      (npe = 9)

         v      (nv = 8)

  v     (nv  = 8)

v      (nv =  4)

   v       (nv = 5)

                     List of determinants shows the sequence of the choice according to Hsiao’s procedure

                    3.3.   Estimation results, hypothesis testing & interpretation

              3.3.1. Results and hypothesis testing during 1991-1999

                We use M1, M2 in combination with e(Office) and e(Market) to divide the model  estimation into four cases. The results are seen in tables 10, 11, 12 and 13.

                   Hypothesis testing for the estimation results is carefully under consideration.

                 +    T-Test for significance of regression coefficients

                 +    LM Test for Serial correlation

                 +    Jarque-Bera Test for Normality

                 +    White's Test for Heteroscedasticity

                 +    Ramsey's Reset Test for Functional Form

                 +    Cusum Test and Chow's test for stability of parameters

                 +    Wald Test for S(lag coefficients) = 0

                 +    Wald Test for S(lag coefficients of gM) = 1

                 +    F-statistic Test for the joint significant of the lags

            3.3.2. Interpretation of the estimation results during 1991-1999

           Generally, gM, gY, p-1, and v in model (1) are jointly significant at different significance levels 10%, 5% and 1%. Thus, they are useful predictors in explaining change in inflation rate during 1991:1-1998:12 and 1991:1-1999:5.

           Basically, gM, gY, v  and p-1 have long-lasting and significant impacts on inflation rate with their signs consistent with the economic theory's prediction.

             Compared with the results in table 10, 11 and 13, gY in table 12, apart from its long-lasting negative impacts, has its impacts on inflation in short duration.

            In essence, if the gM1 changes at some time, it will take one or two months for inflation rate to fully adjust to those changes in Vietnam during this period.

            If the gM2 changes, inflation will fully adjust to those changes in that current month or in one or two months later. In four cases mentioned above, inflation rate is very sensitive to short lags of the growth of the money supply growth.

                 If v changes at some time in the case of official exchange rate, it will take    one, two, three or four months for inflation to fully adjust to those changes.

                 If v changes in the presence of the parallel market exchange rate, it will take three months or five months later for inflation fully adjust to those changes. Moreover, the maximum impact of the significant lag of v is approximately four months in the presence of official exchange rate and is approximately five months in the presence of the parallel market exchange rate.

                 Based on the estimation results of the model specification, the impact of the current value and lag one of gY on inflation in four cases is statistically significant and negative, as expected. It could mean that the change in real industrial output is quite appropriate as a proxy for real income in Vietnam.

                 The estimation results of the model show that all four regressions contain the expected inflation, pe, as a determinant of the inflation in Vietnam. It can be seen from all cases that pe is also a useful predictor of the inflation rate. Such a determinant also has a long-lasting positive impact on the inflation rate in accordance with macroeconomic theory's prediction.

 

3.3.3.  Results and hypothesis testing during 1991-1994 and 1994-1999

     Because four regressions in tables 10, 11, 12 and 13 do not pass the test for structural stability under Cusum test, the stability of estimated parameters in such four regressions does not exist during 1991:1-1998:12 and during 1991:1999:5.

     This instability of the parameters in the model (1) in tables of 10, 11, 12, 13 can happen in October 1994. Based on Chow's test in tables 14, 16, 18 and 20, the null-hypothesis of the stability of the estimated parameters is also rejected.

     3.3.4.   Interpretation results during 1991-1994

    The estimation results of the model specification (1) during 1991:1-1994:10 are basically similar to those obtained during 1991:1-1998:12 and 1991:1-1999:5.

     3.3.5.   Interpretation results during 1994-1999

     During 1994:11-1998:12 and 1994:11-1999:5, the estimation results of the model are basically different from those during 1991:1-1998:12 and 1991:1-1999:5.

     The gM1 and gM2 have both a less long-lasting and short-lasting impact on inflation rate during 1994:11-1998:12 and during 1994:11-1999:5.

 The gY has only a long-lasting negative impact on inflation rate. Furthermore, the p-1 was not jointly significant in explaining the changes in the inflation rate.

     The coefficients of all the lags of v and the sum of its coefficients during 1994:11-1998:12 and 1994:11-1999:5 are not statistically significant. This suggests that exchange rate have no significant effects on inflation. The (deposit) interest rate policy has a less significant impact on inflation rate.

     3.4.    Macroeconomic Policy Implications

          This thesis finds that expected inflation possesses the valuable information of the price behaviour in the long run. Thus, firm commitment to controlling low and stable inflation should be a starting point in policy formulation to consolidate credibility in economic policies and the domestic currency and lower likelihood of high inflation in the future. In the context of too low inflation, more attentions should be paid to readjusting and controlling inflation at more reasonable levels (higher than 3 % and lower than 10 % per year, such as 6% or 7% in chart 10) with the aim of promoting high and sustained economic growth in Vietnam.

This thesis finds that nominal money supply growth (including gM1, gM2) is positively and significantly related to the inflation rate in Vietnam in the long run. Therefore, to sustain a low and stable inflation rate, it is best to provide the SBV greater autonomy in formulating and implementing monetary policy. In the long run, money supply management should be under prudent control by the SBV based on both demand and supply side.

          This thesis finds that the return rate on US dollars possesses the price behaviour information in the long run. The relation between the changes in exchange rate and (deposit) interest rate substantially affects a policy toward promoting VND. Such changes should be sustained reasonably so that inflation can be adjusted to this effort. Also, an active interest rate policy should be seen as a one not only of guaranteeing a just positive deposit interest rate in real terms, but of also taking into account the depreciation rate and interest rate for dollar deposits. Thus, the SBV's efforts to make VND more attractive via interest rate/exchange rate policies should be sustained to be higher effective to keep low inflation.

          This research finds that the magnitude of the determinants of inflation has changed greatly during 1991-1999. It is regarded as one of the main findings and very meaningful for Vietnam's policymakers. It also means that it is necessary and useful to modify some used macroeconomic policies to timely meet big changes in the Vietnam's economy presently.

                        +     Because one of Vietnam's most important goals in 1995-2000 is to obtain high growth, tight monetary policy in past years is not favourable for this goal. The loosened money supply performance in the short run has a less significantly positive impact on inflation compared to its performance in the long run. With new goal of high growth, in the short run the SBV should loosen its money supply management to stimulate demand in the context of ''too'' low inflation.

          +    Besides, although the direct monetary instruments are effective in controlling inflation, these may be harmful to the banking business. Thus, the SBV should enhance the use of indirect monetary policy measures. The reform of the credit policy is one priority.

          +     An active interest rate in defending VND is needed since it acts along with tight fiscal and monetary policy to form people's credibility in State's efforts to control inflation. Still, high deposit interest rates cause higher loan interest rates harmful for economy. SBV should manage interest rate policy (positive real terms) flexibly to promote high growth.

                Exchange rate has an insignificantly impact on inflation since November 1994. Hence, the devaluation of VND has insignificantly affected changes in inflation. Therefore, in the short run, the State Bank of Vietnam should carry out more flexible exchange rate policy to raise Vietnam's competitiveness, helping stimulate demand without fear of a significant rise in inflation.

                  Moreover, in the long run, it will be useful to relax the rigid exchange rate policy by the State Bank. There are two principal ways to enhance the effectiveness of its exchange rate management policy. The first is to introduce a basket of major trading partner currencies as a nominal anchor instead of only the US dollar. The second is that by widening the band, the VND can fluctuate more freely to reflect the market condition.

                 Chart 10:   Scatter plot of growth rate of GDP on Inflation rate in Vietnam.

                     Source:  Author's calculation  based on data collected from IMF (1991, 1999),  Thanh (1996).

 

 

Chapter 4:  Conclusion

           4.1.  Summary of main findings

                The thesis investigates crucial determinants of inflation based on a broad monetarist model that accounts for inflation movement due to changes in money supply and other factors determining the demand for real balances.

                The results show that the model (1) fits monthly data in 1991:1-1999:5 in Vietnam. During 1991:1- 1998:12 and 1991:1-1999:5, gM, gY, p-1 and v are useful predictors in explaining the change in inflation. Such determinants have a long-lasting impact on inflation with their right expected signs.

                  In the long run, tight monetary policy and positively real deposit interest rate policy and careful exchange rate policy have played an important role in controlling inflation in Vietnam in the process of further economic reform.

               In the short run, exchange rate had an insignificant effect on inflation rate. On the whole, the monetary policy has less significantly affected the change in inflation rate in Vietnam.

           4.2.  Policy recommendations

               Firm commitment to controlling and sustaining low inflation should be a starting point in policy formulation to consolidate people's credibility in economic policy and VND and lower likelihood of high inflation in the future.

               It is best to provide larger autonomy to Vietnam's State Bank in formulating and implementing monetary policy with the aim of both keeping inflation reasonable (5-7 % per year) and promoting high economic growth.

               In the long run, monetary policy (money supply& interest rate policy) and exchange rate policy should be under prudent control by SBV based on demand and supply side, aiming at keeping inflation low and stabilizing macroeconomic climate.

           In the short run, SBV should greatly loosen its monetary policy, especially money supply management policy within the context of too low inflation. SBV should carry out its more flexible exchange rate policy with the aim of stimulating demand, without the fear of causing high inflation in Vietnam.

Outline  for  estimating  the model in vietnam

Table 10: Estimation result in case of using M1 and e Office for Vietnam: 1991:1-1998:12

Lag

              gM1

               gY

     p-1 (pe)

v (e Office-id)

 

0

0.0023

(0.071)

-0.0620

(-2.99)***

 

-0.0136

(-0.375)

 

1

0.0974

(2.98)***

-0.0949

(-4.07)***

0.2253

(1.99)**

0.0927

(2.68)***

 

2

0.0693

(2.090)**

 

 

-0.0836

(-0.727)

0.0661

(1.939)*

 

3

-0.0104

(-0.305)

 

 

0.1829

(1.613)

0.0046

(0.130)

 

4

0.0305

(0.871)

 

 

0.1023

(0.957)

0.1069

(2.96)***

 

5

-0.0107

(-0.313)

 

 

-0.0149

(-0.142)

-0.0475

(-1.263)

 

6

 

 

 

0.0433

(0.471)

0.0276

(0.700)

 

7

 

 

 

-0.0113

(-0.119)

0.0026

(0.075)

 

8

 

 

 

0.0498

(0.618)

0.0366

(0.912)

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.1784

7.688***

-0.1569

24.90***

0.4938

18.7***

0.2760

9.994**

 

Wald test for åaiM=1

162.8***

 

 

 

 

F-statistic for the joint

significance of the lags.

2.790***

12.57***

2.78**

4.16***

 

Serial Correlation  (LM test, c2(12))    16.49[0.170]

R-squared                                     0.777

 

Normality (Jarque-Bera test, c2(2))     11.32[0.063]

Adjusted R Squared                     0.687

 

Heteroscedasticity                c2(1)       0.448[0.503] 

S.E.of Regression                         0.787

 

Functional Form                   c2(1)       0.498[0.480]

DW-statistic                                 1.736

 

       Note that:  *, **, and *** denote the significance at the 10%, 5%, and 1% levels, respectively.

       The figures in parentheses mentioned above are t-ratios;

 

Model's equation in Vietnam in 1991:1-1998:12. (Case of M1 and e Office).

 Source:  Author's calculations based on data during 1991:1-1998:12 (monthly data) in the model (1).

Table 11: Estimation result in case of using M2 and e Office  for Vietnam: 1991:1-1998:12

Lag

              gM2

               gY

 p-1 (pe)

v (e Office-id)

 

0

0.1216

(3.11)***

-0.0576

(-2.69)***

 

-0.0876

(-2.427)**

 

1

0.0512

(1.229)

-0.1054

(-4.76)***

0.1425

(1.255)

0.1005

(2.77)***

 

2

0.0966

(2.23)**

 

-0.0859

(-0.729)

0.0536

(1.505)

 

3

0.0233

(0.533)

 

0.1317

(1.127)

0.0140

(0.387)

 

4

0.0553

(1.268)

 

0.0752

(0.674)

0.1234

(3.42)***

 

5

0.0105

(0.253)

 

-0.1449

(-1.322)

-0.0330

(-0.821)

 

6

0.0178

(0.444)

 

0.1176

(1.162)

0.0074

(0.183)

 

7

 

 

-0.0578

(-0.567)

0.0238

(0.638)

 

8

 

 

0.1505

(1.810)*

0.0239

(0.608)

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.3763

6.513**

-0.1630

26.43***

0.3289

4.645**

0.2260

8.164**

 

Wald test for åaiM=1

17.83***

 

 

 

 

F-statistic for the joint

significance of the lags.

2.164**

14.23***

1.640*

4.256**

 

Serial correlation (LM test, c2(12))     16.77[0.158]

R- squared                                0.773

 

Normality (Jarque-Bera test, c2(2))     5.088[0.079]

Adjusted R Squared                 0.676

 

Heteroscedasticity                 c2(1)      0.758[0.384]

S.E.of Regression                     0.801

 

Functional Form                    c2(1)      0.682[0.409]

DW-statistic                             1.819

 

       We note that:  *, **, and *** denote the significance at the 10%, 5%, and 1% levels respectively. 

       The   figures in parentheses mentioned above are t-ratios;

 

Model's equation in Vietnam in 1991:1-1998:12. (Case of M2 and e Office).

 

Source:  Author's calculations based on data during 1991:1-1998:12 (monthly data) in the model (1).

Table 12: Estimation result in case of using M1 and e Market  for Vietnam: 1991:1-1999:5

Lag

gM1

 gY

p-1(pe)

v (e Market-id)

 

0

0.0250

(1.437)

-0.0526

(-2.41)**

 

0.0473

(0.812)

 

1

0.0747

(2.11)**

-0.0616

(-2.7)***

0.2702

(2.15)**

0.0250

(0.426)

 

2

0.0617

(1.89)*

0.0438

(1.837)*

0.1470

(1.254)

0.0195

(0.346)

 

3

-0.0453

(-1.375)

0.0394

(1.608)

0.1914

(1.77)*

0.1341

(2.50)**

 

4

 

0.0105

(0.407)

0.1157

(1.151)

-0.0233

(-0.474)

 

5

 

 

0.0487

(0.476)

 

 

6

 

 

-0.1169

(-1.178)

 

 

7

 

 

-0.0049

(-0.050)

 

 

8

 

 

0.0068

(0.071)

 

 

9

 

 

0.1345

(1.483)

 

 

10

 

 

-0.0290

(-0.324)

 

 

11

 

 

0.0312

(0.343)

 

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.1161

2.865*

-0.0205

0.088

    0.7947

  42.6***

0.2026

7.53***

 

Wald test for åaiM=1

165.9***

 

 

 

 

F-statistic for the joint

significance of the lags.

2.383*

5.20**

6.075**

3.151**

 

Serial correlation (LM test, c2(12))     18.79[0.103]

R- squared                                      0.754

 

Normality (Jarque-Bera test, c2(2))     3.362[0.186]

Adjusted R Squared                       0.662

 

Heteroscedasticity   c2(1)                    1.108[0.292]

S.E. of Regression                          0.796   

 

Functional Form      c2(1)                    3.716[0.054]

DW-statistic                                   1.945

 

       We note that:  *, **, and *** denote the significance at the 10%, 5%, and 1% levels respectively. 

       The figures in parentheses mentioned above are t-ratios;

 

Model's equation in Vietnam in 1991:1-1999:5. (Case of M1 and e Market).

Source:  Author's calculations based on data during 1991:1-1999:5 (monthly data) in the model (1).

Table 13: Estimation result in case of using M2 and e Market  for Vietnam: 1991:1-1999:5

Lag

              gM2

                   gY

p-1 (pe)

v (e Market-id)

 

0

   0.0840

(2.19)**

-0.0666

(-3.18)***

 

-0.0399

(-0.790)

 

1

   0.0660

  (1.70)*

-0.0724

 (-3.38)***

0.2213

(1.945)*

0.0195

(0.349)

 

2

       0.1266

(3.15)***

 

-0.1501

(-1.319)

-0.0233

(-0.421)

 

3

   0.0163

   (0.395)

 

0.1077

(0.998)

0.2055

(3.81)***

 

4

   0.0582

   (1.397)

 

0.1464

(1.345)

-0.0839

(-1.458)

 

5

   -0.0061

   (-0.155)

 

-0.0462

(-0.434)

0.1168

(2.35)**

 

6

   -0.0060

  (-0.153)

 

0.0015

(0.015)

 

 

7

 

 

0.0708

(0.759)

 

 

8

 

 

0.0054

(0.064)

 

 

9

 

 

0.1154

(1.520)

 

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

   0.3400

   5.202**

            -0.1390

           19.7***

      0.4722

    10.7***

0.1947

8.76***

 

Wald test for åaiM=1

  19.7***

 

 

 

 

F-statistic for the joint

significance of the lags.

  2.270**

          9.86***

      2.46**

4.64***

 

Serial correlation (LM test, c2(12))    13.20[0.354]

R- squared                                    0.737

 

Normality (Jarque-Bera test, c2(2))    0.359[0.835]

Adjusted R Squared                     0.644

 

Heteroscedasticity                  c2(2)    0.756[0.384]

S.E. of Regression                        0.836

 

Functional Form                    c2(2)     12.73[0.013]

DW-statistic                                 1.819

 

       We note that:  *, **, and *** denote the significance at the 10%, 5%, and 1% levels respectively. 

       The figures in parentheses mentioned above are t-ratios;

Model's equation in Vietnam in 1991:1-1999:5.

           

    Source:  Author's calculations based on data during 1991:1-1999:5 (monthly data) in the model (1).

Table 14: Estimation result in the case of using M1 and e Office : 1991:1-1994:10

 

Lag

gM1

gY

p-1 (pe)

v (e Office-id)

 

0

0.0868

(1.389)

-0.0475

(-0.426)

 

0.0216

(0.416)

 

1

0.1275

(2.12)*

-0.3980

(-2.90)**

-0.0354

(-0.145)

0.1196

(2.55)**

 

2

-0.0293

(-0.389)

 

 

-0.1701

(-0.774)

0.0877

(1.854)*

 

3

0.0059

(0.096)

 

 

0.0283

(0.117)

0.0534

(1.096)

 

4

0.0417

(0.685)

 

 

0.2068

(1.146)

0.1545

(2.92)**

 

5

0.0097

(0.157)

 

 

-0.1115

(-0.662)

0.0185

(0.331)

 

6

 

 

 

0.0568

(0.391)

-0.0212

(-0.007)

 

7

 

 

 

0.0368

(0.241)

0.0645

(1.121)

 

8

 

 

 

0.1463

(1.139)

-0.0164

(-0.083)

 

Sum of the lag coefficients ( å)

0.2423

-0.4455

0.1580

0.4822

 

F-statistic for joint significance of lags

2.417*

   4.291**

   1.010

     3.65***

Wald test for å=0,c2(1)

3.694*

6.251**

       0.327

8.99***

 

Wald test for åaiM=1                                    26.2***

     Chow test          c2(26)                 40.54

 

 

Table 18: Estimation result in the case of M1 and e Market : 1991:1-1994:10

 

Lag

gM1

  gY

 p-1 (pe)

v (e Market-id)

 

0

-0.0269

(-0.357)

-0.0895

(-0.874)

 

-0.0748

(-0.616)

 

1

-0.0681

(-0.667)

-0.311

(-3.27)***

0.8249

(2.68)**

0.1308

(1.326)

 

2

0.2061

(3.36)***

0.5996

(3.82)***

0.3143

(1.497)

-0.2019

(-2.453)**

 

3

0.0404

(0.614)

0.1268

(1.086)

0.0214

(0.1262)

0.217

(3.512)***

 

4

 

-0.0053

(-0.055)

-0.0529

(-0.326)

-0.2686

(-2.495)**

 

5

 

 

-0.3214

(-1.982)*

 

 

6

 

 

-0.1237

(-1.023)

 

 

7

 

 

0.1203

(1.032)

 

 

8

 

 

-0.1136

(-0.784)

 

 

9

 

 

-0.0433

(-0.338)

 

 

10

 

 

0.0384

(0.227)

 

 

11

 

 

      0.1458

(0.715)

 

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.1515

4.126*

0.3206

0.594

0.8102

12.77**

-0.1967

1.943

 

F-statistic for joint significance of lags

3.458*

5.551*

3.436*

3.511*

 

Source:  Author's calculations based on data during 1991:1-1994:10 (monthly data) in the model (1).

 

Wald test for åaiM=1                                  15.6***

          Chow test           c2(26)                 39.97

 

Table 15: Estimation result in the case of M1 and e Office: 1994:11-1998:12

 

Lag

              gM1

              gY

 p-1 (pe)

v (e Office-id)

 

0

-0.0260

(-0.354)

-0.0460

(-1.908)*

 

-0.1765

(-0.694)

 

1

0.1072

(1.321)

-0.0797

(-2.76)**

0.3124

(1.71)*

-0.1554

(-0.635)

 

2

0.1072

(1.403)

 

 

-0.0235

(-0.123)

0.2403

(1.011)

 

3

0.1277

(1.95)*

 

 

0.179

(1.044)

-0.1882

(-0.805)

 

4

0.0898

(1.047)

 

 

0.2252

(1.055)

0.0874

(0.698)

 

5

-0.0222

(-0.299)

 

 

0.0720

(0.328)

-0.0538

(-0.123)

 

6

 

 

 

-0.1231

(-0.635)

0.8652

(1.278)

 

7

 

 

 

0.2649

(1.335)

-0.5300

(-0.659)

 

8

 

 

 

0.0742

(0.378)

0.2924

(0.404)

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.3837

3.241*

-0.1257

11.06**

0.9819

2.322

0.3814

1.8839

 

Wald test for åaiM=1

6.26***

 

 

 

 

F-statistic for joint significance of lags

2.896*

5.582**

1.412

 4.608*

 

 

Table 19: Estimation result in the case of M1 and e Market: 1994:11-1999:5

 

Lag

gM1

gY

p-1 (pe)

v (e Market-id)

 

0

0.0219

(0.958)

-0.0564

(-1.97)*

 

0.0272

(0.273)

 

1

0.0614

(0.854)

-0.0608

(-1.99)*

0.3025

(1.626)

0.0087

(0.083)

 

2

0.0894

(1.174)

0.0512

(1.421)

0.2215

(1.095)

-0.0078

(-0.068)

 

3

0.0034

(0.057)

0.0267

(0.714)

0.1529

(0.748)

0.0054

(0.047)

 

4

 

0.0022

(0.056)

0.1880

(1.101)

0.0524

(0.473)

 

5

 

 

-0.0511

(-0.246)

 

 

6

 

 

-0.1416

(-0.731)

 

 

7

 

 

0.0507

(0.263)

 

 

8

 

 

0.1310

(0.820)

 

 

9

 

 

0.9973

(0.671)

 

 

10

 

 

0.0373

(0.229)

 

 

11

 

 

-0.0761

(-0.505)

 

 

Sum of the lag coefficients ( å)

Wald test for å=0,c2(1)

0.1761

0.1576

-0.0371

4.502*

1.8124

4.036

0.0859

1.686

 

Wald test for åaiM=1

15.1***