Dr.DEBESH BHOWMIK

Dr.DEBESH BHOWMIK

Monday 27 July 2015

GREEN FREIGHT AND LOGISTICS IN ASIA



The demand for freight and logistics in Asia and the Pacific is expected to grow significantly in the coming years, and it will continue to play a large role in driving economic growth and alleviating poverty in the region. Within the transport sector,
freight and logistics account for a significant portion of total energy use – in many countries upward of 40% – and a correspondingly large share of CO2 emissions.
The promotion of efficient, environmentally sustainable and safe freight transport is an issue of substantial importance and urgency.
Based on the need for countries across Asia and the Pacific to address this issue, the Asian Development Bank (ADB) and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) organized this first regional workshop to take stock of best
practices and systematic approaches towards efficient logistics and green freight.
The event, held 25-27 June 2014 in Singapore, aimed to give recognition to and provide a platform for the exploration of the multiple initiatives currently being developed at different levels of governance (local, national, sub-regional and regional) and by actors from different sectors (public, private, NGOs).
The workshop was arranged as a mix of predefined presentations by global contributors to the green freight and logistics discussion, as well as through facilitated peer learning and exchanges among the key stakeholders active in freight and logistics. Specifically, it aimed to (i) to foster discussion on the potential and benefits of green freight policies in the region; (ii) to identify opportunities that can
be developed into actions and projects; (iii) to shape a broad work plan for national activities; and (iv) to identify training needs according to select target groups (thus establishing a knowledge base in support of green freight and logistics programs in the region). The outputs of the workshop will also provide inputs to the ASEAN Working Groups on Land Transport and Transport Facilitation as well as the United Nations Center of Regional Development (UNCRD)-led initiative to develop a Regional
Framework on Green Freight and Logistics.This document is meant to summarize the workshop, draw out the key messages from each session, and includes a short synopsis of the group work that was
undertaken during the workshop. It also provides recommendations for future action, by ADB and GIZ.


Panel discussions: Green freight and logistics in Asia: Current trends and future pathways
The second panel discussion built on the lessons learned from the first panel to describe the current state of affairs in green freight and logistics in Asia. The panel was chaired by Ms. Glynda Bathan, Deputy Executive Director of Clean Air Asia, who set the stage by requesting panelists to describe steps taken by the stakeholders to make the freight and logistics sector greener, identify “What” are
the key drivers that can facilitate this development; and on “Opportunities” and “Barriers”.The discussion began with a short speech by Mr. Tran Anh Duong, DeputyDirector General of the Ministry of Transport, Viet Nam. He noted that emissions
from transport are not well regulated in Asia in general, and Southeast Asia in particular. With around one million trucks in the country, monitoring stations indicate that levels of PM10 are 1.5 – 2 times greater along the ring road in Hanoi and Ho Chi Min City than legal standards permit. Viet Nam has designed a National
Green Growth Strategy that highlights tasks for the freight sector in the comingyears:
• Increase energy efficiency
• Utilize alternative or renewable fuels
• Implement coastal shipping and inland waterway transport.
Next, Mr. Karmjit Singh, Fellow and Chairman of the Chartered Institute of Logistics and Transport (CILT) Singapore, noted that even in Singapore, the industry is always learning. Singapore is a logistics hub that developed from nothing to become one of
the most efficient airport and seaports ranking globally, not only serving regional but also global trade. In order to improve building energy efficiency, Singapore has implemented incentives for green buildings, with a goal of 80% of buildings being “green” by 2020. The city also needs to deal with new traffic patterns related to movement of the port by 2025, and terminal 5 of the airport constructed around the same time.
Mr. Singh concluded that there are challenges related to the human aspect of freight and logistics. Habits are hard to change, even with incentives. Furthermore, companies and governments look at freight as trucks moving, rather than as drivers driving trucks. Without recognizing the importance of drivers, they are unlikely to
take a role in better driving and emissions reduction.

Mr. Thibodee Harnparasert, Executive Advisor of the Federation of Thai Industries (FTI) then described some of the green freight work being undertaken in Thailand. Thailand has about one million trucks, 140,000 buses, 6.5 million passenger cars, and 6 million diesel pickup trucks. Transport alone consumed 36% of energy in the country, 80% of that from inland transport. In order to deal with this situation, the FTI proposed to government an energy
efficiency program in logistics and transport management, which trained over 2500 professionals from 240 companies in four areas:
• Management: e.g. standardizing maintenance, utilizing GPS and RFID, and shortening loading cycles and space utilization
• Engineering and technologies: e.g. tires can reduce fuel consumption 3-5% if tire pressure is managed
• Middle management: e.g. understanding what load is suitable for what trucks
• Driving: e.g. implementation of daily check sheets, idle time reduction, and being familiar with normal operating performance of the vehicle – not to mention being alert and sober. The final effort discussed by Mr. Harnparasert was that by utilizing GPS and
monitoring truck movement, and standardizing data for logistics, load optimization and back loading could increase significantly. Industry is generating data through this system for decision making by government. The last speaker in the second panel was Mr.
Stephan Schablinski, Executive Director of Green Freight Asia, who advocated that the private sector is not just part of the problem rather, it can be an important part of the solution to freight emissions. He noted that 90% of trucks in Asia and the Pacific are
owned by individual drivers, and only 0.1% are owned by big fleets. Most companies don’t have the capacity to work in terms of
GHG emissions and other global issues related to their work, and therefore economic incentives are necessary. Companies want to
reduce costs and improve profits through more sustainable operations. At the same time, manufacturers would like to choose
greener carriers, but they have little information on which carriers are greener.Green Freight Asia aims to use a methodology to identify companies that are acting to improve their emission profiles, or have committed to act. The organization also
aims to develop a clear-cut matrix of technologies for trucking companies that can help quickly identify which technologies are appropriate for their businesses.
Key discussion points During the panel discussion, several key points were raised:
• Asian countries face a huge challenge in enforcement of fuel and vehicle standards. The reality is that governments need to become more committed to fuel quality standards enforcement, and need to financially support truck owners to upgrade their fleets. Singapore is leading in technology standards for trucks, aiming to shift to Euro VI emission standards by 2017, but challenges remain with cross-border traffic, in a context where each country has its own
standards
• In order to promote its private sector backed green freight labeling scheme, Green Freight Asia requires assistance from intermediaries in each country, and in many cases needs help in providing balanced information in local languages on technologies appropriate for trucks

Saturday 4 July 2015

COINTEGRATION BETWEEN WORLD TRADE AND GOLD AND SDR



This paper was presented  in International Multidisciplinary Research Conference organised by INAAR and CVU and sponsored by Indo-Global Chamber of Commerce at MCCIA, Pune on 30th June,2015.

It is published in International Research Journal of Commerce ,Business and Social Sciences, Vol- IV,Issue-3(I),June 2015, pp-17-23  

COINTEGRATION BETWEEN WORLD TRADE AND GOLD AND SDR
 Dr. Debesh Bhowmik (International Institute for Development Studies, Kolkata)
Key Words- Cointegration, World exports, World imports, SDR, Gold
JEL-C58,F33,P45
I.                    Introduction

Prior to the inception of the Bretton Woods, the economists had been searching for a single currency for the world economy where metallic standard to key currency to multiple currency standard have been examined, yet the imbalance and international liquidity problem could not be solved. Now, IMF, some academicians and politicians  assume that if SDR be the world money for international transactions then liquidity crisis ,global imbalance and financial crises may be solved.
In this respect, we try to verify the relation between the world exports and imports with the world gold reserves and world SDR reserves during 1968-2013.

II.Methodology and Data
We used Johansen (1988) model for cointegration and Johansen (1991, 1996) model for VAR Analysis. We have taken data on world exports , imports , gold and SDR reserves from the International Financial Statistics(IMF) for the period from 1968 to 2013.Assume , x1= world export , x2= world import , y1= world gold reserve, y2= world SDR reserve.

III.The Main Econometric Observations
It is found from the double log regression model that one percent increase in world gold reserves per annum led to 9.648% decrease in world exports per year significantly during 1968-2013.But Johansen cointegration test suggests that these two are not cointegrated during 1968-2013 which is verified by the Trace statistic and λ max statistic .
From the double log regression model ,the estimated regression showed that one percent increase in world SDR reserves per year  led to 1.658% increase in world exports per year during 1968-2013.It is statistically significant . The Johansen cointegration test showed that the Trace Statistic and λ Max Statistic have one cointegrating equation with 5% significant level. Now if we use the double log multiple regression model to relate world export, world gold reserves and world SDR reserves during 1968-2013, we find that one percent increase in world gold reserves per year leads to 1.2953% increase in world export per year which is insignificant  and one percent increase in world SDR reserves per year leads to 1.663% decrease in world exports per year which is significant statistically. Its R2 is high and F statistic is significant.
Logx1= -16.70309+1.2953logy1-1.663logy2
                (-0.6080)   (0.3269)     (8.728)*
 R2= 0.656  , F= 38.162   , DW= 0.471,*=significant at 5% level.
In applying the Johansen cointegration test ,we got the values of  trace statistic and λ Max statistic which showed one cointegrating equation. The values are given in Table-1,
                  

Table-1: Cointegration test of x1,y1 & y2
Hypothesized no of CE(s)
Eigen value
Trace statistic
0.05 cv
prob
None*
0.4658
32.739*
29.797
0.0223
At most 1
0.1512
7.0322
15.494
0.5739
At most 2
0.00747
0.3077
3.84
0.5791
                                                                                    λ Max Statistic
None*
0.4658
25.7071*
21.1316
0.0106
At most 1
0.1512
6.7244
14.264
0.5222
At most 2
0.00747
0.30776
3.841
0.5791
Source-Computed by Author
The estimated VAR model of X1 , Y1, and Y2 is given below,
X1t=-72794.84+0.9916X1t-1+78.119Y1t-1+0.04809Y2t-1
           (-1.008)    (12.447)*        (78.119)        (0.5322)
   R2=0.906  , F= 122.543*
Y1t=216.4743 – 2.33E-06X1t-1+0.7741Y1t-1+9.92E-05Y2t-1
           (0.6382)     (-0.022)            (7.929)*           (0.8359)
  R2= 0.6382   ,   F= 22.347*
Y2t=52002.48+0.31648X1t-1-49.1302Y1t-1+0.7199Y2t-1
          (0.527)        (2.91)*          (-0.484)               (5.838)*
       R2=0.793   , F=48.5848* , *= significant at 5% level.AIC= 55.299  , SC=55.796  , loglikelihood=-1149.295
The VAR model is a good fit with high R2 and F. But its Impulse Response Function showed that the VAR model is quite unstable because of its divergence.
 Fig-1: The Impulse Response Functions of VAR model of x1,y1 &y2

Source-Computed by author
The unit root circle test confirmed that one root lies outside the circle and others lie inside the circle, and thus why VAR is unstable which is shown in Table -2 and Fig-2
                                                     Table-2: Values of Roots
Roots
Modulus
 1.058233
 1.058233
 0.713772 - 0.093269i
 0.719840
 0.713772 + 0.093269i
 0.719840
 Source- Computed by Author
         Fig- 2: Unit root circle

Source- Computed by author
The residual test for normality assured that null hypothesis of normality is rejected because the Skewness,Kurtosis and Jarque-Berra which are distributed as Chi-square are significant.
               
Table-3: Normality test
       component
Skewness
Chi-sq
df
prob
1
 4.200634
 42.54447
1
0.000
2
 1.139789
 8.678463
1
0.000
3
 4.079677
 41.41035
1
0.000
joint
92.63328

3
0.000
component
Kurtosis
Chi-sq
df
prob
1
 24.82540
 95.81405
1
 0.0000
2
 9.425477
 22.91993
1
 0.0032
3
 25.78465
 48.10460
1
 0.0000
joint
166.8386

3
0.000
component
Jarque-Bera



1
 138.3585

2
0.000
2
 31.59839

2
0.000
3
 89.51495

2
0.000
joint
259.4719

6
0.000
Source- Computed by author
The same econometric analysis can be applied in the world import with world gold reserves and world SDR reserves during 1968-2013.The double log linear model  between world import and world gold reserves represents that one percent increase in world reserves in gold per year induced to decrease world imports by 1.027007% significantly per year during 1968-2013.The Johansen Cointegration test suggests that Trace statistics confirmed two integrating equations but λ Max statistics confirmed one cointegrating equation.
The relation between world import and world reserves of SDR during 1968-2013 through double log regression model states that one percent increase in world SDR reserves per year leads to 1.11348% increase in world imports per year which showed statistically significant at 5% level. The Johansen cointegration test also confirmed that there are two cointegrating equations as observed by the Trace statistic and λ Max statistic.
Now the double log multiple regression among the world import, world SDR and gold reserves during 1968-2013 signifies that one percent increase in world SDR per annum leads to 1.10474 % increase in world imports per annum which was found statistically significant but one percent increase in world gold reserves per year leads to 2.30436% decrease in world imports per annum during 1968-2013 which is statistically insignificant. The estimated equation is given below.
logx2=13.2120-2.30436logy1+1.10474logy2
              (0.7480)  (-0.9046)      (9.0174)*
 R2= 0.6772  . F= 41.972*   , DW= 0.646,*= significant at 5% level.
The Johansen cointegration test suggests that the Trace statistic and λ Max statistic assured 3 cointegrating equations and they are cointegrated in the order of I(1,1).The values are given below .
                    Table-4: Cointegration test of x2,y1 & y2
Hypothesized no of CE(s)
Eigen value
Trace statistic
0.05 cv
prob
None*
0.909594
120.1075
29.797
0.000
At most 1*
0.338847
21.566
15.494
0.005
At most 2*
0.106163
4.60149
3.84
0.0319
                                                                   λ Max Statistic
None*
0.909594
98.54142
21.1316
0.000
At most 1*
0.338847
16.96459
14.264
0.018
At most 2*
0.106163
4.601498
3.841
0.0319
Source- Computed by author
The estimated VAR model of X2, Y1, and Y2 are given below,
X2t=-53592.38+1.0917X2t-1+50.4505Y1t-1+0.2843Y2t-1
            (-0.663)     (1.177)       (0.608)          (2.963)*
 R2= 0.441    , F= 9.994
Y1t=217.2006-7.83E-05X2t-2+0.7737Y1t-1+0.000103Y2t-1
          (2.296)*     (-0.072)     (7.964)*        (2.296)*
          R2= 0.638   , F= 22.35*
Y2t=6689.35+2.4565X2t-1-9.9133Y1t-1+0.806149Y2t-1
         (0.0649)   (2.076)*     (-0.093)    (6.586)*
 R2=0.772   ,  F= 43.095* , AIC=55.676  , SC= 56.172  , loglikelihood=-1157.197,*= significant at 5% level.
Again, the values of two roots lie inside the unit circle and one root which is greater than one ,lies outside the unit circle which showed that the VAR model is unstable.
        Table-5 : Values of Roots
Roots
Modulus
 1.801502
 1.801502
 0.753849
 0.753849
 0.116222
 0.116222
Source- Computed by author
Fig- 3: Unit root circle

      Source- Computed by author
The VAR model is found good fit but the Impulse Response Functions are diverging which means the VAR model is unstable. It is shown in Fig-4
            Fig- 4: Impulse response functions of VAR model of x2,y1 & y2

         Source- Computed by author
The residual test for normality showed that the Chi Square distribution of Skewness,Kurtosis and Jarque-Berra are significant which confirmed that null hypothesis of no normality is rejected. It is given in the Table-6.
        Table-6: Normality Test
       component
Skewness
   Chi-sq
df
prob
1
 2.630436
 26.46427
1
0.000
2
 1.166359
 8.993752
1
0.0027
3
 5.084170
 50.37757
1
0.000
joint

85.8356
3
0.000
component
Kurtosis
Chi-sq
df
prob
1
 20.72866
 14.09559
1
 0.0002
2
 9.470174
 22.10563
1
 0.0000
3
 31.35488
 294.9126
1
 0.0000
joint

331.1139
3
0.000
component
Jarque-Bera



1
 40.55987

2
0.000
2
 31.09938

2
0.000
3
 345.2902

2
0.000
joint
416.9495

6
0.000
Source- Calculated by Author.

IV.Conclusion
Thus, it was verified that world exports and imports are positively related with world SDR reserves  but world exports and imports are not always positively/negatively related with world gold reserves during the period of 1968-2013.World export is cointegrated with SDR but not with gold, on the other hand, world import is cointegrated with  both gold and SDR. The multivariate Johansen model showed that both world export and import are significantly cointegrated with gold and SDR.  Their VAR models were found good fit but did not satisfy the stability conditions.  

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