Download Document

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Transcript
Objektif Slot
Calon memenuhi
ekspektasi panel
penemuduga dari
semua aspek
How to succeed in
your graduate
study
By
Khalid Abdul Hamid, PhD
Be prepared
 Somebody wants to shoot you down
 Prepare, prepare and prepare
 Psychologically (Mind and Heart - Attitude)
 Physically (Skill and knowledge, family, etc.)
 Examine things you will be facing (new environments,
new ways of doing things)
 Make all the checklist you need to execute (prepare a
file, contingencies etc.)
 Mind-set change
Study
Examine your curricula
Examine how you could succeed
Examine gaps you have and work it out
now
Curiosity the Basic Ingredient
for Industrial Statistics
[email protected]
Definition
 Curiosity (from Latin curiosus "careful, diligent, curious," akin to cura "care")
is a quality related to inquisitive thinking such as exploration, investigation,
and ...
 cu·ri·os·i·ty (ky r - s -t ). n. pl. cu·ri·os·i·ties. 1. A desire to know or learn. 2. A
desire to know about people or things that do not concern one; nosiness. 3.
An object ...
Basic ingredient
 Basic Ingredients for Weather
 eo.ucar.edu/webweather/basic.htmlCached
 [Temperature] [Pressure] [Volume] [Density] [Combine Ingredients] ·
[Thunderstorms & Tornadoes] [Hurricanes] [Blizzards & Winter Weather]
[Clouds].
Industry Statistics
1. Commodity Production Statistics
In the area of industrial statistics, the United Nations Statistics Division (UNSD) is engaged in
the collection and dissemination of data on the production of major industrial
commodities, both in physical quantities and in monetary value. Data are mainly collected
through a questionnaire sent yearly to national statistical offices. The commodities are
classified according to the UN List of Industrial Products. The data collected are published
in three major publications: the Industrial Commodity Statistics Yearbook, the United
Nations Statistics Yearbook, and the Monthly Bulletin of Statistics.
Data on Industrial Commodity Production can be obtained in the following ways:
The 2008 Industrial Commodity Statistics Yearbook (2 volumes) in hardcover and PDF
format. (order here)
The complete dataset of Industrial Commodity Statistics, currently covering the period
1950-2008 on CD-ROM. (Contact [email protected] to order.)
On-line through the UN Data portal.
Continued….
 In dealing with difficulties later in life, protecting young people from failure
early in life would seem to have another negative effect. And this is in
discouraging them from embarking on any endeavor where there is even the
slightest risk of not succeeding.
 This is reflected in the fields that the students of wealthy families are choosing
to go into in college, and also in their career choices. As Tough notes “there
are fewer entrepreneurs graduating from our best colleges these days; fewer
iconoclasts; fewer artists; fewer everything, in fact, except investment bankers
and management consultants” (loc. 3046).
 And the numbers bear out what Tough is saying. Indeed, consider that
“recently, the New York Times reported that 36 percent of new Princeton
graduates in 2010 took jobs in the finance industry, and another 26 percent
took jobs in a category that… features, prominently, management
consulting…—and this [was] after the near-collapse of the finance industry in
2008. (Before the economic crisis, about three-quarters of Princeton
graduates went into one of those two careers.)” (loc. 3049)
Pesanan Penaja
 http://www.youtube.com/watch?v=UF8uR6Z6KLc&feature=player_embed
ded
 C:\Users\Dell-3\Desktop\Desktop 27Mac2013\IO Workshop at
Intan\CTt4y8bokWs-lecture-7-energy-economics-inputoutput.htm
Session 3
The Power of I-O Analysis:
3 case studies
Input-Output training course, Intan
4th June 2013
Content
Introduction to I-O Tables
Table versus model
Extracting structure information
Aggregating
Case studies using I-O model:
Food and Energy;
Wage and Productivity; and
Subsidy Rationalization
General background
100 i-o users, 100 different programs
spreadsheets:
easy, but not flexible
matrix programming (Gauss, Matlab):
flexible, but not easy
input-output software:
mainly i-o construction, little i-o modelling
Purpose: easy and flexible
easy to use, Windows integrated
data input & model output,
exchangeable with other software
usable for all types of i-o tables:
 interregional, but also single-region and national
all standard I-O analyses covered:
 descriptive statistics, linkage analyses
 additional variables, flexible model extensions
 multiplier and impact analyses
Basic characteristics
 no table construction-use provided model
 no fancy stuff you can do elsewhere (graphics)
 Table files (.tbl) = only the basic I-O table
 Model files (.mdl) = table + all extra information you add yourself to build
your model
 generalized Dimensions, no size restrictions
 generalized endogenous Variables, no feedback
 generalized endogenous Relations, with feedback
Install IRIOS
 http://www.regroningen.nl/irios.html
 Run setup
 Download lab data:
 http://www.regroningen.nl/lab.zip
 Unzip lab.zip to your local working directory (c:\lab)
 Start IRIOS
 New/Model and Open/Table
 Browse to c:\lab and choose “Netherlands.tbl”
Edit table
 Aggregation
 Distribute margins (later)
 Aggregation possible over all 5 dimensions
 Aggregate manufacturing and public utility into “Man_Pub”
 Press Cancel when not saving the aggregated table
 Aggregate Wages, Social insurance and Other Income into “Value Added”
 Aggregating regions: Later
 Note: there is no undo for aggregation!
Larger tables
New/Model and Open/Table
Choose “Asia 2000.tbl”
Aggregate 76 sectors into
Agriculture
Manufacturing
Services
Aggregate imports from Hongkong, EU and ROW into
“total imports”
Descriptive statistics
New/Model and Open/Table
Browse to c:\lab and choose “Netherlands.tbl”
Analysis I-O table
Sector structure
Production: which is the largest sector?
Wages: which sector generates most of the wages?
Exports
All together
Descriptive statistics
 Analysis I-O table
 Output/Sales structure
 Choose Construction
 Calculate shares unaggregated: which is the largest output
coefficient?
 Choose all sectors
 Calculate shares aggregated: intermediate versus final output
 Which industry is the most orientated to intermediate sales?
Descriptive statistics
 Analysis I-O table
 Input/Cost structure
 Choose Manufacturing
 Calculate shares unaggregated: which is the largest input coefficient?
 Choose all sectors
 Calculate shares unaggregated: which sector has the highest input coefficient for
construction?
 Calculate shares aggregated: intermediate versus primary inputs
 Which industry has the highest intermediate input coefficient?
Case studies:
1.Introduction
2.Methodology
3.Results
4.Recommendations
Case study 1:
Food and Energy
Published papers/journals/presentation:
1.
Energy Price Impact on East Asian Region’s Food and Non-food Industry.
Presented by Khalid
Abdul Hamid at The International Conference on Economics and Finance, Kathmandu, Nepal, 20 – 22
April 2012.
2.
Effect of Energy Price increase on East Asian Region’s Food Industries’ interconnectedness
and
Integration. Chapter 10 in Deepening Energy Market
Integration for ERIA by Khalid, A.H., Zakariah,
A.R. and R. Zarina R.M. (August 2011)
3.
Food and Energy MACFEA 15th National Seminar, UITM Hotel, Shah Alam
2011
Selangor, 19—20 July
4.
Effect of Higher Oil Price to Consumer Food Products in Malaysia. Khalid, A.H.,
Zakariah
A.R
and Mohd Khairul Hisyam H.. Article due for publication at the
MJES,
Malaysian
Economic
Association, University of Malaya
5.
The Effect of Higher oil Price on Consumer Food Products in Malaysia. Khalid,
A.R. (Presented at the International Economic Conference,
Anadolu University,
.Vol. 1, T2D Economics of Oil
6.
A.H., Zakariah,
Eskisehir, Turkey
Effect of Energy Price Increase on East Asian Region’s Food Industries:
with special reference to Malaysian Experience. By Khalid, A.H. NEOC, Nov 23, 2011.
Case study 1:
Effect of Energy Price
Increase on East Asian
Region’s Food Industries:
with special reference to Malaysian Experience
Food and Energy
(http://www.eria.org/publications/research_project_reports/deepen-understanding-and-move-forward-energy-market-integration-in-east-asia.html)
Economic Impact
1. Estimation of an economy’s aggregate impact shows the
potential benefits of various forms of growth. As such, in
times of rising oil price it shows susceptibility of the
economy in question. As West (1999) explained it not the
size that is important but magnitude because a small
multiplier can correspond to a large total impact and a
large multiplier to a small impact in an economy
depending on the size of initial changes in the final
demand.
2. The word impact may seem ambiguous since it can be
used in various contexts such as effect, result, incidence,
significance, contribution, consequence and importance.
In the pursuit of measuring the energy price impact, the
primary focus will be on output changes in the oil and nonoil industries, sales patterns, new commitments or
investments, alterations of economic commitment or
assessing current economic significance of established
industries. All these can be traced by the total impact
analysis via final demand, multipliers, linkages and the
extended Leontief‟s price system.
Sectoral Inflationary Rates
 The following Table 4.25 presents the share of each sector in household expenditure or total
private consumption (C), the share of each sector in total gross output (Q), and the share
of each sector in GDP (VA) in the 41 x 41 sector Malaysian I-O Table 2000 and 1978. This is
achieved by transforming each share into weights and multiplying by each sector’s price,
output or VA share, i.e.
 C = P1 (C1/C*) + P2 (C2/C*) +……. + P41 (C41/C*) = ΣPC
 Q = P1(X1/X*) + P2 (X2/X*) +……. + P41 (X41/X*) = ΣPX
 VA= P1(VA1/VA*) + P2 (VA2/VA*) +…….+ P41 (VA41/VA*) = ΣPVA
Table 4.25: Sectoral inflation rate, 1978 and 2000 (in percent)
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
29
40
41
Sectors
Agricultural products other
Plantation
Oils and fats
Other manufacturing
Footwear
Printed products
Industrial chemicals
Paints & lacquers
Drugs & medicines
Soap & cleaning preps
Other chemical products
Petrol & coal products
Processed rubber
Rubber products
Plastic products
China, glass & pottery
Clay products
Cement, lime & plaster
Other non-metal products
Iron & steel
Industrial machinery
Household machinery
Other electrical machinery
Ships & boats
Motor vehicles
Other transport equipment
Electricity & gas
Buildings & constructions
Property and development
Wholesale & retail trade
Hotels & restaurants
Transport
Communication
Banking services
Other financial services
Insurance
Business services
Education - Private
Health - Private
Other services
CPI
0.025
0.000
0.027
0.001
0.068
0.031
0.008
0.011
0.035
0.017
0.022
0.013
0.026
0.019
0.011
0.000
0.005
0.004
0.000
0.013
0.023
0.011
0.004
0.002
0.000
0.001
0.002
0.004
0.009
0.027
0.008
0.005
0.336
0.770
1978
Gross Output
0.014
0.011
0.007
0.008
0.016
0.014
0.007
0.003
0.030
0.008
0.004
0.005
0.003
0.003
0.004
0.009
0.003
0.014
0.001
0.005
0.004
0.001
0.003
0.014
0.021
0.004
0.002
0.002
0.002
0.002
0.024
0.004
0.005
0.017
0.008
0.002
0.003
0.044
0.188
0.551
GDP
0.682
0.773
0.277
0.696
0.549
0.597
0.498
0.491
0.645
0.566
0.668
0.495
0.232
0.641
0.712
0.649
0.537
0.520
0.447
0.628
0.819
0.821
0.737
0.798
0.632
0.739
0.730
0.561
0.840
0.838
0.556
0.610
0.792
0.877
0.662
0.734
0.759
0.864
0.808
0.683
CPI
0.14
0.00
0.07
0.06
0.00
0.01
0.00
0.00
0.00
0.01
0.00
2.54
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.08
0.00
0.04
0.00
0.09
0.09
0.01
0.00
0.00
0.00
0.01
0.00
0.01
0.03
2000
Gross Output
0.02
0.00
0.02
0.14
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.05
0.01
0.00
0.01
0.00
0.01
0.03
0.01
0.03
0.01
0.02
0.01
0.01
0.00
0.00
0.01
0.01
0.00
0.02
GDP
1.79
1.14
1.03
0.42
0.52
0.36
2.83
1.08
0.98
1.31
2.07
18.98
0.33
0.98
0.58
2.08
1.95
1.56
0.71
1.18
0.32
0.14
0.28
0.35
0.21
0.66
2.51
0.55
0.31
0.24
0.53
2.01
0.17
0.07
0.15
0.09
0.51
0.17
0.29
0.63
Aggregate Household Expenditure, Gross Output and GDP
The following table shows the overall impact of price perturbations on the household expenditure
(PC), the cost of output (PQ) and GDP price deflator (PVA). These inflationary costs cuts across
the aggregated CPI, output and value added of the price system in aggregate form as shown
below.
Average for year
Consumption (PC)
Output (PQ)
Value Added (PVA)
Average
Overall
relative
measure
1978
0.04
0.03
0.65
-
2000
0.08
0.01
1.30
-
0.47
2.12
0.50
0.52
Relative measure
Estimating the retail price of food

The price-spread model is a short-run model which classifies 10-food-industries to estimate the impact of
changes of input prices onto consumer food product prices. It assume that consumers do not respond to
retail price changes, whilst food producers do not alter input proportions despite changes in relative
input prices.

Furthermore, output of each industry serves only as a final consumer of food products. In our pricespread model, we compute 10 components of food industries in each EA country as categorized in their
respective CPI to estimate price changes on retail price. Each firm of the respective 10 final food
industries produces a single product by combining a farm commodity with a set of non-farm inputs in
fixed proportions.

In this model, consumer demand is fixed for all levels of retail price. These simplifying assumptions reduce
the computation of a food price estimate to an evaluation of an accounting-type formula. This formula
states that the percentage change in the retail price is a weighted sum of the percentage changes in
input prices, with cost shares (e.g. from the Malaysian I-O tables, 2005) serving as weights:
PR* = PF*SF + Px*Sx
.…. (5)
 where SF and Sx represent the cost shares of food and non-food inputs, respectively, and where PR*, PF*,
Px* denote the percentage changes in the retail, the food price, and the aggregate non-food price,
respectively. The variable Px is the food marketing cost index (FMCI), or the average price of the
aggregate non-food input. The above formula asserts that a 1-per cent increase in the FMCI leads to a
Sx-per cent increase in the retail price.
Cont….
Energy is one of several non-food inputs used to produce food, and the price of energy is approximately about onetwelfth of non-food input prices used to construct the FMCI (i.e. Px). Suppose that food is produced using a single food
input and a single aggregate or representative non-food input, with a price equal to the FMCI. If this single non-food
input is produced from individual non-food inputs in fixed proportions, the retail price formula given by equation (5) above
can be extended directly to:
PR* = PF*SF + Px*Sx = PF*SF + (PE*SE +  Pi*Si) Sx
……. (6)
where SE and Si are the non-food cost shares of energy and the ith non-food input, and PE* and Pi* are the percentage
changes in energy and the other non-farm input prices, respectively. The sum in the parentheses of equation (6)
represents the percentage change in the FMCI (i.e., Px*), and the shares of each term serve as weights on the individual
input prices. Equation (6) states that the percentage increase in the consumer price of food is the weighted sum of the
percentage change in the price of the food ingredient, the energy price, and the other non-food input prices comprising
the FMCI. At this point, it is convenient to describe the main difference between the price-spread and intensity models.
The term, PE*SE in equation (6) is referred to as the direct effect because it denotes the energy cost increase incurred by
producers of the aggregate marketing input.
cPi*Si ,
…… (7)
The second term is referred to as the indirect effect because it measures the effect of a rising energy price on the costs of
other inputs used in producing the marketing input. For example, because energy is used to produce food packaging,
the cost of packaging will rise with higher energy prices. In a typical price-spread model simulation, the indirect effects
would be zero since the price of energy does not affect the price of other marketing inputs. In a typical I-O model
simulation, a change in the price of crude oil could affect the price of all other inputs used in the production of food.
Since we wish to impose the same exogenous change on the two models, we include the indirect effects of energy
increase in both model simulations. In particular, we used the I-O model’s prediction of the percentage change in energy
intensity whilst also using the FMCI in the price-spread model to estimate the effect of a doubling of the crude oil price.
The price-spread model simulation suggests that a doubling of the price of crude oil leads to a 1.119 per cent increase in
FMCI in 2005. This predicted increase in the FMCI is an average of total intensity of two important energy sectors’ total
impact.
This assumption simplifies that each industry’s output serves only at that respective final consumer of food product. Thus,
we can examine each of the 10 components of food industry’s retail price changes from an increase in energy price.

The weights are the derived from averaging the inverse matrix of two main energy-related sectors’.

Sx PF*SF is the direct effect of the energy price increase on the average cost of producing the food product.
Table 10. Retail Price of Food Products in Malaysia, 2005
Food products
Share of non-
FMCI
Change in
Wt.
CPI
Retail
food
*
PR
CPI
%
Price
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.13
1.26
1.44
1.15
0.93
1.11
1.27
1.01
1.16
1.14
4.40
2.90
4.50
1.80
0.60
3.30
0.60
0.80
10.00
1.40
30.30
0.044
0.029
0.045
0.018
0.006
0.033
0.006
0.008
0.100
0.014
0.050
0.036
0.065
0.021
0.006
0.036
0.008
0.008
0.116
0.016
0.361
Rice, Bread, other cereals
0.761
Meat & meat products
0.845
Fish & seafood
0.963
Milk, cheese, & eggs
0.775
Oils and fats
0.623
Fruits & vegetables
0.742
Sugar, jam, honey, chocolate, &
0.855
Food products n.e.c
0.678
confectionery
Food away from home
0.779
Coffee, tea, cocoa, & Non-Alcoholic
0.763
Sum/Total average
Beverages
Source: Calculated from I-O Table 2005, DOS Malaysia
Sectoral food price effects
 Relative prices across sectors of the EA economy
performed differently.
Increased in the energy price
generates more costs in terms of generating value added
and importing input in producing food and non-food
output. This has consequences on policies concerning
interconnectedness of energy inputs along food and nonfood corridors.
 Food productions in developed EA countries are lower than
average total effect, nevertheless, these sectors generate
greater value added. Thus, they are more resilient to
energy price increases;
 In contrast, developing EA countries’ food productions are
higher than total effect, however, generate less value
added; and
 Agricultural-based countries with low technology have low
value-added. Thus, local value added has limits in using
new techniques.
Retail price:
 A rise in energy prices has direct and indirect effects on
an economy. The lower an economy’s energy inputs,
the lower the effect from energy price increases and
likewise. Additionally, such economy’s have greater
potential in nurturing efficiency and diversification with
lower food intake and thus exhibit smaller effects in retail
prices;
 The price-spread effects in terms of energy use, nonfood costs share and CPI differ across food items; and
 The higher the effect of an increase in the oil price, the
greater the retail price. This occurs through channels of
food marketing such as transportation, packaging and
so on.
Table 10. Retail Price of Food Products in Malaysia, 2005
Food products
Share of non-
FMCI
Change in
Wt.
CPI
Retail
food
*
PR
CPI
%
Price
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.49
1.13
1.26
1.44
1.15
0.93
1.11
1.27
1.01
1.16
1.14
4.40
2.90
4.50
1.80
0.60
3.30
0.60
0.80
10.00
1.40
30.30
0.044
0.029
0.045
0.018
0.006
0.033
0.006
0.008
0.100
0.014
0.050
0.036
0.065
0.021
0.006
0.036
0.008
0.008
0.116
0.016
0.361
Rice, Bread, other cereals
0.761
Meat & meat products
0.845
Fish & seafood
0.963
Milk, cheese, & eggs
0.775
Oils and fats
0.623
Fruits & vegetables
0.742
Sugar, jam, honey, chocolate, &
0.855
Food products n.e.c
0.678
confectionery
Food away from home
0.779
Coffee, tea, cocoa, & Non-Alcoholic
0.763
Sum/Total average
Beverages
Source: Calculated from I-O Table 2005, DOS Malaysia
Sectoral Price effects
 Relative prices across sectors of the EA economy performed
differently. Increased in the energy price generates more
costs in terms of generating value added and importing input
in producing food and non-food output.
This has
consequences on policies concerning interconnectedness of
energy inputs along food and non-food corridors.
 Food productions in developed EA countries are lower than
average total effect, nevertheless, these sectors generate
greater value added. Thus, they are more resilient to energy
price increases;
 In contrast, developing EA countries’ food productions are
higher than total effect, however, generate less value
added; and
 Agricultural-based countries with low technology have low
value-added. Thus, local value added has limits in using new
techniques.
Retail price:
 A rise in energy prices has direct and indirect effects on EA
economies. The lower an economy’s energy inputs, the lower the
effect from energy price increases. Additionally, such economy’s
have greater potential in nurturing efficiency and diversification
with lower food intake and thus exhibit smaller effects in retail
prices;
 The price-spread effects in terms of energy use, non-food costs
share and CPI differ across food items; and
 The higher the effect of an increase in the oil price, the greater the
retail price. This occurs through channels of food marketing such as
transportation, packaging and so on.
Case 2: Wage and Productivity
 Effect of wage and energy price change on Malaysian
industrial development. Khalid A.H., Zakariah A.R. and R.
Zarina R.M. Malaysian Institute of Economic Research,
Kuala Lumpur. Proceedings of the Malaysian National
Economic Conference July 2012 and due for publication
in JEM, UKM.
 Identifying key sectors of high income advanced
economy for Malaysia: A comparison between sectoral
and NKEA approaches by Khalid Abdul Hamid and
Zakariah Abdul Rashid, July 2012. (Edited UUM’s Paper)
Case 3: Subsidy Rationalization
 Economic Impacts of Subsidy Rationalization Malaysia by Khalid Abdul Hamid and
Zakariah Abdul Rashid MIER, Malaysia. Chapter 9: in Energy Market Integration in East Asia:
Theories, Electricity Sector and Subsidies By Yanrui Wu, Xunpeng Shi, Fukunari Kimura (Eds.)
ERIA Research Project Report 2011-17 (August 2012).
 Subsidy Internal Briefing Note: Rationalization of Fossil Fuel Subsidy in Malaysia. By Khalid
Abdul
Hamid,
MIER.
For
IISD,
Geneva.
January
2012.
Web
add:
http://www.iisd.org/gsi/resources/citizens-guide-energy-subsidies-malaysia
 Economic Impact of Higher Oil price in Malaysia: Integrated Input-Output Analysis. Khalid
Abdul Hamid, Doctor of Philosophy, UPM 2010.
 Effect of Higher Oil Price to Consumer Food Products in Malaysia. Khalid, A.H., Zakariah, A.R
and Mohd Khairul Hisyam H.. Article due for publication at the MJES, Malaysian Economic
Association, University of Malaya.
 The Effect of Higher oil Price on Consumer Food Products in Malaysia. Khalid, A.H.,
Zakariah, A.R. (Presented at the International Economic Conference, Anadolu University,
Eskisehir, Turkey .Vol. 1, T2D Economics of Oil.
Subsidy rationalization
End of Power
Presentation
11 things you need to do when study
abroad
1.
Make friends with locals
2.
Travel around
3.
Take opportunity to increase your knowledge
4.
Share the knowledge with new neighbours
5.
Learn new traits
6.
Enjoys the facilities
7.
Shop
8.
Sale
9.
Go to movies
10. Experience their delicacies
11.
Learn, unlearn and relearn (for flexibility)
Thriving in Graduate School
 You made it! Now the real work begins.
 Take advantage of all that the campus has to offer. Marymount, for
instance, extends all kinds of services to graduate students—the Center for
Teaching & Learning, counseling, study abroad, multimedia services, etc.
 Connect with other students juggling home/work/school. Some universities
have graduate student associations that facilitate peer support and lobby
on students’ behalf.
 Build relationships with your professors. The University of Washington offers
good practice guidelines.
 Befriend your librarians. They can make your life as a researcher so much
easier. Universities often have institutional subscriptions to online
bibliographic management programs—at Marymount, RefWorks —that
save useful citations for multiple bibliographies.
 Prepare for your career as intensely as you prepared for graduate school.
Hone your writing and presentation skills. Learn how to organize your work
and your time. Seek out opportunities – advice.pdf
 to present—on campus, in the community, and at conferences.
 to publish —everywhere. Work your way up to an academic journal in
your field.
 to network.
 Pat yourself on the back now and then. You are on your way to becoming
one of the roughly 12 percent of Malaysian who hold a graduate or
professional degree.
Parting notes
Be Creative, Innovative and committed in your
works. It’s the signal of success.
Makes things simple, but not easy.
Be moderate which does not mean slow and
procrastinate.
Finally, said Keynes in his remark on the economy
“"In the long run we are all dead”.
Says Islamic economy "in the long run we need to
grow a seed even we know that the world is going
to an end.