QUANTITATIVE ANALYSIS GROUP REPORT PDF

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QUANTITATIVE ANALYSIS

TEAM REPORT

Course Code: ECON1267 Group Members: Dang Minh Chau - s3699387 Le Thuy Duong - s3754192 Le Tran Khanh Linh - s3697282 Phan Thi Cam Thuy - s3811663 Dinh Hong Yen Vy - s3803738 Lecturer: Mr. Selim Ergun Tutorial Time: Friday 11.30 tutorial

Question 1 a. Introductory review about input-output table

Professor Wassily Leontief created Input-output analysis in the 1930s (Leontief, 1974). The primary purpose of the Input-output framework was to analyze interdependencies among industries in the economy. This method is often used to estimate the effects of positive or negative economic shocks and analyze spillover effects throughout the economy. The foundation of the input-output analysis relates to the input-output tables. Such tables include a series of rows and columns of supply chain quantitative data for all sectors in an economy. b. Connection of economic variables in the input-output table and its contribution

to the economic growth estimation The branches are listed in the header row for each row and column. The data in each column corresponds to the amount of input utilized in that industry's production. For example, the column for car manufacturing lists the resources needed to make cars (e.g., steel, aluminum, plastic, electronics). The input-output models consider three types of World: direct, indirect, and induced (Rebecca Bess, Zoë O. Ambargis, 2011). By using input-output models, economists can estimate the change in output between sectors due to input variability in one or more specific industries.For example, a local government wants to build a new bridge and needs to verify the investment costs. To do so, they hire an economist to do an input-output analysis study for estimating the cost of the bridge, the materials needed, and how many workers the construction company will hire. He converts this information into metrics and applies them to an input-output model to find three levels of impact. -

The direct effect of an economic shock is a change in the initial cost. For example, building a bridge will cost cement, steel, construction equipment, labor, and other inputs.

-

The employment of the input suppliers causes the indirect or secondary impact to meet work needs.

-

The effect, also known as a tertiary effect, occurs because the workers of the supplying companies buy more goods and services.

Input-output analysis can also be performed in reverse to determine which effect on the input is the cause of the changes in the output. c. Potential contribution of input-output table estimation methods to the estimation

of environmental and social sustainable development of an economy In my opinion, the input-output table estimation method can be considered as a helpful method in the estimation of environmental and social sustainable development of an economy 2

due to the following principal reasons. First, this method shows the dependence between the output and the input of industries in the economy. Based on this information, economists can assess the linkages between economic sectors, such as having the most influence, the degree of dependence between sectors, and what will happen when promoting industry has grown stronger. Second, the impact on the three levels mentioned above will provide in-depth impact information for economists and policymakers. Based on an analysis of the inputoutput table estimation method, economists, policymakers can have the best overview of all industries in the economic system and give appropriate development directions. However, the input-output table analysis has not considered the price impact, and the financial aspects tend to reduce factors in the macroeconomy. Therefore, to estimate an economy's environmental and social sustainable development, it is necessary to apply other analyzes, such as cost-benefit analysis.

Question 2 a. Technology Matrix

3

Figure 2.1: Estimation of the technology matrix of the 35-industry

b. Analysis of the input and output of each industry Assuming 34 industries as the new variable which I have put in the table below. For example, the industry of Agriculture, hunting, forestry, and fishing is A.

No.

Industry

New Variab le

1

Agriculture, hunting, forestry, and fishing

A

2

Mining and quarrying

B

3

Food, beverages, and tobacco

C

4

Textiles and textile products

D

5

Leather, leather products, and footwear

E

6

Wood and products of wood and cork

F

7

Pulp, paper, paper products, printing, and publishing

G

8

Coke, refined petroleum, and nuclear fuel

H

9

Chemicals and chemical products

I

10

Rubber and plastics

J

4

11

Other non-metallic minerals

K

12

Basic metals and fabricated metals

L

13

Machinery, NEC

M

14

Electrical and optical equipment

N

15

Transport equipment

O

16

Manufacturing, NEC; recycling

P

17

Electricity, gas, and water supply

Q

18

Construction

R

19

Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel

S

20

Wholesale trade and commission trade, except of motor vehicles and motorcycles

T

21

Retail trade, except of motor vehicles and motorcycles; repair of household goods

U

22

Hotels and restaurants

V

5

23

Inland transport

W

24

Water transport

X

25

Air transport

Y

26

Other supporting and auxiliary transport activities; activities of travel agencies

Z

27

Post and telecommunications

AA

28

Financial intermediation

BB

29

Real estate activities

CC

30

Renting of M&Eq and other business activities

DD

31

Public administration and defence; compulsory social security

EE

32

Education

FF

33

Health and social work

GG

34

Other community, social, and personal services

HH

Figure 2.2: Labels of new variables

Total demand of industry A = 0.12c1 + 0.00c2 + 0.17c3 + 0.01c4 + 0.01c5 + … + 0.00c33 + 0.00c34 + external demand of industry A

6

From the input and output data, the technology matrix can be analyzed as: -

For industry A, to produce $c1, it needs to consume 0.12c1 of A

-

For industry B, to produce $c2, it needs to consume 0.00c2 of A

-

For industry C, to produce $c3, it needs to consume 0.17c3 of A

-

For industry D, to produce $c4, it needs to consume 0.01c4 of A

-

…

-

For industry HH, to produce $c34, it needs to consume 0.00c34 of A

Consequently, from the technology matrix, total consumption of industry A is caused by other industries. As a result, the total consumption required by A from other industries is 0.12c1 + 0.00c2 + 0.17c3 + 0.01c4 + 0.01c5 + … + 0.00c33 + 0.00c34 + external demand of industry A c. Estimation and rankings of the total profit(loss) value and profit(loss) margin of the 34-industry To calculate profit or loss and margin of 34 industries that consumption is revenue, production is cost. Two tables below illustrate the Profit (Loss) and Profit (Loss) Margin ranking from the highest to lowest variables.

Industry

Consumption

Production

Profit

Leather, leather products, and footwear

2,880

5,760

(2,880)

Wood and products of wood and cork

4,207

8,414

(4,206)

Textiles and textile products

37,750

75,490

(37,740)

Other non-metallic minerals

38,842

77,684

(38,842)

Manufacturing, nec; recycling

56,100

112,200

(56,100)

7

Air transport

59,903

119,806

(59,903)

Other supporting and auxiliary transport activities; activities of travel agencies

64,698

129,392

(64,694)

Pulp, paper, paper products, printing, and publishing

82,049

164,053

(82,004)

Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel

82,914

165,749

(82,835)

Water transport

91,911

183,812

(91,901)

Rubber and plastics

108,280

216,536

(108,257)

Agriculture, hunting, forestry, and fishing

143,535

281,249

(137,714)

Mining and quarrying

185,017

368,473

(183,456)

Electricity, gas, and water supply

214,981

429,937

(214,956)

Coke, refined petroleum, and nuclear fuel

237,069

473,724

(236,655)

Post and telecommunications

237,468

474,936

(237,468)

Inland transport

303,893

607,704

(303,811)

Financial intermediation

361,063

721,802

(360,739)

Chemicals and chemical products

417,491

834,365

(416,874)

8

Machinery, nec

449,772

899,542

(449,771)

Education

573,717

1,147,435

(573,717)

Renting of M&Eq and other business activities

575,670

1,151,323

(575,653)

Hotels and restaurants

610,365

1,220,723

(610,358)

Other community, social, and personal services

625,709

1,251,418

(625,709)

Food, beverages, and tobacco

670,807

1,337,939

(667,132)

Basic metals and fabricated metal

737,843

1,475,681

(737,838)

Electrical and optical equipment

799,084

1,598,167

(799,083)

Retail trade, except of motor vehicles and motorcycles; repair of household goods

808,298

1,616,529

(808,231)

Wholesale trade and commission trade, except of motor vehicles and motorcycles

839,530

1,678,837

(839,308)

Transport equipment

960,853

1,921,691

(960,838)

1,532,497

3,064,993

(1,532,496)

Health and social work

9

Public administration and defense; compulsory social security

1,607,298

3,214,596

(1,607,298)

Construction

1,684,393

3,368,780

(1,684,387)

Real estate activities

1,960,727

3,921,455

(1,960,727)

Figure 2.3: Profit (Loss) value of 34 industries in 2015, 2016 , 2017

Industry

Margin

Agriculture, hunting, forestry, and fishing

-95.945%

Mining and quarrying

-99.157%

Food, beverages, and tobacco

-99.452%

Coke, refined petroleum, and nuclear fuel

-99.825%

Chemicals and chemical products

-99.852%

Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel

-99.905%

Financial intermediation

-99.910%

Pulp, paper, paper products, printing, and publishing

-99.946%

Inland transport

-99.973%

10

Wholesale trade and commission trade, except of motor vehicles and motorcycles

-99.974%

Textiles and textile products

-99.975%

Wood and products of wood and cork

-99.977%

Rubber and plastics

-99.979%

Electricity, gas, and water supply

-99.989%

Water transport

-99.989%

Retail trade, except of motor vehicles and motorcycles; repair of household goods

-99.992%

Other supporting and auxiliary transport activities; activities of travel agencies

-99.994%

Renting of M&Eq and other business activities

-99.997%

Other nonmetallic minerals

-99.998%

Leather, leather products, and footwear

-99.998%

Transport equipment

-99.998%

Hotels and restaurants

-99.999%

Manufacturing, nec; recycling

-99.999%

11

Basic metals and fabricated metal

-99.999%

Construction

-100.000%

Air transport

-100.000%

Machinery, nec

-100.000%

Electrical and optical equipment

-100.000%

Post and telecommunications

-100.000%

Health and social work

-100.000%

Other community, social, and personal services

-100.000%

Public administration and defense; compulsory social security

-100.000%

Real estate activities

-100.000%

Education

-100.000%

Figure 2.4: Profit (Loss) margin of 34 industries in 2015, 2016 , 2017

The profit (loss) variables express the difference between consumption and production among 34 industries. However, all variables are negative, so they were concluded as the loss variable. Additionally, the industry of leather, leather products, and footwear produces the highest profit, meanwhile the real estate activities industry has the lowest profitable figure. On the other hand, the profit margin presents the profitability of 34 industries, which is displayed in percentage. The industry that comes along with the highest level of profitability is agriculture, hunting, forestry and fishing and the lowest profitability belongs to the education industry. Consequently, the profitable figures of 34 industries are negative, which clearly illustrate Japan's inefficient economy throughout 3 years. 12

d. Discussion and conclusion of all above findings According to the negative result of 34 initial industries of Japan, the overall market experienced the decreasing sign of efficiency. The reduction in the common economy of Japan started from 2015 due to many reasons including to the 0.2% decline of the total domestic products which marked the end of repetitively 8 growing quarters (Harding 2018). Besides, another reason leading to the ineffective economy was the consequence of natural disaster in 2014 which significantly affected the buying power of expenditure industries (Kajimoto 2018). In 2016, the economy experienced a slight increase due to the rising capital expenditure which was driven by the production of cars and semiconductors (Reuters 2018). The positive result of economic development from 2016 leading to the massive growth in 2017 due to the low rate of unemployment and the increasing domestic expenditure to prepare for Tokyo Olympics 2020 (Partington 2017). Overall, there was a prospective increase of Japan’s economy throughout 3 years but the initial decrease in 2014 and 2015 still affected the overall productivity of 34 industries negatively.

Question 3 a. Total Output needed to satisfy the change of the external demand We have the following formula: Total output matrix (P) = Technology matrix (M) x Total output matrix (P) + External demand matrix (D) P–MxP=D (I – M) x P = D P = (I – M)^−1 x D Since the external demand was impacted by the global economic shock 2016 (decrease 10%) and the economic stimulation policies (increase 3%), the new external demand will be: D2016 new = D2016 x 0.9 D2017 new = D2017 x 1.03 Applying the formula to calculate the new Total Output needed to satisfy the change of the external demand, we get the result in the table below:

Total Output needed Industry Code

with the changed External demand

Total Output needed Industry Code

with the changed External demand

13

(USD million)

2016

2017

1

296883,28

377291,82

2

381804,99

3

(USD million)

2016

2017

18

590503,24

651792,58

459181,25

19

337264,39

391619,16

341758,89

447984,41

20

441351,68

514200,11

4

311290,26

353663,69

21

325506,71

379657,80

5

315484,46

358770,08

22

328634,16

376000,37

6

502937,33

562946,12

23

320356,14

369638,89

7

381307,72

446473,40

24

216529,45

237444,79

8

331171,61

397399,22

25

166552,82

196326,99

9

406985,14

486840,89

26

276215,99

319876,72

10

336690,13

384791,85

27

303699,07

352016,08

11

432377,64

481508,85

28

403435,68

472245,91

14

12

473649,94

598579,27

29

631933,33

728603,96

13

225007,41

240854,62

30

472784,03

541325,66

14

397091,35

448557,60

31

512469,76

590892,98

15

435691,45

466349,29

32

192655,30

219921,96

16

320129,05

351548,16

33

510791,27

564452,10

17

345590,81

392513,75

34

326713,90

377617,66

Figure 3.1: Total output of the 34-industry that needed to satisfy the changes of external dem...