(TIỂU LUẬN) connection of economic variables in the input output table and its contribution to the economic growth estimation

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 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 so, they hire an economist to 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 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 a Technology Matrix 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 Agriculture, hunting, forestry, and fishing A Mining and quarrying B Food, beverages, and tobacco C Textiles and textile products D Leather, leather products, and footwear E Wood and products of wood and cork F Pulp, paper, paper products, printing, and publishing G Coke, refined petroleum, and nuclear fuel H Chemicals and chemical products I 10 Rubber and plastics J 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 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 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) 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) 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 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 (USD million) 2016 2017 296883,28 377291,82 381804,99 (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 311290,26 353663,69 21 325506,71 379657,80 315484,46 358770,08 22 328634,16 376000,37 502937,33 562946,12 23 320356,14 369638,89 381307,72 446473,40 24 216529,45 237444,79 331171,61 397399,22 25 166552,82 196326,99 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 demand incurred in year 2016 and 2017 respectively b New input-output table for year 2016-2017 15 16 Figure 3.2: New 34-industry input-output table for year 2016 and 2017 respectively c & d Impacts of global economic shock and economic stimulation policies to the changes of the input-output and profit/loss of industries Profit/Loss Industry code Industry name 2016 Profit Margin (%) 2017 2016 2017 Agriculture, hunting, forestry, and fishing 150838,56 238029,19 103% 171% Mining and quarrying 151169,36 217114,85 66% 90% Food, beverages, and tobacco -33418,78 87556,84 -9% 24% Textiles and textile products 266780,03 309304,99 599% 697% Leather, leather products, and footwear 310603,83 353878,48 6364% 7234% Wood and products of wood and cork 474918,06 535065,94 1695% 1919% Pulp, paper, paper products, printing, and publishing 209830,33 283323,43 122% 174% Coke, refined petroleum, and nuclear fuel 182993,31 39% 85% 92580,13 17 Chemicals products and chemical 23918,30 126417,11 6% 35% 10 Rubber and plastics 193890,62 247581,13 136% 180% 11 Other nonmetallic minerals 362826,90 413539,97 522% 608% 12 Basic metals and fabricated -113410,70 metal 24383,53 -19% 4% 13 Machinery, nec 14470,79 45345,72 7% 23% 14 Electrical equipment optical -41101,33 15878,39 -9% 4% 15 Transport equipment -56203,90 11467,08 -11% 3% 16 Manufacturing, nec; recycling 262273,86 297774,58 453% 554% 17 Electricity, supply 92252,91 173301,03 36% 79% 18 Construction -85135,82 6106,70 -13% 1% 19 Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of fuel 223636,58 274275,82 197% 234% and gas, and water 18 20 Wholesale trade and commission trade, except of motor vehicles and motorcycles -71426,71 -9858,41 -14% -2% Retail trade, except of motor vehicles and motorcycles; repair of household goods -15984,31 30966,09 -5% 9% 22 Hotels and restaurants 7902,63 59153,83 2% 19% 23 Inland transport 99411,38 148397,69 45% 67% 24 Water transport 152998,61 173071,25 241% 269% 25 Air transport 132530,01 161917,28 390% 471% 26 Other supporting and auxiliary transport activities; activities of travel agencies 211854,63 255369,04 329% 396% 27 Post and telecommunications 120748,72 169255,56 66% 93% 28 Financial intermediation 51565,40 106171,25 15% 29% 29 Real estate activities -85560,25 4976,84 -12% 1% 30 Renting of M&Eq and other -185870,72 business activities -106177,12 -28% -16% 21 19 31 Public administration and defense; compulsory social security -63605,15 9872,32 -11% 2% 32 Education -13276,16 15132,37 -6% 7% 33 Health and social work -60125,06 13492,66 -11% 2% 34 Other community, social, and personal services 13651,91 61716,96 4% 20% Figure 3.3: Table presents Profit (Loss) of 34 industries during 2016-2017 From the table, we can see that, for 2016, the global economic shock had a sizable impact on several Japanese industries To be more detailed, 12 industries experienced losses in output and profit (Industry code: 3, 12, 14, 15, 18, 20, 21, 29, 30, 31, 32, 33) Renting of M & Eq and other business activities (Industry code 30) is the one which was most impacted with a profit reduction of - $185870.72 million equivalent to - 28% profit margin However, the remaining industries still witnessed strong profit growth, most notably are Leather, leather products, and footwear (Industry code 5), and Wood and products of wood and cork (Industry code 6) industries with profit margins of 6364% and 1695%, respectively In 2017, thanks to the economic stimulus policy of the Japanese government, almost all the industries grew even though the growth was uneven Following last year's rally, Leather, leather products and footwear, along with Wood and products of wood and cork, continued to lead with profit margins of $353878.48 and $535065.94 (equivalent to the profit margin of 7234% and 1919%) Some industries also have an impressive increase in profit margin including Textiles and textile products (Industry code 4), Other nonmetallic minerals (Industry code 11), Manufacturing, nec; recycling (Industry code 16), Air transport (Industry code 25) Renting of M & Eq and other business activities is the industry with the lowest profit margin Although the loss in profit was less than in 2016, the computation still shows that the industry has suffered a heavy loss and makes it the only case of negative profit margin in 2017 To sum up, the Renting of M & Eq and other business activities is the most damaged industry by the global economic shock On the other hand, Leather, leather products, and footwear, along with Wood and products of wood and cork, are the two industries that have benefited most from the economic stimulation policies of the Japanese government 20 Question Summary Professor Wassily Leontief invented the input-output analysis in the 1930s with the main objective of analyzing interdependencies among industries in the economy (Leontief, 1974) This approach is mostly used to measure the consequences of positive and negative economic shocks, as well as to investigate spillover effects across the economy Economists may measure the change in production between sectors due to input fluctuations in one or more individual sectors using input-output models The method can also be done backwards to decide which effect on the input is causing the output changes The input-output table estimation approach is regarded as a useful tool for estimating an economy's environmental and social long-term growth In 34 industries, the profitability results are negative, illustrating Japan's inefficient economy over years The total industry was seen to be less efficient according to the disappointing results of 34 initial sectors in Japan In 2017, almost all sectors expanded, while development was erratic, with the economic stimulus program of the Japanese government Although the net loss was lower than in 2016, the analysis also indicates that the industry experienced a significant loss and is still seeing a negative profit margin in 2017 In general the Japanese economy has been expected to improve over a three-year period, but the initial decline in 2014 and 2015 has also adversely affected overall production in 34 sectors Recommendations The coming decade gives Japan the chance to transform its course, in part by capitalizing on huge international trade flows, the growth in the developing world of billions of new urban customers, and technological breakthroughs But the current world economy is not just being realigned Japan has the time to take bolder action, larger investments and more profound changes Decades earlier, the world was exposed to "lean" methods by japanese producers These principles can now be applied to emerging markets by companies across the entire Japanese economy and they can make modern technology accessible to them Focus on the goals addressed here will help to tackle lasting legacy problems, and will lead Japan to recovery and renewal more quickly (McKinsey Global Institute 2015) Question a Encryption process from encode to decode of the secret messages Three different messages for the respective three secret agents are: Message (1): “Attack in North State Street in Chicago on Monday afternoon.” Message (2) “Attack in Main Street in Dallas at midnight on Tuesday.” Message (3) “Attack at Diridon Station in San Jose on Friday morning.” The overall encryption process includes encode and decode of the secret messages, in which 21 the encoder is a matrix and the decoder is its inverse ENCODE MESSAGE Use the below x matrix (A) to encode the secret messages: 2 1 2 1 Translate all the letters to numbers: Assign the numbers 1-26 to the letters in the alphabet, for example A = 1, B = 2, C = and so on Since the encoding matrix is a x matrix, only numbers could be encoded at a time Break the message into packets of numbers each: Message (1) 11 18 18 14 13 25 18 20 20 20 15 14 20 14 5 15 14 15 14 19 19 20 15 20 15 15 20 20 14 14 Message (2) 11 19 20 20 14 1 14 15 19 20 14 19 20 12 20 14 22 13 20 12 13 20 18 14 21 25 Message (3) 11 18 19 15 15 20 20 14 14 15 18 20 20 10 14 14 15 20 14 15 25 9 14 19 19 18 13 14 Multiply this matrix on the left by A: Message (1) 28 90 120 66 108 71 62 62 126 113 24 59 94 60 81 49 39 49 91 80 68 102 158 70 114 87 48 110 138 147 43 64 71 31 66 53 47 58 82 81 66 80 122 68 78 59 46 84 88 111 Message (2) 28 74 104 67 49 112 43 135 46 24 57 72 33 33 65 36 95 31 68 88 110 69 35 126 65 165 92 43 63 76 59 44 91 33 88 19 23 66 66 92 59 27 88 57 125 82 Message (3) 28 70 102 107 101 62 59 91 91 21 24 31 75 98 72 46 37 72 66 14 68 86 126 145 131 62 87 67 139 35 43 66 59 60 62 37 44 45 67 14 66 64 90 107 101 60 77 49 109 21 Finally, get the number sequences of three encoded messages: Encoded Message (1) “28 24 68 43 66 90 59 102 64 80 120 94 158 71 122 66 60 70 31 68 108 81 114 66 78 71 49 87 53 59 62 39 48 47 46 62 49 110 58 84 126 91 138 82 88 113 80 147 81 111” Encoded Message (2) “28 24 68 43 66 70 31 86 66 64 102 75 126 59 90 107 98 145 60 107 101 72 131 62 101 62 46 62 37 60 59 37 87 44 77 91 72 67 45 49 91 66 139 67 109 21 14 35 14 21” Encoded Message (3) “28 24 68 43 66 70 31 86 66 64 102 75 126 59 90 107 98 145 60 107 101 72 131 62 101 62 46 62 37 60 59 37 87 44 77 91 72 67 45 49 91 66 139 67 109 21 14 35 14 21” DECODED MESSAGE Use the inverse matrix (A-1) as the decoding matrix: 0 1⁄2 (-1)⁄2 (-1)⁄3 1⁄3 (-1)⁄3 2⁄3 (-1)⁄12 (-1)⁄6 (-1)⁄3 1⁄2 5⁄12 24 1⁄6 1⁄3 (-1)⁄3 1⁄6 3⁄4 (-1)⁄2 (-1)⁄2 (-1)⁄2 3⁄4 Multiply the matrices of coded messages on the left by A -1and then getting the full sequence as shown below: Message (1) 20 20 11 14 14 15 18 20 19 20 20 19 20 18 5 20 14 15 15 14 13 15 14 25 20 18 14 15 15 14 Message (2) 11 19 20 20 14 1 14 15 19 20 14 19 20 12 20 14 13 20 12 13 20 18 14 21 25 Message (3) 11 18 19 15 15 20 20 14 14 15 18 20 20 10 14 14 15 20 14 15 25 9 14 19 19 18 13 14 Convert the number sequences into letters again, we would get three original code messages b Integration of risk management practices with matrices to ensure the safety of the data transmitted online Encryption is the method converting information into secret code, thus hiding its true meaning The science of encrypting and decrypting information is called cryptography, which generally involves the use of secret keys that only the sender and receiver know This empowers the encryption to protect the confidentiality, privacy and integrity of the data stored on computer systems or transmission channels When an encoded message is intercepted by the unauthorized, the time and difficulty of guessing the encryption key is what makes encryption such a valuable security tool However, the cryptographic keys must be carefully managed to ensure data remains protected from theft, loss or misuse, yet accessible when needed Key management, thus, is one of the biggest challenges when designing an encryption strategy and it is necessary to establish a benchmark for how the organization configures, controls, monitors and manages access to its keys Nowadays, cryptography continues playing an important role in numerous fields and industries such as wireless communications, banking systems and businesses Firstly, in banking industries, banks have to encrypt the secret information like credit card data or banking transactions Secondly, in wireless communications, when connected via Bluetooth, two devices will agree on a common pair of keys to exchange encrypted data, thus preventing hackers from decrypting unless they have the share link key Lastly, in terms of business, avoiding hackers and data thieves is the initial priority of corporations when using 25 cryptography as a means of protecting online data 26 References 1) Grady, Patrick and Muller, R Andrew (1986) On the Use and Misuse of Input-Output Based Impact Analysis in Evaluation Published in: The Canadian Journal of Program Evaluation , Vol 3, No (1988): pp 49-61 [Accessed on: 19 April 2021] 2) Harding, R 2018, 'Japan’s economy shrinks for first time since 2015', Financial Times, 16 May, viewed 21 April 2021, 3) Kajimoto, T 2018, 'Japan's economy shrinks most in four years as global risks hit business spending', Reuters, 10 December, viewed 19 April 2021, 4) Leontief, Wassily (1974) Structure of the World Economy: Outline of Simple InputOutput Formulation American Economic Review P 823 – 834 Available at: https://mpra.ub.uni-muenchen.de/22063/ [Accessed on: 19 April 2021] 5) Mckinsey Global Institute 2015, The future of Japan: Reigniting productivity and growth, viewed 22 April 2021, 6) Partington, R 2017, 'Japanese economy posts longest expansion in more than a decade', The Guardian , 14 August, viewed 22 April 2021, 7) R 2018, 'Japan posts fastest economic growth since 2016 in the second quarter', CNBC, September, viewed 22 April 2021, 8) Rebecca Bess, Zoë O Ambargis, (2011) Input-Output Models for Impact Analysis: Suggestions for Practitioners Using RIMS II Multipliers Presented at the 50th Southern Regional Science Association Conference Available at: https://www.bea.gov/system/files/papers/WP2012-3.pdf [Accessed on: 19 April 2021] 9) Nigel, S 2018, ‘How cryptography enables online shopping, cloud tech, and the block 27 chain’, The next web, 29 July, viewed 22 April 2021, 10) 11) Luke, S 2016, ‘Why Cryptography is a new gold for Banking and Blockchain’,Security Intelligent, 30 September, viewed 22 April 2021, 12) 13) Rick, R 2013, ’38 millions reasons to use Cryptography for Business’, 11 November, viewed 22 April 2021, 14) Raymod, K 2018, ‘Why is cryptography important in banking’, viewed 22 April 2021, 15) ‘How encryption works in Bluetooth’, viewed 22 April 2021, 28 ... 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. .. 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. .. + 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