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From the Desert to the Glaciers: Exploring Interregional Connections of the Chilean Economy International Workshop on General Equilibrium Modeling, Universidad Adolfo Ibañez Viña del Mar, December 3-4, 2018 Eduardo Haddad Denise Li Karina Sass Keyi Ussami Sofia Arantes

From the Desert to the Glaciers: Exploring Interregional … · From the Desert to the Glaciers: Exploring Interregional Connections of the Chilean Economy International Workshop

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From the Desert to the Glaciers:

Exploring Interregional Connections

of the Chilean Economy

International Workshop on General Equilibrium

Modeling, Universidad Adolfo Ibañez

Viña del Mar, December 3-4, 2018

Eduardo Haddad Denise Li Karina Sass Keyi Ussami Sofia Arantes

2

Research team – NEREUS

Eduardo Amaral Haddad (coordinator)

Ademir Antônio Moreira Rocha

Bruno Proença Pacheco Pimenta

Denise Leyi Li

Karina Simone Sass

Keyi Ando Ussami

Lucas Cardoso Correa Dias

Raphael Pinto Fernandes

Sofia Marques Arantes

Department of Economics, University of Sao Paulo

Outline

1. Introduction

2. Structure of the interregional data

3. Basic socioeconomic indicators

4. Theoretical background

5. Multiplier analysis

6. Linkage analysis

7. Next steps

Department of Economics, University of Sao Paulo 3

From the Desert to the Glaciers

Department of Economics, University of Sao Paulo 4

5

Introduction

As part of the development of an interregional CGE (ICGE) model

for Chile, a fully specified interregional input-output database was

developed under conditions of limited information.

Such database is needed for calibration of the ICGE model.

Lack of adequate data is a problem: but do you wait until the data

have improved sufficiently, or do you start with existing data, no

matter how imperfect, and improve the database gradually?

Department of Economics, University of Sao Paulo

6

Structure of interregional Input-Output models

Department of Economics, University of Sao Paulo

7

Data demanding process

Department of Economics, University of Sao Paulo

Large amount of data

Problem?!

8

Chilean interregional input-output system, 2014

Department of Economics, University of Sao Paulo

9

List of sectors

Department of Economics, University of Sao Paulo

S1 Agropecuario-silvícola y Pesca

S2 Minería

S3 Industria manufacturera

S4 Electricidad, gas, agua y gestión de desechos

S5 Construcción

S6 Comercio, hoteles y restaurantes

S7 Transporte, comunicaciones y servicios de información

S8 Intermediación financiera

S9 Servicios inmobiliarios y de vivienda

S10 Servicios empresariales

S11 Servicios personales

S12 Administración pública

10

List of regions

Department of Economics, University of Sao Paulo

R1 XV De Arica y Parinacota

R2 I De Tarapacá

R3 II De Antofagasta

R4 III De Atacama

R5 IV De Coquimbo

R6 V De Valparaíso

R7 RMS Región Metropolitana de Santiago

R8 VI Del Libertador General Bernardo O'Higgins

R9 VII Del Maule

R10 VIII Del Biobío

R11 IX De La Araucanía

R12 XIV De Los Ríos

R13 X De Los Lagos

R14 XI Aysén del General Carlos Ibáñez del Campo

R15 XII De Magallanes y de la Antártica Chilena

11

Basic socioeconomic indicators – GDP and population

Department of Economics, University of Sao Paulo Source: Banco Central de Chile.

12

Basic socioeconomic indicators – GDP per capita and labor

Department of Economics, University of Sao Paulo Source: Banco Central de Chile.

13

Main sectorial activity by region

Department of Economics, University of Sao Paulo

Region Main activity % of

RegionTotal

% of Sector Total

R1 De Arica y Parinacota Transporte, comunicaciones y servicios de

información 18% 1.3%

R2 De Tarapacá Minería 35% 8.1%

R3 De Antofagasta Minería 48% 50%

R4 De Atacama Minería 31% 7.9%

R5 De Coquimbo Minería 27% 8%

R6 De Valparaíso Industria manufacturera 28% 14%

R7 Región Metropolitana de Santiago Comercio, hoteles y restaurantes 19% 70%

R8 Del Libertador General Bernardo O'Higgins Minería 20% 9,4%

R9 Del Maule Industria manufacturera 21% 4,5%

R10 Del Biobío Industria manufacturera 36% 4%

R11 De La Araucanía Industria manufacturera 19% 16%

R12 De Los Ríos Industria manufacturera 25% 2,6%

R13 De Los Lagos Industria manufacturera 33% 5,8%

R14 Aysén del General Carlos Ibáñez del Campo Agropecuario-silvícola y Pesca 49% 7,7%

R15 De Magallanes y de la Antártica Chilena Industria manufacturera 29% 1,7%

14

Regional output share by sector

Department of Economics, University of Sao Paulo

Region Agropecuario-

silvícola y Pesca Minería

Industria manufacturera

All Sectors

R1 De Arica y Parinacota 1,4% 0,2% 0,5% 0,7%

R2 De Tarapacá 0,9% 8,1% 1,3% 2,4%

R3 De Antofagasta 0,4% 49,7% 4,6% 10,6%

R4 De Atacama 1,5% 7,9% 0,3% 2,5%

R5 De Coquimbo 5,1% 8,0% 0,6% 2,9%

R6 De Valparaíso 8,3% 7,4% 13,6% 9,4%

R7 Región Metropolitana de Santiago 9,2% 7,8% 41,7% 44,2%

R8 Del Libertador General Bernardo O'Higgins 16,2% 9,4% 4,5% 5,0%

R9 Del Maule 10,4% 0,4% 4,0% 3,6%

R10 Del Biobío 12,6% 0,0% 16,1% 8,9%

R11 De La Araucanía 6,6% 0,0% 2,5% 2,6%

R12 De Los Ríos 4,4% 0,0% 2,6% 1,6%

R13 De Los Lagos 14,0% 0,0% 5,8% 3,7%

R14 Aysén del General Carlos Ibáñez del Campo 7,7% 0,2% 0,2% 0,8%

R15 De Magallanes y de la Antártica Chilena 1,3% 1,0% 1,7% 1,2%

Total 100% 100% 100% 100,0%

Trade Balance (billions CLP 2014)

> 2,000

1,000 - 2,000

0 - 1,000

(-1,000) - 0

(-2,000) - (-1,000)

≤ (-2,000)

RoW

3

4

14

5

2

9

13

10

11

1

12

15

8

6

7

Trade (billions CLP 2014)

< 250

250 - 1,000

1,000 - 2,500

2,500 - 5,000

> 5,000

3

4

14

5

2

9

10

11

1

12

15

13

8

6

7

Trade

Antofagasta

RMS

RoW

La Araucanía

RoW

16

Transport system in Chile x Average travel time

Department of Economics, University of Sao Paulo

17

Theoretical background – Conventional Input-Output model

The conventional input-output model is given by the system of matrix

equations:

(1) 𝑥 = 𝐴𝑥 + 𝑦

(2) 𝑥 = (I – A)-1 y = By

Where 𝑥 and 𝑦 are respectively (nx1) dimension vectors of gross output and

final demand;

𝐴 is a (nxn) matrix of input coefficients 𝑎𝑖𝑗 defined as the amount of product i

required per unit of product j (in monetary terms), for i, j = 1,…, n;

and B is a (nxn) dimension matrix known as the Leontief inverse.

Department of Economics, University of Sao Paulo

18

Theoretical background – Interregional Input-Output model

In an interregional context, with R different regions:

𝑥 =𝑥1

⋮𝑥𝑅

; 𝐴 =𝐴11 ⋯ 𝐴1𝑅

⋮ ⋱ ⋮𝐴𝑅1 ⋯ 𝐴𝑅𝑅

; 𝑦 =𝑦1

⋮𝑦𝑅

𝑎𝑛𝑑 𝐵 =𝐵11 ⋯ 𝐵1𝑅

⋮ ⋱ ⋮𝐵𝑅1 ⋯ 𝐵𝑅𝑅

so that (2) will be:

(3) 𝑥1 = 𝐵11𝑦1 + ⋯ + 𝐵1𝑅𝑦𝑅

𝑥𝑅 = 𝐵𝑅1𝑦1 + ⋯ + 𝐵𝑅𝑅𝑦𝑅

Department of Economics, University of Sao Paulo

19

Theoretical background – Interregional Input Output model

The final demand 𝑦 can be decomposed in expenditures from domestic

regions (𝑣) and from the foreign region (𝑒):

𝑣 =𝑣11 ⋯ 𝑣1𝑅

⋮ ⋱ ⋮𝑣𝑅1 ⋯ 𝑣𝑅𝑅

; 𝑒 =𝑒1

⋮𝑒𝑅

so that (3) will be:

(4) 𝑥1 = 𝐵11(𝑣11+ ⋯ + 𝑣1𝑅 + 𝑒1) + ⋯ + 𝐵1𝑅(𝑣𝑅1+ ⋯ + 𝑣𝑅𝑅 + 𝑒𝑅)

𝑥𝑅 = 𝐵𝑅1(𝑣11+ ⋯ + 𝑣1𝑅 + 𝑒1) + ⋯ + 𝐵𝑅𝑅(𝑣𝑅1+ ⋯ + 𝑣𝑅𝑅 + 𝑒𝑅)

A region’s output depends on demand originating from itself, on demand

from other regions (degree of interregional integration) and also on foreign

demand.

Department of Economics, University of Sao Paulo

20

Regional Distribution of the Average Total and Net Output Multipliers (in %)

Department of Economics, University of Sao Paulo Source: calculations by the authors.

Total output Multiplier Net output Multiplier

Intraregional share

Interregional share

Intraregional share

Interregional share

R1 De Arica y Parinacota 80,61 19,39 48,19 51,81

R2 De Tarapacá 81,12 18,88 50,20 49,80

R3 De Antofagasta 81,41 18,59 51,66 48,34

R4 De Atacama 81,40 18,60 51,53 48,47

R5 De Coquimbo 75,82 24,18 35,79 64,21

R6 De Valparaíso 78,52 21,48 41,57 58,43

R7 Región Metropolitana de Santiago 88,09 11,91 68,67 31,33

R8 Del Libertador General Bernardo O'Higgins 75,64 24,36 35,43 64,57

R9 Del Maule 77,49 22,51 38,76 61,24

R10 Del Biobío 81,00 19,00 48,02 51,98

R11 De La Araucanía 77,67 22,33 31,82 68,18

R12 De Los Ríos 80,02 19,98 37,44 62,56

R13 De Los Lagos 79,95 20,05 37,62 62,38

R14 Aysén del General Carlos Ibáñez del Campo 74,09 25,91 32,69 67,31

R15 De Magallanes y de la Antártica Chilena 85,59 14,41 61,45 38,55

21

Regional Distribution of the Average Total and Net Output Multipliers (in %)

Department of Economics, University of Sao Paulo Source: calculations by the authors.

Total output Multiplier Net output Multiplier

Intraregional share

Interregional share

Intraregional share

Interregional share

R1 De Arica y Parinacota 80,61 19,39 48,19 51,81

R2 De Tarapacá 81,12 18,88 50,20 49,80

R3 De Antofagasta 81,41 18,59 51,66 48,34

R4 De Atacama 81,40 18,60 51,53 48,47

R5 De Coquimbo 75,82 24,18 35,79 64,21

R6 De Valparaíso 78,52 21,48 41,57 58,43

R7 Región Metropolitana de Santiago 88,09 11,91 68,67 31,33

R8 Del Libertador General Bernardo O'Higgins 75,64 24,36 35,43 64,57

R9 Del Maule 77,49 22,51 38,76 61,24

R10 Del Biobío 81,00 19,00 48,02 51,98

R11 De La Araucanía 77,67 22,33 31,82 68,18

R12 De Los Ríos 80,02 19,98 37,44 62,56

R13 De Los Lagos 79,95 20,05 37,62 62,38

R14 Aysén del General Carlos Ibáñez del Campo 74,09 25,91 32,69 67,31

R15 De Magallanes y de la Antártica Chilena 85,59 14,41 61,45 38,55

22

Components of decomposition of regional output based on the sources of final demand (in %)

Department of Economics, University of Sao Paulo Source: calculations by the authors.

ORIGIN OF FINAL DEMAND

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 ROW

REG

ION

AL

OU

TPU

T

R1 52,98 3,39 4,29 0,90 1,17 1,23 7,29 0,58 0,78 1,72 1,02 0,47 1,34 0,30 0,40 22,14

R2 0,56 39,50 1,61 0,37 0,56 0,69 3,90 0,28 0,40 0,96 0,56 0,26 0,73 0,17 0,20 49,26

R3 0,37 0,96 14,14 0,50 1,33 1,79 11,17 0,60 1,07 2,44 1,46 0,67 1,74 0,22 0,20 61,33

R4 0,27 0,75 1,57 22,67 2,03 2,27 14,29 0,71 1,27 2,79 1,65 0,74 1,94 0,25 0,23 46,57

R5 0,18 0,48 1,17 0,56 40,23 1,89 9,53 0,66 0,78 1,52 0,78 0,34 0,96 0,19 0,23 40,51

R6 0,16 0,47 1,03 0,49 1,46 35,37 24,34 1,30 1,22 2,01 1,01 0,40 1,13 0,23 0,25 29,13

R7 0,28 0,67 1,58 0,71 2,08 6,35 51,31 2,72 2,48 4,03 1,92 0,80 2,20 0,41 0,47 21,99

R8 0,15 0,41 0,88 0,40 1,08 2,95 21,66 27,04 1,57 2,20 1,00 0,39 1,07 0,22 0,23 38,74

R9 0,20 0,59 1,15 0,47 1,28 2,70 18,55 1,61 41,54 3,99 1,74 0,58 1,65 0,32 0,32 23,30

R10 0,27 0,81 1,48 0,64 1,46 2,33 15,91 1,21 2,29 40,79 3,31 0,97 2,63 0,51 0,46 24,95

R11 0,18 0,52 1,00 0,42 0,86 1,58 9,35 0,73 1,31 4,44 56,02 1,46 3,21 0,40 0,44 18,08

R12 0,22 0,67 1,27 0,52 1,07 1,77 10,74 0,82 1,27 3,83 3,67 43,30 5,18 0,52 0,46 24,67

R13 0,24 0,74 1,43 0,56 1,13 1,98 11,28 0,89 1,28 3,62 2,80 1,79 44,92 0,64 0,52 26,17

R14 0,29 1,11 2,22 0,60 1,30 3,11 14,66 1,29 1,40 3,26 1,59 0,73 2,49 33,57 1,30 31,09

R15 0,20 0,63 1,07 0,40 0,72 1,01 6,27 0,43 0,65 1,71 1,08 0,51 1,54 0,97 53,39 29,39

Chile 0,7 1,6 2,8 1,1 2,8 7,1 31,1 3,0 3,3 6,6 3,2 1,4 3,6 0,6 1,0 30,0

23

Components of decomposition of regional output based on the sources of final demand (in %)

Department of Economics, University of Sao Paulo Source: calculations by the authors.

ORIGIN OF FINAL DEMAND

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 ROW

REG

ION

AL

OU

TPU

T

R1 52,98 3,39 4,29 0,90 1,17 1,23 7,29 0,58 0,78 1,72 1,02 0,47 1,34 0,30 0,40 22,14

R2 0,56 39,50 1,61 0,37 0,56 0,69 3,90 0,28 0,40 0,96 0,56 0,26 0,73 0,17 0,20 49,26

R3 0,37 0,96 14,14 0,50 1,33 1,79 11,17 0,60 1,07 2,44 1,46 0,67 1,74 0,22 0,20 61,33

R4 0,27 0,75 1,57 22,67 2,03 2,27 14,29 0,71 1,27 2,79 1,65 0,74 1,94 0,25 0,23 46,57

R5 0,18 0,48 1,17 0,56 40,23 1,89 9,53 0,66 0,78 1,52 0,78 0,34 0,96 0,19 0,23 40,51

R6 0,16 0,47 1,03 0,49 1,46 35,37 24,34 1,30 1,22 2,01 1,01 0,40 1,13 0,23 0,25 29,13

R7 0,28 0,67 1,58 0,71 2,08 6,35 51,31 2,72 2,48 4,03 1,92 0,80 2,20 0,41 0,47 21,99

R8 0,15 0,41 0,88 0,40 1,08 2,95 21,66 27,04 1,57 2,20 1,00 0,39 1,07 0,22 0,23 38,74

R9 0,20 0,59 1,15 0,47 1,28 2,70 18,55 1,61 41,54 3,99 1,74 0,58 1,65 0,32 0,32 23,30

R10 0,27 0,81 1,48 0,64 1,46 2,33 15,91 1,21 2,29 40,79 3,31 0,97 2,63 0,51 0,46 24,95

R11 0,18 0,52 1,00 0,42 0,86 1,58 9,35 0,73 1,31 4,44 56,02 1,46 3,21 0,40 0,44 18,08

R12 0,22 0,67 1,27 0,52 1,07 1,77 10,74 0,82 1,27 3,83 3,67 43,30 5,18 0,52 0,46 24,67

R13 0,24 0,74 1,43 0,56 1,13 1,98 11,28 0,89 1,28 3,62 2,80 1,79 44,92 0,64 0,52 26,17

R14 0,29 1,11 2,22 0,60 1,30 3,11 14,66 1,29 1,40 3,26 1,59 0,73 2,49 33,57 1,30 31,09

R15 0,20 0,63 1,07 0,40 0,72 1,01 6,27 0,43 0,65 1,71 1,08 0,51 1,54 0,97 53,39 29,39

Chile 0,7 1,6 2,8 1,1 2,8 7,1 31,1 3,0 3,3 6,6 3,2 1,4 3,6 0,6 1,0 30,0

24

Components of decomposition of regional output based on the sources of final demand (in %)

Department of Economics, University of Sao Paulo Source: calculations by the authors.

ORIGIN OF FINAL DEMAND

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 ROW

REG

ION

AL

OU

TPU

T

R1 52,98 3,39 4,29 0,90 1,17 1,23 7,29 0,58 0,78 1,72 1,02 0,47 1,34 0,30 0,40 22,14

R2 0,56 39,50 1,61 0,37 0,56 0,69 3,90 0,28 0,40 0,96 0,56 0,26 0,73 0,17 0,20 49,26

R3 0,37 0,96 14,14 0,50 1,33 1,79 11,17 0,60 1,07 2,44 1,46 0,67 1,74 0,22 0,20 61,33

R4 0,27 0,75 1,57 22,67 2,03 2,27 14,29 0,71 1,27 2,79 1,65 0,74 1,94 0,25 0,23 46,57

R5 0,18 0,48 1,17 0,56 40,23 1,89 9,53 0,66 0,78 1,52 0,78 0,34 0,96 0,19 0,23 40,51

R6 0,16 0,47 1,03 0,49 1,46 35,37 24,34 1,30 1,22 2,01 1,01 0,40 1,13 0,23 0,25 29,13

R7 0,28 0,67 1,58 0,71 2,08 6,35 51,31 2,72 2,48 4,03 1,92 0,80 2,20 0,41 0,47 21,99

R8 0,15 0,41 0,88 0,40 1,08 2,95 21,66 27,04 1,57 2,20 1,00 0,39 1,07 0,22 0,23 38,74

R9 0,20 0,59 1,15 0,47 1,28 2,70 18,55 1,61 41,54 3,99 1,74 0,58 1,65 0,32 0,32 23,30

R10 0,27 0,81 1,48 0,64 1,46 2,33 15,91 1,21 2,29 40,79 3,31 0,97 2,63 0,51 0,46 24,95

R11 0,18 0,52 1,00 0,42 0,86 1,58 9,35 0,73 1,31 4,44 56,02 1,46 3,21 0,40 0,44 18,08

R12 0,22 0,67 1,27 0,52 1,07 1,77 10,74 0,82 1,27 3,83 3,67 43,30 5,18 0,52 0,46 24,67

R13 0,24 0,74 1,43 0,56 1,13 1,98 11,28 0,89 1,28 3,62 2,80 1,79 44,92 0,64 0,52 26,17

R14 0,29 1,11 2,22 0,60 1,30 3,11 14,66 1,29 1,40 3,26 1,59 0,73 2,49 33,57 1,30 31,09

R15 0,20 0,63 1,07 0,40 0,72 1,01 6,27 0,43 0,65 1,71 1,08 0,51 1,54 0,97 53,39 29,39

Chile 0,7 1,6 2,8 1,1 2,8 7,1 31,1 3,0 3,3 6,6 3,2 1,4 3,6 0,6 1,0 30,0

Linkage analysis - Theoretical background

Hirschman–Rasmussen key sector identification indices

• Backward linkage index (power of dispersion): measure of the sector’s

importance as buyer of intermediate input.

𝑈𝑗 =𝐵.𝑗

𝐵∗

• Forward linkage index (sensitivity of dispersion): measure of the sector’s

importance as provider of intermediate input.

𝑈𝑖 =𝐵𝑖.

𝐵∗

where 𝐵∗ is the mean of all elements of matrix 𝐵, 𝐵.𝑗 is the column mean and

𝐵𝑖. is the row mean.

• Key sectors are the ones with both indices greater than 1.

Department of Economics, University of Sao Paulo 26

Linkage analysis - Theoretical background

Pure Linkage Approach

Measure the importance of the sectors in terms of production generation in

the economy.

Pure Total Linkage = PTL = PBL + PFL

• PBL – Pure Backward Linkage index: measure the pure impact of the

sector’s gross output in the economy, i.e., the impact that is free from

the demand inputs that the region makes from itself, and the feedbacks

from the rest of the economy to the region and vice-versa.

• PFL – Pure Forward Linkage index: measure the pure impact of the gross

output of the economy in the sector.

Department of Economics, University of Sao Paulo 27

Key sectors – (Inter + Intra)regional: HR and Pure linkage index

Source: calculations by the authors.

R3 – II – De Antofagasta

R7 – RMS

R15 – XII - De Magallanes y de la Antártica Chilena

Key sectors – Intraregional: HR and Pure linkage index

R3 – II – De Antofagasta

R7 – RMS

R15 – XII - De Magallanes y de la Antártica Chilena

Next Steps

• Disaggregation

• Sectors

• Products

Fipe - Fundação Instituto de Pesquisas Econômicas 30

[email protected]

www.usp.br/nereus

Department of Economics, University of Sao Paulo 31