Lecture 19: Tourism Infrastructure - USP › nereus › wp-content › uploads › Lecture_19_Tourism_Inf… · Lecture 19: Tourism Infrastructure . 2 Antecedents Methodology Baseline

Prof. Eduardo A. Haddad

Lecture 19: Tourism Infrastructure

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Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

3

The objective of this study was to assess the ex ante economic impacts of the PRODETUR-RJ

PRODETUR-RJ has the following specific goals and expected

outcomes:

Development of tourism in the hinterland

Increase in the average expenditure by tourists

Reduction in seasonality

Increase in the duration of stay

Improvement in the profile of tourism demand

Increase in the average expenditure by tourist

Diversification of tourism segments

4

The study by FIPE reaches the following objectives...

Assess the economic impacts of the investments related to

PRODETUR-RJ, considering that they represent an additional

structuring economic activity

Present the estimates of the direct, indirect, and induced

economic impacts on the activity level of the “sub-pólos”, the

rest of the State and the rest of the country, provided by the

whole set of activities associated with the phases of

implementation of the investments (2010-2013) and the

effects of changes in the matrix of expenditures by

tourists (2013-2020), which would not be observed in the

absence of the project

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... offering a better understanding about the future oportunities associated with the potential impacts of PRODETUR-RJ in the State and its regions

BENCHMARK (today) SCENARIO 2020

2007

2010

2013

2020

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Strategic information generated for the government enables stronger rationale for the investments

Use of strategic information is essential for the assessment of potential gainers and losers in a competitive market

Key information, analytical insights, subsidies for the planning process

of the Ministry of Tourism and the State Government of Rio de Janeiro “Window for the future”:

What will be the expected total level of activity, by sector and by

region? How can the State Government use this information to aggregate

value to its activities? Information on the level of sectoral supply and demand, spatially disaggregated, favors the estimation of potential returns Relevant subsidies for the analysis of specific investment projects Better understanding of the specific role played by different users in different geographical units

7

Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

8

The analytical framework used in this study is based on sound economic data and theory,…

Different models can be used to generate forecasts of economic

variables

Example: time series models – forecasts are simply

(statistical) extrapolations of past trends

It is also possible the create a “portrait” of the economy,

considering both the direct and indirect effects in value added and

employment creation

Example: Input-output models

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... with advantages that give visibility in the debate...

However, few models can generate forecasts considering:

Internal consistency among variables;

Structural relationships of the flows of income of the

economy;

The possibility of incorporation of structural changes, such as

world financial crisis, adoption of new technologies...

General equilibrium models consider that the economy is a system

of interdependent markets, in which the numerical values of the

equilibrium of all variables should be determined simultaneously

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... and technical legitimacy

Economic agents are “intelligent”, reacting to new situations:

Households maximize utility;

Firms maximize profits;

Structural changes over time with implications for the allocation of

economic activities in space;

Transaction costs in space (transportation costs)

Consistent scenarios in all levels of aggregation

Positive reviews in different areas: academia, public sector, private

sector, international organizations

Results are sectorally and regionally disaggregated

110 products

55 sectors

8 regions (7 within RJ)

Time horizon: 2010 a 2020

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Regionalization of the interregional module

Sub-pólo Microrregiões

Metropolitano Rio de Janeiro

Baía da Ilha Grande

Itaguaí

Bacia de São João

Lagos

Macaé

Macacu-Caceribu

Nova Friburgo

Serrana

Barra do Piraí

Vassouras

Agulhas Negras Vale do Paraíba Fluminense

Resto do RJ Demais microrregiões do Estado

Costa Verde

Costa do Sol

Serra Verde Imperial

Vale do Café

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Results are evaluated considering deviations (of a given variable) from the baseline

2007

GDP with PRODETUR RJ

GDP without PRODETUR RJ

Marginal flows

2010 2013 2020

Historical simulation Investiments Effects on tourism

13

The strategy for building the scenarios considers sequentially integrated stages

In “Stage 1”, forecasts for national and sectoral variables are produced

In “Stage 2”, sectoral forecasts for the State of Rio de Janeiro are

genrated

In “Stage 3”, the sectoral forecasts are disaggregated for the regions

within the State

In “Stage 4”, alternative (policy) scenarios are assessed based on

information on deviations from the baseline

National/ sectoral

projections

State disaggregation

Spatial disaggregation

Stage 1 Stage 2 Stage 3

14

Estimated input-output

matrix: 2007

Structural forecasts Scenarios of technological and

by experts preferences changes

Stage 1 Annual forecasts

w ith EFES

Econometric forecasts Macroeconomic forecasts:

DGE model (control)

Stage 2 Annual forecasts Matrix of State structural

w ith B-MARIA-RJ coefficients: 2007

Stage 3 Interregional module Interstate input-output

of spatial interaction module: 2007

Interregional input-output

module: 2007

Forecasts of endogenous Estimated input-output

variables: 2008-2020 matrices: 2008-2010-2015-2020

Forecasts of State

variables: 2008-2020

Forecasts of regional


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Stage 4

Estimated input-output Policy analysis:

matrix: 2007 Deviations from the baseline




w ith EFES


DGE model (control)






module: 2007



Forecasts of State




16

Stage 4

Estimated input-output Policy analysis:

matrix: 2007 Deviations from the baseline




w ith EFES


DGE model (control)






module: 2007



Forecasts of State




17

18

Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

19

Definition of the baseline

A baseline is needed as a reference for the magnitude of the impacts

The baseline was defined taking into account:

i. baseline for GDP and per capita GDP for the regions

ii. estimates (magnitude and forecasts) of the matrices of tourists

flows

iii. estimates for the (domestic and international) tourists expenditure

profiles as well as for indicators of average duration of stay

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(i) Baseline

The baseline characterizes a probable situation for the future of the

economies of Brazil and Rio de Janeiro, given the restrictions under which

they operate and the working hypotheses considered for some fundamental

structural aspects , such as investment rate, household consumption

patterns, sectoral productivity growth, etc.

This situation results from the assumptions made, the existing restrictions,

and from the relatively recent past experience of the economy. In summary,

the baseline should be understood as a likely future path of the Brazilian

economy (and its regions) as the current policies continue to have some

influence during the forecast period.

The goal is to provide a reference for the magnitude of the impacts

of PRODETUR-RJ in a time-consistent context

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(ii) Flows of tourists – magnitude

In order to assess the impacts of PRODETUR-RJ associated with the expected

increases in total expenditures by tourists (given by the intensification of the

flows of tourists, the increase in the average expenditures, or the increase in

the duration of stay), it is important to have an idea about the current flows

and the projected flows in the absence of the investments

This information, however, is only partially available in disperse sources

To obtain an estimate of the flows of tourists between origin-destination

pairs, in the context of our modeling strategy, we have consolidated different

pieces of information on flows of domestic and international tourists, with the

additional task of estimating a model of travel generation and demand in

order to calibrate the matrix of flows of tourists for the base-year of 2007,

from partial information

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(ii) Flows of tourists – magnitude

Sources of information:

a) domestic tourism: estimates of flows of travels to Rio de Janeiro, with

origin within and outside the State (FIPE/EMBRATUR)

b) international tourism: estimates of the number of foreign tourists in the

City of Rio de Janeiro (EMBRATUR)

c) origin of tourists in the main destinations in the “sub-pólos” (TurisRIO)

d) data on population and GDP for the municipalities in the State of Rio de

Janeiro (IBGE)

e) lodging data for the “sub-pólos”;

f) distance and travel time between the main cities in the seven regions of

the model (geo-processing)

Estimates of the flows of tourists between origin-destination pairs, 2007

Ano-base: 2007

Turistas (1000)

Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras Resto_RJ Total

Metropolitano 0,0 2218,7 3543,2 1502,7 248,2 1779,8 361,7 9654,3

Costa Verde 277,8 0,0 12,5 2,5 2,1 36,6 2,0 333,6

Costa do Sol 349,5 9,9 0,0 3,3 0,8 8,2 12,4 384,1

Serra 809,7 10,6 17,8 0,0 1,7 8,9 2,0 850,7

Vale do Café 66,0 4,5 2,2 0,8 0,0 6,9 0,5 81,0

Agulhas Negras 214,9 35,3 10,1 2,0 3,1 0,0 1,6 267,0

Resto_RJ 552,4 24,8 192,5 5,8 2,9 20,8 0,0 799,2

Resto do Brasil 4597,4 1044,5 2039,1 475,4 19,7 371,1 1,7 8548,9

Exterior 1558,0 233,0 330,7 41,2 3,0 1,1 5,0 2172,0

TOTAL 8425,8 3581,4 6148,2 2033,6 281,6 2233,4 387,1 23091,0

% Destino


Metropolitano 0,0 23,0 36,7 15,6 2,6 18,4 3,7 100,0

Costa Verde 83,3 0,0 3,8 0,7 0,6 11,0 0,6 100,0

Costa do Sol 91,0 2,6 0,0 0,8 0,2 2,1 3,2 100,0

Serra 95,2 1,3 2,1 0,0 0,2 1,0 0,2 100,0

Vale do Café 81,5 5,6 2,7 1,0 0,0 8,5 0,6 100,0

Agulhas Negras 80,5 13,2 3,8 0,7 1,2 0,0 0,6 100,0

Resto_RJ 69,1 3,1 24,1 0,7 0,4 2,6 0,0 100,0

Resto do Brasil 53,8 12,2 23,9 5,6 0,2 4,3 0,0 100,0

Exterior 71,7 10,7 15,2 1,9 0,1 0,1 0,2 100,0

TOTAL 36,5 15,5 26,6 8,8 1,2 9,7 1,7 100,0

% Origem


Metropolitano 0,0 62,0 57,6 73,9 88,2 79,7 93,4 41,8

Costa Verde 3,3 0,0 0,2 0,1 0,8 1,6 0,5 1,4

Costa do Sol 4,1 0,3 0,0 0,2 0,3 0,4 3,2 1,7

Serra 9,6 0,3 0,3 0,0 0,6 0,4 0,5 3,7

Vale do Café 0,8 0,1 0,0 0,0 0,0 0,3 0,1 0,4

Agulhas Negras 2,6 1,0 0,2 0,1 1,1 0,0 0,4 1,2

Resto_RJ 6,6 0,7 3,1 0,3 1,0 0,9 0,0 3,5

Resto do Brasil 54,6 29,2 33,2 23,4 7,0 16,6 0,4 37,0

Exterior 18,5 6,5 5,4 2,0 1,1 0,1 1,3 9,4

TOTAL 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0

Ori

gem

Destino

Ori

gem

Destino

Ori

gem

Destino

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(ii) Flows of tourists – forecasts

The 2007 matrix was projected until 2020

The expansion factor used was the relationship between the projected

annual growth rate of per capita GDP in the origin region, and the elasticity

of demand for tourism with respect to per capita GDP in the origin region

(1.5)

Additional information on expected tourists directly associated with the

major sport events that will take place in Rio de Janeiro (World Military

Games, Confederation Cup, FIFA World Cup, and Olympic Games) was added

to the baseline

Forecasts of the flows of tourists between origin-destination pairs, 2010-2020

2010

Turistas (1000)


Metropolitano 0,0 2363,4 3774,2 1600,7 264,4 1895,8 385,3 10283,8

Costa Verde 275,3 0,0 12,4 2,4 2,1 36,1 2,0 330,4

Costa do Sol 364,7 10,3 0,0 3,4 0,9 8,5 12,9 400,7

Serra 872,2 11,4 19,1 0,0 1,8 9,6 2,2 916,2

Vale do Café 73,8 5,1 2,5 0,9 0,0 7,7 0,6 90,5

Agulhas Negras 207,1 33,8 9,6 1,9 3,0 0,0 1,6 257,0

Resto_RJ 567,0 25,4 196,8 5,9 3,0 21,3 0,0 819,4

Resto do Brasil 5007,4 1122,9 2192,1 511,1 21,2 399,0 1,8 9255,4

Exterior 1640,7 237,9 337,7 42,1 3,1 1,1 5,1 2267,6

TOTAL 9008,2 3810,1 6544,4 2168,4 299,4 2379,1 411,5 24621,0

Destino

Ori

gem

2020

Turistas (1000)


Metropolitano 0,0 4394,0 7016,9 2975,9 491,6 3524,6 716,3 19119,4

Costa Verde 322,5 0,0 14,5 2,9 2,5 42,2 2,3 386,9

Costa do Sol 469,6 13,2 0,0 4,4 1,1 11,0 16,6 515,9

Serra 1306,3 17,1 28,6 0,0 2,7 14,3 3,3 1372,3

Vale do Café 101,9 7,0 3,4 1,3 0,0 10,6 0,8 125,0

Agulhas Negras 269,7 44,0 12,6 2,5 3,9 0,0 2,1 334,7

Resto_RJ 746,9 33,4 259,1 7,8 3,9 28,1 0,0 1079,2

Resto do Brasil 7976,3 1791,5 3497,4 815,4 33,8 636,6 2,9 14753,7

Exterior 2474,2 359,5 510,4 63,6 4,6 1,7 7,7 3421,8

TOTAL 13667,4 6659,7 11342,9 3873,7 544,0 4269,1 752,1 41108,8

Destino

Ori

gem

(...)

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(iii) Profile of expenditures by tourists

Information needed for parameterization of the model

Domestic tourism

Micro data from “Caracterização e dimensionamento do turismo

doméstico no Brasil – 2007” (FIPE-EMBRATUR)

Estimates of average per capita expenditures by tourist/day

(composition by destination)

International tourism

2007 Pan-American Games that took place in Rio de Janeiro

F1GP, annually held in São Paulo

“Perfil do Turista Internacional que Visita o Rio”, by Prefeitura da

Cidade do Rio de Janeiro

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Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

28

Basic hypotheses

The assessment of the impacts of the investments considers two

different phases:

the first one related to the construction phase of the

planned investments (2010-2013);

the second one related to the effects on tourism (2013-

2020)

We have considered different sets of hypotheses for the

parameters of tourism, as well as for the sources of financing the

additional expenditures by tourists

We designed three scenarios associated with the direct effects of

PRODETUR-RJ on the profile of tourists in the “sub-pólos”. The

scenarios were built so that the expected effects in Scenario 1 tend

to be gradually magnified in the subsequent scenarios

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Regionalization of the investments of PRODETUR-RJ (USD millions)

The information related to the construction phase was regionalized

according to further information provided by SEOBRAS-RJ

BID GERJ BID GERJ BID GERJ BID GERJ BID GERJ

Metropolitano 4.060 32.000 12.190 0 0 0 510 0 16.804 32.000

Costa Verde 5.702 5.000 10.150 2.500 8.961 0 510 0 24.956 7.500

Costa do Sol 998 0 6.641 0 6.539 0 510 0 15.454 0

Serra Verde Imperial 3.661 0 15.722 2.500 3.633 0 510 0 24.644 2.500

Vale do Café 533 0 4.541 400 2.470 0 510 0 8.334 400

Agulhas Negras 9.319 23.200 13.819 9.400 0 0 510 0 21.808 32.600

Total 24.273 60.200 63.063 14.800 21.603 0 3.060 0 112.000 75.000

2010 2011 2012 2013 Total

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Scenario 1 (more conservative)

It is assumed a gradual increase in the flow of tourists to the “sub-

pólos” Costa Verde and Costa do Sol, from 2013 on, reaching 10%

in 2020 – for the “sub-pólos” of Pólo Serra, the increase would

reach 5% in 2020

For the “sub-pólo” Metropolitano, it is assumed an increase of 10%

in the tourists expenditures on tourist attractions and an average

stay of 10 days (departing from 9,79 in the benchmark), in which a

gradual increase is assumed from 2013

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Scenario 2 (intermediate)

The hypothesis of a gradual increase in the average stay in the

other “sub-pólos”, from 2013, is added to the set of hypotheses of

Scenario 1: Costa Verde (from 6,45 days in 2013 to 7,00 days in

2020); Costa do Sol (from 6,68 to 7,00); “sub-pólos” of Pólo Serra

(from 3,40 to 3,60)

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Scenario 3 (optimistic)

This scenario departs from Scenario 2, considering stronger

increases in the flows of tourists to the “sub-pólos” Costa Verde

and Costa do Sol (12% in 2020), and to the “sub-pólos” of Pólo

Serra (6% in 2020)

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Assumptions on financing – government

Government expenditure

For the expenditures in the construction phase, we assume

the investments from IDB will have no impact in the State

government accounts during the forecast period, while the

counterpart will be financed with a reduction (increase) in the fiscal

surplus (deficit)

For the expenditures on maintenance/operation, it is assumed that

the sources of financing are traditional fiscal sources, and, thus, do

not represent any benefit for the State

34

Assumptions on financing – tourists

Expenditures by tourists

In the case of the additional expenditures by tourists, two

alternative financing hypotheses are considered:

Closure “A”: additional expenditures by tourists are financed by

equivalent reductions in consumption in the respective origin

regions, representing an induced substitution effect in the

consumption basket of travelers

Closure “B”: additional expenditures by tourists are financed by

reduction in personal savings, maximizing the multiplier effects of

expenditures

35

Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

36

Presentation of results

Results on the economic impacts

Gross output, GDP (value added), wage income,

employment, indirect tax revenue (ICMS)

Effects by “sub-pólos”

National and state impacts

The presentation of the results and the ex ante analysis of

PRODETUR-RJ considers:

i. the direct effects derived from the set of hypotheses for

the parameters of tourism in the State on the structure of

additional expenditures by tourists

ii. the systemic effects on the flows of selected variables,

followed by an analysis of the sectoral and regional State

impacts, using a set of summary indicators

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(i) Additional expenditures by tourists

Additional expenditures by tourists in the State of Rio de Janeiro (in USD thousands)

0

50.000

100.000

150.000

200.000

250.000

300.000

350.000

2013 2014 2015 2016 2017 2018 2019 2020

USD

1.0

00

Cenário 1 Cenário 2 Cenário 3

38

The composition of the expenditures, by origin, changes over time, showing an increase in the share of expenditures by foreigners

Structure of additional expenditures by tourists in the State of Rio de

Janeiro: Scenarios 1, 2 and 3 (in % of total)

Scenario 1

Scenario 2

Scenario 3

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020

Cenário 3 Internacional Cenário 3 Doméstico

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020


39

Regionalization of the additional expenditures by tourists in the State of Rio de Janeiro

The hypotheses for the “sub-pólo” Metropolitano, which are the

same in the three scenarios, are dominant in Scenario 1

as we include more favorable hypotheses for the effects on

the duration of stay in the other “sub-pólos” (Scenario 2) and,

additionally, more intense flows of tourists with destination to

those regions (Scenario 3), the effects on the

expenditures become more decentralized from the “sub-

pólo” Metropolitano;

in this context, Pólo Litoral becomes the touristic region

more impacted by the investments of PRODETUR-RJ;

the potential increases in the expenditures by tourists in

Pólo Serra tend to concentrate over time in the “sub-pólo”

Serra Verde Imperial

Regionalization of the additional expenditures by tourists in the State of Rio de Janeiro

In relative terms, however, the ranking of shares by “sub-pólos” in the increases in the expenditures by tourists change in the three scenarios, suggesting an increasing share of the hinterland

Scenario 1 Scenario 2 Scenario 3

40

0

20.000

40.000

60.000

80.000

100.000

120.000

2013 2014 2015 2016 2017 2018 2019 2020

USD

1.0

00

Cenário 3

Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras

0

20.000

40.000

60.000

80.000

100.000

120.000

2013 2014 2015 2016 2017 2018 2019 2020

USD

1.0

00

Cenário 2


0

20.000

40.000

60.000

80.000

100.000

120.000

2013 2014 2015 2016 2017 2018 2019 2020

USD

1.0

00

Cenário 1


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020

Cenário 1


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020

Cenário 2


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018 2019 2020

Cenário 3


41

(ii) Marginal economic flows

Results for the State of Rio de Janeiro consider the estimates

for the three scenarios (1, 2, and 3) under the alternative

financing hypotheses contemplated in the two closures (A and

B); we have, thus, six alternative scenarios

Definition: marginal economic flows are the annual differences

in the economic variables, in relation to the baseline, due to

the changes associated with PRODETUR-RJ, both in the

construction phase and operation phase

As in the model we work with annual flows, we can interpret

the differences that result from the adjustments to the shocks,

in the various scenarios, as changes in the flow of income of

the economy representing deviations from a control path

(given by the baseline)

42

Schematic definition of the marginal effects of PRODETUR-RJ

Again...

2007

GDP with PRODETUR RJ

GDP without PRODETUR RJ

Marginal flows

2010 2013 2020

Historical simulation Investiments Effects on tourism

43

Results

The analysis of the GDP of the six regions in Rio de Janeiro suggests that the

future impacts would have non-negligible spatial focus, with bigger

effects in Pólo Litoral than in Pólo Serra (in 2020)

Scenarios (Family A) Scenarios (Family B)

Effects on “sub-pólo” Metropolitano are less intense, as the region is the main origin of tourists to the other “sub-pólos” in the hinterland/coast

As tourist expenditures are financed by reduction in personal savings, the effects tend to be bigger

The rest of the State tends to be negatively affected, via substitution effect (residents spend in the touristic regions reducing consumption at home)

The rest of RJ would benefit by leakages from other regions

44

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Metropolitano 29.755 24.154 5.867 5.320 16.885 28.893 48.524 58.786 74.914 92.155 110.386

Costa Verde 4.446 4.816 2.972 10.793 11.254 11.971 12.773 13.417 14.204 15.020 15.873

Costa do Sol 8.235 10.173 5.045 23.485 24.302 25.770 27.401 28.717 30.310 31.956 33.664

Serra Verde Imperial 1.899 4.766 996 2.131 2.066 2.135 2.297 2.285 2.354 2.417 2.503

Vale do Café 965 1.219 357 370 322 348 390 408 441 475 513

Agulhas Negras 22.302 18.141 2.457 2.995 2.528 2.683 2.875 2.993 3.163 3.339 3.530

Resto do RJ 2.003 2.009 638 81 -52 -114 -132 -233 -301 -374 -438

Resto do Brasil 75.748 68.672 18.818 -14.887 -21.240 -25.375 -29.583 -34.760 -40.074 -45.746 -51.716

Brasil 145.354 133.950 37.152 30.288 36.066 46.310 64.545 71.613 85.011 99.242 114.317

Metropolitano 15.782 12.456 2.943 937 6.818 12.913 22.951 28.159 36.382 45.176 54.479

Costa Verde 2.328 2.571 1.641 5.439 5.661 6.018 6.417 6.736 7.128 7.534 7.959

Costa do Sol 3.598 4.806 2.588 11.829 12.232 12.957 13.760 14.409 15.194 16.004 16.846

Serra Verde Imperial 989 2.627 545 1.020 935 921 939 884 857 822 796

Vale do Café 489 641 193 186 157 170 190 198 214 230 248

Agulhas Negras 11.139 8.938 1.039 1.508 1.285 1.359 1.449 1.505 1.585 1.667 1.757

Resto do RJ 976 984 307 -37 -125 -180 -221 -293 -357 -424 -488

Resto do Brasil 28.078 25.442 6.972 -7.700 -10.923 -13.340 -16.132 -18.954 -22.096 -25.449 -28.990

Brasil 63.379 58.465 16.229 13.182 16.041 20.819 29.354 32.645 38.906 45.559 52.608

Metropolitano 5.991 4.782 1.147 1.243 3.838 6.515 10.869 13.165 16.756 20.595 24.652

Costa Verde 967 1.052 653 2.467 2.580 2.750 2.942 3.095 3.282 3.477 3.680

Costa do Sol 1.545 1.991 1.041 5.280 5.478 5.812 6.176 6.479 6.840 7.214 7.601

Serra Verde Imperial 394 1.022 212 458 444 458 489 488 502 515 532

Vale do Café 211 271 81 77 65 71 79 82 88 95 102

Agulhas Negras 4.501 3.608 419 662 574 608 648 673 709 746 786

Resto do RJ 385 394 129 -1 -35 -55 -69 -96 -118 -143 -165

Resto do Brasil 11.598 10.499 2.873 -2.862 -4.062 -4.926 -5.898 -6.920 -8.039 -9.232 -10.491

Brasil 25.591 23.619 6.555 7.323 8.882 11.231 15.235 16.966 20.021 23.266 26.696

Metropolitano 1.021 761 169 613 1.549 2.484 3.982 4.791 6.038 7.371 8.777

Costa Verde 183 204 132 953 1.003 1.067 1.138 1.196 1.266 1.338 1.413

Costa do Sol 169 278 179 2.035 2.137 2.268 2.409 2.528 2.670 2.815 2.966

Serra Verde Imperial 76 206 42 178 182 192 206 212 223 234 246

Vale do Café 31 46 15 27 26 28 31 33 36 38 41

Agulhas Negras 848 671 65 229 220 233 249 260 275 290 306

Resto do RJ 70 73 24 -3 -10 -13 -16 -21 -25 -29 -33

Resto do Brasil 1.840 1.667 457 -422 -586 -701 -807 -959 -1.107 -1.265 -1.432

Brasil 4.237 3.905 1.083 3.610 4.521 5.559 7.192 8.040 9.375 10.792 12.286

Metropolitano 289 242 61 199 417 638 990 1.181 1.475 1.788 2.119

Costa Verde 43 46 27 215 227 242 258 271 288 304 322

Costa do Sol 85 101 48 461 484 514 548 576 609 644 679

Serra Verde Imperial 20 45 10 47 49 53 58 61 65 69 73

Vale do Café 9 11 3 7 7 8 9 9 10 11 12

Agulhas Negras 220 180 26 55 53 56 61 64 68 72 77

Resto do RJ 27 27 9 7 6 7 8 9 10 11 12

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Scenario 1A

Dim

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Regional distribution of marginal flows of GDP in 2020

45

Scenario 1A Scenario 2A Scenario 3A

Scenario 1B Scenario 2B Scenario 3B

46

Summary indicators for the State of Rio de Janeiro

Definition: marginal productivity of the investments is the

relationship between the present value (PV) of the marginal flows of

GDP of Rio de Janeiro and the PV of the investments (both in 2010,

considering a discount rate of 12%)

Definition: marginal output of the investments is the relationship

between the present value (PV) of the marginal flows of gross output of

Rio de Janeiro and the PV of the investments (both in 2010, considering

a discount rate of 12%)

the difference between the two indicators refers to the variable

being considered: in the definition of gross output, it is also

included intermediate consumption (in addition to value added)

the analysis is done taking into account two sub-periods 2010-

2015 and 2010-2020, in order to obtain a perspective of the

maturation of the Program

Marginal productivity of the investments

Results show that the marginal

productivity of the investments of

the PRODETUR-RJ is magnified in

the long run

As the project maturates,

productivity gains are bigger, as

there is a potential

complementarity between the

investments of the Program and

the attraction of increasing

expenditures by tourists in the

regions

Marginal Productivity of the

Investments

2010-2015

2010-2020

Discount rate = 12% a.a.

PV of investments = USD 173.394 thousands

47

A B

Cenário 1 0,713 0,882

Cenário 2 0,842 1,134

Cenário 3 0,875 1,196

A B

Cenário 1 1,421 1,883

Cenário 2 2,066 3,159

Cenário 3 2,143 3,305

Marginal output of the investments

In dynamic models, the concept

of marginal indicators of the

investments, in a given point in

time, mixes with the concept of

static mulitpliers

Thus, the results in this slide may

be interpreted as output

multipliers

It means that the private sector

would inject, additionally,

between USD 355 and 1.047

millions in the productive chain

associated with tourism in Rio de

Janeiro in the next 10 years

Marginal Output of the Investments

2010-2015

2010-2020

Discount rate = 12% a.a.

PV of investments = USD 173.394 thousands

48

A B

Cenário 1 1,452 1,750

Cenário 2 1,749 2,261

Cenário 3 1,823 2,386

A B

Cenário 1 2,906 3,722

Cenário 2 4,387 6,306

Cenário 3 4,561 6,603

49

Regional indicators (1)

Regional effects depend upon the hypotheses used for the sources

of financing additional expenditures by tourists (scenarios “A”

versus “B”)

The effects of the scenarios considered in the study tend to be

concentrated in Pólo Litoral, with non-negligible effects on Pólo

Serra

It is noteworthy the polarization role played by RMRJ, which

acts in the direction of internalizing part of the multiplier effects

(mainly in family “B”); thus, the set of de-concentrating

hypotheses used for Scenarios 2 and 3 are less strongly perceived

50

Regional indicators (2)

The relationship between the regional shares in total effects and

the respective regional shares in the investments of PRODETUR-RJ

allows us to assess the degree of relative absorption of the benefits

of the Program

“Sub-pólo” Costa do Sol, in all scenarios, shows a greater relative

capacity of internalizing the socioeconomic effects of the

Program

Finally, the prospects of PRODETUR-RJ tend to be more relevant, in

terms of relative magnitudes, to the economies of Costa Verde and

Costa do Sol

51

Effects on tourism activities (ACT)

There seems to be a re-location effect associated with movements away

from activities that are not directly related to tourism towards tourism

activities (family “A”)

As we eliminate the substitution effect (family “B”), results point to a share

of ACTs – in all variables in all regions – above 50% of the total effects

The dominant role of ACTs in the total effects also suggests the existence of

a core of activities within the productive chain of tourism in the regions, in

which potential clusters are revealed

In scenarios “B”, it is noteworthy that ACTs tend to internalize a smaller

share of regional value added, and, to a certain extent, of wage income. On

the other hand, the share of labor absorption is relatively bigger

ACTs are, in relative terms, activities of lower value added for the

regions, with a higher potential for employment generation with

lower wages

52

Synthesis– Internal Rate of Return

To summarize the GDP effects, we calculated the internal rates of return

(IRR) for the six scenarios (as GDP considers the value added in the

economy, it represents a better measure to assess the economic effects of

PRODETUR-RJ; moreover, it enables comparisons with other experiences):

in the cash flow, in addition to the planned investments in the period

2010-2013, we consider the annual costs of operation and

maintenance in the subsequent years (USD 12.330 thousands)

benefits refer to the marginal flows of GDP in the State economy

results reveal high IRRs, from 17,2% (Scenario 1A) to 45,0%

(Scenario 3B)

53

Synthesis– Internal Rate of Return

National and international experiences with studies that attempted to

estimate profitability of investment projects in tourism, including change and

maintenance of infrastructure, suggest that an IRR of 17,6% is more

realistic, corresponding to Scenario 1A

The study region has already consolidated tourism activities. This implies

that the set of assumptions on incremental flows of tourists – raised by the

State government and the IDB to design the scenarios – is more likely to be

the one associated with Scenario 1

Even considering the more conservative set of hypotheses (Scenario 1A),

the effects of PRODETUR-RJ would be relevant for the economy of

Rio de Janeiro in terms of income and employment generation,

promoting tourism outside the Metropolitan area with non-negligible

multiplier effects

54

Antecedents

Methodology

Baseline

Scenarios

Results

Ex post evaluation

Outline

55

Complexity in isolating the effects of the Program in a dynamic context...

Case 1: “Known” direct effects

If one can observe changes in tourism activity in the region and identify the

role played by the Program, such analytical tool can be used for the ex post

analysis. Information needed:

What is the increase in the flows of tourists that is associated with the

Program?

What change in the duration of stay is associated with the Program?

What change in the profile of expenditures by tourists is associated

with the Program?

...

However, it is very hard to isolate such effects in a dynamic context...

General or specific change?

Other policies to promote tourism in the region?

...

56

... requires monitoring based on indicators “suggested by the model”

Case 2: Impossibility of identifying the direct effects

“Dirty” monitoring, indicative...

Use control group

Model results Monitoring

Existence of a core of activities within the productive chain of tourism in the regions

Identify and monitor activities in the relevant clusters (employment, income...)

Increase in regional dynamism Local indicators vis-à-vis rest of regional/national economies

... ...

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