Prof. Eduardo A. Haddad
Lecture 19: Tourism Infrastructure
2
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
5
... 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
6
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
9
... 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
10
... 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
11
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
12
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
variables: 2008-2020
15
Stage 4
Estimated input-output Policy analysis:
matrix: 2007 Deviations from the baseline
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
variables: 2008-2020
16
Stage 4
Estimated input-output Policy analysis:
matrix: 2007 Deviations from the baseline
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
variables: 2008-2020
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
20
(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
21
(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
22
(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 Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras Resto_RJ Total
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 Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras Resto_RJ Total
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
24
(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 Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras Resto_RJ Total
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 Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras Resto_RJ Total
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
(...)
26
(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
27
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
29
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
30
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
31
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)
32
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)
33
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
37
(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
Cenário 2 Internacional Cenário 2 Doméstico
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2013 2014 2015 2016 2017 2018 2019 2020
Cenário 1 Internacional Cenário 1 Doméstico
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
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 1
Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2013 2014 2015 2016 2017 2018 2019 2020
Cenário 1
Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2013 2014 2015 2016 2017 2018 2019 2020
Cenário 2
Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2013 2014 2015 2016 2017 2018 2019 2020
Cenário 3
Metropolitano Costa Verde Costa do Sol Serra Vale do Café Agulhas Negras
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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AIC
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tho
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Scenario 1A
Dim
en
sio
ns
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
... ...