Yon kad pou evalyasyon ex-ante enpak ekonomik envestisman nan touris: Yon aplikasyon pou Ayiti

A Framework for Ex-Ante Economic Impact Assessment of Tourism Investments An Application to Haiti Onil Banerjee Martin Cicowiez Sebastien Gachot IDB WORKING PAPER SERIES Nº 616 August 2015 Environment, Rural Development and Disaster Risk Management Division Inter-American Development Bank August 2015 A Framework for Ex-Ante Economic Impact Assessment of Tourism Investments An Application to Haiti Onil Banerjee Martin Cicowiez Sebastien Gachot Cataloging-in-Publication data provided by the Inter-American Development Bank Felipe Herrera Library Banerjee, Onil A framework for ex-ante economic impact assessment of tourism investments: an application to Haiti / Onil Banerjee, Martin Cicowiez, Sébastien Gachot. p. cm. — (IDB Working Paper Series ; 616) Includes bibliographic references. 1. Computable general equilibrium models—Haiti. 2. Tourism—Economic aspects— Haiti. 3. Investments, Foreign—Haiti. 4. Economic impact analysis—Haiti. I. Cicowiez, Martín. II. Gachot, Sébastien. III. 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The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent. http://www.iadb.org 2015 Abstract This study develops a linked regional computable general equilibrium and micro-simulation (RCGE-MS) model to assess the regional economy-wide and poverty impacts of a US$36 million investment in tourism in the south of Haiti. The first social accounting matrix for Haiti with a base year of 2012/2013 was constructed to calibrate the model. This research addresses three key gaps identified in the tourism impact assessment literature. First, a destination-specific tourism demand and value chain analysis was used to calibrate the shocks implemented in the model. Second, the RCGE-MS approach moves beyond the representative household configuration to enable more robust analysis of tourism investment impacts on poverty and income inequality. Third, results of this modelling were used to inform a social cost-benefit analysis to provide greater transparency in the evaluation of trade-offs between investment alternatives. Results of this analysis showed a positive impact on sectoral activity, especially for the hotel and restaurant sector (182.1% in 2040) and a 2.0% increase in Gross Regional Product by 2040. The South’s exports fell 4.7% below baseline and imports were 6.1% higher due to the inflow of foreign exchange, the appreciation of the regional real exchange rate, increased demand for most goods and services, and limited regional productive capacity. The rate of unemployment fell from 26% to 23%. The investment helped lift some of the region’s poorest out of poverty, reducing the poverty headcount by 1.6 percentage points. Driving this result was an increase in employment, wages and non-labor income. The linked RCGE-MS approach proves to be a powerful tool for assessing how tourism investments affect regional economic activity and revealing the mechanisms through which tourism can contribute to increased employment opportunities and poverty reduction. Keywords: Computable General Equilibrium, CGE, Tourism Investment, Regional Welfare, Poverty, International Investment, Benefit Cost. JEL Code: C680, D610, R130, O120, O150, F210. 1 Acknowledgments The authors wish to thank the HA-L1095 Team, with special thanks to Michele Lemay, Mercedes Velasco, Bruno Jacquet. Thanks also to Guy Frantz Boucicaut of the Haitian Institute of Statistics and Informatics for assisting with data. Thanks to Carlos Ludena of the IDB and Calvin Djiofack of the World Bank for directing us to critical sources of data. Thanks to Maria Retana of the IDB for the translation of the Model Manual. 2 Table of contents 1. Introduction and Context ............................................................................................................ 3 1.1. The Haitian Context and the IDB’s Sustainable Coastal Development Program 3 1.2. Tourism as a Driver of Economic Growth and Development .............................. 4 2. Methods and Data ....................................................................................................................... 5 2.1. A Regional Computable General Equilibrium Model .......................................... 5 2.2. RCGE Model Dataset ......................................................................................... 10 2.3. Microsimulation Model ...................................................................................... 16 2.4. Microsimulation Model Dataset ......................................................................... 17 3. Simulations ............................................................................................................................... 17 3.1. Scenarios ............................................................................................................. 17 3.2. Results ................................................................................................................ 20 3.2.1. Aggregate Results ....................................................................................................... 20 3.2.2. Sectoral Results ........................................................................................................... 23 3.2.3. Distributive Results ..................................................................................................... 25 3.2.4. Cost-Benefit Analysis ................................................................................................. 26 4. Discussion and Policy Implications .......................................................................................... 27 APPENDIX A: MATHEMATICAL STATEMENT OF RCGE MODEL... ................................ 30 A.1. Introduction ....................................................................................................... 30 A.2. Equations and Variables .................................................................................... 30 APPENDIX B: TECHNICAL NOTE ON THE CONSTRUCTION OF T HE RSAM FOR HAITI’S SOUTH DEPARTMENT .............................................................................................. 45 B.1. Introduction ........................................................................................................ 45 B.2. A Regional Social Accounting Matrix ............................................................... 45 B.3. Data .................................................................................................................... 47 B.4. Steps in Building the RSAM ............................................................................. 48 B.5. Macro SAM ....................................................................................................... 48 B.6. (National) SAM ................................................................................................. 49 B.7. Regional SAM for the South Department .......................................................... 51 APPENDIX C: THE MICROSIMULATION MODEL ............................................................... 53 APPENDIX D: SENSITIVITY ANALYSIS................................................................................ 56 APPENDIX E. REGIONAL/NATIONAL CGE MODEL MANUAL .... .................................... 59 E.1. GAMS Code Organization ................................................................................. 60 E.2. Steps to Implement the Model ........................................................................... 62 E.3. The Data File ...................................................................................................... 63 E.4. The Simulations File .......................................................................................... 77 References ..................................................................................................................................... 86 3 1. Introduction and Context 1.1. The Haitian Context and the IDB’s Sustainable Coastal Development Program Haiti is the poorest country in the Western Hemisphere and one of the poorest in the world. In 2012, Gross National Income per capita was US$760. Of Haiti’s population of 10.2 million, over half live on less than US$1 per day and 80% live on less than US$2 per day. Haiti is also extremely unequal; based on 2012 household survey data, Haiti has a Gini coefficient of 0.61, which has been constant since 2001 (World Bank 2014). International donors have re-doubled efforts to stimulate economic growth and development in Haiti following the devastating impact of the 2010 earthquake. Investment in basic public services and in key productive sectors such as agriculture and manufacturing is needed, all within a context of regulatory reform. Recently, attention has been focused on catalyzing the re- birth of tourism. Haiti was once a well-known tourist destination considered the “pearl of the Antilles” and was one of the most frequented islands in the Caribbean from the 1950s to the 1980s. Thirty years of dictatorship rule and two decades of political and institutional crises, however, have all but erased Haiti from the tourist map for even the more adventure-minded global travelers (Trevelyan 2013). Despite these challenges, tourism demand has been growing in recent years. Since 2007, Haiti received the highest volume of tourists during the first quarter of 2013 and between 2007 and 2011, international tourist volumes increased on average by 4.9% per year. In 2013, tourism contributed US$355.4 million (4.2% of Gross Domestic Product) and 139,000 jobs (3.6% of total employment) considering direct and indirect linkages (WTTC 2014). The current government led by President Michel Martelly is the first to actively support tourism as a driver of growth. Based on Haiti’s Tourism Master Plan, the South Coast, extending from Port a Piment to Jacmel, is a priority region for development (figure 1). The government’s vision calls for the development and consolidation of complementary new and improved tourism options. The IDB’s support has been confirmed in contributing to this initiative through the US$36 million investment in the Sustainable Coastal Tourism Program (HA-L1095). The Program’s main lines of action include development of the tourism product through the enhancement of public tourist attractions; inclusion of local populations into the tourism value 4 chain; basic infrastructure and services to attend to local and tourist needs, and; institutional strengthening and capacity building for enhanced management and development of the sector. Figure 1. Haiti’s South Department and Program primary Zones of Influence. Source: Google Maps, 2014. To assist in the design of the Program, the IDB has commissioned a number of studies. A tourism demand study was undertaken to project the future tourism demand with and without Program (Banerjee, Velasco, and Torres 2014). To provide opportunities for inclusive growth, a pro-poor value chain analysis was conducted focusing on the investment program area of intervention (Armitt, Ashley, and Goodwin 2014). The value chain analysis mapped the tourism value chain to identify nodes of opportunity for increasing linkages between the tourism sector and local populations and production processes, and increasing the share of tourism expenditure that reaches low income people (Armitt, Ashley, and Goodwin 2014, Ashley, Mitchell, and Spenceley 2009, Humphrey 2005, Humphrey and Schmitz 2000, Mitchell and Ashley 2009). This paper uses the results of the tourism demand and value chain analyses to inform the economy-wide evaluation of the tourism investment and calibrate the shocks to be implemented in the model developed herein. 1.2. Tourism as a Driver of Economic Growth and Development The standard view of tourism investment is that it is a driver of economic growth and development with significant potential for poverty alleviation. In developing country contexts, 5 tourism can provide a major source of new off-farm income in rural areas and help bridge inequalities between overpopulated urban areas, such as Port-au-Prince, and rural areas such as the South Coast. An increase in tourism demand can generate increased output from tourism- related sectors through direct, indirect and induced impacts where links between the tourism sector and other economic sectors exist. Where these linkages are strong, the well-publicized and often misused, multiplier effects of tourism investment arise (Gretton 2013, Vanhove 2005). Direct impacts include: employment generation, skill creation, higher wages, and new or improved access to basic services and infrastructure. Indirect channels include price and demand effects for land and local products including agriculture and food/beverage processing (Klytchnikova and Dorosh 2012). Expansion of the tourism sector may, however, come at the expense of output from other sectors through crowding out effects, depending on factor supply constraints of labor, capital and land (Banerjee et al. 2015, Buiter 1976). Crowding out implies higher input prices, and reduced competitiveness in traditional export and import-competing markets through exchange rate appreciation. Higher prices can erode the price-competitiveness of ‘up and coming’ or emerging destinations. Furthermore, where public resources are used to finance tourism investment, private consumption growth tends to slow thereby constraining the potential positive income and employment impacts of tourism-based growth. Thus, to assess the net welfare impact of tourism investment, country-context is critical, especially consideration of factor supply constraints, domestic productive capacity to service the tourism sector, and the macroeconomic and fiscal policy environment (Dwyer, Forsyth, and Spurr 2003, Dwyer et al. 2000, Dwyer, Forsyth, and Spurr 2004). 2. Methods and Data 2.1. A Regional Computable General Equilibrium Model In this study, we develop a single small open Regional recursive dynamic Computable General Equilibrium (RCGE) model to evaluate the economic impact of the IDB’s Sustainable Coastal Tourism Program. The model integrates a relatively standard recursive dynamic computable general equilibrium model with additional equations and variables that single out: (a) the trade relations between the regional economy and the rest of the country, (b) the domestic and foreign 6 tourism demand, and (c) the impact of public capital investment in infrastructure on sectoral productivity. Thus, compared to other CGE models, our RCGE offers a combination of policy- relevant features for the study of tourism investment (or policy) counterfactual scenarios in a regional economy. In Appendix A, the variables and equations of our RCGE model are presented. 1 Figure 2 depicts the circular flow of income within the economy and between the economy and the rest of the country and world. Activities are industries that both demand (as intermediate inputs) and supply goods and services. Goods and services are consumed by households and governments, and supplied to export markets and foreign tourists. Activities also demand factors of production (labor, capital, land, natural resources) for their productive processes and make payments to these factors. These payments are transferred to households in the form of wages and rents. Households may also receive income from transfers from the government and transfers from the rest of the country or world (migrant labor, remittances, government subsidies, gifts, etc.). Households pay taxes, consume and save (invest in the capital account). 1 As an alternative, we could have implemented the local economy-wide impact evaluation (LEWIE) approach proposed by Taylor and others (Taylor and Filipski 2014). However, insufficient data were available at the time; collection of these data would require highly targeted household and business surveys. In addition, we are interested in economy-wide effects at the regional level, beyond what a LEWIE may tell us. Nonetheless, the development of a baseline and ex-post LEWIE is proposed as a component of the IDB’s Monitoring and Ex-Post Impact Evaluation Plan (Banerjee et al. 2014). 7 Figure 2: Flow of payments in the RCGE Source: Authors’ own elaboration. The RCGE model mathematically describes the optimizing behavior of agents in their economic environment; it is a system of equations describing the utility maximizing behavior of consumers, profit maximizing behavior of producers, and the equilibrium conditions and constraints imposed by the macroeconomic environment. Agent behavior is represented by linear and non-linear first order optimality conditions and the economic environment is described as a series of equilibrium constraints for factors, commodities, savings and investment, the government, and rest of the world accounts (Lofgren et al. 2002). The model may be broken into a series of blocks, namely: production, factor markets, institutions, commodity markets, and macroeconomic balances. These model blocks are discussed in turn. Production The model’s structure enables a given activity to produce more than one commodity, while any one commodity may be produced by more than one activity. Firms are price takers and minimize Factor Markets Activities Households Commodity Markets Rest of World + Rest of Country Government Capital Account domestic wages and rents factor demand foreign + RoC wages and rents domestic demand exports imports interm input demand private consumption gov cons and inv indirect taxes private savings transfers transfers transfers direct taxes foreign + RoC savings government savings investment 8 costs subject to nested technological constraints. Sectoral output is determined by combining value added with intermediate consumption through a fixed share, Leontief production function. Composite labor is a constant elasticity of substitution (CES) function of various types of labor indicating imperfect substitution between types of labor. Composite capital and land are also formed in this way. Value added is created by a CES function of factors (labor, capital. land and other natural resources) where firms employ factors until the value of the factor’s marginal product is equal to the factor price. Income and savings Households receive income from labor, capital, land and transfers from other agents including remittances from abroad. Factor income is apportioned to households in fixed shares while income from transfers is the sum of all transfers for each household category. Households pay direct taxes and make transfers to the government, which constitute contributions to social assistance programs (e.g. employment insurance). The government is a consolidated institutional sector; in practical terms, and due to the lack of data, there is only one government which is the sum of central and local governments. Depending on the selected closure rule, government expenditures are exogenous. Disposable household income is equal to household income net of transfers, taxes and savings. Household savings are a linear function of disposable income. Firms receive income from returns to capital and transfers from other agents. Firms pay income tax and also save. The government receives income from income tax paid by firms and households, indirect taxes on goods and services, capital taxes, import duties, production taxes on industries, payroll taxes from labor, export taxes, and income from transfers. Income taxes for firms and households are a linear function of their total income. The rest of the world receives income from the sale of imports, returns to capital and transfers while foreign spending consists of export purchases and transfers to agents in the domestic economy. Transfers to households and firms are treated as proportional to their disposable income while household transfers to other institutions are treated as a linear function of total income. 9 Demand Goods and services are demanded by households, domestic and foreign tourists, the government, investment and as transport and trade margins. Households have a Stone-Geary utility function, with a linear expenditure system (LES) describing household consumption. In a LES, households use their income to first consume a minimum level of subsistence goods and services. With the supernumerary income remaining, households purchase goods and services according to a linear relationship between income and consumption. LES differ from CES functions in that LES functions have non-unitary income elasticities between all pairs of goods enabling flexibility with regards to substitution possibilities in response to changes in relative prices. Investment demand is composed of gross fixed capital formation (GFCF) and changes in inventories. GFCF is endogenous with total investment expenditure balanced by the savings and investment constraint where savings is endogenous. Inventory changes are exogenous in the model and fixed in volume. Investment in goods and services occurs in fixed shares. Government expenditures for a given budget also follow this logic. Tourism demand by commodity can be exogenous or endogenous. In the current application, it is assumed that foreign tourism demand follows an exogenous path, which allows assessment of the impact of increased foreign tourism demand predicted by the destination-specific tourism demand and value chain analysis. The inflow of foreign tourism is an important source of foreign exchange for the South Department. Supply and trade The South Department is too small to affect prices in international and interregional markets and, as a consequence, the RoC and RoW (rest of country and rest of world, respectively) prices are taken to be exogenous. In the tradable goods sectors, the composite commodity price is a weighted average of local prices and import (i.e., from RoC and RoW) prices, whereas in most tourism sectors, prices are determined by local average costs. Thus, tourism services produced in the local economy are assumed to be non-tradable. A constant elasticity of transformation (CET) function describes how industry output responds to changes in prices. This functional form implies that an industry may reorganize production in 10 response to changes in prices, though they cannot perfectly or completely switch from the production of one commodity to another. Industries allocate output to domestic and foreign markets based on the assumption that the goods destined to one market are different from those destined to another market. This assumption is operationalized through a CET function. World export prices are fixed (i.e. the world export demand curve is horizontal). Domestic and imported commodities are aggregated with a CES function. To reflect heterogeneity in goods and services with regards to their origin, goods and services consumed domestically are aggregate goods composed of domestically produced and imported goods, both from the rest the world and the rest of the Haiti. Model dynamics In the RCGE, growth over time is largely endogenous. The economy grows due to accumulation of capital determined by investment and depreciation, labor (determined by exogenously imposed projections), as well as because of improvements in total factor productivity (TFP) which have both endogenous and exogenous components. Apart from an exogenous component, TFP of any production activity potentially depends usually, positively on the levels of government capital stocks and economic openness. On the supply side of the labor markets, unemployment is endogenous: for each labor type, the model includes a wage curve that imposes a negative relationship between the real wage and the unemployment rate (Blanchflower and Oswald 2004). As will be shown, the economic impacts of an increase in inbound tourism depend critically on the assumptions made about the extent of wage flexibility in the economy. In fact, the effects of tourism growth on economic variables will differ depending on the ability of the tourism-related sectors to obtain labor without pushing up wages. For non-labor factors, the supply curves are vertical in any single year. 2.2. RCGE Model Dataset The basic accounting structure and much of the underlying data required to implement our RCGE model is derived from a Regional Social Accounting Matrix (RSAM) constructed for the South Department. An RSAM is a comprehensive, economy-wide statistical representation of a regional economy at a specific point in time. It is a square matrix with identical row and column accounts where each cell in the matrix shows a payment from its column account to its row 11 account. It is used for descriptive purposes and is the key data input for a RCGE. Major accounts in a standard SAM are: activities that carry out production; commodities (goods and services) which are produced and/or imported and sold domestically and/or exported; factors used in production which include labor, capital, land and other natural resources; institutions such as households, government, and the rest of the country and the rest of the world. A stylized RSAM is provided in Appendix B. Generally speaking, most features of the RSAM are familiar from social accounting matrices used in other models. However, our RSAM has some unconventional features related to the explicit treatment of (a) trade relations (i.e., exports and imports) between the South Department and the rest of Haiti, and (b) domestic and foreign tourism-related spending. In this study, the RCGE model was calibrated with the newly-constructed RSAM for fiscal year (FY) 2013 and other data for Haiti and the South Department. The FY 2013 is the latest for which supply and use tables (i.e., the core required data) are available. The main sources of information for building the RSAM were the 2013 supply and use tables, national accounts, balance of payments, government data (specifically, budget and recurrent incomes and expenditures), and income and expenditure household survey data (IHSI 2003, 2012). 2 The RSAM was built following the methods and assumptions described by Jackson (1998), Lahr (1993) and Madsen and Jensen-Butler (1999). Please see Appendix B for further details (Jackson 1998, Lahr 1993, Madsen and Jensen-Butler 1999) Table 1 shows the accounts in the RSAM, which determine the size (i.e. disaggregation) of the model. The RSAM includes 11 sectors (activities and commodities). 3 The factors of production include four types of labor, unskilled (no education and primary education), semi-skilled (secondary education), and skilled (tertiary education). The non-labor factors include a private capital stock, land, and a natural resource used in mining activities. The RSAM also identifies current accounts for institutions (household, government, rest of Haiti, rest of world, tourists 2 This supply and use tables are believed to be the first update since the original I-O table dating back to 1975/76. To construct the government account of the RSAM, The Central Bank of the Republic of Haiti and the Ministry of Economics and Finance were consulted for balance of payments, and income and expenditure data. 3 Unfortunately, the available data (i.e., national supply and use tables and regional employment) does not allow us to better identify the tourism- related industries in the RSAM (see Appendix B). For example, we cannot disaggregate the Transport and communications sector into its two sub-sectors. 12 from Haiti, and tourists from the rest of world), two investment accounts, and accounts for (national and local) taxes. Table 1: Accounts in the Haiti South region FY 2013 regional social accounting matrix Category Item Category Item Agriculture, forestry and fishingFactors (7)Labor, no education Mining Labor, primary education Manufacturing Labor, secondary education Electricity and water Labor, tertiary education Construction Capital Trade Land Hotels and restaurants Extractive natural resources Transport and communications Households Financial services Government Other market services Rest of the world Other non-market services Tourism demand, Rest of th e world Activity tax Rest of the country Commodity tax Tourism demand, Rest of the country Commodity subsidy Savings Import tariff Investment, private Direct tax Investment, government Stock change Sectors (activities and commodities) (11) Savings- Investment (4) Taxes Institutions (6) Source: Authors’ own elaboration. According to our estimates in the RSAM, the South Department’s Gross Regional Product (GRP) reached 28,773 million gourdes in FY 2013 (see Table 1), equivalent to 7.8 percent of the national Gross Domestic Product (GDP). In FY 2013, the regional government current consumption was 1.9 percent of regional GRP. Remittances accounted for 19.1% of GRP. 13 Table 2: GRP structure (million gourdes) Item LCU GDP Share Total Demand Private consumption 16,604.5 57.9 Fixed investment 4,834.8 16.9 Stock change 2.5 0.0 Government consumption 561.0 2.0 Exports 2,045.5 7.1 Exports to RoC 16,946.7 59.1 Tourism demand RoC 0.0 0.0 Tourism demand RoW 375.4 1.3 Total 41,370.4 144.2 Total Supply GDP at market prices 28,686.2 100.0 Imports 8,852.6 30.9 Imports from RoC 3,831.6 13.4 Total 41,370.4 144.2 Source: Authors’ own elaboration; South Department RSAM. The production and trade structure of the South Department is reflected in panels (a) and (b) of Table 3, respectively (see Table 3.c for variable definitions). Column EMPshr in Table 3.a shows the share of each sector in total employment. For example, the tourism-related sector of hotels and restaurants represents one percent of total employment. In turn, Columns EXPshr and IMPshr of Table 3.b show the share of each sector in total exports and imports to and from the rest of world, respectively. Columns EXP-OUTshr and IMP-DEMshr of Table 3.b present, for each sector, the share of exports to RoW in production and the share of imports from RoW in consumption, respectively. For instance, while the mining products sector represents a significant share of export revenue (around 71.4%), their share in total value added is about 4%. The Haiti South Department FY 2013 SAM reports taxes paid by institutions, commodity sales, activities, and tariffs; estimated total regional net tax revenue reached 5.6% of GRP in FY 2013, compared to 8% at the national level. In terms of trade with the rest of Haiti, columns (EXP- RoCshr) and (IMP-RoCshr) of Table 3b show the share of each sector in total exports and imports to and from the rest of the country, respectively. 14 Table 3.a: Sectoral production structure in FY 2013 (percent) Commodity VAshr PRDshr EMPshr Agriculture, forestry and fishing 30.3 33.3 58.9 Mining 0.8 0.9 1.1 Manufacturing 4.1 7.7 3.0 Electricity and water 1.8 2.6 0.2 Construction 23.2 18.7 2.1 Trade 26.4 22.6 22.7 Hotels and restaurants 0.3 0.8 0.7 Hotels and restaurants, imports 0.0 0.0 0.0 Transport and communications 7.1 6.9 0.9 Financial services 2.1 2.1 0.2 Other market services 3.7 3.9 10.1 Other non-market services 0.3 0.3 0.2 Total 100.0 100.0 100.0 Table 3.b: Sectoral trade structure in FY 2013 (percent) Commodity EXPshr EXP- OUTshr IMPshr IMP- DEMshr EXP- RoCshr EXP- RoC- OUTshr IMP- RoCshr IMP- RoC- DEMshr Agriculture, forestry and fishing 16.7 2.8 19.3 20.1 45.2 53.2 20.3 8.8 Mining 0.0 0.0 0.1 13.0 2.2 96.4 1.0 62.1 Manufacturing 60.8 44.3 59.9 75.4 0.1 0.6 5.8 2.9 Electricity and water 0.0 0.0 0.0 0.0 2.7 40.5 1.2 6.5 Construction 0.0 0.0 0.0 0.0 21.2 44.4 9.4 7.4 Trade 0.0 0.0 0.0 0.0 24.1 41.7 11.4 7.1 Hotels and restaurants 12.9 89.3 0.0 0.0 0.0 0.0 0.0 0.2 Hotels and restaurants, imports 0.0 0.0 0.5 100.0 0.0 0.0 0.0 0.0 Transport and communications 6.2 5.0 17.0 26.7 0.8 4.7 36. 5 24.8 Financial services 1.9 5.0 2.0 21.4 1.5 27.1 0.7 3.1 Other market services 1.4 2.0 1.2 6.9 1.9 19.3 1.0 2.4 Other non-market services 0.0 0.0 0.0 0.0 0.3 41.1 12.8 87. 5 Total 100.0 5.6 100.0 25.3 100.0 39.2 100.0 25.3 15 Table 3.c: Variable definitions Variable Definition Variable Definition VAshr value-added share (%) IMP-DEMshr imports as shar e of domestic demand (%) PRDshr production share (%) EXP-RoCshr sector share in total exports to RoC (%) EMPshr share in total employment (%) EXP-RoC-OUTshr exports to RoC as share in sector output (%) EXPshr sector share in total exports (%) IMP-RoCshr sector share in total imports from RoC (%) EXP-OUTshr exports as share in sector output (%) IMP-RoC-DEMshr imports from RoC as share of domestic demand (%) IMPshr sector share in total imports (%)Source: Authors’ own elaboration; South Department RSAM. In 2013, foreign tourism spending in the Haiti South Department totaled 375.4 million of gourdes (Banerjee, Velasco, and Torres 2014). In turn, according to the RSAM, tourism-induced imports (from the rest of Haiti and the rest of the world) were estimated as 153 million of gourdes, or about 41 cents for every gourde of final (foreign) tourism expending in the South Department. 4 The difference between the two figures yields a tourism direct and indirect contribution of 222.4 million gourdes to the South’s GRP. The direct tourism contribution to the South’s GRP alone was 119.7 million gourdes. In terms of employment, the tourism industry in the South Department of Haiti generates 1,976 and 884 direct and indirect jobs, respectively; thus, total employment in tourism related industries is 2,860. Beyond the RSAM, data related to the labor market, depreciation rates for private and public capital, and various elasticities are also used to calibrate the model. These data include number of workers and initial unemployment rates by skill level. The required (exogenous) elasticities include those in production, trade, consumption, and in the wage/rental rate curve. By and large, these data were obtained from best estimates in the literature. The robustness of results to 4 The direct and indirect import content of tourism expenditure was estimated using standard input-output techniques (see (Smeral 2006). Certainly, this estimate is influenced by the assumptions made to estimate the domestic use matrix. Specifically, imports in the supply and use tables correspond to a column vector that reports total imports by commodity. Thus, we created an import matrix by pro-rating the totals across uses by applying the structure implied by the total use matrix; that is, for each row of the total use matrix we computed the percentage of the row total allocated to each sector. Then, we filled in the import matrix by multiplying each commodity total by the appropriate share for each sector. Finally, we subtracted the new import matrix from the total use matrix to obtain the domestic use matrix. 16 variation in these parameters was analyzed with a systematic sensitivity analysis described in detail in Appendix D. 2.3. Microsimulation Model While CGE models are effective in capturing aggregate responses to shocks introduced, for example, an increase in tourism demand through improved tourism destination marketing abroad, the standard configuration of a CGE model is not well suited for analysis of questions related to poverty and income inequality. This is due to the fact that most CGE models use a representative household (RH) formulation where all households in an economy are aggregated into one or a few households to represent household and consumer behavior. The main limitation of the RH formulation is that intra-household income distribution does not respond to shocks (e.g. a tourism investment) introduced into the model. Blake et al. (2009) and Wattanakuljarus and Coxhead (2008) are examples of CGE analyses which use the RH approach and explore tourism impacts on poverty and income distribution (Blake et al. 2009, Wattanakuljarus and Coxhead 2008). To provide greater resolution with regards to household-level impacts, we generate results in terms of poverty and inequality at the micro level by linking the RCGE model with a microsimulation model (see Figure 3). The two are used in a sequential “top-down” fashion (i.e., without feedback): the RCGE communicates with the microsimulation model by generating a vector of real wages 5 , aggregate employment variables such as labor demand by sector and the unemployment rate, and non-labor income. The functioning of the labor market thus plays an important role, and the RCGE model determines the changes in employment by factor type and sector, and changes in factor and product prices that are then used for the microsimulations. In Appendix C we present a more detailed description of the microsimulation model. 5 The real wage is defined in terms of the CPI; see the RCGE model mathematical statement in the Appendix A. [... middle sections omitted for long document ...] 84 tfpelassim -- tfpelassim(sim,a,ac) In this sheet, changes to total factor productivity elasticities for each activity arising from changes to stocks of public capital. It is important to note that tfpelassim should only be adjusted when the model is used in its static mode (i.e. dmod=0) or when the baseline reference scenario is generated under the assumption of a balanced growth path (i.e. dmod=2). Otherwise, modifying the value of tfpelassim would require that the baseline reference scenario to be recreated. layout This sheet presents how information will be organized in the Excel file. In general, it should not be modified by the user. E.5. The Report File The file report (i.e., reporte.gdx) is generated at the end of the execution simulations file sim.gms. The report includes: (1) all endogenous variables (variable name + X); (2) the percentage change from the base for all endogenous variables (variable name + XP); (3) the parameters used to define the counterfactual scenarios (parameter name + x), and; (4) some reports calculated as described below. • modsolstat(solcol,t,sim): solver and model status. Because the RCGE model is a constrained non-linear system, the solver and model status should be 1 and 16, respectively. Otherwise, there has been an error. • SIMSAM(ac,acp,t,sim): a collection of SAMs defined from the results generated by each simulation contained in the simcur set. • simsambalchk(ac,t,sim): is a parameter that allows verification of the equality between SIMSAM rows and columns. • MACROSAM(ac2,ac2p,t,sim): contains an aggregate SAM for each simulated scenario. • macrosambalchk(ac2,t,sim): is a report parameter for ascertaining whether the macrosam in MACROSAM is properly balanced. 85 • gdpindic(igdp,kgdp,t,sim): a summary table that includes GDP and its components, both in real and nominal terms, as well as in absolute terms and as a proportion of GDP. • gdpindicXP(igdp,kgdp,t,sim): is a summary similar to the previous one but presents thee above indicators in percentage changes from values in the base scenario. • sectorstruc(ac,sectorcol,t,sim): is a table that describes the sectoral structure of the economy, for both production and foreign trade. For example, the table contains the participation of each good in total exports and imports, the participation of imports in total consumption, and the participation of exports in total production. • sectorindic(ac,sectorcol2,kgdp,t,sim): is a table similar to the table above, but unlike the previous one, it presents information in absolute values. The sectorindicxp table presents the results as percentage changes from the base scenario. • fiscalindic(fiscalcol,t,sim): contains fiscal indicators such as the ratio of public savings to GDP, and the ratio between tax revenue and GDP, among others. • taxstruc(ac,taxcol,t,sim): contains information on tax revenues in absolute terms, as a proportion of the total of taxes collected, and as a proportion of GDP. • bopindic(bopcol,kgdp,t,sim): contains information on the balance of payments in domestic currency, as a proportion of GDP, and in foreign currency. • actvashr(a,t,sim): contains information on the share of each activity in total value added. • ev(h,t,sim): is the equivalent variation. • cv(h,t,sim): is the compensating variation. • tourindic(ac,ac,kgdp,t,sim): contains reports specific to the tourism sector, such as the national and international tourism demands. The reports that are expressed in local currency are expressed in the currency of the original SAM. 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