An Application for Tourism on the Yucat´an Peninsula
8.5 Scenarios and Preliminary Results
To address some of the questions raised in Section 8.3, this section describes a base scenario and examples of two types of analysis: policy analysis and sensitivity anal-ysis. The base scenario serves as a reference scenario for the policy scenario and the sensitivity run; it should not be seen as a best guess or the most probable out-come. The simulation results should be seen as indicative and should be compared with each other without looking at specific levels or paths.
The base scenario has a steady exogenous growth path for tourism based on the trend of the past 20 years. In this scenario, no policies are imposed. The policy scenario analyzes the effects of government-imposed policies to clean the water used by the resident population and the tourists. It is assumed that these policies are implemented totally and that they are effective. In this case, the indicator for the water quality remains the same over time. The government pays for cleaning the water used by the resident population, and the tourism sector (i.e., hotel owners) pays for cleaning the water used by tourists. In the sensitivity run, the population and the tourists are assumed to use twice as much water as in the base scenario.
Water use per day is not known precisely; therefore, it is useful to analyze the effects of different levels of water use. The policy and sensitivity analyses are illustrations of the type of analysis that is possible with dynamic modeling and simulations. Many other policy and sensitivity analyses can also be performed.
Various indicators for each module give an overview of the results of the sce-narios. In this section, indicators marked with an asterisk (*) are presented and explained systematically.
Tourism indicators: number of tourists*, rooms*, occupancy rate*, price per night.
Economic indicators for both regions: gross output, price, investment, value added; for the tourism region: international investment*, profit per room*.
Demographic indicators for both regions: population size*, labor force, migra-tion rate*, wages.
Environmental indicators: water quality*, quality of beaches and sites.
Governmental indicators: policy percentages, subsidy.
1999 1997
1995 2001 2003 2005 2007 2009 2011 2013 2015 -40
40 20 0 -20 60 80 100
Year
Migrationrate(per1000)
BasePolicy Sensitivity
Figure 8.3. The migration rate (per thousand) in the tourism region for the three scenarios.
Table 8.3 shows the changes in the population in the two aggregated regions of the peninsula. The birth and death rates for both regions are exogenous and equal in the three runs. In the base scenario, the population in the tourism region more than doubles in the 20-year period from 1995–2015. For the rest of the peninsula, the population increases by 60% over that period. The migration rate for the tourism region changes over time depending on the number of tourists and the labor force available (see Figure 8.3). The migrants come partly from the rest of the peninsula and partly from other parts of Mexico. The internal migrants may migrate back if there are no jobs available. The migration rate is very sensitive to changes in the number of tourists.
The migration rate to the tourism region is higher on average in the policy scenario than in the base scenario, because there are more tourists in the former because water quality is better. Thus, over the 20-year period, the population in the tourism region increases more in the policy scenario than in the base scenario.
The population in the rest of the peninsula in 2015 is slightly lower than in the base scenario because part of the migration to the tourism region comes from other parts of the peninsula. The peninsula’s population in 2015 is higher in the policy scenario than in the base scenario.
In the sensitivity run the quality indicator for the water is lower than in the base scenario, which has a negative impact on the number of tourists. Therefore, less labor is needed in the tourism region, implying a lower migration rate to it. The population in the tourism region in 2015 is lower than in the base scenario, while in the rest of the peninsula the population is higher than in the base scenario. The total population in 2015 is slightly lower in this run than in the base scenario.
In the base scenario, the number of tourists more than doubles in the tourism re-gion between 1995 and 2010 at an average rate of about 5% per year (see Figure 8.4
Table 8.3. Total population and population in the two regions for the three scenarios, 1995–2015 (in thousands).
Base Policy Sensitivity
Tourism Other Tourism Other Tourism Other
Year Total region region Total region region Total region region
1995 2,903 416 2,487 2,903 416 2,487 2,903 416 2,487
2000 3,415 576 2,840 3,422 588 2,833 3,410 566 2,845
2005 3,970 727 3,243 3,983 755 3,228 3,952 690 3,261
2010 4,542 847 3,696 4,559 883 3,677 4,520 800 3,720
2015 5,152 976 4,177 5,189 1,053 4,136 5,120 906 4,216
1981 1985 1990 1995 2000 2005 2010 0
5000 4000 3000 2000 1000 6000 7000 8000
Year
Tourists(1000)
Historical BasePolicy Sensitivity
Figure 8.4. Number of tourists (in thousands), historical and in the three scenarios.
Table 8.4. Number of tourists (in thousands) in the three scenarios.
Year Base Policy Sensitivity
1995 2,600 2,600 2,600
2000 3,430 3,495 3,367
2005 4,325 4,470 4,148
2010 5,168 5,459 4,899
2015 6,129 6,795 5,571
and Table 8.4). The quality of the archaeological sites is directly related to the num-ber of tourists. The quality of beaches decreases slightly because the increase in the number of tourists is faster than the increase in the number of rooms. The quality of beaches and archaeological sites decreases as they become more congested. The number of rooms, which depends on investment in tourism, increases from 8,000 to 14,000 in the Canc´un area. The occupancy rate increases because the number of tourists increases faster than the number of rooms (the number of tourists per room and the number of days that people stay remain the same over time). The profit per room increases steadily until 2004, after which it fluctuates between 258 and 283 pesos (in 1994 pesos) per night (see Table 8.5).
The growth in tourism is higher in the policy scenario than in the base scenario because of the government-imposed water policies. Over the 20-year period, the number of tourists is about 10% higher than in the base scenario. As in the other scenarios, the quality of the sites decreases with the number of tourists. The number of tourists and rooms (i.e., occupancy rate) also have an important effect on the quality of the beaches. In this scenario, the occupancy rate increases, and therefore, all else being equal, the quality of the beaches decreases. The number of rooms depends on the profit per room, and thus the number of rooms is higher as well (see Table 8.5). The occupancy rate is, on average, higher than in the base scenario. The
Table 8.5. Number of rooms, occupancy rate, and profit per room (in 1994 pesos) in the three scenarios.
Base Policy Sensitivity
Occupancy Profit per Occupancy Profit per Occupancy Profit per
Year Rooms rate room Rooms rate room Rooms rate room
1995 8,106 0.64 158 8,106 0.64 156 8,106 0.64 158
2000 8,974 0.76 221 8,989 0.78 230 8,955 0.75 212
2005 10,373 0.83 267 10,440 0.86 279 10,296 0.81 251
2010 12,128 0.85 258 12,132 0.90 285 12,047 0.81 228
2015 14,178 0.86 283 14,451 0.94 323 14,058 0.79 233
1999 1997
1995 2001 2003 2005 2007 2009 2011 2013 2015 0
60 40 20 80 100 120
Year
Waterqualityindicator
BasePolicy Sensitivity
Figure 8.5. Water quality indicator for the three scenarios.
costs to the tourists increase over time because of higher demand. An interesting result is that, although the hotel owners have to pay for cleaning the water, they gain from the governmental policy because the profit per room increases. This result may help the government to impose this policy, because they could show that it is profitable in the long run for the tourism sector.
The number of tourists increases less rapidly in the sensitivity run than in the base scenario. In 2015, the number of tourists is 10% lower in the former than in the latter. The quality of the beaches remains the same while the quality of the sites decreases with the number of tourists. The number of rooms and the profit per room increase, but at a lower rate than in the base scenario (see Table 8.5).
Figure 8.5 shows that the water quality indicator in the base scenario decreases over time as a result of water use by the resident population and the tourists. Per day, the tourists use more water than the local population, but of course each tourist stays only for a short period. The water quality affects the number of tourists. It has a natural purification rate that depends on the quality indicator. However, over the course of a year, water use has more impact than the natural purification rate, resulting in decreasing water quality.
In the policy scenario, water quality remains at the same level because of poli-cies ensuring that all the water that is used is cleaned. When twice as much water is used as occurs in the sensitivity analysis, the water quality decreases more than in the base scenario. It is interesting to see how water use may affect tourism, the rest of the economy, and the population in both regions.
Figure 8.6 shows international investment in the tourism sector. International investment depends on the profit per room. In the base scenario, international in-vestment increases, but fluctuates slightly, over time. The policy scenario shows more international investment in the tourism region, because more tourists visit
1999 1997
1995 2001 2003 2005 2007 2009 2011 2013 2015 0
400 300 200 100 500 700 600 800 900
Year
Internationalinvestment(1000pesos)
BasePolicy Sensitivity
Figure 8.6. International investment in the tourism sector (in thousands of 1994 pesos) in the three scenarios.
and therefore the profit per room is higher. The fluctuation is a result of changes in prices and number of tourists and rooms. In the sensitivity run, international investment increases less than in the base scenario.
In the base scenario, economic sectors outside of tourism are also the recipients of national and regional investment. The capital stock increases with those invest-ments. With a growing labor force and increasing prices in this region, the gross output and the profits increase as well. The wages in this region increase because the growth in gross output is higher than the growth in the labor force and the share of gross output going to labor changes only slightly (see Equations E2, E3, E8, and E9 in Appendix 8B).
For the rest of the economy, the policy scenario does not have an important effect on gross output, profits, or wages because the increase in the capital stock outweighs the decrease in labor force in this region.
In the sensitivity run, investments in the rest of the economy, gross output, and profits are lower than in the base scenario. The labor force is slightly higher and the gross output is lower, so the wages in this sector are lower than in the base scenario.
8.6 Conclusions
The goal of this study was to analyze the interactions between tourism, other eco-nomic sectors, environment, and population in a dynamic simulation model in which different policy and development path scenarios can be analyzed. We have constructed a mechanistic model that tries to explain the structure and the behavior of the system dynamically. A dynamic model is used to show the impacts over time and to include delayed effects. It is important to emphasize that the model does not