COVID-19 Effects on Tourist Fees: Bolivia’s National Parks Case Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Data Collection
2.3. Analytical Technique
2.3.1. Survey
2.3.2. Econometric Model
- Demographic Variables: we included age, education, income, and gender to account for the influence of visitors’ backgrounds on their WTP. These variables are standard in survey-based studies, as they help ensure that our results are not biased by demographic differences among respondents. More specifically:
- ∘
- Age: in general, older visitors may have a higher WTP due to a greater appreciation of conservation efforts.
- ∘
- Education: higher education levels might potentially increase WTP as individuals may have a better understanding of the importance of protected areas.
- ∘
- Income: higher income is expected to increase WTP since individuals with higher income can afford to pay more.
- Gender: gender may have varying effects on WTP depending on the cultural and social context, but generally, it can influence WTP patterns.
- Fee Awareness: this variable captures whether respondents were aware of the entrance fees prior to their visit. Awareness of fees can significantly influence WTP, as those who are informed may have different valuation perceptions compared to those who are unaware.
- Prior PA Experience: this variable indicates whether the respondent had previous experiences with PAs. Prior experience can affect WTP because it may shape visitors’ appreciation and understanding of the value of conservation efforts.
- Length of Stay: The duration of the visit was included as a control variable, as it can influence WTP. Longer stays might indicate a higher level of engagement and satisfaction, potentially leading to a higher WTP.
- Mountain Climbing (specific to Sajama National Park): For Sajama National Park, we included an additional variable that indicates whether the respondent engaged in mountain climbing activities during their visit. Mountain climbing is a unique activity that could significantly influence WTP due to its associated costs and perceived value.
3. Results
3.1. Sajama National Park
3.1.1. Descriptive Statistics
3.1.2. Willingness to Pay
3.2. Cotapata National Park
3.2.1. Descriptive Statistics
3.2.2. Willingness to Pay
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Survey | Sajama | Cotapata | |
---|---|---|---|
International Tourists | National Tourists | International Tourists | |
Survey 1 | 0 | 5 | 3 |
Survey 2 | 3 | 10 | 6 |
Survey 3 | 6 | 15 | 9 |
Survey 4 | 10 | 20 | 12 |
Survey 5 | 14 | 25 | 15 |
Variable | Category | 2019 | 2023 |
---|---|---|---|
(%) | (%) | ||
Age | 18–24 | 14.07 | 12.54 |
25–34 | 28.14 | 44.55 | |
35–44 | 12.87 | 15.84 | |
45–54 | 6.89 | 11.88 | |
55+ | 38.02 | 15.18 | |
Gender | Women | 44.58 | 42.57 |
Men | 55.42 | 57.43 | |
Education level | Without formal education | 0 | 0 |
Elementary | 0 | 0 | |
Middle and high school | 17.92 | 11.22 | |
University | 40.42 | 35.97 | |
Graduate degree (Master or PhD) | 41.67 | 52.81 | |
Income level | Less than USD 500 | 10.92 | 4.29 |
USD 500–USD 1500 | 19.65 | 14.19 | |
USD 1500–USD 3000 | 28.38 | 27.72 | |
USD 3000–USD 4500 | 16.16 | 23.1 | |
USD 4500–USD 6000 | 6.99 | 15.18 | |
USD 6000+ | 17.9 | 15.51 |
Variable | (1) Marginal Effect (dy/dx) (Robust std. Err.) | (2) Marginal Effect (dy/dx) (Robust std. Err.) |
---|---|---|
Fee increase | −0.019 | −0.019 |
(0.004) | (0.004) | |
COVID | 0.120 | 0.104 |
(0.041) | (0.041) | |
Age | 0.000 | 0.000 |
(0.002) | (0.002) | |
Education | 0.013 | 0.010 |
(0.029) | (0.029) | |
Income | 0.036 | 0.036 |
(0.015) | (0.015) | |
Gender (male = 1) | −0.088 | −0.103 |
(0.041) | (0.042) | |
Fee awareness | −0.086 | −0.083 |
(0.048) | (0.048) | |
Prior PA experience | −0.049 | −0.052 |
(0.053) | (0.054) | |
Length of stay | −0.011 | −0.027 |
(0.012) | (0.013) | |
Mountain climbing | 0.140 | |
(0.048) |
Variable | Category | Lowland Area Tourists (National Tourists) | |
---|---|---|---|
2019 (%) | 2023 (%) | ||
Age | 18–24 | 15.15 | 41.94 |
25–34 | 42.42 | 25.51 | |
35–44 | 20.88 | 15.25 | |
45–54 | 14.48 | 10.85 | |
55+ | 7.07 | 6.45 | |
Gender | Women | 49.49 | 54.25 |
Men | 50.51 | 45.75 | |
Education level | Without formal education | 0.00 | 0.29 |
Elementary | 1.68 | 1.76 | |
Middle and high school | 75.43 | 20.24 | |
University+ | 22.9 | 77.71 | |
Income level | Less than BOB2500 | 14.86 | 20.53 |
BOB 2500–BOB 4000 | 26.01 | 21.7 | |
BOB 4000–BOB 5500 | 14.19 | 17.89 | |
BOB 5500–BOB 7000 | 12.16 | 12.61 | |
BOB 7000–BOB 9000 | 12.16 | 18.48 | |
BOB 9000+ | 20.61 | 8.8 |
Variable | Category | Mountain Bike Tourists (International Tourists) | |
---|---|---|---|
2019 (%) | 2023 (%) | ||
Age | 18–24 | 35.84 | 15.3 |
25–34 | 51.88 | 63.66 | |
35–44 | 8.53 | 15.03 | |
45–54 | 2.05 | 4.92 | |
55+ | 1.71 | 1.09 | |
Gender | Women | 39.87 | 38.25 |
Men | 60.13 | 61.75 | |
Education level | Without formal education | 0.32 | 0.00 |
Elementary | 0.32 | 0.27 | |
Middle and high school | 21.43 | 10.66 | |
University+ | 77.92 | 89.07 | |
Income level | Less than USD 500 | 16.5 | 6.01 |
USD 500–USD 1500 | 31.99 | 18.85 | |
USD 1500–USD 3000 | 22.56 | 28.42 | |
USD 3000–USD 4500 | 13.8 | 21.31 | |
USD 4500–USD 6000 | 5.05 | 10.66 | |
USD 6000+ | 10.1 | 14.75 |
Tourists | 2019 | 2023 |
---|---|---|
Domestic | BOB. 23 (USD 3.3) | BOB. 20 (USD 2.8) |
Foreign | USD 13 | USD 13 |
Variable | National Tourists Marginal Effect (dy/dx) (Robust Std. Err.) | International Tourists Marginal Effect (dy/dx) (Robust Std. Err.) |
---|---|---|
Fee increase | −0.012 (0.002) | −0.016 (0.003) |
COVID | −0.117 (0.040) | −0.019 (0.026) |
Age | −0.002 (0.001) | −0.001 (0.002) |
Education | 0.025 (0.014) | −0.010 (0.017) |
Income | 0.007 (0.009) | 0.022 (0.009) |
Gender (male = 1) | 0.000 (0.029) | −0.075 (0.025) |
Fee awareness | −0.060 (0.040) | −0.006 (0.051) |
Prior PA experience | −0.001 (0.032) | 0.044 (0.030) |
Length of stay | 0.001 (0.001) | 0.013 (0.014) |
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Rakela, S.; Vilela, T.; Espinoza, S.; Harb, A.M. COVID-19 Effects on Tourist Fees: Bolivia’s National Parks Case Study. Sustainability 2025, 17, 1768. https://doi.org/10.3390/su17051768
Rakela S, Vilela T, Espinoza S, Harb AM. COVID-19 Effects on Tourist Fees: Bolivia’s National Parks Case Study. Sustainability. 2025; 17(5):1768. https://doi.org/10.3390/su17051768
Chicago/Turabian StyleRakela, Stefanie, Thais Vilela, Sophia Espinoza, and Alfonso Malky Harb. 2025. "COVID-19 Effects on Tourist Fees: Bolivia’s National Parks Case Study" Sustainability 17, no. 5: 1768. https://doi.org/10.3390/su17051768
APA StyleRakela, S., Vilela, T., Espinoza, S., & Harb, A. M. (2025). COVID-19 Effects on Tourist Fees: Bolivia’s National Parks Case Study. Sustainability, 17(5), 1768. https://doi.org/10.3390/su17051768