Enhancing Sustainable Fisheries Trade and Food Security Through CPEC in Pakistan
Abstract
1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Hypothesis
2.3. Analytical Framework
- Descriptive statistics (growth rates, percentages, and variability measures) were computed using Microsoft Excel and Python 3.13.5 to provide baseline trends.
- Interrupted Time Series (ITS) models were applied to detect structural breaks in export trajectories around 2015. The specification included time trends, a post-2015 intervention dummy, and their interaction to test for changes in level and slope.
- Difference-in-Difference (DiD) models compared exports to treatment countries (China and Thailand, which are directly connected through CPEC routes) with control countries (e.g., Malaysia and Indonesia, which trade with Pakistan but are not directly affected by CPEC). The interaction term captured the differential post-2015 effect attributable to CPEC. Robust standard errors were used to address heteroscedasticity.
2.4. Analytical Rationale
2.5. Data Limitations and Assumptions
3. Results
3.1. Statistical Analysis of Fish Export to Top Five Asian Countries from 2005 to 2024
3.1.1. Descriptive Trends
3.1.2. Country-Specific Trends
3.2. Interrupted Time Series (ITS) Analysis
3.3. Difference-in-Difference Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Appendix A.1. OLS Regression Results
Dep. Variable: | ln_val | R-squared: | 0.747 | |||
Model: | OLS | Adj. R-squared: | 0.737 | |||
Method: | Least Squares | F-statistic: | 84.04 | |||
Date: | Sun, 17 August 2025 | Prob (F-statistic): | 4.50 × 10−24 | |||
Time: | 19:18:01 | Log-Likelihood: | −73.693 | |||
No. Observations: | 80 | AIC: | 155.4 | |||
Df Residuals: | 76 | BIC: | 164.9 | |||
Df Model: | 3 | |||||
Covariance Type: | HC1 | |||||
coef | std err | z | P > |z| | [0.025] | [0.975] | |
const | 15.7361 | 0.208 | 75.564 | 0.000 | 15.328 | 16.14 |
treat | 1.6583 | 0.228 | 7.271 | 0.000 | 1.211 | 2.105 |
post2015 | 0.4742 | 0.242 | 1.962 | 0.050 | 0.001 | 0.948 |
treat_post | 0.5468 | 0.279 | 1.960 | 0.050 | 0.000 | 1.093 |
Omnibus: | 32.146 | Durbin–Watson: | 0.952 | |||
Prob(Omnibus): | 0.000 | Jarque–Bera (JB): | 65.841 | |||
Skew: | −1.457 | Prob(JB): | 5.04 × 10−15 | |||
Kurtosis: | 6.356 | Cond. No. | 6.85 | |||
Note: Standard Errors are heteroscedasticity robust (HC1). |
Appendix A.2. Supplementary Equations and Model Specifications
Appendix A.2.1. Descriptive Statistics
- µx = Estimation,
- n = Total Number,
- I = Frequency of observation and
- N = Total
- Percentage calculation:
- Percentages ( were calculated as:
- x = Given Quantity,
- n = Total amount, and
- p = percentage of the quantity compared to the total.
- Growth rate:
- Growth Rate (GR) was computed through:
- GR = Growth Rate
- cy = Current year,
- py = Previous year. These metrics provided a descriptive basis for understanding the scale and pace of export changes.
Appendix A.2.2. Statistical Analysis
- Sample mean:
- = mean,
- f = Frequency of each Class,
- = mid-interval value of each class
- N = Total frequency
- = sum of the products of mid–interval Values and their corresponding frequency
- Standard error:
- = Standard Error of the Sample,
- σ = Sample Standard Deviation,
- n = Sample of Samples
- Confidence Interval (95%)
- CI = Confidence interval,
- = sample mean,
- s = sample standard deviation,
- n = Sample Size, and
- z = 1.96 for a 95% level of significance.
Appendix A.2.3. Interrupted Time Series (ITS) Analysis
Appendix A.2.4. Difference in Difference (DiD) Model
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Countries | µ (y−1) | Confidence Interval | |
---|---|---|---|
China | 87,239.65 * | 13,478.63 | 59,028.55–115,450.75 |
Thailand | 61,364.60 * | 8630.39 | 43,300.99–79,428.21 |
Vietnam | 40,277.45 * | 8875.83 | 21,700.11–58,854.79 |
Saudi Arabia | 11,045.21 * | 1087.73 | 8759.98–13,330.44 |
Japan | 8454.00 * | 1027.52 | 6303.37–10,604.63 |
Total Exports | 208,380.91 * | 33,100.10 | 139,093.00–277,668.82 |
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Dahri, A.M.; Yongtong, M. Enhancing Sustainable Fisheries Trade and Food Security Through CPEC in Pakistan. Sustainability 2025, 17, 9121. https://doi.org/10.3390/su17209121
Dahri AM, Yongtong M. Enhancing Sustainable Fisheries Trade and Food Security Through CPEC in Pakistan. Sustainability. 2025; 17(20):9121. https://doi.org/10.3390/su17209121
Chicago/Turabian StyleDahri, Ali Mumtaz, and Mu Yongtong. 2025. "Enhancing Sustainable Fisheries Trade and Food Security Through CPEC in Pakistan" Sustainability 17, no. 20: 9121. https://doi.org/10.3390/su17209121
APA StyleDahri, A. M., & Yongtong, M. (2025). Enhancing Sustainable Fisheries Trade and Food Security Through CPEC in Pakistan. Sustainability, 17(20), 9121. https://doi.org/10.3390/su17209121