Exchange rate volatility and its impact on foreign trade: Evidence from Peru in a period of global and domestic turbulence (2019-2023)

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Type of the article: Research Article

Abstract
Between 2019 and 2023, the Peruvian sol showed an accumulated nominal variation of approximately 12.9%, reflecting moderate depreciation influenced by both external and domestic factors, although in 2022 it appreciated by 4.6%, positioning itself as one of the most stable currencies in the region. The objective of this study was to estimate the impact of exchange rate volatility on Peru’s foreign trade during this period of global and domestic turbulence, employing a quantitative correlational design with secondary data from the Central Reserve Bank of Peru (BCRP) and the National Superintendence of Customs and Tax Administration (SUNAT), analyzed through regression models and statistical tests in SPSS. The results indicate that exchange rate variability explains 61.1% of changes in export volume, 49.8% in import volume, and 45.9% in terms of trade (all p < 0.01), while inflation and GDP also show significant associations with exports and imports, with R² values ranging from 24.5% to 60.4% (p < 0.01). These findings confirm that macroeconomic volatility, particularly exchange rate dynamics, significantly shapes trade performance. From a theoretical perspective, this study provides evidence from a primary-exporting economy, enriching the literature on exchange rate fluctuations in emerging markets, while from a practical standpoint, it underscores the importance of adopting economic and trade policies that mitigate external vulnerability, stabilize exchange rate fluctuations, and strengthen competitiveness. In conclusion, exchange rate volatility exerts a decisive influence on Peru’s foreign trade, reinforcing the need for integrated and sustainable policy measures to ensure stability and long-term growth.

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    • Figure 1. Exchange rate and export volume scatter plot
    • Figure 2. Scatter plot between the exchange rate and import volume
    • Figure 3. Exchange rate and terms-of-trade scatterplot
    • Table 1. Descriptive results for the exchange rate, inflation, and GDP
    • Table 2. Normality of data
    • Table 3. Pearson’s correlation
    • Table 4. Linear regression between the exchange rate and export volume
    • Table 5. Linear regression between the exchange rate and the import volume
    • Table 6. Linear regression between the exchange rate and terms of trade
    • Table 7. Linear regression between inflation and export volume
    • Table 8. Linear regression between inflation and import volume
    • Table 9. Linear regression between inflation and terms of trade
    • Table 10. Linear regression between GDP and export volume
    • Table 11. Linear regression between GDP and import volume
    • Table 12. Linear regression between GDP and terms of trade
    • Conceptualization
      Aurora Caytuiro-Valle, Cristhie Jazmine Vilchez-Julca
    • Data curation
      Aurora Caytuiro-Valle
    • Formal Analysis
      Aurora Caytuiro-Valle
    • Project administration
      Aurora Caytuiro-Valle
    • Visualization
      Aurora Caytuiro-Valle
    • Writing – review & editing
      Aurora Caytuiro-Valle, Franklin Cordova-Buiza
    • Funding acquisition
      Cristhie Jazmine Vilchez-Julca
    • Investigation
      Cristhie Jazmine Vilchez-Julca, Franklin Cordova-Buiza
    • Software
      Cristhie Jazmine Vilchez-Julca
    • Validation
      Cristhie Jazmine Vilchez-Julca
    • Writing – original draft
      Cristhie Jazmine Vilchez-Julca
    • Methodology
      Franklin Cordova-Buiza
    • Resources
      Franklin Cordova-Buiza
    • Supervision
      Franklin Cordova-Buiza