Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.

SEARCH GUIDE  Download Search Tip PDF File

  • articleNo Access

    Measuring Economic Uncertainty Synchrony with Cross-Sample Entropy Under Common External Factors: The Case of Chile

    In this paper, we measured the uncertainty synchrony level of Chilean business economic perception and consumer economic perception, both affected by common external factors reflected in the Global Economy Perception Index (GEPI), unemployment, inflation, interest rate, Monthly Economic Activity (MEAI) and the Economic Policy Uncertainty (EPUI) indexes. We propose using the Composite Multiscale Partial Cross-Sample Entropy (CMPCSE), which quantifies the intrinsic similarity of both time series affected by a common external factor. Uncertainty is measured through the Business Confidence Index (BCI) and Consumer Perception Index (CPI). BCI time series provide useful information about industry, commerce, and the finance, mining, construction and agricultural sectors, the global economic and general business situation. CPI time series measure consumer perception regarding the state of the economy, with consumers evaluating their economic situation and expectations. Results showed a high level of synchronization between business and consumer perceptions in the indexes due to different factors. The most influential in the long term corresponded to unemployment, interest rates, and inflation, EPUI and MEAI, generating uncertainty over a longer period. In addition, the GEPI was found to have an immediate effect on synchronization and high dependence on global uncertainty. Therefore, results could be useful for decision-making related to public policies based on microeconomic indicators of the construction and natural resource sectors, for example.