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The purpose of this study is to examine the relationship between the productive structure and the size of the informal economy in Latin American countries.

The study employs econometric techniques for panel data covering the period from 2002 to 2017 and considering 17 Latin American countries. The evidence presented is based on the informal economy data generated by Medina and Schneider (2018) who estimate the size of the informal economy using a structural equation model and the share of manufacturing in total employment as a measure of the size of the manufacturing sector. Also, the study addresses the possible endogeneity bias in the relationship studied and makes the conclusions more robust, thus avoiding spurious correlations that weaken the findings.

The results indicate that most industrialized Latin American countries are associated with a smaller size of the informal economy.

The findings have important policy implications, as they suggest that Latin American economies need to switch the structure of the economy toward more sophisticated productive structures if they want to reduce the size of the informal economy. Thus, more efforts should be deployed to policies to diversify and upgrade economies.

The study contributes to the literature on the informal economy by connecting the country’s productive structure and informality. Specifically, the results show that the productive structure of countries is a plausible explanation for the size of the informal economy.

Coastal cities offer great ecological, cultural and economic benefits due to their tourism potential. The objective of this research is to (1) identify tourists' post-pandemic motivations, (2) establish a post-pandemic demand segmentation and (3) determine the relationship between post-pandemic segments and loyalty.

This study was carried out in Lima, Peru, a tourist destination on the Pacific Ocean coast. The sample was collected between June and July 2020, during the coronavirus disease 2019 (COVID-19) pandemic. In total, 354 valid questionnaires represented the sample size of this quantitative study. For data analysis, factor analysis and K-means non-hierarchical clustering were used.

The results show four post-pandemic motivational dimensions in coastal cities: “novelty and escape,” “learning and culture,” “destination safety” and “service safety.” Likewise, there are two post-pandemic segments in coastal cities: “safety seekers” who want to feel safe at the destination and with its services, and “multiple motives,” motivated by several reasons simultaneously, such as safety, novelty and escape, and learning and culture. The multiple motives group shows higher return intentions, making it a crucial post-pandemic segment in coastal cities.

The limitations of the present study were the online sampling and the timing when collecting the data since the demand can vary due to seasonal reasons.

Since coastal cities have natural and cultural attractions appealing to many travelers, they should adopt the necessary biosecurity measures to attract the safety seekers’ segment, who wants to feel safe at the destination and with its services. Similarly, the multiple motives’ segment favors safety over other recreational activities in the coastal area, so it is necessary that activities such as sports on the beach, walks, observation of flora and fauna, navigation and interaction with the community, meet the required biosecurity standards.

The results will be used to plan the following actions in coastal destinations and meet the tourists’ demands when this health crisis ends.

In this context, up to date, demand segmentation by motivations in coastal cities during the COVID-19 pandemic has not been investigated. Such a study will help to obtain post-pandemic results regarding the tourism demand for these destinations. To date, there are no studies in coastal cities that analyze demand segmentation and its motivations for the post-COVID-2019 pandemic.