Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/328808 
Year of Publication: 
2023
Citation: 
[Journal:] Economies [ISSN:] 2227-7099 [Volume:] 11 [Issue:] 7 [Article No.:] 183 [Year:] 2023 [Pages:] 1-22
Publisher: 
MDPI, Basel
Abstract: 
The average payment period (APP) is an important measure to monitor public sector liquidity and commercial debt sustainability. In the European Union, the relevance of APP as an indicator to mitigate those concerns was settled by the issuance of a Directive on this topic. Then, considering the likely relationship between the APP and financial distress (FD), this paper aims to assess if the current and historical APP plays a relevant role in explaining the data for 308 Portuguese municipalities' FD. Regression analysis, including panel data and simple linear regression models, is used for the period between 2011 and 2019 (the last year available for APP). The findings show that the number of municipalities that exceed the debt limit has been reducing. Some of them comply with the 30 days threshold being, nonetheless, in a financial distress situation and subject to recovery mechanisms. By APP levels, the findings identify that the APP significantly predicts FD for those entities that do not comply with the threshold. By size, the FD seems to be better explained by historical APP within the smaller entities. Finally, the robustness test and further analyses performed indicate the likely relevance of macroeconomic factors for predicting FD using APP as an explanatory variable. This paper contributes to previous studies on the municipalities' financial condition, namely by considering the APP in the analysis of the financial situation of the municipalities. As a novelty, this study considers a new proxy for municipal FD and panel data analysis.
Subjects: 
average payment period
financial distress
Portuguese municipalities
over-indebtedness
panel data analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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