期刊
ACCOUNTING HISTORY REVIEW
卷 32, 期 1, 页码 59-89出版社
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/21552851.2022.2097929
关键词
Revenue; expenditure; Coimbra; Markov-Switching; transition probability; Early Modern era
类别
资金
- Portuguese national funds through FCT -Fundacao para a Ciencia e a Tecnologia, I.P. [SFRH/BD/143897/2019]
- NECE-UBI, Research Unit in Business Science and Economics, through FCT -Fundacao para a Ciencia e a Tecnologia, I.P. [FCT: UIDB/04630/2020]
- Centre for Social and Organizational Studies (CEOS), through FCT -Fundacao para a Ciencia e Tecnologia, I.P. [FCT: UIDB/05422/2020]
- NECE-UBI
- Fundação para a Ciência e a Tecnologia [SFRH/BD/143897/2019] Funding Source: FCT
This study aims to quantitatively evaluate the relationships between revenues and expenditures and their components in Coimbra Municipality during the Early Modern era. The analysis using Markov-Switching regression techniques shows that most accounting components had a significant impact on revenues and expenditures, while the lack of technological innovation in accounting recording technologies did not affect their development.
The present work aims to evaluate quantitatively the relationships between revenues and their components and expenditures and their components in the Municipality of Coimbra during the Early Modern era (1557-1836), according to the revenue and expenditure books of the Municipality of Coimbra. To examine the proposed relationships, we apply the Markov-Switching regression techniques. It is shown that the Markov-Switching analysis allows a different perception of changing regimes in municipal accounting. The analysis reveals that most accounting components had a significant impact on revenues and expenditures in the short and long term. It is argued that the lack of technological innovation that occurred at the level of accounting recording technologies had no impact on the evolution of revenue, expenditure, and its components. Our empirical results are important to motivate the debate on accounting methods, highlighting the importance of long-term dynamic analysis as opposed to short-term static views.
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