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The purpose of this study is to examine the impact of financial factors on a firm’s financial and tax reporting decisions in the context of a developing country, Sri Lanka. Relevant past studies revealed that firms struggled to achieve both financial and tax reporting goals concurrently. The present study employed quantitative methodology and collected data from audited financial statements of listed firms on the Colombo Stock Exchange from 2017 to 2022, during which tax sheltering practices were restricted under several tax rules. The study adopted a measure developed by Koh and Lee (2015) to specify the firm’s decisionmaking between financial and tax reporting by considering earnings management and tax avoidance. Logistic regression analysis was used to analyse data. In contrast to previous studies, the findings of the present study reflect that firms with more longterm debt financing are likely to engage in aggressive financial reporting. The findings also reveal that firms with a more significant financing deficit are more likely to engage in aggressive financial reporting to seem profitable during fundraising. In contrast, firms with greater access to the external capital market engage in aggressive tax reporting. The findings of this study are useful to determine the decisionmaking methods of managers, auditors, standard setters, and financial statement users in Sri Lanka.

Keywords: Financial Factors, Financial Reporting, Tax Reporting, Colombo Stock Exchange, Sri Lanka

We measured the credit linkages between the banking sectors of 14 Asian economies by constructing Euclidean distances from quarterly data on crossborder claims and liabilities for 2016-2021, thus constructing the Asian regional crossborder credit network. Then we used the network analysis method to analyse the dynamic characteristics of the network structure and study the role and importance of Chinese banking and Japanese banking. The results showed that from 2016 to 2020, the crossborder credit network structure in Asia presented the characteristics of high density and high clustering coefficient. China, Japan, Hong Kong, and Singapore are the core of the network, while peripheral economies tend to converge to the core. From the perspective of the dynamic characteristics of the network and the importance of nodes, Chinese banking played an increasingly important role as a lender of funds, which increased its importance significantly. The economies most closely linked to Chinese banking are Australia, Turkey, and India, but Hong Kong, Macao, and Taiwan are less linked than expected. Japanese banking has been a vital lender, with close links to Hong Kong, Macao, and Singapore. In addition, the banking of Singapore, Australia and Bahrain play a significant intermediary role in the Asian regional network. In particular, crossborder credit

linkages across Asian banking have weakened significantly since 2021, which may be related to the impact of the global pandemic. This paper provides policy enlightenment for developing the crossborder credit business of Chinese banking and promoting regional financial integration in Asia.

Keywords: CrossBorder Credit Network; Asian Regional Banking; CrossBorder Linkages; Network Analysis Method

JEL: F34; F36

Leveraging a comprehensive dataset spanning a significant timeframe, our study employs a multifaceted analytical approach to identify and analyse the key factors that impact the selection of specific locations for Greenfield FDIs. Building on existing literature, our research incorporates novel variables such as regional infrastructure development, government incentives, and local market characteristics to provide a nuanced understanding of the intricate dynamics at play. By utilising advanced econometric models, we aim to unravel the interplay between economic, regulatory, and geographical factors, shedding light on the nuanced considerations that guide MNCs in their strategic investment decisions. In conclusion, this research not only enriches the academic literature on FDI location choices but also provides practical implications for policymakers and industry practitioners navigating the complexities of attracting and managing Greenfield investments in emerging markets, with Vietnam serving as a compelling case study.

This paper employs the CHEER approach in order to investigate the behaviour of the nominal exchange rates of Malaysia, Singapore and Thailand. These three East Asian economies have achieved significant growth rates during the last two decades, while their competitiveness levels in the global markets have increased substantially. The sample used in this study consists of monthly observations, while a cointegration technique that allows for structural breaks in the data has been applied. In brief, the evidence indicates that the CHEER model is valid for these three countries, but only in its weakest form. In general, this finding reflects the efforts of these three countries during the last two decades to integrate with the global capital and goods markets. However, several interventions in the exchange rate regimes of these countries from the respective monetary authorities, as well as the existence of quite high nontariff barriers, prevent these economies from full integration with the global markets.

Keywords: East Asian economies, CHEER model, Structural breaks, Cointegration analysis, Markets’ integration.

JEL Classification: F15, F31, F41

This study examines the fiscal implications of an increasing oldage population in the U.S. (United States) states. Oldage dependency increases government spending on public welfare health and hospitals. It increases property taxes and charges while it has negative effects on individual and corporate income taxes. A one per cent point increase in oldage dependency decreases the state fiscal balance by $120/person. The increase in oldage dependency has implications for U.S. state governments due to the Balanced Budget Requirements. This study provides stakeholders with estimates of the detailed effects of population ageing on certain categories of public expenditures and revenues.

Keywords: Ageing population, Oldage dependency ratio, Fiscal balance, SystemGMM.

JEL codes: J14, H5, H6