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The main aim of this paper is to report on a comprehensive survey of corporate financing decision‐making process in Sri Lankan listed companies and to compare these results with those of similar studies conducted in developed markets.

The study was based on a survey questionnaire distributed among the chief executive officers (CEOs) of companies listed on the Colombo Stock Exchange, with the content of the questionnaire being based upon a review of theoretical and empirical literature in the field of finance.

The results demonstrate an adherence to a financial hierarchy, which appears to be the dominant financial policy among listed Sri Lankan companies. Corporate financing decisions seem to be influenced mostly by interest and tax considerations, while lesser weight is accorded to financial flexibility in determining the amount of funds to be raised externally through debt contracts. The evidence largely supports the propositions of the pecking order model, but also confirms some predictions found in static trade‐off theory.

Some of the most striking implications of the analysis relate to the under‐development of the local capital market, and the apparent need for an efficient financial system that spurs economic growth. An efficient capital market will in turn ensure that capital will be more easily channeled into financing investments.

This paper highlights how and why the determinants of capital structure decisions reported for developed capital markets may differ from those existing in transitional or emerging economies.

This study aims to analyze exchange rate risks and the choice of exchange rate policies in a small open economy indebted in foreign currency, incorporating the financial accelerator mechanism.

To examine discussions on the fear of floating, this study develops a dynamic stochastic general equilibrium model in which a small open economy model has an open economy financial accelerator mechanism as the external borrowing restriction. The author then compares and analyzes the macroeconomic dynamics in response to an exchange rate shock under different exchange rate systems.

The most interesting finding is that the currency peg for a foreign currency used in borrowing is more efficient than the trade-weighted currency basket policy, regardless of trade openness or trade share.

The result implies that in discussions on the fear of floating, more attention needs to be paid to exchange rate risks in finance. It also suggests that exchange rate policy used to mitigate exchange rate risks in finance stabilizes macroeconomic volatility more efficiently.

The paper provides an answer to the question: which is the more serious problem in the fear of floating and to what would the regime be anchored.

The goal of this paper is twofold. First, to examine the role of expectations in shaping agents' behaviour within an extended time frame which incorporates a prolonged harsh downturn of economic activity. Therefore, the authors allow for an indirect impact of economy-wide expectations operating via their coexistence with firms' balance sheet factors. Second, it is tested whether the behaviour of listed firms as regards to debt follows the pecking order theory.

The authors use the panel data methodology in the estimation of the financial structure models since unobservable heterogeneity is an important determinant towards the target leverage. A fixed effects estimation procedure, with robust intercepts allowed to vary across firms, was employed to examine the relationship between leverage and performance.

The findings offer evidence of patterns of pecking order behaviour and thus for the necessity of internal financing over external debt. The authors also extended the set of determinants by investigating the effect of macroeconomic conditions on the debt decision of firms. Contrary to the authors’ expectations, short-run beliefs of economic agents appear to play a negative role in leverage.

This paper contributes to the literature in a number of ways. First, following the growing literature of loan dynamics, the findings provide useful insights into corporate capital structure decisions in an economy in which businesses were almost excluded from external financing for over a decade. Second, in order to better understand corporate financing decisions, it is necessary to consider the overall economic framework in which companies and especially the listed ones operate.

The purpose of this study is to examine the impact of financial distress (FD) on investment-cash flow sensitivity (ICFS) of Indian firms.

The study uses the system generalized method of moments (GMM) technique to investigate the effect of FD on ICFS of Indian firms during the period from 2001 to 2019.

Using FD measures like Ohlson's bankruptcy method, Altman's Z-score model and financial-distress ratio, the researchers find that FD increases ICFS and negatively affects corporate investment. The researchers’ findings explain that FD increases restrictions on external financing, which makes cash flow more important for corporate investment. Additionally, the researchers find that the effects of FD on ICFS are weak (strong) for bigger and group affiliated (smaller and standalone) firms. The study’s findings are robust to several measures of FD, group affiliation and firm size.

First, the researchers find that FD affects the ICFS, therefore, financially distressed firms should have sufficient internal funds or external funds for investment. Second, lending agencies should also consider the firms' FD condition before providing funds to secure their money. Third, investors should be very careful while investing in a financially distressed firm as we find that financially distressed firms face a decline in their investment which might reduce firm profitability.

This study contributes to the existing literature by providing empirical evidence by analyzing the impact of FD on ICFS in the context of India. As per the authors’ knowledge, this is the first-ever attempt to examine the effect of FD on ICFS.

This paper aims to assess to what extent the COVID-19 shock is expected to create a debt crisis in emerging markets and developing economies (EMDEs) through two main questions: what are the main determinants of EMDEs external vulnerability? How vulnerable are EMDEs to the current COVID-19 shock compared to the global financial crisis (GFC)?

In addition to a descriptive analysis of the determinants of EMDEs external vulnerability, this paper designs two sub-indices of overindebtedness and financial fragility that capture EMDEs’ distinct characteristics. The two sub-indices together illustrate the overall external vulnerability to the current shock.

EMDEs are more vulnerable compared to the GFC era. Current debt threats arise mainly from debt architecture and the domination of volatile debt forms – primarily foreign currency-denominated bonds. Excessive fear of debt-deflation spirals after the GFC prompted EMDEs to expand their growth trajectories through a pattern of cheap private lending, loose measures and unmonitored fiscal expansion.

Conclusive post-crisis data are still unavailable.

EMDEs need to balance between temporary accommodative measures and a post-shock policy mix that prevent a deflation spiral without worsening indebtedness and financial fragility. Moreover, financial prudence in face of growing credit demand is crucial, particularly in light of the monetary expansion and injected liquidity.

The indices offer a framework for examining external vulnerability in EMDEs based on theoretical and historical revisions, IMF benchmarks and EMDEs specific debt characteristics. The indices components can be offered for empirical examination in separate future research once conclusive data become available.

This paper aims to empirically investigate the impact of bank market concentration of financial constraints on firm investment.

This analysis is based on cross-industries panel of 368 listed Pakistani non-financial firms over the period of 2001-2009. Further, the Generalized Method of Moments estimation technique has been used to estimate the dynamic panel data model.

By applying a dynamic panel analysis, it was found that small- and medium-sized enterprises (SMEs) are financially constrained in the credit market. The main finding indicates that reduction in bank concentration eases financing constraints, and this effect is more pronounced for SMEs. In addition, while testing the firm opacity in this context, results reveal that opaque firms are more financially constrained, and bank market competition is less favourable to the firms with greater opacity.

The results, first, assess the efficacy of ongoing financial reforms in Pakistan and, second, offer implications for other economies that exhibit financial development similar to that of Pakistan.

The purpose of this paper is to investigate the impact of the macroeconomic condition on investment-cash flow sensitivity (ICFS) of Indian firms and examine whether the effect of macroeconomic condition on ICFS depends on the size and group affiliation of the firm.

An empirical investigation is conducted using a dynamic panel data model or more specifically system generalized method of moments (GMM) estimation technique.

Empirical findings postulate that the availability of cash flow influences the investment decisions which depicts that Indian manufacturing firms are internally as well as externally financially constrained. This study finds that good economic condition (period of high GDP growth rate) reduces the ICFS, although this effect is stronger for small-sized and standalone firms than the large-sized and business group affiliated firms. The authors find that macroeconomic condition has a positive and significant effect on investment decisions.

This study has considered only the non-financial sector. The future research could explore the effect of macroeconomic condition on ICFS might be affected by firm other characteristics such as firm age and firm capital structure.

The government should provide loan on the low rate to the small-sized firms and standalone firms because it is very difficult for these firms to finance their investment during the bad economic condition (period of low high GDP growth rate).

This study contributes to the existing literature by analyzing the impact of the macroeconomic condition on ICFS as well as investment decisions of the Indian manufacturing firms, which is an unexplored issue from an emerging market perspective. To the best of my knowledge, this is a first-ever study which explores the effect of macroeconomic condition on investment decisions with respect to business group affiliation and firm size.

The purpose of this study is to find the relationships among the high- and new-technology enterprise (HNTE) identification policy, firm’s total factor productivity (TFP) and the marketization process by using data obtained from China manufacturing firms.

Propensity matching score – difference-in-difference modeling are used to investigate the relationships among the HNTE identification policy, firm’s TFP and the marketization process. In addition, the complex relations between policy and firm’s TFP, including in the proposed model, are assessed in detail through the mediation analysis.

The results show that the HNTE identification policy can promote firm’s TFP, but its effect depends on the marketization process. The transmission path of HNTE identification policy to promote enterprise productivity lies in the optimization of incentive mechanism, including the improvement of enterprise labor productivity, the reduction of income tax burden and cost and the reduction of financing constraints. In industries and regions with more effective market mechanism, as well as industries with more intense market competition, the productivity promotion effect of the HNTE identification policy is stronger. In industries and regions with low degree of marketization, as well as industries with low degree of market competition, the productivity promotion effect brought by the improvement of incentive mechanism is distorted, which actually inhibit the promotion of enterprises’ TFP.

The study confirms that the HNTE identification policy plays an important role in enhancing the TFP of China’s manufacturing firm. Policy makers can adopt industrial policy in the key industries and technology areas that are meaningful but market failure. Furthermore, it demonstrates that the effect of the HNTE identification policy largely depends on the marketization process. These finding imply that when formulating an industrial policy, the marketization process of the industry and region should be taken into account.

The paper analyzes the relationship among the HNTE identification policy, firm’s TFP and the marketization process. Panel data are used to discuss the mechanism of HNTE identification policy affecting firm’s TFP. The paper also reveals the effect of the marketization process on the effectiveness of the HNTE identification policy.

The purpose of this study is to examine the impact of financial and technical education of chief executive officer (CEO) on investment–cash flow sensitivity (ICFS) of Indian manufacturing firms.

The study uses the dynamic panel data model and more specifically, the system-generalized method of moments (GMM) technique to investigate the effect of CEOs' education on ICFS of Indian manufacturing firms during the period 1998–1999 to 2016–2017.

The study shows that financial (technical) education of CEOs does (not) affect ICFS. The results explain that the role of the CEO's education in ICFS is highly significant during the crisis period. The robustness test depicts that the influence of financial education on ICFS is less (more) for group-affiliated and large-sized firms (stand-alone and small-sized firms). Further, the CEO's education is significantly associated with corporate investment decisions.

Due to the unavailability of the CEO's compensation data for the selected sample, future research could explore the impact of CEO's education with respect to CEO's compensation on ICFS.

First, the authors find that financially educated CEOs affect ICFS; therefore, firms should take care of CEO's education during recruitment of CEOs. Second, lending agencies should also consider the educational background of the CEO before approval of funding to make it safe. Third, investors should keep in mind the educational background of the CEO for the growth of their investment as it may be easier for financially educated CEOs to borrow from the market at the time of requirement.

This study contributes to the existing literature by providing empirical evidence through analyzing the impact of a CEO's education on ICFS in the context of India. This study is very unique in itself as it uses the sample of manufacturing sectors of India, which are growing very fast and attracting global investors to create a global hub of manufacturing in India. This study also considers different types of education such as financial and technical education of CEOs in the context of a developing economy like India. This study made its findings robust across company characteristics and periods based on the financial crisis.

The aim of this paper is to study the impact of the questions and answers (Q&A) between investors and enterprises from the China stock exchange investor interactive platforms on the total factor productivity (TFP) of enterprises.

To show how the interaction influences the TFP of enterprises, the authors select Q&A records from the interactive platforms related to production, R&D and technology through the Latent Dirichlet Allocation (LDA) topic model and choose A-share listed companies from 2010 to 2019 in China as a sample. To treat the data and test the proposed hypothesis, the authors applied OLS regression and endogeneity testing methods, such as the entropy balance test, Heckman two-stage model and the two-stage least squares regression.

This paper finds that interaction between investors and enterprises is positively correlated with TFP, and that improvements in content length and the timeliness of response can promote TFP. Interactive behavior mainly improves the TFP of enterprises by alleviating financing constraints and encouraging enterprises to increase R&D investment. This positive effect is more pronounced in companies with higher agency costs, non-high-tech companies and companies not supported by industrial policy.

The novelty of the research stands in the application of Python's LDA topic model to screen out Q&A records that are directly related to TFP, such as production, R&D, technology, etc., and measures the degree of information interaction between investors and enterprises from multiple dimensions, such as interaction frequency, content length and the timeliness of response.