scholarly journals Tracking Greenfield FDI During the COVID-19 Pandemic: Analysis by Sectors

2021 ◽  
pp. 001573252110313
Author(s):  
Nadia Doytch ◽  
Nishant Yonzan ◽  
Ketan Reddy ◽  
Filip De Beule
Keyword(s):  
Financial Crisis ◽  
Global Financial Crisis ◽  
Global Scale ◽  
Remote Work ◽  
Data Set ◽  
Jel Codes ◽  
Long Run ◽  
Dramatic Decline ◽  
The Global Financial Crisis ◽  
Stability And Resilience

We study the trends and fluctuations in greenfield foreign direct investment (GFDI) during the first wave of the COVID-19 pandemic crisis on a global scale. We analyse the data of a data set of GFDI provided by fDi Markets ( Financial Times) to understand the contraction of GFDI during the first three quarters of the year 2020, taking into account the sector of the investment and the host and home country. We analyse both the long-run trends and the quarter-over-quarter changes in GFDI to capture its fluctuations before and during the first wave of the COVID-19 crisis and the 2008 global financial crisis. Our findings cast light on which countries’ and industries’ GFDIs were most affected by the pandemic crisis and draw a comparison to the global financial crisis. To our surprise, many services industries have shown unexpected resilience of GFDI due to the flexibility for remote work. On the contrary, GFDI in the manufacturing industries, as well as the extractives and the utility industries, has shown a dramatic decline during the pandemic. These contractions raise questions of stability and resilience of the global supply chains these industries are a part of. JEL Codes: F21

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

ASYMMETRIC IMPACT OF EXCHANGE RATE CHANGES ON THE TRADE BALANCE: DOES GLOBAL FINANCIAL CRISIS MATTER?

2018 ◽  
Vol 13 (04) ◽  
pp. 1850015 ◽  
Author(s):  
BISHARAT HUSSAIN CHANG ◽  
SURESH KUMAR OAD RAJPUT ◽  
NIAZ HUSSAIN GHUMRO
Keyword(s):  
Exchange Rate ◽  
Financial Crisis ◽  
Trade Balance ◽  
Global Financial Crisis ◽  
Sample Period ◽  
Asymmetric Effect ◽  
Distributed Lag ◽  
Long Run ◽  
Exchange Rate Changes ◽  
The Global Financial Crisis

Recent studies have been mainly focusing on whether exchange rate changes have a symmetric or asymmetric effect on the trade balance. We revisit this question in the context of US and further extend previous studies by determining whether the relationship between these underlying variables change as a result of the global financial crisis. We use both linear autoregressive distributed lag (ARDL) and non-linear ARDL models for the whole sample period as well as in the pre- and post-crisis periods. Findings suggest that exchange rate changes have an asymmetric effect on the trade balance; however, the asymmetric behavior of the underlying variables change as a result of the financial crisis. In the short run, exchange rate asymmetrically affects trade balance in the post-crisis period only. In the long run, there is an asymmetric effect for all sample periods, where only the devaluation of currency significantly affects the trade balance when the whole sample period is selected. On the other hand, in pre- and post-crisis periods, only appreciation of currency significantly affects the trade balance. This study indicates that determining the asymmetric relationship without considering the global financial crisis may lead to spurious results.

scholarly journals The Integrated Measuring of Working Capital Management Efficiency on Financial Performance in Indonesia Stock Exchange

2015 ◽  
Vol 7 (3) ◽  
pp. 26-33
Author(s):  
Petrus Emanuel De ◽  
Rina Indiastuti . ◽  
Erie Febrian .
Keyword(s):  
Financial Crisis ◽  
Financial Performance ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Chief Financial Officers ◽  
Working Capital ◽  
Data Set ◽  
Crisis Period ◽  
Cash Conversion Cycle ◽  
The Global Financial Crisis

The purpose of this study is to determine the differences effect of working capital efficiency on financial performance during periods of crisis. The measurement is made during the crisis compared to the entire period of observation by using cash conversion cycle (CCC) and working capital policy (both investment policy and financing policy) on the profitability (by return on assets) and market value (by Tobin’s Q). Using all annual financial data of 104 manufacturing firms listed in Indonesia Stock Exchange (IDX) over the period 2005-2013. These periods include the global financial crisis. The panel data set was developed for nine years, which produced 936 firms-years observations. This study uses multivariate regression models with hierarchical regression analysis approach. This approach uses the global financial crisis period as a dummy variable. The results showed that there were differences in the effect of the cash conversion cycle (and its components) and working capital policy on profitability during the crisis period compared to the whole period. In contrast, no differences effect the cash conversion cycle (and its components) and working capital policy on the value of the company in the crisis period compared to the whole period. The manufacturing industries do not apply the efficiency in the management of working capital. The global financial crisis tends the companies to change their working capital policy more efficiently. The researcher can extend this study by doing a qualitative research how to chief financial officers invest and finance day-by-day operation.

scholarly journals Inefficiency patterns in family-owned banks in Bangladesh

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mette Asmild ◽  
Dorte Kronborg ◽  
Tasmina Mahbub ◽  
Kent Matthews
Keyword(s):  
Financial Crisis ◽  
Business Models ◽  
Global Financial Crisis ◽  
Time Window ◽  
Management Practice ◽  
Data Set ◽  
Content Type ◽  
Empirical Results ◽  
The Difference ◽  
The Global Financial Crisis

PurposeMulti-directional efficiency analysis (MEA) is an alternative methodology to data envelopment analysis (DEA) that investigates the improvement potentials in each input and output dimension and identifies a benchmark proportional to these potential improvements. This results in a more nuanced picture of the sources of the inefficiency providing opportunities for additional conclusions about which variables the inefficiency is mainly located on. MEA provides insights into not only the level of the inefficiency but also the patterns within the inefficiency, i.e. its sources and location. This paper applies this methodology to Bangladeshi banks to understand the differences in the inefficiency patterns between different subgroups.Design/methodology/approachThis paper analyses the difference in the pattern of inefficiency between the older family-dominated banks and the newer non-family-owned banks in Bangladesh using the recently developed MEAs technology, which enables analysis of patterns within inefficiencies rather than only levels of (in)efficiency. The empirical results show that whilst there are few significant differences in the levels of variable-specific efficiency scores between the two subgroups, there are clearer differences on the inefficiency contributions from particular outputs in most of the study period and also on most variables in the time window of 2007–2009. This finding provides clues to differences in business models and management practice between the two types of banks in Bangladesh.FindingsThe empirical results show that whilst there are few significant differences in the levels of variable-specific efficiency scores between the two subgroups (older family-dominated banks and the newer non-family-owned banks), there are clearer differences on the inefficiency contributions from particular outputs in most of the study period and also on most variables in the time window of 2007–2009, during the Global Financial Crisis (GFCs). This finding provides clues to differences in business models and management practice between the two types of banks in Bangladesh.Practical implicationsDEA is a conventional tool for benchmarking in management science. However, conventional benchmarking exercises based on DEA do not reveal significant differences in the sources of inefficiency that show differences in business models. While DEA remains the most utilized technique in the efficiency literature, we think that a more flexible and deeper analysis requires something like MEA.Originality/valueThe contribution is twofold. First, examination of performances of family-owned firms is a well-established but analysis of performances of family-dominated banks is relative scarce. Secondly, isolating the sources of inefficiency which differs between types of banks even if there is no difference in inefficiency levels is absolutely new for a complete data set of conventional banks in Bangladesh. It turns out that there are few (significant) differences between the groups in terms of the inefficiency levels, whereas clear patterns emerge in terms of differences in inefficiency contributions between family-dominated and non-family-owned banks, during the Global Financial Crisis

scholarly journals An Early Warning Signal (EWS) Model for Predicting Financial Crisis in Emerging African Economies

2020 ◽  
Vol 12 (1) ◽  
pp. 101
Author(s):  
Kehinde Damilola Ilesanmi ◽  
Devi Datt Tewari
Keyword(s):  
Financial Crisis ◽  
Early Warning ◽  
Financial Stability ◽  
Global Financial Crisis ◽  
Warning Signal ◽  
Multinomial Logit Model ◽  
Set Covering ◽  
Data Set ◽  
Early Warning Signal ◽  
The Global Financial Crisis

The devastating effects of the global financial crisis (GFC) have led to a renewed, global interest in the development of an early warning signal (EWS) model. The purpose of the EWS model is to alert policymakers and other stakeholders to the possibility of the occurrence of a crisis. This study estimates a EWS model for predicting the financial crisis in four emerging African economies using a multinomial logit model and a data set covering the period of January 1980 to December 2017. The result of the study suggests that emerging African economies are more likely to face financial crisis as debts continue to rise without a corresponding capacity to withstand capital flow reversal as well as excessive foreign exchange risk due to currency exposure. The result further indicates that rising debt exposure raises the likelihood of the economies remaining in a state of crisis. This result confirms the significance of a financial stability framework that addresses the issues confronting Africa’s emerging economies such as rising debt profile, liquidity and currency risk exposure.

Corporate Change After the Global Financial Crisis

2020 ◽  
Vol 53 (2) ◽  
pp. 245-271
Author(s):  
Ivo Arnold
Keyword(s):  
Financial Crisis ◽  
Interest Rates ◽  
Business Model ◽  
Global Financial Crisis ◽  
Jel Classification ◽  
Long Run ◽  
Corporate Change ◽  
History Of ◽  
Using Data ◽  
The Global Financial Crisis

Abstract This paper examines the strategic response of the Dutch bank ING to the global financial crisis. Prior to the crisis, ING was a prominent global exponent of direct banking, using the so-called pure play internet (PPI) business model. PPI banking is a hybrid business model that combines features of relationship and transaction banking. Downsides of this business model are that it may lead to overexposure in securities and that it may attract savers that have an above-average sensitivity to interest rates or risk. Using data on the geographical activities of ING, the timeline of relevant events in the history of ING and strategy statements of ING management, we examine how ING has responded to the strategic challenges of the crisis. We conclude that PPI banking should be viewed more as a market penetration strategy than as a full-blown business model that is tenable in the long run. JEL Classification: G01, G21

Volatility of Malaysian conventional and Islamic indices: does financial crisis matter?

2020 ◽  
Vol 11 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Muhamad Abduh
Keyword(s):  
Financial Crisis ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Composite Index ◽  
Least Square ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
The Global Financial Crisis ◽  
The Impact

Purpose This study aims to investigate the volatility of conventional and Islamic indices and to explore the impact of the global financial crisis toward the volatility of both markets in Malaysia. Design/methodology/approach The data consist of financial times stock exchange group (FTSE) Bursa Malaysia Kuala Lumpur Composite Index and FTSE Bursa Malaysia Hijrah-Shari‘ah Index covering the period January 2008-October 2014. Generalized autoregressive conditional heteroskedasticity is used to find the volatility of the two markets and an ordinary least square model is then used to investigate the impact of the crisis toward the volatility of those markets. Findings Interestingly, the result shows that Islamic index is less volatile during the crisis compared to the conventional index. Furthermore, the crisis is proven to significantly affect the volatility of conventional index in the short run and Islamic index in the long run. Originality/value This study explores the volatility–financial crisis nexus, especially for the Islamic financial markets, which to the best of the author’s knowledge, is still lacking empirical research which may improve the understanding upon this issue.

scholarly journals Monetary policy responses to the global financial crisis: A case study of Egypt

2011 ◽  
Vol 7 (3) ◽  
pp. 65-78
Author(s):  
Monal Abdel-Baki
Keyword(s):  
Monetary Policy ◽  
Financial Crisis ◽  
Interest Rates ◽  
Global Financial Crisis ◽  
Reserve Requirements ◽  
Long Run ◽  
Dynamic Stochastic ◽  
The Global Financial Crisis ◽  
The Arab Spring

Among the triggers of the Arab Spring are the declining living standards of the middle and lower income groups. Undoubtedly, the global financial crisis (GFC) is to be partially blamed for weakening the economies of these nations. But was monetary policy ineffective in combating inflation and reducing the meltdown? This paper employs a dynamic stochastic general equilibrium model to assess the effectiveness of the monetary policy in the wake of the GFC. Egypt is selected as a case study due to its overdependence on imported food, the prices of which are relentlessly soaring. The results of the study reveal that the ideal operating targets for the Central Bank of Egypt are the overnight rate and legal reserve requirements. Interest rates are more suitable for long-run impact on the ultimate goals of growth, price stability and job creation. The study culminates in designing a framework to enhance central bankers’ political independence and transparency, which is imperative for nations with high levels of corruption. The study is not only informative to the new Egyptian policymakers, but also to other developing and emerging economies that suffer from symptoms of chronic inflation and looming socio-political turmoil.

Identification of systemically important banks in India using SRISK

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juhi Gupta ◽  
Smita Kashiramka
Keyword(s):  
Systemic Risk ◽  
Banking Sector ◽  
Global Financial Crisis ◽  
Balance Sheet ◽  
Data Set ◽  
Content Type ◽  
Long Run ◽  
Marginal Expected Shortfall ◽  
The Global Financial Crisis ◽  
Systemically Important Banks

Purpose Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019. Design/methodology/approach In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk. Findings This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank. Originality/value Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

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