Comparative Analysis of Trade and Finance in Emerging Economies: Volume 31

This study examined the effect of good stewardship on agency costs and firm performance. The panel data analysis with the Panel Corrected Standard Errors (PCSEs) estimator was employed to analyze the effect of good stewardship on agency cost and the impact of good stewardship on the performance of 37 South African firms from 2007 to 2016. The findings of this study reveal that good stewardship has a significant positive effect on agency costs as well as firm performance, implying that the promotion of good stewardship should be accompanied by suitable strategies to manage additional agency costs.

The establishment of a currency union is a topical issue in the West African Monetary Zone (WAMZ). The subject of currency union formation needs to be reassessed in light of the recent efforts towards the economic integration of west African countries. This study employs the Markov Switching Model (MSM) to determine whether a currency union in WAMZ is feasible. The study analyzes the regime switching behavior in WAMZ countries’ foreign exchange markets before and after the formation of the union. The contribution of this study is two-fold. First, the study accounts for the success or otherwise of the latest efforts to integrate the fiscal and monetary strategies in the zone. Secondly, the study contributes to the literature on the currency union literature in WAMZ by using Markov Switching Model (MSM) to generate novel results. The results of the study revealed that prior to the WAMZ formation, the real exchange rates of member states were more divergent. In contrast, a growing but marginal, convergence was observed after the formation of the zone amongst four (Nigeria, Sierra Leone, Gambia, and Liberia) of the six countries. The authors conclude that while WAMZ is on course for establishing a currency union, their monetary authorities must work together, particularly with Ghana and Liberia, to synchronize their policy efforts, and policy makers must implement policies to strengthen harmonious trade interactions.

This study groups mutual funds using k-means clustering analysis and compares the k-means clustering process with existing clustering techniques using mutual fund data for equity funds, general fixed-income funds, and balanced open-end mutual funds rated by the Association of Investment Management Companies. Data are from January 2016 to December 2020 for 60 months and includes information on prices, risks, and investment policies. The sample for this study comprises 173 funds from 10 asset management companies with the highest net assets. The tool used for analysis is the k-means technique using a statistical package set for k = 3. The funds can be divided into three groups: Group 1 has 5 mutual funds (2.89%), Group 2 has 24 mutual funds (13.87%), and Group 3 has a total of 144 mutual funds (83.24%). In Group 1, four of the five mutual funds are equity funds with a track record of beating the market, and fund managers have good market timing skills. Moreover, the efficiency of fund grouping using the k-means technique was compared with the existing grouping with close results at 57.23%. This work provides a methodology to obtain a better categorization of mutual funds by using k-means clustering, allowing the investors to know how mutual funds are. This categorization is very useful for improving the formulation of mutual funds, with the goal of further optimizing investment.

This study aims to investigate whether the zero-investment portfolio strategy generates higher excess returns for all listed companies in the Stock Exchange of Thailand (SET) or ESG100 stocks. The study period is from January 2016 to December 2020, a total of 60 months. The dividend yield is employed for categorizing the stock into value and growth stocks. The strategy of buying value stocks and short-selling growth stocks is then applied. The results show that investing using the zero-investment portfolio strategy can generate higher returns in an investment portfolio that consists of ESG100 stocks than in an investment portfolio that consists of all stocks in the SET. The optimal holding periods for investing in portfolios that consist of stocks in the SET are 6 months, 9 months, and 12 months, and the optimal holding periods for a portfolio that consists of ESG100 stocks is 6 months. To explain excess returns of stocks in the SET, the Fama and French (2015) five-factor model is employed. There is no relation between risk factors and excess returns for the holding period of 6 months and 12 months. However, excess return is found to have a negative relation with the market risk premium factor for a 9-month holding period. The excess returns of ESG100 stocks are also inversely correlated with investment factors for a holding period of 6 months.

This study tests the influence of Big Five Personality Traits (BFPTs) and demographic factors on Facebook behavior of Posting, Feature Usage, and Making Friends in India, home to the highest number of Facebook users in the world. Gen-Z is the demographic most involved in social media, thus this age group’s behavior can be most accurately gauged from Facebook habits and so it forms the basis of this study. Facebook behavior identified in this study was the outcome of an elicitation study conducted among university students. The sample survey consisted of 290 Facebook users aged between 17 and 24 years. The chapter uses factor analysis and structural equation modeling (SEM) for data analysis. Results revealed that extroverts and those open to experiences would post more. Meanwhile, the conscientious were less inclined to use features such as emoticons while those more agreeable embraced them. Women and those more neurotic would not befriend strangers. Also, posting and feature usage increased with user age. Study results highlight the potential of analyzing Facebook behavior to gauge personalities, which could benefit recruiters and marketers. Academically, this is the first study related to India where a scale for Facebook behavior is developed (namely Posting, Feature Usage, and Making Friends) and then validated for future research work.

In the Lao People’s Democratic Republic (Lao PRD), the services sector accounts for more than 41% of GDP and more than 80% of total trade (World Bank, 2021). Empirical studies show that most of the services trade occurs in the travel and tourism sectors, accounting for more than 50% of the total services trade in the Lao PDR. The services sector also plays an essential role in the Lao PDR’s wholesale and retail sectors, which employ the most significant number of people across all services sectors. The services trade balance was in a surplus between 1997 and 2011, though in 2012, it entered a significant deficit that continues to the present. This study investigates the link between services trade and economic growth in the Lao PDR, building on a recent analysis of the services trade in various economic and economic growth. The authors use econometric methods such as the autoregressive distributed lag (ARDL) bound test and the Granger causality test to analyze time-series data for the Lao PDR from 1990 to 2019. The econometric results demonstrate the long-run relationship between economic growth and variables related to the services trade. This indicates the government and policymakers of the Lao PDR should invest in infrastructure, particularly in trade facilitation and the liberalization of the services sector, to facilitate the acceleration of economic growth.

Portfolio selection has been extensively studied in field of business and economics. Many methods have been developed to construct a well-diversified portfolio that is expected to result in higher investment return with minimum risk. One of the most foundational works contributing to modern portfolio selection is the Markowitz mean variance optimization approach. The Markowitz approach heavily relies on past stock price performance, both in term of correlation structure and the return, to predict the future outcome. We constructed both Markowitz portfolio and the Fundamental Indexing portfolio independently, then using Buffet ratio to weight, combined both portfolio into a newly blended portfolio, test out-of-sample the new portfolio in term of return and then compare it to the Indonesian LQ45 benchmark index. The result shows that the new combined portfolio returns annually on average 43.89% higher than the benchmark index.

This research aims to determine the factors that can affect financial literacy in Micro, Small, and Medium Enterprises (MSMEs), especially regarding loans and budgeting. Data are obtained using a survey of owners or managers of MSMEs, which is then processed using multiple regression. This research contributes toward a deeper understanding of MSMEs’ financial literacy determinants, specifically regarding loans and budgeting, in a pandemic situation that differs from ordinary circumstances and encourages many financial activities to utilize technology. The research results indicate the role of Financial Education, Money Attitude, and Financial Socialization Agents in determining MSMEs’ financial knowledge and skills regarding loans and budgets.

The practice of company development in the twenty-first century diagnoses the appearance of a number of features in the processes of diffusion of innovations. The point is that in the course of the spread of innovative technologies, there is not so much an accelerated displacement of traditional technical systems as their absorption, i.e., a relatively slow replacement of existing equipment with new innovative systems. This phenomenon goes beyond the traditional theory of evolutionary economics and needs special research. This chapter attempts to explain the essence of the occurrence of this phenomenon. The authors are talking about the need for exponential growth of investments in the implementation of innovative projects for the development of technical systems, which a significant number of production organizations are unable to implement. As a result, hybrid technical systems are being formed, in which traditional and innovative technical systems are interfaced. The formation and maintenance of such systems requires unique solutions in the development of R&D and places high demands on the development of the organization’s human capital.

The main objectives of this study were to examine the Lao People’s Democratic Republic (PDR) agricultural exports to the People’s Republic of China (PRC), the tuning of the Agricultural Commodity Frequency Index (ACFI) to non-tariff measures (NTMs), and the coverage ratio of goods to determine the effects of the PRC’s NTMs on Lao PDR’s agricultural exports using a demand export model with a fixed-effect method. The authors found that Lao PDR’s agricultural exports to the PRC increased by an average of 46.91% from 2013 to 2020, covering a total of 51 product codes, comprising six of the most valuable product types (i.e., bananas, corn, tapioca flour, watermelon, sticky rice, and sweet potato) given priority by the PRC. Additionally, from 2013 to 2020, the average ACFI concentration with NTMs was 10.08%, and the average coverage ratio for goods was 14.43%. The results of statistical significance testing at 1% suggest that three factors demonstrated the most significant impact on value: agricultural products facing NTMs in the form of sanitary and phytosanitary (SPS) measures and technical barriers to trade (TBTs), treaties with priority conditions regarding SPSs and priorities for agricultural products, and the real gross domestic product (GDP) of the PRC. Furthermore, a PRC GDP increase of 1% resulted in a 3.1235% impact on Lao PDR exports.

Starting in March 2020, Indonesia had the COVID-19 pandemic. Furthermore, this situation has decreased the utilization of highways due to complying with the government regulation, including work from home and large-scale social restrictions to reduce the spreading the corona virus. There are three highway companies listed on Indonesia Stock Exchange such as CMNP, META, and JSMR. On the other hand, the research about the financial performance and the financial distress prediction in Highways sector, especially in Indonesia is not available during the COVID-19 pandemic. This research is aimed to evaluate the financial distress by the Zmijewski model with two criterions: bankrupt and non-bankrupt zone and the financial performance by state-owned enterprise (SOE) rating with three criterions: healthy, less healthy, and unhealthy condition. The period of research is Q1 2019 – Q1 2020 as the period before the COVID-19 pandemic and Q2 2020 – Q2 2021 as the period during the COVID-19 pandemic. The study concludes that all highway companies was in non-bankrupt zone by the Zmijewski model for both before and during the COVID-19 pandemic. In addition, based on SOE rating on average for the period before the COVID-19 pandemic, CMNP, META, and JSMR achieved rating consecutively BBB, BBB, and BB. Meanwhile, on average, for the period during the COVID-19 pandemic, CMNP, META, and JSMR achieved ratings consecutively BB, BB, and B.

This chapter shows how to identify the characteristics of borrowers that are part of a credit scoring model. The credit risk scoring model is an important tool for evaluating credit risk associated with customer characteristics that affect defaults. This research was conducted at a financial institution, a subsidiary of a commercial bank in Indonesia, to answer the challenge of determining the feasibility of providing financing quickly and accurately. This model uses a logistic regression method based on customer data with indicators of demographic characteristics, assets, occupations, and financing payments. This study identifies nine variables that meet the goodness of fit criteria, which consist of WOE, IV, and p-value. The nine variables can be used as predictors of default probability: type of work, work experience, net finance value, tenor, car brand, asset price, percentage of down payment (DP), interest, and income. The results of the study form a risk assessment model to identify variables that have a significant effect on the probability of default.

This study aims to determine the contribution of capital expenditure from industries on the employment rate in West Java, Indonesia. Capital expenditure from the private sector is always assumed to positively affect the employment rate because the number of investment realization signifies workforce requirement; however, with rapid technological advancement and changes in the social and business environment, does it still reflect the real situation? The main source of data is taken from the Investment Activity Report or Laporan Kegiatan Penanaman Modal (LKPM), which is a report on the growth of a company’s investment realization and the issues encountered by businesses that are submitted regularly to Badan Koordinasi Penanaman Modal/Kementerian Investasi (Indonesia Investment Coordinating Board/Ministry of Investment) or BKPM. LKPM submission is regulated by BKPM Regulation 7/2018, and the purpose of this study is to observe investment realization growth and foster communication between BKPM and businesses. This study is carried out by evaluating LKPM data from companies in the manufacturing industry that conduct their business in West Java Province and comparing it against the employment rate in West Java Province to find out the effects of investment realization on the employment rate. This study finds that there is an effect of all independent variables on the dependent variable. If the conclusion is drawn, there is an influence between the workforce on the investment amount in 2018.

This research investigates the influence of bank loans on Chinese listed companies’ performance by collecting data on bank loan amounts and indicators used to measure performance, such as return on assets (ROA) and Tobin’s Q, semiannually from 2015 to 2020. Pooling panel regression models are employed to determine the relationship between firms’ performance and their amount of bank loans. This study contributes to the literature by controlling for additional bank loan characteristics and comparing the relevance between bank loans and bond issuance. The authors also find that the relationship between firm performance and bank loans shows a nonlinear concave relationship, suggesting the negative impact is more severe in the high loan-to-asset region. The subsample after 2018 shows a significantly positive relationship, indicating that the impact of COVID-19 might alter the prevalent relationship. In addition, short-term debt has a more noticeable negative impact on firm performance than long-term debt. Both results become weaker after COVID-19. This chapter can help listed companies to trade off using long-term or short-term bank loans as their debt financing methods and approach a better capital structure.

In view of the significant changes in the capital structure of China’s real estate industry and enterprises in recent years, this chapter employs financial indicators and the linear regression function to analyze the relationship between corporate debt ratio and the performance of 111 A-share listed real estate enterprises in China. This study finds that the corporate debt ratio of China’s real estate enterprises in the past decade has a significant negative impact on enterprises’ performance. The study also finds that among China’s real estate companies, the corporate debt ratio has a more significant negative impact on the performance of non-state-owned enterprises than state-owned enterprises. In addition, a high debt ratio has a more significant negative impact on return on equity (ROE) than on return on assets (ROA). However, when Tobin’s Q serves as a proxy for firm performance, the negative impact of the corporate debt ratio becomes insignificant in the presence of the firm size factor. The research results of this chapter can provide some reference for subsequent policy-making and investment decisions in the Chinese real estate market.