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The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic error v and a one-sided inefficiency random component u. When v or u has a nonstandard distribution, such as v follows a generalized t distribution or u has a χ2 distribution, the likelihood function can be complicated or untractable. This chapter introduces using indirect inference to estimate the SF models, where only least squares estimation is used. There is no need to derive the density or likelihood function, thus it is easier to handle a model with complicated distributions in practice. The author examines the finite sample performance of the proposed estimator and also compare it with the standard ML estimator as well as the maximum simulated likelihood (MSL) estimator using Monte Carlo simulations. The author found that the indirect inference estimator performs quite well in finite samples.

Positive-framed and negative-framed messages were delivered to examine the effect of framing on intertemporal decisions through lab experiments while holding the level of financial literacy constant. The three big questions adopted by Lusardi and Mitchell were utilized to assess the financial literacy of our subjects before they were asked to complete 20 incentivized intertemporal decisions. A small, delayed reward and a slightly bigger one were incorporated into the intertemporal decisions with a delay of 30 days. The ordinary least square (OLS) shows that the negative relationship between financial literacy and discount rates was held when the delayed reward was small. Interestingly, when the delayed reward became slightly bigger, their discount rates were reduced significantly with the negatively framed message. These findings suggest that the negatively framed message can motivate individuals to save for a greater return in the real world. Lastly, subjects with the highest level of financial literacy were not responsive to the magnitude effect, proving that a financial literacy program is essential to strengthen the individual's financial plan and reduce their discount rates in the developing country context.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

We study the potential effects of pension underfunding on corporate investment, financial constraints and improved employee bonding using 10 Pacific-Basin countries (including the United States, Australia, and eight Asian countries) at heterogeneous economic development stages and different regulatory environments. We document that corporate pensions are significantly underfunded in most countries of our sample in the period of 2001–2017, when interest rates were ultralow in most countries. In addition, firms from countries with stronger employee protection and more generous retirement benefits tend to show higher levels of underfunding in their defined benefit (DB) pension plans. To the extent of pension underfunding imposing constraints on corporate investment, we find that firms in these countries can face more constraints on investment when their pension is underfunded.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

Introduction: Why companies pay dividends and the determinants of dividend policy are considered an unresolved dividend puzzle. To reach a consensus over the puzzle, researchers must investigate the factors affecting dividend policy by incorporating all the determinants into a single research effort.

Purpose: We examine the dividend policy determinants of Sri Lankan firms, explicitly focusing on the banking, finance, and insurance (BFI) sectors.

Methodology: This study uses the quantitative approach applying the Generalized Method of Moments (GMM) system to examine the dividend policy determinants by obtaining secondary data from 51 listed BFI organisations in Sri Lanka.

Findings: The analysis disclosed that the variables of changes in revenues, firm size, liquidity, corporate tax, business risk, and profitability have a positive relationship with dividend yield, whereas investment opportunities, leverage, change in revenues, corporate tax, and firm size impact positively on the propensity to pay dividends in BFI organisations in Sri Lanka. Our findings opine that managers in the BFI industries should prioritise changing their dividend policies by paying close attention to factors, such as dividend yield, changes in revenue, firm size, liquidity, corporate tax ratio, business risk, and profitability because the dividend policy is critical to retaining current investors and luring new ones.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

This chapter examines the impact of sectoral indebtedness on GDP in Czechia, initially a low-indebted small open economy in which debt dynamics are becoming a major concern. The impact of household debt, non-financial corporation debt and public debt is analysed with the use of local projections based on instrumental variable estimations. The results show a more pronounced influence of household debt compared to non-financial corporation and government debt. Initially, increasing household debt stimulates short-run economic activity, but in the medium run, it limits household consumption and negatively affects output. This negative impact gradually turns into a positive effect in the long run. Non-financial corporation debt has a negative short- to medium-run impact but can have a small positive effect in the long run due to the prevalence of tradable industries. Public debt initially has a short-run negative impact, but then gradually becomes positive. Overall, the findings have implications for macroeconomic policies and the importance of monitoring financial stability.