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One of the noteworthy developments in the world economy is the cryptocurrency in general and the bitcoin in particular. Although several types of cryptocurrency are in operation in the current digital economy, the most prevalent is the bitcoin, which was launched formally in 2009 by an individual or group known under the pseudonym Satoshi Nakamoto. The value of bitcoin has increased to such an extend that it reached 19.7 billion US dollars by January 2, 2018 (Statista, 2018). As the bitcoin price touches a new high day by day, various terrorist organizations are using this cryptocurrency to anonymously finance their grotesque terrorist activities around the world by bypassing the surveillance mechanism of the banking system of the respective countries. Against this backdrop, this chapter aims to understand the mechanism of cryptocurrencies in general and the bitcoin in particular. Finally, it also endeavors to identify the trend of the bitcoin economy and its impact on nefarious activities in general and terrorism financing in particular. It has been revealed from the study that cryptocurrency economy has become so popular across the world that it has created an alternative virtual economy devoid of regulations from a specific country or a group of countries. By using vector error correction model (VECM), it had been observed that there exists a statistically significant long-run association between terrorist incidences and bitcoin transaction/circulation in the panel of 12 countries for 2010–2016. However, there is a huge concern over its way of operation and its unholy nexus with terrorism financing.

The Dim Sum bond market in Hong Kong, which allows China to regulate the amount of offshore yuans that flow back into the mainland, has grown steadily since its inception in 2007 and is expected to surpass in 2013 the threshold level that would attract insurers and long-term issuers to the market. Yet, the market has not matured sufficiently relative to the yuan deposit market in Hong Kong that has grown at a much faster pace on account of trade liberalization and the use of yuans in China’s international trade settlements. Even though Hong Kong has fulfilled its role as an offshore currency center for the yuan, it is being challenged by Taiwan, Singapore, and London in terms of being the premier location for the issuance of yuan-denominated bonds outside of Mainland China.

A novel approach to modeling exchange rates is presented based on a set of models distinguished by the drivers of the rate and regime duration. The models are combined into a “meta model” using model averaging and non-nested hypothesis-testing techniques. The meta model accommodates periods of stability and slowly evolving or abruptly changing regimes involving multiple drivers. Estimated meta models for five exchange rates provide a compelling characterization of their determination over the last 40 years or so, identifying “phases” during which the influences from policy and financial market responses to news succumb to equilibrating macroeconomic pressures and vice versa.

Purpose: This chapter looks specifically at the sources of economic policy uncertainty in Nigeria, and discusses their impact on the Nigerian economy while drawing implications for Africa. It identifies factors that transmit uncertainty in economic policy in Nigeria and draw implications for other African countries.

Methodology: This chapter uses a literature survey methodology to identify the sources of economic policy uncertainty in Nigeria.

Findings: The identified sources of economic policy uncertainty in Nigeria are: the frequent changes in central bank policy, unexpected changes in government policy, political interference, unexpected fall in global oil price, recession, and unethical practices.

Implications: The implication of the study is that rising economic policy uncertainty in Nigeria can have a significant effect on the Nigerian economy and for connected African countries.

Originality: Previous studies have not examined the sources of economic policy uncertainty in Nigeria.

The aim of this chapter is to assess the real exchange rate misalignments. A smooth transition autoregressive model (STAR) is used for Tunisian exchange market. This model allows us to see whether these differences are temporary or persistent over the period 1975–2012. We start by defining the exchange rate’s fundamental determinants to provide the equilibrium exchange rate value. Then, we study the observed exchange rate adjustment toward its equilibrium level. Vector autoregressive model and vector error correction model are applied to characterize the joint dynamics of variables in the long run. The results indicate a long-run relationship between variables. In order to consider the nonlinearity for better results, we will move to nonlinear smooth transition model. We found there is a high degree of exchange rate misalignment. We recognized that this difference decreases in the long run and disappears at the end.

Introduction: The Indian insurance sector has a large number of insurance companies. More than 20 companies are in the life insurance business, and nearly 35 are non-life insurers – only one public sector company among the life insurers (Life Insurance Corporation (LIC)). However, there are six public sector insurers in the property insurance division. The government policies have recently increased the foreign direct investment (FDI) share from 49% to 74%.

Purpose: The purpose of the study is based on the latest decision by the Government of India (GOI) to increase the FDI in the insurance sector, which was earlier 49% and now increased to 74%. The study will have objectives that impact change in FDI and its effect on customers’ decisions.

Methodology: This chapter is based on secondary information collected from the Insurance Regulatory and Development Authority and Articles from various journals for objectives 1 and 2. Qualitative analysis is done with the use of NVIVO software. There are primary two objectives taken under consideration in this chapter: objective 1: regulatory framework of insurance sector post-FDI change in limits by GOI and objective 2: customer awareness regarding changed limits of FDI in the insurance sector and its various factors. Fifty-four interviews were conducted, out of which a total of 40 responses have been considered for final analysis. An incomplete and unclear answer has been excluded from the study.

Findings: In the study’s findings, it was found that in accordance with the first objective, GOI changes policies according to time to time. Foreign Direct Investment (FDI) in the insurance sector recently increased by GOI Earlier, it increased in the year 2015 and recently this year, it increased by 49% again to 74%. In the second objective findings, the awareness about changes in FDI in the insurance sector respondent’s sentiments is positive and constructive. A maximum of respondents has said that they are aware of the insurance sector and the participation of various foreign international players in the insurance industry.

Inflation targeting started in 1990 and since then, many industrial and emerging market economies have adopted it. This chapter attempts to study the impact of adoption of inflation targeting on major macroeconomic outcomes across the emerging market countries, by running a panel data study from 1980 to 2018. This chapter obtains mixed results with respect to different macroeconomic indicators. The empirical results indicate that inflation targeting has been successful in bringing down inflation, inflation volatility and GDP growth rate volatility, while inconclusive results are obtained for volatility in exchange rates.

One of the highly debatable issues in the arena of international economics in recent years is whether a country should go for full capital account convertibility. In terms of the timing and process of capital account liberalization, India and China have been remarkably similar. Both started with a more or less closed capital account in the 1970s and the 1980s, in the context of a heavily state-influenced, planned economy. And in both countries, the first wave of liberalization came in the early 1990s and thus, the journey began. The objective of this chapter is to provide a critical analysis of both India and China's approach to the capital account liberalization program in the backdrop of the recent financial crises and to give an account of the theoretical issues that have arisen in international discussions on CAC and India's standpoint on this issue in particular. Second, how far is the capital account liberalization justified in the context of the recent episodes of financial crises that India and China have witnessed? Using a macroempiric model, this chapter tries to answer whether every member country in the IMF should hurriedly go for CAC or not. In addition, empirically through FMOLS, the authors pool in the “Rupee Convertibility” and “Renminbi Internationalization” along with exchange rate variation and its implications for India's and China's BoP situation (in terms of the export–import position and FDI flows) based on data from 1992 to 2017. ^{1 , 2}

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.

We empirically investigate the forecasting ability of USD-INR exchange rate volatility models by considering Google Trends data. Within a multiple regression framework, we use historical volatility and liquidity measures to build our benchmark volatility model (Chandra & Thenmozhi, 2014). Moreover, we extend Bulut (2018) to incorporate indexes for 15 keywords (price-related, income-related, and liquidity-related) from Google Trends data into our benchmark volatility model to evaluate the forecasting ability of the models. Our results indicate that Google Trends data can improve volatility prediction and that among the groups of keywords that we consider, the price-related keywords have the best forecasting ability. Incorporating data on searches for “prices” into the model produces the highest reduction in the forecasting error: a 22.75% decrease compared to the level in the benchmark model. Hence, these empirical findings indicate that Google Trends data contain information that influences exchange rate movements.