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Why did the United States experience a housing and mortgage market boom and bust in the 2000s, while analogous Canadian markets were relatively stable? Both US and Canadian markets are replete with government interventions. In this paper, I account for the US and Canada’s different experiences by arguing that government interventions are not created equal. Some government interventions prevent market participants from pursuing actions that ex ante are reckoned beneficial. Alternatively, other interventions lead to the pursuit of actions that turn out to be costly ex post. It is the latter type that we expect to manifest in crises. The US case is one where government interventions in the mortgage markets led to actions that appeared ex ante beneficial but were revealed to be costly ex post. Alternatively, Canada’s mortgage market was and remains essentially a regulated oligopoly. Regulatory capture makes for a sclerotic market that likely imposes costs on Canadian borrowers in the forms of limited financing options and higher interest rates. However, this sclerosis also lends itself to stability. This market structure made the Canadian mortgage market relatively insusceptible to a bubble.

This chapter aims to improve the mechanisms of economic integration between Russia and Cuba. The methodology used by the author in this chapter is mainly composed of the method of historical-comparative, inductive, and analytical-synthetic analysis. The author used the existing information on the internet and other analyzed references. Additionally, the author qualitatively analyzed the opinions of various experts and drew conclusions. Regional integration is examined conceptually as a basis for a better understanding of integration processes. The research provides historical data after including Cuba in the Council for Mutual Economic Assistance (CMEA), considering this structure as the first one with characteristics of an economic integration structure. Next, the author considered the post-Soviet stage until the present. Statistical data according to the Observatory of Economic Complexity (OEC) summary are provided. These data correspond to the periods from 2018 to 2021 and show the statistics of exports, imports, and other important indicators between the two countries. Based on the analysis, it is necessary to update the integration mechanisms to reduce tariff rates, promote free trade between the two countries, and increase the participation of Russian companies in the Mariel Special Development Zone (ZED Mariel), Havana, Cuba.

The article discusses the current state and problems of increasing the export potential of small and medium-sized enterprises in the Republic of Kazakhstan in the context of the country's regions.

The article aims to identify promising sectors of the economy for small and medium-sized enterprises with export potential to ensure the post-crisis recovery of the national economy and its growth.

Introduction: Big data is that disruptive force that affects businesses, industries, and the economy. In 2021, insurance analytics will include more than simply analysing statistics. According to current trends, new insurance big data analytics (BDA) methods will enable firms to do more with their data. The insurance business has traditionally been conservative, but adopting new technology is no longer only a current trend; it must be competitive. Big data technologies aid in processing a huge amount of data, improve workflow efficiency, and lower operating costs.

Purpose: Some of the most recent developments in big data for insurance and how insurers may use the information to stay ahead of their competitors are discussed in this chapter. This chapter’s prime purpose is to analyse how artificial intelligence (AI), blockchain, and mobile technology change the outlook and working of the insurance sector.

Methodology: To achieve our research purpose, we analyse case studies and literature that emphasise how BDA revolutionises the insurance market. For this purpose, various articles and studies on BDA in the insurance market will be selected and studied.

Findings: From the analysis, we find that the use of big data in the insurance business is growing. The development of BDA has proven to be a game-changing technology in insurance, with a slew of benefits. The insurance sector is now grappling with the risks and opportunities that modern technology presents. Big data offers opportunities that every company must avail of. We can safely argue that big data has transformed the insurance sector for the better. The BDA’s consequences have enabled insurers to target clients more accurately. This chapter highlights that new tools and technologies of big data in the insurance market are increasing. AI is emerging as a powerful technology that can alter the entire insurance value stream. The transmission of any type of digital proof for underwriting, including the use of digital health data, might be a blockchain use case (electronic health record (EHR)). As digital forensics becomes easier to include in underwriting, it must expect price and product design changes in the future. In the future, the internet of things (IoT) and AI will combine to automate insurance processes, causing our sector to transform dramatically. We highlight that these technologies transformed insurance practices and revolutionalised the insurance market.

Introduction: China released an action plan in 2015 to foster the growth of big data, demonstrating that big data development has become an essential and inescapable choice for stabilising growth, advancing reform, adapting structures, helping people’s livelihoods, and supporting government modernisation. The rudimentary ecology of the big data sector, combined with a favourable policy climate, creates ideal conditions for developing big data in China. The use of big data, on the other hand, has steadily shifted from a theory to reality, thanks to the explosive increase of data resources and the rise of specialised big data firms. Globally, the insurance industry is undergoing a technological revolution. The internet, mobile networks, social networks, cloud computing, and big data are all examples of digital technologies that progressively influence daily business operations and will usher in a golden era for the insurance industry.

Purpose: This chapter aims to understand the use of big data in the insurance industry innovation and the challenges insurance companies face. This chapter will also offer insight into the big data strategies of insurance companies.

Methodology: This chapter attempts to study literature reviews related to big data and examines the use of big data in the insurance industry. Also, different techniques associated with collecting big data and an assortment of big data sources are analysed in the context of the developing insurance industry.

Findings: This chapter helps us understand how big data innovations are useful for the insurance industry. The present chapter helps us in understanding the challenges faced by insurance companies. This chapter will also offer insight into the big data strategies of insurance companies.

The COVID-19 pandemic affected entire humanity, sustainable development and international trade. Even if international trade is in the recovery phase, COVID-19 pandemic's adverse effects on sustainable development and trade continue to be experienced globally. Furthermore, break out of the war in Ukraine (WIU) further affected not only Ukraine and Russia but also other countries. Countries have started to experience adverse impacts of the WIU more deeply as this war continues. From the global sustainable development and trade perspectives, the WIU impacts' magnitude is affected by the significance of Ukraine and Russia's role in and contribution to the global economy and trade (e.g. agriculture, energy). All countries, including developed, developing and under-developed countries, have started to be affected at different levels due to the adverse impacts of this war. Based on an in-depth literature review, this chapter aims to investigate the WIU's impacts on global sustainable development and international trade. Furthermore, effects of the WIU on climate change and on the fight against climate change are investigated within the scope of this chapter. This chapter is expected to be useful to all stakeholders of sustainable development including politicians and researchers.

The purpose of the chapter is to describe the concept of conflicts of socio-economic systems on the basis of the theory and methodology of the systemic approach.

The authors use the provisions of the systemic approach.

It is determined that dynamic socio-economic system is susceptible to conflicts, which, according to the Systemic approach, are bifurcation points. The features of conflict that allow defining it as a bifurcation point are its short duration, violation of sustainability of socio-economic system, uncertainty of consequences, influence on the system on the whole (cascade effect), and multiplicity of scenarios of development of socio-economic system after the conflict.

Studying conflict with the help of the theory and methodology of the systemic approach allowed determining the fact that conflict is a violation of order in a socio-economic system (which specifies definition of conflict and its essence) and could be evaluated through the measure of the system’s order (which specifies methodology of conflict evaluation). Moreover, conflict in a socio-economic system emerges not at once – it is accumulated under joint negative influences of internal and external factors. Further, the performed research allows specifying the classification of conflicts, which is offered in previous chapters – according to scenarios of development of socio-economic system after the conflict, normal (leading to normal change of system), abrupt (leading to abrupt change of the system), and attraction (all following states of the system are sustainable) conflicts are possible.

This chapter presents the development prospects of environmentally safe standards in the Russian Federation. It also addresses the imbalance between the natural, socio-economic, and scientific substantiation of green economy development.

The main idea of this chapter is based on the necessity of technological modernization, which would facilitate the reduction of environmentally unfriendly production methods, the decrease in natural resources depletion, and the increase in economy competitiveness by reducing the dependence on carbon energy.

The authors substantiate reasons and effective solutions for a green economy aimed at realization, implementation, and successful exploitation of innovation in the alternative energy production space.

Introduction: Regional economies are significantly shaped by the new developments in technology, digital transformations, as well as by the demographic processes (the ageing population and international migration), all of these being amplified by the Covid-19 pandemics and requiring tailored strategies to bridge regional welfare gaps and enhance sustainable economic development.

Aim: This research provides a review of the interplay between the regional economic welfare and digitalisation, with a keen focus on digital transformations, education, digital skills and risk management strategies in filling development gaps and enhancing regional economic growth in a sustainable development framework, with a keen focus on Romania. In this approach, the study undertakes several essential research questions and designs an advanced theoretical and empirical research to inforce the knowledge in this scientific field.

Method: The methodological framework consists of robust regression models and spatial analysis with two types of spatial models, namely spatial lag-autoregressive and spatial error. National data compiled for Romania during the 2010–2019 lapse of time were exploited.

Findings: Main results encompass that digitalisation coordinates, education and digital skills are essential for enhancing the economic development and labour market performance of various regions in Romania, with beneficial spill-overs on sustainable economic welfare and poverty reduction. These advances bring to the fore important shifts in both demand and supply sides across regional economies that affect the equilibrium and overall performance, while public discourse, regulatory authorities, policy-makers and business representatives render global the keen need to strengthen the understandings in this scientific field.

The purpose of this chapter is to assess the food security situation in Bangladesh based on 2011/2012 Bangladesh Integrated Household Survey data using two commonly measured food security indicators: Food Consumption Score (FCS) and Household Hunger Scale (HHS).

The dependent variable in the model is a categorical variable representing different scales of food security as obtained from the FCS and HHS indicators. These categorical variables are explained by annual remittances received by the households; the demographic characteristics (age, gender, literacy level, and occupation) of the household head; and total monthly income from agricultural and non-agricultural wages using ordered probit regression models.

Results indicated that remittances play an important role in improving the food security of households. Other significant variables in the model were income earned outside of the farm, male-operated household, and literacy. Increasing income from other than the agricultural sector significantly raises the probability of a household being food secure.

The Government of Bangladesh should make the agriculture sector stronger at all levels of the value chain. Additionally, providing income generation opportunities for households outside of the farm can be used as a diversification measure to achieve food security within the country.