Search results

Digital financial inclusion is a need of the recent era in order to flourish the growth of economies as well as businesses and individuals. Thus, varieties of digital technologies are launched to provide ease and leverage to customers’ financial needs. Among the well-known digital technologies, Fintech emerged as a well-known and accepted form of digital technologies. However, the acceptance level is much lower, especially in developing sides of the world like Pakistan where issues related to cyber-security are the major hindrance in the way of digitization and n-tier online payments. However, with a massive youth population, Pakistan also has the opportunity to use Fintech as the major tool for economic and social development. Therefore, this chapter has been written purposely to shed light on the importance, use, and role of Fintech in the growth of developing countries like Pakistan. The purpose is to increase the knowledge of youth about financial technologies especially Fintech so they may embrace their abilities with technological innovation, especially for their financial needs. On the other side, the chapter will also address the lack of research on this emerging trend to diverge the focus of researchers and academicians towards Fintech and its uses, scope, implications, and benefits for developing countries.

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.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

The transformation towards the Green Economy (GE) in Poland is a relatively new topic for researchers, policymakers and business practitioners. A comprehensive picture of the shift towards the GE can help mentioned groups translate theoretical assumptions into practice.

This chapter presents the assessment of Poland's shift towards the GE, measured by the proposed Green Transformation Index (GTI).

The set of GE indicators was elaborated in Structured Literature Review (SLR) variation method. Then, this set of indicators was compared with the Statistics Poland (GUS) secondary data and employed in the taxonometric calculation methods.

In the result, the GTI for the Polish economy was proposed and calculated between 2007 and 2020. The GTI allowed us to present a dynamic analysis of the transformation towards GE in Poland.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

Purpose: FinTech is exploding all over the world. FinTech companies play a critical role in growing the banking industry. This chapter reviews existing literature on FinTech in banking, particularly its publication trend, journal productivity and impact, affiliated organisations and related themes.

Need for the Study: FinTech is reshaping the banking sector as banks move towards digitisation. FinTech has eliminated the need for paper, reduced the requirement for physical presence, and destroyed the necessity for cash. Several researchers have studied the features and benefits of FinTech technologies in the banking field. So, there is a need to analyse the available literature to identify the scope of further research in this field.

Methodology: For a comprehensive review, Bibliometric and content analysis of 77 open access green articles collected through the structured database of ‘Dimensions’ is done. These articles are published in the UGC Journal List Group II.

Findings: It is revealed that the execution of FinTech is continuously increasing in the banking sector, which has resulted in automation in various banking activities. The study revolves around technology and Banking, Financial Inclusion and Growth, and the Impact of the Financial Crisis on Banking and Peer-to-Peer (P2P) lending.

Practical Implications: The conclusions of this study can help academia and industry improve their understanding of FinTech in Banking, specifically its publication trend, geographical distribution, and creation of coherent themes. Careful analysis of collected articles will help to explore the scope of further research.

The seasonality in the behavior of travelers is something that goes back to the origin of the trips themselves. This seasonality is due to multiple factors, some easy to counteract and others difficult to solve. But, regardless of the causes, it is a phenomenon that generates significant negative impacts on society and the environment in which the phenomenon of tourist seasonality occurs. All tourist destinations have seasonality, but in some cases, it is very high and in others it has a minimal incidence. The objective of this chapter is to ponder the impacts and consequences of seasonality in regions with a strong tourism development, allowing to put into context the aspects of society impacted by this phenomenon and the positive implications that the reduction of seasonality would have. For this, an analysis of a theoretical model with two regions in opposite situations is carried out, raising the possible effects of a high seasonality. The cases of the Balearic Islands and the Canary Islands are also reviewed, as real examples of the regional typologies taken into consideration in the theoretical model. This seeks to ponder the problems attributable to seasonality. As a final reflection, the enormous typology of negative impacts generated and the need to continue analyzing the seasonality and its impacts are emphasized.