Jan' 20
The IUP Journal of Applied Economics
Focus
the authors, Sakshi Malik and
Cheshta Kapuria, have analyzed empirically the impact of globalization and other macroeconomic variables on the quality of a country's governance using panel Ordinary Least Squares (fixed effects and random effects) and two-step system Generalized Method of Moments (GMM) on a panel dataset of 14 emerging Asian countries for the period 2005-2017. The results of the study indicate that social and political globalization, urbanization, and information and communication technology infrastructure influence governance favorably, while per capita growth and government consumption have no significant impact on the country's level of governance. The study also finds that social globalization coupled with economic globalization can lead to an improved level of governance. The study highlights that the improved quality of governance can be attained by blending cultural integration with capital flows.
In the second paper, "An Analysis of Political Transfers from the Center to the States in India", the authors, J S Darshini and K Gayithri, have examined the level and changing trends in the process of states' dependency on central transfers and also the economic and political factors influencing the flow of conditional or discretionary transfers to the 14 major Indian states using static panel model for the period 1981-82 to 2014-15. The study reveals that the successive Finance Commissions have gradually enhanced the share of states in the centralized divisible pool over a period of time. The study also reveals the overall empirical outcome that states with a larger fiscal space and Gross State Domestic Product (GSDP) growth were able to get more funds relative to the political factors during the first and third sub-periods. The study highlights that both the economic and political factors together influence the flow of discretionary transfers among states in India.
In the third paper, "On the Informational Efficiency of the Cryptocurrency Market", the authors, Anoop S Kumar, Thota Nagaraju and Taufeeq Ajaz, have analyzed the weak form informational efficiency in the cryptocurrency markets using Cryptocurrency Market Index (CRIX) data. The statistical tests used in this study indicate evidence in support of weak form efficiency. The results of the proposed Adaptability Index (AI) reveal that cryptocurrency markets are adaptive in nature. The study also reveals that cryptocurrency markets exhibit fractal structure.
In the last paper, "Passenger Demand Forecasting in the Ridesharing Context: A Comparison of Statistical and Deep Learning Approaches", the author, Sanjay Fuloria, has forecasted the passenger demand in the ridesharing services in the short run, using exponential smoothing, multiple regression, and a neural network-based algorithm Long Short-Term Memory (LSTM). The study finds that LSTM models perform better in forecasting both for training and validation datasets. The study also reveals that multiple regression performs better than exponential smoothing in training set. In fact, multiple regression method is on a par with LSTM. The study highlights that overall LSTM performs better than the other two methods and could be used for demand forecasting for cabs in the platform economy.
Consulting Editor
| Article | Price (₹) | ||
| The Globalization and Governance Nexus - Evidence from Emerging Asia |
100
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| An Analysis of Political Transfers from the Center to the States in India |
100
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| On the Informational Efficiency of the Cryptocurrency Market |
100
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| Passenger Demand Forecasting in the Ridesharing Context: A Comparison of Statistical and Deep Learning Approaches |
100
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The Globalization and Governance Nexus - Evidence from Emerging Asia
In view of the growing importance of good governance as an accelerator of sustainable development, it becomes indispensable to study its determinants. The present paper empirically analyzes the impact of globalization and other macroeconomic variables on the quality of a country's governance. For this purpose, the paper has applied panel Ordinary Least Squares (fixed effects and random effects) and two-step system Generalized Method of Moments (GMM) on a panel dataset of 14 emerging Asian countries, namely, Bangladesh, Bhutan, Cambodia, India, Indonesia, Lao PDR, Mongolia, Myanmar, Pakistan, Philippines, Sri Lanka, Timor-Leste, Uzbekistan, and Vietnam. The econometric analysis is conducted for the period 2005-2017. In general, the results indicate that social and political globalization, urbanization, and information and communication technology infrastructure influence governance favorably, while per capita growth and government consumption have no significant impact on the country's level of governance. A pertinent finding of the paper is that social globalization coupled with economic globalization can lead to an improved level of governance. Thus, improved quality of governance can be attained by blending cultural integration with capital flows. A key contribution of the paper is that it analyzes the impact of various aspects of globalization-economic, political and social-on the level of governance in emerging Asian countries.
An Analysis of Political Transfers from the Center to the States in India
India is a federal country with asymmetric levels of development. The asymmetries are both vertical and horizontal in nature. This paper proceeds in two stages-in the first stage, it decomposes the level and pattern of fiscal dependency of states on the different components of total transfers. In the second stage, it examines the factors that influence the allocation of conditional/discretionary central transfers to the states. The study finds that successive Finance Commissions have gradually enhanced the share of states in the centralized divisible pool over a period of time. It is evident from the overall empirical outcome that states with a larger fiscal space and Gross State Domestic Product (GSDP) growth were able to get more funds as compared to the prevailing political factors during the first and third sub-periods. In all the three sub-periods, interactive dummies have played a significant role in determining the allocation of federal funds to the states.
On the Informational Efficiency of the Cryptocurrency Market
Using daily returns of the cryptocurrency market index (CRIX), the present study tests for weak form efficiency in the cryptocurrency market using a battery of methods. First, weak form efficiency is checked using three statistical tests. The test results provide overall evidence in support of weak form efficiency. Next, the possibility of the adaptive nature of cryptocurrency markets is tested using the proposed Adaptability Index (AI). The results show that cryptocurrency markets are adaptive in nature. Further, the fractal structure of the cryptocurrency market is established using wavelet power spectrum method.
Passenger Demand Forecasting in the Ridesharing Context: A Comparison of Statistical and Deep Learning Approaches
Forecasting of passenger demand in the short term could be beneficial to the on-demand ride services platforms. This would help the platforms to incentivize drivers by moving them from areas of low demand to high demand. This, in turn, would help the platform companies to maximize their profits too. Using Uber dataset for New York City, the present study compares three different methods-exponential smoothing, multiple regression and Long Short-Term Memory (LSTM)-to forecast passenger demand in the short term. While traditional statistical methods like exponential smoothing and multiple regression are more explainable, deep learning methods like LSTM, with their complex methodologies, are more accurate in some situations. Additionally, temperature dataset for the city of New York is also used for forecasting. The study concludes that LSTM models perform better in forecasting both for training and validation datasets. The research could be further enhanced by using a bigger and geographically diverse dataset.