scholarly journals Regional disparity of covid-19 infections: an investigation using state-level Indian data

2021 ◽  
Author(s):  
Parantap Basu ◽  
Ritwik Mazumder
Keyword(s):  
Panel Data ◽  
Urban Areas ◽  
Herd Immunity ◽  
State Level ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Health Infrastructure ◽  
The World ◽  
Dynamic Panel Regression ◽  
Indian Data

AbstractUsing the state-level panel data for India, we establish that Covid infections are clustered in more urbanized, and prosperous states. Poverty lowers cases showing evidence of herd immunity of poor which stands in sharp contrast with the developed part of the world. Our dynamic panel regression results indicate that Covid infections are persistent across states and unlocking has aggravated the infections. We also find that richer and more urbanised states with better health infrastructure and governance perform more tests. The policy lesson from this exercise is that the authorities should monitor immunization and Covid protocols in densely populated urban areas.

scholarly journals Intellectual capital in Indonesia: dynamic panel approach

2019 ◽  
Vol 13 (2) ◽  
pp. 240-262 ◽  
Author(s):  
Tessa Soetanto ◽  
Pei Fun Liem
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Intellectual Capital ◽  
Significant Relationship ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Content Type ◽  
Low Level ◽  
Dynamic Panel Regression ◽  
High Level

Purpose Intellectual capital (IC) has been considered as a valuable asset in the wealth creation and sustainability of the company; however, limited and mixed results are found on its impact on firm financial performance and market value (MV). This paper aims to investigate the influence of IC toward MV and financial performance of publicly listed firms in Indonesia. In addition, this research also presents the comparison of the high and low level of knowledge industries regarding IC performance. Design/methodology/approach A balanced panel data of 127 firms from 12 industries in Indonesia during 2010 until 2017 was evaluated using dynamic panel regression and administering a well-developed Blundell–Bond instrument (dynamic panel data estimator) to account for endogeneity problem. Findings The results of this study showed that IC had a significant and positive impact on firm performance. Specifically, structural capital efficiency and capital employed (CE) efficiency have been contributed to the value creation of the company, after controlling for firm size and type of industry. Different to the theoretical expectation, this research found no significant relationship between IC and MV of the firm. However, when the sample was clustered into high-level and low-level knowledge industry, CE displayed positive and significant relationship in high-level industry. Originality/value This research contributes to IC research by having a larger sample of Indonesian firms from all industries except banks and financial institutions and using Modified Value Added Intellectual Capital measurement model. To address the endogeneity problem, dynamic panel regression using system generalized method of moment was applied.

scholarly journals Tourism and Economic Growth in Mediterranean Region: Dynamic Panel Data Approach

2016 ◽  
Vol 2 (1) ◽  
pp. 65-84 ◽  
Author(s):  
Blanka Šimundić ◽  
Zvonimir Kuliš
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Mediterranean Region ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
The World ◽  
Global Tourism ◽  
The Mediterranean ◽  
Tourism Arrivals ◽  
Growth Hypothesis

AbstractThe Mediterranean region is one of the leading tourism regions in the world accounting for one third of global tourism receipts and half of global tourism arrivals. This paper aims at providing evidence that tourism can be considered as determinant of economic growth in the Mediterranean region. The results support the postulates of tourism led growth hypothesis, thus giving to the policymakers endorses for improving the tourism competitiveness conditions that will boost the economic growth.

scholarly journals Macroeconomic, Institutional and Bank-Specific Determinants of Non-Performing Loans in Emerging Market Economies: A Dynamic Panel Regression Analysis

2019 ◽  
Vol 8 (3) ◽  
pp. 95-110
Author(s):  
Yilmaz Bayar
Keyword(s):  
Regression Analysis ◽  
Banking Sector ◽  
Emerging Market ◽  
Dynamic Panel Data ◽  
Emerging Market Economies ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Market Economies ◽  
Nonperforming Loans ◽  
Dynamic Panel Regression

Abstract Banking sector is important for various macroeconomic and microeconomic variables in terms of mobilization of funds, increasing savings, and providing alternative investment instruments suited to the every person by minimizing the risk of adverse selection and moral hazard, allocating funds to most productive projects, risk diversification. Therefore, sound functioning of the banking sector is critical especially for emerging and developing countries. This study explores the macroeconomic, institutional, and bank-specific factors behind nonperforming banking loans as an indicator of banking sector functioning in emerging market economies over the 2000-2013 period by employing the system GMM dynamic panel data estimator. Results of the dynamic panel regression analysis showed that economic growth, inflation, economic freedom (institutional development), return on assets and equity, regulatory capital to risk-weighted assets, and noninterest income to total income affected nonperforming loans negatively, while unemployment, public debt, credit growth, lagged values of nonperforming loans, cost to income ratio and financial crises affected nonperforming loans positively.

scholarly journals Legal Instruments for Stimulating Interregional Competition for Investment

2020 ◽  
Vol 16 (2) ◽  
pp. 649-665
Author(s):  
V.F. Lapo
Keyword(s):  
Economic Integration ◽  
Driving Force ◽  
Spatial Competition ◽  
Federal District ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Investment Promotion ◽  
Positive Effects ◽  
Economic Interaction ◽  
Dynamic Panel Regression

In order to study the role of legal instruments in stimulating the spatial competition and economic integration of the entities of the Russian Federation, it is necessary to examine a system of interacting regions. Regional laws on investment promotion have been acting and improving for a long time. Thus, the paper examines the set of these laws and their impact on interregional integration and regional competition. The study identifies three levels of competition: the all-Russian competition, competition within federal districts, and competition between neighbouring regions. As benefits as instruments for attracting investments are applied in regions, they influence the decision to invest in other regions. Therefore , the developed econometric mode l of dynamic panel regression of investments assesses the economic interaction between the regions. The model “the dynamic panel regression of investments taking into account the competition between the regions” (DPRI-CR) includes stimulation instruments and spatially weighted variables related to regional benefits. The indicators for assessing regional spatial interaction are based on the coefficients of the similarity of the legal systems in two regions. Testing of the DPRI-CR demonstrates the exiting external positive, negative and neutral effects of investment benefits that significantly differ depending on the level of competition. An increase in the regional economic integration causes an increase in the positive and negative effects. Consequently, the investment policies that are aimed at increasing economic interaction should take into account the region’s economic integration with the economies of the neighbouring regions, regions of the federal district and other entities of the country. The regions, which are closely integrated with the majority of regions, have the most opportunities to use the external effects. They can apply either “driving force of the economy” instruments to enhance positive effects or “driving force of the progress” instruments to increase their competitive position.

Explaining stock market returns in Sub-Saharan Africa using an alternate uncovered interest rate parity framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kofi Bondzie Afful ◽  
William Opoku
Keyword(s):  
Money Supply ◽  
Random Effects ◽  
Stock Markets ◽  
Critical Examination ◽  
Panel Regression ◽  
Market Returns ◽  
Dynamic Panel ◽  
Content Type ◽  
Dynamic Panel Regression ◽  
Sub Saharan

PurposeSub-Saharan African (SSA) stock exchanges are imperfect and inefficient. Therefore, orthodox finance theories are unable to completely explain their market returns. Such models mainly identify anomalies when applied to the sub-region. Consequently, this paper develops an original theoretical model to better explain market returns on the sub-continent.Design/methodology/approachThis paper develops an alternate analytical framework that combines adaptive expectations, Keynesian LM model and modified uncovered interest parity (UIP) formulations to address empirical anomalies identified by previous literature when analyzing SSA's inefficient stock markets. Using panel data, the study first computes the fixed as well as random effects regressions and, later, a Generalized Method of Moments (GMM) dynamic panel regression for further empirical analysis.FindingsBoth the fixed and random effects regression results indicate that the relative output-money supply disparity and foreign inflation-money supply growth rate spread have positive effects on market returns in SSA. On the other hand, foreign interest rates have an inverse effect. Although the GMM dynamic panel regression has similar results, it additionally finds that market returns in SSA are autoregressive. This suggests that past returns are persistent.Research limitations/implicationsA key implication is that multipliers and transmission mechanisms in SSA may take longer to adjust, thereby limiting short-run market returns. Also, policymakers must encourage a critical mass of firms to list in order to enhance efficiency. Additionally, policy variables significantly influence returns. One limitation is the high market segmentation in SSA. This heightens heterogeneity, emphasizing fixed effects.Practical implicationsAlso, the findings of this study may not apply to all emerging economies as SSA economies are highly heterogeneous.Social implicationsThe segmented nature of SSA stock markets may have implications for income inequality and the distribution of resources within the economy. Also, it indicates that there are limits to how firms use capital markets on the sub-continent.Originality/valueThis paper abstracts from the strict ideal market conditions prescribed by modern finance theories and develops an original modified UIP model. It finds that SSA stock markets may be more sensitive to policy variables, instead of determinants postulated by orthodox finance concepts. The study offers opportunities for further critical examination of returns in imperfect frontier markets.

scholarly journals Dynamic Panel Modeling of Climate Change

Econometrics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 30
Author(s):  
Peter C. B. Phillips
Keyword(s):  
Estimation Method ◽  
Practical Implementation ◽  
Model Parameters ◽  
Panel Regression ◽  
Climate Data ◽  
Dynamic Panel ◽  
Panel Regressions ◽  
Regression Parameters ◽  
Dynamic Panel Regression ◽  
Temperature Radiation

We discuss some conceptual and practical issues that arise from the presence of global energy balance effects on station level adjustment mechanisms in dynamic panel regressions with climate data. The paper provides asymptotic analyses, observational data computations, and Monte Carlo simulations to assess the use of various estimation methodologies, including standard dynamic panel regression and cointegration techniques that have been used in earlier research. The findings reveal massive bias in system GMM estimation of the dynamic panel regression parameters, which arise from fixed effect heterogeneity across individual station level observations. Difference GMM and Within Group (WG) estimation have little bias and WG estimation is recommended for practical implementation of dynamic panel regression with highly disaggregated climate data. Intriguingly, from an econometric perspective and importantly for global policy analysis, it is shown that in this model despite the substantial differences between the estimates of the regression model parameters, estimates of global transient climate sensitivity (of temperature to a doubling of atmospheric CO2) are robust to the estimation method employed and to the specific nature of the trending mechanism in global temperature, radiation, and CO2.

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