Financial and Panel Data Econometrics

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematics and Finance".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 36939

Special Issue Editor


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Guest Editor
Faculty of Business and Law, Deakin University, Burwood, VIC 3125, Australia
Interests: financial econometrics; panel data econometrics; energy; environment; disaster; experimental economics

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the broad topic of “Financial and Panel Data Econometrics” and includes novel research on the application of financial and panel data econometrics techniques for modeling of a wide range of issues, including energy, resources, commodity and financial asset prices, returns, and volatility, and in the pricing, hedging, and risk management of all different types of assets, commodities, financial instruments, and disasters.

Theoretical and empirical articles on the application of novel financial and panel data techniques in estimation, simulation, optimization, and calibration with applications to energy, resources, commodity and asset pricing, derivative valuation, hedging, and risk/disaster management are welcome.

Contributions focusing on univariate, multivariate, spatial or high-dimensional applications in today’s complex world, novel measures of financial risk, and other types of risks implied from energy, resources, commodity, and financial derivative markets, and on the use of high-frequency data of all sorts, are encouraged. Papers related to big data and machine learning in the context of financial and panel data econometrics are highly encouraged.

Dr. Shuddhasattwa Rafiq
Guest Editor

Manuscript Submission Information

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Keywords

  • Financial econometrics
  • Panel data econometrics
  • Energy pricing, volatility
  • Commodity pricing, volatility
  • Financial instrument pricing, volatility
  • Derivative modeling
  • Panel data multivariate models
  • Special models
  • Big data analysis of asset markets
  • Machine learning to analyze resources, energy, commodity, and financial markets
  • Hedging and portfolio management
  • Financial and economic crisis
  • Disaster and climate change

Published Papers (9 papers)

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Research

7 pages, 714 KiB  
Article
Investigating the Impact of Trade Disruptions on Price Transmission in Commodity Markets: An Application of Threshold Cointegration
by Janelle Mann and Derek Brewin
J. Risk Financial Manag. 2021, 14(9), 450; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14090450 - 20 Sep 2021
Cited by 1 | Viewed by 1333
Abstract
Threshold cointegration is introduced as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact of trade disruptions on prices. The threshold cointegration technique [...] Read more.
Threshold cointegration is introduced as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact of trade disruptions on prices. The threshold cointegration technique that is employed is flexible in that it allows the number of thresholds and their location to be determined endogenously and the threshold variable to be exogenous to the system. We innovate on the threshold cointegration technique by selecting a measure of trade disruptions as the threshold variable. This innovation can be used for any commodity market that is spatially connected due to arbitrage; however, to illustrate its usefulness we apply the technique to trade disruptions for canola traded between Canada and China using weekly data between 2014 and 2019 and find that canola trade disruptions between Canada and China impacted global price transmission and resulted in market fragmentation. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
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9 pages, 225 KiB  
Communication
Is Industry Size a Carrier for Wage Inequality? A Panel Study Addressing Independent Variables of Inherently Different Sizes across Units
by Jarle Aarstad and Olav Andreas Kvitastein
J. Risk Financial Manag. 2021, 14(9), 436; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14090436 - 09 Sep 2021
Cited by 3 | Viewed by 1285
Abstract
We address how independent variables of inherently different sizes across units, e.g., small vs. large industries, in panel regression is an advantage interpretively. Analyzing a Norwegian industry panel, we find that wage inequality is a function of industry size, particularly size increase, in [...] Read more.
We address how independent variables of inherently different sizes across units, e.g., small vs. large industries, in panel regression is an advantage interpretively. Analyzing a Norwegian industry panel, we find that wage inequality is a function of industry size, particularly size increase, in an absolute number of firms. A possible reason is that specialized skilled employees negotiate higher wages when there are many legal entities. The findings can also imply that wage inequality is more sensitive to random change, particularly an increase, in large rather than small industries. We conclude that particularly large industries are positive carriers of wage inequality and discuss potential underlying causal mechanisms such as monopolistic competition. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
16 pages, 722 KiB  
Article
Time-Varying Risk and the Relation between Idiosyncratic Risk and Stock Return
by Chengbo Fu
J. Risk Financial Manag. 2021, 14(9), 432; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14090432 - 09 Sep 2021
Cited by 3 | Viewed by 2711
Abstract
This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are studied separately. We start from the historical [...] Read more.
This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are studied separately. We start from the historical trend in the magnitude of risk and then turn to the relation between idiosyncratic risk and stock returns. The result shows that both components of risk for individual stocks are changing over time. They increased from the 1960s to the 1990s/2000s and then declined until today. This paper also studies the risk-return tradeoff by investigating the relation between idiosyncratic risk and stock return in the long run. Stocks are sorted into portfolios for analysis and the whole sample period is further decomposed into decades for subgroup analysis. Multivariable regressions are used to study this relation as we control for beta, size, book-to-market ratio, momentum and liquidity. From a historical point of view, we show that the relation between idiosyncratic risk and stock return is time-varying, and it did not exist in certain decades. The results indicate that the risk-return tradeoff also varied in history. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
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9 pages, 280 KiB  
Article
FDML versus GMM for Dynamic Panel Models with Roots Near Unity
by Adrian Mehic
J. Risk Financial Manag. 2021, 14(9), 405; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14090405 - 26 Aug 2021
Cited by 2 | Viewed by 1964
Abstract
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is [...] Read more.
This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm rather than the exception in economic panels, particularly in financial management. While the CU-GMM is shown to have lower bias and higher power, it suffers from severe size distortions, which are exacerbated when the data approaches non-stationarity. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
7 pages, 242 KiB  
Article
Loan Delinquency: Some Determining Factors
by Fennee Chong
J. Risk Financial Manag. 2021, 14(7), 320; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14070320 - 12 Jul 2021
Cited by 2 | Viewed by 8036
Abstract
The main objective of this paper is to investigate the determining factors of loan delinquencies from the perspective of borrower attributes and loan characteristics. Empirical results indicated that the borrower-lender distance factor, collateral, education levels as well as availability of a monthly budget [...] Read more.
The main objective of this paper is to investigate the determining factors of loan delinquencies from the perspective of borrower attributes and loan characteristics. Empirical results indicated that the borrower-lender distance factor, collateral, education levels as well as availability of a monthly budget are having significant effects on loan delinquencies. On the other hand, level of income and gender have no significant impact on repayment behaviour. Credit is good as it allows the borrowers financial flexibility, however, debt is viewed as bad if it was not managed properly. Therefore, a correct attitude towards credit management and self-discipline can be encouraged to reduce loan default rates. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
17 pages, 405 KiB  
Article
A Reappraisal of the Prebisch-Singer Hypothesis Using Wavelets Analysis
by Hany Fahmy
J. Risk Financial Manag. 2021, 14(7), 319; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14070319 - 12 Jul 2021
Cited by 1 | Viewed by 3125
Abstract
The Prebisch-Singer (PS) hypothesis, which postulates the presence of a downward secular trend in the price of primary commodities relative to manufacturers, remains at the core of a continuing debate among international trade economists. The reason is that the results of testing the [...] Read more.
The Prebisch-Singer (PS) hypothesis, which postulates the presence of a downward secular trend in the price of primary commodities relative to manufacturers, remains at the core of a continuing debate among international trade economists. The reason is that the results of testing the PS hypothesis depend on the starting point of the technical analysis, i.e., stationarity, nonlinearity, and the existence of structural breaks. The objective of this paper is to appraise the PS hypothesis in the short- and long-run by employing a novel multiresolution wavelets decomposition to a unique data set of commodity prices. The paper also seeks to assess the impact of the terms of trade (also known as Incoterms) on the test results. The analysis reveals that the PS hypothesis is not supported in the long run for the aggregate commodity price index and for most of the individual commodity price series forming it. Furthermore, in addition to the starting point of the analysis, the results show that the PS test depends on the term of trade classification of commodity prices. These findings are of particular significance to international trade regulators and policymakers of developing economies that depend mainly on primary commodities in their exports. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
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15 pages, 324 KiB  
Article
A Panel Data Analysis of Economic Growth Determinants in 34 African Countries
by Larissa Batrancea, Malar Mozhi Rathnaswamy and Ioan Batrancea
J. Risk Financial Manag. 2021, 14(6), 260; https://doi.org/10.3390/jrfm14060260 - 09 Jun 2021
Cited by 19 | Viewed by 4808
Abstract
The research study investigated the economic determinants of economic growth in 34 countries across Africa during a two-decade period (2001–2019). For this purpose, the sample included a wide range of economies, from low income to high income and from low human development to [...] Read more.
The research study investigated the economic determinants of economic growth in 34 countries across Africa during a two-decade period (2001–2019). For this purpose, the sample included a wide range of economies, from low income to high income and from low human development to high human development, according to recent international rankings provided by the World Bank and the United Nations Development Programme. By means of a multimodal approach centered on panel data modelling, we showed that economic growth, proxied by the GDP growth rate, was substantially influenced by economic indicators such as imports, exports, gross capital formation, and gross domestic savings. We also showed that foreign direct investment inflows and outflows play an important role for capital and savings. Our empirical results offer insights on strategies that national authorities could implement to boost economic growth and development across the African continent. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
14 pages, 355 KiB  
Article
Potato Importance for Development Focusing on Prices
by Olli Salmensuu
J. Risk Financial Manag. 2021, 14(3), 137; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14030137 - 23 Mar 2021
Cited by 3 | Viewed by 4039
Abstract
This paper studies potato prices and consumption in the progress of economic development. Potato status tends to evolve from a luxury to a normal and, lastly, to an inferior good. In the developed world, where the potato thrived and became a food for [...] Read more.
This paper studies potato prices and consumption in the progress of economic development. Potato status tends to evolve from a luxury to a normal and, lastly, to an inferior good. In the developed world, where the potato thrived and became a food for the poor, prices of the inferior potato attract little interest due to general welfare, which further complicates discerning economic effects by computation. Contrarily, in many developing countries, due to supply constraints the potato is a relative expensive, non-staple, normal good, with little social significance. Whereas it is a common misconception that tastes in developing countries differ from advanced economies, low incomes, together with relatively high potato prices, present a real and obvious hindrance to wider potato use among the poor in the underdeveloped world. Local regressions on FAO data reveal empirical advantages favoring potato price system research in developing countries, more likely yielding predictable, statistically significant, unbiased results. Correct policies could increase potato importance in developing countries and stimulate sustainable and pro-poor growth where consumers receive affordable potatoes, while also producer incentives for greater productivity improve. Furthermore, potato-led research presents widening potential into also understanding general social structures of underdevelopment as similar factors explain both cross-border incomes and potato prices. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
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18 pages, 1062 KiB  
Article
Causal Links between Trade Openness and Foreign Direct Investment in Romania
by Malsha Mayoshi Rathnayaka Mudiyanselage, Gheorghe Epuran and Bianca Tescașiu
J. Risk Financial Manag. 2021, 14(3), 90; https://0-doi-org.brum.beds.ac.uk/10.3390/jrfm14030090 - 24 Feb 2021
Cited by 19 | Viewed by 7251
Abstract
In this increasingly globalized era, foreign direct investments are considered to be one of the most important sources of external financing for all countries. This paper investigates the causal relationship between trade openness and foreign direct investment (FDI) inflows in Romania during the [...] Read more.
In this increasingly globalized era, foreign direct investments are considered to be one of the most important sources of external financing for all countries. This paper investigates the causal relationship between trade openness and foreign direct investment (FDI) inflows in Romania during the period 1997–2019. Throughout this study, Trade Openness is the main independent variable, and Gross Domestic Product (GDP), Real Effective Exchange Rate (EXR), Inflation (INF), and Education (EDU) act as control variables for investigating the relationships between trade openness (TOP) and FDI inflow in Romania. The Auto Regressive Distributed Lag (ARDL) Bounds test procedure was adopted to achieve the above-mentioned objective. Trade openness has negative and statistically significant long-run and short-run relationships with FDI inflows in Romania throughout the period. Trade openness negatively affects the FDI inflow, which suggest that the higher the level of openness is, the less likely it is that FDI will be attracted in the long run. The result of the Granger causality test indicated that Romania has a unidirectional relationship between trade openness and FDI. It also showed that the direction of causality ran from FDI to trade openness. Full article
(This article belongs to the Special Issue Financial and Panel Data Econometrics)
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